Genetics and Breedingin Aquaculture

Proceedings of the 44th
U.S.–Japan Aquaculture
Panel Symposium
NOAA Northwest Fisheries Science Center
2725 Montlake Boulevard East
Seattle, WA
November 1, 2016

U.S. DEPARTMENT OF COMMERCE
National Oceanic and Atmospheric Administration
National Marine Fisheries Service
NOAA Technical Memorandum NMFS-F/SPO-175

Genetics and Breeding in Aquaculture

Proceedings of the 44th U.S.–Japan
Aquaculture Panel Symposium
NOAA Northwest Fisheries Science Center
2725 Montlake Boulevard East
Seattle, WA
November 1, 2016
Kristen Gruenthal1, Clete Otoshi2, Paul Olin3, and Mike Rust2 (editors)
1

Contractor with Earth Resources Technology, Inc.
NOAA National Marine Fisheries Service
Office of Aquaculture1315 East–West Highway
Silver Spring, MD 20910

2

NOAA National Marine Fisheries Service
Office of Aquaculture1315 East–West Highway
Silver Spring, MD 20910

3

California Sea Grant
UCSD Scripps Institution of Oceanography
133 Aviation Boulevard, Suite 109
Santa Rosa, CA 95403
NOAA Technical Memorandum NMFS-F/SPO-175
November 2017

U.S. Department of Commerce
Wilbur Ross, Secretary of Commerce
National Oceanic and Atmospheric Administration
RDML Timothy Gallaudet, Acting NOAA Administrator
National Marine Fisheries Service
Chris Oliver, Assistant Administrator for Fisheries

SUGGESTED CITATION:
Kristen Gruenthal, Clete Otoshi, Paul Olin, and Mike Rust (editors). 2017.
Genetics and Breeding in Aquaculture: Proceedings of the 44th U.S.–
Japan Aquaculture Panel Symposium, Seattle, WA, November 1, 2016.
U.S. Dept. Commerce, NOAA Tech.Memo. NMFS-F/SPO-175, 78 p.
A COPY OF THIS REPORT MAY BE OBTAINED FROM:
Northwest Fisheries Science Center
2725 Montlake Boulevard East
Seattle, WA 98112
OR ONLINE AT:
http://spo.nmfs.noaa.gov/tech-memos
Reference throughout this document to trade names does not imply
endorsement by the National Marine Fisheries Service, NOAA.
Cover photo of juvenile California yellowtail, Seriola dorsalis, swimming in a
research tank at Hubbs–SeaWorld Research Institute in San Diego, California.
Photo credit: Mark Drawbridge, Hubbs–SeaWorld Research Institute.

Table of Contents
Introduction
Michael B. Rust

1

Integrated Multi-Trophic Aquaculture (IMTA) as aCountermeasure for Coastal Oligotrophication in Japan

Satoshi Watanabe, Natsuki Hasegawa, Yuka Ishihi, Toshinori Takashi, Tomomi Mizuno,
and Junya Higano

2Interactions Between Shellfish Aquaculture and the Environment
in the Northeastern U.S.
8
Matthew Poach, Bob Alix, Paul Clark, April Croxton, Mark Dixon, Cathy Kuropat,
Judy Li, Renee Mercaldo-Allen, Shannon Meseck, Lisa Milke, Dylan Redman, Julie Rose,
Barry Smith, and Gary Wikfors

Land-based Aquaculture of Red-Spotted Grouper (Epinephelus
akaara) Using the Closed Recirculation System

10

Using Physiological Tools to Assess and Optimize Aquacultureof California Yellowtail, Seriola dorsalis

14

Paradigm Shift in Fish Breeding: Marker-Assisted Selection to
Genomic Selection

20

Genomic Analyses to Inform Sablefish Aquaculture Research

25

Masatsugu Takano, Tetsuo Morita, and Yoshihisa Yamamoto

Nicholas C. Wegner, Laura Schwebel, and John R. Hyde

Akiyuki Ozaki, Kazuo Araki, Jun-ya Aoki, Yukinori Shimada, Hiroyuki Okamoto,
Hironori Usuki, Koichi Okuzawa, Kazunori Yoshida, and Tsutomu Noda
Krista M. Nichols, Andrew Jasonowicz, Giles Goetz, J. Adam Luckenbach, andFrederick W. Goetz

Mutagenesis and Genome Editing for Aquaculture Fish Species:
Modification of SCPP Genes in Tiger Pufferfish (Takifugu rubripes) 26
Hiroyuki Okamoto, Takashi Ishikawa, Wataru Kai, Issei Nishiki, Yuki Iwasaki,
Kenta Kishimoto, Yu Murakami, Masato Kinoshita, and Atushi Fujiwara

Genome-enabled Selection Doubles the Accuracy of Predicted
Breeding Values for Bacterial Cold Water Disease ResistanceCompared to Traditional Family-based Selection in Rainbow
Trout Aquaculture

33

Atlantic Salmon and Eastern Oyster Breeding Programs at the
National Cold Water Marine Aquaculture Center

44

Roger L. Vallejo, Timothy D. Leeds, Guangtu Gao, James E. Parsons, Kyle E. Martin,
Jason P. Evenhuis, Breno O. Fragomeni, Gregory D. Wiens, and Yniv Palti

Gary S. Burr, Michael R. Pietrak, Brian C. Peterson, Dina A. Proestou, andWilliam R. Woltersiii

The Molluscan Breeding Program: 20 Years of Selective
Breeding of the Pacific Oyster, Crassostrea gigas, on theWest Coast of the U.S.

50

Seriola Genomics and the Knowledge Repository serioladb.org

52

Uses of Genetic Parentage Analysis in Cultured California
Yellowtail (Seriola dorsalis)

58

Past, Present, and Future Research on Ostreid Herpesvirus 1
Infections of the Pacific Oyster in Tomales Bay, California

63Type 1 Ostreid Herpesvirus (OsHV-1) Variants in Japan

64

Epigenetic Considerations in Aquaculture

68

Romain Morvezen, Claudio de Melo, Blaine Schoolfield, Evan Durland, Brett Dumbauld,and Chris Langdon
Andrew Severin, Catherine Purcell, Mark Drawbridge, Rick Masonbrink,
Arun Seetharam, Akiyuki Ozaki, Kazuo Araki, Hironori Usuki, Koichi Okuzawa,
Mituru Ototake, Fuminari Ito, and John Hyde

Matthew Craig, Catherine Purcell, Kevin Stuart, Mark Drawbridge, and John Hyde

Colleen A. Burge and Carolyn S. Friedman

Yoshiko Shimahara, Satoshi Watanabe, Jun Kurita, Ikunari Kiryu, Toyohiro Nishioka,
Kei Yuasa, Morihiko Kawana, Takashi Kamaishi, and Norihisa Oseko
Mackenzie Gavery and Steven Robertsiv

Introduction
Genetic improvement has contributed significantly to advances in aquaculture
production. Traditional selective breeding has a long history of improving
production traits in livestock and is having progressively greater impacts inaquaculture. However, a new alphabet soup of technologies—QTLs, MAS,
CRISPR, TALENs, gBLUP, and Big Data!—that can be used to improve production
efficiency, product quality, and fish health will significantly accelerate this process.
In health management, for example, genetic tools used to improve disease
resistance and immune response, better understand pathogens, and develop
vaccines have strengthened the aquaculture industry. In terms of sustainability,
understanding genetic interactions between wild and cultured stocks and genetic
and epigenetic resilience to environmental change are also research priorities
shared by the Fisheries Research and Education Agency (FREA) of Japan, theNational Oceanic and Atmospheric Administration (NOAA), and the U.S.
Department of Agriculture. Opportunities created by this science will be ofeven greater importance in the future. This Proceedings concludes three UJNR
Symposia focused on these interrelated topics. Proceedings from the previous
two Symposia were published by NOAA (42nd UJNR Proceedings) and FREA
(43rd UJNR Proceedings). Some common themes include genetic, genomic,
and transcriptomic resource development; improvement through selective
breeding using genetic, genomic, pedigree, and phenotypic data; chromosome
set manipulation such as triploid induction; emerging technologies like genome
editing and epigenetics; and assessing competitive, genetic, and fitness impacts
on wild populations using empirical data and modeling. Finally, these meetings
have facilitated the exchange of scientists toward developing competitive new andenhancing existing aquaculture industries on both sides of the Pacific. We hope
this Proceedings and the previous two will serve as a good launching point for
those wanting more information on these exciting topics.

Michael B. Rust
NOAA Fisheries Office of Aquaculture
United States Panel Chair

1Integrated Multi-Trophic Aquaculture (IMTA) as a Countermeasure for
Coastal Oligotrophication in Japan
Satoshi Watanabe1*, Natsuki Hasegawa1, Yuka Ishihi1, Toshinori Takashi2, Tomomi Mizuno3, and Junya Higano4
National Research Institute of Aquaculture, Japan Fisheries Research and Education Agency, 422-1
Nakatsuhamaura, Minamiise, Mie, 516-0193, Japan
2
Seikai National Fisheries Research Institute, Japan Fisheries Research and Education Agency, 1551-8 Taira,Nagasaki, Nagasaki, 851-2213, Japan3
Department of Agriculture, Forestry and Fisheries, Mie Prefectural Government, 13 Komei, Tsu, Mie 514-8570,
Japan
4
National Research Institute of Fisheries and Environment of Inland Sea, Japan Fisheries Research and
Education Agency, 2-17-5 Maruishi, Hatsukaichi, Hiroshima 739-0452, Japan
1

Corresponding author: swat@affrc.go.jp
Keywords: IMTA, eutrophication, oligotrophication, feed conversion ratio

ABSTRACT

Along with reinforcement of economic stability, oneof the important goals of IMTA is to mitigate effluent
load from finfish culture for environmental integrity.
In contrast, we are trying to develop techniques touse IMTA to compensate for the reduced aquaculture
productivity of bivalves and seaweeds associated withthe coastal oligotrophication. The amount of NH4+-N
excretion from the red seabream aquaculture in
Hasamaura Cove, Mie Prefecture was estimated to be
9.2 t/year. The amount of nitrogen extracted by green
alga, Monostroma nitidum (Japanese common nameis Hitoegusa) aquaculture in the cove was estimatedto be 2.9% of the red seabream NH4+-N excretion. M.
nitidum was found to have a nitrogen content twice ashigh in Hasamaura Cove than those cultured in nearby
bays without finfish aquaculture. The red seabream
NH4+-N excretion is equivalent to the amount of
nitrogen in 2071 t/year (wet weight) of the Manila clamsuspended culture production. Thus, IMTA has a big
potential to enhance aquaculture production by using
what would otherwise be fish waste.

Intensification of aquaculture production has caused
environmental deterioration associated with waterand sediment eutrophication, resulting in sporadic
mass fish kills in some parts of the world. In contrast,
eutrophication has been reduced in coastal watersof Japan because of diminished production andimproved feeding efficiency of finfish aquaculture
and/or mitigation efforts that regulate the allowableamount of terrestrial nitrogen/phosphorus discharge
to the sea. Red seabream, Pagrus major, aquaculture
production, for instance, peaked in the early 1990s andhas been in a decreasing trend since 2000 in Japan. The
levels of surface dissolved inorganic nitrogen (DIN)
have gradually decreased, while phosphorus levels
have been rather constant in Ise Bay since the 1990s,
possibly causing a nutrient imbalance for primary
production. Surface chlorophyll a levels have been ina decreasing trend since the 1990s, and the occurrence
frequency of harmful algal bloom has decreased
by 90% since 1979 in Ise Bay. The oligotrophication(relative to the past) of coastal waters is considered tohave brought about a decline in carrying capacity of
the coastal environment, causing in part a continuous
decrease in some coastal fishery resources and reduced
productivity in molluscan and algal aquaculture. The
national production of the Manila clam, Ruditapes
philippinarum, for example, has continuously declined
for thirty years, falling below 10% of the peak value
marked in the mid-1980s. In Ariake Bay, DIN
deficiency causes bleaching of cultured nori, Pyropia
yezoensis, severely reducing the market value especiallytowards the end of the culture season in early spring.
Integrated multi-trophic aquaculture (IMTA) is
an aquaculture approach that combines culture of
economically important species from different trophic
levels, typically finfish, organic extractive species (e.g.
bivalve) and inorganic extractive species (e.g. seaweed).

INTRODUCTION
Intensification of aquaculture production has caused
environmental deterioration associated with waterand sediment eutrophication and consequent harmful
algal bloom, hypoxia and sulfide production, resulting
in sporadic mass fish kills in some parts of the world.
Eutrophication is harmful for not only the cultured
fish but also surrounding environments. In contrast,
eutrophication has been reduced in coastal waters ofJapan because of diminished production and improved
feeding management of finfish aquaculture and/or enforcement of the Total Pollutant Load Control
System, issued by the Ministry of the Environment
in 1979, which regulates the allowable amount ofterrestrial nitrogen/phosphorus discharge to the sea.
The oligotrophication (relative to the past) of coastal
2

bays, Mie Prefecture. Nitrogen content of M. nitidum
was analyzed by an elemental analyzer, Flash EA112(ThermoFisher Scientific).

waters is considered to have brought about a decline incarrying capacity of the coastal environment, causing
in part a continuous decrease in some coastal fisheryresources and reduced productivity in molluscan andalgal aquaculture. Benthic fish fisheries production in
Seto Inland Sea, for instance, has decreased markedly,
and the fishery production of the benthic fish was
found to be negatively correlated with the dissolved
inorganic nitrogen (DIN) level in the coastal water(Handa and Harada, 2012).

RESULTS AND DISCUSSION
The Total Pollutant Load Control System (TPLCS) has
been implemented to mitigate the eutrophication of
the closed sea areas in Japan (i.e. Tokyo Bay, Ise Bay
and Seto Inland Sea) since 1979. Allowable amountsof terrestrial nutrient discharge to the sea areas are
set every five years, and for instance the target values
for N and P discharge to Ise Bay during the seventhterm (i.e. 2011 to 2016) were 115 t/day and 8.7 t/day,
respectively. Eutrophication caused by aquaculture
effluent has been regulated by Sustainable Aquaculture
Production Assurance Act (APAA) issued by the
Fisheries Agency since 1999. With the assistance of theprefectural extension workers, fisheries cooperative
associations as a group or individual farmers having ademarcated fishery right submit an Aquaculture Area
Improvement Plan, which prescribes (i) the waterarea concerned and the species of the farmed aquatic
animals and plants, (ii) improvement goal of theaquaculture area, (iii) measures to be taken to improve
the aquaculture area and their implementation
time, and (iv) establishment of the facilities andorganizational system necessary to improve theaquaculture area, to the respective government officeevery five years. Typically, appropriate maximum
culturing density is set to be less than 95% of thetrimmed mean excluding the largest and the smallest
values of the density from the previous five-year
term. The farmers may receive subsidy for pension
plans to compensate for the income loss incurred by
the reduced aquaculture production. The reduced
production also intends to prevent oversupply andsubsequent price drop of the products. This may be
one of the causes of Japan’s decreasing aquaculture
production, along with competition with cheaper
labour in developing countries despite the continuous
and rapid global expansion of aquaculture production.

In this paper, the trends in environmental factors in Ise
Bay and southern coast of Mie Prefecture, Japan, will
be introduced based on the statistical data provided
by the prefectural and national government. The
relationship between the environmental factors andfisheries production will be discussed. Finally, ourattempt to use integrated multi-trophic aquaculture(IMTA) to enhance unfed aquaculture production inrecent oligotrophic environments will be introduced.

MATERIALS AND METHODS
Statistical data for environmental parameters in Ise
Bay, central Japan, were obtained from the report ofSenkai Teisen Chosa (shallow sea fixed line survey), amonthly monitoring survey conducted at 16 stations
by Mie Prefecture Fisheries Research Institute (Mie
Prefecture Fisheries Research Institute, 1972-2016). The
monthly data for dissolved inorganic nitrogen (DIN,
i.e. the sum of NH4+, NO2-, NO3-), PO4-P, chlorophylla and sea surface temperature were smoothed by
13-month moving average operation. Where the datacollections were not complete in some stations, missing
data were ignored, and the grand mean of all stations
were obtained to analyze the change in trend.
Aquaculture production data were obtained from the
Ministry of Agriculture, Forestry and Fisheries web
site, Kaimen Gyogyou Seisan Toukei Chosa (marine
fisheries production statistics survey): http://www.
maff.go.jp/j/tokei/kouhyou/kaimen_gyosei/index.html.

Because of the mitigation efforts, water quality has
been gradually improving along the coast of Japan.
In Ise Bay, the DIN level has a long term decreasing
trend with big fluctuations over the past thirty years(Fig. 1). For example, the annual mean DIN level was
11.2 mM and 4.6 mM in 1985 and 2015, respectively(i.e. 58.9% reduction in 30 years). Phosphate level,on the other hand, did not decrease between 1985
(0.59 mM) and 2003 (0.63 mM) and had a decreasing
trend with large fluctuations between 2004 (0.79mM) and 2015 (0.27 mM) (Fig. 2). The difference
observed in nitrogen and phosphate levels between
1985 to 2004 might be attributable to the introductionof phosphate-free detergents and establishment of
coagulation sedimentation method in the late 1970s,
which had already reduced the phosphate level before

Ammonium (NH4+) excretion rate (TAN) of red
seabream (Pagrus major) is reported by Takashi et al.
(2017) as follows: TAN (mg-N/day) = 0.013exp0.07TW1.01,
where T is water temperature (°C) and W is fish weight(g). This formula was used to estimate annual NH4+
excretion by red seabream aquaculture in Hasamaura
Cove, Mie Prefecture. Information on the red seabream
production in the area was obtained from Mie Prefectural
Government statistics, details of which will not be
disclosed in this paper. For feed conversion ratio (FCR)
of red seabream aquaculture, the common value of 2.5
was used for calculations.
Green alga, Monostroma nitidum (Japanese common
name is Hitoegusa) specimens were collected fromaquaculture sites in Hasamaura Cove and adjacent3

Figure 1. Surface water dissolved inorganic nitrogen (DIN)
level in Ise Bay. DIN is the sum of ammonium, nitrate andnitrite.

Figure 2. Surface water phosphate level in Ise Bay.

1985 (Washio 2015). The denitrification method fornitrogen removal, on the other hand, did not become
widely used until 1990s, resulting in nitrogen oversupply relative to phosphate (i.e. N-P imbalance)
during this period. The ratio of nitrogen andphosphate in seawater is known to alter phytoplankton
species compositions (e.g. Rhee 1978), which may
subsequently affect aquaculture production of bivalves
that feed on the phytoplankton. Reasons for reductionin phosphate with large fluctuation over the past
decade are unknown.

nutrient level is probably one of the key causes ofthe long-term subsiding HAB. Similarly, the surface
chlorophyll a level has been in a decreasing trend
in Ise Bay (Fig. 4), indicating the reduced primary
production of not only HAB species but also otherphytoplankters which may play important roles insupporting the food web in the area. Occurrence of
HAB is more frequent along the southern coast of Mie
Prefecture facing the Pacific Ocean.
While the reduced occurrence of HAB is favorable
to fisheries and aquaculture, the reduced primary
production started to be conceived as a problem inmany parts of Japan. It is considered that reduced
benthic fish and bivalve production, as well as
bleaching of cultured nori (Pyropia yezoensis) thalli(i.e. darker color commands a higher price) are in part
attributable to insufficient supply of nutrients to thecoastal waters (Handa and Harada 2012; Yamamoto2003). The Manila clam (Ruditapes philippinarum)
production has drastically dwindled in Mie Prefecturefrom 1224 t/year in 1985 to 106 t/year in 2015 (Fig. 5)
concomitantly with the drop in the DIN level (r2 =0.54, p < 0.0001) and the chlorophyll a level (r2 = 0.31,
p < 0.01). Although there are complex, multiple factors
involved in the diminution of the clam production (e.g.

Occurrence of harmful algal bloom (HAB) is
tightly linked with seawater nutrient levels (Honjo
1994). Mie Prefecture Fisheries Research Instituteregularly monitors occurrence of HAB; the HAB
species are as follows: Heterocapsa circularisquama,
Chattonella marina, C. antiqua, Dictyocha fibula(syn C. globosa), Heterosigma akashiwo, Karenia
mikimotoi (syn Gymnodinium mikimotoi), Ceratium
furuca, Prorocentrum dentatum, Noctiluca scintillans,and Akashiwo sanguinea. The frequency of HAB
has been markedly reduced in Ise Bay (Fig. 3). HAB
was observed 31 times (i.e. gross number and notnecessarily equals the actual occurrence) in 1985,
whereas it was observed only once in 2015. Reduced

Figure 4. Surface water chlorophyll a level in Ise Bay.

Figure 3. Observed number of harmful algal bloom (HAB)in Ise Bay.

4

Figure 5. Fisheries production of the Manila clam
(Ruditapes philippinarum) in Mie Prefecture.

Okamoto 2009) and causative relationship between
the nutrient environment and fishery production is
not fully elucidated, reduction in food supply seems
to be at least partially responsible for the diminution.
Similar oligotrophication problems are also reported
from freshwater systems in North America (Stockner
et al. 2000).
Water quality has also been improving in some semiclosed bays along the ria coastline of southern Mie
Prefecture, where the TPLSC is not applied, largely
because of diminished finfish aquaculture production
and improved feeding managements. These areas used
to have large amounts of red seabream and yellow tail
(Seriola quinqueradiata) aquaculture production, andeutrophication derived from the aquaculture effluent
was problematic (Abo 2000). However, red seabream
production in Mie Prefecture is in a decreasing trend
in both volume and value (Fig. 6) because of varied
reasons, such as the enforcement of the APAA since2004, reduced profitability due to international
competition, aging of the operators, as well as damage
caused by the 2011 Great East Japan Earthquake. The
number of management bodies (mostly self-owned
businesses) of red seabream aquaculture was reduced
from 287 in 2003 to 115 in 2014 in Mie Prefecture (Fig.
6). Yellowtail aquaculture sites have been relocatedfrom inner bay to offshore for better water exchange.
Switch of aquaculture feed from raw bait to pellets
significantly contributed in the fish productivity andreduction in effluents.

Figure 6. Production volume (upper) and value (lower)of the red seabream (Pagrus major) aquaculture in Mie
Prefecture.

(Robinson and Chopin 2004; Chopin 2006). Alongwith reinforcement of economic stability, one of theimportant goals of IMTA is to mitigate effluent loadfrom finfish aquaculture for environmental integrity.
In contrast, we are trying to develop techniques touse IMTA to compensate for the reduced aquaculture
productivity of bivalves and seaweeds associated withthe coastal oligotrophication.
The nitrogenous waste production rate from red
seabream aquaculture was estimated in Hasamaura
Cove, a semi-closed bay in southern part of Mie
Prefecture. As of 2012, there were 13 management
bodies, and approximately 157 t of red seabream wasproduced annually in Hasamaura Cove. The red
seabream seeds are stocked at around 60 g in bodyweight and harvested at around 1.4 kg after three yearsof culture with 85% survival rate. Assuming an FCR
of 2.5, the amount of nitrogen given to the fish in thefeed was estimated to be 24.2 t/year, 40% of which was
calculated to be used for the fish growth, 17% wasted
as leftover feed, 38% excreted as NH4+-N, and 5%
excreted as feces (Fig. 7). Therefore, the total nitrogenload to the environment from the red seabream culture
was estimated to be 14.5 t/year, in which 9.2 t/year
was NH4+-N that could be readily used for primaryThus, oligotrophication rather than eutrophication
is an issue in Japan, as is the reduced aquaculture
profitability of some finfish. Establishing a method
to make use of fed aquaculture effluent to enhance
unfed aquaculture productivity is desirable. Integrated
multi-trophic aquaculture (IMTA) is an aquaculture
approach that combines culture of economicallyimportant species from different trophic levels,
typically finfish, organic extractive species (e.g.
bivalve) and inorganic extractive species (e.g. seaweed)
5Figure 8. Nitrogen content of green alga Hitoegusa(Monostroma nitidum) in Hasamura Cove and nearby
bays in Mie Prefecture. The names of Bay A and B are notdisclosed.

Figure 7. Nitrogen budget of red seabream aquaculture
in Hasamaura Cove, Mie Prefecture estimated by a massbalance model.

production. The chlorophyll a level was observed
to be higher near the red seabream cages, with the
maximum layer expanding horizontally towards theinner part of the cove.

Considering that the fisheries production of theManila clam in Mie Prefecture has fallen below 1000 t/
year (Fig. 5), the nutrient provision from red seabreamaquaculture via primary production might have huge
potential to enhance bivalve production.

Despite the relatively small amount compared to
the TPLCS target value of 115 t-N/day in Ise Bay, thenitrogenous wastes from red seabream aquaculture
seemed to have an influence on the product quality ofM. nitidum cultured in Hasamaura Cove. Darker M.
nitidum with higher nitrogen content is considered abetter quality product and fetches higher unit price(e.g. farm gate price ranging from approx. JPY 3,500
to 13,000 per kg in dry weight). The mean nitrogencontent of M. nitidum cultured in Hasamaura Covewas more than twice as high as those cultured in
nearby bays along the same coastline without finfish
aquaculture (Fig. 8). Furthermore, there was a negative
correlation between the nitrogen content of M.
nitidum and the distance between the red seabream
cages and M. nitidum culture sites in Hasamaura Cove.
These imply that the effluents from the red seabreamaquaculture have a potential to fertilize M. nitidum.
The amount of nitrogen extracted by M. nitidum
culture in Hasamaura cove (i.e. 264 kg/year of harvest
in 2014) was equivalent to 2.9% of the red seabream
NH4+-N excretion.

Thus, IMTA has great potential to enhance aquaculture
production by using what would otherwise be fish
waste. Further studies are underway on aquaculture
techniques to provide useful information forestablishment of effective IMTA systems to utilize
aquaculture effluent in oligotrophic waters.

REFERENCES
Abo, K. 2000. Fluctuation of hypoxic water masses ina fish farming ground of semi-enclosed estuary
facing the ocean. Bulletin of National ResearchInstitute of Aquaculture 29: 141-216 (in Japanesewith English abstract).
Chopin, T. 2006. Integrated multi-trophic aquaculture:what it is, and why you should care anddon’t confuse it with polyculture. Northern
Aquaculture. July/August: 4.
Handa, H., and K. Harada. 2012. Setonaikai toubu(harimanada) no eiyouen kankyou to gyogyou(nutrient environment and fishery in Eastern
Seto Inland Sea) Aquabiology 199: 132-141 (inJapanese).
Higano, J., and D. Asao. 2017. Significance of thesuspended culture of asari clam Ruditapes
philippinarum and obstacles to increase its use.
Journal of Fisheries Technology 9: 87-100 (inJapanese with English abstract).
Honjo, T. 1994. The biology and prediction ofrepresentative red tides associated with fish kills inJapan. Reviews in Fisheries Science 2: 225-253.
Mie Prefecture Fisheries Research Institute. 1972- 2016.
Gyogyo kaikyo yoho jigyo kekka houkokusho(fisheries oceanography forecast project report)(in Japanese).

Because of severely dwindled Manila clam fisheries
production in many parts of Japan including Mie
Prefecture, suspended culture of the Manila clam hasrecently been drawing much attention (Higano andAsao 2017). A simple box model analysis estimatedthat the amount of NH4+-N excretion from the red
seabream aquaculture in Hasamaura Cove was
equivalent to the amount of nitrogen in 2071 t/year(wet weight) of Manila clam production, based on
the ongoing experimental data on growth, survival(Hasegawa unpublished data), food consumption
and metabolism (Watanabe unpublished data) of theManila clam under suspended culture conditions.
6

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Chopin, T., C. Yarish, R. Wilkes, E. Belyea, S. Lu, and
A. Mathieson. 1999. Developing Porphyra/salmon
integrated aquaculture for bioremediation anddiversification of the aquaculture industry. Journalof Applied Phycology 11: 463–472.
This is one of the first papers on IMTA (referred
to as integrated culture) combining salmon cage
culture and Porphyra (currently Pyropia) species
culture to alleviate the seasonal nutrient depletionby using the significant loading of salmon farms,
which is then valued (wastes become fertilizers)
and managed (competition for nutrients between
desirable algal crops and problem species associatedwith severe disturbances). The development ofintegrated aquaculture systems is a positive initiativefor optimizing the efficiency of aquaculture operations,while maintaining the health of coastal waters.
Watanabe, S., M. Kodama, and M. Fukuda. 2009.
Nitrogen stable isotope ratio in the manila clam,
Ruditapes philippinarum, reflects eutrophicationlevels in tidal flats. Marine Pollution Bulletin 58:
1447–1453.
The authors revealed that the nitrogen stable
isotope ratio (d15N) in the soft tissues of the manila
clam, Ruditapes philippinarum, could be used as anindicator of anthropogenic eutrophication levels
in tidal flat environments. In addition, they foundthat the acid insoluble fraction of the shell organic
matrix, conchiolin, could be used as a proxy for thesoft tissues in d15N analyses, which would result ineasier storage handling and the expansion of chances
for sample acquisition. Understanding the effects ofanthropogenic eutrophication on coastal fisheries mayhelp in the enhancement of fishery production byeffective utilization of sewage effluents, as well as in theconsequent reduction of eutrophication.

7

Interactions Between Shellfish Aquaculture and the Environment in the
Northeastern U.S.
Matthew Poach1*, Bob Alix2, Paul Clark2, April Croxton2, Mark Dixon2, Cathy Kuropat2, Judy Li2, Renee
Mercaldo-Allen2, Shannon Meseck2, Lisa Milke2, Dylan Redman2, Julie Rose2, Barry Smith2, and Gary Wikfors2
U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Marine FisheriesService, James J. Howard Marine Sciences Laboratory, Highlands, NJ 07732, USA.
2
U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Marine FisheriesService, Milford Laboratory, Milford, CT 06460, USA.
1

Corresponding author: matthew.poach@noaa.gov
Keywords: Not available.

ABSTRACTnitrogen removal and water clarity improvements byshellfish throughout New England and on the west
coast of the Korean peninsula. U.S. study locations
have included NY, CT, RI and MA and species
included ribbed mussels, blue mussels, clams andoysters. Research indicated that shellfish are able toadapt to a wide range of environmental conditions,but careful site selection is needed to maximize
environmental benefits of aquaculture operations.
Ultimately, this work demonstrates that shellfish
aquaculture can have a positive role in eutrophic
ecosystems. We plan to continue our work on
interactions between aquaculture and the environmentby expanding into multi-trophic and off-shore
aquaculture systems in New England.

Opposition to new shellfish aquaculture operationsin the Northeastern U.S. frequently is based upon
the premise that these commercial operations havenegative environmental consequences. This perception
is not consistent with the myriad of ecosystem services
that are attributed to shellfish, including improving
water clarity, reducing excess nutrients, providing
habitat, stabilizing sediments, and serving as a foodfor wildlife and humans. Researchers at the Milford
Laboratory have worked to quantify the complex
interactions between shellfish aquaculture and thenatural environment across the Northeastern UnitedStates region and beyond.

REFERENCES

From 2008-2010 experiments were conducted in
East Creek, Long Island, New York to quantify theenvironmental footprint of a floating upweller system(FLUPSY) within the surrounding embayment.
Metrics such as dissolved nutrients, phytoplankton
abundance and community composition, chlorophylla, temperature, salinity, and dissolved oxygen were
measured. Results of the multi-year study indicatethat the FLUPSY had a very small role in ecosystem
function compared with the range of naturalenvironmental variation within the East Creek
System. From 2009 to 2013, studies were conducted
to measure the consequences of hydraulic dredging
for clam harvest upon sediment chemistry and thebenthic community in coastal Milford Connecticut.
Milford Laboratory data indicated that hydraulicdredging caused initial, short-lived changes in
sediment chemistry that resolved within a few weeks.
Disturbance of the benthic community was minimal
and the community that inhabited this nearshorezone was naturally resilient to a dynamic physicalenvironment.

Li, Y., S.L. Meseck, M.S. Dixon, K. Rivara, andG.H. Wikfors. 2012. Temporal variability inphytoplankton removal by a commercial,suspended eastern oyster nursery and effects
on local plankton dynamics. Journal of Shellfish
Research 31: 1077-1089.
Meseck, S.L., Y. Li, M.S. Dixon, K. Rivara, G.H.
Wikfors, and G.I. Luther. 2012. Effects of acommercial, suspended eastern oyster nursery
upon nutrient and sediment chemistry in atemperate, coastal embayment. Aquaculture andEnvironment Interactions 3: 65-79.
Li, Y., S. Meseck, M. Dixon, J. Rose, B. Smith, and G.
Wikfors. 2013. Short term effects of a commercial
eastern oyster nursery upon nutrient and plankton
dynamics of a coastal embayment: observations
from mesocosm experiments. Aquaculture
Research 46(9): 2049-2064.
Mercaldo-Allen, R., R. Goldberg, P. Clark, C. Kuropat,
S.L. Meseck, and J.M. Rose. 2016. Benthic ecology
of northern quahog beds with different hydraulicdredging histories in Long Island Sound. Journalof Coastal Research 32(2): 408-415.

Milford research also has quantified the environmental
benefits of shellfish aquaculture. Starting in 2011, thebiodeposition method was employed to measure
8

Meseck, S.L., R. Mercaldo-Allen, J.M. Rose, P. Clark,
C. Kuropat, J.J. Pereira, and R. Goldberg. 2014.
Impacts of hydraulic dredging for Mercenaria
mercenaria, northern quahog, on sedimentbiogeochemistry. Journal World Aquaculture
Society 45(3): 301-311.
Goldberg, R., J.M. Rose, R. Mercaldo-Allen, S.L.
Meseck, P. Clark, C. Kuropat, and J.J. Pereira.
2014. Effects of hydraulic dredging on the benthic
ecology and sediment chemistry on a cultivatedbed of the hard clam, Mercenaria mercenaria.
Aquaculture 428–429: 150–157
Goldberg, R., R. Mercaldo-Allen, J.M. Rose, P. Clark,
C. Kuropat, S. Meseck, and J. Pereira. 2012. Effectsof hydraulic shellfish dredging on the ecology ofa cultivated clam bed. Aquaculture Environment
Interactions 3: 11-21.

Galimany, E., J.M. Rose, M.S. Dixon, and G.H.
Wikfors. 2013. Quantifying feeding behavior ofribbed mussels (Geukensia demissa) in two urbansites (Long Island Sound, USA) with different
seston characteristics. Estuaries and Coasts, 1-9.
Rose, J.M., S.B. Bricker, M.A. Tedesco, and G.H.
Wikfors 2014. A role for shellfish aquaculture incoastal nitrogen management. Environmental
Science & Technology 48, 2519-2525.
Rose, J.M., S.B. Bricker, and J.G. Ferreira. 2015.
Comparative analysis of modeled nitrogen
removal by shellfish farms. Marine Pollution
Bulletin 91, 185-190.

9

Land-based Aquaculture of Red-Spotted Grouper (Epinephelus akaara)
Using the Closed Recirculation System
Masatsugu Takano1*, Tetsuo Morita2, and Yoshihisa Yamamoto2
Headquarters, Japan Fisheries Research and Education Agency, Minato-mirai 2-3-3, Queen’s Tower B 15F,
Nishiku, Yokohama, Kanagawa 221-6115, Japan
2
Yashima Laboratory, National Research Institute of Fisheries and Inland Sea, Japan Fisheries Research and
Education Agency, Yashima-higashimachi 234, Takamatusu Kagawa 761-0111, Japan
1

Corresponding author: masatsug@affrc.go.jp
Keywords: Epinephelus akaara, recirculating aquaculture system

ABSTRACT

MATERIALS AND METHODS

The red-spotted grouper, Epinephelus akaara, is acommercially valuable fish in Japan. Because of its highvalue, this species is expected to be a new target fish
for aquaculture. However, its culture is thought to bedifficult because of its slow growth (four or five years
until the fish are of commercial size). To achieve faster
growth and higher feed efficiency for the red-spottedgrouper, we investigated different water temperaturesusing a closed recirculation system. In higher watertemperatures between 16 °C and 31 °C, growth was
faster. The best feed efficiency was obtained at 25 °C.
We also carried out similar experiments with salinity.
Together, we were able to determine the optimum
water temperature and salinity conditions for theeffective growth of red-spotted grouper.

Growth Due to the Difference in the Rearing
Water Temperature
We compared the growth, daily feeding rate and feed
conversion efficiency of the red-spotted grouper
using the closed recirculation system at the Yashima
Laboratory of the National Research Institute ofFisheries and Inland Sea in August (to September)2013. Twenty specimens were held for 30 days in
two 80 L tanks (containing 75 L of seawater) in eachexperiment. The mean body weight was 88 g at the
beginning. These experiments were performed at 16,
22, 25, 28 and 31 °C.
Growth Due to the Difference in the Rearing
Salinity

INTRODUCTION

We compared the growth and feed conversion efficiency
in different salinity conditions. Thirty specimens were
held for 32 days in two 80 L tanks (containing 75 L ofseawater) in each experiment. The mean body weightwas 23 g at the beginning. These experiments were
performed in 6, 13, 19, 26, 32 and 38 psu.

The red-spotted grouper belongs to the family
Serranidae, which is great interest in this species
as new target fish for aquaculture due to its highcommercial price in Japan (Nambu 2014). However,
because it takes four to five years for this species toreach commercial size, we needed to develop methods
for shortening the rearing period to decrease the costof culturing the fish (Morita 2014). In Japan, research
on closed recirculation systems was started in the
1950s. Dr. Saeki and Dr. Hirayama were pioneers inresearch on closed recirculation systems, including
development of the bio-filter (Yamamoto et al. 2008).
We started technical development of the closed
recirculation system for seed production of red sea
bream in 2000 at the Yashima Laboratory (Yamamoto
et al. 2013). In this study, to shorten the culture periodof the red-spotted grouper, we investigated optimum
water temperature and salinity by using the closed
recirculation system, which allowed us to maintain
optimal water conditions.

RESULTS
Growth Due to the Difference in the Rearing
Water Temperature
The rates of the increased weight are shown in Fig. 1.
The rates of the increased weight (final body weight/ initial body weight x 100) were 101 % (16 °C), 104 %(19 °C), 108 % (22 °C), 116 % (25 °C), 116 % (28 °C) and
129 % (31 °C). Those fish in the controls (16 °C) didn’t
increase in weight (101 %).
The daily feeding rate (average feed weight / bodyweight over the 30 days) was 4 % (16 °C), 7 % (19 °C),
16 % (22 °C), 18 % (25 °C), 24 % (28 °C) and 35 % (3110Figure 1. Growth due to the difference in the rearing watertemperature. All statistics were done by independent t-test.
No statistically significant difference was found amongtemperatures.

Figure 2. Daily feeding rate due to the difference in therearing water temperature. All statistics were done byindependent t-test. No statistically significant difference
was found among temperatures.

Figure 4. Growth due to the difference in the rearing
salinity. The line graph (open circle) is feed conversion
efficiency, the bar graph is rate of the increased weight. All
statistics were done by independent t-test. No statisticallysignificant difference was found among salinities in eachexperiment.

Figure 3. Feed conversion efficiency due to the differencein the rearing water temperature. All statistics were doneby independent t-test. No statistically significant difference
was found among temperatures.

Example in Larger-scale Culture Tanks°C). The daily feeding rate is shown in Fig. 2. From
16 °C to 31 °C, feeding rate rose as the rearing watertemperature is higher.

From these results, we conducted the breeding
experiment in the larger 5 kL culture-scale tank (total
water quantity was 8 kL, including in the closed
recirculation system) in September 2013. The bodyweight at the beginning was 8.6 g ± 1.5 g (5.3 g - 11.7 g).
Two thousand specimens were used in each treatment.
The change of the body weight from 4 days to 66 daysis shown in Fig. 5.

The feed efficiency was calculated using following
formula: feed conversion efficiency (%) = ((final weight- initial weight) / total feed weight) x 100. The feed
conversion efficiencies were 13 % (16 °C), 53 % (19 °C),
49 % (22 °C), 89 % (25 °C), 65 % (28 °C) and 78 % (31°C). The feed conversion efficiency is shown in Fig. 3.
From 16 °C to 31 °C, the highest of the feed conversion
was obtained at 25 °C.

Three treatment groups (25 °C, 30 °C and 25 °C (lowsalinity)) were reared in closed recirculation systems.
Growth Due to the Difference in the Rearing
In all three treatments, a difference in weight gain
Salinity
was apparent early when compared to the control,
where the water temperature and the salinity was not
adjusted. Among the three treatments, the weight
The rates of the increased weight and the feed
gain was the largest in the test group with water
conversion efficiency are shown in Fig. 4. The trends
in weight increase and feed conversion across different temperatures of 25 °C plus low salinity (20-29 ‰).
These conditions (25 °C plus low salinity) would allow
salt concentrations were similar. The rate of thegrowth of red-spotted grouper up to the commercial
increased weight was 116 % (6 psu), 147 % (13 psu), 156% (19 psu), 152 % (26 psu), 143 % (32 psu) and 138 % (38 size (500 g) within two years.
psu). The feed conversion efficiency was 42 % (6 psu),
90 % (13 psu), 93% (19 psu), 87% (26 psu), 79 % (32psu) and 70 % (38 psu). The growth rate was faster inwater of 19 psu and 26 psu compared with 32 psu and
38 psu. Some specimens died in the water below 6 psu.
11

Figure 5. Change in body weight in larger scale culture tanks (5 kL). Closed circle and Purple lines show results at 25°C. Open circle and Broken line show results at 25 °C + low-salinity. Square with Red line shows results at 30 °C. Threetreatments (purple, broken, and red) were reared using closed recirculation systems. Triangle and Blue lines show
results where water temperature and salinity were not adjusted. Significant differences, using Tukey’s test (p = 5 %),were found between the 25 °C + low salinity treatment and the other treatments for all weeks after the 4th week.

DISCUSSION

2001). It has been suggested that closed recirculation
systems would be suitable for breeding research tocompare environmental conditions and study controlof fish diseases.

The red-spotted grouper is a new potential target foraquaculture because of its high commercial value inJapan. However, its culture is thought to be difficult
due to its slow growth where four to five years areneeded to reach commercial harvest size (Nambu
2014). Our results suggest that the closed recirculation
system can assist in the expansion of land-based
aquaculture. The traditional flow-through system isexpensive to maintain in optimum condition, but theclosed recirculation system solves this problem byreusing drainage. (Yamamoto et al. 2008). In addition,
we were able to improve rearing techniques for a slow
growth fish with great potential for aquaculture. Ourinvestigation revealed the optimal water temperatureand salinity for growth of red-spotted grouper
to commercial size is only two years in a closed
recirculating aquaculture system.

However, since the breeding conditions of the redspotted grouper using traditional flow-through systems
had only been studied in larger tanks (Nambu, 2014)
and recirculation systems in smaller tanks, economic
analysis of production in closed recirculation systems
versus conventional flow-through systems has not
yet been investigated. To address this question, we
also needed to investigate breeding conditions in alarger tank at a scale suitable for practical application.
Finally, it will be necessary to perform a cost analysis
in the future in order to develop practical aquaculture
technology using the closed recirculation system.

CONCLUSION

Furthermore, mass mortalities associated with viralnervous necrosis (VNN) have occurred in red-spottedgrouper reared in a traditional flow-through system
not only in Japan but also in other countries (Lin et al.

The results of this study demonstrated the potential
for large-scale production of red-spotted grouper
using a closed recirculating aquaculture system.
However, in order to enable commercial adoption of
12this technology, we need to develop more practicaltechnologies and cost analyses. Thus, it is necessary tofurther develop appropriate rearing techniques for fishgrown in the closed recirculation system.

Morita, T. 2014. Potential for circulating land farming
business of red spotted grouper Epinephelus
akaara. Aquaculture Business 51(13): 14-16.
Yamamoto, Y., and S. Hayase. 2008. Thematic regional
reviews: Japan. In The future of mariculture: aregional approach for responsible development in
the Asia-Pacific region. FAO Fisheries Proceedings
11: 189-198.
Yamamoto, Y., M. Kamoshida, and T. Takeuchi.
2013. Examination of suitable condition ofrecirculation rate in a closed recirculating system
for larviculture of red sea bream, Pagrus major.
Eco-Engineering 25(2): 49-58.

ACKNOWLEDGMENTS
We deeply appreciate the assistance of the members of
the Yashima Laboratory, National Research Instituteof Fisheries and Inland Sea, Japan Fisheries Researchand Education Agency, for rearing the red-spottedgrouper. We are grateful to Dr. Takayuki Kogane(Tamano Laboratory, National Research Institute ofFisheries and Inland Sea, Japan Fisheries Research and
Education Agency) for providing specimens of the
red-spotted grouper. We also thank Dr. Masahiro Imai
(Yashima Laboratory, National Research Institute ofFisheries and Inland Sea, Japan Fisheries Research and
Education Agency) for advice on this study.

ANNOTATED BIBLIOGRAPHY OF KEY
WORKSMidooka, A. 2012. The development of seedproduction technology by using low salinity
treatment. Aqua Net 7: 42-45.

REFERENCES

This is one of the first reports on effectiveness using
low-salinity treatment of red-spotted grouper’s seedproduction. The author suggested that examining
the optimum salinity setting and the effective
period at rearing of the red-spotted grouper for the
improvement of the survival rate, also reported thepossibility of the cost saving effect by using the closed
recirculation system in low-salinity rearing.

Lin L., J. He, K.-i. Mori, T. Nishioka, J.L. Wu, S. Weng,
K. Mushiake, M. Arimoto, and T. Nakai. 2001.
Mass mortalities associated with viral nervous
necrosis in hatchery-reared groupers in the
People’s Republic of China. Fish Pathology 36(3):186-188.
Nambu, T. 2014. II-7. Seed production and aquaculture
technology of red spotted grouper Epinephelus
akaara. Nippon Suisan Gakkaishi 80(6): 1000.

13

Using Physiological Tools to Assess and Optimize Aquaculture of
California Yellowtail, Seriola dorsalis
Nicholas C. Wegner1*, Laura N. Schwebel1,2, and John R. Hyde1
12Southwest Fisheries Science Center, NOAA Fisheries, La Jolla, CA 92127
University of San Diego, 5998 Alcala Park, San Diego, CA 92110

Corresponding author: nick.wegner@noaa.gov
Keywords: yellowtail, physiology, metabolism, fitness, aquaculture

ABSTRACTsashimi products as well as premium fish fillets.
However, unlike salmonids, which have a much longer
history in aquaculture, basic research is required to
inform best practices for rearing yellowtail in a healthy,
sustainable way. Historically, the culture of Seriola has
involved collecting early life stage juveniles from thewild that are transferred to pens and reared to market
size. However, the regional and, in many cases, thedeclining availability of wild seed (Nakada 2002, 2008)
has led to more recent efforts to produce eggs and larvae
in a hatchery setting from wild-captured broodstock(Moran et al. 2007; Stuart and Drawbridge 2013).

The California yellowtail (Seriola dorsalis) is apromising candidate for offshore commercial
aquaculture in southern California. However, best
rearing practices for this and other Seriola species arestill under development, and our work has shown thatyellowtail spawned and reared in captivity are typicallyless healthy than their wild-caught counterparts.
Our research thus seeks to use various physiologicaltools and metrics to monitor fish health, fitness, andgrowth in an attempt to enhance rearing techniques.
Over the past few years, our work has focused on 1)
examining fitness differences between wild-caught
and aquaculture-reared individuals through measuresof critical swimming speed and metabolic rate, 2)
determining the adverse effects of an extremelycommon deformity (an uninflated gas bladder) in
hatchery-reared yellowtail on their critical swimming
speed, metabolic rate, growth rate, and feed conversion
ratio, and 3) investigating the potential growth andhealth benefits of forced exercise on early juvenilestage yellowtail. Our results suggest that although wildcaught fish tend to show better health and metabolic
efficiency, great strides in yellowtail health and fitness
in aquaculture have occurred during the durationof our research, and eliminating deformities suchas uninflated gas bladders greatly increases growout
efficiency. While our swimming exercise studies
are still underway, preliminary data suggest that ashort duration of exercise (3-4 weeks) followed by
growout in standard rearing tanks produces a growthadvantage. Such exercise regimes may thus represent
not only a mechanism for improving fish health andfitness, but also a non-genetic and non-hormonal
treatment to accelerate growth of fish for food or wild
stock enhancement.

Recent research in larval rearing techniques has opened
the opportunity for expanding Seriola aquaculture
development; however, further research is needed tounderstand and optimize the rearing process. Overthe past five years, research at the Southwest Fisheries
Science Center has used a variety of physiologicaltools to assess the health and fitness of the California
yellowtail (Seriola dorsalis) to enhance rearing
protocols. Specifically, this has included three studies: 1)
examination of differences in metabolic and swimming
fitness between aquaculture-reared and wild-caught
fish to provide baseline metrics and achievable
health standards for hatchery-reared yellowtail, 2)
determination of the adverse effects of an uninflated gas
bladder (a common hatchery deformity) on the fitnessof aquaculture-reared yellowtail, and 3) examination of
the potential beneficial effects of forced exercise on thegrowth and health of yellowtail reared in captivity.
This work builds upon preliminary research presented
at the 2014 UJNR workshop which comparedaquaculture-reared and wild-caught S. dorsalis
in terms of swimming performance (e.g., criticalswimming speed) and metabolic fitness (e.g., standard
metabolic rate) as indicators of fish “physiologicalwell-being.” Having established baseline metrics foryellowtail, we apply these to examine the physiologicalcosts of S. dorsalis lacking a properly inflated swim
bladder. While the exact cause of this deformity is
not well understood, it is important to understandpotential health impacts (and associated production
costs) associated with rearing fish with this deformity.

INTRODUCTION
The carangid genus Seriola, or amberjack species, hasbeen identified as a group with ideal characteristics
for warm water aquaculture. Seriola species have fast
growth rates, demonstrate adaptability to hatcheryproduction and pen culture, and provide high value
14

(minutes) at the fatigue velocity, ti is the time interval
for each velocity increment (30 minutes), and Vi is thelast incremental speed increase (either 5 cm s-1 or 10 cms-1). Following experimentation, swimming speed wascorrected for the solid blocking effect of the flow meter
during calibration and for the fish in the chamber (Belland Terhune 1970).

We test the hypothesis that, because the gas bladderregulates buoyancy and thus fish with this deficiency
are negatively buoyant, this deformity results insubstantial metabolic costs that likely influence energy
allocation and growth.
Finally, exercise has been shown to be a promising
non-invasive, non-hormonal method to stimulate
growth (Brown et al. 2011; Palstra et al. 2015; Yogata
and Oku 2000), lower feed conversion ratios (Palstra
et al. 2015; Yogata and Oku 2000), and potentiallyaffect metabolic rate (Brown et al. 2011), resulting
in improved fitness. However, the results of exercise
conditioning for S. dorsalis, and for the closely
related S. lalandi, have varied in terms of swimming
speed, exercise duration, and feeding parameters, so
it is unclear how much exercise is needed to elicit afavorable response. This study thus aimed to makepreliminary evaluations on the effect of exercise
duration on growth and fitness in S. dorsalis.

Oxygen consumption rates (ṀO ) were determinedfor each fish at each swimming speed using a fiber
optic oxygen sensor. Shortly after the step increase inswimming speed, the respirometer was temporarily
sealed from the inflow and outflow of fresh seawater,
and the rate of oxygen consumption was observed
until the oxygen level of the swim tunnel water reachedapproximately 80% saturation, at which point thesystem was flushed and then ṀO measurements wererepeated at that speed, if possible. To compensate fordifferences in fish mass and water temperature between
trials, ṀO measurements were adjusted to a water/ body temperature of 18°C (using Q10 = 2) (Pirozzi
and Booth 2009) and to a body mass of 80 g (using
mass0.80). Metabolic data were then used to create
an exponential regression relationship for ṀO vs.
swimming speed for each individual. Each regression
line was extrapolated to a swimming speed of 0 cm s-1
to estimate the standard metabolic rate for that fish.
2

2

2

METHODS
Fish Collection and Husbandry

2

Aquaculture-reared California yellowtail used in thiswork were provided by Hubbs-SeaWorld ResearchInstitute (HSWRI) in San Diego, CA, and weretransferred to the experimental aquarium facility at
the Southwest Fisheries Science Center (SWFCS) for
physiological experimentation. Wild juvenile yellowtail
associated with drifting kelp in local offshore waters
were captured by hook and line. All fish were fed
commercial pellet fish feed to satiation six days a week
and were kept for a minimum of five weeks in theaquarium facility before any experimentation began.

Study 2: Fitness and Growth of Yellowtail witha Swim Bladder Deformity

Study 1: Swimming and Metabolic Fitness
of Aquaculture-reared and Wild-caught
Yellowtail

Swimming and metabolic fitness as well as the somatic
growth and efficiency of food use were examinedin aquaculture-reared yellowtail with both properly
inflated (functional) and non-inflated (non-functional)
swim bladders in comparison to wild-captured
individuals. Each group (inflated n=40, uninflated
n=40, wild n=39) was kept in a separate oval tank
(3200 l) with consistent water and feed conditions foran 8-month growout period to track fitness and growthover time.

In order to examine potential differences in theswimming and metabolic fitness of aquaculturereared and wild-caught yellowtail, measures of criticalswimming speed and metabolic rate were made usinga small 5.4 l Brett-style swim tunnel respirometer.
Following a 1 h acclimation period, fish were forced
to swim at incremental velocities (5-10 cm s-1) for
30 minutes until the speed was too fast for the fishto maintain its position within the tunnel (i.e., toexhaustion). The critical swimming speed (Ucrit) was
estimated by the equation:

Methods for determining critical swimming speed andstandard metabolic rate were repeated as in Study 1 at
two time points during growout: once at the beginningof the growout period using a 5.4 l swim tunnel
respirometer and once approximately four months
later using a 30 l swim tunnel respirometer. These time
points were selected based on optimal fish size forproper utilization of the two available swim tunnels.
Swim tunnel trials were conducted on 7-9 individuals
randomly selected from each group at each time point.
Somatic measurements were taken for all individuals
in each group at the beginning and end of the 8-month
growout period, and growth rate was calculated as theaverage initial mass subtracted from the average final
mass (g), divided by the number of days of growth.
All fish were hand fed to prevent over feeding. The(1)
where Ucrit is the critical swimming speed (cm s-1),
Vp is the highest speed sustained for a full 30-minuteincrement (cm s-1), tf is the time the fish swam
15

feed conversion ratio (FCR) was calculated using theequation:(2)
Study 3: Examination of the Effect of Exercise
on Metabolism and Growth
For the final study, aquaculture-reared yellowtail were
exercised in custom-designed fish raceways (Fig. 1)
in order to examine the potential beneficial effects ofexercise on metabolic fitness and growth. Fish wereforced to swim against a current in the raceways at
predetermined optimal swimming speeds (6-8 BLs-1) for different durations of time (two, three, or fourweeks). Following exercise, fish were removed fromthe raceways to separate growout tanks with thesame parameters as a non-exercised control group(3200 l oval tank). Metabolic rate, growth, and feed
conversion ratio were then tracked over a six-month
growout period. Metabolic rates were determined fora subset of fish (n = 8) randomly selected from eachgroup measured in the week following exercise andat two other time points (1.5 and three months postexercise) using incremental velocity trials in swim
tunnel respirometers as previously described. After
swim tunnel experimentation, fish were measured as
described above and sacrificed. The rest of the fish weregrown out and somatic measurements were taken on asubset of 30 fish from each group every two weeks.

Figure 1. Custom-designed fish raceway used for exercise
training of California yellowtail in Study 3.

speed of 0 cm s-1 shows that the standard metabolic
rate of aquaculture-reared yellowtail (7.31 ± 2.32 mgO2
kg-1 min-1) was significantly greater than that of wildcaught individuals (3.94 ± 1.60 mgO2 kg-1 min-1).
These data show reduced fitness of aquaculture-reared
yellowtail in comparison to wild-caught individuals as
manifested through differences in critical swimming
speed and standard metabolic rate. Such reductions
in fitness are likely associated with rearing in a
suboptimal aquaculture setting (e.g., lower wateror diet quality, decreased physical activity) or may
reflect suboptimal phenotypes having a higher chancefor survival in captivity. Both scenarios are likely at
work and highlight the need for both genetic studies
for the selection of broodstock that produce thehighest quality offspring as well as experimentation todetermine best rearing practices (i.e., determinationof feed, water, and other environmental impacts onfish fitness and growth). This study also suggeststhat aspects of both the swimming and metabolic
fitness of S. dorsalis can be improved in culture
growout operations. For example, a 50% reductionin the standard metabolic rate of aquaculture-reared
yellowtail (to that observed in wild-caught fish) should
result in lower feed requirements and substantial costsavings to aquaculture producers.

Statistical Analyses
Swimming and metabolic metrics in Study 1 werecompared between aquaculture-reared and wildcaught yellowtail using a two-tail t-test. A single factor
ANOVA with a post-hoc Tukey test was performed on
critical swimming speed data, standard metabolic data,and somatic measurement data for Studies 2 and 3.
Statistical significance was established at P ≤ 0.05.

RESULTS AND DISCUSSION
Study 1: Swimming and Metabolic Fitness
of Aquaculture-reared and Wild-caught
yellowtail

Study 2: Fitness and Growth of Yellowtail witha Swim Bladder Deformity
While the results of this study are still being assessed,
preliminary data reveal that the standard metabolic rateand critical swimming speed for yellowtail reared inaquaculture with inflated and uninflated swim bladders
did not differ significantly (Table 1). However, yellowtail
with uninflated swim bladders were found to havehigher feed conversion ratios and slower growth rates
than those of yellowtail with properly inflated swim
bladders. This less efficient resource allocation likely
results from the need of yellowtail that lack a functional
swim bladder to swim at faster speeds to generate

The mean maximum sustainable swimming speed
for 10 aquaculture-reared yellowtail (77.08 ± 9.36 cm
s-1, 4.16 ± 0.62 BL s-1) was significantly slower thanthat determined for seven wild caught individuals ofsimilar size (92.93 ± 13.32 cm s-1, 4.80 ± 0.52 BL s-1).
Aggregate data showing the relationship between ṀO
and swimming velocity for all metabolic measurements
for 10 aquaculture-reared and seven wild-caught
yellowtail are shown in Fig. 2. Extrapolation ofregression equations for individual fish to a swimming
2

16

Figure 2. Oxygen uptake (ṀO ) of aquaculture-reared (grey circles) and wild-caught (black
circles) California yellowtail, S. dorsalis, swimming at variable speeds in a swim tunnel
respirometer in Study 1. For direct comparison all data were adjusted to a mass of 80 g using
M0.80 and water temperature of 18°C using Q10 = 2.0. Regression lines are for observational
purposes only; standard metabolic rate was determined from individual fish data.
2

Table 1. Metrics of physical fitness and growth for aquaculture-reared S. dorsalis with properly inflated and uninflated
swim bladders in comparison to wild captured yellowtail (Study 2).
Ucrit (Start)
Ucrit (4 months)
SMR (Start)
SMR (4 months)
Growth RateGroup
(BL s-1)(BL s-1)(mgO2 kg-1 s-1)
(mgO2 kg-1 s-1)
FCR
(g day-1)
Wild
5.34 ± 0.59
4.31 ± 0.35
2.97 ± 0.93
2.96 ± 0.83
1.41
2.79
Inflated
5.12 ± 0.99
4.50 ± 0.37
5.17 ± 1.93
3.55 ± 1.95
1.50
3.20
Uninflated
5.20 ± 0.53
4.25 ± 0.62
5.43 ± 1.69
3.41 ± 1.59
2.08
2.64

Critical swimming speed (Ucrit) and standard metabolic rate (SMR) are shown at the start of the experiment (mean mass = 63.79 ± 17.81 g) and again
approximately four months later (412.15 ± 61.94 g). Statistically significant differences indicated in bold. Values given as means ± standard deviation.

Table 2. Mean size [fork length (FL), total length (TL) and mass] ± standard deviation of fish in each exercise group (2,3, 4 weeks of sustained swimming at 6-8 body lengths per second), compared to a non-exercised control group after a
14-week grow-out period (Study 3).
Group
Four Weeks
Three Weeks
Two WeeksControl

Note: Data are preliminary.

FL (cm)29.73 ± 1.39
29.69 ± 1.14
29.44 ± 1.54
29.30 ± 1.43

TL (cm)32.80 ± 1.54
32.86 ± 1.32
32.52 ±1.76
32.18 ± 1.52

Mass (g)471.47 ± 73.79
472.20 ± 61.81
452.13 ± 87.22
411.20 ± 70.05% mass difference(above control)
14.66
14.83
9.95
0.00

Table 3. Feed conversion ratio for three groups of exercised yellowtail in comparison to a non-exercised control (Study 3).
Group
Four Weeks
Three Weeks
Two WeeksControl

Total Food Consumed
(kg)
48.95
56.30
55.29
48.66

Note: Data are preliminary.

Total Mass Gained (kg)
43.56
51.03
50.51
42.59

17

FCR
1.12
1.10
1.09
1.14

% difference
from control
1.65
3.44
4.20
0.00

hydrostatic lift in order tocompensate for their negative
buoyancy. The resulting
increase in required food foryellowtail with this deformity
likely signifies that it is not
economical to rear them tomarket size.
Like Study 1, this study also
showed that aquaculture
yellowtail (both with andwithout properly inflated
gas-bladders) had a higher
standard metabolic rate thanthat of wild-caught fish at thestart of the experiment (Table1). Interestingly, there was nota significant difference in thecritical swimming speed of
Figure 3. Mean standard metabolic rate (SMR) for each group (2, 3, 4 weeks ofaquaculture-reared and wildsustained exercise) in comparison to a control at three time points post exercise
caught fish in this study, and(Study 3). Means for each group are shown with 95% confidence intervals and were
the difference in standard
standardized to 22 °C (using Q10 = 2) and scaled to the mean mass at each time
metabolic rate was less thanpoint (using M0.80). Data are preliminary.
that previously observed (i.e.,in Study 1). This suggests thatenhancements in rearing protocols between Study 1
on metabolism by lowering the standard metabolic(a 2012 cohort) and this study (using a 2015 cohort)
rate of yellowtail exercised for three and four weeks
have likely increased the fitness of yellowtail reared inby approximately 15%. This decrease in standard
aquaculture. While it appears that improvements have metabolic rate may allow more energy to be allocatedbeen made, the potential negative effects of captive
toward growth resulting in the increased body size
rearing were seen in that after four months, wildobserved in Table 2. However, preliminary results alsocaught yellowtail no longer showed a metabolic fitness indicate this metabolic advantage is not retained overadvantage in comparison to aquaculture-reared fishtime and that within 1.5 months there is no longer(Table 1).
a metabolic difference between groups. Preliminary
feed conversion data (Table 3) suggests only slightdifferences in feed efficiency between groups, but a fullThis study thus demonstrates that there is continued
analysis still needs to be completed.
room for improvement in aquaculture-reared fish inlowering their standard metabolic rates, which could
improve efficiency and lower feed conversion ratios.
While the results of this and previous studies on other
Ideally, farmed fish would have metabolic rates andSeriola species indicate exercise has a positive effect on
feed conversion ratios similar to those observed in
growth, the magnitude of this effect seems to be highly
wild fish while maintaining the high growth rates ofvariable, ranging from 10 to 46% (Yogata and Oku
the inflated group (Table 1). This combination would
2000; Brown et al. 2011; Palstra et al. 2015). The large
produce physiologically fit and healthy fish that could
variation in observed growth rates likely reflects variablebe produced more efficiently and sustainably.
conditions between studies including temperature,swimming speed, exercise duration, and the initial size ofStudy 3: Examination of the Effect of Exercise the fish in each experiment. Analysis and interpretationof our results is ongoing, and due to variability in theon Metabolism and Growth
response to exercise, we plan to replicate these trials on
future cohorts. Our results suggest exercise has a strong,
Preliminary somatic growth measurements taken
immediate physiological effect, but timing (yellowtail
14 weeks following completion of the exercise trials
life stage and duration of exercise) and environmental
show that the exercised fish are 10-15% larger than thevariables (temperature, flow speed) play important roles
controls (Table 2). Preliminary metabolic results (Fig.
in optimizing the response.
3) suggest that exercise may also have positive effects

18

REFERENCES

This study investigated the effect of swimming exercise
on the growth of cultured New Zealand yellowtail
kingfish, Seriola lalandi, at different water temperaturesand swimming speeds. Two growth trials exposed fish todifferent exercise levels (determined by current speed) at
14.9° and 21.1°C. Lengths and weights were measured foreach fish before and post exercise, along with metabolic
rates using a respirometer. Results of these trials showedthat exercise yielded a 10% increase in growth but
only at low swimming speeds (0.75 BL s-1) and at atemperature of 21.1°C. Experiments using a swim tunnel
respirometer indicated that exercise training had noeffect on metabolic scope or critical swimming speeds
but it did improve swimming efficiency.

Bell, W.H., and L.D.B. Terhune. 1970. Water tunnel
design for fisheries research. Fisheries Research
Board of Canada Technical Report, Pp. 69.
Brown, E.J., M. Bruce, S. Pether and N.A Herbert. 2011.
Do swimming fish always grow fast? Investigating
the magnitude and physiological basis of
exercise-induced growth in juvenile New Zealandyellowtail kingfish, Seriola lalandi. Fish Physiology
and Biochemistry 37: 327-336.
Moran, D., C.K. Smith, B. Gara, and C.W. Poortenaar.
2007. Reproductive behaviour and early
development in yellowtail kingfish (Seriola lalandi
Valenciennes 1833). Aquaculture 262: 95-104.
Nakada, M. 2002. Yellowtail culture development
and solutions for the future. Reviews in Fisheries
Science. 10: 559-575.
Nakada, M. 2008. Capture-based aquaculture ofyellowtail. In Lovatelli A., Holthus P.F. (eds.),
Capture-based Aquaculture, Global Overview,
FAO Fisheries Technical Paper No. 508. FAO,
Rome, Pp. 199-215.
Palstra, A.P., D. Mes, K Kusters., J.A.C. Roques, G. Flik,K. Kloet, and R.J.W. Blonk. 2015. Forced sustained
swimming exercise at optimal speed enhances
growth of juvenile yellowtail kingfish (Seriolalalandi). Frontiers in Physiology 5: 506.
Pirozzi, I., and M.A. Booth. 2009. The routine
metabolic rate of mulloway (Argyrosomus
japonicus: Sciaenidae) and yellowtail kingfish(Seriola lalandi: Carangidae) acclimated to six
different temperatures. Comparative Biochemistry
and Physiology 152A: 586-592.
Stuart, K.R., and M. Drawbridge. 2011. The effect oflight intensity and green water on survival andgrowth of cultured larval California yellowtail(Seriola lalandi). Aquaculture 321: 152-156.
Yogata, H., and H. Oku. 2000. The effects of swimming
exercise on growth and whole‐body protein andfat contents of fed and unfed fingerling yellowtail.
Fisheries Science 66: 1100-1105.

Palstra, A.P., D. Mes, K. Kusters, J.A.C. Roques, G. Flik,K. Kloet, and R.J.W. Blonk. 2015. Forced sustained
swimming exercise at optimal speed enhances
growth of juvenile yellowtail kingfish (Seriolalalandi). Frontiers in Physiology 5: 506.
The swimming exercise trials in this study for Seriolalalandi resulted in 46% greater increases in mass and
92% larger increases in length compared to nonexercised controls. This study thus showed greater
exercise benefits than those observed in the Brown et al.
(2012) study (above), and these differences were likely
related to using more optimal exercise swimming speeds.
The exercise and control groups in this study were fed
equivalent rations, indicating the exercised fish had
more efficient resource allocation, resulting in a lower
feed conversion ratio (1.21 vs. 1.74 for non-exercised
yellowtail). These researchers thus suggest that growthrate can be greatly enhanced without increased feeding.
Palstra, A.P., and J.V. Planas (eds). 2013. Swimming
Physiology of Fish: Towards Using Exercise
to Farm a Fit Fish in Sustainable Aquaculture.
Springer-Verlag, Berlin.
This multi-chaptered volume reviews the relevant
advances in understanding the physiology of fish
swimming and examines topics ranging from fishbiomechanics and migrations to the potential benefitsof swimming exercise in aquaculture resulting inchanges in fish growth and flesh quality. It brings
together both field and laboratory studies to better
understand the physiology of fish swimming with theintent to apply such findings to enhance aquaculture
practices. A chapter by Davison and Herbertsummarizes research activities and advances onswimming-enhanced growth.

ANNOTATED BIBLIOGRAPHY OF KEY
WORKSBrown, E.J., M. Bruce, S. Pether, and N.A. Herbert.
2011. Do swimming fish always grow fast?
Investigating the magnitude and physiologicalbasis of exercise-induced growth in juvenile New
Zealand yellowtail kingfish, Seriola lalandi. Fish
Physiology and Biochemistry 37: 327-336.

19

Paradigm Shift in Fish Breeding: Marker-Assisted Selection to
Genomic Selection
Akiyuki Ozaki1*, Kazuo Araki1, Jun-ya Aoki1, Yukinori Shimada1, Hiroyuki Okamoto1, Hironori Usuki1, Koichi
Okuzawa1, Kazunori Yoshida2, and Tsutomu Noda2
National Research Institute of Aquaculture, Fisheries Research Agency, 422-1, Nakatsuhamaura, Minamiisecho, Watarai-gun, Mie, 516-0193, Japan
2
Seikai National Fisheries Research Institute, Fisheries Research Agency, 122-7, Nunoura, Tamanoura-machi,
Goto-shi, Nagasaki, 853-0508, Japan
1

Corresponding author: aozaki@affrc.go.jp
Keywords: marker-assisted selection (MAS), genomic selection (GS), polygenic QTL, yellowtail (Seriola
quinqueradiata), EST-based SNPs

ABSTRACTdevelopment of the GS technology, the discovery ofmassive numbers of genetic markers (usually SNPs),and high-throughput technology to genotype animals
for thousands of SNPs in a cost-effective manner. It
is anticipated that future application of genetics andbreeding will shift to GS from MAS in aquaculture.

High density SNP arrays have become the tool ofchoice for quantitative trait locus (QTL) mapping,genome-wide association studies (GWAS), andmarker-assisted selection (MAS). The essentialconditions for DNA marker-assisted selection are 1)
development of useful resource families to evaluate
phenotypes and information about genetic linkages
and 2) a large number of polymorphic genetic markers.
Some of the cases have already reached a practicalstage and have been used in genetic improvement ofcertain species of aquaculture fish. Earlier mapping
studies have identified QTL for important commercial
traits, such as disease resistance, and combining
the resources of a high density genetic map withgenome sequence data facilitates the fine mappingof these loci. Otherwise, traditional MAS has not
resulted in widespread use of DNA information in
animal breeding. The main reason was that the traits
of interest in livestock production were much more
complex than expected; they were determined bythousands of genes with small effects on phenotype.
These effects were usually too small to be statisticallysignificant and they were ignored. In aquaculture
species, these very stringent tests result in only thelargest QTL being found. Those large QTL results were
often limited to disease resistance, including Japaneseflounder resistant to lymphocystis disease, Atlantic
salmon resistant to infectious pancreatic necrosis(IPN), and yellowtail resistant to Benedenia disease.

INTRODUCTION
Construction of genetic linkage maps andidentification of QTL are beginning to make an impact
on animal breeding by providing DNA markers linked
to QTL affecting phenotypic traits of interest. Suchmolecular markers can be used in marker-assisted
selection (MAS). The advantages of MAS, i.e., selection
based partly or fully on DNA marker genotypes, areobvious as compared with the conventional selective
breeding. MAS is especially useful for traits that are
difficult to measure or are expressed the phenotype
late in development. Implementation of MAS requires
DNA markers that are tightly linked to QTL for traits
of interest found through QTL mapping or association
studies (Lande and Thompson 1990). Ideally, the DNA
markers should be the linkage disequilibrium (LD)blocks underlying the phenotypic variation. QTL
studies in aquaculture species have covered a wide
range of traits including disease resistance, growth,stress resistance, reproduction and other traits. The
results of these studies provide a good starting point tosearch for QTL within breeding populations. However,of the QTL detected from experimental crosses, onlya small number of them have been followed up by
confirmation and fine-mapping, and the responsible
genes have not been identified. Regardless, there are
already a few applications of MAS in commercial
breeding programs in aquaculture species (Fuji et al.
2007; Moen et al. 2009; Ozaki et al. 2012).

While it might be difficult to find the largest QTL forother traits like growth and tolerance of low fish meal
feed and apply MAS, genomic selection (GS) has apossibility to improve such traits, which are dominatedby polygenic QTL. GS assumes that all markers might
be linked to a gene affecting the trait and concentrates
on estimating their total effect rather than testing
its significance. Therefore, these technologicalbreakthroughs are resulting in the current wide-spreaduse of DNA information in animal breeding: theIn aquaculture, disease resistance traits, for example, areof particular importance. In intensive culture systems,
opportunities for avoidance or escape are minimal.
Furthermore, interactions between fish and viral,
20

microbial, parasite pathogens that may be harmless
under natural conditions often result in disease problems
in aquaculture systems because of the added stress from
biological, physical and chemical factors (Wedemeyer1996). In contrast to farm animals, the animal strainsused in aquaculture are usually very recent derivatives ofwild strains (Duarte et al. 2007), and therefore have had
little time to adapt to the new disease pressures.

order to minimize genotyping error, the accuracy of
genotypes in the progeny was checked against the
male and female parental alleles. Genotype data wereconverted to a backcross format even though thegrandparent genotype was unknown. Pairwise analysis
was performed, and markers were sorted into linkage
groups at a minimum LOD threshold of 5.0. Linkage
phases were determined retrospectively by examining
the assortment of alleles among linked markers.

The yellowtail amberjack (Seriola quinqueradiata)
is, as are its relatives the gold-striped amberjack (S.
lalandi) and the greater amberjack (S. dumerili), an
important species in marine finfish aquaculture in
Japan. Production of cultured species of yellowtail
in Japan was approximately 152,800 tons in 2009,
which accounts for 59 % of marine finfish aquaculture
in Japan (MAFF Japan 2009). Yellowtail have been
cultured in southern areas of Japan using juveniles
caught from natural stocks. Although basic research on
disease, nutrition and pond management has supported
the development of the yellowtail aquaculture industry,
genetic improvement programs leading to improveyellowtail lines are only at the beginning.

ssGBLUP and ssGWAS were performed on the same
EST-based SNP data set. Software used for evaluation
included the BLUPf90 family of programs (Misztal etal. 2014).

RESULTS AND DISCUSSION
A total of 6,275 EST-based SNPs were mapped to 24
linkage groups (Fig. 1, Table 1). This map is currently
being used to map QTL for a number of commercially
important traits, giving us confidence that it will bepossible to rapidly develop domesticated yellowtail
strains, and will be used to improve the assembly of theyellowtail genome.

To move genetic improvement for yellowtail amberjack
forward, we are researching the practical applicationof selection for economically important traits basedon genetic resources available in natural populationsof yellowtail amberjack. More recently, high-density
linkage maps generated by SNP array data have provento be crucial for the accurate assembly of scaffolds andcontigs in whole-genome sequencing efforts. Highdensity SNP arrays have become the tool of choicefor QTL mapping, genome-wide association studies(GWAS), MAS and genomic selection (GS). In thisstudy, Affymetrix SNP array was used to genotype
460 samples collected across five families from a wild
population of yellowtail in coastal waters of Goto
Fukue-island. We then use those SNP data for QTL
interval mapping and a GWAS for GS.

In this study, we performed QTL analyses using five
F1 strains of yellowtail to find genetic evidence ofresistance to Benedenia disease. By using a highdensity linkage map based on SNP markers, we
identified some chromosomal regions containing QTL
that were reported in previous study (Ozaki et al. 2013).
These previous QTL and new QTL discovered here,with medium to large effects on Benedenia disease
resistance, were localized to specific linkage groups
Table 1. Numbers of EST-based SNPs in five analysis
families. A total of 6,275 EST-based SNPs were mapped to
24 linkage groups using five families. LOD threshold was
5.0. Linkge phases were determined retrospectively byexamining the assortment of alleles among linked markers.
Male and female linkage maps were created separately.

MATERIALS AND METHODS

Male
LGR-MSNPGr1
LGR-MSNPGr3
LGR-MSNPRr1
LGR-MSNPWw2
LGR-MSNPWw7

To establish an EST (expressed sequence tag) -based
SNP array, a cDNA library was generated from pooled
RNA samples extracted from 11 tissues from a single
individual. Sequencing on a Roche/454 GS FLX
platform generated 1,353,405 reads. Sequencing for
SNP identification produced 570,846 raw reads derived
from the full-length library and 456,482 raw reads
derived from the 3’-anchored library generated from500 juveniles. Quality-based variant calling using CLC
Genomics Workbench detected 9,356 putative biallelic
SNPs in 6,025 contigs, with a minor allele frequency(MAF) >25 %.

avg. of five male
SSR Buri linkage
map ver. 4.0.1
FemaleLGR-FSNPGr1
LGR-FSNPGr3
LGR-FSNPRr1
LGR-FSNPWw2
LGR-FSNPWw7

A linkage analysis was performed using application
package of LINKMFEX version 2.3. This application
can separate alleles from male or female origin. In

avg. of five female
SSR Buri linkage
map ver. 4.0.1

21

length(kosambi)
1138.5cM
1355.7cM
1106.3cM
1380.9cM
1171.2cM
except overlap
markers1230.5cM

no. of markers
1449loci
1237loci
1418loci
1362loci
1301loci

avg. of markers
0.79cM
1.10cM
0.78cM
1.01cM
0.90cM

Total 4587loci
0.27cM1224.0cM

1044loci

1.17cM

length(kosambi)
752.8cM
1036.1cM
1065.4cM
986.1cM
910.4cM
except overlap
markers
950.2cM

no. of markers
1304loci
1299loci
1352loci
1293loci
1445loci

avg. of markers
0.58cM
0.80cM
0.79cM
0.76cM
0.63cM1031.1cM

Total 4444loci
0.21cM
1042loci

0.99cM

Figure 1. Example of a SNP linkage map in yellowtail. A total of 6.275 EST-based SNPs were mapped to 24 linkage
groups. LOD threshold was 5.0. Linkage phases were determined retrospectively by examining the assortment of alleles
among linked markers.

in the analysis families (Fig. 2).
These loci were responsible for up
to 81.2 % of the total phenotypicvariation. Finding this QTL region
strongly supports the potential for
success of MAS for this disease.
GS appears to be a difficult method
when compared with a QTL study,
but it is not so different fromtraditional BLUP, wherein the A(allele) matrix is replaced with a G(genotype) matrix or H (haplotype)matrix composite of both.
The results showed SNPs withsignificant phenotypic associations
exist in certain chromosomal
regions (Fig. 3). Both interval QTL
mapping and GWAS methods haveadvantages and disadvantages,
but it is possible to use the same
SNP data with each method.
Reliability will depend on thequality of the reference sequence
data and the SNPs themselves,
which come from re-sequencing

Figure 2. Example of OTL interval mapping result within a linkage group.
Quantitative trait loci (QTL) associated with resistance to parasitic disease(Benedenia seriolae) in yellowtail. Distance along x-axis in cM.

22

Figure 3. Example gnuplot of weighted ssGWAS depicting individual SNP (opencircles) effects using the same data set associated with resistance to parasitic
disease (Benedenia seriolae) in yellowtail. SNPs are color-coded by linkage group.
Distance along x-axis in cM.

data. If sequence data continue to improve, the method
used will shift from QTL to MAS, and genetic breeding
methods will be able to shift from MAS to GS.

Ozaki, A., K. Yoshida, K. Fuji, S. Kubota, W. Kai, J.Y.
Aoki, Y. Kawabata, J. Suzuki, K. Akita, T. Koyama,
M. Nakagawa, T. Hotta, T. Tsuzaki, N. Okamoto,K. Araki, and T. Sakamoto. 2013. Quantitative
trait loci (QTL) associated with resistance toa monogenean parasite (Benedenia seriolae)
in yellowtail (Seriola quinqueradiata) throughgenome wide analysis. PLoS One 8(6): e64987.
Wedemeyer, G. 1996. Physiology of fish in intensive
culture systems. London: Chapman & Hall.

REFERENCES
Duarte, C.M., N. Marba, and M. Holmer. 2007. Rapid
domestication of marine species. Science 316: 383383.
Fuji, K., O. Hasegawa, K. Honda, K. Kumasaka, T.
Sakamoto, and N. Okamoto. 2007. Markerassisted breeding of a lymphocystis diseaseresistant Japanese flounder (Paralichthys
olivaceus). Aquaculture 272: 291–295.
Lande, R., and R. Thompson. 1990. Efficiency ofmarker-assisted selection in the improvement of
quantitative traits. Genetics 124: 743–756.
MAFF Japan. 2009. Ministry of Agriculture. Forestry
and Fisheries. Annual Statistics of Fishery and
Aquaculture Production. Statistics Department.
(in Japanese)
Misztal, I., S. Tsuruta, D. Lourenco, Y. Masuda, I.
Aguilar, A. Legarra, and Z. Vitezica. 2014. Manualfor BLUPF90 family of programs. http://nce.ads.
uga.edu/html/projects/programs/
Moen, T., M. Baranski., A.K. Sonesson, and S.
Kjoglum. 2009. Confirmation and fine-mappingof a major QTL for resistance to infectious
pancreatic necrosis in Atlantic salmon (Salmosalar) population-level associations between
markers and trait. BMC Genomics 10: 368.
Ozaki, A., K. Araki, H. Okamoto, et al. 2012. Progressof DNA marker-assisted breeding in maricultured
finfish. Bulletin of Fisheries Research Agency 35:
31–37.

ANNOTATED BIBLIOGRAPHY OF KEY
WORKSFuji, K., O. Hasegawa, K. Honda, K. Kumasaka, T.
Sakamoto, and N. Okamoto. 2007. Markerassisted breeding of a lymphocystis diseaseresistant Japanese flounder (Paralichthys
olivaceus). Aquaculture 272: 291–295.
An allele of a microsatellite, Poli9-8TUF, has adominant effect at a single major locus and is
responsible for resistance to lymphocystis disease(LD-R) in Japanese flounder. We developed a new
population of Japanese flounder produced by marker
assisted breeding using this allele. A female thatoriginated from the KP-B inbred line with LD-R thatwas homozygous for the favorable allele (B-favorable)
and a male from a commercial stock bred for higher
growth rate and good body shape were selected asparents. A female was selected as the LD-R-bearing
parent because the recombination rate of females islower in the region where the LD-R locus is located.
As expected, the B-favorable allele was transmitted as aheterozygote to the progeny (LD-R+ population). The
23

LD-R+ population, when tested at two commercial fish
farms that had LD outbreaks, showed no incidence of
LD at either farm, while a control population without
B-favorable alleles (LD-R−) had incidences of 4.5%
and 6.3% at the two farms. These results show thatmarker-assisted breeding using molecular markers
linked to an economically important trait is an efficient
strategy for breeding.

Benedenia infections caused by the monogenean
fluke ectoparasite Benedenia seriolae seriously impact
marine finfish aquaculture. Genetic variation in thehost has been inferred to play a significant role indetermining the susceptibility to this parasitic disease.
To evaluate the genetic basis of Benedenia disease
resistance in yellowtail (Seriola quinqueradiata), a
genome-wide and chromosome-wide linkage analyses
were initiated using F1 yellowtail families (n = 90 per
family) based on a high density linkage map with 860
microsatellite and 142 single nucleotide polymorphism(SNP) markers. Two major quantitative trait loci
(QTL) regions on linkage groups Squ2 (BDR-1) andSqu20 (BDR-2) were identified. These QTL regions
explained 32.9–35.5% of the phenotypic variance.
On the other hand, the relationship between QTL
for susceptibility to B. seriolae and QTL for fish bodysize were investigated. The QTL related to growth
was found on another linkage group (Squ7). As aresult, the authors present first genetic evidence that
contributes to detailing phenotypic resistance to
Benedenia disease, and the results will help resolve themechanism of resistance to this important parasitic
infection of yellowtail.

Moen, T., Baranski, M., Sonesson, A.K. and Kjoglum,
S. (2009) Confirmation and fine-mapping of amajor QTL for resistance to infectious pancreatic
necrosis in Atlantic salmon (Salmo salar):population-level associations between markers
and trait. BMC Genomics 10, 368.
Infectious pancreatic necrosis (IPN) is one of the mostprevalent and economically devastating diseases inAtlantic salmon (Salmo salar) farming worldwide. The
disease causes large mortalities at both the fry- andpost-smolt stages. Family selection for increased IPN
resistance is performed through the use of controlled
challenge tests, where survival rates of sib-groups arerecorded. However, since challenge-tested animals
cannot be used as breeding candidates, within family
selection is not performed and only half of thegenetic variation for IPN resistance is being exploited.
DNA markers linked to quantitative trait loci (QTL)
affecting IPN resistance would therefore be a powerfulselection tool. The aim of this study was to identify andfine-map QTL for IPN-resistance in Atlantic salmon
for use in marker-assisted selection to increase therate of genetic improvement for this trait. The QTL
confirmed in this study represents a case of a major
gene explaining the bulk of genetic variation for apresumed complex trait. QTL genotypes were deduced
within most parents of the 2005 generation of a major
breeding company, providing a solid framework forlinkage-based MAS within the whole populationin subsequent generations. Since haplotype-trait
associations valid at the population level were found,
there is also a potential for MAS based on linkage
disequilibrium (LD). However, in order to use MAS
across many generations without reassessment oflinkage phases between markers and the underlying
polymorphism, the QTL needs to be positioned witheven greater accuracy. This will require higher marker
densities than are currently available.

Meuwissen, T.H., B.J. Hayes, and M.E. Goddard. 2001.
Prediction of total genetic value using genome-wide
dense marker maps. Genetics 157(4): 1819-1829.
Recent advances in molecular genetic techniques will
make dense marker maps available and genotyping
many individuals for these markers feasible. Here,
we attempted to estimate the effects of approximately
50,000 marker haplotypes simultaneously from alimited number of phenotypic records. A genomeof 1000 cM was simulated with a marker spacing of
1 cM. The markers surrounding every 1-cM region
were combined into marker haplotypes. Due to finite
population size N(e) = 100, the marker haplotypes
were in linkage disequilibrium with the QTL locatedbetween the markers. Using least squares, all haplotype
effects could not be estimated simultaneously. When
only the biggest effects were included, they were
overestimated and the accuracy of predicting genetic
values of the offspring of the recorded animals was
only 0.32. Best linear unbiased prediction of haplotype
effects assumed equal variances associated to each 1-cM
chromosomal segment, which yielded an accuracyof 0.73, although this assumption was far from true.
Bayesian methods that assumed a prior distributionof the variance associated with each chromosome
segment increased this accuracy to 0.85, even when theprior was not correct. It was concluded that selection
on genetic values predicted from markers could
substantially increase the rate of genetic gain in animals
and plants, especially if combined with reproductive
techniques to shorten the generation interval.

Ozaki, A., K. Yoshida, K. Fuji, S. Kubota, W. Kai, J.Y.
Aoki, Y. Kawabata, J. Suzuki, K. Akita, T. Koyama,
M. Nakagawa, T. Hotta, T. Tsuzaki, N. Okamoto,K. Araki, and T. Sakamoto. 2013. Quantitative
trait loci (QTL) associated with resistance toa monogenean parasite (Benedenia seriolae)
in yellowtail (Seriola quinqueradiata) throughgenome wide analysis. PLoS One 8(6): e64987.

24

Genomic Analyses to Inform Sablefish Aquaculture Research
Krista M. Nichols1*, Andrew Jasonowicz2, Giles Goetz3, J. Adam Luckenbach3, and Frederick W. Goetz2
Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, NOAA,
Seattle, WA
2Environmental and Fisheries Sciences Division, Northwest Fisheries Science Center, National Marine FisheriesService, Manchester Research Station, NOAA, Manchester, WA
3
Environmental and Fisheries Sciences Division, Northwest Fisheries Science Center, National Marine FisheriesService, NOAA, Seattle, WA
1Corresponding author: krista.nichols@noaa.gov
Keywords: Not available.

ABSTRACTANNOTATED BIBLIOGRAPHY OF KEY
WORKS

The marine fish species, sablefish (Anoplopoma
fimbria, black cod), are long-lived, migratory species
native to the west coast of the U.S. Sablefish is an ideal
species for aquaculture because of their high market
value and fast growth in culture. The development of
the species for aquaculture will benefit from genomic
technologies for a number of objectives, including:1) an understanding of the genetic stock structurein the wild, from which progenitor broodstock isdeveloped, 2) an understanding of the genetic basis ofimportant production traits, and 3) the developmentof comprehensive genotyping assays for screening
sablefish in culture. We discuss in this presentation ourfindings of genetic stock structure in wild populations,and future directions in genome sequencing andgenomics of quantitative traits. Using Restriction Site
Associated DNA sequencing (RADseq), we identified
more than 100,000 SNPs in >400 individuals collectedfrom a U.S. West Coast surveys from the Bering
Sea in Alaska to southern California. After filtering
for genetic analyses, 2661 SNPs were used to assess
population structure and test for signatures of natural
selection and association with environmental variables.
Our results show a lack of population structure andadaptive variation in Sablefish, and are suggestiveof a single panmictic population that is likely the
result of a complex juvenile life history and longrange movements as adults. Our current studies now
focus on understanding the genetic basis of sexuallydimorphic growth in Sablefish, and the development ofa refined genome assembly to provide a reference forgenomic studies in this species.

Jasonowicz, A.J., F.W. Goetz, G.W. Goetz, andK.M. Nichols. 2017. Love the one you’re with:genomic evidence of panmixia in the sablefish(Anoplopoma fimbria). Canadian Journal of
Fisheries and Aquatic Sciences 74(3): 377-387.
This study examines genetic stock structure in
Sablefish along the U.S. West Coast and Alaska
using RADseq, and finds no evidence for populationdifferentiation.
Luckenbach, J.A., and W.T. Fairgreve. 2016. Gonadal
sex differentiation and effects of dietary
methyltestosterone treatment in Sablefish(Anoplopoma fimbria). Fish Physiology andBiochemistry 42: 233-248.
An important characterization of sex differentiation in
Sablefish, and identification of the developmental time
period sensitive to sex reversal by dietary testosterone.
Rondeau, E.B., A.M. Messmer, D.S. Sanderson, S.G.
Jantzen, K.R. von Schalburg, , D.R. Minkley, J.S.
Leong, G.M. Macdonald, A.E. Davidsen, W.A.
Parker, R.S. Mazzola, B. Campbell, and B.F. Koop.
2013. Genomics of sablefish (Anoplopoma fimbria):
expressed genes, mitochondrial phylogeny, linkage
map, and identification of a putative sex gene.
BMC Genomics 14: 452.
An important paper providing evidence for thesablefish sex determining gene, which will be
important in understanding genetic sex control insablefish. This paper also provides the first draft
genome sequence that we are currently improving
with additional sequence data, and provides the firstcomprehensive genomic resource for this fish species.

25

Mutagenesis and Genome Editing for Aquaculture Fish Species:
Modification of SCPP Genes in Tiger Pufferfish (Takifugu rubripes)
Hiroyuki Okamoto1*, Takashi Ishikawa1, Wataru Kai2, Issei Nishiki2, Yuki Iwasaki2, Kenta Kishimoto3, Yu
Murakami3, Masato Kinoshita3, and Atushi Fujiwara2
National Research Institute of Aquaculture, Japan Fisheries Research and Education Agency (FRA), 422-1
Nakatsuhamaura, Minami-Ise, Mie, 516-0193, Japan
2
National Research Institute of Fisheries Science, Japan Fisheries Research and Education Agency (FRA),
Yokohama, Kanagawa, 236-8648, Japan
3
Kyoto University, Kitashirakawa-Oiwakecho, Sakyo-ku, Kyoto, Kyoto, 606-8502, Japan
1

Corresponding author: hiokamot@affrc.go.jp
Keywords: mutagenesis, TILLING, genome editing, CRISPR/Cas, tiger pufferfish (Takifugu rubripes)

ABSTRACT

successes in aquaculture. TILLING has been applied
to experimental fish such as zebrafish and medaka. In
these instances, researchers have subjected adult fish
to a bath of strong alkylating agents (e.g., N-ethylN-nitrosourea (ENU)). Exposure to the chemicalmutagen induces single nucleotide substitutions in the
genomes of all cells but particularly in the gametes.
Because the body size of most intensively cultured
food fish is much larger than these experimental
species, it is not practical to use whole-body bathsof ENU solution. To address this, methods havebeen developed to induce mutagenesis by soaking
eggs or sperm in ENU solution or injecting ENU
solution into the abdominal cavity of ripe males. The
single nucleotide substitution mutation will induce:
1) inhibition of gene function by generation of stopcodons in protein coding regions, 2) reduction/
modification of protein function by amino acidsubstitution, 3) increase/decrease of the gene
expression amount due to mutation of the expression
regulatory region. As such, it is one technique used
for functional analysis of genes. It has been reported
that mutant individuals doubled the muscle content
of grass carp in China in 2011 (Jiang et al. 2011), andthe utilization of mutation breeding technology in theworld had begun.

There is increasing interest in manipulating thefunction of target genes to achieve production gains
not only in agriculture but also in aquaculture.
Of these, the two primary methods are chemicalmutagenesis, including TILLING and genome
editing. In order to reduce the need for performing
a tooth cutting procedure to prevent mutual bitingin tiger puffer farming, we developed the basic
technology for creating individuals whose functionof nine SCPP genes involved in tooth formation
was suppressed. We comprehensively searched formutants in the genes of about 850 progeny of amutagenesis (TILLING) treatment male, but mutants
with the suppressed function were not obtained. On
the other hand, by genomic editing technology, we
succeeded in producing pufferfish with mutations in
one of the SCPP genes, and analysis using the variant
homozygote individuals is expected in the future.

INTRODUCTION
Mutation breeding has been used in the agricultural
field since the first half of the 20th century, and varietiesthat have been produced of rice, barley, cotton and soon have been put to practical use worldwide. For a longtime in the field of fish farming, this method was limited
to technical research testing, and practical application
was hardly done. Although transgenic techniques are
not often used, there are several alternatives.

Whereas chemical mutagens induce genome-wide
random mutations, artificial nuclease for genome
editing technology can target mutations to a specificlocus with random-length deletion or specificnucleotide sequence replacement. The mutationinduction ratio has been greatly improved using
genome editing technologies like ZFN, TALEN or
CRISPR, which is a mutation inducing technique fora specific gene, and fruitful results are being reported
even in experimental fish (Ansai et al. 2012). Thesemethods are attracting worldwide attention as a new
breeding technology (NBT).

In recent years, a technique called TILLING (Targeting
Induced Local Lesions In Genomes) was developed
to introduce a genetic saturation mutation (single
nucleotide mutation) into fish sperm with a chemicalmutagen; specific gene mutant individuals from amutant population are then found by nucleotide
sequence analysis (Wienholds et al. 2002; Taniguchi
et al. 2006). Chemical mutagenesis has been widelyused in agriculture, but there have been few reported
26

Figure 2. Production of a tiger pufferfish mutant population.
Figure 1. Teeth of tiger pufferfish.

Detection of Mutated Bases on SCPP genes

In tiger puffer farming, it is necessary to perform
a tooth cutting operation to prevent a decrease incommercial value due to a loss of fin or mortality bymutual biting (Fig. 1). However, since tooth cutting isvery hard work for fish farmers and stressful for fish,measures to reduce labor are desired. Teeth of teleostfish and mammalian teeth have the hardest substancesin their outermost layers, such as enameloids (teleostfishes) and enamel (mammals). They are functionallyand morphologically similar structures. However, thecrystal structures of both were thought to be different
from each other because the connective tissues fromwhich they are derived are different (Kogaya andIwaku 2004). Thus, the teeth of teleost fishes andmammals might be morphologically and functionallysimilar but evolved separately (parallel evolution).
However, in 2005, the secretory calcium-binding
phosphoprotein (SCPP) was clarified as a gene groupinvolved in the formation of teeth in tiger pufferfish(Takifugu rubripes) (Kawasaki et al. 2005), andmolecular evolutionary analysis revealed that the SCPP
gene is a major gene group related to universal teeth
mineralization in vertebrate teeth evolution (Kawasaki
and Weiss 2008).

For each of the nine secreted calcium-binding
phosphoprotein SCPP genes, 48 regions (about 200
bp per region) from the 5 ‘ upstream were chosen,
including SPARC (Exons 2, 3, 4, 5, 6: 445 bases),
SPARCL1 (Exons 2, 3, 4: 1145 bases), SCPP1 (Exons 2,
3, 4, 5, 6, 7, 8, 9: 480 bases), SCPP2 (Exon 2, 3, 4, 5,
6, 7, 8: 661 bases), SCPP3A (Exons 2, 3, 4: 259 bases),
SCPP3B (Exons 2, 3, 4: 289 bases), SCPP3C Exons 2,
3, 4: 277 bases), SCPP4 (Exons 2, 3, 4, 5, 6: 741 bases),
SCPP5 (Exons 2, 3, 4, 5, 6, 7 + 8: 409 bases), and 48
pairs of sequence-specific amplification primers were
designed (Fig. 3).
Four genomic DNAs extracted from each individual
were pooled, and the 48 amplicons (4,706 bases total)
were attached to a sample identification adapter using
a multi-amplicon production system, Access ArrayTM(Fluidigm). For each amplicon, nucleotide sequence
data was acquired using the next generation sequencer,
Ion PGM ™ (Thermo Fisher Scientific). The data wasanalyzed (mutation screening) using genome analysis
software, CLC genomics workbench (Filgen), to
identify mutated amino acids and to select mutants.

MATERIALS AND METHODS

Obtaining Sperm and Eggs of Tiger Pufferfish
for Genome Editing

Production of the Tiger Pufferfish Mutant
Population

In order to obtain fertilized eggs necessary for genome
editing for tiger pufferfish, we transferred unfertilized
eggs and semen from the Mie Prefectural Fish Farming
Center in Owase City to Tamaki Station FRA in
Tamaki Town. We got fertilized eggs by artificial
insemination. In addition, in Kamiura Station, early
artificial maturation tests were conducted on one maleand three females to obtain eggs in between January
and March. The obtained eggs were used for the
genome editing test.

The following tests were conducted on the creationand selection of functionally deficient individuals for
the SCPP gene using the mutation method, TILLING.
The genomic DNA was extracted from each individual
in a mutant population of about 850 fish produced
using frozen sperm derived from male tiger pufferfish
treated with the chemical mutagen, ENU (Kuroyanagi
et al. 2013) (Fig. 2).

27

Figure 3. Nucleotide sequence region (blue) of nine SCPP genes mutated by next generation
sequencing.

RESULTS AND DISCUSSION

Production of Base Deficient Individuals of
SCPP Genes

Detection of Mutated Bases in SCPP Genesby Next Generation Sequencing

The following tests were conducted on the creationand selection of individuals with deficient SCPP
genes using the genome editing systems TALEN
or CRISPR. TALEN or CRISPR/Cas, which can
specifically inhibit the function of any target genes,
were used. For TALEN, RNAs were synthesized by
mMESSAGE mMACHINE (SP6) (Thermo Fisher
Scientific) using TALEN A and B pair plasmids
against the SPARCL1 gene donated from Hiroshima
University. For designing guide RNA targeting thenucleotide sequences of SCPPs 1, 2, 3A, 3B, 3C, 4,
and 5, SPARC and SPARCL1 genes used in CRISPR,
a free design tool (https: / /wwws.blueheronbio.com/
external/tools/gRNASrc.jsp) was used. The designed
crRNA was synthesized with tracrRNA by Fasmac.
For DNA cleavage enzyme Cas9, pCS2 + hspCas9(Addgene) plasmid DNA was digested with NotI,
and the RNA was synthesized using mMESSAGE
mMACHINE (SP6). The crRNA, tracrRNA, and Cas9
RNA were adjusted to concentrations of 33, 67, and
200 ng/μl, respectively, and microinjected into eachfertilized egg. Mutant individuals were confirmed byheteroduplex mobility assay (HMA) analysis using
MultiNa (Shimadzu). In some eggs, RNA synthesizedfrom pCS2mt-GFP (Addgene) was co-injectedwith CRISPR/Cas9 RNA for SCPP to monitor gene
expression into embryoid bodies.

The genomic DNA sequence of the parent fish wasused as a reference sequence to detect mutated basesin the mutant population. Mutations in the genomic
DNA of the mutant population having an occurrence
frequency of 5 % or less when compared to the parent
sequence were regarded as sequencing error, and thoseexhibiting frequencies of 10 % or more must be errors
other than mutagenesis. As a result of removing thein/del sites from the analysis data, nine mutations
without amino acid substitutions (synonymous) were
found in four genes, SCPP2, SCPP3A, SCPP3C andSPARC (Fig. 4), and five mutations with amino acidsubstitutions (non-synonymous) were found in two
genes (SCPP3A: one site, SCPP3C: four sites). In thelatter cases, cysteine ​​was mutated to tryptophan in
SCPP3A and threonine was mutated to alanine (threesites) or isoleucine (one site) in SCPP3C. No stop
mutation was found in any of the genes. As a result of
this analysis, the mutation introduction rate detectedin the genomic region of the SCPP gene group was
0.0004%, which was lower than the initial expectation
about 0.4% obtained with other genes so far. For thisreason, we speculate that the SCPP gene may be in agenomic region where mutation induction is difficult.
28

Figure 4. Mutation points detected in SCPP gene.

Artificial Early Maturation Induction of Tiger
Pufferfish

It was also clear that the above amino acid mutant
types were supposed to be heterozygous and did nothave a large influence on the teeth formation, since nosingle individual with incomplete tooth formation wasobserved in this test group. Possible reasons are thatthese mutations of the SCPP gene might be recessive or
the mutations do not affect gene expression or proteinfunction. It was also considered that a wild type SCPP
gene might be responsible for compensating for any
reduced function in the mutant SCPP.

In order to increase the chances of microinjection,
we tried early maturation of tiger pufferfish. In midNovember, a tank of pufferfish was cooled from 20 °C
to 15 °C over 10 days at -0.5 °C/day, then maintained at
15 °C for 16 days. Later, the temperature was increased
0.5 °C every two weeks starting at the beginning ofDecember, and then maintained at 17 °C from earlyFebruary. The day length was natural day length. In
early March, egg diameter was confirmed by cannulain three females at about 800-1,000 μm. When fish
were injected one to two times with 2,500 IU of
human chorionic gonadotropin for each 4-5 kg bodyweight, ovulation was observed four days after the
first injection, with an initial egg diameter of 1,034
μm; 12 days after injection at 936 μm; and 23 days
after injection at 857 μm. For each individual, the egg
collection period was not stable, but it indicated thepossibility to take eggs about 1-2 months early from all
three fish, which will provide us more opportunities
for microinjection.

Transportation and Microinjection Testing ofTiger Pufferfish Eggs
To ensure that microinjection opportunities occurred
more than once in a year, we were donated tiger
pufferfish unfertilized eggs from Mie Prefectural Fish
Farming Center in Owase City. However, prior to
conducting the genome editing test, we first needed
to investigate whether transporting the eggs to the
Tamaki Station near our institute from Owase Stationin the Mie Prefectural Center for one hour by car,followed by microinjection after artificial insemination,
were possible. It was found that hatching larvae can beobtained after artificial insemination of unfertilized
eggs maintained at a water temperature of 17 °C for as
long as three to seven hours after spawning. Hatchinglarvae were obtained without problem even after
microinjection was carried out after one additional
hour. At 48 hours after fertilization, the survival rate
was 80-90 % as judged by methylene blue staining
pattern. Even when eggs two or three days after
fertilization were transported by car at 17.3-17.8 °C, thesurvival rate was 90 %, as also judged by methylene
blue staining, with 51.6 % GFP signal positive
individuals (n = 281). From these results, it was clearthat the genome editing test would be possible tocarry out even when receiving and transporting tiger
pufferfish unfertilized eggs from a remote place.

Production of Tiger Pufferfish Individuals with
Mutant SCPP Genes by Genome Editing
Since it was not possible to create mutants by TILLING
mutagenesis, we attempted to create mutants by
TALEN, one of the genome editing techniques.
TALEN-RNAs, SPARCL1-TALEN-A and B pairs for the
SPARLCL1 gene, a member of SCPP gene family, weremicroinjected in fertilized eggs artificially inseminatedat the Tamaki Station using the transported eggs fromthe Owase Station. Screening for mutant individuals
was performed by HMA analysis. Mutagenizedindividuals were searched for in approximately 80
hatching fish, but no characteristic mutational band
shift was observed, and mutants could not be obtained.
29However, the TALENs were confirmed to have DNA
cleavage activity in cultured cells, so it was unclear whymutants could not be obtained.

of the genes involved. Eventually, we expect a
reduction in the amount of tooth cutting work neededin future puffer farming as a result of this research.

Since the molecular weight of RNA used in CRISPR/
Cas is smaller than that used in TALEN, RNA for
many genes can be edited and microinjected into
one egg at the same time. Therefore, CRISPR/Cas
can perform efficiently with less laboratory materials
and breeding spaces. In order to carry out genome
editing by CRISPR/Cas, necessary guide RNA wasdesigned and synthesized for nine kinds of SCPP
genes. Microinjection was performed on fertilized eggs
for each of 12 guide RNAs, and mutagenic activity wasinvestigated. DNA was extracted from the egg two days
after fertilization and HMA analysis was performedon the amplicon DNA of each gene. The cleavage
activity of each guide RNA was strong for SCPP3A- 2, 3B - 1, 3B - 2, 3C - 1, and 4 and SPARC but weakfor SCPP1, 2, 3A - 1, 3C - 2, and 5 and SPARCL1. A
guide to SCPP5 – chosen because it is one of the genes
expressed in various tissues during teeth development– and artificial nuclease RNA were microinjected into
approximately 500 fertilized eggs. The developing
ratio immediately before hatching was 35.5 %, and50 mutant candidate juveniles were obtained at twomonths of age after hatching. Pit tags were installed ata body length of 5-7 cm in seven mutant individuals
obtained by the HMA method (Fig. 5). We visuallychecked the external form of the tooth, but clear
morphological defect was not observed.

Genome editing is preferred when genes or candidate
genes that are associated with desirable traits havebeen identified. In the absence of this information, or
if there is a need to survey for alternative phenotypes,
chemical mutagenesis is the preferred method. To
date, few candidate genes have been identified forcommercially important traits such as growth, disease
resistance, and food conversion efficiency. This isbecause such traits are controlled by complex gene
networks, with each gene having a very small effectindividually. It is expected that improvements in our
understanding of gene functions related to commercial
traits could be made by further investment inmutagenesis and gene editing research.

ACKNOWLEDGMENTS
We thank Dr. Takashi Yamamoto and Dr. Tetsushi
Sakuma at Hiroshima University for giving our team
the TALEN plasmid and Kazuhiro Okada, Tohru
Kasuya, Shouhei Sugiyama and their colleagues in the
Mie Prefectural Fish Farming Center for their kind
donation of tiger pufferfish sperm and eggs in part.
We also thank Dr. Koichi Okuzawa and Dr. Hironori
Usuki for valuable comments, and Naomi Yamasaki,
Hideyuki Fujita, Takeshi Taguchi, Tomoyo Nozaki,
Akemi Nakanishi Yukinori Shimada and Toshiya
Yamaguchi for their assistance with our research.
This work was supported in part by Grants-in-Aid
for Scientific Research from Fisheries Research and
Education Agency of Japan and JSPS KAKENHI Grant
Number JP26450273.

In the obtained genome edited F0 individuals, we
suspect that the heterozygous mutation was introducedin the somatic tissues as a mosaic, so any functional
deficiency was considered to be limited. It is necessary
to create subsequent generations of F1 and F2
individuals to evaluate the formation of teeth in whole
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species and also genetic breeding of microorganisms
and crops, the application of the mutagenesis in fish
breeding has been only rarely reported.

Results: In this study, we developed the TILLING
method in fugu with ENU mutagenesis and highresolution melting (HRM) analysis to detect base
ANNOTATED BIBLIOGRAPHY OF KEY
pair changes in target sequences. Fugu males were
WORKS
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(F1). The fertilization and the hatching ratios weresimilar to those of the control and did not reveal a
Clustered regularly interspaced short palindromic
dose dependency of ENU. Genomic DNA from therepeats (CRISPR)/CRISPR-associated (Cas) systemharvested F1 offspring was used for the HRM analysis.
based RNA-guided endonuclease (RGEN) has recently To obtain a fish exhibiting a useful phenotype (e.g. highemerged as a simple and efficient tool for targetedmeat production and rapid growth), fugu myostatin
genome editing. In this study, we showed successful(Mstn) gene was examined as a target gene, because
targeted mutagenesis using RGENs in medaka, Oryzias it has been clarified that the mstn deficient medaka
latipes. Somatic and heritable mutations were induced
exhibited double-muscle phenotype in common with
with high efficiency at the targeted genomic sequence
MSTN knockout mice and bovine MSTN mutant.
on the DJ-1 gene in embryos that had been injected
As a result, ten types of ENU-induced mutations
with the single guide RNA (sgRNA) transcribed by a T7 were identified including a nonsense mutation in the
promoter and capped RNA encoding a Cas9 nuclease.
investigated region with HRM analysis. In addition, theThe sgRNAs that were designed for the target genomic
average mutation frequency in fugu Mstn gene was 1
sequences without the 5′ end of GG required by the T7 mutant per 297 kb, which is similar to values calculated
promoter induced the targeted mutations. This suggests for zebrafish and medaka TILLING libraries.
that the RGEN can target any sequence adjacent toan NGG protospacer adjacent motif (PAM) sequence,
which occurs once every 8 bp. The off-target alterations Conclusions: These results demonstrate that the
TILLING method in fugu was established. We anticipate
at 2 genomic loci harboring double mismatches in thethat this TILLING approach can be used to generate a
18-bp targeting sequences were induced in the RGENwide range of mutant alleles, and be applicable to many
injected embryos. However, we also found that thefarmed fish that can be chemically mutagenized.
off-target effects could be reduced by lower dosagesof sgRNA. Taken together, our results suggest that
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Background: In fish breeding, it is essential to discover for 45 min, and then wild-type eggs were fertilized.
The results indicated that the proportion of embryos
and generate fish exhibiting an effective phenotype
with morphological abnormalities at segmentation
for the aquaculture industry, but screening for natural
stage or dead fry at hatching stage increased withmutants by only depending on natural spontaneous
increasing ENU dose up to 10 mM. Choosing a dosemutations is limited. Presently, reverse genetics hasthat was mutagenic, but provided adequate numbers
become an important tool to generate mutants, whichof viable fry, an F1 population was generated from 1
exhibit the phenotype caused by inactivation of amM ENU-treated sperm for screening purposes. The
gene. TILLING (Targeting Induced Local Lesions IN
ENU-treated F1 population showed large variations in
Genomes) is a reverse genetics strategy that combines
31

growth during the first year. A few bigger mutants withmorphologically normal were generated, as comparedto the controls. Analysis of DNA from 15 F1 ENUtreated individuals for mutations in partial coding
regions of igf-2a, igf-2b, mstn-1, mstn-2, fst-1and fst-2
loci revealed that most ENU-treated point mutations
were GC to AT or AT to GC substitution, which
led to nonsense, nonsynonymous and synonymous
mutations. The average mutation rate at the examinedloci was 0.41%. These results indicate that ENU
treatment of mature sperm can efficiently induce point
mutations in grass carp, which is a potentially usefulapproach for genetic improvement of these fish.

Russell, W. L., L. B. Russell, and E. M. Kelly. 1958.
Radiation dose rate and mutation frequency.
Science 128(3338): 1546-1550.

New data have clearly confirmed the earlier findingthat specific locus mutation rates obtained withchronic gamma irradiation of spermatogonia arelower than those obtained with acute x-rays. Since thisresult is in contrast to classical findings for Drosophila
spermatozoa, and apparently contradicts one of thebasic tenets of radiation genetics, it was important
to determine what factors were responsible for it.
Experiments undertaken for this purpose reveal thefollowing: (i) the lower mutation frequency is due
Russell, W. L., P. R. Hunsicker, D. A. Carpenter, C. V.
mainly to difference in dose rate of radiation, rather
Cornett, and G. M. Guinn. 1989. Effect of dosethan quality; (ii) a dose-rate effect is not obtained in
fractionation on the ethylnitrosourea induction of experiments with mouse spermatozoa, confirming
specific-locus mutations in mouse spermatogonia. classical findings for spermatozoa, and indicating
Proceedings of the National Academy of Sciencesthat the explanation for intensity dependence inof the USA 79: 3592-3593.
spermatogonia resides in some characteristic ofgametogenic stage; and (iii) a dose-rate effect isfound not only in spermatogonia but also in oocytes,
As measured by specific-locus mutations in mousewhere cell selection is improbable, indicating thatspermatogonia, fractionating a dose of 100 mg of
the radiation intensity effect is on the mutation
ethylnitrosourea per kg of body weight into doses ofprocess itself. A threshold response for all mutations
10 mg/kg injected intraperitoneally at weekly intervals
in spermatogonia and oocytes is not a necessary
greatly reduces the mutation frequency compared withconsequence of the findings. Plausible hypotheses
that from a single dose of 100 mg/kg. Because there isconsistent with the present results can lead to otherindependent evidence that the doses of 10 and 100 mg/
kg reach the germ cells in amounts directly proportional predictions. From a practical point of view, the results
indicate that the genetic hazards, at least under someto the injected dose, the lower mutational responseradiation conditions, may not be as great as thosewith the fractionated dose is attributed to repair. The
induced mutation rate expected from a single 10-mg/kg estimated from the mutation rates obtained withacute irradiation. However, it should not be forgotten
dose (on the assumption that this would be 1/10th therate observed after 10 such doses) would be only 75% of that even the lower mutation rates obtained with thepresent intensity levels are still appreciable (16).
the spontaneous mutation rate. Mouse spermatogonia
apparently have an efficient repair system that is
effective even against a potent mutagen.

32

Genome-enabled Selection Doubles the Accuracy of Predicted Breeding
Values for Bacterial Cold Water Disease Resistance Compared to
Traditional Family-based Selection in Rainbow Trout Aquaculture
Roger L. Vallejo1*, Timothy D. Leeds1, Guangtu Gao1, James E. Parsons2, Kyle E. Martin2, Jason P. Evenhuis1, Breno
O. Fragomeni3, Gregory D. Wiens1, and Yniv Palti1
National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States
Department of Agriculture, Kearneysville, WV, USA
2
Troutlodge, Inc., P.O. Box 1290, Sumner, WA, USA
3
Animal and Dairy Science Department, University of Georgia, Athens, GA, USA
1

Corresponding author: roger.vallejo@ars.usda.gov
Keywords: aquaculture; genomic selection; disease resistance; bacterial cold water disease; rainbow trout

ABSTRACTINTRODUCTION

We have shown previously that bacterial cold water
disease (BCWD) resistance in rainbow trout can be
improved using traditional family-based selection, but
progress has been limited to exploiting only betweenfamily genetic variation. Genomic selection (GS) is a newalternative enabling exploitation of within-family genetic
variation. We compared three GS models to predictgenomic-enabled breeding values (GEBVs) for BCWD
resistance in a commercial rainbow trout populationand compared the accuracy of GEBVs to traditional
breeding values (EBVs) estimated with a pedigree-based
BLUP model. For these comparisons, we used BCWD
survival phenotypes recorded on 7893 training fish from102 families, from which 1473 fish from 50 families had
genotypes (57K SNP array). Naïve siblings of the training
fish (n = 930 testing fish) were genotyped to predict
their GEBVs, of which 193 were mated to produce
138 progeny testing families (PTFs). In the following
generation, 9968 progeny from the PTFs were BCWD
phenotyped to empirically assess the accuracy of GEBV
predictions made on their non-phenotyped parents.
The accuracy of GEBVs from all three GS models were
substantially higher than the BLUP model EBVs, with
the increase in accuracy ranging from 83.3% to 108.8%
depending on the GS model and survival phenotype
used. Reducing the training sample size to n = ~1000
had no negative impact on the accuracy (0.67−0.72),
but with n = ~500, the accuracy dropped to 0.53−0.61,
if the training and testing fish were full-sibs, and evensubstantially lower to 0.22−0.25 when they were notfull-sibs. Thus, using progeny performance data, we haveshown that the accuracy of genomic predictions with
GS models (0.63−0.71) is substantially higher than the
traditional pedigree-based BLUP model (0.34−0.36). We
also found that using a much smaller training sample
size compared to similar studies in livestock, GS cansubstantially improve the selection accuracy and genetic
gains for BCWD resistance in commercial rainbow trout
aquaculture.

Bacterial cold water disease (BCWD) causes
significant mortality and economic losses in salmonid
aquaculture, and methods to control outbreaks arelimited (Nematollahi et al. 2003; Barnes and Brown
2011). We previously reported a family-based, selective
breeding program (Silverstein et al. 2009), with theobjective of increasing rainbow trout resistance against
Flavobacterium psychrophilum (Fp), the etiologicalagent of BCWD. Resistance to laboratory injection
challenge with Fp strain CSF259-93 is a moderately
heritable trait that responds to selection (Leeds et al.
2010). The genetic architecture of resistance is complex(Vallejo et al. 2010) and we previously identified several
major resistance QTL in the NCCCWA odd- and evenyear rainbow trout selective-breeding populations(Wiens et al. 2013; Vallejo et al. 2014; Liu et al. 2015a;
Palti et al. 2015b). While those loci can be evaluatedfor marker assisted selection (MAS) following finemapping, the complex genetic architecture of BCWD
resistance and high genetic variation we discovered inpast studies (Leeds et al. 2010; Vallejo et al. 2014; Liu etal. 2015b; Palti et al. 2015b) led us to hypothesize that agenome-enabled selection approach would be a more
efficient strategy for improving rainbow trout genetic
resistance against BCWD.
Genomic selection is a methodology (Meuwissen et al.
2001) that is revolutionizing animal and plant breeding.
This method uses dense marker genotypes that cover
the genome, combined with phenotypic data to predict
breeding values of all genotyped individuals. In GS, areference population is genotyped and recorded for thetrait to train the GS model and estimate the effects ofeach single nucleotide polymorphism (SNP). Selection
candidates are also genotyped, and by combining their
genotypes with the estimated SNP effects, genomicenabled breeding value (GEBV) are estimated forthe selection candidates. The GS approach does
not necessarily require pedigree recording and the33

MATERIALS AND METHODS

selection candidates do not need phenotypes. Thus,
the GS methodology is particularly relevant fortraits that cannot be measured directly on selection
candidates, including carcass traits, sex-limited traits,
and disease resistance, and has been demonstrated tobe very effective in commercial dairy cattle (Hayes etal. 2009a; VanRaden et al. 2009; Goddard et al. 2011;
Wiggans et al. 2011). For aquaculture species, themain advantage of GS is that it enables exploitation ofwithin-family genetic variation for traits that cannot bemeasured directly on selection candidates. In addition
to increasing accuracy of selection, GS is expected
to reduce rates of inbreeding because the increased
accuracy of Mendelian sampling terms in GS allows for
identification and selection of elite breeding candidates
from more families, with lower co-selection of sibs
(Daetwyler et al. 2007; Dekkers 2007).

Fish Rearing and Disease Challenge
All fish work was conducted in accordance withnational and international guidelines. The protocol forthis study was approved by the Institutional Animal
Care and Use Committee (IACUC; Protocol # 053)
of the U.S. Department of Agriculture, Agricultural
Research Service, the National Center for Cool andCold Water Aquaculture. All efforts were made toensure fish welfare and to minimize suffering.
Details of the fish rearing conditions and the 21-day
survival trial following intraperitoneal injection with
Flavobacterium psychrophilum (Fp), the causative agentof bacterial cold water disease (BCWD), have beenreported elsewhere (Silverstein et al. 2009; Leeds et al.
2010). Mortalities were removed and recorded daily
and fin clipped. Fish that survived to day 21 postinfection were euthanized in 200 mg L-1 of tricaine
methanesulfonate, MS 222 (Sigma-Aldrich, St. Louis,
MO, USA) for at least 10 min prior to sampling of
fin clips. Fin clips from all mortalities and survivors
were individually kept in 95% ethanol until DNA wasextracted using established protocols (Palti et al. 2006).

The genomic BLUP (GBLUP) method assumes a
polygenic architecture of the trait and uses all themarkers data in estimating the genomic relationship
G matrix; in contrast, the Bayesian variable selection
methods assume that the genetic variance is explainedby a reduced number of markers with small-moderateor large effects (Habier et al. 2007; Hayes et al. 2009b;de los Campos et al. 2013; Fernando and Garrick 2013;
Tiezzi and Maltecca 2015). Based on this assumption,
GBLUP is not expected to perform as well as Bayesianvariable selection models when the trait is notpolygenic and it is controlled by several moderate-tolarge effect QTL. The GBLUP method was modified
into the single-step GBLUP method which allows the
combination of the pedigree (A) and genomic-derived
relationships (G) into a combined relationship matrix(H) (Aguilar et al. 2010; Legarra et al. 2014) and to theweighted single-step GBLUP method which emulates
the Bayesian variable selection models by fitting in
the model selected SNPs that explain moderate-large
fraction of the genetic variance (Wang et al. 2012).
Therefore, when evaluating a trait for the first time ina population, it is important to compare the accuracy
of GEBV predictions from several GS models to thoseobtained with pedigree-based BLUP.

Training and Testing Data
The training sample included 102 pedigreed fullsib (FS) families from year-class (YC) 2013 of the
Troutlodge, Inc., all-female, May-spawning population(Fig. 1). The 102 YC 2013 families represented anucleus breeding population undergoing selection
for growth, and thus had not previously been selected
for BCWD resistance. The fish from YC 2013 families
were evaluated in the laboratory BCWD challengein two tanks per family, with an initial stocking of 40
fish per tank (total phenotyped fish n = 7893). The
original study design was to sample n = 1500 fishwith phenotypes and genotypes from 50 FS families.
Of the 50 FS families, 25 were full-sibs of the testing
sample and 25 were least related to the testing sample
families based on pedigree records. We sampled ~40
fish from the 25 FS families that were closely related
to the testing sample and ~20 fish per family from theother less related 25 families. In practice, we sampled n= 1473 fish with phenotypes and genotypes from those
50 families (n = 17-40 per family). Thus, from the 7893
BCWD evaluated fish, 1473 fish had genotype data.

This study was conducted to assess the potential
impact of GS on commercial breeding in rainbow trout
aquaculture, as well as the feasibility of its real-time
implementation into current commercial breeding
schemes. Thus, the objectives of this study were to (1)predict GEBV for BCWD resistance in a commercial
breeding population that has been selected primarilyon growth; (2) compare the accuracy of pedigreebased EBV with that of GEBV from three GS models
using progeny performance data; and (3) assess theimpact of the study design on the accuracy of genomic
predictions using different sampling schemes.

The testing sample included 930 potential breeders
or selection candidates (sires and dams) that weredisease naïve fish sampled from 25 families (n = 31 to
44 testing fish per family). The testing fish had familybased EBV for survival days (DAYS) and survival

34

Figure 1. Scheme of genomic selection for BCWD resistance in rainbow trout used in this study.

status (STATUS) that were estimated with a pedigreebased BLUP model (described below) using BCWD
survival records measured on their siblings and any
collateral relatives among the 102 FS families (n =7893). Each of these testing fish also had predicted
GEBV from GS models (also described below).

previously described in (Palti et al. 2015a). Our quality
control (QC) bioinformatics pipeline filtered out SNPs
with significant distortion from the expected Mendelian
segregation in each FS family (Bonferroni adjusted to
P < 0.10) and also removed two training fish that did
not have genotypes that matched the parents based on
the pedigree records. After genotype data QC, a total of
41,868 SNPs were included in the genotype dataset.

To assess the accuracy of the GEBV, we generated 138
next-generation YC 2015 FS progeny testing families(PTF) from crosses that involved 193 of the YC 2013
testing fish (Fig. 1). These 138 YC 2015 PTF were
phenotyped in 2015 for BCWD survival (n = 9968) to
calculate the mean progeny phenotype (MPP) per PTF.

Before training the GS models, all genotyped SNPs
were further filtered using QC algorithms that are
implemented in the computer program BLUPF90(Misztal et al. 2015). The QC retained SNPs with agenotype calling rate higher than 0.90, minor allele
frequency higher than 0.05, and departures from HardyWeinberg equilibrium less than 0.15 (difference between
expected and observed frequency of heterozygotes).
Parent-progeny pairs were tested for discrepant
homozygous SNPs, those SNPs with a conflict rate ofmore than 1% were discarded. After this final QC step,
35,636 SNPs remained for the GS analysis.

BCWD Resistance Phenotypes
Survival DAYS, the number of days to death postchallenge, were recorded for a total of 21 days postchallenge, with survivors being assigned a value of 21
d post-challenge. Each fish also had a binary survival
STATUS record. The binary STATUS had two classes:
two for fish that were alive on day 21 post-challenge
and one for fish that died during the 21 d post challenge
evaluation period. In the GS analysis, we used DAYS
and STATUS records from training sample fish to
estimate marker effects to then predict GEBV for DAYS
and STATUS for each of the testing sample fish.

Estimation of Pedigree-based EBV
For the testing fish, we estimated EBV for BCWD
resistance phenotypes using a pedigree-based BLUP
(P-BLUP) model. Family-based EBV were estimatedusing BCWD survival records measured on siblingsof the testing fish and any collateral relatives. The
phenotypic dataset included records from n = 7893 fishfrom 102 FS families. The pedigree dataset included
32,279 fish from seven generations.

SNP Genotyping Platform
Genotyping was performed by a commercial
genotyping service provider (Neogen, Inc., Lincoln,NE) using the Rainbow Trout Axiom® 57K SNP array, as
35

Based on past genetic analyses for estimating EBV for
BCWD resistance in rainbow trout (Leeds et al. 2010;
Vallejo et al. 2016), we decided to use an animal modelthat included a population mean, random animal
genetic and random residual effects. The records of
the BCWD survival phenotypes DAYS and STATUS
were fit into P-BLUP linear and threshold models,
respectively, using the computer application BLUPF90(Misztal et al. 2015).

Before performing the GS analysis with ssGBLUP
and wssGBLUP, we estimated genetic parameters to
use as priors in the Bayesian analysis of the binary
trait STATUS as previously described in (Vallejo et al.
2016). The MCMC Gibbs sampling scheme included
a total of 210,000 iterations; the first 10,000 iterations
were discarded as burn-in iterations. Then, fromthe remaining 200,000 samples, one from every 40
samples were saved for analysis. This Gibbs sampling
scheme collected 5000 independent samples foranalysis. The proper mixing and convergence of these
MCMC iterations were also assessed using the R
package CODA (Plummer et al. 2006).

Estimation of GEBV with Bayesian Variable
Selection Models
The SNP genotype data from the training fish (YC 2013
families), with their corresponding BCWD phenotypicrecords, were used to train the prediction model andestimate marker effects using the Bayesian variableselection model BayesB implemented in the software
GENSEL (Fernando and Garrick 2009) as previously
described in (Vallejo et al. 2016); an animal model wasused that included a population mean, random marker
and random error effects. The mixture parameter
was assumed to be known and defined to meet thecondition , where is the number of training fish. After
testing by performing 5-fold cross-validation analyses(results not presented), we decided to use in the final
GS analysis with BayesB because it yielded the best
accuracy predictions.

Predictive Ability and Bias of EBV and GEBVThe predictive ability (PA) of EBV and GEBV, which areboth estimates of additive genetic effects, was estimatedunder the assumption that the correlation of mid-parent
EBV or GEBV with the mean progeny performance(MPP) for each PTF is an estimate of the accuracy of theestimated breeding values (Odegard et al. 2007; Chenget al. 2015; Vallejo et al. 2016). We used the mid-parent
EBV or GEBV instead of the individual EBV or GEBV
of each parent because the testing fish were mated toeach other to generate the 138 PTF, rather than matingeach testing fish to a large random sample of fish froma common genetic background, as is often done in GSstudies with terrestrial agricultural animals and birds.

The software GENSEL uses a Gibbs sampling approachin the BayesB analysis (Garrick and Fernando 2013).
In this study, DAYS and STATUS were analyzed
using 210,000 Markov chain Monte Carlo (MCMC)
iterations, of which the first 10,000 samples werediscarded as burn-in. From the remaining 200,000
samples, we saved one from every 40 samples, thus
a total of 5,000 samples were used in the analysis.
The proper mixing and convergence of the MCMC
iterations were assessed using the R package CODA
(Plummer et al. 2006).

Bias of the EBV was estimated as the regression
coefficient of MPP on predicted mid-parent EBV(bMPP.EBV). Similarly, bias of the GEBV was estimatedas the regression coefficient of MPP on predicted
mid-parent GEBV (bMPP.GEBV). A value of 1.0 for the
regression of true breeding value, performance
phenotype or MPP on predicted EBV or GEBV istheoretically expected for unbiased estimates of
BV, and a deviation from 1.0 can be interpreted as
prediction bias (Saatchi et al. 2013).

Estimation of GEBV with Single-step GBLUP
Models

Impact of GS Study Design on Accuracy of
GEBVThe SNP genotype data from training fish andpedigree information on all fish included in this GS
study were used to estimate GEBV for the testing
sample fish (n = 930 full-sibs of training fish thatwere not disease challenged) using two methods: (i)single-step genomic BLUP (ssGBLUP) (Aguilar et al.
2010; Christensen and Lund 2010) and (ii) weighted
ssGBLUP (wssGBLUP), as previously described(Vallejo et al. 2016). The linear and threshold models
to estimate GEBV for DAYS and STATUS, respectively,
included a population mean, random animal genetic
effects, and random error effects and were fitted aspreviously described in Vallejo et al. (2016) using thesoftware BLUPF90 (Misztal et al. 2015).

To evaluate the impact of sample size and relatedness
between the training and testing fish on the accuracy
of GEBV predictions, we used five GS schemes thatwere developed using the genotype and phenotype
records collected in this study, as outlined in Table 3.
The following study design variables were evaluated:size of the training data (~500, ~1000 or ~1500 fish);number of training families (25 or 50 families); sizeof the training families (20 or 40 fish per family);and proportion of fish in the training data that werefull-sibs (FS) of the testing fish (Table 3). For thelatter variable, scheme 1 = 0.66 means that 66% of the
fish in the training data were FS of fish in the testing
data; scheme 2 = 0.50 means that 50% of the fish in
the training data were FS of fish in the testing data;
36

Table 1. Accuracy of genomic prediction for BCWD survival DAYS in rainbow trout.
Training sample
Testing sample
ModelaPhenotyped fish Genotyped fish
Effective SNPsh2 b
Genotyped fish
P-BLUP
7893
0
0
0.37
0
ssGBLUP
7893
1473
35,6360.33
930
wssGBLUP2
7893
1473
35,6230.33
930
wssGBLUP3
7893
1473
35,6230.33
930
BayesB
1473
1473
35,6360.23
930

Predictive abilityc
0.34
0.63
0.67
0.65
0.71

Biasd
0.86
0.99
0.71
0.65
1.16

Table 2. Accuracy of genomic prediction for BCWD survival STATUS in rainbow trout.
Training sample
Testing sample
ModelaPhenotyped fish Genotyped fish
Effective SNPsh2 b
Genotyped fish
P-BLUP
7893
0
0
0.35
0
ssGBLUP
7893
1473
35,6360.35
930
wssGBLUP2
7893
1473
35,6230.35
930
wssGBLUP3
7893
1473
35,6230.35
930
BayesB
1473
1473
35,6360.25
930

Predictive abilityc
0.36
0.66
0.70
0.68
0.71

Biasd
0.67
0.86
0.68
0.64
1.01

The estimated breeding values (EBVs) were estimated with a pedigree-based animal model (P-BLUP); and the genomic EBVs (GEBVs) were
estimated with three genomic selection models: single-step GBLUP (ssGBLUP), weighted ssGBLUP (wssGBLUP), and Bayesian method (BayesB).
The wssGBLUP2 and wssGBLUP3 correspond to iterations 2 and 3, respectively.
b
For the GS models, h2 is the proportion of phenotypic variance explained by the markers. For the P-BLUP model, h2 is the trait narrow-sense
heritability estimated from pedigree and phenotypic records.
c
The predictive ability of EBV (PAEBV) or GEBV (PAGEBV) was defined as the correlation of midparent EBV or GEBV with MPP from each PTF:PAEBV = CORR(MPP, Midparent EBV); PAGEBV = CORR(MPP, Midparent GEBV).
d
The bias of EBV (BiasEBV) or GEBV (BiasGEBV) was defined as the regression coefficient of performance MPP on predicted midparent EBV or GEBV:BiasEBV = REGRES(MPP, Midparent EBV); BiasGEBV = REGRES(MPP, Midparent GEBV).
a

The estimated breeding values (EBVs) were estimated with a pedigree-based animal model (P-BLUP); and the genomic EBVs (GEBVs) were
estimated with three genomic selection models: single-step GBLUP (ssGBLUP), weighted ssGBLUP (wssGBLUP), and Bayesian method (BayesB).
The wssGBLUP2 and wssGBLUP3 correspond to iterations 2 and 3, respectively.
b
For the GS models, h2 is the proportion of phenotypic variance explained by the markers. For the P-BLUP model, h2 is the trait narrow-sense
heritability estimated from pedigree and phenotypic records. The heritability estimated on the underlying scale of liability was transformed to theobserved scale of survival STATUS.
c
The predictive ability of EBV (PAEBV) or GEBV (PAGEBV) was defined as the correlation of midparent EBV or GEBV with MPP from each PTF:PAEBV = CORR(MPP, Midparent EBV); PAGEBV = CORR(MPP, Midparent GEBV).
d
The bias of EBV (BiasEBV) or GEBV (BiasGEBV) was defined as the regression coefficient of performance MPP on predicted midparent EBV or GEBV:BiasEBV = REGRES(MPP, Midparent EBV); BiasGEBV = REGRES(MPP, Midparent GEBV). The predicted EBV and GEBV for STATUS estimated on theunderlying scale of liability were transformed to the observed scale (probability of survival).
a

Table 3. Accuracy of genomic prediction for BCWD resistance with BayesB using progeny testing familiesa in five GS
schemes.
GS
FamilyTraining–testing
DAYSf
STATUSf
scheme Number Size
relationshipc
Training size
πdSNPse PAGEBVg
BiasGEBVh
PAGEBVg
BiasGEBVh
b
1
50
20–40
1473
0.66
0.97 1069
0.71
1.16
0.71
1.01
2
50
20
991
0.50
0.98 713
0.67
1.55
0.67
1.51
3
25
40
979
1.00
0.98 713
0.69
1.26
0.72
1.23
4
25
20
497
1.00
0.987 463
0.53
1.37
0.61
1.66
5
25
20
494
0.00
0.987 463
0.25
3.33
0.22
5.08

A sample of 193 testing fish (from total n = 930 testing fish) were inter-mated to develop 138 progeny testing families (PTFs). After disease evaluationof progeny from the 138 PTFs (n = 9968), we estimated the mean progeny phenotype (MPP) for each PTF.
b
In scheme 1, there were two groups of training families: (i) A set of 25 families with 40 offspring each that contributed fish to the testing sample; and(ii) A set of 25 families with 20 offspring each that did not contribute fish to the testing sample.
c
Proportion of training fish that were full-sibs (FS) of testing fish: scheme 1= 0.66 indicates that 66% of training fish were FS of testing fish; scheme
2 = 0.50 indicates that 50% of training fish were FS of testing fish; schemes 3 and 4 = 1.0 indicates that ALL training fish were FS of testing fish; andscheme 5 = 0.0 indicates that NONE of training fish were FS of testing fish (i.e., training and testing fish were sampled from different families).
d
BayesB method uses a mixture parameter (π) that specifies the proportion of loci with zero effect, and the analyses included 35,636 effective SNPs.
e
Number of SNPs that are sampled as having non-zero effect (1 − π) and fitted simultaneously in the multiple regression model.
fBacterial cold water disease (BCWD) resistance phenotypes: BCWD survival days (DAYS) and survival status (STATUS).
g
The predictive ability of GEBV (PAGEBV) was defined as the correlation of MPP with midparent GEBV from each PTF: PAGEBV = CORR(MPP, Midparent GEBV).
hBias of GEBV (BiasGEBV) was defined as the regression coefficient of performance MPP on predicted midparent GEBV: BiasEBV = REGRES(MPP,
Midparent EBV); BiasGEBV = REGRES(MPP, Midparent GEBV). The predicted GEBV for STATUS estimated on the underlying scale of liability wastransformed to the observed scale (probability of survival).
aschemes 3−4 = 1.0 means that all fish in the training
data were FS of fish in the testing data; and scheme
5 = 0.0 means that none of the fish in the training
data were FS of fish in the testing data (i.e., fish in the
training and testing data were sampled from different
families from the same breeding population). In
scheme 1, there were two distinct groups of training
families: (i) a set of 25 families with ~40 progeny each(n= 979) that also contributed fish to the testing dataand (ii) a set of 25 families with ~20 progeny each(n= 494) that did not contribute fish to the testingdata (Fig. 2). In scheme 2, we used both groups again
but reduced the number of fish sampled per family
in group (i) to ~20 (n = 497). In scheme 3, we only
sampled group (i) (n = 979). In scheme 4, we only
sampled group (i) again, but reduced the number of37

Figure 2. Relative increase in accuracy of GEBV from GS
models over those estimated with pedigree-based BLUP
model.

Figure 3. Accuracy of GEBV for BCWD resistanceestimated with BayesB in five GS schemes.

fish sampled per family to ~20 (n = 497). In scheme 5,
we only sampled group (ii). The accuracy of predicted
GEBV for each tested GS scheme was estimated using
the BayesB method.

Comparing Accuracy of EBV and GEBVThe relative increase in accuracy of GEBV from GS
models over those estimated with the classical P-BLUP
model is shown in Fig. 3. Overall, the GS models
substantially outperformed the P-BLUP model. The
highest increase in accuracy of prediction was achieved
with BayesB (DAYS = 108.8%; STATUS = 97.2%)
followed by wssGBLUP at iteration 2 (wssGBLUP2)(DAYS = 97.1%; STATUS = 94.4%). The wssGBLUP2
outperformed the wssGBLUP at iteration 3(wssGBLUP3) (DAYS = 91.2%; STATUS = 88.9%). The
lowest increase in accuracy of prediction was achieved
with ssGBLUP (DAYS = 85.3%; STATUS = 83.3%).

RESULTS
Heritability of BCWD Resistance
Estimates of the narrow-sense heritability for DAYS
and STATUS were equal to 0.37 and 0.35, respectively,
using the BLUP model without genomics data (Tables
1 and 2). Similarly, the proportion of phenotypicvariance explained by the markers for DAYS andSTATUS ranged from 0.23 to 0.33 and from 0.25 to
0.35, respectively, using the GS models.

Accuracy of GEBV in the Five GS Schemes
The accuracies of GEBV for DAYS and STATUS
obtained with BayesB using the five GS schemes are
in Table 3. Schemes 1 and 3 had the highest prediction
accuracies (0.69 to 0.72), followed by scheme 2 (0.67).
Scheme 4 GEBV had moderate accuracies (0.53 to 0.61)
that were substantially lower than those for schemes 1
to 3. Scheme 5 had the lowest accuracies (0.22 to 0.25)
among the tested GS schemes. The accuracies of GEBV
from scheme 5 were even lower than the classicalpedigree-based BLUP model accuracies (0.34 to 0.36)(Tables 1 and 2).

Accuracy and Bias of EBV
The prediction accuracy (PA) of EBV for DAYS was
marginally lower than the PA of EBV for STATUS(Tables 1 and 2). The bias of EBV for DAYS deviatedless from 1.0 than the bias of EBV for STATUS.
Accuracy and Bias of GEBVThe PA of GEBV for DAYS ranged from 0.63 to 0.71
and the BayesB model had genomic predictions withthe highest accuracy (Table 1). The bias of the GEBV
for DAYS ranged from 0.65 to 1.16 and the predictions
obtained with ssGBLUP were the least biased. The for
STATUS ranged from 0.66 to 0.71 and BayesB resulted
in genomic predictions with the highest accuracy(Table 2). The bias of GEBV for STATUS, ranged from
0.64 to 1.01 and the predictions obtained with BayesB
were the least biased.

DISCUSSION
The accuracy of GEBV for DAYS and STATUS weresimilar when using the Bayesian method BayesBand higher than those estimated with ssGBLUP and
wssGBLUP (Table 1 and 2). However, the accuracies
of GEBV for STATUS were slightly higher thanthose estimated for DAYS when using ssGBLUP and
wssGBLUP methods, which may be due to (1) a better

38

fit of the binary trait STATUS with a threshold model
than the discrete data DAYS with a linear model, (2)our imprecise measure of DAYS for fish that survived
the challenge (arbitrarily assigned 21 days of survival),and (3) the resulting slightly higher heritability of
STATUS compared to DAYS.

mostly moderate to large effects can yield GEBV withhigher accuracy than GS models that use pedigreeand phenotype records with marker genotype data ina single-step GS BLUP analysis (Aguilar et al. 2010;
Christensen and Lund 2010; Legarra et al. 2014). Thus,
our finding that wssGBLUP2, which fits only SNPs
with an effect different from zero and weighted by their
genetic variance (Wang et al. 2012) to emulate Bayesian
In this study, the accuracy of genomic predictions forvariable selection models, predicts GEBV with higher
BCWD resistance ranged from 0.63 to 0.72, which isaccuracy than ssGBLUP and remarkably close to
substantially higher than accuracies of EBV estimatedwith the classical P-BLUP model and is also significantly BayesB was largely expected.
higher than the 0.55 maximum realized accuracy of EBV
prediction using pedigree and phenotype data with aComparing GS Study Designs
P-BLUP model given a heritability of 0.30 for BCWD
resistance (Van Vleck et al. 1987).
The most interesting result from comparing thedifferent GS sampling schemes was that the accuracy
The accuracy of genomic prediction in dairy cattleof scheme 3 was similar to that of scheme 1, in spite ofexceeded 0.8 for milk production traits and 0.7 forthe smaller training data size of scheme 3 (n = 979 vs.
health-related traits using large reference populationsn = 1473), which is likely due to the higher relationshipthat included progeny-tested bulls with highly accurate
between the training and testing fish in scheme 3 (1.0
phenotypes based on average daughter performancevs. 0.66) and also because the average relationship(Lund et al. 2011; Wiggans et al. 2011). In this study,
among the fish in the training data was higher in
it was remarkable to have genomic evaluations with
scheme 3 than in scheme 1 (Fig. 2; Table 3). Thesean accuracy of 0.71 using a relatively small training
results validate the notion that if the main breeding
dataset (n = 1473) in comparison to those used in dairy
objective is to obtain high accuracy GEBV only for
cattle. We hypothesize that the relatively high accuracy
selection candidates (not for the entire population),achieved in the current study was due to the highthen we should design GS studies that ensure a highrelationship between the training and testing fish, thegenetic relationship between the training and testingsmall effective population size of this farmed rainbow
fish, and also a high average relationship among thetrout population, which leads to extensive linkage
training fish (Pszczola et al. 2012; Wu et al. 2015).
disequilibrium (LD) and a substantially smaller number Likewise, the prediction accuracy of scheme 3 wasof effective chromosome segment effects to be estimated, better than that of scheme 2 (0.69 to 0.72 vs. 0.67)
hence better predictions and higher accuracies
because of the following two design characteristics: (i) a(Daetwyler et al. 2010), and the high extent of longhigher relationship between training and testing fish inrange LD observed in admixed salmonid populations
scheme 3 than in scheme 2 (1.0 vs. 0.5) and (ii) a higher(Rexroad and Vallejo 2009; Odegard et al. 2014).
average relationship among training fish in scheme
3 than in scheme 2 due to the larger family size ofscheme 3. The substantial superiority of scheme 3 overComparing GS Models
scheme 4 on accuracy of predictions (0.69 to 0.72 vs.
0.53 to 0.61), in spite of the same level of relationships
The differences in accuracy between the GS models
between the training and testing fish in those twothat we tested here were small and all of themschemes, was due to the overall larger sample size andoutperformed the classical P-BLUP model. For DAYS
larger family size in scheme 3. Scheme 5 had genomic
and STATUS, the GEBV obtained with BayesB had
predictions with the lowest accuracy (0.22 to 0.25)
the highest accuracy (0.71), and the GEBV obtained
because the relationship between training and testingwith ssGBLUP had the lowest accuracy of predictions
fish was the lowest and the overall sample size was the(0.63 to 0.66). The wssGBLUP2 model outperformed
lowest of the five GS training fish sampling schemes.
ssGBLUP by 0.04 units of accuracy for both
BCWD phenotypes. The Bayesian method BayesB
outperformed wssGBLUP2 marginally by 0.01 and 0.04 These results have important implications on thedesign of effective GS studies in finfish aquaculture
units of accuracy for STATUS and DAYS, respectively.
using similar SNP array densities for genotyping,because they highlight the following: (1) thePreviously, in a different rainbow trout population,
importance of a high relationship between training andwe showed that BCWD resistance is controlled byoligogenic inheritance of a few moderate to large effect testing fish for genomic prediction, i.e. the accuracyof predictions will drastically drop if the training and
QTL and many genes/loci each with a small effect(Vallejo et al. 2010; Vallejo et al. 2014; Palti et al. 2015b). testing fish are sampled from different families within
Thus, given this genetic architecture, variable selection a population, and (2) the accuracy of GEBV from GS
across populations will be relatively low, i.e. training
models (Meuwissen et al. 2001; Fernando and Garrick
2013; Garrick and Fernando 2013) that fit markers with sample from one population and testing from another.
39

Additional Remarks
In comparison to dairy cattle and other livestock
species, one of the main challenges of implementing
GS in traditional family-based breeding programswith salmonid species is the large number of selection
candidates and the limited value of the individual
candidates compared to the genotyping cost.
Nevertheless, the classical sib-testing scheme used indisease resistance breeding programs with salmonids
can be redesigned to capitalize on the ability of GS toincrease the accuracy of breeding value prediction andrate of genetic progress. To this end, for implementing
GS for BCWD resistance in sib-selection schemes in
the rainbow trout industry, we suggest combining afirst step of sib-testing disease challenge evaluations
to pre-select families for disease resistance, assuggested elsewhere (Sonesson and Meuwissen 2009;
Lillehammer et al. 2013; Odegard and Meuwissen2014), with a second step of selective genotyping
individuals from the disease resistance pre-selectedfamilies to reduce genotyping costs. In this GS scheme,
the disease phenotype and marker genotype records
from the pre-selected families can be used to train theprediction model and then, in a third step, to predict
GEBV for each genotyped selection candidate fromfamilies that were pre-selected at the first step.
So far, to the best of our knowledge, this is the firststudy that assesses the accuracy of genomic predictions
for BCWD resistance using progeny performancedata and empirically tests the potential of GS to
exploit within-family genetic variation in sib-selection
breeding schemes in the rainbow trout industry. In thisstudy, we have shown that (i) the accuracy of genomic
predictions is substantially higher than those from aclassical P-BLUP model; (ii) high and near-optimalaccuracy of genomic predictions for BCWD resistancecan be obtained in the rainbow trout commercial
population that was evaluated in this study using a
relatively small training sample size of n = 1000; and(iii) the accuracy of GEBV estimated with BayesB ishigher than those from wssGBLUP3 and ssGBLUP,
followed by the accuracy of wssGBLUP2. Finally, thisstudy provides guidelines for the implementation of
GS in the rainbow trout industry.

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was simulated with a marker spacing of 1 cM. The
markers surrounding every 1-cM region were combined
into marker haplotypes. Due to finite population size
(Ne = 100), the marker haplotypes were in linkage
disequilibrium with the QTL located between themarkers. Then using least squares, all haplotype effects
could not be estimated simultaneously. When only thebiggest effects were included, they were overestimatedand the accuracy of predicting genetic values of theoffspring of the recorded animals was only 0.32. Next,
with best linear unbiased prediction of haplotype
effects assuming equal variances associated to each
1-cM chromosomal segment, the accuracy of genomic
predictions increased to 0.73. They also used Bayesian
methods that assumed a prior distribution of thevariance associated with each chromosome segment
and increased the accuracy to 0.85. The authors
concluded that selection on genetic values predictedfrom high density marker maps could substantially
increase the rate of genetic gain in animals and plants.
With this publication, the authors proposed a GS
method that today has revolutionized traditional
animal and plant breeding programs. The authors laidout concepts and methods that are used in our GS
research in rainbow trout aquaculture.
Odegard, J., T. Moen, N. Santi, S. A. Korsvoll, S.
Kjoglum, and T. H. Meuwissen. 2014. Genomic
prediction in an admixed population of Atlantic
salmon (Salmo salar). Frontiers in Genetics 5: 402.
The authors for the first time tested the reliabilityof genomic selection (GS) models in an admixed
population of Atlantic salmon. The models included
ordinary genomic BLUP models (GBLUP), using
genome-wide SNP markers of varying densities(1–220K), a genomic identity-by-descent model (IBD-GS),
using linkage analysis of sparse genome-wide markers,
as well as a classical pedigree-based model. The authors
compared the reliability of the models using 5-foldcross-validation, and the studied traits were salmon lice
resistance (LR) and fillet color (FC) with heritability of
0.14 and 0.43, respectively. Overall, the authors foundthat all genomic models outperformed the classicalpedigree-based model for both traits and at all marker
densities. However, the relative improvement differedconsiderably between traits, models and marker
densities. For the highly heritable FC, the IBD-GS had
similar reliability as GBLUP at high marker densities(>22K). In contrast, for the lowly heritable LR, IBDGS was clearly inferior to GBLUP, irrespective of
marker density. Hence, GBLUP was robust to marker
density for the lowly heritable LR, but sensitive tomarker density for the highly heritable FC. The
authors hypothesized that this phenomenon may be
explained by historical admixture of different founderpopulations, expected to reduce short-range linkage
disequilibrium (LD) and induce long-range LD. The

ANNOTATED BIBLIOGRAPHY OF KEY
WORKS
Meuwissen, T. H. E., B. J. Hayes, and M. E. Goddard.
2001. Prediction of total genetic value using
genome-wide dense marker maps. Genetics 157:
1819-1829.
This is a landmark publication on whole genomeenabled selection. Using computer simulated data, theauthors proposed the method of genomic selection(GS) when high density SNP chips were not yet
available for any plant and livestock species. The
authors attempted to estimate the effects of ~50,000
marker haplotypes simultaneously from a limited
number of phenotypic records. A genome of 1000 cM
42authors also highlighted that using ordinary GBLUP,
the typical long-range LD of an admixed population
may be effectively captured by sparse marker density,
while efficient utilization of relationship information
may require denser markers (e.g., >22K).

models to predict genomic breeding values (GEBVs)
for BCWD resistance, compared the predictive ability(PA) of GEBVs to pedigree-based estimated breedingvalues (EBVs), and compared the impact of two
SNP genotyping methods on the accuracy of GEBV
predictions. The best GEBV predictions were similar to
EBV with PA values of 0.49 and 0.46 vs. 0.50 and 0.41
for DAYS and STATUS, respectively. Among the GEBV
prediction models, ssGBLUP consistently had thehighest PA. The RAD genotyping platform had GEBVs
with similar PA to those of GEBVs from the Chip
platform. The overall GEBV accuracy in this study was
low to moderate, likely due to the small training sample
used. In this study, the authors explored the potentialof GS for improving resistance to BCWD in rainbow
trout using, for the first time, progeny testing data toassess the accuracy of GEBVs, and it provided the basis
for further investigation on the implementation of GS
in commercial rainbow trout populations.

Vallejo, R. L., T. D. Leeds, B. O. Fragomeni, G. Gao, A.
G. Hernandez, I. Misztal, T. J. Welch, G. D. Wiens,and Y. Palti. 2016. Evaluation of genome-enabled
selection for bacterial cold water disease resistanceusing progeny performance data in rainbowtrout:insights on genotyping methods and genomic
prediction models. Frontiers in Genetics 7: 96.
The authors evaluated the potential utility of
implementing GS in traditional family-based selective
breeding programs using training and testing fishsampled from the first generation of the NCCCWA’s
BCWD resistance breeding line. The authors used GS

43

Atlantic Salmon and Eastern Oyster Breeding Programs at the National
Cold Water Marine Aquaculture Center
Gary S. Burr1*, Michael R. Pietrak1, Brian C. Peterson1, Dina A. Proestou2, and William R. Wolters1
USDA Agricultural Research Service, National Cold Water Marine Aquaculture Center, 25 Salmon Farm Road,
Franklin, ME 04634, USA
2
USDA Agricultural Research Service, National Cold Water Marine Aquaculture Center, 469 CBLS, 120 Flagg
Road, Kingston, RI 02881, USA
1

Corresponding author: gary.burr@ars.usda.gov
Keywords: Atlantic salmon, eastern oyster, breeding program, disease resistance

ABSTRACTINTRODUCTIONThe USDA-ARS National Cold Water Marine
Aquaculture Center (NCWMAC) focuses on the
coldwater marine aquaculture industry’s highest
priority research needs including development of
improved genetic stocks. Coldwater aquaculture
production has potential for expansion, and bothAtlantic salmon and Eastern oysters are widely
accepted by American consumers. Commercial
salmon and oyster producers predominantly utilize
stocks that are not many generations removed fromwild, unselected strains. North America salmon
producers are legally required to culture certified
stocks of North American salmon. The NCWMAC is
the USDA-ARS facility supporting the U.S. coldwater
marine aquaculture industry by developing genetically
improved salmon stocks for the past thirteen years.
Aquaculture of the Eastern oyster is a large segment ofshellfish aquaculture in the U.S. and minimal selective
breeding has been accomplished. In both species,
there is a need to improve the performance of existing
stocks. Our research meets this need through thefollowing objectives: 1) define phenotypes, estimate
genetic and phenotypic parameters, and develop aselection index in Atlantic salmon for important traits
such as carcass weight, cold tolerance, fillet color, fat
content, and sea lice resistance; 2) evaluate and validate
the usefulness of incorporating genomic information
into the salmon breeding program; and 3) establish
links between disease susceptible and resistantphenotypes and genotype for the Eastern oyster.
Identification of genes associated with oyster disease
will provide markers that can be used to enhance
and accelerate the development of high-performing
oyster lines through selective breeding and will
support the East Coast shellfish aquaculture industry.
Research accomplished with salmon will result in thedevelopment of genetically improved Atlantic salmon
for release to U.S. producers and consumers.

Selective breeding is a powerful tool in animalhusbandry. The USDA-ARS started the National Cold
Water Marine Aquaculture Center (NCWMAC) in2003 to begin a genetic selection and improvement
program for Atlantic salmon (Salmo salar L.) of
North American origin. The program was started in
response to producer requests for assistance when
U.S. regulations were established to prohibit theculture of Atlantic salmon with European genes as amechanism to protect populations of wild Atlantic
salmon federally listed as endangered. This regulation
essentially prohibited culture of existing commercially
improved stains as they are all based on European
genetic stocks. In 2013, requests from East Coast
U.S. oyster producers resulted in the expansion of
the program to include selection of Eastern oysters(Crassostrea virginica Gmelin 1791).
Selective breeding programs for Atlantic salmon beganover 40 years ago in Norway, and currently, various
programs exist in all of the major salmon producing
regions (Gjedrem and Baranski 2009). The primary
focus of most of these programs, including the oneat NCWMAC, is improved growth. The response insalmon to selection for growth or weight is robustwith a 10-15% gain per generation (Gjedrem andBaranski 2009), which has resulted in the growth rate
for salmon doubling in 6-7 generations of selection(Gjedrem and Baranski 2009). Despite achieving adoubling in growth rate, selective breeding programs
have not been able to manifest this in halving the
production time as might be expected. The NCWMAC
has been focusing on how to realize and characterize
the response to selection for growth in Atlantic
salmon. More recently, resistance to sea lice infection
has been added as an important selection criteria.
Sea lice (Lepeophtheirus salmonis Krøyer 1837) was
estimated to cause the global salmon farming industry
approximately $742 million USD in damage in 2012
44

(Roth 2015). Traditionally, control of sea lice has reliedon the use of various chemotherapeutics; however,resistance to many of these has recently led to a hostof non-chemotherapeutic control strategies including
selective breeding (Aaen et al. 2015; McNair 2015;
Roth 2015; Gjerde et al. 2011). The NCWMAC beganevaluating their pedigreed families for sea lice resistancein 2015 for inclusion into the breeding selection program.
Concurrently, the program is exploring approaches toestimate genotypic breeding values in addition to theexperimentally derived phenotypic breeding values inorder to improve overall trait selection.

approximately 15 months after hatching, fish fromeach family were pit tagged. Each tank was suppliedwith 2.0 ppt salinity water from a recirculating
biological filtration system and illuminated on anatural photoperiod. Fish were fed a commercial diet
(45%P, 25%F) from Arvotec® automatic feeders at a
rate determined by fish size and temperature fromexperimental growth models (Ursin 1967; Ruohonen
and Markinen 1992).
Salmon Sea Lice Challenges

One fish from each family was stocked into 12 1-m3
There are currently three breeding programs for themeter tanks. Each tank contained 100-120 fish (oneEastern oyster in the U.S. in Maine, New Jersey andfish per family). In order to make sea lice counting
Virginia. Each of these programs has selected for
manageable, fish in a single tank were exposed to 100
improved oyster growth and survival to regionallycopepodid per fish for two hours to allow the sea lice
important conditions and pathogens. The NCWMAC
to settle on the fish. After 12 to 15 days, depending on
has established a program in Rhode Island with thethe temperature, the sea lice were allowed to develop togoal of working across the different strains produced by the chalamus stage (an attached sessile stage) and thenthese programs to characterize and enhance resistance counted. This procedure was repeated for each tank to
to Dermo, which is caused by the parasite Perkinsus
stagger the collection of sea lice settlement data. Thismarinus (Mackin, Owen and Collier) Levine 1978.
procedure has also been done for every year sea lice
The disease is spread from Massachusetts through thesettlement data have been collected.
Gulf of Mexico and can cause > 50% annual crop loss
on infected farms. The program is currently working
Oyster Breeding Program
to identify genes associated with parasite resistance,
avoidance and susceptibility with an ultimate goal of
The oyster breeding program at the NCWMAC
developing genetic markers for selection. In addition,
obtained family stocks from the Virginia Institute of
the program is collaborating on the Eastern Oyster
Marine Science (VIMS), Rutgers University and the
Genome Project to facilitate future selection efforts.
University of Maine. Oysters are cultured in tanks
containing seawater. Eastern oysters are exposed to
In summary, the NCWMAC is focused on utilizing
Dermo and survival, parasite load, feeding behavior
genetic selection and various genetic tools to improveand gene expression profiles are measured.
strains of the commercially important species Atlantic
salmon and Eastern oyster. Here, we discuss examples
of current efforts including characterizing the response Table 1. Estimates of heritabilities (h2±SE) for total sea lice
to selection for improved growth, selecting forcount (TC), sea lice density (LD), and body weight (BW),resistance and developing genetic tools to improve the and the estimated phenotypic (rp±SE above diagonal) andgenetic correlations (rg±SE below diagonal) among theselection for sea lice and P. marinus resistance.
three traits.

METHODS

Trait
TC
LDa
BW

Atlantic Salmon Fish Culture
Originally, individual families of Atlantic salmon
were obtained from the existing industry in Maine.
Additional strains of Atlantic salmon were obtained:
a wild non selected strain from the U.S. Fish andWildlife Service (Green Lake and Craig Brook
National Fish Hatcheries) and a landlocked strain fromGrand Lake, Maine. Fry were transferred after hatching
but prior to first feeding, into individual 0.15-m3 tanks
from a recirculating biological filtration system. At
approximately 30 days after initiation of feeding anda fish weight of 1-2 g, fish densities were equalized
by stocking 250 fish at random into each tank. At

a

h2±SE
0.11±0.05
0.14±0.06
0.30±0.09

rp±SE
TC
—
0.87±0.08-0.03±0.27

rg±SE
LD
0.92*
—
-0.60±0.20

BW
0.10*
-0.14*—

Unitless calculated index based on body weight and lice counts.

Table 2. Estimates from heritabilities (h2±SE) for lice density.
2015
2016
Infection Dates
Jun 26-Nov 8
Jun 15-Aug 22
Tanks Infected
915
Avg # Fish/Family
8.3 (5-10)
13.8 (10-15)
Avg Weight
295.1
210.3
Avg # Lice/Fish21.1 (8.1-60)
52.4 (32.4-114.6)
Lice/cm2
0.05
0.22
Lice Density
0.52
1.55
Heritability
0.19 (0.108)
0.17 (0.098)

45

Figure 1. Average lice density for each family in 2015 (top) and 2016 (bottom). Families ordered along x-axis from lowest
to highest lice density.

Statistical Analysis of Phenotypes

correlations were estimated from the components
of variance and covariance. The (co)variances were
estimated from bivariate analyses of pairs of traits.
The REML estimates were used to obtain Best Linear
Unbiased Predictors (BLUP) of individual breedingvalues for carcass weight.

Three body size traits (total, carcass, and fillet weights)
and sea lice data (lice density) were analyzed withan animal model including fixed effects (stock, sex,
stage of sexual maturity, and replicate culture tank),
random animal genetic, and residual effects. Estimatesof variance components that maximize the restricted
likelihood (REML) were obtained with a derivativefree algorithm using the MTDFREML programs(Boldman and Van Vleck 1991; Boldman et al. 1995).
The parents of the families were assumed to beunrelated. Heritabilities, genetic and environmental

RESULTS AND DISCUSSION
Sea lice challenges were added to the breeding programat the request of industry. The average sea lice density
was highly correlated with total sea lice count andnegatively correlated with body weight. Total lice countwere positively correlated with lice density and bodyweight (Table 1). The estimates of heritabilities for sea
lice resistance ranged from 0.11 ± 0.05 to 0.14 ± 0.06,
which is similar to what has previously been observed
for natural infection challenges (Glover et al. 2005;
Kolstad et al. 2005) but lower than observed for tankinfections (Kolstad et al. 2005; Gjerde et al. 2011). The
natural infection challenges recorded both motile andsessile stages which could result is different heritability
estimates (Glover et al. 2005; Kolstad et al. 2005).
Gjerde et al. (2011) only counted sessile sea lice and had
a lower initial infection rate compared to our studies(74 or 36 compared to 100 for our trails). In later trials(Table 2, Fig. 1), we observed more uniform infectionof the fish and a higher estimated heritabilities. The
calculated heritabilities were 0.17 ± 0.11 in 2015 and0.19 ± 0.10 in 2016. We will continue to evaluate sea lice
resistance for families in each year class.

Figure 2. Percent difference in weight between theselected strain.

46

57% to 141% over the unselected strain
grown under the same conditions(Fig. 2). Gjedrem (2005) and Gjedremand Baranski (2009) estimated thatan Atlantic salmon breeding program
should be able to produce fish withincreased growth by around 15% eachgeneration. We are able to obtain
similar gain per generation (Bill
Wolters personal communication).
We are currently adding fillet pigment
content (color), fillet fatty acid content(EPA and DHA levels), and fillet lipid
levels to the breeding program. The
breeding program at the NCWMAC
will soon be adding genomic breedingvalues to the EBVs that are currently
in use to further enhance selection fordesirable traits.
The NCWMAC oyster breeding
program is currently evaluating fivedifferent oyster stocks for resistance toDermo. Oysters that were susceptible
to the disease had the highest parasiteload, while resistant families had thelowest parasite load (Fig. 3). Oysters
Figure 3. Dermo mean parasite load by family (top) and survival over time
appear to be able to control their(days) of challenged oysters by family (bottom).
exposure to the parasite by reducing
feeding rates (Fig. 4). However, oysters
Growth rates are also being evaluated in the selectedthat are able to reduce their exposure to the parasite
strain of North American Atlantic salmon withare not the best families at resisting or tolerating theassistance of industry partners. Currently, we are
infection. In the future, oysters that are resistant tousing a wild unselected strain as a control, and we are
disease through phenotypic trials will be used todetecting increases in the selected strain ranging from identify genes associated with resistance, tolerance47

Figure 4. Modes of Dermo resistance by families in the Eastern oyster breeding program.

and susceptibility to Dermo. This should allow thedevelopment of genetic markers to assist with selection
similar to the Atlantic salmon breeding program.

Proestou, D.A., B.T. Vinyard, R.J. Corbett, J.
Piesz, S.K. Allen, J.M. Small, C. Li, M. Liu,
G. DeBrosse, X. Guo, and P. Rawson. 2016.
Performance of selectively-bred lines of easternoyster, Crassostrea virginica, across eastern U.S.
estuaries. Aquaculture 464: 17-27.
Ruohonen, K., and T. Makinen. 1992. Validation of
rainbow trout (Oncorhynchus mykiss) growthmodel under Finnish circumstances. Aquaculture
105: 353-362.
Roth, M. 2015. Management of sea lice on farmed
salmon with veterinary medicines and biologicalcontrol strategies. International Animal Health
Journal 2: 32-37.
Wolters, W.R., F.T. Barrows, G.S. Burr, and R.W. Hardy.
2009. Growth parameters of wild and selectedstrains of Atlantic salmon, Salmo salar, on two
experimental diets. Aquaculture 297: 136-140.
Ursin, E. 1967. A mathematical model of some aspectsof fish growth, respiration, and mortality. Journalof the Fisheries Research Board of Canada 24:
2355-2453.

REFERENCES
Aaen, S.M., K.O. Helgesen, M.J. Bakke, K. Kaur,and T.E. Horsberg. 2015. Drug resistance in sea
lice: a threat to salmonid aquaculture. Trends in
Parasitology 31: 72-81.
Boldman, K. G. and L. D. Van Vleck. 1991. Derivativefree restricted maximum likelihood estimation in
animal models with a sparse matrix solver. Journalof Dairy Science 74: 4337-4343.
Boldman, K. G., L. A. Kriese, L. D. Van Vleck, C. P.
Van Tassell, and S. D. Kachman. 1995. A manual
for use of MTDFREML. A set of programs to
obtain estimates of variances and covariances. U.S.
Department of Agriculture, Agricultural ResearchService, USA, http://aipl.arsusda.gov/curtvt/
remlman.ht.
Gjedrem, T. (ed.). 2005. Selection and breeding
programs in Aquaculture. Springer, Dordecht, The
Netherlands, 364 pp.
Gjedrem, T. and M. Baranski. 2009. Selective breeding
in aquaculture: an introduction. Reviews: Methods
and Technologies in Fish Biology and Fisheries 10,
Springer, Dordecht, The Netherlands.
Gjerde, B., J. Odegard, and I. Thorland. 2011. Estimatesof genetic variation in the susceptibility ofAtlantic salmon (Salmo salar) to the salmon louse
Lepeophtheirus salmonis. Aquaculture 314: 66-72.
McNair, C.M. 2015. Ectoparasites of medical andveterinary importance: drug resistance and theneed for alternative control methods. Journal of
Pharmacy and Pharmacology 67: 351-363.

ANNOTATED BIBLIOGRAPHY OF KEY
WORKS
Gjedrem, T. (ed.). 2005. Selection and breeding
programs in Aquaculture. Springer, Dordecht, The
Netherlands, 364 pp.
Gjedrem, T., and M. Baranski. 2009. Selective breeding
in aquaculture: an introduction. Reviews: Methods
and Technologies in Fish Biology and Fisheries 10,
Springer, Dordecht, The Netherlands.
The books referenced above describe selective breeding
programs for a wide range of cultured species. The
editor and many authors are from Norway, which has

48

the longest running Atlantic salmon selective breeding
program in the world.

The article referenced above looked at the performanceof selectively-bred lines of eastern oysters in five
representative grow-out sites and detected significant
effects of selection and large and significant genotype
by environment interactions. This information will be
useful in evaluating current breeding strategies for theeastern oyster.

Gjerde, B., J. Odegard, and I. Thorland. 2011. Estimatesof genetic variation in the susceptibility ofAtlantic salmon (Salmo salar) to the salmon louse
Lepeophtheirus salmonis. Aquaculture 314: 66-72.

Ermgassen, P. S. E., M. D. Spalding, B. Blake, L. D.
The paper above provides a brief overview of previous
Coen, B. Dumbauld, S. Geiger, J. H. Grabowski, R.
research looking at the heritability of sea lice resistance,
Grizzle, M. Luckenbach, K. McGraw, W. Rodney,
while importantly demonstrating the need to normalize
J. L. Ruesink, S. P. Powers, and R. Brumbaugh.
lice infection counts to a factor, such as lice density, that2012. Historical ecology with real numbers: pastaccounts for fish size at the time of infection.
and present extent and biomass of an imperiled
estuarine habitat. Proceedings of the Royal Society
Proestou, D.A., B.T. Vinyard, R.J. Corbett, J.
of London B: Biological Sciences. 279: 3393-3400.
Piesz, S.K. Allen, J.M. Small, C. Li, M. Liu,
G. DeBrosse, X. Guo, and P. Rawson. 2016.
The article referenced above analyzed historical shellfish
Performance of selectively-bred lines of easternlanding and biomass data along the Eastern U.S. coastoyster, Crassostrea virginica, across eastern U.S.
and correlated it to various anthropogenic stressors
estuaries. Aquaculture 464: 17-27.
including overexploitation, habitat degradation, climatechange and the resultant spread of disease.

49

The Molluscan Breeding Program: 20 Years of Selective Breeding of
the Pacific Oyster, Crassostrea gigas, on the West Coast of the U.S.
Romain Morvezen1, Claudio de Melo2, Blaine Schoolfield1, Evan Durland1, Brett Dumbauld3, and Chris Langdon1
Department of Fisheries and Wildlife and Coastal Oregon Marine Experiment Station, Hatfield Marine Science
Center, Oregon State University, 2030 Marine Science Drive, Newport, OR 97365.
2
Laboratory of Marine Mollusks, Department of Aquaculture, Federal University of Santa Catarina,
Florianópolis, SC, 88061-600, Brazil
3
USDA-ARS, Hatfield Marine Science Center, Oregon State University, 2030 Marine Science Drive, Newport,
OR 97365.
1

Corresponding author: Not available.
Keywords: Not available.

ANNOTATED BIBLIOGRAPHY OF KEY
WORKSABSTRACTThe Molluscan Broodstock Program (MBP) was
initiated in 1996 by Oregon State University (OSU)
and the U.S. Dept. of Agriculture with the goalof increasing the performance of Pacific oysters(Crassostrea gigas) for use in aquaculture on the West
Coast, USA. MBP utilizes a family-based selection
breeding design and was founded by broodstockcollected from wild populations in Washington State
and British Columbia, Canada. Breeding design andhatchery production of larvae and spat is undertaken
by OSU at the Hatfield Marine Science Center in
Newport, Oregon and families are planted out forfield trait estimates at industry sponsored field sites
along the West Coast. The selection process utilizes anindex based on family performances for three traits ofinterest: family yield, average individual harvest weightand survival. Results of five generations of selective
breeding show that substantial genetic gains havebeen attained. Realized gains are lower than expected,
however, and we suspect this might be caused bycompetition for food in dense culture conditions anda changing climate, including intensified upwelling
events, which bring deep, acidified, and nutrientrich water to the surface. Heritability estimates havedeclined in the last two generations of the program,which corroborate these results and further suggest
a changing environment. Significant genetic byenvironment (GxE) interactions have been detected
between Puget Sound and coastal estuarine plantout sites, indicating major environmental differences
between the two types of sites. Taken together, theseresults are being used to develop modified breeding
approaches for MBP, including a more careful indexing
approach to take into account GxE interactions.
Further considerations for MBP include breeding for
new traits in response to emerging issues such as ocean
acidification and diseases.

Langdon, C., F. Evans, D. Jacobson, and M. Blouin.
2003. Yields of cultured Pacific oysters Crassostrea
gigas Thunberg improved after one generation of
selection. Aquaculture 220(1): 227-244.
This publication marks the first evaluation of thegenetic gain obtained by the MBP after one generationof selection. The authors demonstrate significant
improvement in yields of selected lines compared
to unselected controls. However, they found only
weak correlation between family performances inintertidal and subtidal environments, which indicatedpossible interactions between family performance andenvironment.
Evans, F., S. Matson, J. Brake, and C. Langdon. 2004.
The effects of inbreeding on performance traitsof adult Pacific oysters (Crassostrea gigas).
Aquaculture 230(1): 89-98.
The effect of inbreeding was evaluated in the context
of a commercial growing operation by measuring
survival, family yield, and individual growth after
one or two growing season. Results showed thatfamilies with a high (F = 0.2) inbreeding coefficientperformed worse than families with a low (F = 0.006)
inbreeding coefficient, and this effect was stronger
after two growing seasons. The result called for a strict
monitoring of inbreeding in a selective broodstock
program, such as the MBP.
Melo, C. M. R., E. Durland, and C. Langdon. 2016.
Improvements in desirable traits of the Pacificoyster, Crassostrea gigas, as a result of fivegenerations of selection on the West Coast,
USA. Aquaculture 460: 105-115.
50

Authors evaluated the heritability, genetic correlations,and genetic gain for survival, individual weight, andyield over five generations of selective breeding in the
MBP. Substantial genetic gain was observed throughout
generations except for individual weight, where gains
were limited after the second generation. Realized gains
were less than expected, however, given the genetic

gain, perhaps due to poor control over the selection ofbroodstock for controlled crosses. Heritabilities seemed
to decline in the 4th and 5th generations, and the authors
suspect this was caused by changing environmental
conditions, such as the intensification of upwelling
events due to climate change.

51Seriola Genomics and the Knowledge Repository serioladb.org
Andrew Severin1*, Catherine Purcell2, Mark Drawbridge3, Rick Masonbrink1, Arun Seetharam1, Akiyuki Ozaki4,
Kazuo Araki4, Hironori Usuki4, Koichi Okuzawa4, Mituru Ototake4, Fuminari Ito5, and John Hyde2
Genome Informatics Facility, 206 Science I, Iowa State University, Ames, Iowa 50011
Southwest Fisheries Science Center, NOAA Fisheries, 8901 La Jolla Shores Dr., La Jolla, CA 92037
3
Hubbs-SeaWorld Research Institute, 2595 Ingraham Street, San Diego, CA 92109
4
Headquaters, Research Management Department, Japan Fisheries Research and Education Agency
5
National Research Institute of Aquaculture, Japan Fisheries Research and Education Agency
1

2

Corresponding author: severin@iastate.edu
Keywords: aquaculture, Seriola dorsalis, genome browser, sex determination

ABSTRACT

region and globally. More recently, S. dorsalis and S.
rivoliana have been considered prime candidates foraquaculture development in Southern California and
Hawaii, respectively.

Due to the high value of Seriola in the seafoodindustry, Seriola aquaculture is of great interest in the
U.S. and elsewhere. Hatchery production of Seriola
species is accelerating but has been hindered by apropensity for deformities and growth heterogeneity
developed during larval and early juvenile stages that
limits production capacity and efficiency.

Agriculture and livestock production went througha genomic revolution in the first decade of the new
century shortly after the sequencing of the humangenome in 2001 (Lander et al. 2001) as observedby the sequencing of 40 or so agriculture species(Michael and VanBuren 2015) and the five major
livestock species (cow, pig, sheep, horse, and chicken)
by 2012 (Bai et al. 2012). Aquaculture is now similarly
going through its own genomic revolution with thesequencing of (rainbow trout, sea bass, Atlantic
salmon, tilapia, catfish, flounder, and Atlantic cod)
(Palti et al. 2011; Terova et al. 2014; Spivakov et al.
2014). It is now possible for small groups as opposedto large consortia to create genomic resources toimprove production of a species in agriculture,
livestock and aquaculture. These resources can beused to gain an understanding of the genetic basisof traits that currently limit/enhance developmentof domestic aquaculture (Rondeau et al. 2013).
These resources can be used to identify the genetic
element responsible for traits of economic importancesuch as disease resistance, growth rate, tolerance ofenvironmental stressors, diet/nutrition, reproduction,and general health (Fuji et al. 2010; Huete-Pérez
and Quezada 2013; Ozaki et al. 2013; Spivakov et al.
2014). High throughput sequencing that includes a
combination of second generation Illumina/PacBio,
third generation NanoPore technologies and superlong distance information library preparation methods(Dovetail Chicago and HiC) makes it possible for
rapid application of these sequencing technologies andprovides advancements in broodstock selection andsustainable Seriola aquaculture.

To advance Seriola aquaculture, we are developing
genomic resources for Seriola dorsalis and Seriola
rivoliana. The starting point for this resource includes
a draft genome assembly with gene annotations for S.
dorsalis. In addition, we have resequenced 90 fish fromthree locations (Cedros Island, La Paz, and San Diego)
and generated an F2 population to explore the genetic
component in malformations in juvenile fish (swim
bladder inflation, several head and jaw deformities andmalformations in the operculum and branchiostegal
structures).
To consolidate this data into a single knowledge
repository, we are creating an international web
resource, serioladb.org. As yellowtail culture grows,
the genetic tools on the website will be made available
to producers and other groups working to improve
culture for this and other Seriola species. This research
may also serve as a model for genetic resource
development for aquaculture species or conservation
dependent species with limited genomic resources
and may help reveal genomic regions and genes
contributing to trait variation in wild populations.

INTRODUCTION
Aquaculture production is becoming increasingly
important to global food supplies. Amberjacks or
yellowtail are fishes of the genus Seriola (S. dorsalis,
S. dumerili, S. lalandi, S. rivoliana, S. quinqueradiata).
Japan has been very successful with the culture andproduction of S. quinqueradiata and S. dumerili as partof the high valued sashimi industry prominent in thatIn this study, we describe preliminary data from thegenome assembly project of Seriola dorsalis and theapplication of resequencing of 90 Seriola dorsalis fish
to identify the Sex Determining Region (SDR). We
52

compare our progress with preliminary data fromongoing assembly projects of Seriola quinqueradiata
and Seriola dumerili with our Japanese collaborators.
Given the relative ease at which genomic data can
now be generated, we also describe the need for andimplementation of a better genomic resource to manage
these data by groups collaborating across the world.

TASSEL (version 5) (Bradbury et al. 2007). TASSEL
identified the sex-determining region (scaffold 22
between 231,000 and 420,000bp).
All insertions/deletions (InDels) greater than
40 nucleotides in the SDR were identified. One
61-nucleotide deletion on scaffold 22, starting at baseposition 246,495 on scaffold 22, was identified asheterozygous in females and homozygous in males.
Two sets of primers, SdorDel01 and SdorDel02, were
designed to span across the deletion using Primer3(Untergasser et al. 2012). PCR products were visualizedusing a 2% agarose gel electrophoresis with 100bp size
standard markers (ThermoFisher Scientific, Waltham,
MA, USA) run at 78V for 40 and 60 minutes, for
SDorDel02 and SDorDel01, respectively.

METHODSDNA from a juvenile S. dorsalis (50 days post-hatching)
was extracted from an individual from HubbsSeaWorld Research Institute (San Diego, CA), which
was humanely euthanized by overdose with MS-222.
The tissue was placed immediately into InvitrogenTM
RNAlater® Stabilization Solution (ThermoFisher
Scientific, Waltham, MA, USA), stored for 24 hours at
4°C and then frozen at -20°C until DNA extraction.

Genome statistics from draft genome assemblies
for Seriola quinqeradiata and Seriola dumerili wereobtained through a personal communication with
Ozaki. Genome papers for these species are currently
in progress; however, a draft of the S. dumerili genome
was used in an initial exploration of synteny between
S. dorsalis and S. dumerili. Opscan (0.1) (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3961402/),
which uses fastp alignments and the NeedlemanWunsch-Sellers Algorithm to calculate orthologous
gene families was used to determine the synteny. All
alternatively spliced variants and all possible multifamily genes were considered. To infer synteny,iAdHoRe (3.0.01) (https://www.ncbi.nlm.nih.gov/
pubmed/17947255?dopt=Abstract) was used with aprob_cutoff=0.001, level two multiplicons only, gap_
size=15, cluster_gap=20, q_value=0.9, and a minimumof three anchor points. Syntenic regions are displayedusing Circos (0.69.2) (http://genome.cshlp.org/
content/early/2009/06/15/gr.092759.109.abstract).

Several hundred wild Seriola dorsalis fish were collected
via hook and line by either private sport anglers orcommercial/subsistence fishers aboard various fishingvessels from San Diego, California; Cedros Island,
Mexico; and La Paz, Mexico. Sex phenotype wasdetermined by scientific observers examining gonadal
tissue. Muscle, fin, or gonadal tissue was placed in 100%
ethanol and DNA from 90 samples was extracted (15 ofeach sex from each of the three locations for a total of
45 male and 45 female specimens).
The DNeasy Blood and Tissue Kit (Qiagen, Hilden,
GER) was used to extract DNA from all samples
following the manufacturer’s protocol. Heart andspleen tissue was used from the specimen undergoinggenomic sequencing. Muscle, fin, or gonadal tissue wasused for the 90 specimens undergoing resequencing.
Samples prepared for the genomic and re-sequencing
applications were sent to the DNA Sequencing Facility
at Iowa State University (Ames, Iowa) for library
preparation and sequencing.

We are in the process of creating a genomics toolbox
and web resource that will facilitate the explorationand integration of large sequencing data sets. Website
content will be generated using the Drupal Luggage
Suite, which has form-based entry and was developed
here at ISU. The website will include JBrowse (Skinneret al. 2009), a Genome Browser for visualization of dataaligned to the Seriola genome and InterMine (Smith etal. 2012; Lyne et al. 2013), an open source data warehousethat enables researchers to explore biological data.

MaSuRCA assembler (version 2.3.2) (Zimin et al. 2013)
was used to assemble the raw data. Scaffolds were
filtered with the following parameters: scaffolds were
removed when they contained fewer than 800 bases orwhen 90% of the total scaffold length was containedin a different larger scaffold. The scaffolds must also
contain a gene or be larger than 10,000 bases. BRAKER(Nanda et al. 2002; Hoff et al. 2015)England was used
to annotate the genome using 547 million 50 bp PE
raw RNA-Seq data from a related project.

Table 1. Comparison of assembly quality statistics for three
Seriola species.
S. dorsalis S. dumerili
S. quinqeradiata
Scaffolds
4,439
1,341
3,902
N50
1.5 Mb
5.8 Mb
0.8 Mb
Nucleotide
653 Mb671 Mb844 Mbcontent
Genes
45,58147,313in progress

Raw DNA resequencing reads were aligned to theassembled genome using BWA-MEM (Li 2013). SNPsand InDels were called using GATK (McKenna et al.
2010). A genome-wide association study (GWAS) using
a Generalized Linear Model (GLM) was performed in
53

Figure 1. Circos plot comparing the largest scaffolds of Seriola dorsalis (green, on the left) with thecorresponding syntenic scaffolds in Seriola dumerili (blue, on the right). Significant synteny is observedwith only a couple potential chromosomal rearrangements.

RESULTS AND DISCUSSION

total nucleotides in the assembly. N50 for S. dorsalis,
S. dumerili and S. quinqeradiata is 1.5 Mb, 5.8 Mb
and 0.8 Mb, respectively. The S. dumerili preliminary
assembly is better due to additional long read data thatwas collected for that assembly from PacBio (Menlo
Park, CA, USA). All future assemblies will include
both PacBio and super long-range information fromeither Dovetail Chicago libraries or genetic mapsthat should bring these assemblies close to complete
chromosomal level assemblies. Comparisons between
S. dorsalis and S. dumerili reveal a great deal ofsynteny between these species. As more Seriola species
genomes become available and researchers perform
Genome Wide Association Studies for specific traits ofinterest (disease resistance, growth rate, tolerance ofenvironmental stressors, diet/nutrition, reproduction,

High throughput sequencing has become a powerfultool in developing genomic resources (Taylor 2014)(Dunham et al. 2014), and these data are being used
to begin developing genomic resources for several
Seriola species. Together, we and our collaborators at
the Japan Fisheries Research and Education Agency
have three Seriola genomes in varying stages ofassembly and publication (Table 1). We can see thatthe quality of these preliminary assemblies based on
the number of scaffolds between these species arevery similar 4,439; 1,341; and 3,902 for S. dorsalis, S.
dumerili and S. quinqeradiata, respectively. N50 isanother measure of the assembly quality. The sumof all scaffolds N50 size and smaller equals half the54

Figure 2. Graph of negative log 10 p-values GWAS output from TASSEL plotted across a portion of scaffold 22 in the
Seriola dorsalis genome. The figure shows many SNPs in linkage disequilibrium with significant correlation to the sex
phenotype.

Fuji et al. 2010). However, the marker reported inthat study does not distinguish sex in other Seriola
species (Ozaki, pers. com) and lies just outside of the
SDR. Interestingly, markers we have identified forsex determination did not work in a small number ofS. rivoliana specimens, although the effectiveness inother Seriola species has not yet been tested.

and general health), there will be great potential totranslate these findings among species (Fig. 1).
The assembled S. dorsalis genome was used to alignresequencing data from the sexed 90 wild-caught fish.
The Sex Determining Region (SDR) was identified
along with a sex-specific marker based on a 61
nucleotide deletion (Fig. 2). The identified SDR in S.
dorsalis is consistent with the known sex marker in
S. quinqueradiata (ssr263g21) (Koyama et al. 2015),
which maps just upstream of this region: scaffold
22 at 194817-194840 base pairs (linkage group 12;

With the collection of vast quantities of sequencing
data comes the responsibility to make this data
available to the public. This poses challenges sincefunding and personnel to curate genomic web

Figure 3. Form-based page creation and data deposition ensures the website is easy to maintain, build
and search.

55

Figure 4. Professional looking main page of Serioladb.that was created using the Drupal Luggage suite.

resources are limited and the ability to sequence a
species increasingly becomes easier. In an attempt toovercome these challenges, a form-based web-content
generating approach will be adopted for Serioladb.
org where multiple groups working on Seriola species
from across the world can collaboratively curate the
web resource to add their data and knowledge. By
using forms (Fig. 3), web content creation will beuser friendly with a uniform format for generated
content that looks professional (Fig. 4). The content
and organization of the website will be specific toeach genomic resource and the collaborating group
maintaining it. However, there are several curation
tasks that can and should be automated such as
the creation of files for download and tracks to bevisualized in the genome browser. While we are stillin the process of figuring out how to make it easier
to collaborate on a shared genomic resource, we are
excited about how Serioladb.org and similar genomic
resources will advance sustainable aquaculture.

REFERENCES
Bai, Y., M. Sartor, and J. Cavalcoli. 2012. Current
status and future perspectives for sequencing
livestock genomes. Journal of Animal Science andBiotechnology 3(1): 8.
Bradbury, P. J., et al. 2007. TASSEL: software for
association mapping of complex traits in diverse
samples. Bioinformatics 23(19): 2633-2635.
Fuji, K., et al. 2010. Identification of the sex-linked
locus in yellowtail, Seriola quinqueradiata.
Aquaculture 308: S51-S55.
Hoff, K. J., et al. 2015. BRAKER1: Unsupervised RNAseq-based genome annotation with GeneMark-ET
and AUGUSTUS. Bioinformatics 32(5): 767-769.
Huete-Pérez, J. A., and F. Quezada. 2013. Genomic
approaches in marine biodiversity andaquaculture. Biological Research 46(4): 353-361.
Koyama, T., et al. 2015. Identification of sex-linked
SNPs and sex-determining regions in theyellowtail genome. Marine Biotechnology 17(4):502-510.
Lander, E. S., et al. 2001. Initial sequencing and analysisof the human genome. Nature 409(6822): 860-921.

56

Authors sampled 42 Seriola lalandi from South
Africa, Japan, New Zealand, California, Mexico
Pacific, Mexico Gulf and Chile to better understandregional populations and evolutionary patterns. Two
mitochondrial genes (CR and COI) and four nuclear
genes (RAG2, EHHADH, UBE3A, and MLL) were used
to generate a phylogenetic tree with Seriola dumerili as
an outgroup. Based on this data, it was concluded thatfish currently named as Seriola lalandi in fact comprise
three species. The authors propose that Seriola lalandiin the Northwest Pacific revert to the name Seriola
aureovittata and the Northeast pacific fish should
revert to the name Seriola dorsalis while the fish in thesouthern hemisphere should remain as Seriola lalandi.

Li, H. 2013. Aligning sequence reads, clone sequences
and assembly contigs with BWA-MEM. arXiv:
1303.3997 [q-bio.GN].
Lyne, M., et al. 2013. metabolicMine: an integrated
genomics, genetics and proteomics data
warehouse for common metabolic diseaseresearch. Database 2013: bat060.
McKenna, A., et al. 2010. The Genome Analysis
Toolkit: a MapReduce framework for analyzing
next-generation DNA sequencing data. Genome
Research 20(9): 1297-1303.
Michael, T. P., and R. VanBuren. 2015. Progress,
challenges and the future of crop genomes.
Current Opinion in Plant Biology 24: 71-81.
Nanda, I., et al. 2002. A duplicated copy of DMRT1 in
the sex-determining region of the Y chromosomeof the medaka, Oryzias latipes. Proceedings of the
National Academy of Sciences of the United Statesof America 99(18): 11778-11783.
Ozaki, A., et al. 2013. Quantitative trait loci (QTL)
associated with resistance to a monogenean
parasite (Benedenia seriolae) in yellowtail (Seriola
quinqueradiata) through genome wide analysis.
PLoS ONE 8(6): e64987.
Palti, Y., et al. 2011. A first generation integrated map of
the rainbow trout genome. BMC Genomics 12: 180.
Rondeau, E. B., et al. 2013. Genomics of sablefish(Anoplopoma fimbria): expressed genes,
mitochondrial phylogeny, linkage map andidentification of a putative sex gene. BMC
Genomics 14: 452.
Skinner, M. E., et al. 2009. JBrowse: A next-generation
genome browser. Genome Research 19(9): 1630-1638.
Smith, R. N., et al. 2012. InterMine: a flexible data
warehouse system for the integration and analysisof heterogeneous biological data. Bioinformatics
28(23): 3163-3165.
Spivakov, M., et al. 2014. Genomic and phenotypiccharacterization of a wild medaka population:
towards the establishment of an isogenic population
genetic resource in fish. G3 4(3): 433-445.
Taylor, J. F. 2014. Implementation and accuracy ofgenomic selection. Aquaculture.
Terova, G., et al. 2014. Proteomic profiling of sea bass
muscle by two-dimensional gel electrophoresis
and tandem mass spectrometry. Fish Physiology
and Biochemistry 40(1): 311-322.
Untergasser, A., et al. 2012. Primer3 – new capabilities
and interfaces. Nucleic Acids Research 40(15): e115.
Zimin, A. V., et al. 2013. The MaSuRCA genome
assembler. Bioinformatics 29(21): 2669-2677.

Westesson, O., M. Skinner, and I. Holmes. 2012.
Visualizing next-generation sequencing data with
JBrowse. Briefings in Bioinformatics 14(2): 172-177.
The authors describe a web-based browser for
displaying genetic sequencing data at the nucleotide
level. JBrowse is the successor to the very successful
GBrowse genome browser. The most significant
advance is the user-side processing of tracks forvisualization, which allows for greater scalability
without significant investment on the server side.
Other improvements include Google maps-stylebrowser interface with smooth transitions. JBrowse
is actively maintained and can be downloaded fromhttps://github.com/GMOD/jbrowse. JBrowse is an
important tool for the visualization of high throughput
sequencing data and should be included in any
aquaculture genomic resources toolkit.
Ficklin, S. P., L. A. Sanderson, C. H. Cheng, M. E.
Staton, T. Lee, I. H. Cho, S. Jung, K. E. Bett, and
D. Main. 2011. Tripal: a construction toolkit for
online genome databases. Database 2011: bar044.
In this work, the authors describe web based
content management system named Tripal. Once a
research group starts to accumulate high throughput
sequencing data such as a genome assembly,
annotation, SNPs, a genetic map, and epigenetic dataetc, Tripal provides a web interface that organizes thisdata in a database for easy display on web pages. It is
widely used by model organisms (FlyBase, WormBase,
Genome Database for Rosaceae, TreeGenes and so on).
The Chado database that serves to store and distributethe data to the webpages can also be used by JBrowse
to visualize genomic data.

ANNOTATED BIBLIOGRAPHY OF KEY
WORKSMartinez-Takashita, N., C. Purcell, C. Chabot, M.
Craig, C. Paterson, J. Hyde, and L. Allen, 2015. A
tale of three tails: cryptic speciation in a globally
distributed marine fish of the genus Seriola.
Copeia 103(2): 357-368.

57

Uses of Genetic Parentage Analysis in Cultured California Yellowtail(Seriola dorsalis)
Matthew Craig1*, Catherine Purcell1, Kevin Stuart2, Mark Drawbridge2, and John Hyde1
NOAA National Marine Fisheries Service, Southwest Fisheries Science Center, 8901 La Jolla Shores Dr., La Jolla,
California, 92037 USA
2
Hubbs Sea World Research Institute, 2595 Ingraham St., San Diego, California, 92109 USA
1

Corresponding author: matthew.craig@noaa.gov
Keywords: microsatellites, egg quality, aquaculture, yellowtail, Seriola

ABSTRACTpelagic genus with species ranging globally in all but
Polar Regions. All species of Seriola are importantcomponents of coastal ecosystems and are favoredspecies for recreational and commercial fishing. With
the rising practice of aquaculture, members of the genus
Seriola have also become a practical and cost-effective
culture species. Three species of Seriola are primarily
cultured for large-scale production: Seriola dumerili,
Seriola lalandi sensu lato, and Seriola quinquradiata.

The genus Seriola is an important group of cultured
species representing a more than USD$1.5 million
industry. With the demand for seafood continuallyrising, this popular group of fishes is a prime candidate
for culture, thus supplementing supply and relieving
harvest pressure on wild populations. In a culture
setting, we have the ability to obtain a complete setof genetic markers for the brood stock, allowing for
determination of the parental contribution to each
spawning event. In order to maximize output andquality of offspring, we explored the various usagesof genetic parentage data in a cultured populationof the California yellowtail, Seriola dorsalis. It wasdetermined that parentage was informative in not
only allowing for an estimate of parental contribution
numerically but was also able to provide linkages to
egg quality and may provide linkages to the presence/
absence of deformities in offspring.

The yellowtail jack (Seriola lalandi sensu lato; Fig.
1) was thought to be a single, cosmopolitan species
with a disjunct distribution. Yellowtail jacks are
now considered to be a complex of at least threemorphologically similar species: S. aureovittata(western Pacific), S. dorsalis (eastern Pacific), and S.
lalandi (southern hemisphere; Martinez-Takeshita
et al., 2015). These species have been commerciallycultured in Japan for decades with production having
recently spread to Australia, New Zealand, Chile,and Mexico. Yellowtail are also likely to become an

INTRODUCTION
As harvest rates from capture fisheries have begun
level off, the demand for seafood and fishery products
continues to increase (FAO 2012). To satisfy thisdemand, aquaculture has become increasingly
important on a global scale, making it one of thefastest-growing animal food-producing sectors,
increasing at an average annual rate of 8.8 % since the1980s (FAO 2012). The number of species in culture
and the number of locations using culture production
has risen substantially in the past two decades (Fraser
et al. 2010; Lorenzen et al. 2012). Although aquaculture
is seen as a way to reduce fishing pressure on natural
populations, it also allows for the introduction of novel
species to the market.

Figure 1. Photograph of Seriola dorsalis taken in California.
(Photograph by B. Gratwicke. Reproduced withoutchanges under Creative Commons License 2.0 https://creativecommons.org/licenses/by/2.0/legalcode. Source:
https://www.flickr.com/photos/briangratwicke/5625034070/
in/photostream/, 14 December 2016.)

Among the numerous species of finfish that are
produced at scales that are relevant to market demand
are jacks of the genus Seriola (Carangidae). Among
all sectors of the fishery, the estimated global market
value of Seriola is $1.5 billion USD. Seriola is a coastal
58

Table 1. Number of male and female California yellowtail
broodstock in the Hubbs-Sea World Research Instituteculture facility, 2013-2016.
Sex
2013
2014
2015
2016
Male
11
19
19
18
Female
8
18
18
13
Total
19
37
37
31

important aquaculture fish in Southern California
within the next few years, where it is also the target ofcommercial and recreational fisheries.
Since 2013, researchers at the NOAA NMFS Southwest
Fisheries Science Center (SWFSC) have been working
in collaboration with researchers at the Hubbs Sea
World Research Institute (HSWRI) to evaluate thegenetic architecture of the HSWRI California yellowtail
production system. In particular, we were interested
in determining the spawning dynamics of this system.
That is, we questioned how successful spawning eventswere distributed among the broodstock population. We
therefore embarked on a study of parentage, examining
the genetic signatures of larvae and matching them tothe most likely female and male brood fish. With thisinformation, important lessons could be learned about
spawning dynamics and quality of production runs
from individual parent pairs. This report documents
some of the uses of genetic parentage analysis in
California yellowtail (CYT).

Genetic Methods
From each spawning event, a random sample of 47
yolk-sac larvae zero days post hatch were sampled
for genetic analysis. DNA was extracted from wholelarvae using a 10% Chelex resin solution incubated at
60°C for 20 minutes followed by 103°C for 25 minutes.
Nine microsatellite loci (Table 2) were used to createa genetic profile for each larva that could then be
matched to previously determined genetic profiles ofthe broodstock (Smith, 2015; Craig, M. unpublisheddata). The polymerase chain reaction (PCR) was used
to amplify the nine loci. PCR reactions consisted of thefollowing in 11 μl volumes: 10X PCR Buffer (670mM
Tris, 166mM (NH4)2SO4, 20mM MgCl2, 100mM
2-mercaptoethanol, pH=8.8), 2 mM each dNTP, 5 mg
bovine serum albumin (BSA), 10 mM of each primer,
1 unit of Taq polymerase, and ~10 μg sample DNA.
Thermal cycling conditions for each reaction were:
94°C for 4 minutes, followed by 35 cycles of 94°C for
30 seconds, annealing (53-59°C; Table 2) 35 seconds,
72°C for 30 seconds, and a final extension at 72°C for 5
minutes. Two multiplex reactions (four loci each) were
performed for eight of the loci and the ninth was run
independently (Table 2). Forward primers for all PCRs
were marked with fluorescent labels for genotyping on
an ABI 3730 genetic analyzer using 1/200 diluted PCR
products and HiDi/Rox size standard.

METHODS
The HSWRI CYT Production System
Hubbs Sea World Research Institute is located on
Mission Bay in San Diego, California. The primary
CYT broodstock were collected from the wild off
the coast of Southern California and are housed in asingle, 140 m3 flow-through tank. Ambient water is
extracted from the adjacent Mission Bay, filtered, andthe flow rate allows for 3-6 turnovers per day. The tankis open to natural light cycling. More information on
the CYT production system may be found in Stuart
and Drawbridge (2013). Spawning occurs during thenormal spawning season for wild fish and the natural
broadcast spawning of CYT occurs several times fromMarch through September. The CYT broodstock has
consisted of varying numbers of male and females
from 2013-2016 (Table 1). Fertilized eggs are collected
and reared under controlled conditions.

Genotypes were scored using GeneMapper v5.0
(company). Allele calls were standardized to whole
numbers and parentage was assessed using Cervus
v. 3.0.6. The most likely parent pair was determinedusing combined LOD scores at 80 % (relaxed) and 95%(strict) confidence intervals with a minimum of fiveloci scored per individual.

Table 2. PCR primers used for California yellowtail microsatellite parentage analysis.

Annealing
Temp (C)SEQU38F/56-TAMN/CCATTACAATTTGTCTCTCCTTATCAACACACGAGCG53
SEQU77F/5hex/CCTACACATGCACATGAACAAGGCTGATACGTCATG
55
SDUGA3DF /56-fam/CTCAACATGAGAGGCAACGGCATGGCTTCATGGGAAGG
55
SDU46F/56-TAMN/GCAGTGTGAGCCATACATTAC CTACAGGACAAAAGCCATT
55
SDU4F/56-fam/GGAAATAGTTTGGATCACGCTGG GGATGCTCAGTGAAGTTGTGC
55
SEQU320F /5hex/GACAGGGTAAGAAACGAAACGACAATGACCAAAGCTGCC
59
SEQU230F /56-fam/CTCCAGAAACGCCACATAAC
AAGCAAACCGCACAAGTAGG59
SDU10F/56-TAMN/CCAAGTCCTCCGCTACTACCAT CCTTGTGGATGACCTGTTTG
59
Locus

Forward

Reverse

SDN06F

/56-fam/GGGTTTGTGCTGTGAGTG

TCCGTCTGTCTTTTCCTGT

59

59

Approx. Fragment
Length (bp)100-145
135-190140-180
220-260
270-31090-140150-165
250-310300-330

RESULTS
From 2013-2015, we genotyped 3170 from 68 spawns,
2789 from 50 spawns, and 3275 larvae from 70 spawns,
respectively. Parentage was assigned for 100% of alllarvae at the strict (95%) confidence level. In all years,
one large female (tag number 083-027-609) contributed
disproportionally high numbers of offspring for each
spawning event, with additional females contributing
far less until 2015. In all three years, males contributedroughly equally per spawning event.

DISCUSSION
The parentage analyses allowed for a careful evaluationof several important factors in the spawning dynamics
for captive CYT at HSWRI. In particular, we wereable to assess proportional contributions by individual
broodstock fish. This allowed for comparisons of two
key factors in the production system: egg quality foreach female and proportion of deformities resulting
from individual parents and parental pairs.
Individual Parental Contribution
In 2013, the broodstock population consisted of eightfemales and 11 males (Table 1). In 2014, an additional 10
females and eight males were added to the population.
In all three years, one large female produced ~40% of
all eggs produced, far out producing other females inthe system. This may be problematic in culture systems
as any dominant producer may not be producing thehighest quality offspring and a lack of genetic diversity
in offspring may result in deleterious effects on future
generations through inbreeding depression.

the viability of her eggs was alarmingly lower in 2015
than in 2013, dropping from 59.9 % to just 9.6%. The
female was near the maximum size and age known for
CYT, which may suggest that age is playing a large rolein determining the quality of the eggs produced.
Offspring Deformities and Growth Rates
Another important aspect of culture production is
ensuring that naturally occurring offspring deformities
are not propagated in a system. Careful manipulationof broodstock populations can prevent this, and ourassessment of parentage yielded some interesting
results. Growth rates of larvae are often variable foreach batch with larvae of the same age being quite
different in size (Fig. 2). There are also several known
deformities in CYT larvae produced in culture
facilities, many of which include incomplete or
abnormal formation of the operculum (Fig. 3).
We compared the proportion of abnormally large andsmall larvae produced by several female CYT in the
HSWRI system to a random sample of all larvae. We
found that two females produced abnormally highproportions of undersized offspring when comparedwith the overall population.
We also compared the frequency of offspring
deformities from male broodstock and from various
parental pairs. In the male population, two individuals
produced disproportionately higher frequencies of all
deformities relative to a random sample. We also foundthat, when paired with any female, the pair produced
disproportionately high numbers of deformities.

Egg Quality
A central concept in fisheries biology is that larger
females produce more and better offspring. Often
termed the BOFFF (Big, Old, Fat, Fecund, Female)
hypothesis, this idea hinges on size as being a limiting
factor for absolute number of eggs and female canproduce, and that younger, smaller females may pay
high energetic costs to produce high-quality eggs.
Few studies have evaluated how this hypothesis forindividuals reaching the end of their lifespan. Our
results challenge this hypothesis and suggest that withsenescence comes a reduction in egg quality.
In all three years examined, one female dominatedthe spawning events in terms of the number of larvae
produced. While the number of offspring produced
was proportionally higher than any other female, thequality of her eggs was among the lowest and declined
each year. In 2013, the total annual fecundity for thisindividual was 1,181,577 eggs/kg/year, while in 2015 it
had dropped to 423,157 egg/kg/year. More importantly,

Figure 2. Growth differences in captive bred California
yellowtail at 31 days post hatch.

60

Martinez-Takeshita, N., C. M. Purcell, C. L. Chabot,
M. T. Craig, C. N. Paterson, J. R. Hyde, and L. G.
Allen. 2015. A tale of three tails: cryptic speciation
in a globally distributed marine fish of the genus
Seriola. Copeia 103: 357-368.
Smith, E. 2015. Evaluation of reproductive strategies
in captive California yellowtail (Seriola dorsalis)using genetic parentage analysis. MS Thesis,
University of San Diego, 135 pp.
Stuart, K. R., and M. A. Drawbridge. 2013. Captive
spawning and larval rearing of California
yellowtail (Seriola lalandi). Aquaculture Research
44: 728-737.

ANNOTATED BIBLIOGRAPHY OF KEY
WORKS
Purcell, C., C. Chabot, M. Craig, N. MartinezTakeshita, L. Allen, and J. Hyde. 2015. Developing
a genetic baseline for the yellowtail amberjack
species complex, Seriola lalandi sensu lato, toassess and preserve variation in wild populationsof these globally important aquaculture species.
Conservation Genetics 16(6): 1475-1488.
The authors present a global description of genetic
variation in the Seriola lalandi species complex.
Overall genetic differentiation among locations, as
revealed by microsatellite data, was highly significant(FST = 0.085, DEST = 0.382, P < 0.001), and pairwise
estimates of divergence derived from mitochondrialand microsatellite data support the presence of four
significantly differentiated populations corresponding
to the N.E. Pacific, N.W. Pacific, S. Pacific, and South
Atlantic. Based on the genetic differentiation detectedin this study, and recently published sequence data,
these populations more accurately reflect the presenceof at least three cryptic species of Seriola. Especiallystrong genetic differentiation between hemispheres
indicates that the equatorial region is a significant
dispersal barrier for yellowtail. This study represents
the broadest geographic investigation of genetic
population structure conducted, to date, for specimensof the S. lalandi complex.

Figure 3. Opercular deformities in captive bred California
yellowtail.

CONCLUSION
Knowledge of the dynamics of captive broodstock
populations can inform culture practices in several
ways. We showed that spawning by individual
members with the CYT culture population at HSWRI
is uneven. We also demonstrated that individual
members of the broodstock population can contributedifferentially to the number of offspring with suboptimal growth rates or deformities. In response tothis work, the female that was producing most of
the eggs, although at low quality, was removed fromthe broodstock population. This manipulation of
the broodstock based on examination of parental
contribution to the offspring produced will ensure thatquantity and quality are maximized in the HSWRI
production system.

Baskett, M., and R. Waples. 2013. Evaluating alternative
strategies for minimizing unintended fitness
consequences of cultured individuals on wild
populations. Conservation Biology 27(1): 83-94.
The authors discuss important considerations for the
maintenance of adaptively positive traits in cultured
populations in order to minimize impact on wild
populations due to accidental or intentional release
into the wild. The authors quantitatively assessed
two strategies: 1. Reduce selection in captivity or 2.
Maintaining a second population to minimize captive/

REFERENCES
FAO. 2012. The state of world fisheries and aquaculture.
Food and Agriculture Organization of the United
Nations, Rome, p 209.
61

wild interactions. They concluded that the appropriate
approach depends on the goals of the culture activity.

This paper demonstrates that the nominal species
Seriola lalandi is actually comprised of three distinct
species. The authors present compelling evidence forgenetic separation of populations. This information is
critical in culture applications for this species in thatwhat were once considered populations of the same
species will now be separated in new broodstock groups.

Martinez-Takashita, N., C. Purcell, C. Chabot, M.
Craig, C. Paterson, J. Hyde, and L. Allen, 2015. A
tale of three tails: cryptic speciation in a globally
distributed marine fish of the genus Seriola.
Copeia 103(2): 357-368.

62

Past, Present, and Future Research on Ostreid Herpesvirus 1
Infections of the Pacific Oyster in Tomales Bay, California
Colleen A. Burge1 and Carolyn S. Friedman2
Institute of Marine and Environmental Technology, University of Baltimore County, 701 E Pratt Street,
Baltimore, MD 21224 USA
2School of Aquatic & Fishery Sciences, University of Washington, Box 355020, Seattle, Washington 98195 USA
1Corresponding author: Not available.
Keywords: Not available.

ABSTRACT
Large-scale sporadic mortalities of juvenile Pacificoyster, Crassostrea gigas have occurred in Tomales
Bay, California, for 20 years. The Ostreid herpesvirus 1(OsHV-1) is the identified causative agent consistently
associated with mortalities, with a confirmed
infectious etiology. OsHV-1 is a global pathogen ofbivalve molluscs, although detection in the UnitedStates is limited to Tomales Bay and nearby Drakes
Bay. OsHV-1 is a member of the Order Herpesvirales,
sharing common morphological criteria withvertebrate herpesviruses, although sequence data
indicates a tenuous relationship. OsHV-1 was classified
as the first member of an invertebrate herpesvirus
family, Family Malacoherpesviridae. Sequence data
indicate that multiple global variants of OsHV-1 exist,
and the virus detected in Tomales Bay is not identicalto any one variant. Elevated water temperatures are
consistently associated with oyster mortalities in
Tomales Bay and may trigger viral replication and/ortransmission of OsHV-1 to naïve juvenile oysters.
Laboratory trials indicate qPCR and RT qPCR canbe used to demonstrate virus replication and gene
expression. Survival of young Pacific oysters in
Tomales Bay is dependent on outplant time, size, andoyster stock, indicating genetic improvement anddevelopment of biomarkers for improved survivalof Pacific oysters infected with OsHV-1 is possible.
Since 2008, an economically devastating increase in
C. gigas mortality in France has been associated witha new genetic variant OsHV-1 µvar, which is lethal
to all life history stages. OsHV-1 µvar continues tospread in Europe, and a similar variant causes losses
in Australia, New Zealand, and Asia. OsHV-1 µvar’s
ability to kill seed and adults heightens concern overthis variant relative to its progenitor, OsHV-1, whichis lethal to larvae and seed only. OsHV-1 resistancehas been shown to confer resistance to µvar. Recent
studies demonstrated the ability to select for resistanceto OsHV-1, and we propose studies to evaluate
selection of resistance to both OsHV-1 µvars and theirprogenitor in U.S. oyster lines.

63

Type 1 Ostreid Herpesvirus (OsHV-1) Variants in Japan
Yoshiko Shimahara1*, Satoshi Watanabe2, Jun Kurita3, Ikunari Kiryu3, Toyohiro Nishioka1, Kei Yuasa2, Morihiko
Kawana4, Takashi Kamaishi5, and Norihisa Oseko2
National Research Institute of Aquaculture, FRA, Tsuiura, Kamiura, Saiki, Oita 879-2602, Japan
National Research Institute of Aquaculture, FRA, Nakatsuhamaura 422-1, Minamiise, Mie 516-0193
3
National Research Institute of Aquaculture, FRA, Hiruda 224-1, Tamaki, Mie 519-0423
4
Hokkaido National Fisheries Research Institute, FRA, Nakanoshima 2-2, Toyohira-ku, Sapporo, Hokkaido 0620922, Japan
5
Headquarters, Fisheries Research Agency, Yokohama, Kanagawa 220-6115, Japan
1

2

Corresponding author: shimahara@affrc.go.jp
Keywords: OsHV-1, Crassostrea gigas, Japan

ABSTRACTINTRODUCTION

Ostreid herpesvirus 1 (OsHV-1) μVar is a variantof OsHV-1 newly reported from France (GenBank
accession no. HQ842610), and it is suspected of being
the causative agent of acute mass mortality eventsof Pacific oysters Crassostrea gigas during summer
in Europe since 2008. OsHV-1 μVar differed fromreference OsHV-1 by nucleotide mutations in the
C2/C6 fragment, including ORF4, and in the IA2/
IA1 fragment, including ORF42/43 (Segarra et al.
2010). Japan is one of the major producers of Pacificoyster. Our previous study indicated that 23 types of
OsHV-1 variant, showing 96% to 99% similarity to thereference OsHV-1, were obtained from Pacific oyster,
kumamoto oyster (C. sikamea) and suminoe oyster (C.
ariakensis) collected in 2007 and from Pacific oyster
collected in 2011 in Japan (Shimahara et al. 2012).
Although 18 variants among the obtained 23 possesseda microsatellite deletion in C2/C6 unique to OsHV1 μVar, the nucleotide sequence was not identical to
the OsHV-1 μVar. In this study, further surveillanceof OsHV-1 variants was conducted for Pacific oysters
in 2012. Nine hundred spat, or juveniles, of Pacificoyster collected in the four main oyster producing
areas were subjected to PCR using the primer pairs C2
and C6 (Renault and Arzul 2001). PCR products were
amplified from 40 out of 900 oysters and 11 different
nucleotide sequences, showing 96% to 99% similarity
to the reference OsHV-1, were obtained. Although
11 sequences among the 13 possessed a microsatellitedeletion unique to OsHV-1 μVar, all PCR products
contained two conserved nucleotides that were sharedwith the reference OsHV-1 and not with OsHV-1 μVar.
Here, we found variable types of OsHV-1 in oysters inJapan, which had different nucleotide sequences fromthat of OsHV-1 μVar in France.

Ostreid herpesvirus 1 (OsHV-1) μVar is a variantof OsHV-1 newly reported from France (GenBank
accession no. HQ842610), and it is suspected of being
the causative agent of acute mass mortality eventsof Pacific oysters Crassostrea gigas during summer
in Europe since 2008. OsHV-1 μVar differed fromreference OsHV-1 by nucleotide mutations in the C2/
C6 fragment, including ORF4, and in the IA2/IA1
fragment, including ORF42/43 (Segarra et al. 2010).
Our previous study indicated that 23 types of OsHV1 variant showing 96% to 99% similarity to thereference OsHV-1 were obtained from Pacific oyster,
kumamoto oyster (C. sikamea) and suminoe oyster (C.
ariakensis) collected in 2007 and from Pacific oyster
collected in 2011 in Japan (Shimahara et al. 2012).
Although 18 variants among the obtained 23 possesseda microsatellite deletion in C2/C6 unique to OsHV1 μVar, the nucleotide sequence was not identical to
the OsHV-1 μVar. Although large-scale mortality
outbreaks, such as those seen recently in Europe, have
not occurred in the shellfish farms where OsHV-1
positive samples were collected, further epidemiologicalstudy must be undertaken to collect more information.
In this study, further surveillance of OsHV-1 variants
was conducted for Pacific oysters in 2012.

MATERIALS AND METHODS
Nine hundred spat, or juveniles, of Pacific oyster werecollected from four main oyster producing areas,
including Miyagi, Hiroshima, Mie and Okayama (Fig.
1), and subjected to DNA extraction with Maxwell 16
Tissue DNA Purification Kit (Promega, Madison, WI,USA) following the manufacturer’s instructions. PCRtargeting the C2/C6 fragment including ORF4 was

64

Basic alignments ofnucleotide sequenceswere made using
GENETYX-MAC software(GENETYX, Tokyo,
Japan). The sequences
obtained were comparedwith those of variants
recently reported by
Renault et al. (2012),
reference OsHV-1(AY509253) (Davidson
et al. 2005), and OsHV-1
μVar (HQ842610) (Segarra
et al. 2010).

RESULTS ANDDISCUSSION
The C2/C6 product ofapproximately 700 bp was
amplified from 40 outof 900 samples in 2012
(Table 1). Although thedetection rate was lower
than those investigatedpreviously, the C2/C6
product was detected in
DNA extracted from spattaken from all samplingareas. The nucleotide
sequences of the C2/C6
Figure 1. Map of Japan showing the four Prefectures where oyster samples were
products were polymorphic
collected.
and 11 different nucleotide
sequences, JPType 1, 2, 6,
9,
27,
28,
29,
30,
31,
32
and
33
(Fig. 2), were obtained.
performed using the primer pairs C2: 5’-CTC TTT
Two
types
of
OsHV-1
weresimultaneously
present in
ACC ATG AAG ATA CCC ACC-3’ and C6: 5’-GTG
twoanimals
collected
inMiyagi.
One
animalcontained
CAC GGC TTA CCA TTT TT-3’ in a final reaction
JPType
2
and
9,
while
the
other
contained
JPType6volume of 20 μL, as described by Renault and Arzul
and
33.
The
11
sequences
were
96%
to
99%
homologous(2001). The PCR reaction mixture contained 0.5 U
to the reference OsHV-1 (AY509253). Althoughof TaKaRa Ex Taq Hot Start Version (TaKaRa, Shiga,
10 sequences among the obtained 11 possessed aJapan), 2 μL of 10x reaction buffer, 0.5 pmol of dNTP’sand 20 pmol of each primer. One microliter of template microsatellite deletion unique to OsHV-1 μVar, all PCR
products contained two conserved nucleotides that were
DNA was added to each mixture. The programoshared with the reference OsHV-1 and not with OsHV-1
consisted of one cycle of denaturation at 94 C for 10omin, followed by 40 amplification cycles at 94 C for 30 μVar. OsHV-1 μVar, which is one of the major concerns
for oyster producers in France at present, has not yet
sec, 63oC for 30 sec, and 72oC for 30 sec, with a finalobeen found in Japan. Furthermore, the nucleotide
extension step of 72 C for 7 min. PCR products weresequences obtained in this study were not identical topurified using Agencourt AMpure (Beckman Coulter,
those previously found in France, Ireland, the United
Danvers, MA, USA) following the manufacturer’s
States, New Zealand, and China (Renault et al. 2012;
instructions and sequenced directly using the BigDye
Martenot et al. 2011, 2012).
Terminator Kit v3.1 (Applied Biosystems, CA, USA).
Sequencing reactions were purified with Agencourt
Of the 23 variants of OsHV-1 previously detected in
CleanSEQ (Beckman Coulter, Danvers, MA, USA)
Japan (Shimahara et al. 2012), four variants, JPTypefollowing the manufacturer’s instructions and loaded
into an ABI PRISM 3130 xl Genetic Analyzer (Applied 1, 2, 6, and 9, were persistently present in 2012 (Table2). The four variants were present in at least two
Biosystems, Foster City, CA, USA).

65

Figure 2. C2/C6 sequence alignment of OsHV-1 variants obtained in this study (JPType 1, 2, 6, 9, 27, 28, 29, 30, 31,
32 and 33) compared with those of reference OsHV-1 (AY509253) and OsHV-1 μVar (HQ842610). The locations of the
microsatellite zone and the initiation codon for ORF 4 are indicated. OsHV-1 μVar is characterized by a deletion of 12
consecutive nucleotides in the microsatellite zone, two non-synonymous substitutions, and the other mutations in thisC2/C6 fragment. The major deletion in the microsatellite zone, and the substitutions of the two nucleotides in ORF 4, areframed. The substitutions of two nucleotides in ORF4 are conserved in all JPTypes found in the present study.

66

geographic areas in a series of observations in 2007,2011 and 2012. It was considered that JPType 1, 2, 6,
and 9 had spread to different areas by translocation of
infected spat and continuously infect oysters in eacharea, probably due to the slightly higher infectivity
than the other variants. However, infections by thesevariants do not seem to be expanding either temporally
or geographically. The distribution of the OsHV-1
variants were different from that in France, where
OsHV-1 μVar has been rapidly increased and dominant
after the outbreaks (Segarra et al. 2010). In addition,
large-scale mortality outbreaks, such as those seen
recently in Europe, have not occurred in the shellfish
farms where OsHV-1 positive samples were collected.
It is considered that the OsHV-1 variants in Japan may
not be as pathogenic as OsHV-1 μVar in France.

Martenot, C., S. Fourour, E. Oden, A. Jouraux, E.
Travaille, J. P. Malas, and M. Houssin. 2012.
Detection of the μVar in the Pacific oyster
Crassostrea gigas before 2008 in France anddescription of two new microvariants of theOstreid Herpesvirus 1 (OsHV-1). Aquaculture 338341: 293-296.
OIE. 2017. Infection with Ostreid Herpesvirus 1
Microvariants. Manual of Diagnostic Tests for
Aquatic Animals. OIE, Paris.
Renault, T., and I. Arzul. 2001. Herpes-like virus
infections in hatchery-reared bialve larvae in
Europe: specific viral DNA detection by PCR.
Journal of Fish Disease 24: 161-167.
Renault, T., P. Moreau, N. Faury, J-F. Pepin, A. Segarra,
and S. Webb. 2012. Analysis of clinical Ostreid
Herpesvirus 1 (Malacoherpesviridae) specimentsby sequencing amplified fragments from three
Since OsHV-1 μVar had a high impact on the oyster
virus genome areas. Journal of Virology 86: 5942aquaculture industry in France, OsHV-1 microvariants,
5947.
including OsHV-1 μVar, were listed in aquatic animal
Renault, T., and B. Novoa. 2004. Viruses infecting
diseases by the World Organisation for Animal Healthbivalve molluscs. Aquatic Living Resources 17:(OIE). OsHV-1 microvariants are termed as “OsHV-1,
397-409.
which have sequence variations in a microsatellite locus
upstream of the ORF4 and in ORF4 itself and ORF42/43 Segarra, A., J. F. Pepin, I. Azul, B. Morga, N. Faury
and T. Renault. 2010. Detection and description
when compared with the reference type (AY509253)”of a particular Ostreid herpesvirus 1 genotype(OIE 2017). It is uncertain if the Japanese variants areassociated with massive mortality outbreaks ofincluded in OsHV-1 microvariants, since ORF42/43
Pacific oysters, Crassostrea gigas, in France inwere not analyzed in this study. However, the functions
2008. Virus Research 153: 92-99.
of the ORF4 and ORF42/43 are not well determined,
Shimahara, Y., J. Kurita, I. Kiryu, T. Nishioka, K. Yuasa,
and it is unknown if they reflect pathogenicity of
M. Kawana, T. Kamaishi and N. Oseko. 2012.
OsHV-1. Although isolation and cultivation of OsHVSurveillance of type 1 ostreid herpesvirus (OsHV1 has not been successful due to the lack of suitable1) variations in Japan. Fish Pathology 47: 129-136.
cell lines (Renault and Novoa, 2004), pathogenicity of
OsHV-1 μVar was determined by using the infectedanimals (Segarra et al. 2010). Experimental infection
ANNOTATED BIBLIOGRAPHY OF KEY
with OsHV-1 will be conducted to determine theWORKSpathogenicity of the Japanese variants in a future study.
Shimahara, Y., J. Kurita, I. Kiryu, T. Nishioka, K. Yuasa,
ACKNOWLEDGMENTS
M. Kawana, T. Kamaishi and N. Oseko. 2012.
Surveillance of type 1 ostreid herpesvirus (OsHVThe authors are grateful to the Prefectures of1) variations in Japan. Fish Pathology 47: 129-136.
Hiroshima, Mie, Miyagi, and Okayama for providing
the oysters used in the present study. This study
Ostreid herpesvirus 1 (OsHV-1) μVar is a variant
was supported by grants from the Food Safety andof OsHV-1 that is suspected of being the causative
Consumer Affairs Bureau, Ministry of Agriculture,agent of acute mass mortality events of Pacific oysters
Forestry, and Fisheries of Japan.
during summers in Europe since 2008. The authors
investigated a distribution of OsHV-1 variants in
six main oyster-producing areas in Japan by PCR
REFERENCES
to determine whether OsHV-1 μVar was present inJapan. PCR products were amplified from 123 out of
Davison, A.J., B.L. Trus, N. Cheng, A.C. Steven, M.S.
1,714 oysters, and 23 different nucleotide sequences
Satson, C. Cunningham, R.M. Le Deuff, and T.
were obtained. Although 18 sequences among the 23
Renault. 2005. A novel class of herpesvirus withbivalve hosts. Journal of General Virology 86: 41-53. obtained possessed a microsatellite deletion uniqueto OsHV-1 μVar, all PCR products contained two
Martenot, C., E. Oden, E. Travaille, J. P. Malas, andconserved nucleotides that were shared with reference
M. Houssin. 2011. Detection of different variants
OsHV-1 and not OsHV-1 μVar in ORF4. It was foundof Ostreid Herpesvirus 1 in the Pacific oyster,that variable types of OsHV-1 distribute throughout
Crassostrea gigas between 2008 and 2010. Virus
Japan, but their nucleotide sequences were not
Research, 160: 25-31.
completely identical to OsHV-1 μVar.
67

Epigenetic Considerations in Aquaculture
Mackenzie Gavery* and Steven Roberts
School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195
Corresponding author: mackenzie.gavery@noaa.gov
Keywords: epigenetics, DNA methylation, aquaculture, shellfish

ABSTRACThistone modifications and non-coding RNA activity,
influence gene expression primarily through local
modification of chromatin. Unlike DNA, epigenetic
Epigenetics has garnered considerable attention inmarks can be directly influenced by the environment,
many aspects of agricultural production, particularly
and because of this, have been shown to be important
where environmental conditions can be manipulated
mediators of phenotypic responses to environmental
or natural variation exists. In the past decade,signals (Fig. 1). For example, in mammals, nutrition
technology and our fundamental knowledge of(Weaver et al. 2004), exposure to toxins (Dolinoy ettranscriptional regulation has dramatically increased
al. 2006), and photoperiod (Azzi et al. 2014) have allto where we are now able to characterize numerous
been associated with changes in DNA methylation
aspects of epigenetic variation in aquaculture species.
This review will introduce key concepts and definitions and concomitant changes in phenotype. Fish, whileof epigenetic mechanisms including DNA methylation, less studied, show similar environmental sensitivity
in DNA methylation patterns (Wang et al. 2009;
histone modifications and non-coding RNA, review
Strömqvist et al. 2010; Campos et al. 2013). Many
the current understanding of epigenetics in both fish
environmentally-induced epigenetic changes areand shellfish and propose key areas of aquaculture
transient, while some may persist over the course of an
where epigenetic knowledge could be applied. Basedorganism’s lifetime (Weaver et al. 2004; Dolinoy et al.
on aspects of life history and husbandry practices
2006; Heijmans et al. 2008). In certain cases, epigenetic
in aquaculture species, application of epigenetic
changes can be transgenerationally inherited
knowledge could have a significant impact on
productivity and sustainability of aquaculture practices. (Guerrero-Bosagna et al. 2010; Manikkam et al. 2012).
As such, it is important to understand the nature andConversely, there is the possibility that elucidating thefunction of these mechanisms and their influence onrole of epigenetic mechanisms in aquaculture species
phenotype in fish and shellfish.
may upend traditional assumptions about selection
practice. Ultimately, there are still many unansweredquestions regarding how epigenetic mechanisms might Interest in epigenetics has been gaining ground in
agricultural science for crops (Ong-Abdullah et al.
be leveraged in aquaculture.
2015; Álvarez-Venegas and De-la-Peña 2016) and,more recently, livestock (Goddard and Whitelaw
INTRODUCTION
2014; González-Recio 2015), but less is known about
epigenetic mechanisms in economically valuable
Maintaining and improving aquaculture production
aquaculture species. Considering that a majority ofrequires an understanding of genetic and physiological aquaculture takes place in open or natural systems
mechanisms that control desired traits. An
subject to environmental change, it is important tounderstanding of these mechanisms has led to theconsider the role of epigenetics. This is particularly
development of pioneering biotechnological methods
the case now that tools and resources are available
that have important applications. For example,
to study these important molecular mechanisms. In
molecular markers are used in broodstock selection
recent years, studies in species ranging from salmonids
and transcriptomic studies have been used to improveto sea bass to oysters and mussels are providing theenvironmental conditions to decrease physiologicalfirst evidence that epigenetics is associated withstress in animals. Recently, interest in epigenetics hascommercially important traits in aquaculture species.
surged within the agricultural community as it becomes In sea bass and half smooth tongue sole, temperatureclearer that epigenetic mechanisms can provide a
induced sex-determination has been associated withmeasurable link between environment and phenotype.
changes in DNA methylation (Navarro-Martin 2011;
Shao et al. 2014). In salmonids, there is some evidence
Epigenetics refers to heritable processes that alterthat changes in DNA methylation are associated withgene activity without manipulating the underlying
variation in life history phenotypes including early
DNA sequence (Jablonka and Lamb 2002). Epigenetic
male maturation (Morán et al. 2011), smoltification
mechanisms (or ‘marks’), including DNA methylation, (Morán et al. 2013), and anadromy (Baerwald et al.
68Figure 1. Schematic representation of epigenetic influence on phenotype. Markers used for characterizingorganismal variation are listed.

DNA Methylation

2016). Recent studies in European sea bass and rainbow
trout examined the role of epigenetics in mediating
phenotypic responses to various aspects of diet (Terova
et al. 2016; Marandel et al. 2016; Panserat et al. 2017).
In Pacific oysters, the role of epigenetics in mediating
effects of temperature on oyster physiology has been
investigated (Fellous et al. 2015). As is described below,
the relationship between epigenetics and phenotype isless clear in shellfish as opposed to finfish.

DNA methylation refers to the enzymatic addition ofa methyl group to a cytosine residue in DNA, which
occurs almost exclusively at CpG dinucleotides (i.e.
a cytosine located 5’ of a guanine) in animals. The
enzymatic machinery supporting DNA methylation
includes a family of DNA methyltransferases (DNMTs)
including the maintenance methyltransferase DNMT1(responsible for copying pre-existing DNA methylation
patterns to the new strand during mitosis) and thede novo methyltransferases DNMT3A/3B. DNA
methylation is known to be repressive when locatedin promoters of genes through associations with otherDNA binding proteins or through physical blockingof transcription factors (Bell and Felsenfeld 2000);
however, DNA methylation located in gene bodies is
associated with high levels of expression (Jones 1999).
Therefore, although typically associated with silencing,
the regulatory role of DNA methylation is specific to
the genomic context. In mammals, DNA methylation
plays important roles in providing genomic stability
through repression of transposable elements (Maloisel
and Rossignol 1998), genomic imprinting (Belland Felsenfeld 2000), and dosage compensation(Csankovszki et al. 2001). DNA methylation is also
important for cell-type differentiation and embryonicdevelopment (Li et al. 1992). DNA methylation is
the most well studied epigenetic mechanism, where

This mini-review will introduce key concepts anddefinitions of epigenetic mechanisms, briefly review
the literature as it pertains to the nascent field of
epigenetics in aquatic species and highlight key aspectsof aquaculture that would benefit from a deeper
understanding of the role of epigenetics. There havebeen excellent reviews published recently regarding
epigenetics, primarily DNA methylation, and various
aspects of finfish aquaculture (e.g. Li and Leatherland
2013; Moghadam 2016) and those will be highlighted
where appropriate.

WHAT IS EPIGENETICS?
The following section will briefly describe specificepigenetic marks and review where we stand in termsof understanding (or lack of understanding) the
relationship between epigenetics, environment andphenotypes in aquaculture species.
69

a majority of studies have been done in plants andmammals. For instance, in these systems, it has beenshown DNA methylation is sensitive to external factors
including nutrition (Dolinoy et al. 2006) exposure totoxins (Dolinoy et al. 2007), and photoperiod (Azziet al. 2014). It is important to note that the meiotic
transmission of DNA methylation patterns, thus
the opportunity for transgenerational epigenetic
inheritance through DNA methylation, is rare in
mammals, which undergo extensive DNA methylation
reprogramming in early embryos (Daxinger andWhitelaw 2012). As you will see in the following
sections, it is unclear if and to what extent DNA
methylation resetting occurs in fish and shellfish.

replaced with protamines, suggesting that these marks
may have a role transferring epigenetic information to
the embryo (Brykczynska et al. 2010; Wu et al. 2011).
Non-coding RNA
Although a large majority of the genome istranscribed, only a small portion of these transcripts
code for protein. These non-coding transcripts,
originally regarded as ‘junk’, are now recognized fortheir role in modulating gene expression and are
categorized broadly as non-coding RNA (ncRNA).
There are two major classes of ncRNA: long ncRNA(> 200 nt) and small ncRNA (< 200 nt), which
includes micro RNA (miRNA), short interfering
RNA (siRNA), and piwi-interacting RNA (piRNA).
Small ncRNAs are highly conserved and their majormechanism of action is to inhibit protein synthesisby blocking or degrading primary transcripts (seereview by Castel and Martienssen 2013). Long ncRNAs(lncRNA) by contrast are less conserved and havecomplex mechanisms of action that may work either
in cis or trans (see review by Wang and Chang 2011).
Non-coding RNAs have important functions in gene
expression and have demonstrated to be important
regulators of genome stability, environmental plasticity
and embryonic development (Mercer et al. 2009;
Bizuayehu et al. 2014). Generally speaking, ncRNA
molecules are considered ‘epigenetic’ in the traditional
sense because they interact with other epigenetic
mechanisms, such as DNA methylation and histone
modifications, to silence or activate various parts of the
genome (Peschansky and Wahlestedt 2014).

Histone Modifications
Chromatin is a dynamic structure that supports boththe packaging of the genome into the nucleus, andimportantly, the regulation of genes and other genomic
regions via changes in DNA accessibility (Cheung etal. 2000). The basic repeating structure of chromatinis the nucleosome, which consists of DNA wrappedaround histone proteins. These histones can be posttranslationally modified at their N-terminal tails
altering the degree of which DNA can be wrappedaround them resulting in either euchromatin (referring
to open chromatin that is accessible to transcription
factors, RNA polymerase II (Pol II) and other DNA
binding proteins that support gene expression) or
heterochromatin (referring to tightly packed DNA
associated with transcriptional silencing). These states
are dependent on the type (i.e. acetylation, methylation,
phosphorylation, ubiquitylation) and location (e.g.
various lysine or arginine residues) of the modification(for a complete list of modifications, see review by
Lawrence et al. 2016). These various modifications
can exist in bivalent and multivalent states with eachother and have led to the much debated existence ofthe ‘histone code’ (Jenuwein and Allis 2001). These
modifications are enabled by various families of
enzymes including histone acetylases (HATs), histone
deacetylases (HDACs), histone methyltransferases(e.g. HMT) and histone demethylases (e.g. Jumonji
and Lys-specific demethylase). Modifications areimportant for regulation of gene activity but also
have roles in DNA repair, replication, and cell fate/
determination (see reviews by Lawrence et al. 2016;
Martin and Zhang 2005; Eberharter and Becker2002). The enzymatic machinery responsible for thesemodifications are highly regulated during embryonicdevelopment (Lin and Dent 2006), and like DNA
methylation, can be altered by various environmental
conditions (Chinnusamy and Zhu 2009). Less isknown about the mitotic and meiotic persistence ofhistone modifications, but interestingly, it has beenshown in both mammals and zebrafish that certain
modified histones are non-randomly retained during
spermatogenesis when the majority of these proteins are

TAXA SPECIFIC PATTERNS
Epigenetic mechanisms and particularly DNA
methylation have been the focus of numerous studies
in both fish and shellfish in recent years. However, amajority of what we know about epigenetics in animals
comes from studies done in mammals and care should
be taken when generalizing functions from mammals
to fish and shellfish. Although there are certainly
similarities (e.g. DNA methylation patterns are very
similar across all vertebrates), there are also importantdifferences (e.g. invertebrate DNA methylation patterns
are very different from vertebrates). This section will
focus on foundational information about epigenetic
marks in fish and shellfish and highlight bothsignificant gaps in our understanding as well as noting
differences from well-studied mammalian systems.
DNA Methylation in Fish and Shellfish
DNA methylation is the most well-studied epigenetic
mark among fish and shellfish. Both fish and shellfish
have genes present that encode basic methylation
machinery (e.g. DNMTs and MBDs) and DNA
70methylation is present in all species examined todate. However, there are striking differences in
DNA methylation patterns between vertebrates andinvertebrates as well as significant unknowns in termsof DNA methylation resetting in both fish and shellfish.

methylation does appear to be associated with gene
regulation in shellfish. In the Pacific oyster, high levelsof methylation in gene bodies (and putative promoter
regions) were associated with high levels of expression(Gavery and Roberts 2013; Olson and Roberts 2014).
Interestingly, genes with limited methylation in oysters
have variability in exon-specific expression acrosstissue types, indicating that hypomethylation allows
increased plasticity (Gavery and Roberts 2013). While
more studies are needed to quantify this relationship,
there are significant implications for improving
resilience in shellfish - particularly if DNA methylation
patterns are heritable. There are few studies on
heritability of DNA methylation patterns in shellfish,
however, a small study looking at methylation statesin parents and larvae found significant clustering of
methylation patterns within families, indicating thatmethylation patterns differ significantly dependingon the male parent (Olson and Roberts 2015). Morerecently, Rondon et al. (2017) have shown parental
herbicide exposure influences progeny DNA
methylation patterns in oysters.

Considerable work has been done on understanding
patterns and functions of DNA methylation in modelfish species such as zebrafish and medaka, withincreasing information on DNA methylation in nonmodel species. For example, a recent review by Metzger
and Schulte (2016) extensively covers the current
state of knowledge of DNA methylation patterns andfunctions in marine fish. Generally speaking, DNA
methylation patterns are similar across all vertebrates
which exhibit a ‘global’ DNA methylation pattern,meaning majority of CpGs are methylated with the
exception of regions of DNA with high CpG content
referred to as CpG islands. In comparison to mammals,
however, global DNA methylation levels are higher infish though the significance of this remains unclear(Jabbari 1997; Zhang et al. 2016). The function of
DNA methylation also appears to be similar acrossvertebrates with the exception of a role in genomic
imprinting which is unique to mammals (Potok et al.
2013). One outstanding question concerns the extent
of DNA methylation resetting in fish. While mammals
undergo extensive DNA methylation reprogrammingin the early embryo (Daxinger and Whitelaw 2012),
it is unclear to what extent DNA methylation
reprogramming occurs in fish (Potok et al. 2013;
Jiang et al. 2013). A recent study, discussed in moredetail in the following section, shows clear evidenceof transgenerational inheritance of environmentallyinduced DNA methylation patterns in a fish, suggestingat least some of the genome escapes putative resetting
between generations (Shao et al. 2014). Certainly
there is a need for more detailed studies on the extent
of DNA methylation resetting in fish, particularly incultured aquatic species. In addition, more studies
should examine the potential meiotic inheritance ofenvironmentally-induced epigenetic changes.

Histone Modifications in Fish and Shellfish
Histone modifications and their dynamics havebeen studied in zebrafish where evidence indicatesmodifications are conserved among vertebrates.
Functional analysis of histone acetylation in zebrafish
confirms its role in embryogenesis (Vastenhouw andSchier 2012) and in tissue regeneration (Stewart etal 2009). In terms of meiotic inheritance, zebrafish
show multivalent modified histone retention in
sperm similar to mammals (Wu et al. 2011). Studies
examining histone modification in non-model fish
are rare, though recent studies in rainbow trout andEuropean sea bass indicate that diet influences bulk
histone modification levels and can regulate theexpression of associated enzymes (Marandel et al. 2016;
Terova et al. 2016; Panserat et al. 2017).
Histone modifications are less studied in shellfish, butwork by Fellous et al. (2014) identified homologs ofJumonji histone demethylase genes (Jmj) in Pacificoysters that, similar to vertebrates, were regulated during
embryonic development. A subsequent study showed thatboth bulk histone methylation levels and the expressionof histone demethylases were responsive to temperatureduring development, suggesting a role for histone
modifications in mediating the physiological responsesof oysters to temperature (Fellous et al., 2015). Histones
are not replaced with protamines in bivalve sperm as they
are in mammals, rather they are replaced with various
sperm nuclear basic proteins that may be protmaine- or
histone-like (Ausio 2006). Additional research will be
required to determine to what extent histones and theirmodifications are retained in bivalve sperm, shedding
light on the potential transmission of epigenetic
information from parent to offspring in bivalves.

Invertebrate DNA methylation patterns are strikingly
different from vertebrates. Whereas vertebrates exhibita global pattern of DNA methylation, invertebrates
show a ‘mosaic’ pattern with stretches of methylated
DNA punctuating regions of unmethylated DNA(Tweedie et al. 1997; Simmen et al. 1999). DNA
methylation was examined genome-wide in the
Pacific oyster where it was reported that 15% of CpGs
were methylated in a somatic tissue, whereas 60-70%
of CpGs are methylated in mammals (Gavery andRoberts 2013). In oysters, as in other invertebrates, themethylated fraction tends to consist of gene bodies,while other genomic regions exhibit less methylation.
Unlike vertebrate species, transposable elements
show surprisingly little methylation in oysters andother invertebrate species (Simmen et al. 1999; Fenget al. 2010; Zemach et al. 2010). Functionally, DNA
71

Non-coding RNA in Fish and Shellfish

There are several lines of evidence for developmental
programming in fish, and for an excellent review see
Jonnson and Jonnson (2014). Traits associated withearly environmental conditions include metabolism,growth, sex determination, fecundity, and behavior(Jonnson and Jonnson 2014). There are also several
examples where environmental memory has been
described in shellfish. In some instances, this occurs
within a generation and in other cases there istransmission of information from parents to offspring.
Within generation environmental memory has been
described in Olympia oysters where early larval
exposure to ocean acidification impacted juvenile
traits (Hettinger et al. 2013). Adult Manila clams
exposed to low pH during gonadal maturation havefaster growing offspring compared to controls (Zhaoet al. 2017). In the Sydney rock oyster, larvae producedby parents incubated under low pH conditions
are larger and develop faster in low pH conditions
and also have higher fitness as adults (Parker et
al. 2012, 2015). In addition to water chemistry,disease is another significant concern in shellfish
aquaculture. There is increasing evidence to suggest
prior exposure to immune challenge can increase
response later in life and that this environmental
memory can be transmitted to offspring. Green etal. (2016) demonstrated offspring of Pacific oyster
parents treated with poly(I:C) possess enhanced
protection against Ostreid herpesvirus type I infection.
The mechanism(s) responsible for providing thismemory are not fully understood in cultured species
and arguably not required to improve aquaculture
production, though we would suggest that elucidating
the epigenetic mechanisms involved could increase thedegree and breadth of improvement.

A majority of studies on non-coding RNAs in fish andshellfish focused on miRNAs, including importantaquaculture species [e.g. Atlantic salmon (Bekaert etal. 2013; Andreassen et al. 2013) and rainbow trout(Juanchich et al. 2016)]. There are several examples
of examining miRNAs in a physiological context
including: maternal transcripts in the egg (e.g. Ma
et al. 2012), immune function (e.g Andreassen et al.
2017) and embryonic development (Bizuayehu et al.
2015). There is less information about other types ofsmall ncRNA, except in zebrafish where, for example,
piRNA have been shown to silence transposable
elements in gametes, functioning similarly as inmammals (Houwing et al. 2007). Recently there havebeen several descriptions of long non-coding RNAsin salmonids including associations between lncRNA
expression and disease in both Atlantic salmon andrainbow trout (Boltaña et al. 2016; Valenzuela-Miranda
et al. 2016; Paneru et al. 2016).
Predictably, non-coding RNAs are less investigatedin shellfish, though generally speaking, miRNAs andtheir biogenesis are highly conserved over evolutionary
scales (Wheeler et al. 2009). As such, genes for miRNAbiogenesis have been detected in bivalve species(Rosani et al. 2016). With respect to long non-coding
RNAs, researchers have reported an association withlarval development in the Pacific oyster (Yu et al. 2016).

POTENTIAL AQUACULTURE
APPLICATIONS
Environmental Manipulation

Two relevant cases for aquaculture where theepigenetic mechanisms have been described involvesex determination in fish. In European sea bass
(Dicentrarchus labrax), exposure to high temperature in
early development is associated with a higher proportionof phenotypic males (Navarro-Martin et al. 2009). In
work done by Navarro-Martin et al. (2011) this early hightemperature exposure was associated with increased
DNA methylation in the promoter of the aromatasegene (cyp19a1a) in adults. Furthermore, the authors
showed that in vitro methylation of the aromatasepromoter was sufficient to suppress transcription of
the gene. More recently, the commercially important
half-smooth tongue sole (Cynoglossus semilaevis) wasused as a model to investigate the role of epigenetic
regulation in environmental sex determination.
Using genome-wide DNA methylation profiling, theinvestigators showed that pseudomales (generated byexposing genetic females to high temperature during asensitive developmental window) exhibit methylation
patterns consistent with genetic males, both of which
differ from the methylome of normal females. Excitingly,

Given what we know about environmental influenceson epigenetic mechanisms in fish and shellfish
and the relationship with phenotype, one avenue
where epigenetics and aquaculture could intersect
is environmental manipulation. In addition tomechanisms described in the previous section, there
is also the fundamental concept of “developmental
programming”. Developmental programming suggeststhat environmental conditions experienced in early-life
influence phenotypes later in life and this has gained
momentum in human research (e.g. Gluckman et al.
2008). In other words, developmental programming
offers an environmental memory that could be
beneficial in controlled aquaculture settings. However,in some cases embryos and juveniles are not raised in
the same environmental conditions as the adults. For
example, hatchery-reared salmon or hatchery-reared
bivalve juveniles placed into a natural setting for growout. Identifying sensitive periods for environmental
memory could offer a “programming window” that
could be leveraged in husbandry practices.
72

it was reported that global methylation patterns are
inherited by F1 pseudomale offspring generated bycrosses between pseudomales and normal females,suggesting transgenerational epigenetic inheritance ofenvironmentally-induced sex reversal in this species(Shao et al. 2014). Controlling sex in fish broodstockis certainly a priority for aquaculture and these studies
shed light on the epigenetic mechanisms that could beleveraged in future work. More work would be needed toestablish the degree of mechanism conservation acrossspecies exhibiting environmental sex determination.

It should also be noted that epigenetics might makegenetic selection more challenging. Many organisms
have the potential to generate new genetic variation in
response to stressful conditions through modulation of
epigenetic marks associated with transposable elements(Dowen et al. 2012; Yu et al. 2013; reviewed by Rey et al.
2016). Transposable elements, or “jumping genes”, areregions of repetitive DNA that can move and amplify
their copy number in the host genome. In the model
plant Arabidopsis, the genomic response to bacterial
challenge was a global reduction of DNA methylation
and reactivation of previously silent TEs associatedwith defense genes (Yu et al. 2013). It is interesting toconsider that in invertebrates, shown specifically in
C. gigas, that TEs are not preferentially methylated(Gavery and Roberts 2013; Olson and Roberts 2015). It
has been hypothesized that the lack of TE silencing by
DNA methylation may indicate pressure to generate
and maintain genetic diversity in a species that
inhabits heterogeneous environments (Gavery andRoberts 2014). This means that in theory, if culture
conditions become stressful, shellfish could respond bymodulating transposable element expression to create
new genetic variation (Rey et al. 2016), thereby having
the unintended consequences of “erasing” phenotypic
gains made through selective breeding.

Nutrition and feeding are important aspects ofaquaculture production, and research has shown
memory of early-life nutritional conditions
influences key phenotypic traits later in life. In
mammals, nutritional status of the mother can
predispose offspring to adult onset metabolic disease
and mounting evidence suggests that epigenetic
mechanisms are involved (reviewed by Vickers etal. 2014). In fish, rainbow trout swim-up fry fed
a plant based diet for three weeks showed higher
growth rates, feed intakes, and feed efficiencies
when challenged again with a plant based dietafter seven months of grow out on a fishmeal/fish oil diet (Geurden et al. 2013). Interestingly, ina follow up study, transcriptomic analyses suggestthat epigenetic mechanisms may be involved in this
response (Balasubramanian et al. 2016). In addition,a study looking at vitamin supplementation at first
feeding in rainbow trout identified changes in global
methylation and histone modification four months
after the supplementation had ended, despite noobserved phenotypic responses (Panserat et al.
2017). Collectively, these studies provide the first link
between early-environmental exposures and epigenetic
mechanisms in aquaculture species.

CONCLUSIONS
Epigenetics has the potential to change the way
we think about how a phenotype is generated andmaintained. Through a greater understandingof DNA methylation, histone modifications andncRNAs we can functionally annotate genomes,
better predict phenotypic outcomes of earlyenvironmental exposures, and possibly select on
epigenetic markers. With careful experimental designand special considerations for epigenetic differences
between taxa (see Lea et al. 2016), the aquaculturecommunity is primed to begin to integrate epigenetics
into husbandry practices. The concepts and ideas
of epigenetics provide an attractive lens throughwhich to consider manipulation of traits throughenvironmental memory or selection of beneficial traits
based on epigenetic markers. It is also important toconsider that epigenetics may also function to disrupt
predictable, robust phenotypes through the creation ofnew, unexpected variation.

Epigenetic Selection
Beyond understanding how early environmental
exposure can be used for improving aquaculture,
there is the possibility epigenetic markers could be
integrated into broodstock selection. This is plausible
as in one important agriculture commodity, oil palms,
it has been shown that a critical trait, oil content, canbe epigenetically selected for (Ong-Abdullah et al.
2015). While there is much more we need to learn withregard to desired phenotypes and epialleles, work suchas this demonstrates value in including epigenetics inassociation studies. Furthermore, Patel et al. (2013)
have shown in a clinical study that integrating both
genetic (SNP) and epigenetic (DNA methylation)markers in genome wide association studies improved
associations with a phenotype (i.e. diabetes). The
influence of epigenetics, specifically DNA methylation,
on estimating breeding values for quantitative traits
has been considered recently for finfish aquaculture ina review by Moghadam et al. (2015).

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ANNOTATED BIBLIOGRAPHY OF KEY
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datasets and a positive relationship between intragenic
methylation and gene expression levels was identified.
These data suggest that DNA methylation patterns may
play a role in regulating gene expression in molluscs.

Gavery, M.R., and S.B. Roberts. 2014. A context specificrole for DNA methylation in bivalves. Briefings inFunctional Genomics doi:10.1093/bfgp/elt054.
A review of current knowledge of DNA methylation inbivalves. A primary conclusion is that the functionalrole of the gene could influence the role of DNA
methylation in influencing expression.

Navarro-Martín, L., J. Viñas, L. Ribas, N. Díaz, A.
Gutiérrez, et al. 2011. DNA methylation of the
gonadal aromatase (cyp19a) promoter is involvedin temperature-dependent sex ratio shifts in theEuropean sea bass. PLoS Genetics 7: e1002447.
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Olson, C.E., and S.B. Roberts. 2014. Indication offamily-specific DNA methylation patterns indeveloping oysters. bioRxiv doi: http://dx.doi.
org/10.1101/012831

Roberts, S. 2015. Compilation of DNA Methylation
Genome Feature Tracks (Crassostrea
gigas). figshare https://dx.doi.org/10.6084/
m9.figshare.1456226.v2

This study provides the first single-base pair resolution
DNA methylomes for both oyster sperm and larval
samples from multiple crosses. While sample sizes arevery low, this work suggests DNA methylation patterns
could be inherited.

Genome feature tracks and accompanying IGV session
file to visualize DNA methylation data for the Pacificoyster (Crassostrea gigas).

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