SC/65b/SD02

Update of stock structure of humpback whales in the
Antarctic feeding grounds as revealed by microsatellite
DNA data (SC/65b/J31Rev)
Naohisa Kanda, Mutsuo Goto, and Luis A. Pastene
The Institute of Cetacean Research, 4-5 Toyomi-cho, Chuo-ku, Tokyo 104-0055, Japan

Contact email: kanda@cetacean.jp

ABSTRACTThis paper is a revised version of SC/F14/J31 presented to the JARPAII Special Permit Review Workshop,
which takes the workshop’s recommendations into consideration.
A total of 581 humpback whale biopsy samples obtained from Areas III to VI during surveys of the JARPA and
JARPAII up to 2010/11 season as well as International Decade for Cetacean Research/Southern Ocean Whaleand Ecosystem Research (IDCR/SOWER) were analyzed using 14 microsatellite DNA loci in order to describe
their stock structure in the Antarctic feeding ground. The number of the loci used was increased from six in thepaper submitted to the JARPA Review workshop in 2006. In three of 37 cases of duplicate sampling, the second
samples were collected at least a day apart (1 day, 9 years, and 11 years). Paternity analysis of 13 calf andmother pairs failed to detect any potential fathers in the samples for the calves. After exclusion of some of thesesamples, 528 were used for further analyses at stock level. These individuals were divided into four groups basedon the IWC management areas: IIIE (N=93), IV (N=218), V (N=153) and VIW (N=64). Heterogeneity tests for
temporal and special genetic differences were conducted for each of the three different cases: samples offemales+males, females only, and males only. FST values for these tests were also calculated. Although a few
cases of small temporal genetic differences were detected within the areas, major genetic differences wereobserved among the different areas in all of the cases. In addition to that, stronger differentiation was seen infemales than in males although both sexes basically showed similar pattern for the spatial differentiation. These
results corresponded to those of the previous studies. Despite the increase of the number of loci, the level of thestock differentiation (FST = 0.003) was still too low to conduct a clustering analysis at the individual level.
With substantial increases in the numbers of the analyzed microsatellite loci and the biopsy samples, ourgenetic study again showed that humpback whales from the different stocks occupied the research areas withhigher differentiation in females than in males. The level of the genetic differentiation among the areas was still
so low that further analysis would require using samples from their breeding areas to better understand the stock
structure in the feeding grounds. This study demonstrated one of the significant contributions of non-lethal partof the comprehensive large-scale JARPAII to acquire valuable information for effective management of large
whales in the Antarctic.

KEYWORDS: ANTARCTIC, BIOPSY SAMPLING, FEEDING GROUNDS, GENETICS, HUMPBACKWHALEINTRODUCTION
Humpback whales conduct seasonal migration between mid to high latitudinal waters in summer for feeding andlow latitudinal waters in winter for breeding. In the Antarctic, humpback whales appear to congregate into fiveor six distinct feeding groups during the austral summer season that roughly match to IWC Management Areas
I-VI (Mackintosh, 1965).
At the JARPA Review workshop in 2006, Pastene et al., (2006) conducted genetic analyses of humpback
whales from the JARPA research area (Areas III to VI) using mitochondrial DNA and microsatellite DNA
markers, and demonstrated that humpback whales from the different areas belonged to genetically different
groups because of the observed genetic differences among them. In addition, it showed that the level of genetic

1

SC/65b/J31Rev

differentiation was larger in females than in males, strongly suggesting higher female phylopatry and large maledispersion in the feeding grounds. The next question to be addressed was whether or not these feeding groups
were genetically distinct enough from each other that they could correspond to breeding stocks. Pastene et al.
(2013) conducted mtDNA analysis using samples from both the feeding and breeding grounds, and showed thegenetic differences observed among the areas were a consequence of the different proportions of the stocks fromsingle stock occupancy in some areas to multi-stock occupancy in other areas.
This study used microsatellite DNA markers to analyze the same humpback whale samples from Areas III to
VI used in Pastene et al. (2013). The main purpose of the study is to better understand their stock structure byincreasing the number of the loci from Pastene et al. (2006). In that study, the use of the only six loci might haveresulted in the observed low level of the genetic differentiation among the samples. The estimated FST value wasabout 0.005. At that level of differentiation, it was difficult to conduct clustering analysis at the individual base.
In this paper, we increased the number of the microsatellite loci to 14. In addition, sample size was also
substantially increased from the previous study because of the effort of JARPAII.
This paper is the revised version of SC/F14/J31 to cover the recommendations of the Panel of the Expert
Workshop to review the JARPAII Special Permit Research Programme held at Tokyo from 24 - 28 of February,
2014. The panel recommends that SC/F14/J31 should provide locus-specific HW results with FIS in Table 3 andFST per comparison in Tables 4-9.
MATERIALS AND METHODS
Samples
Table 1 shows the number of humpback whale biopsy samples used in this study separated by IWC management
areas. A total of 581 samples were obtained from the JARPA and JARPAII surveys up to 2010/11 season as well
as International Decade for Cetacean Research/Southern Ocean Whale and Ecosystem Research(IDCR/SOWER).
DNA extraction
In regard to our DNA data quality control under the IWC guidelines, see Kanda et al. (2014). Total DNA wasextracted from 0.05 g of biopsy skin tissue using either the protocol of Sambrook et al. (1989) or GENTRA
PUREGENE DNA extraction kit (QIAGEN). Extracted DNA was stored in the TE buffer (10 mM Tris-HCl, 1
mM EDTA, pH 8.0).
Microsatellite analysis
Genetic variation at microsatellite loci was analyzed using 14 sets of primers: AC137, CA234 (Bérubé et al.,2005), EV1, EV14, EV37 (Valsecchi and Amos, 1996), GT23, GT195, GT271, GT310 (Bérubé et al., 2000),
GATA28, GATA53, GATA98, GATA417, TAA31 (Palsbøll et al., 1997). All except EV1 and EV14 were
designed specifically from humpback whales. Amplified products were run on a 6% polyacrylamide
denaturating gel using a BaseStation 100 DNA fragment analyzer (Bio-Rad), and then sizes of visualized alleles
were determined manually in relation to the internal size standard (Genescan 400HD, Life technologies) as wellas the humpback whale’s microsatellites of known size that were rerun on each gel. The sex of the whales wasdetermined through co-amplification of SRY locus located on the Y chromosome and GT23, which is a slight
modification from Abe et al. (2001). With this combination of loci, males show amplified products of both SRY
and GT23 loci, while females show only GT23.
Data analysis
MICRO-CHECKER (van Oosterhout et al., 2004) was used to check for null alleles and reading/typing errors.
The number of alleles per locus, allelic richness, and expected heterozygosity per locus was calculated using
FSTAT 2.9.3 (Goudet, 1995). Statistical tests for the deviations from expected Hardy-Weinberg genotypic
proportions for each of the loci were conducted, as well as their FIS values (Weir and Cockerham, 1984) were
calculated, using GENEPOP 4.0 (Rousset, 2008). Paternity analysis for assignment of mother and calf pairs totheir potential fathers using genetic markers was conducted using CERVUS (Marshall et al., 1998). In order toexamine genetic differences among samples, conventional hypothesis testing procedure was conducted using
heterogeneity test in microsatellite allele frequencies among samples. A probability test (or Fisher’s exact test)
implemented in GENEPOP 4.0 (Rousset, 2008) was used to conduct the heterogeneity tests. Our null hypothesis
to be tested is whether or not the samples came from a genetically same group of humpback whales. If
statistically significant allele frequency differences exist, it could indicate these samples came from geneticallydifferent stocks of humpback whales. Statistical significance was determined using the chi-square value obtained
from summing the negative logarithm of p-values over the 14 microsatellite loci (Sokal & Rohlf 1995). FST value
was calculated using either GENEPOP 4.0 or FSTAT 2.9.3.

2

SC/65b/J31Rev

RESULTS AND DISCUSSION
Among 37 cases of the duplicate sampling, the second samples of three cases were collected at least a day apart(1 day, 9 years, and 11 years; Table 2). One case was first collected in Area IV and was recollected in Area III,
while the other two cases were collected and re-collected in the same area. Because Pastene et al. (2013) showed
the migration of whales from the same stock to Areas III and IV, our results were consistent to the feeding site
fidelity of humpback whales in the Antarctic. Thirteen calf and mother pairs were used for paternity analysis, but
no potential father was detected in the samples.
After exclusion of the second individuals from the duplicated samples and calves sampled with mothers, a
total of 528 samples were used for further analyses. These individuals were divided into four groups based on the
management areas: IIIE (N=93), IV (N=218), V (N=153) and VIW (N=64). The levels of genetic diversity of thearea samples were represented as an average number of alleles per locus, average allelic richness, and expected
average heterozygosity (Table 3). These values were similar among them as well as to those based on the six locipreviously reported in Pastene et al. (2006). No evidence of statistical significant p-values were obtained fromthe tests for deviation from the Hardy-Weinberg expected genotypic proportions were observed at each of theloci after correction for multiple tests (Rice, 1989) as well as at all the loci combined (Table 3). FIS values
appeared to have no trends toward either homozygote excess or heterozygote excess (Table 3).
Heterogeneity tests for genetic differences among the samples from the different areas were conducted forthree different cases: samples of females+males, females only, and males only, respectively (Tables 4-9). FST
values for each of the comparisons were also calculated. For the females+males case, first, genetic differencesamong the different year samples within the areas were examined (Table 4). No evidence of genetic differences
was found among the samples from the different years in Areas IIIE, IV, and V, while small level of genetic
differences was observed in Area VIW. Because the observed significance in Area VI was small and none of thepair-wise comparisons among the year samples was significant (results not shown), the samples from thedifferent years within each of the areas were combined for further analysis. FST values were indeed low ranging
from -0.0007 to 0.0026. Evidence of the genetic differences was then detected among the samples from thedifferent areas (Table 5). Pair-wise comparisons showed evidence of statistically significant differences for all
possible area-pairs (Table 5). Despite the significant differences from the heterogeneity tests, FST values were
low for among the all areas (0.0026) as well as for the pair-wise comparisons (0.0004 - 0.0037) (Table 5).
The heterogeneity tests for the females only and males only cases in general showed similar results to eachother with clearer spatial structuring in females than in males (Tables 6-9). A yearly genetic difference was
detected at Area V in females only case and at area VIW in males only case (Tables 6 and 8). In the females only
case, two (94/95x98/99 and 98/99x08/09) out of the 21 pair-wise comparisons were significant with close-to 5%
p-values (0.035 and 0.049). In the males only case, one (96/97x00/01) out of three pair-wise comparisons was
significant with a 0.017 p-value. Because it was difficult to conclude whether or not these yearly differences had
any biological meanings, we combined the year samples within the areas for the next tests. Evidence of thegenetic difference among the different areas was detected in both cases. In the females only case, all of thepair-wise comparisons showed the statistically significant difference, whereas in the males only case, all except
Areas IIIxV and Areas VxVI comparisons showed the statistically significant difference (Tables 7 and 9). Again,
despite the significant differences from the heterogeneity tests, FST values were low for among the all areas(0.0025 for the females only and 0.0028 for males only) as well as for the pair-wise comparisons (-0.0002 0.0042; 0.0009 - 0.0035).
The results of this study were consistent to those previously reported based on six microsatellite loci as whale
groups occupying the different areas were genetically different from each other with stronger differentiation infemales than in males. Pastene et al. (2013; see also 2006) analyzed mitochondrial DNA variations on humpback
whales from both the feeding and breeding grounds to better describe their stock structure, and showed that IVfrom 80˚E to 120˚E was occupied by one stock (Western Australia stock) and V from 140˚E to 160˚E by anotherstock (Eastern Australia stock). The rest of the areas were mixing areas of the adjacent stocks. Despite thesubstantial increase in the number of the loci, the level of the stock differentiation (FST around 0.003) was still
too low to conduct a clustering analysis at the individual level. In such a situation, it was difficult for this study
to further distinguish between stock mixing and stock core areas without using the data from the breeding areas.
Future microsatellite study should use the samples from the breeding areas. Nevertheless, substantial increases in
the numbers of the analyzed microsatellite loci and the biopsy samples allowed us to confirm our previous
conclusion on the humpback whale stock structure in the Antarctic. This study demonstrated one of thesignificant contributions of non-lethal part of the comprehensive large-scale JARPAII to acquire valuable
information for effective management of large whales in the Antarctic.

3

SC/65b/J31Rev

ACKNOWLEDGEMENTS
We would like to thank all the researchers and crew members of JARPA/JARPA II and IDCR/SOWER surveys
involved in the sampling of the Antarctic biopsy samples used in this study. We also would like to thank H.
Hatanaka for his useful comments on an earlier version of this manuscript and the Panel member of the review
workshop for their constructive comments and advices for the manuscript.
REFERENCES
Abe, H., Goto, M., Pastene, L.A., Dewa, K., Naito, E. 2001. Practical use of multiplex fluorescent PCR for
cetacean sex identification. Mar. Mammal Sci. 17: 657-664.
Bérubé, M., Jørgensen, H., Mcewing, R., and Palsbøll, P.J. 2000. Polymorphic di-nucleotide microsatellite lociisolated from the humpback whale, Megaptera novaeanglliae. Mol. Ecol. 9:2181-2183.
Bérubé, M., Rew, M.B., Skaug, H., Jørgensen, H., Robbins, J., Best, P., Sears, R., and Palsbøll, P.J. 2005.
Polymorphic microsatellite loci isolated from humpback whale, Megaptera novaeanglliae and fin whale,balaenoptera physalus. Cons. Genet. 6: 631-636.
Buchanan, F.C., Friesen, M.K., Littlejohn, R.P., and Clayton, J.A. 1996. Microsatellites from beluga whale
Delphinapterus leucas. Mol. Ecol. 5:571-575.
Goudet, J. 1995. FSTAT, version 1.2: a computer program to calculate F-statistics. J. Hered. 86:485-486.
Kanda, N., Goto, Oikawa, H., and Pastene, L.A. 2014. A note on sampling and laboratory procedure protocols of
the genetic work at the Institute of Cetacean Research. Paper SC/F14/J27 presented to the JARPAII Review
Workshop, Tokyo, February 2014.
Mackintosh, N.A. 1965. The stocks of whales. Fishing News (Books) Ltd., London. 232pp.
Marshall, T.C., Slate, J., Kruuk, L., and Pemberton, J.M. 1998. Statistical confidence for likelihood-based
paternity inference in natural populations. Mol. Ecol. 7: 639-655.
Pastene, L.A., Goto, M., Nishiwaki, S., Yoshida, H. and Kanda, N. 2006. Genetic characteristics and population
structure of humpback whales in the Antarctic feeding ground as revealed by mitochondrial DNA control
region seqwuencing and microsatellite analyses. Paper SC/D06/J31 presented to the JARPA Review
Workshop, December 2006 (unpublished). 14pp.
Pastene, L.A., Kitakado, T., Goto, M., and Kanda, N. 2013. Mixing rates of humpback whales of Stocks D, E
and F in the Antarctic feeding grounds based on mitochondrial DNA analyses. Paper SC/65a/SH13
presented to the IWC Scientific Committee, June 2013, Cheju Island, Korea (unpublished).
Palsbøll, P.J., Bérubé, M., Larsen, A.H., and Jørgensen, H. 1997. Primers for the amplification of tri-and
tetramer microsatellite loci in baleen whales. Mol. Ecol. 6:893-895.
Rice, W.R. 1989. Analyzing tables of statistical tests. Evolution 43:223-225.
Rousset, F. 2008. Genepop'007: a complete re-implementation of the genepop software for Windows and Linux.
Mol. Ecol. Resources 8:103-106.
Sambrook, J., Fritsch, E.F., and Maniatis, T. 1989. Molecular cloning: A laboratory manual. 2nd edn. Cold
Spring Harbor Laboratory, New York, USA.
Sokal, R.R., and Rohlf, F.J. 1995. Biometry: the Principles of Statistics in Biological Research. Freeman andCompany, New York.
Valsecchi, E., and Amos, W. 1996. Microsatellite markers for the study of cetacean populations. Mol. Ecol.
5:151-156.
van Oosterhout, C., Hutchinson, W.F., Wills, D.P., and Shipley, P. 2004. MICRO-CHECKER: software for
identifying and correcting genotyping errors in microsatellite data. Mol. Ecol. Notes 4:535-538.
Weir, B.S., and Cockerham, C.C. 1984. Estimating F-statistics for the analysis of population structure. Evolution
38: 1358-1370.

Table 1. The number of humpback whale biopsy samples usid in this study by surveys and areas.
SurveySurvey area
IIIE

IV

V

VIW

JARPA

56 (33, 23)

132 (58, 74)

106 (56, 50)

46 (18, 28)

JARPAII

14 (6, 8)

49 (26, 23)

61 (36, 25)

3 (0, 3)

IDCR/SOWER

36 (24, 12)

51 (30, 21)

7 (3, 4)20 (12, 8)All

106 (63, 43)

232 (114, 118)

174 (95, 79)

69 (30, 39)

Total (female, male)4

SC/65b/J31Rev

Table 2. Sampling dates and lcoations of the matched samples.
Sampling

lat.

long.

Cap.→recap.

1994/2/12

66.54

70.07E

IV → IIIE, 9 yrs later

2003/12/14

60.31S

48.57E

Sex
Female1997/1/25

61.44S

151.42E

2008/12/13

63.05S138.26E

2002/2/12

64.08S96.58E

2002/2/13

64.06S

97.24E

FemaleMale

V → V, 11 yrs later

IV → IV, next day

Table 3. Genetic diversity indices estimated from all samples within each of survey areas.
Genetic indice

Survey area
IIIE

IV

V

VIW

No. alleles per locus

10.6

11.9

11.9

10.1

Allelic richness per locus

10.2

10.3

10.7

10.1

Heterozygosity

0.758

0.752

0.755

0.746

Hardy-Weinberg / Fis
GATA4170.960-0.016

0.618

0.002

0.063

0.026

0.044

0.094

GATA280.889-0.0460.909-0.0250.749-0.0040.666-0.038GATA98

0.023

0.081

0.051

0.016

0.403

-0.037

0.438

0.011

TAA31

0.459

0.030

0.910

0.041

0.881

0.028

0.331

-0.038GATA530.512-0.0300.432-0.0090.644-0.0630.981-0.049

GT23

0.376

0.025

0.223

0.007

0.797

0.039

0.751

-0.018

GT195

0.725

0.000

0.624

-0.006

0.384

0.039

0.344

0.099

AC137

0.683

-0.0180.740-0.0050.605-0.010

0.446

0.059

EV1

0.141

-0.099

0.392

0.039

0.401

0.006

0.115

-0.007

GT271

0.675

-0.033

0.773

0.022

0.620

-0.0490.113-0.022

CA234

0.231

-0.086

0.872

0.003

0.533

0.041

0.652

0.070

GT310

0.470

-0.075

0.065

0.038

0.618

-0.0220.750-0.067

EV14

0.740

0.012

0.057

0.018

0.473

0.004

0.276

-0.016

EV37

0.904

-0.0220.638-0.018

0.070

0.021

0.024

-0.006

All

0.677

0.451

5

0.668

0.157

SC/65b/J31Rev

Table 4. Results (p-values) of heterogeneity tests for year
differences within areas and Fst: Females+Males.
IIIE
IV
V
p-value
0.814
0.555
0.204
Fst
-0.0052-0.00070.0015
Bold p-values indicate statistically significance.

VIW
0.049
0.0026

Table 5. Results (p-values) of heterogeneity tests among areas and Fst: Females+Males.
Among areas
IIIExIV
IIIExV
IVxV
IIIxVIWIVxVIWp-value
Highly sig.
>0.001>0.001>0.001>0.001>0.001
Fst
0.00260.00330.00370.00290.00120.0018
Bold p-values indicate statistically significance.

VxVIW
0.04710.0004

Table 6. Results (p-values) of heterogeneity tests for year
differences within areas and Fst: Females only.
IIIE
IV
V
VIW
0.015
p-value
0.595
0.510
xxx
Fst
-0.002
0.000
0.008
xxx
Bold p-values indicate statistically significance. XXX indicates no comparison due to the small sample sizes.
Table 7. Results (p-values) of heterogeneity tests among areas and Fst: Females only.
Among areas
IIIExIV
IIIExV
IVxV
IIIxVIWIVxVIWp-value>0.0010.014>0.001>0.001
0.019
0.046
Fst
0.00250.00350.00420.0027-0.0002-0.0002
Bold p-values indicate statistically significance.

VxVIW
0.045
0.0002

Table 8. Results (p-values) of heterogeneity tests for year
differences within areas and Fst: Males only.
IIIE
IV
V
p-value
0.414
0.641
0.284
Fst
-0.0037-0.00180.0030Bold p-values indicate statistically significance.

VIW
0.020
0.0085

Table 9. Results (p-values) of heterogeneity tests among areas and Fst: Males only.
Among areas
IIIExIV
IIIExV
IVxV
IIIxVIWIVxVIW>0.001
0.009
0.007
0.022
0.001
p-value
0.067
Fst
0.00280.00350.00190.00320.00160.0035
Bold p-values indicate statistically significance.

6

VxVIW
0.163
0.0009