J-STAGE Advance published date: May 24, 2021

TAGUCHI, GOTO, MILMANN, SICILIANO, TIEDEMANN AND PASTENENEW INSIGHTS INTO THE GENETIC STRUCTURE OF
SEI WHALES (BALAENOPTERA BOREALIS)
AT THE INTER-OCEANIC SCALE
Mioko TAGUCHI1*, Mutsuo GOTO1, Lucas MILMANN2, 3,
Salvatore SICILIANO4, Ralph TIEDEMANN5 and Luis A. PASTENE1, 6
Institute of Cetacean Research, Toyomi-cho 4–5, Chuo-ku, Tokyo 104–0055, Japan2
Grupo de Estudos de Mamíferos Aquáticos do Rio Grande do Sul (GEMARS),
Rua Bento Gonçalves 165, sala 1002, Torres, RS, 95560–000, Brazil
3
Applied Ecology and Conservation Lab, Programa de Pos-graduação em Ecologia e Conservação da
Biodiversidade, Departamento de Ciencias Biológicas, Universidade Estadual de Santa Cruz (UESC),
Rodovia Jorge Amado, km 16, Ilhéus, BA, 45662–900, Brazil
4
Fundação Oswaldo Cruz/Fiocruz, Av. Brasil, 4.365 & Grupo de Estudos de Mamíferos Marinhos daRegião dos Lagos (GEMM-Lagos), Rio de Janeiro, RJ 21040–900, Brazil
5
Unit of Evolutionary Biology/Systematic Zoology, Institute of Biochemistry and Biology, University of
Potsdam, Karl-Liebknecht-Str. 24–25, Haus 26, 14476 Potsdam, Germany
6
Project Microbiomes as Bioindicators of the Aquatic Ecosystem Health in Chilean Patagonia, Centro deEstudios del Cuaternario de Fuego-Patagonia y Antártica (CEQUA), Punta Arenas, Chile*Corresponding author: taguchi@cetacean.jp
1

Abstract
To describe global genetic diversities and genetic structure of sei whales, population genetic
and phylogenetic analyses were performed using mitochondrial DNA (mtDNA) control region
sequence (480 bp) data from specimens collected in three oceanic regions: North Paciﬁc (NP:n=39), North Atlantic (NA: n=84) and Southern Hemisphere (SH: n=6). Microsatellite DNA(msDNA) analyses were also performed using genotype data at seventeen loci in a sub-set ofsamples (n=39 in NP and n=4 in SH). The haplotype (h) and nucleotide (π) diversities werehigher in NP (h=0.92 and π=0.009) and SH (h=1.00 and π=0.012) than in NA (h=0.68
and π=0.002). The haplotype frequency was signiﬁcantly diﬀerent among the three oceanic
regions, and the conventional pairwise FST estimates support the diﬀerence between NA andthe other two populations. Furthermore, except for one haplotype, there were no other shared
haplotypes among the three oceanic regions, suggesting contemporary migration and geneﬂow would be strongly restricted at inter-oceanic scales. This inference was also supported by
the msDNA analyses. The haplotype genealogy reconstructed by the maximum-likelihood approach strongly supported two clusters, the ﬁrst consisting of NA haplotypes, and the second
consisting of NP and SH haplotypes. This genealogy was supported by the statistical parsimony haplotype network. These results indicated hierarchical genetic structuring of sei whales
globally, in which whales in SH are genetically closer to NP whales than to NA whales. Basedon a comparison of the inter-oceanic genetic structure and phylogeny of the sei whales withthose of ﬁn whales, which is another cosmopolitan baleen whale species, it is suggested thatthe genetic structure of sei whales reﬂects occasional gene ﬂow between the Northern andSouthern hemispheres and/or incomplete lineage sorting, similar to the case of ﬁn whales.
Key words:

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sei whale, stock structure, control region, worldwide, phylogeography.

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Introduction
The sei whale, Balaenoptera borealis, is one of the large baleen whales inhabiting all the major
open oceans, except the northern Indian Ocean (Horwood, 1987; Rice, 1998). Sei whales live up to
sixty years and their body length reaches up to 20 m. It is believed that they migrate from low-latitudes
winter breeding grounds to summer feeding grounds in high-latitudes, although little is known about
the migratory routes and the exact location of breeding grounds of this species. This migration pattern,coupled with asynchronous seasonal breeding cycles between the Northern and Southern hemispheres,should favor reproductive isolation and resultant genetic divergence of sei whales between the hemispheres, as observed in other cosmopolitan baleen whales, e.g., ﬁn whale, Balaenoptera physalus (Archer et al., 2013) and humpback whale, Megaptera novaeangliae (Jackson et al., 2014). Furthermore,
the continental masses separating the North Atlantic from the North Paciﬁc have probably prevented
gene ﬂow of sei whales between the two oceans since the closure of the Panama Seaway, which is believed to have occurred during the Pliocene (Coates et al., 1992).
Previous published population genetic work of sei whales is limited, despite their global distribution. Pioneering work was carried out by Wada and Numachi (1991) based on allozymes. This study
revealed allele frequencies of three polymorphic allozymes to be signiﬁcantly diﬀerent between Antarctic and North Paciﬁc sei whales, without any further diﬀerentiation within the oceans. The genetic
homogeneity within the western North Paciﬁc was supported by the subsequent work by Kanda et al.
(2006) using microsatellite DNA (msDNA) polymorphisms at seventeen loci. The most recent study
used mitochondrial DNA (mtDNA) control region sequences and msDNA genotypes. The study foundevidence of genetic structuring between North Paciﬁc and North Atlantic sei whales, but not within
the North Atlantic (Huijser et al., 2018). Taking these previous ﬁndings together, it is highly possible that sei whales are genetically diﬀerentiated among North Paciﬁc (NP), North Atlantic (NA) andoceans of the Southern Hemisphere (SH).
The objective of this study was to describe global genetic diversities and genetic structure of sei
whales using mtDNA control region sequences and msDNA genotype data of this species worldwide.
This is the ﬁrst study to incorporate sei whale samples from the NP, NA and SH.

Materials and Methods
Laboratory procedures
Samples and DNA extraction
A total of 44 tissue samples of sei whales (Fig. 1) was collected from three sources: (1) whaling
under the second phase of the Japanese Whale Research Program under Special Permit in the western
North Paciﬁc (JARPNII) in 2002 (n=39); (2) biopsy sampling under the Japanese Whale Research
Program under Special Permit in the Antarctic (JARPA) in 2000/01 (n=3) and 2002/03 (n=1); (3)stranding at southern Brazil in 2015 (n=1, export and import CITES permits 18BR030112/DF and
18JP000006/TI, respectively). Note that the 39 samples collected in the western North Paciﬁc were
the same as those used in the previous msDNA analyses (Kanda et al., 2006), but their nucleotide sequences at mtDNA control region were determined for the ﬁrst time in the present study.
Sampled skin tissues were preserved in 99% ethanol or stored frozen at −20°C until use. Total
genomic DNA was extracted from 0.05 g of skin tissue using either the standard phenol-chloroform
method (Sambrook et al., 1989) or the Gentra Puregene kits (QIAGEN). Extracted DNA was stored in
TE buﬀer (10mM Tris-HCl, 1mM EDTA, pH 8.0).
MtDNA sequencing
For all samples subjected to the DNA extraction, 534 base pairs (bp) of the mtDNA control region
were ampliﬁed by the polymerase chain reaction (PCR) using the set of primers MT4 (Árnason etCetacean Popul. Stud. (CPOPS), Full paper
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Fig. 1. Geographical position of samples newly sequenced and/or genotyped in the present study. Symbol
shape indicates sample population: circle (NP, n=39), triangle (SH, n=5).

al., 1993) and Dlp5R (5′-CCA TCG AGA TGT CTT ATT TAA GGG GAA C-3′). PCR was carried out ina 25 µL reaction mixture containing 10–100 ng of template DNA, 0.2 mM of dNTPs, 0.1 mM of eachprimer, 0.5 units of EX Taq DNA polymerase (TaKaRa), and 1× PCR buﬀer. Each reaction was performed with an initial denaturation step at 95°C for 5 minutes, followed by 30 cycles of 30 seconds at
94°C, 30 seconds at 50°C and 30 seconds at 72°C, with a ﬁnal extension step at 72°C for 10 minutes.
PCR products were puriﬁed using MicroSpin S-400HR columns (Pharmacia Biotech). Cycle sequencing was performed using BigDye terminator cycle sequence Kit (Applied Biosystems) and the PCRprimers, following the protocols of the manufacturer. The cycle sequencing products were puriﬁed using AutoSeq G-50 spin Columns (Pharmacia Biotech). The labeled sequencing fragments from tissue
samples from JARPNII and JARPA were resolved using an ABI PRISM 377, while the fragment of
the stranding sample was sequenced with ABI3500 Genetic Analyzers (Applied Biosystems).
MsDNA genotyping
Three samples collected under the JARPA in 2000/01 and one stranding sample collected in southern Brazil in 2015 were genotyped at 17 nuclear msDNA loci, i.e., EV1, EV14, EV21, EV94, EV104(Valsecchi and Amos, 1996), GT011 (Bérubé et al., 1998), GT23, GT211, GT271, GT310, GT575(Bérubé et al., 2000), GAT A28, GAT A53, GAT A98, GAT A417, GGAA520 (Palsbøll et al., 1997),
and DlrFCB17 (Buchanan et al., 1996), in three multiplex ﬂuorescent PCRs. Each of the multiplex
PCRs was carried out in a 10 µL reaction mixture, containing 10–100 ng of template DNA, 5 µL of 2×
Type-it Multiplex PCR master mix (QIAGEN), and 1 µL of primer mix (2 μM each primer), at 95°C
for 5 minutes, followed by 28 cycles at 95°C for 30 seconds/54, 58 or 59.5°C for 90 seconds/72°C for
30 seconds, and a post-cycling extension at 60°C for 30 minutes. PCR products were electrophoresedon an ABI3500 DNA Analyzer (Applied Biosystems), and allele sizes were determined using a 600
LIZ size standard (Applied Biosystems) and GeneMapper v. 4.0 (Applied Biosystems).
DatasetIn order to investigate the global genetic structure, mtDNA and msDNA data were divided into
three oceanic regions: (1) North Paciﬁc (NP); (2) North Atlantic (NA); (3) Southern Hemisphere (SH).

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MtDNACombining the 44 mtDNA control region sequences newly sequenced in this study with the 85
sequences generated in the previous studies (of which, 84 were from the Gulf of Maine, Iceland andAzores (Huijser et al., 2018) and one from the Antarctic Ocean (Sasaki et al., 2005)) resulted in a totalof 129 mtDNA sequences of sei whales from NP (n=39), NA (n=84) and SH (n=6) (Table 1).
MsDNA
Combining msDNA genotypes of the four new individuals from SH (three from the Antarctic andone from Brazil), with a subset of genotype data in NP generated by Kanda et al. (2006), resulted in a
total of 43 genotype set of sei whales from NP (n=39) and SH (n=4) (Table 1). The newly obtained
msDNA scores were standardized to the previous scores, which Kanda et al. (2006) generated using
the BaseStation100 DNA fragment analyzer (Bio-Rad), by comparing the scores of the same samples
between the present and previous platforms.
Data analyses
MtDNA
Haplotype (h) and nucleotide (π) diversities with sample standard deviations (Nei, 1987) were estimated using the program ARLEQUIN v. 3.5.2.2 (Excoﬃer and Lischer, 2010).
The diﬀerence in mtDNA haplotype frequency among oceanic regions was tested using the Monte Carlo simulation-based chi-square test of independence with 10,000 replicates (Roﬀ and Bentzen, 1989) in R (R Core Team, 2016). The conventional FST estimates between oceanic regions were
calculated using 10,000 random permutations of the original dataset, as implemented in ARLEQUIN.
The FDR correction (Benjamini and Hochberg, 1995) was used to adjust the statistical signiﬁcancelevel in the pairwise estimates.
The mtDNA haplotype genealogy of sei whales was reconstructed using the maximum-likelihood
approach (ML-tree) with 10,000 bootstrap resampling in the program MEGA ver. 10.0.5 (Kumar etal., 2018). The best-ﬁt nucleotide substitution model was determined based on the Bayesian Information Criterion using MEGA, and Tamura 3-parameter model (Tamura, 1992) with G=0.487 and
I=0.747 was selected. Two sequences of Balaenoptera edeni (GenBank accession number: X72196)
and Balaenoptera brydei (unpublished data) were used as outgroups in the analysis. The statisticalparsimony network (Clement et al., 2000) of mtDNA control region haplotypes was also depictedusing the program PopART (Leigh and Bryant, 2015).
MsDNA
The departure from Hardy–Weinberg equilibrium (HWE) was tested and the inbreeding coeﬃcient(FIS; Weir and Cockerham, 1984) was estimated, using GENEPOP (Raymond and Rousset, 1995;
Rousset, 2008). The number of alleles (A), allelic richness (AR) and expected heterozygosity (HE)
Table 1. Numbers of mitochondrial (mt) and microsatellite (ms) DNA data used in this study. The mtDNA
nucleotide sequences in NP were newly obtained from the same samples used for msDNA analyses in Kanda
et al. (2006).

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Table 2. Summary of mtDNA variations of sei whales and haplotype frequency in each of and across the oceanic regions. Numbers in ‘Variable site’ represent nucleotide positions corresponding to ‘H01’ deposited in DDBJ under the accession no. LC629100. See Table 1 for abbreviations of the oceanic region.
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were estimated using the program FSTAT ver. 2.9.3.2 (Goudet, 1995).
Bayesian clustering analysis was performed to infer the most likely number of clusters using
STRUCTURE 2.3.4 (Pritchard et al., 2000). The analysis was conducted with ten independent runs
for K=2–3. All runs were performed with 100,000 Markov chain Monte Carlo repetitions and 10,000
burn-in length using the admixture model with correlated allele frequencies. The web-based program
STRUCTURE HARVESTER (Earl and von Holdt, 2012) was used to estimate the mean posterior
probability of the data. Additionally, principal component analysis (PCA) was performed in R using
the ‘dudi.pca’ function in the ade4 package (Chessel et al., 2004; Dray et al., 2007).

Results
Genetic variations
MtDNA
The mtDNA control region sequences (480 bp) of 129 sei whales from the three oceanic regions
contained 31 variable nucleotide sites and a single indel (1 bp) deﬁning 31 haplotypes, of which 23
were novel (deposited in GenBank with accession numbers: LC629100–LC629122) (Table 2). Apartfrom haplotype ‘NA6’, none of the haplotypes were shared among oceanic regions. Haplotype ‘NA6’
was shared between NA and SH (Table 2). The h and π for the total samples were 0.86 and 0.013,
respectively (Table 2). These estimates were higher in SH (1.00 and 0.012) and NP (0.92 and 0.009)
than in NA (0.68 and 0.002).
MsDNA
All 17 msDNA loci were polymorphic in a total of 43 sei whales in NP and SH, with locus-speciﬁcallele numbers from 3 alleles at GAT A53 and GT271 to 17 alleles at DlrFCB17 (Table 3). The AR
was higher in SH than in NP. No signiﬁcant deviations from HWE were observed in each locus or
across the loci of NP and SH (Table 3). Although the signiﬁcant departure from HWE was detected at
GAT A417 when the two populations were combined (Table 3), the global test did not support the statistical signiﬁcance.

Table 3. Summary statistics of 17 msDNA loci of sei whales: A, the number of alleles; AR, allelic richness; HE,
expected heterozygosity; FIS, inbreeding coeﬃcient; HWE, p-value of the Hardy-Weinberg equilibrium test.
FIS and HWE at GT011 in SH were incomputable since one of two alleles was represented by only one copy.
See Table 1 for abbreviations of the oceanic region. Bold text indicates the statistical signiﬁcance at α=0.05.

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Table 4. Conventional pairwise FST estimates between oceanic regions for mtDNA. Asterisks show the statistical signiﬁcance after FDR correction: *p<0.05, **p<0.01, ***p<0.001. See Table 1 for abbreviations of
the oceanic regions.

Table 5. Summary of STRUCTURE analyses showing the average ln Pr(X|K) for each of K, and respective
probability.

Genetic diﬀerentiation and structure
MtDNA
The haplotype frequency was signiﬁcantly diﬀerent among the three oceanic regions (χ 2=246.48,
p<0.001). Conventional pairwise FST estimates were signiﬁcantly diﬀerent from zero in the pairs of NP
and NA as well as SH and NA, but no signiﬁcant diﬀerence was seen between SH and NP (Table 4).
MsDNA
The STRUCTURE analyses conducted for diﬀerent sampling partitions without information on
their geographic origins presented the highest probability at K=1 (Table 5). However, the four sei
whales from the SH were distinguishable from NP whales by high posterior probabilities (q>0.8) of
belonging to a particular cluster at K=2 (Fig. 2).
In PCA analysis, the ﬁrst (PC1) and second (PC2) principal components explained 9.81% and6.95% of the total variation, respectively. This analysis suggests that the 43 sei whales could be divided into two distinct clusters (NP and SH) along the PC1 axis (Fig. 3).
Phylogenetic analyses
The ML-tree showed two clusters supported by high bootstrap values (Fig. 4a), one which consistedof haplotypes found in NA and the other of haplotypes found in NP and SH. Within the NP/SH cluster,
the ML-tree also showed a sub-cluster containing four of the six haplotypes found in SH, i.e., ‘NA6’,‘H87’, ‘H88’ and ‘H90’. However, this cluster had a low bootstrap value (Fig. 4a).
The statistical parsimony network showed the two clusters were separated by six mutational steps,
which consisted of a star-like genealogy of haplotypes found in NA, and more complex structures in
NP and SH (Fig. 4b). The haplotype network also showed that all haplotypes found in SH were separated from those in NP by several mutational steps.
The haplotype ‘NA6’ found in both NA and SH was located in the NP/ SH cluster in each topology(Fig. 4).

Discussion
This is the ﬁrst population genetic study of sei whales worldwide. In particular, analyses using
msDNA has never been reported in SH sei whales. Notwithstanding the small number of samples usedfrom SH, the preliminary ﬁndings of this study provide some new insights into the genetic structure
and phylogeography of this species.

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Fig. 2. Bar plot of posterior probabilities in STRUCTURE analyses for sei whales in oceans of the Southern
Hemisphere (SH) and the North Paciﬁc (NP): (a) K=2 and (b) K=3. Each individual is characterized by athin vertical line, which is divided into K colored segments on the basis of the individual’s membership fractions in K clusters.

Genetic structure
The haplotype frequency of sei whales was signiﬁcantly diﬀerent among the three oceanic regions,and the conventional pairwise FST estimates suggested the genetic diﬀerentiation of this species between NA and the other two oceanic regions. This observation is consistent with the pattern of genetic
diﬀerentiation of sei whales between NP and NA presented by Huijser et al. (2018). Although the
FST estimates did not support a genetic diﬀerence between NP and SH, given no haplotype sharing,the insigniﬁcant result was likely to be caused by the small sample size in SH. In fact, Wada and Numachi (1991) using a larger number of samples demonstrated the signiﬁcant genetic diﬀerentiation
between NP and SH sei whales. Furthermore, this inference was supported by the msDNA analyses.
The STRUCTURE analysis suggested that the most likely number of populations at Hardy-Weinberg/
linkage equilibrium in the data set consisting of sei whales in SH and NP was one, which was consistent with no deviations from HWE in each of and across populations. However, despite the small
sample size in SH, the four SH sei whales were distinguishable from the NP whales by high posterior
probabilities (q>0.8) when K=2 was assumed. This was also supported by the result of multivariable
analysis, i.e., PCA, separating the four sei whales from other NP whales along the ﬁrst PC axis.
The PCA analysis also showed a large genetic variation of SH cluster consisting of samples collected across the vast oceanic region, i.e., the western South Atlantic and the Antarctic Ocean. This,
coupled with high h in SH, might be suggestive of an inclusion of samples derived from multiple
breeding populations in a single sample population. Given the genetic structuring shown in other SH
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Fig. 3. Result of PCA analysis on genotypes at seventeen msDNA loci. See Table 1 for abbreviations of theoceanic regions.

Fig. 4. Genealogy reconstructed by the maximum-likelihood approach (a), and statistical parsimony network(b) of mtDNA control region haplotypes of sei whales. The phylogenetic tree was rooted by outgroup of B.
brydei and B. edeni, which was drawn to scale with branch lengths measured in the number of substitutions
per site. Only bootstrap values above 60% are shown. Asterisk shows haplotypes shared among oceanic regions. Circles of the haplotype network represent diﬀerent haplotypes. The colors and sizes of circles refer tothe geographical origin and abundance of haplotypes, respectively. Small black circles indicate intermediate
haplotypes not found in this study. See Tables 1 and 2 for abbreviations of the geographical origin of haplotypes and haplotype information, respectively.

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baleen whales (e.g., humpback whales, Olavarría et al., 2007; Antarctic minke whales, Pastene andGoto, 2016), that possibility could not be excluded at this stage.
The haplotype network and ML-tree strongly supported the divergence of haplotypes found in NA
from those in NP and SH, as shown by Huijser et al. (2018). The haplotype network further showedthat all haplotypes found in SH were separated from those in NP by several mutational steps. The MLtree revealed a sub-cluster containing most of the haplotypes found in SH, however, there was no signiﬁcant bootstrap support. These results are indicative of ocean-speciﬁc mitochondrial lineages, which
are compatible with the observed diﬀerence in the degrees of the pairwise FST estimates among sei
whales from the three oceanic regions.
Taking all the present and previous ﬁndings together, sei whales appear to be signiﬁcantly diﬀerentiated among oceanic regions hierarchically, and whales in SH are more closely related to whales
in NP than to whales in NA. Except for haplotype ‘NA6’, there were no other haplotypes that wereshared among the three oceanic regions, which suggests that contemporary migration and gene ﬂow
would be strongly restricted at inter-oceanic scales.
Interestingly, the pattern of inter-oceanic genetic structuring observed in the present study was similar
to that in ﬁn whales with the lower FST estimates between NP and SH (mtDNA, 0.005–0.106; singlenucleotide polymorphisms (SNPs), 0.098) than between NA and NP (mtDNA, 0.018–0.198; SNPs,
0.1668) as well as between NA and SH (mtDNA, 0.017–0.121; SNPs, 0.1447) (Archer et al., 2019). This,
coupled with genealogical concordance between ﬁn and sei whales described below, suggests that the pattern of genetic structuring in sei whales could be attributed to historical events, i.e., recent occasional geneﬂow between the Northern and Southern hemispheres and/or incomplete lineage sorting (ILS).
Phylogeographic inferences
The ML-tree found no evidence of divergence of SH haplotypes from NP ones, despite the inference of genetic diﬀerentiation between the two oceanic regions. ILS and/or recent occasional geneﬂow may explain this observation, because they can be the cause of shared genetic variations among
populations after their divergence. The mtDNA phylogenetic study of ﬁn whales demonstrated a polyphyletic pattern of NP and SH haplotypes (Archer et al., 2013), which was similar to that of the sei
whale. The study also suggests the possibilities of a relatively recent introgression between the twooceans and/or retention of ancestral polymorphisms due to ILS of the large whale species.
Huijser et al. (2018) inferred that an expansion of the North Atlantic sei whale population occurred
after the last glacial maximum (LGM, 26.5–19 thousand years ago; Clark et al., 2009) based on phylogeographic analyses. The star-like genealogy of haplotypes and lower genetic diversities observed in
NA in the present study would be attributed to this historical event in the case of the NA sei whales.
On the other hand, SH and NP haplotypes showed more complex structures with a high number of
haplotypes of intermediate frequency on the network. Given the inferences of ILS with high h in NP
and SH, the result could reﬂect ancestral polymorphisms of NP and SH whales in a large long term
eﬀective population size. It seems that they have been separated long enough to be void of shared
haplotypes, but not long enough to have evolved reciprocal mitochondrial monophyly. Such reciprocalmonophyly is indeed observed among NA and the combined NP/SH cluster, suggesting a considerably
more ancient divergence.
In the present study, there are also signs of recent or contemporary occasional inter-oceanic migration/dispersal events, one from SH to NA (NA6) and one from NP to SH (SH1). This inference
is compatible with the restricted but rare inter-equatorial gene ﬂow inferred in humpback whales(e.g., Jackson et al., 2014) and ﬁn whales (Cabrera et al., 2019). So far, there is no direct evidence
for trans-equatorial gene ﬂow in sei whales. However, this seems probable in this species, given its
high mobility as demonstrated by tagging studies (e.g., Olsen et al., 2009) and continuous distribution
across the equatorial waters inferred from stranding records along the northern coast of Brazil (e.g.,
Costa et al., 2017; Mayorga et al., 2020; Milmann et al., 2020).
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Conclusion
Notwithstanding the small sample size used from SH, the present study demonstrated the hierarchical genetic structuring of sei whales globally for the ﬁrst time, with high genetic diversity in SH/NP,
in which whales in SH are genetically closer to NP whales than to NA whales. These ﬁndings, coupledwith the previous ﬁndings in sei whales as well as in other cosmopolitan baleen whales, suggested thefollowing phylogeographical scenarios of this species: (1) a shorter history of divergence among SH
and NP, leading to retention of ancestral polymorphisms due to ILS in SH and NP, (2) occasional geneﬂow between the Northern and Southern hemispheres.
Extended genetic analyses using larger sample sizes across the oceans and more genetic loci haveto be conducted in this species to investigate ﬁner genetic structure and demographic estimates, e.g.,
migration rate and eﬀective population size.
Acknowledgements

We thank all researchers, crew members and colleagues who contributed to the collection of genetic samples used in thisstudy. We are grateful to Hiroyuki Oikawa (ICR) for his assistance in the laboratory work, and to Naohisa Kanda (JANUS)
for preparing the msDNA data used in this study. We would also like to thank the anonymous reviewers for their helpfulcomments on the manuscript.

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Received: November 18, 2020
Accepted: March 22, 2021
Published online: May 24, 2021

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