Remarkably low mtdna control-region diversity and shallow population structure in Pacific cod Gadus macrocephalus

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1 Journal of Fish Biology (2010) 77, doi: /j x, available online at wileyonlinelibrary.com Remarkably low mtdna control-region diversity and shallow population structure in Pacific cod Gadus macrocephalus M. Liu*, Z. C. Lu, T.X.Gao*, T. Yanagimoto and Y. Sakurai *Fisheries College, Ocean University of China, Qingdao, Shandong , China, Liaoning Marine Fisheries Research Institute, Dalian, Liaoning , China, Division of Oceanic Resources, National Institute of Far Seas Fisheries, Yokohama , Japan and Division of Marine Environment and Resources, Graduate School of Fisheries Science, Hokkaido University, Hakodate, Hokkaido , Japan (Received 17 September 2009, Accepted 25 June 2010) To investigate the genetic diversity and describe the population structure in Gadus macrocephalus, a 452 base pair (bp) fragment of the mitochondrial DNA control region was analysed in 259 individuals. The results showed remarkably low nucleotide diversity and a lack of genealogical structure. Small but significant genetic differentiations, however, were detected among north-western Pacific populations, but no large-scale regional differences were detected. These results indicate that populations of G. macrocephalus in the north-western Pacific are genetically subdivided and represent evolutionary lineages that should be managed individually. Journal compilation 2010 The Fisheries Society of the British Isles Key words: barriers to gene flow; control region; Gadus macrocephalus; genetic bottleneck; genetic structure; historical demography. INTRODUCTION The contemporary genetic architectures of high-latitude marine species were strongly influenced by climatic oscillations during the Pleistocene Epoch (Avise et al., 1998; Wares & Cunningham, 2001; Dodson et al., 2007). Intraspecific mitochondrial (mt) DNA lineages and geographic groupings have been detected in some marine fishes with distributions around the North Pacific, including chum salmon Oncorhynchus keta (Walbaum) (Sato et al., 2004), capelin Mallotus villosus (Müller) (Dodson et al., 2007) and Pacific herring Clupea pallasii Valenciennes (Liu et al., unpubl. data). These groupings are generally attributed to isolation and divergence in refuges during glacial periods. Pacific cod Gadus macrocephalus Tilesius is a member of the family Gadidae and supports one of the most important fisheries in the North Pacific. It is a demersal fish distributed around the North Pacific from the northern Yellow Sea off China to Author to whom correspondence should be addressed at present address: 5 Yushan Road, Qingdao, Shandong , China. Tel.: ; fax: ; gaozhang@ouc.edu.cn 1071 Journal compilation 2010 The Fisheries Society of the British Isles

2 1072 M. LIU ET AL. Santa Monica Bay in California (Bakkala et al., 1984). The aim of the present study was to survey genetic diversity within and among populations and to infer the extent of population structuring in G. macrocephalus based on the analysis of mtdna control-region (CR) variation. The effective population size for mtdna is a quarter of that of nuclear genes, because mtdna genes are haploid and are maternally inherited. Consequently, genetic drift in mtdna markers may produce higher levels of population differentiation than drift in nuclear markers (Birky et al., 1989). These characteristics are ideal for assessing the genetic effects of contemporary barriers to gene flow and for detecting the effects of recent historical demography. The present study evaluates the relative importance of two sources of genetic variation among populations of G. macrocephalus: the influence of present-day barriers to gene flow and the influence of historical demographic events on contemporary population structure. Grant et al. (1987) found two genetically distinct groupings (a North American group and an Asian group) by examining allozyme variation in 11 G. macrocephalus populations. Therefore, a deep phylogeographic break and intraspecific cladogenesis is expected to appear in the pattern of mtdna variation in G. macrocephalus across its range. Several important contemporary-acting environmental factors, such as geographic barriers, ocean currents and sea temperature, are expected to shape and maintain the patterns of population structure in G. macrocephalus. Such knowledge may be critical for the conservation and sustainable management of genetic resources for this species. MATERIALS AND METHODS SAMPLES AND DNA AMPLIFICATION A total of 259 adult G. macrocephalus were collected in from nine geographical locations extending over most of the species range in the North Pacific Ocean (Table I and Fig. 1). Muscle tissue (n = 154) was preserved in 95% ethanol, and fins (n = 105) were dried for DNA extraction. Genomic DNA was extracted following the procedures described by Sambrook et al. (1989). The first hypervariable segment of the mtdna CR was amplified with the primers DL-F: 5 -CCCACCACTAACTCCCAAAGC-3 (forward) and DL-R: Table I. Sampling data and molecular diversity indices for Gadus macrocephalus ID Sampling locations Collection period N n S h ± s.e. π ± s.e. (%) YS Yellow Sea January ± ± SJ Sea of Japan September ± ± EH Eastern Hokkaido January ± ± OS Okhotsk Sea April ± ± AI Aleutian Islands February ± ± UP Unimak Pass February ± ± KI Kodiak Island March ± ± HS Hecate Strait March ± ± GG Gulf of Georgia April ± ± h, haplotype diversity; N, samples size; n, number of haplotypes; S, number of segregating sites; π, nucleotide diversity.

3 PHYLOGEOGRAPHY OF GADUS MACROCEPHALUS Eurasia North America 60 KI YS 3 AI UP 5 OS 8 6 SJ 4 EH 2 North Pacific 1 HS GG Fig. 1. Map of the study area depicting sample locations and schematic map of dominant currents warm ( ) and cold ( ) in the North Pacific. (1) Kuroshio Current, (2) Tsushima Warm Current (3) Yellow Sea Warm Current, (4) North Pacific Drift, (5) Alaska Current, (6) Subarctic Current, (7) California Current and (8) Oyashio Current. YS, Yellow Sea; SJ, Sea of Japan; EH, Eastern Hokkaido; OS, Okhotsk Sea; AI, Aleutian Islands; UP, Unimak Pass; KI, Kodiak Island; HS, Hecate Strait; GG, Gulf of Georgia. 5 -CTGGAAAGAACGCCCGGCATG-3 (reverse) (Han et al., 2008), which amplified a 479 base pair (bp) fragment. Polymerase chain reaction (PCR), purification of PCR product and sequencing were carried out according to protocols in Liu et al. (2007) for the CR. STATISTICAL ANALYSES Sequences were edited and aligned using DNASTAR (DNASTAR Inc.; and have been deposited in the GenBank database under accession numbers HM HM Molecular diversity indices were estimated with Arlequin 3.1 (Excoffier et al., 2006). Genetic relationships were assessed with neighbour-joining (NJ) trees (Saitou & Nei, 1987). The F81 model was selected as the best-fitted model for the data in ModelTest 3.6 (Posada & Crandall, 1998) and was used for the NJ tree reconstruction implemented in PAUP* 4.0b10 (Swofford, 2002) with all sites weighted equally. Bootstrap analysis with replicates was used to evaluate support for nodes in the NJ tree (Felsenstein, 1985). In addition, genealogical relationships were also examined by constructing haplotype networks using the reduced median-network approach (Bandelt et al., 2000). Pair-wise genetic divergences between populations were estimated using the fixation index φ ST (Excoffier et al., 1992). The significances of pair-wise population comparisons were tested with 5000 permutations, and P -values were adjusted with the sequential Bonferroni correction (Rice, 1989). A hierarchical analysis of molecular variance (AMOVA) was used to search for significant genetic partitions among populations (Excoffier et al., 1992). First, two large geographic groups were tested following the results of Grant et al. (1987). Samples from the Yellow Sea (YS), the Sea of Japan (SJ), Okhotsk Sea and eastern Hokkaido (EH) were grouped into an Asian group, and samples from the Aleutian Islands (AI), Unimak Pass (UP), Kodiak Island (KI), Hecate Strait (HS) and the Gulf of Georgia (GG) were grouped into a coastal North America group. Furthermore, samples were evaluated using an adjacent-sample-pooling analysis (Buonaccorsi et al., 2002). Adjacent samples were pooled to create two or more groups. This procedure is warranted by a more or less linear arrangement of populations around the

4 1074 M. LIU ET AL. North Pacific and by the finding of isolation by distance (Cunningham et al., 2009). The best grouping of populations would show the greatest and most significant levels of between-group heterogeneity (φ CT ), while at the same time showing the smallest and least significant levels of within-group heterogeneity (φ SC ). Plots of φ ST from the adjacent-sample-pooling analysis were constructed and examined for peaks that may indicate significant barriers to gene flow (Hyde & Vetter, 2009). Groups of samples based on these peaks were assessed by AMOVA. Both pair-wise φ ST comparisons and AMOVA were performed in Arlequin. To test for isolation by distance (Slatkin, 1993), pair-wise values of φ ST (1 φ ST ) 1 (Rousset, 1997) were plotted against geographical distance between sample sites. Negative values of φ ST were set to zero. When the straight-line distance between sample locations was blocked by land, distances were measured following the coastline between samples. Mantel tests for isolation by distance (IBD) were performed using IBDWS (isolation by distance web service at ibdws/) (Bohonak, 2002; Jensen et al., 2005). Deviations from neutrality were tested with Tajima s D (Tajima, 1989) and Fu s F S (Fu, 1997). Significant negative D and F S values can be interpreted as signatures of population expansion or a selective sweep. Mismatch distributions (Schneider & Excoffier, 1999) were used to investigate the demographic history of G. macrocephalus. Approximate dates of population expansion were estimated with τ = 2ut (Rogers & Harpending, 1992), where u is the mutation rate for the whole sequence under study, and t is the time since population expansion. Both neutrality tests and mismatch distributions were analysed with Arlequin. As a result of the lack of mutation rate calibration for the G. macrocephalus CR, a divergence rate of 3 10% per million years (Myr) was used (Liu et al., 2007) to provide an approximate time frame for evaluating phylogeographical hypotheses. RESULTS After the unreadable sites close to the primer at the 5 end were removed, 452 bp unambiguous CR sequences were obtained for 259 specimens. Sequence comparison of the segment revealed 22 polymorphic sites (eight parsimony informative sites) with 11 transitions, nine transversions and five indels. These polymorphic sites defined 25 haplotypes, of which 14 haplotypes were singletons, eight haplotypes were shared among populations and three haplotypes were found in more than one individual, but in only one population. Overall haplotype diversities and nucleotide diversities of 0 66 ± 0 02 and ± , respectively, were found. Intrapopulation diversity indices appear in Table I, but no clear geographical trend was apparent in G. macrocephalus. Topologies lacked bootstrap support at internal nodes in the NJ tree of the 25 haplotypes. The minimum-spanning network was double star-like with two central common haplotypes (Hap1 and Hap6) surrounded by 23 low-frequency haplotypes (Fig. 2). The two common haplotypes that were shared by almost all the populations appeared in 212 (82%) individuals. No more than two mutational steps had occurred between haplotypes. Both the NJ tree and the haplotype network suggested a lack of genealogical structure in G. macrocephalus. Eleven (11) of the 36 possible φ ST comparisons were statistically significant at the 0 05 level, and almost all these significant differences involved samples from the SJ, YS, and OS (Table II). Two of the largest values of φ ST were for SJ v. YS and SJ v. OS, both of which were highly significant (P <0 001) after Bonferroni correction. The AMOVA test did not show significant genetic differentiations between the two geographic groups postulated by Grant et al. (1987) (φ CT = 0 007; P = 0 12). Adjacent-sample-pooling analysis (Fig. 3) indicated that samples could be partitioned into five groups (YS v. SJ+ EH v. OSv. AIv. UP+ KI + HS + GG) with φ CT =

5 PHYLOGEOGRAPHY OF GADUS MACROCEPHALUS 1075 H17 H23 H24 H7 H3 H4 H15 H5 H2 H12 H11 H18 H6 H1 H13 H14 H21 H8 H19 H22 H20 H16 H25 H10 H9 Fig. 2. Haplotype network for Gadus macrocephalus. Size of circles is approximately proportional to the frequency of each haplotype. The shortest lines represent one mutational step., Yellow Sea;, Sea of Japan;, eastern Hokaido;, Okhotsk Sea;, Aleutian Islands;, Unimak Pass;, Kodiak Island;, Hecate Strait;,GulfofGeorgia (P = 0 01), φ ST = (P = 0 05) and φ SC = (P = 0 68) base on mtdna data. The Monmonier s maximum difference algorithm produced identical results to the AMOVA-based adjacent-population-pooling analysis (data not shown). Mantel tests for isolation by distance over most of the geographic distribution of the species (Fig. 4) did not show IBD (r 2 = 0 017). Considering only the four populations from coastal North America in the north-eastern Pacific, however, a moderate IBD pattern was revealed (r 2 = 0 680), although the pair-wise φ ST values were not significant between these samples. Neutrality tests were performed by pooling all G. macrocephalus sequences. Both Tajima s D ( 2 269, P<0 001) and Fu s F S ( , P<0 001) were negative and significant, indicating significant departure from mutation-drift equilibrium. The mismatch distribution between haplotypes showed a unimodal shape Table II. Pair-wise φ ST (below diagonal) values (above diagonal) among Gadus macrocephalus Populations YS SJ EH OS AI UP KI HS GG YS SJ 0 082** EH 0 030* OS ** AI 0 066* * UP * * KI * HS * GG * * YS, Yellow Sea; SJ, Sea of Japan; EH, Eastern Hokkaido; OS, Okhotsk Sea; AI, Aleutian Islands; UP, Unimak Pass; KI, Kodiak Island; HS, Hecate Strait; GG, Gulf of Georgia. *Significant at P<0 05; **Significant at P<0 001 (after Bonferroni correction).

6 1076 M. LIU ET AL. F CT (a) YS SJ EH OS AI UP KI HS GG Location (b) 0 2 F CT SJ EH OS AI Location Fig. 3. Plots of φ CT values generated during adjacent-sample pooling analyses based on subdivision of (a) all populations and (b) populations from the Sea of Japan (SJ), eastern of Hokkaido (EH), Okhotsk Sea (OS) and Aleutian Islands (AI) into two groups. Vertical broken lines denote peaks of φ CT,whichwere subsequently analysed by AMOVA to test for population subdivision. YS, Yellow Sea; UP, Unimak Pass; KI, Kodiak Island; HS, Hecate Strait; GG, Gulf of Georgia F ST (1 F ST ) Geographic distance (km) Fig. 4. Plot of pair-wise estimates of φ ST (1 φ ST ) 1 v. geographic distance between populations of Gadus macrocephalus. Circles represent all pair-wise populations and triangles were only for coastal North America. A regression line is fitted to data from the four populations of coastal North America.

7 PHYLOGEOGRAPHY OF GADUS MACROCEPHALUS 1077 Frequency Pair-wise differences Fig. 5. The observed pair-wise difference ( ) and the expected mismatch distributions under the sudden expansion model ( ) of control-region haplotypes in Gadus macrocephalus. (Fig. 5), although the expansion model was rejected (P SSD = 0 007, P Rag < 0 001). Tau (τ), which reflects the location of the mismatch distribution crest, provides a roughly estimated time when rapid population expansion started. The observed value of τ was for the pooled sample. Based on divergence rates of 3 10% per Myr, the estimated time of expansion was years ago. DISCUSSION Contrary to expectations, no phylogenetic lineages or genealogical structure were detected in the geographical distributions of mtdna CR variants in the nine samples of G. macrocephalus from across most of the species range. This species is thought to have been derived from an Atlantic ancestor (Grant & Ståhl, 1988; Carr et al., 1999; Coulson et al., 2006). These studies postulated that G. macrocephalus dispersed into the North Pacific across the Arctic Ocean following the opening of the Bering Strait in the mid-pliocene Myr before present (b.p.) (Marincovich & Gladenkov, 2001). Obviously, populations of G. macrocephalus would have been influenced by large-scale ocean cooling and coastal glaciations in many places during the Pleistocene (Hewitt, 1996; Avise et al., 1998). As with other fishes (Sato et al., 2004; Dodson et al., 2007; Liu et al., 2007), this species is likely to have contracted to geographically isolated refuges during glacial advances and expanded during interglacial periods to colonize previously glaciated coastal areas. If small population sizes characterized refuge populations, then the relatively low intraspecific diversity in G. macrocephalus may be due to historical bottlenecks in these refuges. Alternatively, low diversity may also result from founder effects during colonization (Grant & Bowen, 1998). The observed shape of the mismatch distribution showed a sharp drop from the crest, indicating that a large amount of genetic diversity in G. macrocephalus may have been lost rapidly. The estimate of a start of rapid population growth c b.p indicates that the most recent expansion occurred during the interglacial period prior to the last glacial maximum (LGM) b.p (Hewitt, 1996), during which sea levels dropped by m (Lambeck et al.,

8 1078 M. LIU ET AL. 2002). Severely reduced habitats would have forced many populations into extinction and may have caused intraspecific diversity to decrease sharply. Another possible explanation for the low intraspecific diversity is selection on the mtdna of G. macrocephalus. Although selection is unlikely to occur on CR mutations, selection on the linked coding regions of mtdna could still influence the patterns of variation in CR sequences (Bucciarelli et al., 2009). Demographic population expansions, following a reduced effective size and a selective sweep by a favoured haplotype lineage, are not mutually exclusive processes, and both may have influenced the contemporary genetic architecture observed in this species. This assumption was based on the premise that the expansion occurred after the LGM. When the populations expanded into new habitats from the refuges, the new environment variables such as hypoxia and temperature may not have been suitable for most invaders, leaving only a few survivors. Haplotypes H1 and H6 may represent the ancestral haplotypes that survived a population bottleneck or an episode of selection. The species exhibited remarkably low nucleotide diversity (0 0019), which is uncommon for mt control regions in pelagic and demersal fishes. Similar cases were also observed in two merluccid species, Cape hake Merluccius paradoxus Franca and austral hake Merluccius australis (Hutton), with mtdna CR diversities of π = and , respectively (Machado-Schiaffino et al., 2009; von der Heyden et al., 2009). Additionally, haplotype diversities in these species are also low, ranging from h = On the one hand, both low h and π suggest either a recent population bottleneck or a founder event by a few mtdna lineages (Grant & Bowen, 1998). On the other hand, the low diversity of the CR may result from lower mutation rates relative to coding sequences (Bucciarelli et al., 2009), although this has not been demonstrated for gadid fishes. In addition to the low mtdna CR diversity observed in the present study, a study of allozyme variation also indicated low genetic diversity relative to Atlantic cod Gadus morhua L. (Grant & Ståhl, 1988) and other marine fishes (Ward et al., 1994). The low allozyme diversity was interpreted to indicate that a strong bottleneck had occurred in ancestral G. macrocephalus during or after the colonization of the North Pacific by an Atlantic ancestor (Grant & Ståhl, 1988). These estimates of low diversity, however, contrast with the results of a recent study of microsatellite variation, which showed relatively high observed heterozygosities in populations of G. macrocephalus along coastal North America (Cunningham et al., 2009). The contrast between allozyme and microsatellite diversities is probably due to a greater mutation rate in non-coding microsatellite loci (Bouza et al., 2002). The discordance between mtdna and microsatellite diversities may be due to the theoretical fourfold lower female-effective population size for uniparentally, than for biparentally, transmitted genes. Thus, all else being equal, mtdna is more subject to the effects of genetic drift during population bottlenecks and founder effects than is nuclear variation. Another possibility is a high rate of microsatellite mutation, estimated to be 10 2 to 10 6 per generation (Lai & Sun, 2003), which could be higher than the mutation rate for the mtdna CR. Small but significant genetic differentiations were detected among the populations of G. macrocephalus. Despite the failure of AMOVA to detect the postulated geographic groups defined by Grant et al. (1987), the distributions of mtdna CR variants resolved five significant genetic partitions among populations. The Yellow Sea and Okhotsk Sea populations were genetically distinct from the population in the

9 PHYLOGEOGRAPHY OF GADUS MACROCEPHALUS 1079 Sea of Japan, and the easternmost Aleutian Island population was distinct from North America populations. Derived haplotypes, such as H2, H22, H24 and H25, which were observed in only a single sample, contributed heavily to these geographical subdivisions, and their restricted distributions may reflect limited gene flow among contemporary populations. The test for IBD among all populations showed that genetic distance was not correlated with geographic distance (Fig. 4), indicating that contemporary marine environmental factors may play important roles in shaping the genetic structure of G. macrocephalus. Although this species has larvae that spend some time in the plankton passively drifting, dispersal, and hence gene flow, may be limited by shoreline barriers and currents. For example, the Tsushima Warm Current may act as a barrier, as suggested for other species (Gong et al., 1991). The influence of a warm-water barrier between the Sea of Japan and the Yellow Sea may be reflected by the large value of φ ST and the larger φ ST estimates between populations in the Yellow Sea and populations at other locations. The optimal spawning temperature for G. macrocephalus ranges from 0 to 13 C (Alderdice & Forrester, 1971), but seawater temperatures in the Tsushima Strait are usually above 14 C throughout the year. The Tsushima Warm Current also appears to act as a temperature barrier for another fish species, C. pallasii. This isolation promotes divergence in morphology and genetics between populations in the Sea of Japan and the Yellow Sea (Tang, 1991; Kobayashi, 1993). North-western Pacific populations show much greater population structure than do populations in the north-eastern Pacific. In addition to contemporary barriers to dispersal, this structure may reflect historical isolations in marginal seas during Pleistocene glaciations. Most of the marginal seas in the North Pacific are located in the north-western Pacific and include the Yellow Sea, Sea of Japan and Okhotsk Sea. These seas are partially isolated by shallow sills, islands and peninsulas that separate them from the North Pacific. During the LGM, these seas were further isolated by a drop in sea level (Lambeck et al., 2002), and these isolated seas may have acted as refuges for populations of G. macrocephalus. Compared with the north-western Pacific, the north-eastern Pacific lacks marginal seas and has a more stable marine climate. Thus, there may have been fewer opportunities for isolation during Pleistocene glaciations and few limits on contemporary gene flow. Nevertheless, there was a trend of isolation by distance (r 2 = 0 68) among populations in the north-eastern Pacific. A monotonic increase in genetic distance occurred with geographical distance, even though pair-wise φ ST values between populations were small and not statistically significant. IBD also applies in the distributions of microsatellite markers among North American populations of G. macrocephalus, indicating that gene flow was limited between coastal populations (Cunningham et al., 2009). Both the results suggest that the population genetic structuring of this species is probably determined by limited dispersal. Unlike the results for microsatellites, however, the population in the Georgia Basin did not show a significant difference from coastal populations in mtdna CR. Restricted larval dispersal was thought to be caused by complex physiographic and circulatory features in the Georgia Basin (Cunningham et al., 2009). Additionally, the larger mutation rate for microsatellite DNA than for mtdna may contribute to this discordance between the two molecular markers.

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