Research Article |
Corresponding author: Tianxiang Gao ( gaotianxiang0611@163.com ) Academic editor: Maria Elina Bichuette
© 2019 Lu Liu, Xiumei Zhang, Chunhou Li, Hui Zhang, Takashi Yanagimoto, Na Song, Tianxiang Gao.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Liu L, Zhang X, Li C, Zhang H, Yanagimoto T, Song N, Gao T (2019) Population genetic structure of Marbled Rockfish, Sebastiscus marmoratus (Cuvier, 1829), in the northwestern Pacific Ocean. ZooKeys 830: 127-144. https://doi.org/10.3897/zookeys.830.30586
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Sebastiscus marmoratus is an ovoviviparous fish widely distributed in the northwestern Pacific. To examine the gene flow and test larval dispersal strategy of S. marmoratus in Chinese and Japanese coastal waters, 421 specimens were collected from 22 localities across its natural distribution. A 458 base-pair fragment of the mitochondrial DNA (mtDNA) control region was sequenced to examine genetic diversity and population structure. One-hundred-six variable sites defined 166 haplotypes. The populations of S. marmoratus showed high haplotype diversity with a range from 0.8587 to 0.9996, indicating a high level of intrapopulation genetic diversity. Low non-significant genetic differentiation was estimated among populations except those of Hyogo, Behai, and Niiigata, which showed significant genetic differences from the other populations. The demographic history examined by neutrality tests, mismatch distribution analysis, and Bayesian skyline analysis suggested a sudden population expansion dating to the late Pleistocene. Recent population expansion in the last glacial period, wide dispersal of larvae by coastal currents, and the homogeneity of the environment may have important influences on the population genetic pattern. Knowledge of genetic diversity and genetic structure will be crucial to establish appropriate fishery management of S. marmoratus.
Genetic diversity, genetic structure, historical population demographics, mtDNA control region, Sebastiscus marmoratus
The Marbled Rockfish, Sebastiscus marmoratus (Cuvier, 1829), valued for its high nutritional value and palatability (
The mitochondrial DNA (mtDNA) control region has been shown to be particularly effective in detecting population genetic structure and diversity, owing to its high polymorphism, maternal inheritance, high mutation rate, and nonrecombinant DNA (
While S. marmoratus has been widely studied with respect to taxonomy (
The goals of this study were to estimate genetic diversity, to characterize genetic structure, and to reconstruct the evolutionary relationships of S. marmoratus in its distribution range. Failure to characterize population units can lead to overfishing and severe decline (
From June 2009 to August 2015, we collected 421 wild S. marmoratus from 22 locations in coastal China and Japan, 10–24 specimens per site (Fig.
Region | Population | Abbreviation | Number size | Collection date |
---|---|---|---|---|
China coast | Weihai | WH | 24 | June, 2009 |
Rushan | RS | 23 | June, 2009 | |
Qingdao | QD | 24 | July, 2009 | |
Zhoushan | ZS | 24 | January, 2015 | |
Wenzhou | WZ | 14 | September, 2010 | |
Xiamen | XM | 24 | March, 2014 | |
Shantou | ST | 21 | August, 2015 | |
Huizhou | HZ | 21 | September, 2010 | |
Guangzhou | GZ | 18 | September, 2010 | |
Hainan | HN | 14 | September, 2010 | |
Beihai | BH | 24 | February, 2015 | |
Total | 231 | |||
Japan coast | Niigata | NI | 15 | June, 2015 |
Ishikawa | IS | 10 | September, 2012 | |
Yokosuka | YK | 22 | November, 2011 | |
Tottori | TO | 24 | June, 2015 | |
Shizuoka | SH | 12 | September, 2012 | |
Awaji | AW | 15 | September, 2012 | |
Hyogo | HO | 24 | June, 2015 | |
Hakata Island | HA | 14 | November, 2011 | |
Kochi | KO | 23 | September, 2012 | |
Iki Island | IK | 21 | September, 2012 | |
Ariake-kai | AR | 10 | September, 2012 | |
Total | 190 |
Genomic DNA was extracted from muscle tissue by proteinase K digestion followed by a standard phenol-chloroform technique. Fragments of the mtDNA control region were amplified with primers referenced from
Polymerase chain reactions (PCR) were carried out in 25 μL of reaction mixture containing 10–100 ng template DNA, 0.1 µL (5 U/µL) Taq DNA polymerase (Takara Co., Dalian, China), 1.5 µL (10 pmol/µL) of each forward and reverse primer, and 2 µL (200 µmol/L) deoxy-ribonucleoside triphosphate (dNTP). The PCR amplification was conducted in a Biometra thermal cycler under the following conditions: 2 min initial denaturation at 95 °C; 40 cycles of 60 s at 94 °C for denaturation, 45 s at 52 °C for annealing, and 60 s at 72 °C for extension; and a final extension at 72 °C for 8 min. The PCR product was purified with a Gel Extraction Mini Kit (Watson BioTechnologies Inc., Shanghai, China). The purified product was used as the template DNA for cycle sequencing reactions performed using BigDye Terminator Cycle Sequencing Kit (v. 2.0, PE Biosystems, Foster City, CA, USA), and bi-directional sequencing was conducted on an Applied Biosystems Instrument Prism 3730 automatic sequencer (Sunny Biotechnology Co. Ltd, Shanghai, China) with both forward and reverse primers. The primers used for sequencing were the same as those used for PCR amplification.
All sequences were edited and aligned manually by DNAStar software (DNAStar Inc., Madison, WI, USA) using default settings and were manually corrected. The genetic diversity indices of S. marmoratus, including haplotype diversity (h), nucleotide diversity (π), mean number of pairwise differences (k), and number of polymorphic sites were calculated by ARLEQUIN v. 3.5 (
Nucleotide sequence evolution models were evaluated using likelihood-ratio tests implemented by Modeltest v. 3.06 (
Characterization of population subdivisions and population structure were conducted using a hierarchical analysis of molecular variance (AMOVA) of different gene pools (
The Tajima D and Fu’s FS tests were examined for neutrality (
Bayesian skyline analyses, implemented in BEAST v. 1.7.4 (
A 458 bp segment of the mtDNA control region was amplified, and 106 polymorphic sites were detected, including 89 transitions and 17 transversions. A total of 166 haplotypes were identified based on the sequence variation in 421 individuals from 22 locations. Among these, 84 haplotypes were shared. The most common haplotypes, Hap4 and Hap5, were both shared by 40 individuals. Haplotype sequences were deposited in GenBank under accession numbers KY703229–KY703394.
The estimated nucleotide diversity (π) and haplotype diversity (h) for the locations are shown in Table
Genetic diversity parameters among population of S. marmoratus from 22 locations.
Population code | Number of haplotypes | Haplotype diversity (h) | Nucleotide diversity (π) | Number of polymorphic sites (S) | Mean number of pairwise (k) differences |
---|---|---|---|---|---|
WH | 23 | 0.9964±0.0133 | 0.0235±0.0123 | 46 | 10.753±5.072 |
RS | 14 | 0.9526±0.0252 | 0.0216±0.0114 | 38 | 9.874±4.689 |
QD | 23 | 0.9964±0.0133 | 0.0208±0.0110 | 38 | 9.532±4.531 |
ZS | 16 | 0.9601±0.0238 | 0.0219±0.0116 | 36 | 10.024±4.748 |
WZ | 12 | 0.978±0.0350 | 0.0167±0.0093 | 31 | 7.634±3.789 |
XM | 18 | 0.9565±0.0311 | 0.0236±0.01244 | 42 | 10.795±5.090 |
ST | 15 | 0.9524±0.0317 | 0.0194±0.0100 | 36 | 8.090±4.269 |
HZ | 14 | 0.9524±0.0278 | 0.0173±0.0093 | 27 | 7.884±3.820 |
GZ | 16 | 0.9804±0.0284 | 0.0221±0.0118 | 36 | 10.111±4.847 |
HN | 13 | 0.9890±0.0314 | 0.0110±0.0063 | 26 | 9.050±4.435 |
BH | 16 | 0.9638±0.0208 | 0.0140±0.0077 | 32 | 6.408±3.145 |
AR | 9 | 0.9778±0.0540 | 0.0216±0.0122 | 31 | 9.878±4.943 |
IK | 15 | 0.9571±0.0301 | 0.0239±0.0126 | 39 | 10.940±5.184 |
NI | 10 | 0.9238±0.0530 | 0.0156±0.0089 | 30 | 7.130±3.544 |
IS | 7 | 0.8667±0.1072 | 0.0224±0.0126 | 25 | 10.251±5.117 |
TO | 19 | 0.9783±0.0187 | 0.0224±0.0118 | 39 | 10.275±4.859 |
SH | 11 | 0.9848±0.0403 | 0.0224±0.0124 | 28 | 10.242±5.033 |
YK | 19 | 0.9740±0.0276 | 0.0229±0.0121 | 45 | 10.471±4.963 |
KO | 14 | 0.9368±0.0306 | 0.0251±0.0132 | 45 | 11.485±5.404 |
AW | 15 | 0.9996±0.0243 | 0.0171±0.0095 | 26 | 7.846±3.869 |
HA | 10 | 0.9560±0.0377 | 0.0179±0.0099 | 28 | 8.209±4.052 |
HO | 7 | 0.8587±0.0337 | 0.0098±0.0056 | 13 | 4.520±2.304 |
Total | 166 | 0.956±0.0035 | 0.022±0.011 | 106 | 9.952±4.561 |
An unrooted phylogenetic tree was reconstructed by neighbor-joining analysis using 166 haplotypes with the best nucleotide substitution mode (HKY+I+G) rooted with the outgroup S. schlegelii. There were no significant genealogical branches or clusters corresponding to sampling localities (Fig.
Genetic differentiation among the 22 locations was evaluated based on Fst values (Table
BH | GZ | HA | HN | HO | HZ | IK | IS | KO | QD | RS | SH | ST | TO | WH | WZ | XM | NI | YK | ZS | AR | AW | |
BH | ||||||||||||||||||||||
GZ | 0.034 | |||||||||||||||||||||
HA | 0.006 | -0.023 | ||||||||||||||||||||
HN | 0.147* | 0.004 | 0.026 | |||||||||||||||||||
HO | 0.674* | 0.610* | 0.657* | 0.654* | ||||||||||||||||||
HZ | 0.085* | 0.018 | 0.017 | -0.001 | 0.649* | |||||||||||||||||
IK | 0.081* | -0.003 | -0.002 | -0.001 | 0.611* | 0.035 | ||||||||||||||||
IS | 0.232* | 0.036 | 0.096 | -0.022 | 0.674* | 0.079 | 0.012 | |||||||||||||||
KO | 0.143* | 0.021 | 0.033 | -0.022 | 0.604* | 0.044 | -0.023 | -0.034 | ||||||||||||||
QD | 0.057* | -0.016 | -0.020 | -0.016 | 0.613* | 0.001 | 0.003 | 0.028 | 0.018 | |||||||||||||
RS | 0.054* | -0.014 | -0.020 | -0.011 | 0.613* | 0.003 | -0.005 | 0.027 | 0.005 | -0.016 | ||||||||||||
SH | 0.019 | -0.036 | -0.054 | -0.007 | 0.633* | 0.011 | -0.008 | 0.037 | 0.010 | -0.033 | -0.039 | |||||||||||
ST | -0.005 | -0.015 | -0.030 | 0.053 | 0.638* | 0.038 | 0.017 | 0.107 | 0.059* | 0.004* | 0.003 | -0.026 | ||||||||||
TO | 0.084* | -0.009 | -0.004 | -0.005 | 0.609* | 0.028 | -0.017 | -0.005 | -0.013 | -0.012 | -0.010 | -0.017 | 0.020 | |||||||||
WH | 0.092* | -0.007 | 0.004 | -0.034 | 0.599* | -0.004 | 0.007 | 0.001 | -0.003 | -0.013 | 0.026 | -0.017 | 0.027* | -0.009 | ||||||||
WZ | 0.041 | 0.046 | -0.018 | 0.109 | 0.664* | 0.077 | 0.064* | 0.200* | 0.109* | 0.042* | 0.050 | 0.024 | 0.036 | 0.074 | 0.067 | |||||||
XM | 0.096* | -0.002 | 0.011 | -0.018 | 0.602* | 0.019 | 0.004 | -0.016 | -0.001 | -0.064 | -0.010 | -0.012 | 0.021* | -0.008 | -0.020 | 0.081* | ||||||
NI | 0.081* | 0.066 | 0.012 | 0.116 | 0.677* | 0.094 | 0.100* | 0.211* | 0.136* | 0.051* | 0.083 | 0.042* | 0.056 | 0.110 | 0.101 | 0.030 | 0.103* | |||||
YK | 0.034 | -0.018 | -0.029 | 0.005 | 0.608* | 0.014 | -0.012 | 0.042 | 0.007 | -0.013 | -0.009 | -0.022 | -0.011 | -0.017 | -0.012 | 0.030 | -0.002 | 0.070* | ||||
ZS | 0.061* | -0.002 | -0.016 | 0.015 | 0.610* | 0.033 | 0.015 | 0.042 | 0.023 | 0.009 | 0.007 | -0.016 | -0.001 | 0.009 | 0.010 | 0.045 | 0.004 | 0.038 | -0.010 | |||
AR | 0.030 | -0.031 | -0.060 | -0.013 | 0.650* | 0.006 | -0.052 | 0.026 | -0.016 | -0.038 | -0.038 | -0.049 | -0.020 | -0.036 | -0.022 | 0.002 | -0.016 | 0.004 | -0.047 | -0.023 | ||
AW | 0.026 | -0.029 | -0.019 | 0.020 | 0.655* | 0.010 | 0.012 | 0.074 | 0.033 | -0.012 | -0.023 | -0.029 | -0.070 | 0.002 | -0.012 | 0.051 | -0.010 | 0.097* | -0.020 | 0.008 | 0.029 |
AMOVA of S. marmoratus populations based on mtDNA control region sequences.
Source of variation | Observed partition | |||
---|---|---|---|---|
Variance components | Percentage variation | Φ Statistics | P | |
1. Complete gene pool (WH, RS, QD, ZS, WZ, XM, ST, HZ, GZ, HN, BH, AR, IK, NI, IS, TO, SH, YK, KO, AW, HA, HO) | ||||
Among populations | 0.6804 | 13.59 | ΦST=0.1359 | 0.0000±0.0000 |
Within populations | 4.3268 | 86.41 | ||
2. Two gene pools (WH, RS, QD, ZS, WZ, XM, ST, HZ, GZ, HN, BH) (AR, IK, NI, IS, TO, SH, YK, KO, AW, HA, HO) | ||||
Among groups | 0.0224 | 0.45 | ΦCT=0.0045 | 0.1927±0.0038 |
Among populations within groups | 0.6688 | 13.33 | ΦSC=0.1339 | 0.0000±0.0000 |
Within populations | 4.3269 | 86.23 | ΦST=0.1377 | 0.0000±0.0000 |
3. Three gene pools (WH, RS, QD) (ZS, WZ, XM, ST, HZ, GZ, HN, BH) (AR, IK, NI, IS, TO, SH, YK, KO, AW, HA, HO) | ||||
Among groups | -0.0389 | -0.78 | ΦCT=-0.0078 | 0.6663±0.0045 |
Among populations within groups | 0.7059 | 14.14 | ΦSC=0.1403 | 0.0000±0.0000 |
Within populations | 4.3268 | 86.64 | ΦST=0.1336 | 0.0000±0.0000 |
4. Five gene pools (WH) (RS, QD) (ZS, WZ) (XM, ST, HZ, GZ, HN, BH) (AR, IK, NI, IS, TO, SH, YK, KO, AW, HA, HO) | ||||
Among groups | -0.1703 | -3.43 | ΦCT=-0.8840 | 0.8841±0.0032 |
Among populations within groups | 0.8066 | 16.25 | ΦSC=0.0000 | 0.0000±0.0000 |
Within populations | 4.3269 | 87.18 | ΦST=0.0000 | 0.0000±0.0000 |
Tajima’s D (D = -1.027; P > 0.05) and Fs test (Fs = -23.917; P < 0.01) results were negative, indicating departure from selective neutrality (Table
The Bayesian skyline plot (Fig.
Bayesian skyline plot showing the effective female S. marmoratus population size through time. Black solid lines are median estimates of NeT (Ne=effective female population size; T=generation time); blue shading represents the 95% confidence interval of NeT. The y-axis was plotted on a logarithmic scale.
Tajima’s D and Fu’s FS, corresponding P-value, and mismatch distribution parameter estimates for each population of S. marmoratus.
Population | Tajima’s D | Fu’s Fs | Mismatch distribution | ||||||
---|---|---|---|---|---|---|---|---|---|
D | P | Fs | P | τ (95% CI) | θ0 | θ1 | SSD | HRI | |
BH | -1.089 | 0.149 | -4.828 | 0.031 | 6.709 (4.043,10.332) | 0.002 | 26.364 | 0.009ns | 0.480ns |
GZ | -0.291 | 0.442 | -5.588 | 0.016 | 12.738 (5.533, 16.066) | 0.000 | 48.730 | 0.018ns | 0.027ns |
HA | -0.508 | 0.333 | -1.114 | 0.271 | 8.049(4.088,10.371) | 0.009 | 66.982 | 0.058ns | 0.124ns |
HN | 0.177 | 0.615 | -4.933 | 0.015 | 12.803(5.627,19.664) | 0.002 | 23.016 | 0.020ns | 0.039ns |
HO | 0.878 | 0.832 | 1.688 | 0.782 | 5.467(0.803,10.469) | 0.967 | 9.946 | 0.032ns | 0.069ns |
HZ | -0.034 | 0.542 | -2.647 | 0.120 | 13.922(0.000,85.547) | 0.000 | 13.865 | 0.011ns | 0.016ns |
IK | -0.224 | 0.450 | -2.256 | 0.173 | 12.078(7.684,14.979) | 0.000 | 99.219 | 0.023ns | 0.051ns |
IS | 0.363 | 0.694 | 0.757 | 0.628 | 14.285(6.186,20.066) | 0.005 | 29.102 | 0.046ns | 0.084ns |
KO | -0.405 | 0.372 | -0.645 | 0.402 | 13.199(8.232,17.143) | 0.000 | 83.906 | 0.032ns | 0.060ns |
QD | -0.457 | 0.351 | -14.813 | 0.000 | 11.434(4.629,16.014) | 0.139 | 29.270 | 0.016ns | 0.022ns |
RS | -0.404 | 0.369 | -1.192 | 0.314 | 13.385(4.031,18.676) | 0.002 | 23.507 | 0.034ns | 0.035ns |
SH | 0.118 | 0.592 | -3.022 | 0.050 | 8.398(1.467,91.398) | 4.888 | 38.945 | 0.046ns | 0.050ns |
ST | -0.659 | 0.297 | -3.169 | 0.092 | 6.348(1.977,22.352) | 4.104 | 31.631 | 0.034ns | 0.036ns |
TO | -0.215 | 0.474 | -5.824 | 0.025 | 11.219(5.793,13.742) | 0.014 | 54.141 | 0.003ns | 0.007ns |
WH | -0.721 | 0.246 | -13.615 | 0.000 | 13.646(5.686,18.615) | 0.004 | 27.832 | 0.012ns | 0.011ns |
WZ | -1.115 | 0.133 | -3.865 | 0.030 | 9.010(4.488,12.814) | 0.021 | 24.199 | 0.010ns | 0.030ns |
XM | -0.417 | 0.384 | -4.241 | 0.063 | 14.230(7.807,18.992) | 0.000 | 33.264 | 0.025ns | 0.026ns |
NI | -1.142 | 0.116 | -1.163 | 0.259 | 3.281(0.191,19.438) | 4.706 | 18.687 | 0.028ns | 0.064ns |
YK | -0.743 | 0.242 | -7.208 | 0.006 | 7.867(4.506,16.061) | 3.841 | 90.938 | 0.018ns | 0.023ns |
ZS | -0.109 | 0.527 | -2.516 | 0.174 | 13.576(5.086,18.025) | 0.000 | 25.162 | 0.012ns | 0.013ns |
AR | -0.742 | 0.240 | 1.813 | 0.137 | 12.568(6.381,16.771) | 0.004 | 47.383 | 0.029ns | 0.061ns |
AW | -0.151 | 0.478 | -9.125 | 0.001 | 2.242(0.559,13.279) | 7.604 | 99999 | 0.009ns | 0.014ns |
Pooled | -1.027 | 0.133 | -23.917 | 0.005 | 12.305(8.693,15.988) | 0.434 | 24.668 | 0.004ns | 0.005ns |
Inbreeding depression and other genetic problems impacted by human behavior can be monitored by assessing genetic diversity under natural conditions (
Compared with anadromous and freshwater fishes, marine species are generally expected to show a low degree of genetic differences among geographic regions owing to their high dispersal potential through planktonic drifting of eggs, larvae, or adults and the absence of physical barriers (
Recent research reveals that the currently most common unintentional pathway for the transport of marine organisms is the ballast water of commercial vessels (
We may conclude that transportation via ballast water may be a source of genetic homogeneity of S. marmoratus. It has been transported among ports and wharves along the NW Pacific Ocean and into rocky coastal areas with the release of ballast water, where it can easily survive (
Using genetics to understand biogeography is important to determine patterns influencing distribution of geographically distant populations. Genetic diversity, genetic distribution patterns, and effective population size were also influenced by paleogeological changes and fluctuations as well as life history and marine environment factors (
Significant genetic differences were revealed between Hyogo and other populations based on the star-like network tree and Fst value analysis, which suggests that the deep and semi-open area of inland waters might have an impact on the geographic isolation. Genetic differences among Hyogo, Behai, and Niigata populations and between Hyogo, Behai, and Niigata and the other populations were primarily significant, and possibly relate to convergence evolution (
Climate fluctuations caused by glacial-interglacial alternation, early life-history, and ecological characteristics, combined with transport via ballast water may play important roles in the extensive gene flow among populations and the current genetic distribution pattern of S. marmoratus. Information provided by the current study will facilitate its comprehensive management. Future studies should be based on informative nuclear markers to provide additional information on genetic structure and differentiation of populations of S. marmoratus.
This work was supported by the National Natural Science Foundation of China (grant numbers 41776171, 41176117, 31172447) and Fund of Key Laboratory of South China Sea Fishery Resources Exploitation & Utilization, Ministry of Agriculture and Rural Affairs, P. R. China (grant numbers FREU2018-04). The authors are very grateful to Dr Linlin Zhao, Dr Zhiqiang Han, Mr Yanping Wang, and Mr Long Yan forsample collection. The authors are also very grateful to Mr Wei Zhou and Dr Jiaguang Xiao for helping with data analysis.