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Journal of Tropical Oceanography >

2020 , Vol. 39 >Issue 4: 42 - 49

DOI: https://doi.org/10.11978/2019115

Marine Biology

Genetic polymorphism of the Brushtooth lizardfish Saurida undosquamis based on mitochondrial D-loop sequences

  • LI Min , 1, 2, 3 ,
  • KONG Xiaolan 1 ,
  • XU Youwei 1 ,
  • CHEN Zuozhi , 1, 2, 3
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  • 1. Key Laboratory of Open-Sea Fishery Development, Ministry of Agriculture and Rural Affairs, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510300, China
  • 2. Guangdong Provincial Key Laboratory of Fishery Ecology and Environment, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510300, China
  • 3. Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
CHEN Zuozhi. E-mail:

Received date: 2018-11-13

  Request revised date: 2020-01-11

  Online published: 2020-07-27

Supported by

Foundation item: Natural Science Foundation of Guangdong Province(2014A030310177)

Financial Fund of the Ministry of Agriculture and Rural Affairs(NFZX2018)

Special Fund for Promoting Marine Economic Development of Guangdong Province(GDME-2018E004)

Central Public-interest Scientific Institution Basal Research Fund, South China Sea Fisheries Research Institute, CAFS(2019TS13)

Copyright

Copyright reserved © 2020. Office of Acta Agronomica Sinica All articles published represent the opinions of the authors, and do not reflect the official policy of the Chinese Medical Association or the Editorial Board, unless this is clearly specified.
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Abstract

The Brushtooth lizardfish (Saurida undosquamis) is one of the economically important demersal fishes. The population genetic structure and genetic diversity of S. undosquamis from the coast of China were examined based on the complete control region (D-loop) sequences. A total of 129 individuals from six geographic populations were sequenced. Seventy-one polymorphic sites were detected, which defined 101 haplotypes. Results show S. undosquamis from the coast of China are characterized by quite high haplotype diversity (0.9873 ± 0.0048) and relative low nucleotide diversity (0.0132 ± 0.0067). Phylogenetic tree for haplotypes based on Neighbour-joining method shows shallow topology and reveals no significant divergent clades. Haplotypes from each geographic population were scattered throughout the NJ tree, showing no significant genetic differentiation between populations. Analyses of molecular variance suggest nearly all the genetic variation (99.87%) is attributed to variability within populations, while little variations (0.13%) are found between populations. Most of the pairwise FST values between different populations are quite low, which implies a high rate of gene flow and genetic homogeneity between populations. The results demonstrate high genetic diversity and little genetic differentiation for S. undosquamis from the coast of China. They belong to the same population (panmixia), and a single-stock management regime could be supported in fishery management.

Key words： lizardfish; demersal fishes; fisheries management; genetic structure; genetic diversity

Cite this article

LI Min , KONG Xiaolan , XU Youwei , CHEN Zuozhi . Genetic polymorphism of the Brushtooth lizardfish Saurida undosquamis based on mitochondrial D-loop sequences[J]. Journal of Tropical Oceanography, 2020 , 39(4) : 42 -49 . DOI: 10.11978/2019115

花斑蛇鲻(Saurida undosquamis)是一种隶属灯笼鱼目(Myctophiformes)、狗母鱼科(Synodidae)的暖水性底层鱼类, 分布于东印度洋和西北太平洋近岸(Froese et al, 2019)。在中国主要分布于南海北部近岸海域, 常常与多齿蛇鲻(S. tumbil)混栖(陈再超 等, 1982; 江艳娥 等, 2019)。蛇鲻类是南海区重要的底层经济鱼类, 是底拖网渔获中的优势种(许友伟 等, 2015; 杨炳忠 等, 2017), 在历次渔业资源调查中经常居底层鱼类捕捞量的前列(黄梓荣, 2002; 舒黎明 等, 2014a, b)。然而近年来蛇鲻类资源严重衰退(孙典荣 等, 2004), 目前其渔获物主要以当龄鱼和幼鱼为主(陈作志 等, 2012; 舒黎明 等, 2014a)。
为防止过度捕捞、资源衰退导致种群适应力的下降, 在渔业管理中应当依据种群的特征来分配不同作业区域的捕捞强度(Reiss et al, 2009; Coates et al, 2018)。种群遗传学通过研究种群中基因和基因型频率的维持和变化, 探明种群的遗传特征以及种群之间的联系, 在渔业管理上具有重要参考价值(Palsbøll et al, 2007)。目前, 关于花斑蛇鲻的研究多集中在形态(Chhandaprajnadarsini et al, 2018)、年龄与生长(陈作志 等, 2012; 舒黎明 等, 2014a; 江艳娥 等, 2019)、繁殖(Mali et al, 2017)、种群动力学(Najmudeen et al, 2019)和资源量评估(张俊 等, 2015; 蔡研聪 等, 2018)等方面, 而尚未有种群遗传相关的报道。本研究利用在鱼类种群遗传分析中广泛应用的线粒体控制区(control region, D-loop)序列, 分析了中国海域6个花斑蛇鲻地理群体的种群遗传结构和遗传多样性特征, 旨在为该渔业资源的可持续利用提供科学的参考和依据。

1 材料与方法

1.1 实验材料

实验所用的花斑蛇鲻样本采集于2013年7月至2016年7月之间, 利用底层单拖网渔船在防城港(FCG)、三亚(SY)、海口(HK)、珠海(ZH)、汕头(ST)和泉州(QZ)附近海域(图1)采集。每个采样点随机挑选20余尾样本置于-20℃冷库带回实验室进行实验。采样点经纬度信息和样本数量见表1。
图1 花斑蛇鲻样本的采集点示意图

该图基于“百度地图个性在线编辑器”中审图号为GS(2019)5218号的标准地图制作

Fig. 1 Map of sampling sites for S. undosquamis

表1 花斑蛇鲻样本信息及D-loop区序列遗传多样性参数

Tab. 1 Specimen information of S. undosquamis and genetic diversity parameters based on D-loop sequences

地理群体(缩写) 采样点位置 样本量/个 单倍型数量/个 单倍型多样性(h±SD) 核苷酸多样性(π±SD)
防城港(FCG) 108°30'E, 21°00'N 21 19 0.9905 ± 0.0178 0.0110 ± 0.0058
三亚(SY) 109°46'E, 17°58'N 22 21 0.9957 ± 0.0153 0.0148 ± 0.0077
海口(HK) 111°18'E, 20°18'N 22 21 0.9957 ± 0.0153 0.0135 ± 0.0071
珠海(ZH) 114°05'E, 21°41'N 21 20 0.9952 ± 0.0165 0.0142 ± 0.0074
汕头(ST) 116°55'E, 23°00'N 22 19 0.9827 ± 0.0208 0.0129 ± 0.0068
泉州(QZ) 119°02'E, 24°36'N 21 21 1.0000 ± 0.0147 0.0128 ± 0.0068
总计 / 129 101 0.9873 ± 0.0048 0.0132 ± 0.0067

注: SD为标准差(Standard Deviation)

1.2 基因组DNA提取

取30mg肌肉于1.5mL离心管内, 使用组织破碎仪(BulletBlender STORM, 美国)研磨。研磨前加入海洋动物DNA提取试剂盒(天根, 北京)中的裂解液, 再依据试剂盒说明提取基因组总DNA。用分光光度计检测DNA浓度后置于-20℃保存。

1.3 PCR扩增与测序

依照国际基因数据库中蛇鲻属的线粒体基因组序列, 设计用于扩增D-loop区序列的引物: CR-F(5'-ACCTCTACCACTGACTCCCAAAGCC)和CR-R(5'-TTCTCACAGGGGGGTAGATGCTTG)。聚合酶链式反应(Polymerase Chain Reaction, PCR)体系各组分的浓度依据Taq酶(TaKaRa, 大连)的使用说明来确定。PCR程序如下: 94℃预变性5min; 接着94℃变性20s, 58℃退火20s, 72℃延伸90s, 以上共运行30个循环; 之后72℃延伸4min。选取电泳单一条带产物送华大基因公司进行双向测序, 测序引物与扩增引物相同。

1.4 数据分析

每个样本测序后的正反序列用DNAStar软件中的SeqMan组件拼接, 辅以手工校正。通过BioEdit 7(Alzohairy, 2017)整合所有序列, 然后在MEGA 7(Kumar et al, 2016)中进行比对, 截取完整的D-loop区序列, 并基于AIC(Akaike information criterion)标准, 筛选用于系统发育和群体遗传分析的核苷酸进化最适模型。
所有样本的序列通过Dnasp 6(Rozas et al, 2017)软件生成单倍型, 使用MEGA 7选择邻接法(neighbor-joining, NJ)构建系统发育关系树, 外群选择蛇鲻属另一种类——鳄蛇鲻(Saurida wanieso)D- loop区序列。单倍型的分布及频次依次在各个地理群体进行标记。系统发育的进化模型为MEGA 7确定的带Gamma参数(Gamma shape parameter)和不变位点(invariable sites)的Tamura-Nei模型(TN93+G+I, 其中G=0.50, I=0.87), 用1000次抽样评估系统树各分支的可靠性(bootstrap值)。
各个地理群体样本的遗传多样性指数通过Dnasp 6和Arlequin 3.5(Excoffier et al, 2010)计算获得。利用Arlequin 3.5软件计算地理群体间的遗传分化指数(FST), 采用种群分化测试检测单倍型在群体间分布频率的差别, 并用分子方差分析(analysis of molecular variances, AMOVA)检验不同遗传结构水平上的协方差的显著性(P)。以上分析均通过10000次重复抽样检验显著性, 进化模型均采用上文确定的TN93+G+I模型。

2 结果

2.1 序列特征及遗传多样性

花斑蛇鲻D-loop区序列全长为921bp, 在5′端高变区发现有1个碱基位置(T/-)的缺失。所有序列共包含71个多态性位点, 核苷酸多样性系数π为0.0132 (SD=0.0067) (表1)。所有样本检测到101个单倍型, 单倍型多样性系数h为0.9873 (SD= 0.0048)。绝大部分单倍型(92个)属于个体特异单倍型, 另外9个单倍型为共享单倍型, 其中Hap12和Hap1被所有(6个)群体共有, Hap9被4个群体共有, 其余共享单倍型被3个或2个群体共有(图2)。花斑蛇鲻各个群体间D-loop序列的遗传多样性指数并无显著差异, 与样本总体处于同一水平, 均呈现出很高的单倍型多样性(0.9827~1.0000)和较低的核苷酸多样性(0.0110~0.0148)。
图2 花斑蛇鲻D-loop区序列单倍型邻接树的拓扑结构及在地理群体中的分布

各分支标记大于70%的自展值(百分数, 图中未标示百分号); Saurida wanieso代表外群鳄蛇鲻; 带框的单倍型为共享单倍型; 各颜色代表不同地理群体来源的单倍型, 数字代表单倍型频率

Fig. 2 Topology of NJ tree for S. undosquamis D-loop sequence haplotypes, and distribution of haplotypes among geographic populations.

Bootstrap values of >70% are shown at nodes (percentage). Saurida wanieso is used as outgroup. The shared haplotypes are framed. The colors represent the corresponding geographic populations, and the numbers represent the haplotype frequencies

2.2 单倍型系统发育关系

基于Tamura-Nei距离用邻接法构建的花斑蛇鲻D-loop区序列单倍型的系统发育树(邻接树)见图2。邻接树大部分分支的支持率(自展值)不高, 树形的拓扑结构很浅, 未形成分化显著的支系结构。从单倍型在地理群体中的分布可以看出, 各个群体包含的单倍型均分散于邻接树的支系中, 未形成明显的聚集, 说明各个地理群体之间D-loop区序列的遗传分化不明显。

2.3 种群遗传结构

基于D-loop区序列的花斑蛇鲻地理群体的分子方差分析结果如表2所示。群体之间的遗传变异百分比仅占0.13%, 群体内的遗传变异占99.87%, 样本总体的遗传分化指数仅为0.0013(P=0.3992), 表明花斑蛇鲻整体的遗传变异绝大部分来自于地理群体内部, 各个群体之间的基因交流很频繁, 导致群体间缺乏遗传差异。
表2 花斑蛇鲻6个地理群体D-loop区序列遗传变异的分子方差分析

Tab. 2 Analysis of molecular variance for six populations of S. undosquamis based on D-loop sequences

变异来源 自由度(无量纲) 变异百分比/% 分化指数(Fst) P值
群体间 5 0.13 / /
群体内 123 99.87 / /
所有样本 128 / 0.0013 0.3992

注:“/”表示无此项

花斑蛇鲻地理群体相互之间的遗传分化指数(表3)显示, 除了FCG与ZH群体之间外(FST=0.0478, P=0.0202), 其余群体之间的FST值统计检验均不显著, 且FST值均很小, 甚至是负值, 表明群体间遗传分化水平很低, 存在高度的遗传同质性。
表3 花斑蛇鲻两两地理群体间D-loop区序列的遗传分化指数(对角线下方)及显著性水平(对角线上方)

Tab. 3 Pairwise FST (below diagonal) and P values (above diagonal) among geographic populations of S. undosquamis based on D-loop sequences

FCG SY HK ZH ST QZ
FCG 0.0773 0.0707 0.0202 0.1060 0.1605
SY 0.0269 0.9300 0.6829 0.8408 0.7405
HK -0.0267 -0.0211 0.7952 0.9263 0.8341
ZH 0.0478 -0.0126 -0.0155 0.9421 0.2658
ST -0.0506 -0.0176 -0.0204 -0.0238 0.3424
QZ 0.0164 -0.0155 -0.0178 0.0071 0.0017
此外, 两两群体间的随机交配假设检验(表4)表明, 绝大部分群体间(除了FCG-SY和FCG-HK)的检验水平并不显著, 符合单倍型在群体间是随机分布的假设。样本整体的检测结果(P=1.0000)也显示花斑蛇鲻群体间符合随机交配群(panmixia)的假设, 与分子方差分析呈现的遗传同质性结果一致。
表4 花斑蛇鲻两两地理群体间随机交配假设检验的显著性水平

Tab. 4 P values of exact test of sample differentiation of S. undosquamis based on D-loop haplotype frequencies

FCG SY HK ZH ST
SY 0.0146
HK 0.0351 0.7368
ZH 0.2855 0.2921 0.1818
ST 0.3906 0.7042 0.8730 0.6746
QZ 0.5270 0.3033 0.4864 0.3926 0.9453

3 讨论

管理单元的正确划分是物种资源可持续利用的前提条件(Cadrin et al, 2014), 种群是渔业开发和管理的基本单位, 对渔业区划和资源利用具有指导性意义。分子标记是一种广泛应用的鱼类种群判别方法。文章利用线粒体D-loop区序列标记揭示了中国近海分布的花斑蛇鲻不存在显著遗传分化的谱系, 其遗传变异几乎都来自个体之间, 不同区域群体间不具备明显的遗传分化, 表明花斑蛇鲻间的基因流很强烈, 属于同一个种群(unit population)。
在缺乏物理阻隔的开放海洋环境中, 许多生物在很大地理尺度下表现出无明显的遗传分化(Palumbi 1994; Hewitt 2000), 主要可能归因于其被动或者主动的扩散能力。蛇鲻类生物栖息于近底层, 成体没有明显的集群洄游特性。然而成熟个体全年均可产卵, 产卵场主要分布于水深50~90m的近海, 其浮性卵可以借助近岸的海洋洋流如中国沿岸流(苏纪兰, 2005)和黑潮支流等扩散, 使不同海域间产生基因交流, 从而形成遗传同质化。这种遗传结构类型与南海陆架区大多数鱼类如多齿蛇鲻(孙冬芳 等, 2010)、短尾大眼鲷(Priacanthus macracanthus) (熊丹 等, 2015)和黄斑篮子鱼(Siganus oramin) (黄小林 等, 2018)等类似。这种无遗传分化(no differentiation)的种群在渔业资源的管理上可作为一个管理单元(management units, MUs)来看待(Laikre et al, 2005)。同时需要指出的是, 线粒体序列标记毕竟没有覆盖至整个基因组, 在种群遗传分析时存在分辨率不够的局限性, 为了获得更为确切的种群判别结果, 后续研究中可以引入微卫星、简化基因组标记等进行分析。
遗传多样性是指物种遗传变异的总和, 是物种生存、进化和适应环境的基础。物种对环境的适应能力决定于其遗传多样性或遗传变异的高低(Frankham et al, 2002)。在生物资源的开发利用中, 需要正确认识和关注其遗传多样性水平的变化。过度的开发往往导致该物种资源遗传多样性的降低, 从而有导致其环境适应性降低和增加灭绝的风险。本研究表明中国海域的花斑蛇鲻具有很高的单倍型多样性(h=0.9873)和较低的核苷酸多样性(π= 0.0132)。根据Grant等(1998)对海水鱼类h和π值组合模式的解释, 这种现象可能是花斑蛇鲻种群历史上经历过快速扩张, 随着种群数量的增加, 单倍型多样性显著提高, 而核苷酸变异的累积还未达到一个较高的水平。多数海洋鱼类(基于相同的标记分析)具备类似的高h低π特征, 如同属的多齿蛇鲻(h=0.9570, π=0.0074)(孙冬芳 等, 2010), 以及其他南海近岸鱼类如黄斑篮子鱼(h=0.9000, π=0.0142) (黄小林 等, 2018)、大斑石鲈(Pomadasys maculatus; h=0.9884, π=0.0076)(郜星晨 等, 2016)、卵形鲳鲹(Trachinotus ovatus; h=0.9510, π=0.0209)(吕金磊 等, 2017)、细鳞鯻(Terapon jarbua; h=1.0000, π=0.0220) (杨喜书 等, 2018)和棘头梅童鱼(Collichthys lucidus; h=0.9130, π=0.0141)(梁述章 等, 2019)等。
Pinsky等(2014)指出在高捕捞压力下, 种群遗传结构显著且有效群体大小较小的鱼类的遗传多样性会显著降低。蛇鲻作为一类重要的经济鱼类, 近年来资源开发力度较大(陈作志 等, 2012; 舒黎明 等, 2014a), 而花斑蛇鲻的单倍型多样性仍处于较高水平, 可能是由于花斑蛇鲻的资源量基数大, 且各地理群体间没有显著的遗传差异, 频繁的基因交流在一定程度上抵消了大量捕捞对种质的衰退效应。本研究获得的花斑蛇鲻遗传多样性指标可作为本底资料, 为今后该渔业资源的种质遗传监测与研究提供参照。

References

Publishing order | Descend order by publishing year | Descend order by cited within
[1]
蔡研聪, 徐姗楠, 陈作志, 等, 2018. 南海北部近海渔业资源群落结构及其多样性现状[J]. 南方水产科学, 14(2):10-18.

CAI YANCONG, XU SHANNAN, CHEN ZUOZHI, et al, 2018. Current status of community structure and diversity of fishery resources in offshore northern South China Sea[J]. South China Fisheries Science, 14(2):10-18 (in Chinese with English abstract).

[2]
陈再超, 刘继兴, 1982. 南海经济鱼类[M]. 广州: 广东科学与技术出版社: 184-188(in Chinese).

[3]
陈作志, 邱永松, 徐姗楠, 等, 2012. 北部湾花斑蛇鲻生物学特征的演化[J]. 中国水产科学, 19(2):321-328.

CHEN ZUOZHI, QIU YONGSONG, XU SHANNAN, et al, 2012. Evolution of biological characteristics of Saurida undosquamis (Richardson) in the Beibu Gulf, South China Sea[J]. Journal of Fishery Sciences of China, 19(2):321-328 (in Chinese with English abstract).

[4]
郜星晨, 章群, 薛丹, 等, 2016. 基于线粒体控制区部分序列的南海大斑石鲈遗传多样性分析[J]. 海洋科学, 40(7):41-45.

GAO XINGCHEN, ZHANG QUN, XUE DAN, et al, 2016. Genetic diversity of Pomadasys maculatus in coastal waters of South China Sea via mtDNA control region partial sequences[J]. Marine Sciences, 40(7):41-45 (in Chinese with English abstract).

[5]
黄小林, 李文俊, 林黑着, 等, 2018. 基于线粒体DNA D-loop序列的黄斑篮子鱼群体遗传多样性分析[J]. 热带海洋学报, 37(4):45-51.

HUANG XIAOLIN, LI WENJUN, LIN HEIZHAO, et al, 2018. Genetic variations among Siganus oramin populations in coastal waters of southeast China based on mtDNA control region sequences[J]. Journal of Tropical Oceanography, 37(4):45-51 (in Chinese with English abstract).

[6]
黄梓荣, 2002. 休渔对南海北部多齿蛇鲻资源的影响[J]. 湛江海洋大学学报, 22(6):26-31.

HUANG ZIRONG, 2002. Effect of Close Season on Bloch et Schneider (S. tumbil) Stock in the North of South China Sea[J]. Journal of Zhanjiang Ocean University, 22(6):26-31 (in Chinese with English abstract).

[7]
江艳娥, 许友伟, 范江涛, 等, 2019. 南海北部陆架水域多齿蛇鲻与花斑蛇鲻的年龄与生长[J]. 中国水产科学, 26(1):82-90.

JIANG YAN’E, XU YOUWEI, FAN JIANGTAO, et al, 2019. Age and growth of Saurida tumbil and Saurida undosquamis in the continental shelf of the northern South China Sea[J]. Journal of Fishery Sciences of China, 26(1):82-90 (in Chinese with English abstract).

[8]
梁述章, 宋炜, 马春艳, 等, 2019. 基于线粒体控制区的中国近海棘头梅童鱼群体遗传结构研究[J]. 海洋渔业, 41(2):138-148.

LIANG SHUZHANG, SONG WEI, MA CHUNYAN, et al, 2019. Genetic structure of Collichthys lucidus populations from China coastal waters based on mt DNA control region[J]. Marine Fisheries, 41(2):138-148 (in Chinese with English abstract).

[9]
吕金磊, 章群, 杨喜书, 等, 2017. 基于线粒体控制区的中国南海海域卵形鲳鲹遗传多样性[J]. 海洋渔业, 39(3):241-248.

LV JINLEI, ZHANG QUN, YANG XISHU, et al, 2017. Genetic diversity of Trachinotus ovatus in the South China Sea inferred from Mitochondrial DNA control region sequences[J]. Marine Fisheries, 39(3):241-248 (in Chinese with English abstract).

[10]
舒黎明, 邱永松, 2004a. 南海北部花斑蛇鲻生长死亡参数估计及开捕规格[J]. 湛江海洋大学学报, 24(3):29-35.

SHU LIMING, QIU YONGSONG, 2004a. Estimate for growth, mortality parameters and first capture specification suggestion of Saurida undosquamis (Richardson) in Northern South China Sea[J]. Journal of Zhanjiang Ocean University, 24(3):29-35 (in Chinese with English abstract).

[11]
舒黎明, 邱永松, 2004b. 南海北部多齿蛇鲻生物学分析[J]. 中国水产科学, 11(2):154-158.

SHU LIMING, QIU YONGSONG, 2004b. Biology analysis of Saurida tumbil in northern South China Sea[J]. Journal of Fishery Sciences of China, 11(2):154-158 (in Chinese with English abstract).

[12]
苏纪兰, 袁业立, 2005. 中国近海水文[M]. 北京: 海洋出版社: 1-367(in Chinese).

[13]
孙冬芳, 董丽娜, 李永振, 等, 2010. 南海北部海域多齿蛇鲻的种群分析[J]. 水产学报, 34(9):1387-1394.

SUN DONGFANG DONG LI’NA LI YONGZHEN, et al, 2010. Population analysis of Saurida tumbil in the Northern South China Sea[J]. Journal of Fisheries of China, 2010,34(9):1387-1394 (in Chinese with English abstract).

[14]
孙典荣, 林昭进, 2004. 北部湾主要经济鱼类资源变动分析及保护对策探讨[J]. 热带海洋学报, 23(2):62-68.

SUN DIANRONG, LIN ZHAOJIN, 2004. Variations of major commercial fish stocks and strategies for fishery management in beibu gulf[J]. Journal of Tropical Oceanography, 23(2):62-68 (in Chinese with English abstract).

[15]
熊丹, 李敏, 陈作志, 等, 2015. 南海短尾大眼鲷的种群遗传结构分析[J]. 南方水产科学, 11(2):27-34.

XIONG DAN, LI MIN, CHEN ZUOZHI, et al, 2015. Genetic structure of Priacanthus macracanthus population from the South China Sea[J]. South China Fisheries Science, 11(2):27-34 (in Chinese with English abstract).

[16]
许友伟, 陈作志, 范江涛, 等, 2015. 南沙西南陆架海域底拖网渔获物组成及生物多样性[J]. 南方水产科学, 11(5):76-81.

XU YOUWEI, CHEN ZUOZHI, FAN JIANGTAO, et al, 2015. Composition and biodiversity of catches by bottom trawl fishery in southwestern continent shelf of Nansha area[J]. South China Fisheries Science, 2015,11(5):76-81 (in Chinese with English abstract).

[17]
杨炳忠, 杨吝, 谭永光, 等, 2017. 南海区2种桁杆虾拖网渔获组成调查与分析[J]. 南方水产科学, 13(6):115-122.

YANG BINGZHONG, YANG LIN, TAN YONGGUANG, et al, 2017. Analysis of catch composition of two shrimp beam trawls in South China Sea[J]. South China Fisheries Science, 13(6):115-122 (in Chinese with English abstract).

[18]
杨喜书, 章群, 薛丹, 等, 2018. 中国近海细鳞鯻线粒体控制区的遗传多样性[J]. 生态学报, 38(5):1852-1859.

YANG XISHU, ZHANG QUN, XUE DAN, et al, 2018. Genetic analysis of Terapon jarbua in coastal waters of China by using mitochondrial DNA control region sequencing[J]. Acta Ecologica Sinica, 38(5):1852-1859 (in Chinese with English abstract).

[19]
张俊, 陈国宝, 陈作志, 等, 2015. 南沙南部陆架海域渔业资源声学评估[J]. 南方水产科学, 11(5):1-10.

ZHANG JUN, CHEN GUOBAO, CHEN ZUOZHI, et al, 2015. Acoustic estimation of fishery resources in southern continental shelf of Nansha area[J]. South China Fisheries Science, 11(5):1-10 (in Chinese with English abstract).

[20]
ALZOHAIRY A M, 2011. BioEdit: an important software for molecular biology[J]. GERF Bulletin of Biosciences, 2(1):60-61.

[21]
CADRIN S X, KERR LA, MARIAN S, 2014. Chapter One-Stock identification methods: an overview[M]//CADRIN S X, KERR LA, MARIAN S. Stock Identification Methods. 2nd ed. San Diego: Elsevier Inc.: 1-5.

[22]
CHHANDAPRAJNADARSINI E M, ROUL S K, SWAIN S, et al, 2018. Biometric analysis of brushtooth lizard fish Saurida undosquamis (Richardson, 1848) from Mumbai waters[J]. Journal of Entomology and Zoology Studies, 6(2):1165-1171.

[23]
COATES D J, BYRNE M, MORITZ C, 2018. Genetic diversity and conservation units: dealing with the species-population continuum in the age of genomics[J]. Frontiers in Ecology and Evolution, 6:165.

[24]
EXCOFFIER L, LISCHER H E L, 2010. Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows[J]. Molecular Ecology Resources, 10(3):564-567.

PMID

[25]
FRANKHAM R, BALLOU J D, BRISCOE D A, 2002. Introduction to conservation genetics[M]. Cambridge: Cambridge University Press: 78-104.

[26]
FROESE R, PAULY D, (20190801)[20190925] FishBase [DB/OL]. https://www.fishbase.in/summary/Saurida-undosquamis.html

[27]
GRANT W S, BOWEN B W, 1998. Shallow population histories in deep evolutionary lineages of marine fishes: insights from sardines and anchovies and lessons for conservation[J]. Journal of Heredity, 89(5):415-426.

[28]
HEWITT G M, 2000. The genetic legacy of the Quaternary ice ages[J]. Nature, 405(6789):907-913.

DOI PMID

[29]
KUMAR S, STECHER G, TAMURA K, 2016. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets[J]. Molecular Biology and Evolution, 33(7):1870-1874.

DOI PMID

[30]
LAIKRE L, PALM S, RYMAN N, 2005. Genetic population structure of fishes: Implications for coastal zone management[J]. Ambio, 34(2):111-119.

PMID

[31]
MALI K S, KUMAR M V, FAREJIYA M K, et al, 2017. Reproductive biology of Saurida tumbil (Bloch 1795) and Saurida undosquamis (Richardson 1848) inhabiting Northwest coast of India[J]. International Journal of Pure & Applied Bioscience, 5(6):957-964.

[32]
NAJMUDEEN T M, SEETHA P K, ZACHARIA P U, 2019. Stock dynamics of the brushtooth lizardfish Saurida undosquamis (Richardson, 1848) from a tropical multispecies fishery in the southeastern Arabian Sea[J]. Aquatic Living Resources, 32(5):9.

[33]
PALSBØLL P J, BÉRUBÉ M, ALLENDORF F W, 2007. Identification of management units using population genetic data[J]. Trends in Ecology & Evolution, 22(1):11-16.

PMID

[34]
PALUMBI S R, 1994. Genetic divergence, reproductive isolation, and marine speciation[J]. Annual Review of Ecology and Systematics, 25:547-572.

[35]
PINSKY M L, PALUMBI S R, 2014. Meta-analysis reveals lower genetic diversity in overfished populations[J]. Molecular Ecology, 23(1):29-39.

DOI PMID

[36]
REISS H, HOARAU G, DICKEY-COLLAS M, et al, 2009. Genetic population structure of marine fish: mismatch between biological and fisheries management units[J]. Fish and Fisheries, 10(4):361-395.

[37]
ROZAS J, FERRER-MATA A, SÁNCHEZ-DELBARRIO J C, et al, 2017. DnaSP 6: DNA sequence polymorphism analysis of large data sets[J]. Molecular Biology and Evolution, 34(12):3299-3302.

DOI PMID

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