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南海大眼金枪鱼和黄鳍金枪鱼的群体遗传结构 被引量:10

Population genetics of tunas in South China Sea inferred from control regions
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摘要 测定了南海西沙和南沙群岛附近海区(11~12°N,15°N;110~112°E)黄鳍金枪鱼61尾(17尾成鱼、44尾幼鱼)和大眼金枪鱼26尾(22尾成鱼、4尾幼鱼)的线粒体基因组控制区部分序列(D-loop),结合GenBank数据库中印度洋、太平洋和大西洋群体的同源数据,分析结果:(1)黄鳍金枪鱼与大眼金枪鱼均具极高的单倍型多样性(Hd>99%),聚类树及群体间分化指数(FST和Snn)表明大眼金枪鱼群体分化程度明显高于黄鳍金枪鱼群体;(2)大眼金枪鱼和黄鳍金枪鱼的南海群体与印度洋群体之间基因流最强(Nm=51.638和261.280 10),其次为太平洋群体(Nm=10.868 8和-50.801 81);(3)黄鳍金枪鱼和大眼金枪鱼都基本服从群口扩张模型,而mismatch分布分别呈单、双峰,其中大眼金枪鱼的南海群体扩张较晚(Tau=7.902)且最为明显(θ1/θ0=99 999/14.752)。 The South China Sea(SCS)surrounded by the first island chain is a semi-enclosed sea linking the Indian Ocean and the Pacific Ocean.The population genetic features of the two most important economic species,yellowfin tuna(YFT,Thunnus albacares,17 adults and 44 juveniles)and big eye tuna(BET,T.obesus,22 adults and 4 juveniles)in SCS(11-12°N,15°N;110-112°E),have been analyzed based on the partial mitochondrial D-loop sequences.Our data supported the following conclusions:(1) both species were high nucleotide variation with very high haplotype diversities(Hd99%),while the evidence from fixation indexes,and cluster trees showed the population diversity of BET was higher than those of YFT;(2) For BET and YFT,the strongest gene flow between populations in SCS and the Indian Ocean were 51.638 and 261.280 10,then the Pacific by 10.868 8 and-50.801 81,respectively;(3) both species obey the sudden expansion model.Contrasted with the unimodal of YFT,the mismatch distribution of BET,as well as the SCS population,were bimodal.Moreover,the spanning time of SCS population of BET was later inferred from the Tau(=7.902)with biggest spanning scale(θ1/θ0=99 999/14.752).The results should be basic information for fisheries management,fishing quotas determination as well for aquaculture of tuna.
出处 《水产学报》 CAS CSCD 北大核心 2012年第2期191-201,共11页 Journal of Fisheries of China
基金 国家自然科学基金项目(30972253) 广东省自然科学基金项目(10452408801004224)
关键词 大眼金枪鱼 黄鳍金枪鱼 群体遗传 线粒体基因组控制区 big eye tuna(Thunnus obesus) yellowfin tuna(Thunnus albacares) population genetics D-loop
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