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A novel method for the identification of seahorses (genus Hippocampus) using cross-species amplifiable microsatellites

机译:一种利用跨物种可扩增微卫星鉴定海马(海马属)的新方法

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Seahorses (genus Hippocampus) are flagship species for marine conservation and evolutionary studies. Wild seahorse populations have declined sharply because of overfishing or other disrupting activities, which are attracting increasing global concern for their threatened status. For study of their population status, the identification of young seahorses by morphological examination has been controversial and remains a difficult task due to overlapping of meristic and morphological characters. Here we reported a simple and sensitive method to identify seahorse species from China based on cross-species microsatellites. The cross-species amplification success rate varied from 40.0% to 90.0% depending on the species, with a mean value of 59.6%. According to allele presence/absence of cross-species microsatellites, all the individuals representing 10 seahorse species could be accurately identified using one or more loci. In addition, we found both genome size and genetic distance between the source and target species negatively correlated with microsatellite cross-species amplification success. Moreover, a Neighbor-Joining dendrogram was constructed based on genetic similarity and suggested that the 10 seahorse species could be divided into four groups. These results demonstrate our method could improve the identification of seahorses, providing data to understand seahorse stock structure and recruitment dynamics, and therefore resources conservation. (C) 2015 Elsevier B.V. All rights reserved.
机译:海马(海马属)是海洋保护和进化研究的旗舰物种。由于过度捕捞或其他破坏性活动,野生海马种群急剧减少,这引起全球对其威胁地位的日益关注。为了研究它们的种群状况,通过形态学检查鉴定年轻海马一直是有争议的,并且由于特征和形态特征的重叠,仍然是一项艰巨的任务。在这里,我们报告了一种基于跨物种微卫星识别中国海马物种的简单而灵敏的方法。跨物种的扩增成功率从40.0%到90.0%取决于物种,平均值为59.6%。根据等位基因是否存在跨物种微卫星,可以使用一个或多个基因座准确识别代表10种海马物种的所有个体。此外,我们发现基因组大小和源物种与目标物种之间的遗传距离与微卫星跨物种扩增成功呈负相关。此外,基于遗传相似性构建了邻居加入树状图,并建议将10种海马物种分为四类。这些结果表明,我们的方法可以改善海马的识别,提供数据以了解海马的种群结构和招聘动态,从而节省资源。 (C)2015 Elsevier B.V.保留所有权利。

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