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Variation of Amplified Fragment Length Polymorphisms in Yukon River Chum Salmon: Population Structure and Application to Mixed-Stock Analysis

机译:育空河鲑鱼中扩增片段长度多态性的变异:种群结构及其在混合种群分析中的应用

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摘要

The population structure of fall-run Yukon River chum salmon Oncorhynchus keta has been studied previously using allozyme, microsatellite, and mitochondria! markers. However, genetically similar populations from tributaries near the U.S.-Canadian border render mixed-stock analyses (MSAs) difficult in the fisheries from lower portions of the Yukon River; MSA simulation apportionment estimates are less than 90% accurate for the border region divided by country of origin. To increase the accuracy and precision of contribution estimates to harvests in the Yukon River and to improve our understanding of the population structure of fall-run chum salmon, we investigated the variation of amplified fragment length polymorphisms (AFLPs). Our results show thatYukon River chum salmon populations are structured by both seasonal race and geographic region. As expected, the MSA is most successful when mixtures are allocated to geographic regions. Both AFLP and microsatellites have better than 80% apportionment accuracy in MSA simulations for the U.S. and Canadian border regions, but neither approach clearly or consistently outperforms the other. In general, the population structure resolved by AFLP is similar to that observed for other genetic markers. Relatively weak population divergence, rather than shortcomings of the previously studied genetic marker systems, appears to be the limiting factor in attaining high levels of accuracy and precision in MSA.
机译:先前已使用同工酶,微卫星和线粒体研究了秋天运行的育空河密鲑Oncorhynchus keta的种群结构!标记。然而,在美加边境附近,支流的遗传相似种群使育空河下游部分的渔业难以进行混合种群分析。对于边界区域除以原籍国,MSA模拟分配估计的准确度不到90%。为了提高对育空河收成的估计贡献的准确性和准确性,并增进我们对秋色鲑的种群结构的了解,我们研究了扩增片段长度多态性(AFLP)的变异。我们的结果表明,育空河的鲑鱼种群是由季节性种族和地理区域构成的。不出所料,将混合物分配到地理区域时,MSA最成功。在美国和加拿大边境地区的MSA模拟中,AFLP和微卫星的分摊精度均高于80%,但两种方法都不明显或始终优于其他方法。通常,AFLP解析的种群结构与其他遗传标记观察到的相似。相对较小的群体差异,而不是先前研究的遗传标记系统的缺点,似乎是在MSA中获得高水平准确性和精密度的限制因素。

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