School of Aquatic and Fishery Sciences, University of Washington Seattle, WA, USA.
Gene Conservation Laboratory, Alaska Department of Fish and Game Anchorage, AK, USA.
Evol Appl. 2014 Mar;7(3):355-69. doi: 10.1111/eva.12128. Epub 2014 Jan 2.
Recent advances in population genomics have made it possible to detect previously unidentified structure, obtain more accurate estimates of demographic parameters, and explore adaptive divergence, potentially revolutionizing the way genetic data are used to manage wild populations. Here, we identified 10 944 single-nucleotide polymorphisms using restriction-site-associated DNA (RAD) sequencing to explore population structure, demography, and adaptive divergence in five populations of Chinook salmon (Oncorhynchus tshawytscha) from western Alaska. Patterns of population structure were similar to those of past studies, but our ability to assign individuals back to their region of origin was greatly improved (>90% accuracy for all populations). We also calculated effective size with and without removing physically linked loci identified from a linkage map, a novel method for nonmodel organisms. Estimates of effective size were generally above 1000 and were biased downward when physically linked loci were not removed. Outlier tests based on genetic differentiation identified 733 loci and three genomic regions under putative selection. These markers and genomic regions are excellent candidates for future research and can be used to create high-resolution panels for genetic monitoring and population assignment. This work demonstrates the utility of genomic data to inform conservation in highly exploited species with shallow population structure.
近年来，群体基因组学的进展使得检测先前未识别的结构、获得更准确的人口参数估计和探索适应性分化成为可能，这可能彻底改变了利用遗传数据管理野生种群的方式。在这里，我们使用限制位点相关 DNA（RAD）测序鉴定了 10,444 个单核苷酸多态性，以探讨来自阿拉斯加西部的 5 个奇努克鲑（Oncorhynchus tshawytscha）群体的种群结构、人口动态和适应性分化。种群结构的模式与过去的研究相似，但我们将个体分配回其起源地的能力得到了极大提高（所有种群的准确率均超过 90%）。我们还计算了在不剔除连锁图谱上鉴定的物理连锁位点的情况下和剔除后的有效种群大小，这是一种针对非模式生物的新方法。有效种群大小的估计通常在 1000 以上，并且当不剔除物理连锁位点时会向下偏。基于遗传分化的异常值检验确定了 733 个位点和三个可能受到选择的基因组区域。这些标记和基因组区域是未来研究的优秀候选者，可以用于创建用于遗传监测和种群分配的高分辨率面板。这项工作证明了基因组数据在具有浅种群结构的高度开发物种的保护中的实用性。
