Enhanced genetic differentiation of Japanese chum salmon identified from a meta-analysis of allele frequencies
Enhanced genetic differentiation of Japanese chum salmon identified from a meta-analysis of allele frequencies
复制标题
通过等位基因频率的荟萃分析发现日本鲑鱼的遗传分化增强
DOI：
10.1101/828780
复制
发表时间：
2021
影响因子：
4.1
通讯作者：
Shuichi Kitada and Hirohisa Kishino
中科院分区：
文献类型：
--
作者：
Abe H.;Takeuchi T.;Taru M.;Sato-Okoshi;W.;Okoshi;K.;Shuichi Kitada and Hirohisa Kishino
遗传资源鉴定（GSI）是太平洋鲑（OncorhynchusSpp.）该研究提供了丰富的环太平洋地区等位酶、微卫星和单核苷酸多态性（SNP）的遗传基线数据。在这里，我们分析了成年鲑鱼（Oncorhynchus凯塔）的已发表数据集，即10个微卫星，53个SNP和线粒体DNA位点（mtDNA 3，控制区和NADH-3组合），来自相同分布范围内的495个地点（n= 61，813）。微卫星位点的TreeMix分析确定了最大的收敛向日本/韩国人群，并建议从日本/韩国到俄罗斯和阿拉斯加半岛的两个混合事件。SNPs是有目的地从快速进化的基因中收集的，以增加GSI的能力。最大的预期杂合性在日本/韩国人群的微卫星，而它是最大的在阿拉斯加西部人群的SNP，反映了SNP的发现过程。对微卫星SNP群体结构的回归表明，根据与预测结构的偏差选择SNP位点。具体而言，我们将SNP的采样位置与微卫星的采样位置相匹配，并对从微卫星成对FST值获得的匹配位置的二维标度（MDS）进行SNP等位基因频率的回归分析。MDS的第一轴表明，在美国和俄罗斯人口的纬度渐变，而第二轴显示日本/韩国人口的分化。前5个异常SNP包括mtDNA 3、U 502241（未知）、GnRH 373、ras 1362和TCP 178，它们是通过主成分分析确定的。我们总结了53个核基因周围的SNPs和mtDNA 3位点的功能，通过参考基因数据库系统，并提出他们可能会影响鲑鱼的健身。
Genetic stock identification (GSI) is a major management tool of Pacific salmon (OncorhynchusSpp.) that has provided rich genetic baseline data of allozymes, microsatellites, and single‐nucleotide polymorphisms (SNPs) across the Pacific Rim. Here, we analyzed published data sets for adult chum salmon (Oncorhynchus keta), namely 10 microsatellites, 53 SNPs, and a mitochondrial DNA locus (mtDNA3, control region, and NADH‐3 combined) in samples from 495 locations in the same distribution range (n= 61,813). TreeMix analysis of the microsatellite loci identified the greatest convergence toward Japanese/Korean populations and suggested two admixture events from Japan/Korea to Russia and the Alaskan Peninsula. The SNPs had been purposively collected from rapidly evolving genes to increase the power of GSI. The largest expected heterozygosity was observed in Japanese/Korean populations for microsatellites, whereas it was largest in Western Alaskan populations for SNPs, reflecting the SNP discovery process. A regression of SNP population structures on those of microsatellites indicated the selection of the SNP loci according to deviations from the predicted structures. Specifically, we matched the sampling locations of the SNPs with those of the microsatellites and performed regression analyses of SNP allele frequencies on a 2‐dimensional scaling (MDS) of matched locations obtained from microsatellite pairwiseFSTvalues. The MDS first axis indicated a latitudinal cline in American and Russian populations, whereas the second axis showed differentiation of Japanese/Korean populations. The top five outlier SNPs included mtDNA3, U502241 (unknown), GnRH373, ras1362, and TCP178, which were identified by principal component analysis. We summarized the functions of 53 nuclear genes surrounding SNPs and the mtDNA3 locus by referring to a gene database system and propose how they may influence the fitness of chum salmon.