摘要
为了解花斑副沙鳅Parabotia fasciata的种质资源现状,基于cyt b基因序列比较分析了长江水系4个野生群体和5个养殖群体的遗传多样性水平.结果显示,208个样本共检测到29个单倍型,38个多态位点.群体总体单倍型多态性较高(Hd=0.711),核苷酸多态性较低(Pi=0.002 35),但野生群体(Hd=0.602,Pi=0.003 74)的遗传多样性显著大于养殖群体(Hd=0.381,Pi=0.000 91),说明养殖群体需要增加亲本资源.中性检验、错配分布和贝叶斯天际图结果表明,野生群体在历史上经历了种群扩张.赤水群体的单倍型最多,遗传多样性最高(Hd=0.836,Pi=0.008 99),与其他群体遗传距离大,说明赤水河的花斑副沙鳅资源较丰富,且已形成相对独立、稳定的地理种群,种质优良,适合用作人工繁殖和新品系创制的种源.
Abstract
In order to understand the current status of Parabotia fasciata germplasm resources,the genetic diversity of 9 P.fasciata populations(4 wild populations from Yangtze River and 5 cultured populations)from 7 sites was compared and analyzed based on cyt b gene sequence characteristics.The results showed that a total of 29 haplotypes and 38 polymor-phic loci were detected in 208 samples.The number of haplotypes in the wild populations was 26,while that of the cul-tured populations was only 4.The overall haplotype polymorphism(Hd=0.711)was relatively high,while nucleotide poly-morphism(Pi=0.002 35)was relatively low.The genetic diversity of wild populations(Hd=0.602,Pi=0.003 74)was sig-nificantly higher than that of cultured populations(Hd=0.381,Pi=0.000 91),and this might be due to the cultured popula-tions came from fewer captive-bred parents.The results of neutrality tests,the mismatch peak diagram and Bayesian sky-line plots for the whole wild populations showed a historical expansion.Chishui River population had the most haplotypes and the highest genetic diversity among all the populations(Hd=0.836,Pi=0.008 99),and had large genetic distance and genetic differentiation from other wild populations(0.006 61-0.007 29).These indicated that the current hydrological conditions in the Chishui River were conducive to the hidden habitat and reproduction of P.fasciata.Therefore,Chishui River has a population rich in resources and has formed a stable and relatively independent geographic population with ex-cellent germplasm suitable for future artificial breeding and strain creation.
基金项目
湖北省重点研发计划(2021BBA088)
中国科学院项目(内陆水体鱼类多样性监测网专项)()
内江师范学院创新团队项目(2021TD03)
维普
万方数据