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翘嘴鳜微卫星标记及其与主要经济性状的相关分析 被引量:9

Analysis of Microsatellite DNA Markers Emphasis on Correlation with Some Economically Important Traits in Mandarin fish Siniperca chuatsi
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摘要 利用筛选出的7对具有较高多态性的微卫星标记,检测106尾翘嘴鳜Siniperca chuatsi选育个体的基因组DNA,分析这些微卫星标记与翘嘴鳜体长、体质量和体高的相关性。结果获得67个等位基因,各位点的等位基因数为3~19,片段大小在147~530bp之间;期望杂合度0.5092~0.9207,均值为0.7574;各位点的多态信息含量在0.4639~0.9101之间,均值为0.7197,表明所选择的SSR标记识别力较高,适用于翘嘴鳜选育群体遗传分析和标记辅助育种研究。相关性分析结果表明,G4位点中含有的片段为219bp等位基因的基因型(229/219或219/219)个体的体质量、体长和体高的表型效应显著高于其他的基因型,G10位点中246/246基因型的体质量和体高表型效应显著高于其他基因型,可作为未来翘嘴鳜分子标记辅助育种的重要参考位点。 The genomic DNA properties and the correlation between the microsatellite markers and three economic traits including body weight, body length, and body height were analyzed in 106 individuals of mandarin fish Siniperca chucasi based on the seven high polymorphism microsatellite markers. A total of 67 different alleles were observed, with alleles ranging from 3 to 19 per locus, and the DNA fragment length was varied from 147 bp to 530 bp. The expected heterozygosity was found to be from 0.5092 to 0.9207 with mean value of 0.7574, and the polymorphism information content (PIC) to be ranged from 0.4639 to 0.9101 with mean value of 0.7197, indicating that the selected microsatellite markers were practicable for the genetic analysis and molecular marker assisted breeding of the mandarin fish. The correlation analysis revealed that the genotype in locus G4 with DNA fragment length of 219 (229/219 or 291/219) had significantly higher phenotype effect on body weight, body length and body height than others. However, the genotype (246/246) in locus G10 had significantly higher phenotype effect on body weight and body height. Both loci appear to offer some important reference information in the future research on molecular marker assisted breeding of the mandarin fish.
出处 《水产学杂志》 CAS 2017年第1期11-18,共8页 Chinese Journal of Fisheries
基金 广东省战略性新兴产业核心技术攻关项目(2012A020800001) 广东省教育厅项目(cxzd1104) 佛山市引进科技创新团队资助计划(2014IT100122)
关键词 翘嘴鳜 微卫星标记 经济性状 相关性分析 Siniperca chuatsi microsatellite marker economic trait correlation analysis
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