机构地区:[1]上海海洋大学水产与生命学院,上海201306 [2]中国水产科学研究院黄海水产研究所,海水养殖生物育种与可持续产出全国重点实验室,青岛海洋科技中心海洋渔业科学与食物产出过程功能实验室,山东青岛266071 [3]海南中正水产科技有限公司,海南东方572633
出 处:《水产学报》2024年第12期40-50,共11页Journal of Fisheries of China
基 金:国家重点研发计划(2022YFD2400202);中国水产科学研究院科技创新团队(2020TD26);现代农业产业技术体系专项(CARS-48);广东省“十四五”广东省农业科技创新十大主攻方向“揭榜挂帅”项目(2022SDZG01);泰山学者工程;山东省重点研发计划(农业良种工程)(2024LZGC038)。
摘 要:为鉴定出与凡纳滨对虾生长性状相关的SNP位点和功能基因,本研究针对来自具有快速生长特性的选育和引进品系共74个家系进行生长和存活测试,利用液相芯片“黄海芯1号”(55K SNP)对其中39个家系个体进行高通量基因分型,通过ssGBLUP方法估计了体重性状的基因组遗传参数,并首次利用ssGWAS和FarmCPU方法解析了可能与其关联的SNP位点及功能基因。遗传参数估计结果显示,收获体重的遗传力为0.47,表现为中高水平,表明该群体具有较大的遗传改良潜力。ssGWAS和FarmCPU分析结果显示,两种方法分别筛选到了2个和6个全基因组水平显著关联SNP位点(P<1.26×10^(-6)),表型变异解释率为2.71%~6.76%,其中共有位点1个;分别筛选到9个和14个全基因组水平潜在显著关联的SNP位点(P<2.523×10^(-5)),表型变异解释率为1.33%~6.76%;QQ图显示,FarmCPU较ss GWAS能够更好地控制分析结果的假阳性。根据7个显著关联的SNP位点注释到15个候选基因,与神经系统、肌肉发育和能量代谢等功能有关。其中基于两种方法共有显著关联位点注释到2个基因LOC113809777与LOC113809778,前者为促进糖原分解的水解酶,后者作为转录调控因子,与基因表达调控相关。研究表明,基于液相芯片“黄海芯1号” 55K SNP信息,利用ssGWAS和FarmCPU方法,可以筛选出与凡纳滨对虾收获体重显著关联的SNP位点,研究结果为解析生长性状的遗传基础提供了重要参考。Growth and survival tests were conducted on 74 families,comprising both selection and introduced populations with fast growth rates to identify single nucleotide polymorphisms(SNPs)and functional genes associated with growth traits in Litopenaeus vannamei.High-throughput genotyping of individuals from 39 families was carried out using the"Yellow Sea Chip No.1"liquid chip,which included 55K SNPs.Genomic genetic parameters for harvest body weight were estimated using the ssGBLUP method.Additionally,the ssGWAS and FarmCPU methods were employed for the first time to discover potentially associated SNPs and candidate genes.The estimation of genetic parameters revealed a heritability of 0.47 for harvest body weight,indicating a moderate to high potential for genetic improvement within the population.The ssGWAS and FarmCPU analyses identified two and six genome-wide significant SNPs(P<1.26×10^(−6)),respectively,explaining phenotypic variation ranging from 2.71%to 6.76%.A common SNP was also identified among them.Furthermore,both methods separately screened nine and 14 suggestive genome-wide SNPs(P<2.523×10^(−5)),explaining phenotypic variation ranging from 1.33%to 6.76%.QQ plots demonstrated that FarmCPU exhibited superior control over false positives compared to ssGWAS.Gene annotation of the seven significantly associated SNPs revealed 15 candidate genes related to functions such as the nervous system,muscle development,and energy metabolism.Notably,the common significantly associated SNP was annotated to two genes:LOC113809777,which encoded a hydrolase promoting glycogen hydrolysis,and LOC113809778,a transcriptional regulatory factor associated with gene expression regulation.In conclusion,utilizing the"Yellow Sea Chip No.1"liquid chip,the ssGWAS and FarmCPU methods facilitated the identification of significantly associated SNPs with harvest weight in L.vannamei,offering valuable insights into the genetic basis of growth traits.
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