鸡产蛋期剩余采食量的随机回归分析及遗传标记筛选  

Random Regression Analysis on Residual Feed Intake in Laying Hens with and Identification of the Genetic Markers

作　　者：郭军[1] 邵丹[1] 窦套存[1] 马猛[1] 卢建[1] 胡玉萍[1] 王星果[1] 王强[1] 李永峰 郭伟 童海兵[1] 曲亮[1] GUO Jun;SHAO Dan;DOU TaoCun;MA Meng;LU Jian;HU YuPing;WANG XingGuo;WANG Qiang;LI YongFeng;GUO Wei;TONG HaiBing;QU Liang(Jiangsu Institute of Poultry Science,Yangzhou 225125,Jiangsu)

机构地区：[1]江苏省家禽科学研究所,江苏扬州225125

出　　处：《中国农业科学》2024年第22期4568-4577,共10页Scientia Agricultura Sinica

基　　金：科技创新2030—重大项目(2023ZD04052);国家现代农业产业技术体系建设专项(CARS-40-S23);江苏省种业振兴揭榜挂帅项目(JBGS[2021]104);国家现代农业产业技术体系建设专项(CARS-40-K01)。

摘　　要：【目的】以GWAS方法分析剩余采食量(residual feed intake, RFI)随机回归模型多项式系数,解析产蛋期RFI遗传结构,为选育蛋鸡RFI研究奠定基础。【方法】数据采集自东乡绿壳蛋鸡-白来航鸡F2分离群体。收集体重、蛋重、产蛋数和采食量数据,依据Koch方法分别计算40周龄、60周龄剩余采食量。采集1 534只F2代产蛋鸡血液样本,酚仿法提取基因组DNA,以600 K基因芯片进行基因分型。SNPs数据经质量控制后,进行基因型数据填充,并确定分离群体主成分。以随机回归模型分析分离群体方差组分及遗传参数。利用Gemma软件以混合线性模型分析随机回归模型多项式系数,从而获得RFI关联的SNP位点。对显著性位点进行基因注释。针对RFI多项式系数伪表型数据,计算染色体遗传力和单倍型片段长度。【结果】随机模型固定效应、加性遗传效应以及永久环境效应宜嵌入二阶勒让德多项式,残差做同质化处理。鸡产蛋期剩余采食量属于中等遗传力性状,遗传力范围为0.23—0.32,随周龄增加而增加;重复力为0.63—0.68,表明通过3—4次重复测量可准确估计RFI表型值;随着周龄间隔增加,RFI遗传相关系数、表型相关系数呈现逐渐递减;加性遗传矩阵多项式系数第一主成分占96.12%。产蛋期剩余采食量GWAS分析的膨胀系数为1.026,表明线性混合模型中的主成分已经消除潜在的层化结构。鸡5号染色体NAV2基因附近检测到与产蛋期RFI显著关联的QTL遗传座位,在显著性SNP之下有11个支持位点超过基因组潜在水平线。显著性SNP可解释1.73%的表型方差,单倍型片段长度达到286 kb。此外,鸡12号、27号染色体也检测到基因组潜在水平SNP,其中27号染色体上的潜在水平位点位于NGFR上游。染色体遗传力与染色体长度呈正比关系,表明RFI受微效多基因控制。【结论】应用随机回归模型解析了产蛋期RFI遗传参数;以多项式系数为G【Objective】In this study,the polynomial coefficients of the random regression model were analyzed with genome wide association study(GWAS)to dissect the genetic architecture of the residual feed intake(RFI)in the lay,so as to lay the foundation for the selection of the RFI in laying hens.【Method】Data were collected from an F2 segregation population of Dongxiang blue-shelled chickens and White Leghorn. The phenotypic data set included body weight, egg size, egg production, and feed intake. The residual feed intake at 40 and 60 weeks of age were calculated with Koch’s method, respectively. Blood samples were collected in F2 generation. Genomic DNA was extracted with the phenol chloroform method. 1 534 hens were genotyped using 600 K gene microarray. The SNPs data were quality controlled. Missing data was imputed by Beagle software. The principal components were determined by using Plink software. The random regression model was used to analyze the variance components and genetic parameters of the segregation population. Gemma software was used to analyze the polynomial coefficients with a mixed linear model to obtain the significant P-value associated with the RFI in the lay. Gene annotation was carried out on the significant SNP. Chromosome heritability and haplotype block were calculated for RFI polynomial coefficients. 【Result】The second-order Legendre polynomials should be embedded in fixed, additive genetic, and permanent environmental effects. The homogeneous residual variance was harbored in the random regression model. The RFI in the lay showed moderate levels of heritability. The heritability on the RFI ranged from 0.23 to 0.32, and increased with hen age. The repeatabilities were 0.63-0.68, so this indicated that the RFI phenotype value could be accurately estimated by 3-4 repeated measurements. The genetic correlation coefficients in the RFI gradually decreased as the week intervals increased, as did the phenotypic correlation coefficients. The first principal component of the additive gene

关 键 词：剩余采食量 随机回归模型 遗传力 重复力 全基因组关联分析 

分 类 号：S831[农业科学—畜牧学]