黄岩(1994–),女,硕士研究生,研究方向为数量遗传学.E-mail:ayan0827@163.com
S917
国家重点研发计划“蓝色粮仓科技创新”重点专项(2018YFD0900201)； 中央公益性科研院所基本科研业务费专项资金项目(2019ZY09).
在间断性状全基因组关联分析中, 当基因组数据存在复杂群体分层时, 广义线性模型需要同时考虑上百个协变量, 其求解速度会大大下降而且还会产生异常解。本研究目的是把简单回归结果中显著位点的效应值和遗传力的尺度转化为可解释的广义线性回归结果。首先对亲缘关系矩阵进行谱分解, 特征向量作为主成分(PC), 矫正间断性状中的群体分层; 再求解每一个主成分的回归系数, 并将众多协变量与其各自的回归系数相乘, 得到的乘积合并为一个新的协变量; 然后将它作为简单回归的协变量, 逐个对标记进行关联检验; 最后对筛选获得的候选数量性状核苷酸(QTN)进行广义线性模型回归分析, 将效应和方差转化为广义线性回归模型尺度。采用本研究提出的方法与直接考虑主成分的广义线性回归模型, 分别对半滑舌鳎(Cynoglossus semilaevis)的性逆转性状进行全基因组关联分析, 结果表明，本研究方法的 QTN 检测效率更高，共检测出 6 个 QTN，其中 5 个 QTN 位于 Z 染色体上， 1 个 QTN 位于 W 染色体上，并且在基因组控制方面，本研究方法的基因组控制值与直接考虑 PC 的广义线性回归模型的基因组控制值相同，均为 1.01，处于较优水平。结论认为, 基于主成分分析的简单回归尺度转换方法能够在保证准确率的情况下提升 QTN的检测效率, 实现间断性状快速稳健的全基因组关联分析, 同时检测出的 QTN能为半滑舌鳎性逆转性状的研究提供理论指导。
In genome-wide association analysis of discontinuous traits, when complex population stratification exists in genomic data, the generalized linear model needs to consider hundreds of covariables at the same time, which slows the calculation speed and presents abnormal solutions. This study aimed to transform the effect value and heritability scale of significant loci in simple linear regression results into interpretable generalized linear regression results. First, the eigenvectors solved by spectral decomposition of the kinship matrix were considered as the principal components (PCs) to correct the population stratification in the discontinuous traits dataset. Then, a new covariate was formed through the sum of the multiplications of each covariate, and its regression coefficient of the principal component was computed using a linear regression model. The new covariate was used as the covariable of simple regression to carry out correlation tests for markers one by one. Finally, the generalized linear model was used for regression analysis of candidate quantitative trait nucleotides (QTNs), and the effects and variance were transformed into the generalized linear regression model scale. The genome-wide association analysis of sex reversal traits in half-smooth tongue sole (Cynoglossus semilaevis) was conducted using the new method and the generalized linear regression model with direct consideration of principal components: The results show that the QTN detection efficiency of this method is higher, a total of 6 QTNs were detected, including 5 QTNs on Z chromosome and 1 QTN on W chromosome. In addition, in terms of genome control, the genome control value of the method in this study is the same as that of the generalized linear regression model which directly considers PC, which is at an optimal level of 1.01. Therefore, the simple regression scaling transformation method based on principal component analysis improved the detection power for QTN detection, while retaining the accuracy of results, with fast and robust genome-wide association analysis of discontinuous traits. In addition, the QTNs detected by the new method proposed in this study can provide theoretical guidance for the study of sex reversal traits in half-smooth tongue soles.
黄岩,宋禹昕,蒋丽,杨润清.简单回归尺度转换实现半滑舌鳎性逆转基因的高效定位[J].中国水产科学,2022,29(2):245-251
HUANG Yan, SONG Yuxin, JIANG Li, YANG Runqing. Efficiently mapping the sex reversal genes of half-smooth tongue sole, Cynoglossus semilaevis using simple regression scale transformation[J]. Journal of Fishery Sciences of China,2022,29(2):245-251
