利用两种统计模型对中国肉用西门塔尔牛屠宰性状的全基因组关联分析

Genome-wide Association Study for Carcass Traits Using Two Statistic Models in Chinese Simmental Beef Cattle

旨在利用两种统计模型对中国肉用西门塔尔牛的胴体重和骨重两个屠宰性状进行全基因组关联分析(GWAS),并比较不同模型的分析结果,促进GWAS的方法研究。本研究以1 301头中国肉用西门塔尔牛为试验材料,通过实地采集和测量获得样品和表型数据,通过提取样品DNA,并利用Illumina BovineHD(770K)芯片分型获得基因型数据,采用线性混合模型(LMM)和复合区间定位-线性混合模型(CIM-LMM)两种模型进行关联分析,定位影响目标性状的显著SNPs及候选基因;同时对两种模型的GWAS结果进行对比,探讨模型的优劣。结果表明,CIM-LMM检测到了LMM检测的所有显著SNPs(P<0.05),显示出更高的统计效力。本研究共识别8和7个SNPs分别与胴体重、骨重显著关联,其中有2个SNPs与这两个性状都相关。这些SNPs主要分布于3、5、6、10、14、16、17号染色体上,其中6号和14号染色体显著SNPs分布较为集中;最终找到了11个候选基因,同时探讨了GCNT4、ALDH1A2、LCORL和WDFY3等基因的功能。本研究为中国肉用西门塔尔牛屠宰性状的遗传机理做了探索,并且为GWAS研究方法开拓了新的思路。

The objective of this study was to conduct a genome-wide association study（GWAS）for carcass weight and bone weight by using two statistic models in 1 301 Chinese Simmental beef cattle and promote the research of GWAS method by comparing the results of the two models.The samples and phenotype data were obtained by field collection and measurement,and the genotype data were obtained by Illumina Bovine HDBeadChip（770 K）after genomic DNA extracted from samples.Two statistic models were used to conduct the GWAS,which including linear mixed model（LMM）and composite interval mapping-linear mixed model（CIM-LMM）,and the significant single nucleotide polymorphisms（SNPs）and candidate genes associated with target traits were identified.In addition,the performance of the models was assessed according to GWAS results.The results showed that the more significant SNPs were detected by CIM-LMM（P〈0.05）,which overlapped the SNPs detected by LMM and performed a higher detection power than LMM.There were 8 and 7 SNPs associated with carcass weight and bone weight,respectively and2 SNPs associated with both traits.These SNPs were mapped on chromosome 3,5,6,10,14,16 and 17,while mainly focused on chromosome 6 and 14.Finally,11 candidate genes were identified and the functions of GCNT4,ALDH1 A2,LCORLand WDFY3 genes were discussed.This research further explore the potential genetic mechanism of carcass traits in Chinese Simmental beef cattle and offer new ideas for GWAS methods.