应用Target-Seq技术对肉牛生长性状显著关联基因组区域进行精细定位

Growth production is significant economic trait, which makes the study of its functional genes become current research focuses in molecular breeding of beef cattle. Application of Genome-wide association study (GWAS) is becoming a research trend for the identification of a number of genetic variants and candidate genes in complex quantitative traits loci related to economically important traits of the main livestock and poultry. However, the challenge facing the next step of GWAS is how to perform further analysis by utilizing the genome-wide genotype data to identify more susceptibility genes/loci of complex traits. Fine mapping appears to be an effective strategy to identify the causative variants and genes in the susceptibility regions associated with economically important traits for the post-GWAS era.. Based on the statistical analysis of phenotypic data from our resource population of Chinese Simmental and the results of high-density SNP genotyping chip, GWAS for a total of 10 growth traits will be performed. Then, we will select the candidate genomic regions significantly related to growth traits and obtain comprehensive genome information in the trait-associated regions using Targeted Sequencing (Target-Seq) technology. Fine mapping will be carried out by the joint analysis of next-generation sequencing and genome-wide association study (NGS-GWAS). Combined with bioinformatics method, the causative variants and candidate genes in the susceptibility regions associated with growth traits of beef cattle will be identified, which will facilitate us to detect major genes and genetic variations involved in growth traits and provide insights into theoretic basis of functional validation.

生长性状是肉牛的重要经济性状，对其功能基因定位一直是肉牛分子育种的研究热点。应用GWAS方法发掘数量性状候选基因是当前畜禽经济性状研究的主要分析策略，但是如何利用GWAS数据提高发现功能基因/位点的效能，是GWAS面对的挑战。后GWAS时代的主要任务之一就是要对复杂经济性状易感区域内的关键遗传变异进行精细定位，并阐明其生物学功能。.本研究基于团队构建的中国西门塔尔牛资源群体表型数据统计分析和高密度SNP芯片分型结果，开展肉牛10个生长性状指标的GWAS分析，选择与生长性状显著相关的候选基因组区域，应用目标区域测序(Target-Seq)技术，挖掘目标区域内全面遗传变异信息。通过对变异所在位点的精细定位，开展NGS-GWAS联合分析，并结合生物信息学方法，从基因组水平鉴定出目标区域内与肉牛生长性状最显著关联的关键SNP位点和候选基因，为进一步鉴别影响肉牛生长性状的主效基因和遗传变异奠定理论。

肉牛生长的快慢直接影响肉牛行业整体盈利能力和效率，进而影响肉牛产业的发展。生长性状作为复杂的数量性状，由多基因控制，受遗传和环境的共同影响。对显著关联SNP所在的染色体区域进行目标区域重测序，再与GWAS分析策略相互补充，是后GWAS时代复杂性状遗传机制研究的主要方向之一。本研究基于团队构建的中国西门塔尔牛群体为主要研究对象，开展肉牛10个生长性状指标的GWAS分析，定位出一系列与肉牛生长性状相关的基因组区域，通过定制特异性探针，与基因组DNA进行芯片杂交，富集特定染色体的靶标区域DNA，再结合高通量测序技术，鉴定出了目标区域内全部遗传变异，初步确认出与肉牛生长性状相关的候选功能基因和显著SNPs位点，包括罕见变异位点和small Indels等，完成了肉牛生长性状紧密关联目标区域的精细定位。通过分步变异筛选，剔除群体中同义突变和常见突变，重点关注不同表型组中的稀有非同义突变，基于集合的分析鉴定出了在不同的表型组合中所共享的关键稀有变异，首次获得了生长性状高表型组共享的69个非同义稀有变异的62个基因，以及低表型组中67个非同义稀有变异相关的66个基因，对这些基因进行GO和KEGG富集分析发现它们参与到各种生长发育过程。为提升对它们之间基因互作关系的系统理解，我们分别对这两组基因构建了共表达网络，结果发现这两组基因构建的子网络明显不同。总之，本项目应用目标区域测序（Target-Seq）技术，精确定位了目标区域内全部遗传变异信息，挖掘出与研究性状密切关联的SNPs位点和候选基因，初步揭示了这些基因和变异位点的生物学功能，为明确肉牛生长性状的调控机理提供了参考。