基于序列的比利时蓝肉牛线性分类性状GWAS揭示了哺乳动物调节体型基因的新编码变异

IF 3.6 1区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE
José Luis Gualdrón Duarte, Can Yuan, Ann-Stephan Gori, Gabriel C. M. Moreira, Haruko Takeda, Wouter Coppieters, Carole Charlier, Michel Georges, Tom Druet
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引用次数: 0

摘要

为基因组选择程序进行基因分型和表型分型的个体队列为更好地理解与复杂性状相关的遗传变异提供了机会。在这里,我们对精选肉牛的体型和肌肉发育相关性状进行了关联研究。我们利用多个性状信息来提炼和解释显著的关联。在对14,762头比利时蓝牛肉(BBB)奶牛进行多步基因型插入到序列水平后,我们对与肌肉发育和体型相关的11个性状进行了全基因组关联研究(GWAS)。经鉴定的37个全基因组显著数量性状位点(QTL)根据其位置可浓缩为11个独特的QTL区域。在大多数这些区域发现了多效效应的证据(例如,相关关联信号,候选变异可信集(CS)之间的重叠)。因此,我们采用多性状方法结合不同性状的信息来完善CS。在几个QTL区域,我们发现了与其他物种的生长和身高相关的强候选基因,如LCORL-NCAPG或CCND2。对于其中一些基因,在CS中发现了相关的候选变异,包括EZH2、PAPPA2和ADAM12中三个新的错义变异,LCORL中可能还有两个额外的编码变异,以及与CCND2和ARMC12相关的候选调节变异。引人注目的是,与尺寸或肌肉发育特征相关的其他四个QTL区域与先前发现的五种(隐性)有害编码变体相关。我们的研究进一步支持了一组共同的基因控制着哺乳动物物种的体型。特别是,我们在人类和牛的身高相关基因列表中添加了新的基因。我们还在其中一些基因中发现了新的强有力的候选因果变异,加强了它们因果关系的证据。在我们的QTL区域发现了几个品种特异性的隐性有害变异,这可能是BBB牛肌肉发育的极端选择的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sequenced-based GWAS for linear classification traits in Belgian Blue beef cattle reveals new coding variants in genes regulating body size in mammals
Cohorts of individuals that have been genotyped and phenotyped for genomic selection programs offer the opportunity to better understand genetic variation associated with complex traits. Here, we performed an association study for traits related to body size and muscular development in intensively selected beef cattle. We leveraged multiple trait information to refine and interpret the significant associations. After a multiple-step genotype imputation to the sequence-level for 14,762 Belgian Blue beef (BBB) cows, we performed a genome-wide association study (GWAS) for 11 traits related to muscular development and body size. The 37 identified genome-wide significant quantitative trait loci (QTL) could be condensed in 11 unique QTL regions based on their position. Evidence for pleiotropic effects was found in most of these regions (e.g., correlated association signals, overlap between credible sets (CS) of candidate variants). Thus, we applied a multiple-trait approach to combine information from different traits to refine the CS. In several QTL regions, we identified strong candidate genes known to be related to growth and height in other species such as LCORL-NCAPG or CCND2. For some of these genes, relevant candidate variants were identified in the CS, including three new missense variants in EZH2, PAPPA2 and ADAM12, possibly two additional coding variants in LCORL, and candidate regulatory variants linked to CCND2 and ARMC12. Strikingly, four other QTL regions associated with dimension or muscular development traits were related to five (recessive) deleterious coding variants previously identified. Our study further supports that a set of common genes controls body size across mammalian species. In particular, we added new genes to the list of those associated with height in both humans and cattle. We also identified new strong candidate causal variants in some of these genes, strengthening the evidence of their causality. Several breed-specific recessive deleterious variants were identified in our QTL regions, probably as a result of the extreme selection for muscular development in BBB cattle.
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来源期刊
Genetics Selection Evolution
Genetics Selection Evolution 生物-奶制品与动物科学
CiteScore
6.50
自引率
9.80%
发文量
74
审稿时长
1 months
期刊介绍: Genetics Selection Evolution invites basic, applied and methodological content that will aid the current understanding and the utilization of genetic variability in domestic animal species. Although the focus is on domestic animal species, research on other species is invited if it contributes to the understanding of the use of genetic variability in domestic animals. Genetics Selection Evolution publishes results from all levels of study, from the gene to the quantitative trait, from the individual to the population, the breed or the species. Contributions concerning both the biological approach, from molecular genetics to quantitative genetics, as well as the mathematical approach, from population genetics to statistics, are welcome. Specific areas of interest include but are not limited to: gene and QTL identification, mapping and characterization, analysis of new phenotypes, high-throughput SNP data analysis, functional genomics, cytogenetics, genetic diversity of populations and breeds, genetic evaluation, applied and experimental selection, genomic selection, selection efficiency, and statistical methodology for the genetic analysis of phenotypes with quantitative and mixed inheritance.
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