冰岛马的步态遗传学不仅限于 DMRT3,RELN 和 STAU2 也被确定为两个新的候选基因

IF 3.6 1区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE Genetics Selection Evolution Pub Date : 2023-12-11 DOI:10.1186/s12711-023-00863-6
Heiðrún Sigurðardóttir, Henrik Boije, Elsa Albertsdóttir, Thorvaldur Kristjansson, Marie Rhodin, Gabriella Lindgren, Susanne Eriksson
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引用次数: 0

摘要

在驯养的动物中,许多重要的性状都很复杂,受到大量基因、基因相互作用和环境影响的调控。冰岛马的步态 "步伐 "能力在很大程度上受 DMRT3 基因单一突变的影响,但也可能存在遗传修饰因子。本研究旨在通过全基因组关联研究(GWAS)确定影响步态能力和步态质量的新遗传因素,并将新发现与之前确定的数量性状位点(QTL)和突变相关联。利用 670 K+ Axiom 马基因分型阵列对 372 匹冰岛马进行了基因分型,其中 362 匹马的步态评分来自育种现场测试。一项基因组分析发现,Equus caballus 染色体(ECA)4、9 和 20 上的几个 SNP 与育种现场测试的步态评分相关(p < 1.0 × 10-5)。ECA4 和 9 上的两个新 QTL 分别位于 RELN 和 STAU2 基因内,这两个基因以前曾与小鼠的运动行为有关。这两个 QTL 上最常见的单倍型对步速评分有很大的有利影响。RELN基因的第二高频单倍型与tölt、toott、gallop和canter的得分呈正相关。同样,STAU2 基因的第二高频单倍型对小跑和奔跑的得分也有有利影响。在起搏能力不同的马匹组中,还观察到 RELN 和 STAU2 基因单倍型的不同基因型比例。此外,还检测到 RELN 和 STAU2 基因的 QTL 与 DMRT3 基因之间存在相互作用(p < 0.05)。据估计,ECA4、9和20上的新QTL以及DMRT3变异的影响共同占步态步伐表型变异的27.4%。除了 DMRT3 基因的贡献之外,我们的研究结果还提供了有关步速遗传结构的宝贵信息,并指出了导致这一性状复杂性的遗传相互作用。要全面了解潜在的遗传因素和相互作用,还需要进一步的研究。
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The genetics of gaits in Icelandic horses goes beyond DMRT3, with RELN and STAU2 identified as two new candidate genes
In domesticated animals, many important traits are complex and regulated by a large number of genes, genetic interactions, and environmental influences. The ability of Icelandic horses to perform the gait ‘pace’ is largely influenced by a single mutation in the DMRT3 gene, but genetic modifiers likely exist. The aim of this study was to identify novel genetic factors that influence pacing ability and quality of the gait through a genome-wide association study (GWAS) and correlate new findings to previously identified quantitative trait loci (QTL) and mutations. Three hundred and seventy-two Icelandic horses were genotyped with the 670 K+ Axiom Equine Genotyping Array, of which 362 had gait scores from breeding field tests. A GWAS revealed several SNPs on Equus caballus chromosomes (ECA) 4, 9, and 20 that were associated (p < 1.0 × 10–5) with the breeding field test score for pace. The two novel QTL on ECA4 and 9 were located within the RELN and STAU2 genes, respectively, which have previously been associated with locomotor behavior in mice. Haplotypes were identified and the most frequent one for each of these two QTL had a large favorable effect on pace score. The second most frequent haplotype for the RELN gene was positively correlated with scores for tölt, trot, gallop, and canter. Similarly, the second most frequent haplotype for the STAU2 gene had favorable effects on scores for trot and gallop. Different genotype ratios of the haplotypes in the RELN and STAU2 genes were also observed in groups of horses with different levels of pacing ability. Furthermore, interactions (p < 0.05) were detected for the QTL in the RELN and STAU2 genes with the DMRT3 gene. The novel QTL on ECA4, 9, and 20, along with the effects of the DMRT3 variant, were estimated to account jointly for 27.4% of the phenotypic variance of the gait pace. Our findings provide valuable information about the genetic architecture of pace beyond the contribution of the DMRT3 gene and indicate genetic interactions that contribute to the complexity of this trait. Further investigation is needed to fully understand the underlying genetic factors and interactions.
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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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