对单一犬种的选择特征的分析表明,最近的选择是对形态和行为特征的选择

Juliane Friedrich, Andrea Talenti, Per Arvelius, Erling Strandberg, Marie J. Haskell, Pamela Wiener
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引用次数: 8

摘要

强大的选择导致现代犬种形态和行为的多样性,这使得狗成为研究这些特征潜在遗传结构的有趣模型动物。然而,品种间分析的结果可能会混淆在品种发育过程中共同选择的行为和形态特征的选择特征。在这项研究中,我们评估了同一品种的狗的独特资源的群体遗传差异,但系统的行为选择只在一个群体。我们利用这些不同的育种背景来识别最近选择的特征。种群内的选择特征在4号染色体和19号染色体上发现,其中行为相关基因的选择特征最强。表现出强烈分化选择信号的区域位于染色体1、24和32上,包括生理特征和行为的候选基因。一些选择特征似乎是由与毛色相关的位点驱动的(Chr 24;ASIP)和长度(Chr 32;FGF5),而另一些则显示出与行为有关的证据。我们的研究结果表明,狗品种的选择特征是由形态和行为的选择驱动的。此外,我们还证明了将选择扫描与关联分析相结合可以有效地解剖选择下的性状。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Unravelling selection signatures in a single dog breed suggests recent selection for morphological and behavioral traits

Unravelling selection signatures in a single dog breed suggests recent selection for morphological and behavioral traits

Strong selection has resulted in substantial morphological and behavioral diversity across modern dog breeds, which makes dogs interesting model animals to study the underlying genetic architecture of these traits. However, results from between-breed analyses may confound selection signatures for behavior and morphological features that were coselected during breed development. In this study, we assess population genetic differences in a unique resource of dogs of the same breed but with systematic behavioral selection in only one population. We exploit these different breeding backgrounds to identify signatures of recent selection. Selection signatures within populations were found on chromosomes 4 and 19, with the strongest signals in behavior-related genes. Regions showing strong signals of divergent selection were located on chromosomes 1, 24, and 32, and include candidate genes for both physical features and behavior. Some of the selection signatures appear to be driven by loci associated with coat color (Chr 24; ASIP) and length (Chr 32; FGF5), while others showed evidence of association with behavior. Our findings suggest that signatures of selection within dog breeds have been driven by selection for morphology and behavior. Furthermore, we demonstrate that combining selection scans with association analyses is effective for dissecting the traits under selection.

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