Genomic insights into the recent evolution and biodiversity of Italian sheep breeds

基因组学视角揭示意大利绵羊品种的近期演变和生物多样性

阅读:1

Abstract

Italy hosts a remarkable ovine biodiversity shaped by centuries of history, regional traditions, and environmental heterogeneity. This diversity sustains agricultural production as well as ecosystem services and cultural heritage. Yet, many local breeds are undergoing severe demographic decline. To explore these dynamics, we analyzed census data from all registered Italian sheep, which revealed highly variable situations across breeds but confirmed that most are currently at risk of extinction. To complement this picture, we genotyped 34 Italian sheep populations using the Ovine50K BeadChip and compared them with foreign breeds with recognized herd books in Italy. Genomic analyses of diversity (including inbreeding and effective population size), population structure, and genomic background provided insights into the state of genetic variation and relationships among breeds, including patterns of introgression. By comparing these results with data from populations sampled twenty years ago, we assessed temporal changes in diversity, genomic background, and selection signatures. Fst analyses highlighted genomic regions that have undergone the most marked shifts, allowing us to explore associated genes and QTLs. Correlations between Fst and environmental changes across 20 variables further emphasized the role of local adaptation in shaping genomic landscapes. In addition, local ancestry inference in two breeds (Gentile di Puglia and Nera di Arbus) with evidence of recent admixture identified genomic regions influenced by gene flow. Overall, our study illustrates the complex evolutionary dynamics of Italian sheep breeds and underscores the importance of integrating demographic analyses with genomic tools to guide their conservation and sustainable management.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。