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GIANLUCA SOTTILE

Combined approaches to identify genomic regions involved in phenotypic differentiation between low divergent breeds: Application in Sardinian sheep populations

  • Autori: Mastrangelo S.; Ben Jemaa S.; Sottile G.; Casu S.; Portolano B.; Ciani E.; Pilla F.
  • Anno di pubblicazione: 2019
  • Tipologia: Articolo in rivista
  • Parole Chiave: genome-wide methods; genomic regions; Ovine BeadChip50K; Sardinian sheep breeds
  • OA Link: http://hdl.handle.net/10447/362520

Abstract

Selective breeding has led to modifications in the genome of many livestock breeds. In this study, we identified the genomic regions that may explain some of the phenotypic differences between two closely related breeds from Sardinia. A total of 44 animals, 20 Sardinian Ancestral Black (SAB) and 24 Sardinian White (SW), were genotyped using the Illumina Ovine 50K array. A total of 68, 38 and 15 significant markers were identified using the case–control genome-wide association study (GWAS), the Bayesian population differentiation analysis (FST) and the Rsb metric, respectively. Comparisons among the approaches revealed a total of 22 overlapping markers between GWAS and FST and one marker between GWAS and Rsb. Three markers detected by Rsb were also located near (<2 Mb) to highly significant regions identified by GWAS and FST analyses. Moreover, one candidate marker identified by GWAS and FST approaches was located in a run of homozygosity island that was shared by both breeds. We identified several genes involved in many phenotypic differences (such as stature and growth, reproduction, ear size, coat colour, behaviour) between the two analysed breeds. This study shows that combining several genome-wide approaches could improve discovery of regions involved in the variability of breeding traits and responsible for the phenotypic diversity even between closely related breeds. Overall, the combination of such genome-wide methods can be extended to other livestock breeds that share between them a similar genetic background, to understand the process that shapes the patterns of genetic variability between closely related populations.