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Updated: Dec 25, 2025

Genetic Variant Detection in the CALR gene using High Resolution Melting Analysis
Published on: August 26, 2020
Genome-wide detection of signatures of selection in three Valdostana cattle populations
Salvatore Mastrangelo1, Slim Ben Jemaa2, Elena Ciani3
1Dipartimento Scienze Agrarie, Alimentari e Forestali, University of Palermo, Palermo, Italy.
Abstract:
The Valdostana is a local dual purpose cattle breed developed in Italy. Three populations are recognized within this breed, based on coat colour, production level, morphology and temperament: Valdostana Red Pied (VPR), Valdostana Black Pied (VPN) and Valdostana Chestnut (VCA). Here, we investigated putative genomic regions under selection among these three populations using the Bovine 50K SNP array by combining three different statistical methods based either on allele frequencies (FST ) or extended haplotype homozygosity (iHS and Rsb). In total, 8, 5 and 8 chromosomes harbouring 13, 13 and 16 genomic regions potentially under selection were identified by at least two approaches in VPR, VPN and VCA, respectively. Most of these candidate regions were population-specific but we found one common genomic region spanning 2.38 Mb on BTA06 which either overlaps or is located close to runs of homozygosity islands detected in the three populations. This region included inter alia two well-known genes: KDR, a well-established coat colour gene, and CLOCK, which plays a central role in positive regulation of inflammatory response and in the regulation of the mammalian circadian rhythm. The other candidate regions identified harboured genes associated mainly with milk and meat traits as well as genes involved in immune response/inflammation or associated with behavioural traits. This last category of genes was mainly identified in VCA, which is selected for fighting ability. Overall, our results provide, for the first time, a glimpse into regions of the genome targeted by selection in Valdostana cattle. Finally, this study illustrates the relevance of using multiple complementary approaches to identify genomic regions putatively under selection in livestock.
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