2024 : 11 : 5
Mohammad Hossein Moradi

Mohammad Hossein Moradi

Academic rank: Associate Professor
ORCID: https://orcid.org/0000-0001-5877-0866
Education: PhD.
ScopusId: 7004477102
HIndex:
Faculty: Agriculture and Environment
Address: Arak University
Phone:

Research

Title
RNA-Seq based selection signatures analysis for identifying genomic footprints associated with fat-tail phenotype in sheep
Type
JournalPaper
Keywords
RNA-Seq datasets, selection signatures, fat deposition, thin- and fat-tailed sheep, SNP calling
Year
2024
Journal Frontiers in Veterinary Science
DOI
Researchers Hossein Abbasabadi ، Mohammad Reza Bakhtiarzade ، Mohammad Hossein Moradi ، John Mak Ivan

Abstract

Understanding the genetic background behind the fat-tail development in sheep is essential to develop breeding programs for genetic improvement, while fat-tail is gradually losing its importance in modern sheep industry systems. Here, to identify genomic regions influencing fat-tail size in sheep, a comprehensive selection signatures analysis was performed, through comparison of fat- and thin-tailed sheep breeds. Furthermore, to gain first insights into the potential use of RNA-Seq for selection signature analysis, SNP calling was performed using RNA-Seq datasets. In total, 45 RNA-Seq samples related to seven cohort studies were analyzed and FST method was used to detect selection signatures. Our findings indicated that RNA-Seq could be of potential utility for selection signatures analysis. In total, 877 SNPs were found in 92 genomic regions to be under selection, which were related to 103 genes. Functional annotation analysis reinforced this hypothesis that genes involved in fatty acid oxidation may modulate fat accumulation in tail of sheep. In agreement with most of previous studies, our results re-emphasize that BMP2 gene is targeted by selection during sheep evolution. Further gene annotation analysis revealed that a large number of genes are directly associated with fat metabolism including those were previously reported as candidates involved in sheep fat-tail morphology such as NID2, IKBKG, RGMA, IGFBP7, UBR5 and WLS. Moreover, a number of genes were of particular interest, as they were well-known fat metabolism-associated genes and treated as novel candidates involved in fat-tail size including BDH2, ECHS1, AUH, ERBIN and CYP4V2. Consistent with the selection signatures analysis, principal component analysis clustered the samples into two completely separated groups according to fat- and thin-tailed breeds. Our results provide novel insights into the genomic basis of phenotypic diversity related to fat-tail of sheep breeds, which can be used to determine the direction for improving breeding strategies in the future.