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Updated: Sep 16, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
Genome-wide association studies and candidate genes networks affecting reproductive traits using Iranian Holstein
Narges Maddahi1, Mostafa Sadeghi2, Seyed Reza Miraee Ashtiani1
1Department of Animal Science, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.
Background:
The reproduction process in domestic animals is one of the most important challenges of animal husbandry. Fertility is an important trait that contributes to herd profitability and can be improved by genomic information. One of the best ways to investigate the association between single nucleotide polymorphisms (SNPs) and phenotypic performance is the genome-wide association study (GWAS). The aim of our study was to identify the genomic regions affecting reproductive traits, interval between first and last insemination (IFL), days open (DO), days from calving to first service (DFS), number of services per conception (NSPC), age at first calving (AFC) and age at first insemination (AFI) using SNP chip data in Iranian Holstein cows.
Results:
GWAS analysis for all reproductive traits based on the significant-association threshold P < 1 × 10-8, led to the identification of 55 single nucleotide polymorphisms (SNPs) for IFL (n = 3), DFS (n = 0), DO (n = 5), NSPC (n = 5), AFI (n = 33), and AFC (n = 9) traits. Based on the results of gene ontology analysis, 54 different candidate genes for reproductive traits were identified in this study. For IFL, NSPCC, DO, AFC, and AFI traits 4, 8, 11, 10, and 21 candidate genes were identified in the vicinity of significant SNPs, respectively. Key genes with biologically important positions for heifers (ATG7, PTPN5, STAC, GAD2, PLXDC2, KARS1, PRIM2, and ZNF597) and cows (LPL, SERP2, BIRC6, CENPU, PIK3C3, and MYLK3) can be mentioned.
Conclusions:
Our results identified 55 marker-trait associations (MTAs) and 54 different candidate genes associated with reproductive traits. As a result, the SNPs and candidate genes discovered in this study can be used in genomic experiments to improve the reproductive performance of Iranian Holstein dairy cows and provide new information about the genetic architecture of these traits.
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