Identification of the Genetic Characteristics of Copy Number Variation Regions in Diverse Goat Populations

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Authors: Weiwei Li, Yixin Su, Can Liu, Xiaochun Yan, Qi Lv, Rui Su
Cited by: 1
References: 33

Abstract

Background: Copy number variation (CNV) is an important class of structural variations (SVs) that contribute to phenotypic diversity and environmental adaptation in animals. However, large-scale population-level analyses of CNVs in goats remain limited. This study aimed to comprehensively characterize CNVs and explore their potential roles in economically important traits in Chinese goat populations. Methods: Whole-genome resequencing data from 151 individuals representing 17 Chinese goat breeds were analyzed. CNV regions (CNVRs) were identified across the genome, followed by gene annotation, functional enrichment analysis, and population differentiation analysis based on VST. Results: A total of 5636 CNVRs were identified from 151 individuals of 17 goat breeds, including 1365 duplication CNVRs, 4241 deletion CNVRs, and 30 both CNVRs. These CNVRs collectively spanned 2.38% of the goat genome. A total of 912 protein-coding genes overlapped with these CNVRs. After Bonferroni correction, GO enrichment analysis showed that these genes were significantly enriched in terms related to transmembrane transport, cell projection, ion binding, and ATP binding. Population differentiation analysis identified several CNVR-associated candidate genes with potential relevance to production or adaptive traits, including ABCC4, APOL3, EXOC3L4, ERG, B4GALT1, and FTH. Conclusions: This study provides a comprehensive CNVR map of Chinese goat populations and offers insights into the genetic basis of economically important traits, contributing to future genetic improvement and breeding strategies in goats.

Fields of Study & Subjects

Genomic variations and chromosomal abnormalities Genetic Mapping and Diversity in Plants and Animals Genetic Associations and Epidemiology

Publication details

Journal / source
Genes
Publisher
MDPI AG
Volume
17
Issue
6
Pages
627–627
Publication date
30 May 2026
Language
EN