Interrogating the Milk Yield Genome: A Comparative Whole Genome Association Study in Guanzhong and Beetal Goats

Introduction: Goat milk production is a vital economic trait, driven by rising global demand due to its digestibility, nutritional benefits, and hypoallergenic properties. To explore the genetic basis of milk yield, a genome-wide association study (GWAS) was conducted using whole-genome sequencing (WGS) data from two dairy goat breeds, Guanzhong (China) and Beetal (Pakistan). The present study aimed to identify genomic variants linked to milk yield in Guanzhong (China) and Beetal (Pakistan) goat breeds by performing an in silico GWAS using available WGS data. Materials and methods: Raw sequencing reads from both breeds were retrieved from public repositories and processed through an established bioinformatics pipeline. A GWAS was performed using a linear mixed model with GCTA and GEMMA, accounting for population structure and polygenic background. After quality control and alignment to the ARS1 goat reference genome using BWA, single-nucleotide polymorphisms (SNPs) were identified, and variants were filtered using SAMtools/BCFtools by applying thresholds of minor allele frequency (> 5%) and genotype call rate (> 90%). Population structure was assessed through principal component analysis and a genomic kinship matrix, both conducted using GCTA software, to control for stratification. The Manhattan plot revealed several genome-wide significant peaks, including loci near LALBA, PRLR, and SPP1, which are associated with lactation traits in dairy goats. Results: The GWAS revealed significant SNPs near LALBA on chromosome 19 (p = 1 × 10-¹⁰) and PRLR on chromosome X (p = 3.2 × 10-⁹) strongly associated with milk yield in Guanzhong and Beetal goats. In Guanzhong goats, SNPs near ANPEP, ADRA1A, and PRKG1 exhibited significant allele frequency differences, while in Beetal goats, SNPs near IGFBP3 and LEPR were linked to lactation traits. These loci provided robust genomic markers for enhancing the dairy goat breeding program. Conclusion: The present study demonstrated the feasibility of WGS-based GWAS in goats and identified candidate loci such as SPP1, ERBB4, and LALBA, previously linked to lactation, that may serve as genomic markers in future selection programs.

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Journal
Small Animal Advances
Published
2025-08-30
DOI
https://doi.org/10.58803/saa.v4i3.36
Primary Topic
Genetic and phenotypic traits in livestock
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article
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article

Interrogating the Milk Yield Genome: A Comparative Whole Genome Association Study in Guanzhong and Beetal Goats

Nauman Khan, Umar Bin Abdul Aziz, Fasih ur Rehman, Hanbing Yan et al.
Small Animal Advances
Genetic and phenotypic traits in livestock
article

Interrogating the Milk Yield Genome: A Comparative Whole Genome Association Study in Guanzhong and Beetal Goats

Nauman Khan, Umar Bin Abdul Aziz, Fasih ur Rehman, Hanbing Yan, Muhammad Mushahid, Xiaoqian Wang, Abdul Rehman, Xiaopeng An, Jiayuan Li, M. Yousaf
article en

Abstract

Introduction: Goat milk production is a vital economic trait, driven by rising global demand due to its digestibility, nutritional benefits, and hypoallergenic properties. To explore the genetic basis of milk yield, a genome-wide association study (GWAS) was conducted using whole-genome sequencing (WGS) data from two dairy goat breeds, Guanzhong (China) and Beetal (Pakistan). The present study aimed to identify genomic variants linked to milk yield in Guanzhong (China) and Beetal (Pakistan) goat breeds by performing an in silico GWAS using available WGS data. Materials and methods: Raw sequencing reads from both breeds were retrieved from public repositories and processed through an established bioinformatics pipeline. A GWAS was performed using a linear mixed model with GCTA and GEMMA, accounting for population structure and polygenic background. After quality control and alignment to the ARS1 goat reference genome using BWA, single-nucleotide polymorphisms (SNPs) were identified, and variants were filtered using SAMtools/BCFtools by applying thresholds of minor allele frequency (> 5%) and genotype call rate (> 90%). Population structure was assessed through principal component analysis and a genomic kinship matrix, both conducted using GCTA software, to control for stratification. The Manhattan plot revealed several genome-wide significant peaks, including loci near LALBA, PRLR, and SPP1, which are associated with lactation traits in dairy goats. Results: The GWAS revealed significant SNPs near LALBA on chromosome 19 (p = 1 × 10-¹⁰) and PRLR on chromosome X (p = 3.2 × 10-⁹) strongly associated with milk yield in Guanzhong and Beetal goats. In Guanzhong goats, SNPs near ANPEP, ADRA1A, and PRKG1 exhibited significant allele frequency differences, while in Beetal goats, SNPs near IGFBP3 and LEPR were linked to lactation traits. These loci provided robust genomic markers for enhancing the dairy goat breeding program. Conclusion: The present study demonstrated the feasibility of WGS-based GWAS in goats and identified candidate loci such as SPP1, ERBB4, and LALBA, previously linked to lactation, that may serve as genomic markers in future selection programs.

Small Animal AdvancesVol. 4(3)
North West Agriculture and Forestry University (CN), University of Agriculture Faisalabad (PK), University of Veterinary and Animal Sciences (PK)
Openalex Percentile: Top 75%
Genetic and phenotypic traits in livestock
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