Genome-Wide Association Analysis of Dorsal Black Stripe Trait in Youzhou Dark Goat

The dorsal black stripe trait is widespread among mammals and holds significant importance for breed identification, genetic breeding, and evolutionary studies. This research aimed to reveal the genetic basis of this trait by screening molecular markers and candidate genes associated with the dorsal black stripe trait in Youzhou dark goats, thereby providing scientific support for the conservation and utilization of local genetic resources.

A total of 137 healthy adult Youzhou dark goats were selected as subjects and phenotypically classified based on the presence or absence of the dorsal black stripe trait. Genomic DNA was extracted from venous blood samples and subjected to whole-genome resequencing (WGS) to generate raw sequencing data. After quality assessment, the data were aligned to the goat reference genome ARS1 (GCF_001704415.1) to obtain genome-wide single nucleotide polymorphism (SNP) markers. High-quality SNPs were retained after strict quality control using Plink software, followed by principal component analysis (PCA) and population structure analysis (Admixture) to assess genetic background, and pairwise algorithm-based linkage disequilibrium (LD) estimation. Genome-wide association study (GWAS) was performed using GEMMA to identify SNPs significantly associated with the dorsal black stripe trait (threshold = 7.57×10^-7), and significant loci were annotated using Bedtools to mine nearby candidate genes. Meanwhile, genome-wide selection scans were conducted with VCFtools using a 50 kb sliding window and 10 kb step size to compute population genetic differentiation index (Fst) and nucleotide diversity ratio (π-ratio). Regions falling within the top 5% of both metrics were defined as positively selected regions, from which candidate genes were annotated and subjected to KEGG pathway enrichment analysis. Additionally, SNPs within a key region on chromosome 18 (NC_030825.1: 12403900–17000000) were extracted and annotated using ANNOVAR to analyze variant distribution among genes in this region.

Phenotypic statistics showed that among the 137 Youzhou dark goats, 60 individuals exhibited the dorsal black stripe trait, while 77 did not. WGS generated a total of 4.04 Tb of valid data, with an average efficiency rate of 99.31%, Q30 of 96.48%, and an average sequencing depth of 10.49×. After quality control, a total of 13211396 high-quality SNPs were retained for subsequent analysis. Population structure analysis indicated no clear genetic differentiation between goats with the have and non-have dorsal black stripe. GWAS identified three SNPs significantly associated with the dorsal black stripe trait in goats. Among these, SNP1 and SNP2 were annotated within introns of the peroxisomal biogenesis factor 5-like gene (PEX5L), while SNP3 was located in an intron of the genetic suppressor element 1 gene (GSE1). The chi-square test showed that the genotype distributions of the three SNPs differed significantly between the groups with have and non-have dorsal black stripe (P < 0.001). Specifically, the GG genotype of SNP1 and the TT genotype of SNP2 were primarily observed in the group with have dorsal black stripe, while the CC genotype of SNP3 was mainly found in the group with non-have dorsal black stripe. Selection signature analysis detected 4373 candidate selective sweep regions, corresponding to 1544 candidate genes, including PEX5L and GSE1. These selected genes were significantly enriched in 18 KEGG pathways (P < 0.05), such as the cAMP signaling pathway, gap junction, and adherents junction. Further analysis of the key region on chromosome 18 demonstrated that GSE1 exhibited the highest genetic variability, with a total of 1277 SNPs (18 in exons, 1259 in introns), significantly exceeding the variant counts of other genes in this region.

Integrating WGS-based GWAS and selection signature analyses, this study identified PEX5L and GSE1 as key candidate genes for the dorsal black stripe trait in Youzhou dark goats. The findings provide a theoretical foundation for elucidating the molecular genetic mechanisms underlying this trait in goats and would facilitate marker-assisted selection in breeding programs as well as sustainable utilization of local genetic resources.