Genotype variant calls (VCF) dataset of Mahuang chicken

Genome-wide association studies (GWAS) offer an efficient strategy for mapping economic traits in livestock, yet optimizing resolution in local genetic resources requires cost-effective sequencing approaches. This study utilized low-coverage whole-genome sequencing (LCWGS; ~1.07×) coupled with genotype imputation across 725 individuals from an indigenous Chinese chicken breed (Mahuang) to map variants underlying growth and reproduction. High-depth sequencing (30×) of 40 representative individuals served as a baseline, yielding over 14 million imputed single-nucleotide polymorphisms (SNPs) after strict filtering. To maximize statistical power and control for confounding population structures, association analyses for healthy brood rate, body weight at 70 days, and age at first egg were executed using three distinct statistical frameworks: a General Linear Model (GLM), a Mixed Linear Model (MLM), and the Fixed and Random Model Circulating Probability Unification (FarmCPU). While no significant associations were detected for healthy brood rate, FarmCPU successfully identified prominent, high-confidence quantitative trait loci (QTLs) on autosomes 1, 2, 3, and 12 above the strict Bonferroni-corrected threshold. Functional annotation implicated key candidate genes, including ANKRD26 for age at first egg, and CACNA1D and PDE10A for 70-day body weight. To confirm these genomic signals, kompetitive allele-specific PCR (KASP) genotyping was conducted on an independent cohort, successfully validating the diagnostic marker associations of SNPs rs312633977 and rs738889991 with reproductive onset and growth, respectively. These findings demonstrate the robust utility of an LCWGS-to-KASP pipeline for high-resolution mapping in local poultry breeds, providing validated molecular markers tailored for marker-assisted selection programs.