Applicability and performance evaluation of the Shennong 1 Chicken 40K Liquid chip in commercial chicken populations

To evaluate the applicability and analytical performance of the Shennong 1 Chicken 40K Liquid chip (Shennong chip) in commercial chicken populations, parental lines of Australorp (Arp) and Rhode Island Red (RIR) chickens were analyzed using both whole-genome resequencing (WGS) and Shennong chip genotyping. A total of 128 individuals were included. The performance of Shennong chip was evaluated by comparing its results with those of WGS through population genetics analyses, including assessment of population structure, genetic diversity and selection signatures. Across analyses, Shennong chip showed high concordance with WGS in population genetic inference. For example, the first two principal components derived from the two datasets showed nearly identical distributions, with Pearson correlation coefficients close to 0. 99. Similar cluster pattern was observed between WGS and Shenong chip results in ancestry inference at K = 2 and K = 3. Genetic diversity estimates suggested moderate levels of variation (Shennong chip: He ≈ 0. 34–0. 40; WGS: pi ≈ 0. 0027–0. 0037) across all four parental lines, with relatively higher diversity (He ≈ 0. 40; pi ≈ 0. 0037) observed in the Rhode Island Red D line. The SNP chip reliably captured major population structure patterns, genetic diversity differences among parental lines, and biologically interpretable selection signals. Functional enrichment analyses based on SNP chip–derived candidate regions further revealed distinct selection orientations between parental lines. LSBL analysis identified Arp-specific selection signals, while joint F _ ST and nucleotide diversity analyses revealed pronounced divergence between RIR C and D. Functional enrichment highlighted neural signaling–related genes in RIR C (e. g. , GRIK1) and metabolic and immune-related genes in RIR D (e. g. , AvBD genes) Overall, these results demonstrate that SNP chip provides a reliable, cost-effective, and scalable alternative to WGS for population genetic and breeding-oriented genomic analyses in commercial chicken populations.