The production performance of pigs has been significantly improved due to long-term artificial selection, and the specific variation characterizations (selection signatures) emerged from the selected genome regions. Different types of breeds are subjected to different selection intensities and had different selection signatures. Selective sweep analysis is one of major methods to detect the selection signatures. In this study, based on the 60K BeadChip genotyping data of both commercial Large White (n=45) and local Tongcheng pigs (n=45), genetic differentiation coefficient Fst was applied to detect the selection signatures. Using gPLINK software to set quality control standards, a total of 34 304 SNPs were selected for statistical analysis. Fst values between two breeds were estimated with Genepop package and the average Fst value was 0.3209. Setting Fst>0.7036 (1% of total number of Fst values) as selection threshold, 344 SNPs were obtained and SNP location annotation indicated that there were 79 candidate genes (Sus scrofa Build 9). Furthermore, network analysis was performed using Ingenuity Pathway Analysis and the preliminary results suggested that most genes were in-volved in growth, reproduction, and immune response, such as NCOA6, ERBB4, RUNX2, and APOB genes. The findings from this study will contribute to further identification of candidate genes and causal mutations implying for meat production and disease resistance in pig.
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