Abstract：As a famous local pig breed in China, Taihu pig (Sus scrofa) has many characteristics such as high fecundity, resistance to rough feeding, good disease resistance and good flesh quality. It has been an important genetic resource for molecular breeding and genome selection. Based on the bioinformatics techniques such as pig quantitative trait locus (QTL) database, gene ontology (GO) database and ingenuity pathway analysis (IPA) database, this study mined the genes related to growth traits in pigs. In order to verify the accuracy of the candidate genes obtained, this study uploaded the candidate genes to the IPA database for online analysis. The results indicated that the candidate genes obtained were mainly enriched in 10 gene networks, and they were mainly enriched in gene expression, body development, cell growth, embryonic development, bone and muscle system development and other functions. Many candidate genes related to pig growth traits have been widely studied and reported. All of the above indicated that the candidate genes of pig growth trait obtained had a certain degree of confidence. This study based on the sequencing data in genotyping by genome reducing and sequencing (GGRS) platform, detected the SNPs of 6 Taihu pig breeds and screened out specific SNPs which had interspecific differences with western breeds. Then through the analyses of genetic correlation, SNP specificity, SNP location and other information, this study predicted the sites where can genetically improve the local breeds of Taihu by gene editing. In order to screen out the best single guide RNA (sgRNA) near the gene editing site and complete the gene editing, this study prepared a script based on Perl language to analyze the whole pig genome, and found out the protospacer adjacent motif (PAM) and sgRNA target sites in pig genome. In the pig genome, a total of 127 353 502 PAM sites were detected, with an average of one PAM site per 20 bp, and these PAM sites were evenly distributed within the chromosome. A total of five PAM types were observed in this study, including TGG, AGG, GGG, CGG and NGG. The frequency of NGG was very low, only 0.0082%, probably due to low quality sequences. The other four PAM sites accounted for 34.52%, 32.61%, 26.43% and 6.43%, respectively. At the same time, this study screened out the best sgRNA for CRISPR/Cas9 gene editing by the off-target analysis of sgRNA in pig genome. 428 candidate genes for growth traits in pigs were got, and the number of specific SNPs related to growth of the pig breeds Erhualian, Fengjing, Jiaxing, Mizhu, Mmeishan, Shawutou, Smeishan were 412、282、372、414、393、279、458, respectively. Next, based on the off-target analysis, four optimal sgRNAs were provided for each growth-related SNP site. This study provides the data foundation for subsequent efficient and accurate gene editing.
