Summary Growth and fatness traits are complex and economically important traits in the pig industry. The molecular basis underlying porcine growth and fatness traits remains largely unknown. To uncover genetic loci and candidate genes for these traits, we explored the GeneSeek GGP Porcine 80K SNP chip to perform a GWAS for seven growth and fatness traits in 365 individuals from the Sujiang pig, a recently developed breed in China. We identified two, 17, one and 11 SNPs surpassing the suggestively significant threshold (P < 1.86 × 10−5) for body weight, chest circumference, chest width and backfat thickness respectively. Of these SNPs, 20 represent novel genetic loci, and five and four SNPs were respectively associated with chest circumference and backfat thickness at a genome‐wide significant threshold (P < 9.31 × 10−7). Eight SNPs had a pleiotropic effect on both chest circumference and backfat thickness. The most remarkable locus resided in a region between 72.95 and 76.27 Mb on pig chromosome 4, harboring a number of previously reported quantitative trait loci related to backfat deposition. In addition to two reported genes (PLAG1 and TAS2R38), we identified four genes including GABRB3, ZNF106, XKR4 and MGAM as novel candidates for body weight and backfat thickness at the mapped loci. Our findings provide insights into the genetic architecture of porcine growth and fatness traits and potential markers for selective breeding of Chinese Sujiang pigs.
A biogeographic estimate of a certain population can not only discern population substructure in the whole genome association study, but also provide informative clues for forensic investigations when obtained DNA genotypes do not find a match in the available forensic DNA database. In this study, 100 ancestry informative single nucleotide polymorphisms (AISNPs) were first presented to differentiate three continental ancestries (African, East Asian and European). Ultimately, forty-two AISNPs were chosen from the 100 AISNPs. Distinguishing power of the 100 and 42 AISNPs for differentiating continental populations was further evaluated with population cluster analyses. Results indicated both of AISNP sets could efficiently differentiate 11 training populations from the three continents. Further validation of 42 AISNPs in testing population set indicated these 42 AIS-NPs performed well for ancestry inferences of these testing individuals. Ancestry components of Uyghur group were assessed by comparing with different continental populations based on these 42 AISNPs. Results revealed that East Asian populations contributed more ancestry components to the studied Uyghur group than European populations. In conclusion, our study is expected to provide more AISNP markers and enrich extant reference database.
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