Population genetic structure analysis and identification of backfat thickness loci of Chinese synthetic Yunan pigs

Abstract

Yunan is a crossed lean meat pig breed in China. Backfat thickness is the gold standard for carcass quality grading. However, over 14 years after breed registration, the backfat of Yunan thickened and the consistency of backfat thickness decreased. Meanwhile, no genetic study has been ever performed on Yunan population. So, in this study we collected all the 120 nucleus individuals of Yunan and recorded six backfat traits of them, carried out population genetic structure analysis, selection signals analysis and genome-wide association study of Yunan pigs with the help of their founder population Duroc and Chinese native Huainan pigs, to determine the genomic loci on backfat of Yunan. Genetic diversity indexes suggested Yunan pigs had no inbreeding risk while population genetic structure showed they had few molecular pedigrees and were stratified. A total of 71 common selection signals affecting growth and fat deposition were detected by FST and XP-CLR methods. 34 significant loci associated with six backfat traits were detected, among which a 1.40 Mb region on SSC4 (20.03–21.43 Mb) were outstanding as the strong region underlying backfat. This region was common with the results of selection signature analysis, former reported QTLs for backfat and was common for different kinds of backfat traits at different development stage. ENPP2, EXT1 and SLC30A8 genes around were fat deposition related genes and were of Huainan pig’s origin, among which Type 2 diabetes related gene SLC30A8 was the most reasonable for being in a 193.21 Kb haplotype block of the 1.40 Mb region. Our results had application value for conservation, mating and breeding improvement of backfat thickness of Yunan pigs and provided evidence for a human function gene might be reproduced in pigs.

Identification of genomic diversity and selection signatures in Luxi cattle using whole-genome sequencing data

“…The “1,000 Bull Genome” project has greatly met people’s demand for functional gene mining of important economic traits and provided a theoretical basis and technical support for the development of efficient cattle breeding technology [ 38 ]. However, the current sequencing objects are mainly commercial varieties, and limited attention is paid to the genomic diversity and whole-genome scanning footprint of positive selection characteristics of indigenous varieties [ 39 ]. This study lays a foundation for the study of genetic diversity and genetic characteristics of other indigenous cattle in China in the future.…”

“…The "1,000 Bull Genome" project has greatly met people's demand for functional gene mining of important economic traits and provided a theoretical basis and technical support for the development of efficient cattle breeding technology [38]. However, the current sequencing objects are mainly commercial varieties, and limited attention is paid to the genomic diversity and whole-genome scanning footprint of positive selection characteristics of indigenous varieties [39]. This To improve detection efficiency and reduce false positives, we used pi, F st and XP-EHH methods to identify plausible positive selection regions associated with important economic traits in LUX, and if a gene is clearly detected by at least two methods, then it will be used as a candidate gene for further analysis.…”

Genomic prediction based on selective linkage disequilibrium pruning of low-coverage whole-genome sequence variants in a pure Duroc population

“…Phenotypic data included age at 100 kg live weight (AGE), backfat thickness (BF), and total teat number (TTN), representing quantitative traits with three distinct genetic architectures. In this population, AGE is a typical “infinitesimal trait” (i.e., no major QTL could be detected after long-term artificial selection), whereas TTN is mainly affected by several major QTL on Sus scrofa 11.1 chromosome (SSC)7 and BF is a transitional quantitative trait affected by several major loci and many minor gene interactions [ 28 , 32 , 33 ]. The trait statistics are summarized in Table 1 and Additional file 1 : Fig.…”

Evaluation of the Genetic Diversity, Population Structure and Selection Signatures of Three Native Chinese Pig Populations

“…Similarly, understanding the genetic structure of a population is significant for comprehending individual migration, introgression, the evolution process of said population and breed classification. Unsurprisingly, there has been considerable research in animal species using genetic markers, including pigs [ 7 , 8 , 9 ]. For instance, Chen et al (2022) investigated the population structure and genetic diversity of four indigenous pig breeds from eastern China based on single nucleotide polymorphism (SNP) chip and provided new insights for further conservation of these indigenous genetic resources [ 10 ].…”