The Tibetan pig is one of domestic animals indigenous to the Qinghai-Tibet Plateau. Several geographically isolated pig populations are distributed throughout the Plateau. It remained an open question if these populations have experienced different demographic histories and have evolved independent adaptive loci for the harsh environment of the Plateau. To address these questions, we herein investigated ~ 40,000 genetic variants across the pig genome in a broad panel of 678 individuals from 5 Tibetan geographic populations and 34 lowland breeds. Using a series of population genetic analyses, we show that Tibetan pig populations have marked genetic differentiations. Tibetan pigs appear to be 3 independent populations corresponding to the Tibetan, Gansu and Sichuan & Yunnan locations. Each population is more genetically similar to its geographic neighbors than to any of the other Tibetan populations. By applying a locus-specific branch length test, we identified both population-specific and -shared candidate genes under selection in Tibetan pigs. These genes, such as PLA2G12A, RGCC, C9ORF3, GRIN2B, GRID1 and EPAS1, are involved in high-altitude physiology including angiogenesis, pulmonary hypertension, oxygen intake, defense response and erythropoiesis. A majority of these genes have not been implicated in previous studies of highlanders and high-altitude animals. Tibetan pig populations have experienced substantial genetic differentiation. Historically, Tibetan pigs likely had admixture with neighboring lowland breeds. During the long history of colonization in the Plateau, Tibetan pigs have developed a complex biological adaptation mechanism that could be different from that of Tibetans and other animals. Different Tibetan pig populations appear to have both distinct and convergent adaptive loci for the harsh environment of the Plateau.

Background: Elucidation of the pig transcriptome is essential for interpreting functional elements of the genome and understanding the genetic architecture of complex traits such as fat deposition, metabolism and growth. Results: Here we used massive parallel high-throughput RNA sequencing to generate a high-resolution map of the porcine mRNA and miRNA transcriptome in liver, longissimus dorsi and abdominal fat from two full-sib F₂ hybrid pigs with segregated phenotypes on growth, blood physiological and biochemical parameters, and fat deposition. We obtained 8,508,418-10,219,332 uniquely mapped reads that covered 78.0% of the current annotated transcripts and identified 48,045-122,931 novel transcript fragments, which constituted 17,085-29,499 novel transcriptional active regions in six tested samples. We found that about 18.8% of the annotated genes showed alternative splicing patterns, and alternative 3' splicing is the most common type of alternative splicing events in pigs. Cross-tissue comparison revealed that many transcriptional events are tissue-differential and related to important biological functions in their corresponding tissues. We also detected a total of 164 potential novel miRNAs, most of which were tissue-specifically identified. Integrated analysis of genome-wide association study and differential gene expression revealed interesting candidate genes for complex traits, such as IGF2, CYP1A1, CKM and CES1 for heart weight, hemoglobin, pork pH value and serum cholesterol, respectively. Conclusions: This study provides a global view of the complexity of the pig transcriptome, and gives an extensive new knowledge about alternative splicing, gene boundaries and miRNAs in pigs. Integrated analysis of genome wide association study and differential gene expression allows us to find important candidate genes for porcine complex traits.

Background: Copy number variation (CNV) is a major source of structural variants and has been commonly identified in mammalian genome. It is associated with gene expression and may present a major genetic component of phenotypic diversity. Unlike many other mammalian genomes where CNVs have been well annotated, studies of porcine CNV in diverse breeds are still limited. Result: Here we used Porcine SNP60 BeadChip and PennCNV algorithm to identify 1,315 putative CNVs belonging to 565 CNV regions (CNVRs) in 1,693 pigs from 18 diverse populations. Total 538 out of 683 CNVs identified in a White Duroc × Erhualian F₂ population fit Mendelian transmission and 6 out of 7 randomly selected CNVRs were confirmed by quantitative real time PCR. CNVRs were non-randomly distributed in the pig genome. Several CNV hotspots were found on pig chromosomes 6, 11, 13, 14 and 17. CNV numbers differ greatly among different pig populations. The Duroc pigs were identified to have the most number of CNVs per individual. Among 1,765 transcripts located within the CNVRs, 634 genes have been reported to be copy number variable genes in the human genome. By integrating analysis of QTL mapping, CNVRs and the description of phenotypes in knockout mice, we identified 7 copy number variable genes as candidate genes for phenotypes related to carcass length, backfat thickness, abdominal fat weight, length of scapular, intermuscle fat content of logissimus muscle, body weight at 240 day, glycolytic potential of logissimus muscle, mean corpuscular hemoglobin, mean corpuscular volume and humerus diameter. Conclusion: We revealed the distribution of the unprecedented number of 565 CNVRs in pig genome and investigated copy number variable genes as the possible candidate genes for phenotypic traits. These findings give novel insights into porcine CNVs and provide resources to facilitate the identification of trait-related CNVs.

Recently, genome-wide association studies (GWAS) have been reported on various pig traits. We performed a GWAS to analyze 22 traits related to growth and fatness on two pig populations: a White Duroc × Erhualian F2 intercross population and a Chinese Sutai half-sib population. We identified 14 and 39 loci that displayed significant associations with growth and fatness traits at the genome-wide level and chromosome-wide level, respectively. The strongest association was between a 750 kb region on SSC7 (SSC for Sus scrofa) and backfat thickness at the first rib. This region had pleiotropic effects on both fatness and growth traits in F2 animals and contained a promising candidate gene HMGA1 (high mobility group AT-hook 1). Unexpectedly, population genetic analysis revealed that the allele at this locus that reduces fatness and increases growth is derived from Chinese indigenous pigs and segregates in multiple Chinese breeds. The second strongest association was between the region around 82.85 Mb on SSC4 and average backfat thickness. PLAG1 (pleiomorphic adenoma gene 1), a gene under strong selection in European domestic pigs, is proximal to the top SNP and stands out as a strong candidate gene. On SSC2, a locus that significantly affects fatness traits mapped to the region around the IGF2 (insulin-like growth factor 2) gene but its non-imprinting inheritance excluded IGF2 as a candidate gene. A significant locus was also detected within a recombination cold spot that spans more than 30 Mb on SSCX, which hampered the identification of plausible candidate genes. Notably, no genome-wide significant locus was shared by the two experimental populations; different loci were observed that had both constant and time-specific effects on growth traits at different stages, which illustrates the complex genetic architecture of these traits. We confirm several previously reported QTL and provide a list of novel loci for porcine growth and fatness traits in two experimental populations with Chinese Taihu and Western pigs as common founders. We showed that distinct loci exist for these traits in the two populations and identified HMGA1 and PLAG1 as strong candidate genes on SSC7 and SSC4, respectively.

Fatty acid composition in muscle is an important factor that affects the nutritive value and taste of pork. To investigate the genetic architecture of fatty acid composition of pork, we measured fatty acid contents in longissimus dorsi muscle of 1244 pigs from three divergent populations and conducted genome-wide association studies (GWAS) for fatty acid contents. We detected 26 genome-wide significant quantitative trait loci (QTL) on eight chromosomes (SSC for Sus scrofa) for eight fatty acids. These loci not only replicated previously reported QTL for C18:0 on SSC14 and C20:0 on SSC16, but also included several novel QTL such as those for C20:1 on SSC7, C14:0 on SSC9, and C14:0, C16:0 and C16:1 on SSC12. Furthermore, we performed a meta-analysis of GWAS on five populations, including the three populations that were investigated in this study and two additional populations that we had previously examined. This enhanced the strength of the associations detected between fatty acid composition and several marker loci, especially for those for C18:0 on SSC14 and C20:0 on SSC16. The genes ELOVL5, ELOVL6, ELOVL7, FASN, SCD and THRSP, which have functions that are directly relevant to fatty acid metabolism, are proximal to the top associated markers at six significant QTL. The findings improve our understanding of the genetic architecture of fatty acid composition in pork and contribute to further fine-map and characterize genes that influence fatty acid composition.