Preadipocyte differentiation plays a critical role in subcutaneous fat deposition in pigs. However, the roles of different RNAs, such as messenger RNAs (mRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) in the differentiation process of subcutaneous preadipocytes, are still largely unclear. In the present study, a transcriptome analysis, including the analysis of mRNAs, lncRNAs, and circRNAs, during different differentiation stages, namely, day 0 (D0), day 2 (D2), day 4 (D4), and day 8 (D8), of subcutaneous preadipocytes from Chinese Erhualian pigs was performed. A total of 1554, 470, 1344, 1777, and 676 differentially expressed (DE) mRNAs, 112, 58, 95, 136, and 93 DE lncRNAs, and 902, 787, 710, 932, and 850 DE circRNAs were identified between D2 and D0, between D4 and D2, between D8 and D4, between D4 and D0, and between D8 and D0, respectively. Furthermore, functional enrichment analysis showed that the common DE mRNAs during the entire differentiation process were mainly involved in lipid metabolic and cell differentiation processes. Additionally, co-expression network analysis identified the potential lncRNAs related to adipogenesis, e.g., MSTRG.131380 and MSTRG.62128. Our study provides new insights of the expression changes of RNAs during adipogenic differentiation, which might contribute to the phenotype of subcutaneous adipogenesis. These results greatly improve our understanding of the molecular mechanisms regulating subcutaneous fat deposition in pigs.

Birth weight is an economically important trait in pig production because it directly impacts piglet growth and survival rate. In the present study, we performed a genome wide survey of candidate genes and pathways associated with individual birth weight (IBW) using the Illumina PorcineSNP60 BeadChip on 24 high (HEBV) and 24 low estimated breeding value (LEBV) animals. These animals were selected from a reference population of 522 individuals produced by three sires and six dam lines, which were crossbreds with multiple breeds. After quality-control, 43,257 SNPs (single nucleotide polymorphisms), including 42,243 autosomal SNPs and 1,014 SNPs on chromosome X, were used in the data analysis. A total of 27 differentially selected regions (DSRs), including 1 on Sus scrofa chromosome 1 (SSC1), 1 on SSC4, 2 on SSC5, 4 on SSC6, 2 on SSC7, 5 on SSC8, 3 on SSC9, 1 on SSC14, 3 on SSC18, and 5 on SSCX, were identified to show the genome wide separations between the HEBV and LEBV groups for IBW in piglets. A DSR with the most number of significant SNPs (including 7 top 0.1% and 31 top 5% SNPs) was located on SSC6, while another DSR with the largest genetic differences in F_ST was found on SSC18. These regions harbor known functionally important genes involved in growth and development, such as TNFRSF9 (tumor necrosis factor receptor superfamily member 9), CA6 (carbonic anhydrase VI) and MDFIC (MyoD family inhibitor domain containing). A DSR rich in imprinting genes appeared on SSC9, which included PEG10 (paternally expressed 10), SGCE (sarcoglycan, epsilon), PPP1R9A (protein phosphatase 1, regulatory subunit 9A) and ASB4 (ankyrin repeat and SOCS box containing 4). More importantly, our present study provided evidence to support six quantitative trait loci (QTL) regions for pig birth weight, six QTL regions for average birth weight (ABW) and three QTL regions for litter birth weight (LBW) reported previously by other groups. Furthermore, gene ontology analysis with 183 genes harbored in these 27 DSRs suggested that protein, metal, ion and ATP binding, viral process and innate immune response present important pathways for deciphering their roles in fetal growth or development. Overall, our study provides useful information on candidate genes and pathways for regulating birth weight in piglets, thus improving our understanding of the genetic mechanisms involved in porcine embryonic or fetal development.

As typical Chinese indigenous pig breeds, Erhualian and Meishan have been widely used to produce new strain or breed in the world. However, the genetic basis of characteristics of these pig breeds is still limited. Moreover, considering cost and output of sequencing, it is necessary to further develop cost-effective method for pig genome screening. To contribute on this issue, we developed a SLAF-seq (specific-locus amplified fragment sequencing) method for pigs and applied it to analyze the genetic difference among Landrace, Erhualian, and Meishan pigs. A total of 453.75 million reads were produced by SLAF-seq. After quality-control, 165,670 SNPs (single nucleotide polymorphisms) were used in further analysis. The results showed that Landrace had distinct genetic relationship compared to Erhualian (F_ST = 0.5480) and Meishan (F_ST = 0.5800), respectively, while Erhualian and Meishan held the relatively close genetic relationship (F_ST = 0.2335). Furthermore, a genome-wide scanning revealed 268 differentially selected regions (DSRs) with 855 genes and 256 DSRs with 347 genes between Landrace and the two Chinese indigenous pig breeds and between Erhualian and Meishan, respectively. This study provides a new cost-effective method for pig genome study and might contribute to a better understanding on the formation mechanism of genetic difference among pigs with different geographical origins.

IgG subclass diversification is common in placental mammals. It has been well documented in humans and mice that different IgG subclasses, with diversified functions, synergistically regulate humoral immunity. However, our knowledge on the genomic and functional diversification of IgG subclasses in the pig, a mammalian species with high agricultural and biomedical importance, is incomplete. Using bacterial artificial chromosome sequencing and newly assembled genomes generated by the PacBio sequencing approach, we characterized and mapped the IgH C region gene locus in three indigenous Chinese breeds (Erhualian, Xiang, and Luchuan) and compared them to that of Duroc. Our data revealed that IGHG genes in Chinese pigs differ from the Duroc, whereas the IGHM, IGHD, IGHA, and IGHE genes were all single copy and highly conserved in the pig breeds examined. Most striking were differences in numbers of IGHG genes: there are seven genes in Erhualian pigs, six in the Duroc, but only five in Xiang pigs. Phylogenetic analysis suggested that all reported porcine IGHG genes could be classified into nine subclasses: IGHG1, IGHG2a, IGHG2b, IGHG2c, IGHG3, IGHG4, IGHG5a, IGHG5b, and IGHG5c. Using sequence information, we developed a mouse mAb specific for IgG3. This study offers a starting point to investigate the structure-function relationship of IgG subclasses in pigs.