Pathogen stimulations and immune cells synergistically affect the gene expression profile characteristics of porcine peripheral blood mononuclear cells.

BACKGROUND: Pigs serve as a crucial source of protein in the human diet and play a fundamental role in ensuring food security. However, infectious diseases caused by bacteria or viruses are a major threat to effective global pig farming, jeopardizing human health. Peripheral blood mononuclear cells (PBMCs) are a mixture of immune cells that play crucial roles in immunity and disease resistance in pigs. Previous studies on the gene expression regulation patterns of PBMCs have concentrated on a single immune stimulus or immune cell subpopulation, which has limited our comprehensive understanding of the mechanisms of the pig immune response. RESULTS: Here, we integrated and re-analyzed RNA-seq data published online for porcine PBMC stimulated by lipopolysaccharide (LPS), polyinosinic acid (PolyI:C), and various unknown microorganisms (EM). The results revealed that gene expression and its functional characterization are highly specific to the pathogen, identifying 603, 254, and 882 pathogen-specific genes and 38 shared genes, respectively. Notably, LPS and PolyI:C stimulation directly triggered inflammatory and immune-response pathways, while exposure to mixed microbes (EM) enhanced metabolic processes. These pathogen-specific genes were enriched in immune trait-associated quantitative trait loci (QTL) and eGenes in porcine immune tissues and were implicated in specific cell types. Furthermore, we discussed the roles of eQTLs rs3473322705 and rs1109431654 in regulating pathogen- and cell-specific genes CD300A and CD93, using cellular experiments. Additionally, by integrating genome-wide association studies datasets from 33 complex traits and diseases in humans, we found that pathogen-specific genes were significantly enriched for immune traits and metabolic diseases. CONCLUSIONS: We systematically analyzed the gene expression profiles of the three stimulations and demonstrated pathogen-specific and cell-specific gene regulation across different stimulations in porcine PBMCs. These findings enhance our understanding of shared and distinct regulatory mechanisms of genetic variants in pig immune traits.

Comprehensive analysis of circular RNAs in porcine small intestine epithelial cells associated with susceptibility to Escherichia coli F4ac diarrhea.

BACKGROUND: Diarrhea is one of the most common diseases in pig industry, which seriously threatens the health of piglets and causes huge economic losses. Enterotoxigenic Escherichia coli (ETEC) F4 is regarded as the most important cause of diarrhea in piglets. Some pigs are naturally resistant to those diarrheas caused by ETEC-F4, because they have no F4 receptors (F4R) on their small intestine epithelial cells that allow F4 fimbriae adhesion. Circular RNA (circRNA) has been shown to play an important regulatory role in the pathogenesis of disease. We hypothesized that circRNAs may also regulate the adhesion of piglet small intestinal epithelial cells to ETEC F4 fimbriae. However, the circRNA expression profiles of piglets with different Enterotoxigenic Escherichia coli F4 fimbriae (ETEC-F4ac) adhesion phenotypes are still unclear, and the intermediate regulatory mechanisms need to be explored. Hence, the present study assessed the circRNA expression profiling in small intestine epithelial cells of eight male piglets with different ETEC-F4 adhesion phenotypes and ITGB5 genotypes to unravel their regulatory function in susceptibility to ETEC-F4ac diarrhea. Piglets were divided into two groups: non-adhesive group (n = 4) with CC genotype and adhesive group (n = 4) with TT genotype. RESULTS: The RNA-seq data analysis identified 13,199 circRNAs from eight samples, most of which were exon-derived. In the small intestine epithelial cells, 305 were differentially expressed (DE) circRNAs between the adhesive and non-adhesive groups; of which 46 circRNAs were upregulated, and 259 were downregulated. Gene ontology and KEGG enrichment analysis revealed that most significantly enriched DE circRNAs' host genes were linked to cytoskeletal components, protein phosphorylation, cell adhesion, ion transport and pathways (such as adherens junction, gap junction) associated with ETEC diarrhea. The circRNA-miRNA-mRNA interaction network was also constructed to elucidate their underlying regulatory relationships. Our results identified several candidate circRNAs that affects susceptibility to ETEC diarrhea. Among them, circ-SORBS1 can adsorb ssc-miR-345-3p to regulate the expression of its host gene SORBS1, thus improving cell adhesion. CONCLUSION: Our results provided insights into the regulation function of circRNAs in susceptibility to ETEC diarrhea of piglets, and enhanced our understanding of the role of circRNAs in regulating ETEC diarrhea, and reveal the great potential of circRNA as a diagnostic marker for susceptibility of ETEC diarrhea in piglets.

Comprehensive Analysis of the lncRNA-miRNA-mRNA Regulatory Network for Intramuscular Fat in Pigs.

Intramuscular fat (IMF) is an essential trait closely related to meat quality. The IMF trait is a complex quantitative trait that is regulated by multiple genes. In order to better understand the process of IMF and explore the key factors affecting IMF deposition, we identified differentially expressed mRNA, miRNA, and lncRNA in the longissimus dorsi muscle (LD) between Songliao Black (SL) pigs and Landrace pigs. We obtained 606 differentially expressed genes (DEGs), 55 differentially expressed miRNAs (DEMs), and 30 differentially expressed lncRNAs (DELs) between the SL pig and Landrace pig. Enrichment results from GO and KEGG indicate that DEGs are involved in fatty acid metabolism and some pathways related to glycogen synthesis. We constructed an lncRNA-miRNA-mRNA interaction network with 18 DELs, 11 DEMs, and 42 DEGs. Finally, the research suggests that ARID5B, CPT1B, ACSL1, LPIN1, HSP90AA1, IRS1, IRS2, PIK3CA, PIK3CB, and PLIN2 may be the key genes affecting IMF deposition. The LncRNAs MSTRG.19948.1, MSTRG.13120.1, MSTRG.20210.1, and MSTRG.10023.1, and the miRNAs ssc-miRNA-429 and ssc-miRNA-7-1, may play a regulatory role in IMF deposition through their respective target genes. Our research provides a reference for further understanding the regulatory mechanism of IMF.

Competing endogenous RNA network construction based on long non-coding RNAs, microRNAs, and mRNAs related to fat deposition in Songliao black swine.

China has a long history of pig breeding and a number of local breeds. The Songliao Black pig, bred in China in 2009, shows high variation in backfat thickness and therefore is well-suited to fat deposition research. Fat deposition is a complex trait, and the underlying regulatory factors are not fully characterized. In this study, the molecular basis of fat deposition traits was evaluated by comparisons between three individuals with extremely high-backfat thickness and three with extremely low-backfat thickness selected from 53 gilts. Subcutaneous adipose tissues of the back were collected for strand-specific library RNA sequencing (RNA-seq) and small RNA-seq. We identified 13 184 mRNAs, 2046 long non-coding (lnc)RNAs, and 494 micro (mi)RNAs by high-throughput sequencing. Furthermore, we detected 150 differentially expressed mRNAs, 66 differentially expressed lncRNAs, and eight differentially expressed miRNAs. A functional enrichment analysis indicated that these genes are involved in multiple fat metabolism-related pathways, including positive regulation of fat cell differentiation, and fat digestion and absorption. We used various algorithms (miRanda, TargetScan, and RNAhybrid) to predict targeting relationships and constructed a competing endogenous RNA network containing seven lncRNAs, three miRNAs, and six mRNAs. All these genes were differentially expressed between the extremely high and low backfat thickness groups or enriched in pathways related to fat metabolism. Our results provide insight into the regulatory mechanisms by which non-coding RNAs and their target genes influence backfat deposition in pigs. Furthermore, our newly constructed competing endogenous RNA (lncRNA-miRNA-mRNA) network provides a basis for further exploration of fat deposition traits and non-coding RNA functions.

Application and prospect of gene chip in genetic breeding of livestock and poultry.

Gene chip is a high-throughput technique for detecting specific DNA sequences by DNA or DNA-RNA complementary hybridization, among which SNP genotyping chips have been widely employed in the animal genetics and breeding, and have made great achievements in cattle (Bos taurus), pigs (Sus scrofa), sheep (Caprinae), chickens (Gallus gallus) and other livestock. However, genomic selection applied in production merely uses genomic information and cannot fully explain the molecular mechanism of complex traits genetics, which limits the accuracy of genomic selection. With the continuous progresses in epigenetic research, the development of commercial methylation chips and the application of the epigenome-wide association study (EWAS), DNA methylation has been extensively used to draw the causal connections between genetics and phenotypes. In the future, it is hopefully expected to develop methylation chips customized for livestock and poultry and explore methylation sites significantly related to economic traits of livestock and poultry through EWAS thereby extending the understanding of causal variation of complex traits. Combining methylation chips and SNP chips, we can capture the epigenomic and genomic information of livestock and poultry, interpret genetic variation more precisely, improve the accuracy of genome selection, and promote the fine evolution of molecular genetic breeding of livestock and poultry. In this review, we summarize the application of SNP chips and depict the prospects of the application of methylation chips in livestock and poultry. This review will provide valuable insights for further application of gene chips in farm animal breeding.

Characterization of peripheral white blood cells transcriptome to unravel the regulatory signatures of bovine subclinical mastitis resistance.

Subclinical bovine mastitis is a pathogenic infection of the breast characterized by a marked decrease in milk production and quality. As it has no obvious clinical symptoms, diagnosis and treatment are challenging. Therefore, searching for biomarkers in cows' peripheral white blood cells is valuable for preventing and treating subclinical mastitis. Thus, in this study, the transcriptome of peripheral blood from healthy and subclinical mastitis cows was characterized to find the regulatory signatures of bovine subclinical mastitis using RNA-seq. A total of 287 differentially expressed genes (DEGs) and 70 differentially expressed lncRNAs (DELs) were detected, and 37 DELs were documented near known Quantitative Trait Loci (QTL) associated with the mastitis of cows. Bioinformatic analysis indicated that lncRNAs MSTRG25101.2, MSTRG.56327.1, and MSTRG.18968.1, which are adjacent to the SCS QTL and SCC QTL, may be candidate lncRNAs that influence the pathogenesis of mastitis in cows by up-regulating the expression of genes TLR4, NOD2, CXCL8, and OAS2. Moreover, the alternative splicing (AS) pattern of transcriptional sequence differences between healthy cows and subclinical mastitis cows suggested a molecular mechanism of mastitis resistance and susceptibility. A total of 2,212 differential alternative splicing (DAS) events, corresponding to 1,621 unique DAS genes, were identified in both groups and significantly enriched in immune and inflammatory pathways. Of these, 29 DAS genes were subject to regulation by 32 alternative splicing SNPs, showing diverse and specific splicing patterns and events. It is hypothesized that the PIK3C2B and PPRPF8 splice variants associated with AS SNPs (rs42705933 and rs133847062) may be risk factors for susceptibility to bovine subclinical mastitis. Altogether, these key blood markers associated with resistance to subclinical mastitis and SNPs associated with alternative splicing of genes provide the basis for genetic breeding for resistance to subclinical mastitis in cows.

Favored single nucleotide variants identified using whole genome Re-sequencing of Austrian and Chinese cattle breeds.

Cattle have been essential for the development of human civilization since their first domestication few thousand years ago. Since then, they have spread across vast geographic areas following human activities. Throughout generations, the cattle genome has been shaped with detectable signals induced by various evolutionary processes, such as natural and human selection processes and demographic events. Identifying such signals, called selection signatures, is one of the primary goals of population genetics. Previous studies used various selection signature methods and normalized the outputs score using specific windows, in kbp or based on the number of SNPs, to identify the candidate regions. The recent method of iSAFE claimed for high accuracy in pinpointing the candidate SNPs. In this study, we analyzed whole-genome resequencing (WGS) data of ten individuals from Austrian Fleckvieh (Bos taurus) and fifty individuals from 14 Chinese indigenous breeds (Bos taurus, Bos taurus indicus, and admixed). Individual WGS reads were aligned to the cattle reference genome of ARS. UCD1.2 and subsequently undergone single nucleotide variants (SNVs) calling pipeline using GATK. Using these SNVs, we examined the population structure using principal component and admixture analysis. Then we refined selection signature candidates using the iSAFE program and compared it with the classical iHS approach. Additionally, we run Fst population differentiation from these two cattle groups. We found gradual changes of taurine in north China to admixed and indicine to the south. Based on the population structure and the number of individuals, we grouped samples to Fleckvieh, three Chinese taurines (Kazakh, Mongolian, Yanbian), admixed individuals (CHBI_Med), indicine individuals (CHBI_Low), and a combination of admixed and indicine (CHBI) for performing iSAFE and iHS tests. There were more significant SNVs identified using iSAFE than the iHS for the candidate of positive selection and more detectable signals in taurine than in indicine individuals. However, combining admixed and indicine individuals decreased the iSAFE signals. From both within-population tests, significant SNVs are linked to the olfactory receptors, production, reproduction, and temperament traits in taurine cattle, while heat and parasites tolerance in the admixed individuals. Fst test suggests similar patterns of population differentiation between Fleckvieh and three Chinese taurine breeds against CHBI. Nevertheless, there are genes shared only among the Chinese taurine, such as PAX5, affecting coat color, which might drive the differences between these yellowish coated breeds, and those in the greater Far East region.

Genetic parameter analysis of reproductive traits in Large White pigs.

OBJECTIVE: The primary objective of this study was to determine the genetic parameters for reproductive traits among Large White pigs, including the following traits: total number born (TNB), number born alive (NBA), litter birth weight (LBW), average birth weight (ABW), gestation length (GL), age at first service (AFS) and age at first farrowing (AFF). METHODS: The dataset consisted of 19,036 reproductive records from 4,986 sows, and a multi-trait animal model was used to estimate genetic variance components of seven reproductive traits. RESULTS: The heritability estimates for these reproductive traits ranged from 0.09 to 0.26, with the highest heritability for GL and AFF, and the lowest heritability for NBA. The repeatabilities for TNB, NBA, LWB, ABW, and GL were ranged from 0.16 to 0.34. Genetic and phenotypic correlations ranged from -0.41 to 0.99, and -0.34 to 0.98, respectively. In particular, the correlations between TNB, NBA and LBW, between AFS and AFF, exhibited a strong positive correlation. Furthermore, for TNB, NBA, LBW, ABW, and GL, genetic correlations of the same trait between different parities were moderately to strongly correlated (0.32 to 0.97), and the correlations of adjacent parities were higher than those of nonadjacent parities. CONCLUSION: All the results in the present study can be used as a basis for the genetic assessment of the target population. In the formulation of dam line selection index, AFS or AFF can be considered to combine with TNB in a multiple trait swine breeding value estimation system. Moreover, breeders are encouraged to increase the proportion of sows at parity 3-5 and reinforce the management of sows at parity 1 and parity ≥8.

Using Machine Learning to Identify Biomarkers Affecting Fat Deposition in Pigs by Integrating Multisource Transcriptome Information.

Fat deposition in pigs is not only closely related to pig production efficiency and pork quality but also an ideal model for human obesity. Transcriptome sequencing is widely used to study fat deposition. However, due to small sample sizes, high false positive rates, and poor consistency of results from different studies, new strategies are urgently needed. Machine learning, a new analysis method, can effectively fit complex data and accurately identify samples and genes. In this study, 36 samples of adipose tissue, muscle tissue, and liver tissue were collected from Songliao black pigs and Landrace pigs, and the mRNA of all the samples was sequenced. In addition, we collected transcriptome data for 64 samples in the GEO database from four different sources. After standardization and imputation of missing values in the data set comprising 100 samples, traditional differential expression analysis was carried out, and different numbers of expressed genes were selected as features for the training model of eight machine learning methods. In the 1000 replications of fourfold cross validation with 100 samples, AdaBoost performed best, with an average prediction accuracy greater than 93% and the highest mean area under the curve in predicting the high- and low-fat content groups among the eight ML methods. According to their performance-based ranks inferred by AdaBoost, 12 genes related to fat deposition were identified; among them, FASN and APOD were specifically expressed in adipose tissue, and APOA1 was specifically expressed in the liver, which could be important candidate biomarkers affecting fat deposition.

Identification of Long Non-Coding RNAs Involved in Porcine Fat Deposition Using Two High-Throughput Sequencing Methods.

Adipose is an important body tissue in pigs, and fatty traits are critical in pig production. The function of long non-coding RNA (lncRNA) in fat deposition and metabolism has been found in previous studies. In this study, we collected the adipose tissue of six Landrace pigs with contrast backfat thickness (nhigh = 3, nlow = 3), after which we performed strand-specific RNA sequencing (RNA-seq) based on pooling and biological replicate methods. Biological replicate and pooling RNA-seq revealed 1870 and 1618 lncRNAs, respectively. Using edgeR, we determined that 1512 genes and 220 lncRNAs, 2240 genes and 127 lncRNAs were differentially expressed in biological replicate and pooling RNA-seq, respectively. After target gene prediction, we found that ACSL3 was cis-targeted by lncRNA TCONS-00052400 and could activate the conversion of long-chain fatty acids. In addition, lncRNA TCONS_00041740 cis-regulated gene ACACB regulated the rate-limiting enzyme in fatty acid oxidation. Since these genes have necessary functions in fat metabolism, the results imply that the lncRNAs detected in our study may affect backfat deposition in swine through regulation of their target genes. Our study explored the regulation of lncRNA and their target genes in porcine backfat deposition and provided new insights for further investigation of the biological functions of lncRNA.

Identification of key genes affecting porcine fat deposition based on co-expression network analysis of weighted genes.

BACKGROUND: Fat deposition is an important economic consideration in pig production. The amount of fat deposition in pigs seriously affects production efficiency, quality, and reproductive performance, while also affecting consumers' choice of pork. Weighted gene co-expression network analysis (WGCNA) is effective in pig genetic studies. Therefore, this study aimed to identify modules that co-express genes associated with fat deposition in pigs (Songliao black and Landrace breeds) with extreme levels of backfat (high and low) and to identify the core genes in each of these modules. RESULTS: We used RNA sequences generated in different pig tissues to construct a gene expression matrix consisting of 12,862 genes from 36 samples. Eleven co-expression modules were identified using WGCNA and the number of genes in these modules ranged from 39 to 3,363. Four co-expression modules were significantly correlated with backfat thickness. A total of 16 genes (RAD9A, IGF2R, SCAP, TCAP, SMYD1, PFKM, DGAT1, GPS2, IGF1, MAPK8, FABP, FABP5, LEPR, UCP3, APOF, and FASN) were associated with fat deposition. CONCLUSIONS: RAD9A, TCAP, SMYD1, PFKM, GPS2, and APOF were the key genes in the four modules based on the degree of gene connectivity. Combining these results with those from differential gene analysis, SMYD1 and PFKM were proposed as strong candidate genes for body size traits. This study explored the key genes that regulate porcine fat deposition and lays the foundation for further research into the molecular regulatory mechanisms underlying porcine fat deposition.

Variations in Microbial Diversity and Metabolite Profiles of Female Landrace Finishing Pigs With Distinct Feed Efficiency.

To enhance pig production, feed efficiency (FE) should be improved; however, the mechanisms by which gut microbes affect FE in pigs have not been fully elucidated. To investigate the differences between the composition and functionality of the gut microbiota associated with low and high FE, microbial compositions were characterized using 16S rRNA sequencing, functional annotations were performed by shotgun metagenomics, and metabolomic profiles were created by GC-TOF-MS from female Landrace finishing pigs with low and high feed conversion ratios (FCRs). Lactobacillus was enriched in the gut microbiota of individuals with low FCRs (and thus high FE), while Prevotella abundance was significantly higher in individuals with high FCRs (and thus low FE). This may be linked to carbohydrate consumption and incomplete digestion. The activity of pathways involved in the metabolism of cofactors and vitamins was greater in pigs with lower FE. We also identified differences in pyruvate-related metabolism, including phenylalanine and lysine metabolism. This suggests that pyruvate metabolism is closely related to microbial fermentation in the colon, which in turn affects glycolysis. This study deepens our understanding of how gut microbiota are related to pig growth traits, and how regulating microbial composition could aid in improving porcine FE. However, these results need to be validated using a larger pig cohort in the future.

A Single-Step Genome Wide Association Study on Body Size Traits Using Imputation-Based Whole-Genome Sequence Data in Yorkshire Pigs.

The body shape of a pig is the most direct production index, which can fully reflect the pig's growth status and is closely related to important economic traits. In this study, a genome-wide association study on seven body size traits, the body length (BL), height (BH), chest circumference (CC), abdominal circumference (AC), cannon bone circumference (CBC), rump width (RW), and chest width (CW), were conducted in Yorkshire pigs. Illumina Porcine 80K SNP chips were used to genotype 589 of 5,572 Yorkshire pigs with body size records, and then the chip data was imputed to sequencing data. After quality control of imputed sequencing data, 784,267 SNPs were obtained, and the averaged linkage disequilibrium (r 2) was 0.191. We used the single-trait model and the two-trait model to conduct single-step genome wide association study (ssGWAS) on seven body size traits; a total of 198 significant SNPS were finally identified according to the P-value and the contribution to the genetic variance of individual SNP. 11 candidate genes (CDH13, SIL1, CDC14A, TMRPSS15, TRAPPC9, CTNND2, KDM6B, CHD3, MUC13, MAPK4, and HMGA1) were found to be associated with body size traits in pigs; KDM6B and CHD3 jointly affect AC and CC, and MUC13 jointly affect RW and CW. These genes are involved in the regulation of bone growth and development as well as the absorption of nutrients and are associated with obesity. HMGA1 is proposed as a strong candidate gene for body size traits because of its important function and high consistency with other studies regarding the regulation of body size traits. Our results could provide valuable information for pig breeding based on molecular breeding.

Novel DNA methylation markers of PRRSV-specific antibodies and their intergenerational transmission from pregnant sows to piglets.

The main strategy for preventing porcine reproductive and respiratory syndrome (PRRS) is vaccination. However, current commercial porcine reproductive and respiratory syndrome virus (PRRSV) vaccines have limited effectiveness and may even cause infections in pigs. The identification of stable molecular markers associated with immune responses to PRRSV vaccination in pigs provides a new approach for PRRS prevention. DNA methylation, the most stable epigenetic molecular marker related to PRRSV vaccination, has not been investigated. In the current research, we used whole genome bisulfite sequencing (WGBS) to investigate DNA methylation in pregnant sows that received PRRSV vaccination and their piglets with high and low PRRSV-specific antibody levels. By performing methylation data analysis and basing on our previous transcriptomic studies, we identified several differentially methylated genes (DMGs) that are involved in the pathways of inflammatory and immune responses. Among the DMGs, ISG15, MX1, SERPINE1, GNG11 and IFIT3 were common hub genes in the two generations. MX1 and GNG11 were located in quantitative trait loci related with PRRSV antibody titer and PRRSV susceptibility, respectively. These results suggest that PRRSV vaccination in sows induces DNA methylation changes in genes and DNA methylation changes occur through intergenerational transmission. The novel DNA methylation markers and target genes observed in our study provide new insights into the molecular mechanisms of immune responses to PRRSV vaccination across two pig generations.

Identification of Potential Candidate Genes From Co-Expression Module Analysis During Preadipocyte Differentiation in Landrace Pig.

Preadipocyte differentiation plays an important role in lipid deposition and affects fattening efficiency in pigs. In the present study, preadipocytes isolated from the subcutaneous adipose tissue of three Landrace piglets were induced into mature adipocytes in vitro. Gene clusters associated with fat deposition were investigated using RNA sequencing data at four time points during preadipocyte differentiation. Twenty-seven co-expression modules were subsequently constructed using weighted gene co-expression network analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses revealed three modules (blue, magenta, and brown) as being the most critical during preadipocyte differentiation. Based on these data and our previous differentially expressed gene analysis, angiopoietin-like 4 (ANGPTL4) was identified as a key regulator of preadipocyte differentiation and lipid metabolism. After inhibition of ANGPTL4, the expression of adipogenesis-related genes was reduced, except for that of lipoprotein lipase (LPL), which was negatively regulated by ANGPTL4 during preadipocyte differentiation. Our findings provide a new perspective to understand the mechanism of fat deposition.

Genome-Wide Detection of Selection Signatures in Duroc Revealed Candidate Genes Relating to Growth and Meat Quality.

With the development of high-throughput genotyping techniques, selection signatures in the genome of domestic pigs have been extensively interrogated in the last decade. The Duroc, a major commercial pig breed famous for its fast growth rate and high lean ratio, has not been extensively studied focusing on footprints of intensively artificial selection in their genomes by a lot of re-sequencing data. The goal of this study was to investigate genomic regions under artificial selection and their contribution to the unique phenotypic traits of the Duroc using whole-genome resequencing data from 97 pigs. Three complementary methods (di, CLR, and iHH12) were implemented for selection signature detection. In Total, 464 significant candidate regions were identified, which covered 46.4 Mb of the pig genome. Within the identified regions, 709 genes were annotated, including 600 candidate protein-coding genes (486 functionally annotated genes) and 109 lncRNA genes. Genes undergoing selective pressure were significantly enriched in the insulin resistance signaling pathway, which may partly explain the difference between the Duroc and other breeds in terms of growth rate. The selection signatures identified in the Duroc population demonstrated positive pressures on a set of important genes with potential functions that are involved in many biological processes. The results provide new insights into the genetic mechanisms of fast growth rate and high lean mass, and further facilitate follow-up studies on functional genes that contribute to the Duroc's excellent phenotypic traits.

Identification of Differentially Expressed MicroRNAs and Their Potential Target Genes in Adipose Tissue from Pigs with Highly Divergent Backfat Thickness.

Fatty traits are very important in pig production. However, the role of microRNAs (miRNAs) in fat deposition is not clearly understood. In this study, we compared adipose miRNAs from three full-sibling pairs of female Landrace pigs, with high and low backfat thickness, to investigate the associated regulatory network. We obtained an average of 17.29 million raw reads from six libraries, 62.27% of which mapped to the pig reference genome. A total of 318 pig miRNAs were detected among the samples. Among them, 18 miRNAs were differentially expressed (p-value < 0.05, |log2fold change| ≥ 1) between the high and low backfat groups; 6 were up-regulated and 12 were down-regulated. Functional enrichment of the predicted target genes of the differentially expressed miRNAs, indicated that these miRNAs were involved mainly in lipid and carbohydrate metabolism, and glycan biosynthesis and metabolism. Comprehensive analysis of the mRNA and miRNA transcriptomes revealed possible regulatory relationships for fat deposition. Negatively correlated mRNA-miRNA pairs included miR-137-PPARGC1A, miR-141-FASN, and miR-122-5p-PKM, indicating these interactions may be key regulators of fat deposition. Our findings provide important insights into miRNA expression patterns in the backfat tissue of pig and new insights into the regulatory mechanisms of fat deposition in pig.

Detection and analysis of genome-wide copy number variation in the pig genome using an 80 K SNP Beadchip.

Copy number variation (CNV) is an important source of genetic variability in human or animal genomes and play key roles in phenotypic diversity and disease susceptibility. In the present study, we performed a genome-wide analysis for CNV detection using SNP genotyping data of 857 Large White pigs. A total of 312 CNV regions (CNVRs) were detected with the PennCNV algorithm, which covered 57.76 Mb of the pig genome and correspond to 2.36% of the genome sequence. The length of the CNVRs on autosomes ranged from 1.77 Kb to 1.76 Mb with an average of 185.11 Kb. Of these, 220 completely or partially overlapped with 1,092 annotated genes, which enriched a wide variety of biological processes. Comparisons with previously reported pig CNVR revealed 92 (29.49%) novel CNVRs. Experimentally, 80% of CNVRs selected randomly were validated by quantitative PCR (qPCR). We also performed an association analysis between some of the CNVRs and reproductive traits, with results demonstrating the potential importance of CNVR61 and CNVR283 associated with litter sizes. Notably, the GPER1 gene located in CNVR61 plays a key role in reproduction. Our study is an important complement to the CNV map in the pig genome and provides valuable information for investigating the association between genomic variation and economic traits.

Transcriptome analysis of miRNA and mRNA in the livers of pigs with highly diverged backfat thickness.

Fat deposition is very important in pig production, and its mechanism is not clearly understood. MicroRNAs (miRNAs) play critical roles in fat deposition and energy metabolism. In the current study, we investigated the mRNA and miRNA transcriptome in the livers of Landrace pigs with extreme backfat thickness to explore miRNA-mRNA regulatory networks related to lipid deposition and metabolism. A comparative analysis of liver mRNA and miRNA transcriptomes from pigs (four pigs per group) with extreme backfat thickness was performed. We identified differentially expressed genes from RNA-seq data using a Cufflinks pipeline. Seventy-one differentially expressed genes (DEGs), including twenty-eight well annotated on the porcine reference genome genes, were found. The upregulation genes in pigs with higher backfat thickness were mainly involved in fatty acid synthesis, and included fatty acid synthase (FASN), glucokinase (GCK), phosphoglycerate dehydrogenase (PHGDH), and apolipoprotein A4 (APOA4). Cytochrome P450, family 2, subfamily J, polypeptide 34 (CYP2J34) was lower expressed in pigs with high backfat thickness, and is involved in the oxidation of arachidonic acid. Moreover, 13 differentially expressed miRNAs were identified. Seven miRNAs were associated with fatty acid synthesis, lipid metabolism, and adipogenic differentiation. Based on comprehensive analysis of the transcriptome of both mRNAs and miRNAs, an important regulatory network, in which six DEGs could be regulated by differentially expressed miRNAs, was established for fat deposition. The negative correlate in the regulatory network including, miR-545-5p and GRAMD3, miR-338 and FASN, and miR-127, miR-146b, miR-34c, miR-144 and THBS1 indicate that direct suppressive regulation may be involved in lipid deposition and energy metabolism. Based on liver mRNA and miRNA transcriptomes from pigs with extreme backfat thickness, we identified 28 differentially expressed genes and 13 differentially expressed miRNAs, and established an important miRNA-mRNA regulatory network. This study provides new insights into the molecular mechanisms that determine fat deposition in pigs.

Comparative adipose transcriptome analysis digs out genes related to fat deposition in two pig breeds.

Fatness traits are important in pigs because of their implications for fattening efficiency, meat quality, reproductive performance and immunity. Songliao black pigs and Landrace pigs show important differences in production and meat quality traits, including fatness and muscle growth. Therefore, we used a high-throughput massively parallel RNA-seq approach to identify genes differentially expressed in backfat tissue between these two breeds (six pigs in each). An average of 37.87 million reads were obtained from the 12 samples. After statistical analysis of gene expression data by edgeR, a total of 877 differentially expressed genes were detected between the two pig breeds, 205 with higher expression and 672 with lower expression in Songliao pigs. Candidate genes (LCN2, CES3, DGKB, OLR1, LEP, PGM1, PCK1, ACACB, FADS1, FADS2, MOGAT2, SREBF1, PPARGC1B) with known effects on fatness traits were included among the DEGs. A total of 1071 lncRNAs were identified, and 85 of these lncRNAs were differentially expressed, including 53 up-regulated and 32 down-regulated lncRNAs, respectively. The differentially expressed genes and lncRNAs involved in glucagon signaling pathway, glycolysis/gluconeogenesis, insulin signaling pathway, MAPK signaling pathway and so on. Integrated analysis potential trans-regulating or cis-regulating relation between DEGs and DE lncRNAs, suggested lncRNA MSTRG.2479.1 might regulate the expressed level of VLDLR affecting porcine fat metabolism. These results provide a number of candidate genes and lncRNAs potentially involved in porcine fat deposition and provide a basis for future research on the molecular mechanisms underlying in fat deposition.