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.

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.

Identification of DNA methylation regulated novel host genes relevant to inhibition of virus replication in porcine PK15 cell using double stranded RNA mimics and DNA methyltransferase inhibitor.

During RNA viruses's replication, double-stranded RNA (dsRNA) is normally produced and induce host innate immune response. Most of gene activation due cytokine mediated but which are due to methylation mediated is still unknown. In the study, DNA methylome was integrated with our previous transcriptome data to investigate the differentially methylated regions and genes using MeDIP-chip technology. We found that the transcriptional expressions of 15, 37 and 18 genes were negatively related with their promoter DNA methylation levels in the cells treated by PolyI:C, Aza-CdR, as well as PolyI:C plus Aza-CdR, respectively, compared with the untreated cells. GO analysis revealed hypo-methylated genes (BNIP3L and CDK9) and a hyper-methylated gene (ZC3HAV1) involved in the host response to viral replication. Our results suggest that these novel genes targeted by DNA methylation can be potential markers relevant to virus replication and host innate immune response to set up a medical model of infectious diseases.

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.

Long Noncoding RNA Lnc-SEMT Modulates IGF2 Expression by Sponging miR-125b to Promote Sheep Muscle Development and Growth.

BACKGROUND/AIMS: Long noncoding RNAs (lncRNAs) are RNA transcripts that are more than 200 nt long but have little protein-coding potential. Within the last few years, thousands of lncRNAs have been identified and their functions in biological processes have begun to be understood. Although many studies havebegun to examine the functions of many noncoding RNAs, very little is known about the functions of long noncoding (lncRNA) function of livestock production and molecular mechanisms of their functions are still lackingrelated to livestock production. METHODS: Expression of sheep enhanced muscularityTranscript lncRNA (lnc-SEMT) and miR-125b were examined in sheep using quantitative reverse-transcription polymerase chain reaction. Expression of Myod (myogenic determination factor), Myog (myoglobin) and Insulin-like growth factor 2 (IGF2)were examined by Western Blot.Luciferase reporter assays were performedto confirm the relationship between lnc-SEMT and miR-125b. RESULTS: Here, we identified a novel lnc-SEMT that promote sheep myoblast differentiation in vitro and enhanced sheep muscularity in vivo. Functional analyses showed that lnc-SEMT accelerates sheep myoblast differentiation in vitro. lnc-SEMT transgenic sheep exhibit a muscle hypertrophy phenotype characterized by increased body weight, and increased the number of muscle fibers indicating that lnc-SEMT play an important role in the regulation of skeletal muscle differentiation in vivo. Our results show that lnc-SEMT acts as a molecular sponge by antagonizing miR-125b to control IGF2 protein labundance in vitro and in vivo. CONCLUSION: In brief, lnc-SEMT is the first example of a lncRNA could be a useful candidate for improving biological growth traits such as skeletal muscle production in sheep.

Differences in gut microbiota composition in finishing Landrace pigs with low and high feed conversion ratios.

The goal of this study was to evaluate the microbial communities in the gut and feces from female finishing Landrace pigs with high and low feed conversion ratio (FCR) by 16S rRNA gene amplicon sequencing. Many potential biomarkers can distinguish between high and low FCR groups in the duodenum, ileum, cecum, colon, and rectum, according to linear discriminant analysis effect sizes. The relative abundance of microbes were tested by Mann-Whitney test between the high and low FCR groups in different organs: Campylobacter, Prevotella and Sphaerochaeta were different in the duodenum (P < 0.05); Sanguibacter, Kingella and Anaeroplasma in jejunum; Anaeroplasma, Arthrobacter, Kingella, Megasphaera and SMB53 in the ileum; Butyricicoccus, Campylobacter, Mitsuokella, and Coprobacillus in the cecum; Lactococcus and Peptococcus in the colon; Staphylococcus in the rectum; and Rothia in feces. The prevalence of microbial genera in certain locations could potentially be used as biomarkers to distinguish between high and low FCR. Functional prediction clustering analysis suggested that bacteria in the hindgut mainly participated in carbohydrate metabolism and amino acid metabolism, and different in the relative abundance of metabolic pathways, as predicted from the microbial taxa present, were identified by comparing the high and low groups of each location. The results may provide insights for the alteration of the intestinal microbial communities to improve the growth rate of pigs.

Genome-wide effects of DNA methyltransferase inhibitor on gene expression in double-stranded RNA transfected porcine PK15 cells.

Double-stranded RNA (dsRNA) is produced in host cells during viral replication. The effects of DNA demethylation on gene expression in dsRNA transfected swine cells are unclear. The study aims to profile the transcriptome changes which are induced by DNA methyltransferase inhibitor (Aza-CdR) in porcine PK15 cells transfected with viral-like dsRNA (Poly(I:C)). A total of 44, 76 and 952 differentially expressed genes (DEGs) were detected in the cells treated by Poly(I:C) plus Aza-CdR (P+A), Poly(I:C) (P) or Aza-CdR (A) alone compared to the controls (C). Immune response-related pathways are observed in the comparison of A vs. C and P vs. C, and the genes in the pathways were recovered in the comparison of (P+A) vs. C. GO analysis indicated that Aza-CdR has negative regulatory effects on viral reproduction. The results suggest that the stimulant of Poly(I:C) could be regressed by Aza-CdR. These observations provide new insights into the epigenetic regulatory effects on viral replication.

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.

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.

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.

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.

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.

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.

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.