Identification of genes for controlling swine adipose deposition by integrating transcriptome, whole-genome resequencing, and quantitative trait loci data

Whole genome and transcriptome analyses identify genetic markers associated with growth traits in Qinchuan black pig

BACKGROUND

Growth traits are economically important traits in pig breeding. However, the genetic mechanism of growth traits is still unclear. Qinchuan Black (QCB) pigs are crossbred and produced by hybridizing Guanzhong Black (GZB) pigs and Large White (LW) pigs, its characteristics include fast growth and excellent meat quality. In this study, whole genome and transcriptome analyses revealed the candidate genes associated with growth traits in QCB pigs based on imputed low-coverage whole-genome resequencing data.

RESULTS

In total, we used 197 low-depth whole-genome resequencing data with an average depth of 3.5X, and then the data were imputed to resequencing data using SWIM reference panel, the imputation accuracy parameters, allele frequency r2 and concordance rate were 0.86 and 95.83%, respectively. We used two methods to investigate the candidate genes affecting the growth traits of QCB pigs, a total of 371 PSGs were identified, which related to muscle tissue development, tissue development and system development. A total of 30,489,782 SNPs were retained. A GWAS of ten growth traits by using fixed and random model circulating probability unification (FarmCPU) model, was performed in QCB pigs. We discovered seven genome wide significant SNPs and eight genome wide suggestive significant SNPs associated with body weight at 2 months (2-BW), body length at 2 months (2-BL), body height at 2 months (2-BH) and body height at 4 months (4-BH), and eighteen potential candidate genes were discovered. Transcriptomic data revealed that 18 differentially expression genes related to muscle and growth and development. Additionally, whole genome and transcriptome analyses found six genes (TENM3, CTNND2, RIMS1, PCDH7, ADGRL3 and CTNNA3) may affect the growth traits in Qinchuan Black pigs.

CONCLUSION

Our study shows that more candidate genes associated with pig growth traits can be identified by whole genome and transcriptome analyses. We found that six genes may be new key candidate genes affecting pig growth traits. In conclusion, this study elucidated the molecular genetic mechanisms of growth traits and identified new molecular breeding targets, offering a robust scientific basis for advancing breeding strategies and genetic investigations within this breed.

Transcriptome and Metabolome Insights into Key Genes Regulating Fat Deposition and Meat Quality in Pig Breeds

Meat quality is a complex trait that exhibits significant variation across pig breeds, and the regulatory mechanisms governing pork meat quality are not fully elucidated. We compared the transcriptomics and metabolomics of the longissimus dorsi (LD) muscle between the Songliao Black Pig (SBP) and Large White × Landrace Pig (LWLDP) to investigate breed-specific differences in meat quality and underlying regulatory pathways. The results showed that SBP meat had a higher marbling score and backfat thickness, a richer color, a lower shear force, and reduced drip loss. Fatty acid (FA) analysis identified 15 significant FAs in the LWLDP, with docosahexaenoic acid (DHA) in the SBP, while amino acid (AA) analysis revealed no breed-based differences. Transcriptome analysis identified 134 upregulated and 362 downregulated genes in the SBP. Protein-protein interaction (PPI) network analysis found 25 key genes, which are associated with muscle development, fat deposition, and overall meat quality, while genes in the insulin signaling pathway, such as PPP1R3B, PPARGC1A, SOCS1, EIF4E, PRKAR2A, PRKAG2, and FASN, play a crucial role in balancing fat metabolism and catabolism. Metabolomic analysis identified 89 upregulated and 10 downregulated metabolites in the SBP, primarily involved in fructose and mannose metabolism, amino acid biosynthesis, nucleotide sugar metabolism, and glucagon signaling pathways. Gene-metabolite association analysis found that the PPP1R3B gene had a strong association with Thr-Leu, Maltol, D-myo-Inositol-4-phosphate, and Fructose-6-phosphate, while MYOG correlated with Mannose-6-phosphate, Fructose-1-phosphate, Mannose-1-phosphate, and Glucose-6-phosphate. In contrast, NR4A3 and PPARGC1A showed a strong negative correlation with most upregulated metabolites. In conclusion, this study identified functional genes, elucidated the mechanisms associated with meat quality traits, and identified gene-metabolite associations involved in energy metabolism, muscle development, and fat deposition, providing valuable insights into the molecular mechanisms that regulate meat quality between pig breeds.

Differential chromatin accessibility and Gene Expression Associated with Backfat Deposition in pigs

BACKGROUND

Backfat serves as a vital fat reservoir in pigs, and its excessive accumulation will adversely impact pig growth performance, farming efficiency, and pork quality. The aim of this research is to integrate assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) and RNA sequencing (RNA-seq) to explore the molecular mechanisms underlying porcine backfat deposition.

RESULTS

ATAC-seq analysis identified 568 genes originating from 698 regions exhibiting differential accessibility, which were significantly enriched in pathways pertinent to adipocyte differentiation and lipid metabolism. Besides, a total of 283 transcription factors (TFs) were identified by motif analysis. RNA-seq analysis revealed 978 differentially expressed genes (DEGs), which were enriched in pathways related to energy metabolism, cell cycle and signal transduction. The integration of ATAC-seq and RNA-seq data indicates that DEG expression levels are associated with chromatin accessibility. This comprehensive study highlights the involvement of critical pathways, including the Wnt signaling pathway, Jak-STAT signaling pathway, and fatty acid degradation, in the regulation of backfat deposition. Through rigorous analysis, we identified several candidate genes (LEP, CTBP2, EHHADH, OSMR, TCF7L2, BCL2, FGF1, UCP2, CCND1, TIMP1, and VDR) as potentially significant contributors to backfat deposition. Additionally, we constructed TF-TF and TF-target gene regulatory networks and identified a series of potential TFs related to backfat deposition (FOS, STAT3, SMAD3, and ESR1).

CONCLUSIONS

This study represents the first application of ATAC-seq and RNA-seq, affording a novel perspective into the mechanisms underlying backfat deposition and providing invaluable resources for the enhancement of pig breeding programs.

Identification of potential tissue-specific biomarkers involved in pig fat deposition through integrated bioinformatics analysis and machine learning

Backfat thickness (BT) and intramuscular fat (IMF) content are closely appertained to meat production and quality in pig production. Deposition in subcutaneous adipose (SA) and IMF concerns different genes and regulatory mechanisms. And larger studies with rigorous design should be carried to explore the molecular regulation of fat deposition in different tissues. The purpose of this study is to gain a better understanding of the molecular mechanisms underlying differences in fat deposition among different tissues and identify tissue-specific genes involved in regulating fat deposition. The SA-associated datasets (GSE122349 and GSE145956) and IMF-associated datasets (GSE165613 and GSE207279) were downloaded from the Gene Expression Omnibus (GEO) as the BT and IMF group, respectively. Subsequently, the Robust Rank Aggregation (RRA) algorithm identified 27 down- and 29 up-regulated differentially expressed genes (DEGs) in the BT group. Based on bioinformatics and three machine learning algorithms, four SA deposition-related potential biomarkers, namely ACLY, FASN, ME1, and ARVCF were selected. FASN was evaluated as the most valuable biomarker for the SA mechanism. The 18 down- and 34 up-regulated DEGs in the IMF group were identified, and ACTA2 and HMGCL were screened as the IMF deposition-related candidate core genes, especially the ACTA2 may play the critical role in IMF deposition regulation. Moreover, based on the constructed ceRNA network, we postulated that the role of predicted ceRNA interaction network of XIST, NEAT1/miR-15a-5p, miR-16-5p, miR-424-5p, miR-497-5p/FASN were vital in the SA metabolism, XIST, NEAT1/miR-27a/b-3p, 181a/c-5p/ACTA2 might contribute to the regulation to IMF metabolism, which all gave suggestions in molecular mechanism for regulation of fat deposition. These findings may facilitate advancements in porcine quality at the genetic and molecular levels and assist with human obesity-associated diseases.

Comparative transcriptome analysis of longissimus dorsi muscle reveal potential genes affecting meat trait in Chinese indigenous Xiang pig

In this study, we compared the transcriptome of longissimus dorsi muscle between Guizhou Xiang pigs (XP) and Western commercial Large White pigs (LW), which show diffirent meat quality between them. In terms of meat quality traits, the pH 45 min, color score, backfat thickness, and intramuscular fat (IMF) content were higher in Xiang pigs than in Large White pigs (P < 0.01), while the drip loss, lean meat percentage, shear force, and longissimus dorsi muscle area of Xiang pigs were lower than that of Large White pigs (P < 0.01). Nutrients such as monounsaturated fatty acid (MUFA), total amino acids (TAA), delicious amino acids (DAA) and essential amino acids (EAA) in Xiang pigs were higher than that in Large White pigs, and the proportion of polyunsaturated fatty acid (PUFA) of Xiang pigs was significantly lower than Large White pigs (P < 0.01). Transcriptome analysis identified 163 up-regulated genes and 88 genes down-regulated in Xiang pigs longissimus dorsi muscle. Combined with the correlation analysis and quantitative trait locis (QTLs) affecting meat quality, a total of 227 DEGs were screened to be significantly associated with meat quality values. Enrichment analysis indicated that numerous members of genes were gathered in muscle development, adipogenesis, amino acid metabolism, fatty acid metabolism and synthesis. Of those, 29 genes were identified to be hub genes that might be related with the meat quality of Xiang pig, such as MYOD1, ACTB, ASNS, FOXO1, ARG2, SLC2A4, PLIN2, and SCD. Thus, we screened and identified the potential functional genes for the formation of meat quality in Xiang pigs, which provides a corresponding theoretical basis for the study of the molecular regulatory mechanism of pork quality and the improvement of pork quality.

Alternative Polyadenylation of Malic Enzyme 1 Is Essential for Accelerated Adipogenesis

Understanding the mechanism of adipogenesis is an important basis for improving meat quality traits of livestock. Alternative polyadenylation (APA) is a vital mechanism to regulate the expression of eukaryotic genes. However, how the individual APA functions in adipogenesis remains elusive. This study was intended to investigate the effect of malic enzyme 1 (ME1) APA on adipogenesis. Here, intracellular lipid droplets were stained using Oil red O. 3' RACE was used to verify APA events of the ME1 gene. Interactions between ME1 3' untranslated region (3' UTR)-APA isoforms and miRNAs, as well as differential expression of isoforms, were examined using dual-luciferase reporter and molecular experiments. The mechanism of ME1 APA on adipogenesis was explored by gain and loss of function assays. In this study, two ME1 isoforms with different 3' UTR lengths were detected during adipogenesis. Moreover, the ME1 isoform with a short 3' UTR was significantly upregulated compared with the one with a long 3' UTR. Mechanistically, only the long ME1 isoform was targeted by miR-153-3p to attenuate adipogenesis, while the short one escaped the regulation of miR-153-3p to accelerate adipogenesis. Our results reveal a novel mechanism of ME1 APA in regulating adipogenesis.

Genome-Wide Association Study for Somatic Skeletal Traits in Duroc × (Landrace × Yorkshire) Pigs

The pig bone weight trait holds significant economic importance in southern China. To expedite the selection of the pig bone weight trait in pig breeding, we conducted molecular genetic research on these specific traits. These traits encompass the bone weight of the scapula (SW), front leg bone weight (including humerus and ulna) (FLBW), hind leg bone weight (including femur and tibia) (HLBW), and spine bone weight (SBW). Up until now, the genetic structure related to these traits has not been thoroughly explored, primarily due to challenges associated with obtaining the phenotype data. In this study, we utilized genome-wide association studies (GWAS) to discern single nucleotide polymorphisms (SNPs) and genes associated with four bone weight traits within a population comprising 571 Duroc × (Landrace × Yorkshire) hybrid pigs (DLY). In the analyses, we employed a mixed linear model, and for the correction of multiple tests, both the false discovery rate and Bonferroni methods were utilized. Following functional annotation, candidate genes were identified based on their proximity to the candidate sites and their association with the bone weight traits. This study represents the inaugural application of GWAS for the identification of SNPs associated with individual bone weight in DLY pigs. Our analysis unveiled 26 SNPs and identified 12 promising candidate genes (OPRM1, SLC44A5, WASHC4, NOPCHAP1, RHOT1, GLP1R, TGFB3, PLCB1, TLR4, KCNJ2, ABCA6, and ABCA9) associated with the four bone weight traits. Furthermore, our findings on the genetic mechanisms influencing pig bone weight offer valuable insights as a reference for the genetic enhancement of pig bone traits.

Identification of genes related to growth traits from transcriptome profiles of duck breast muscle tissue

The growth and development of duck skeletal muscle is an important economic trait that is genetically regulated. The internal mechanism underlying the regulation of skeletal muscle growth and development in ducks remains unclear. The purpose of this study was to identify candidate genes related to the growth of duck skeletal muscle. RNA-sequencing technology was used to compare the transcriptome of duck breast muscles in an F2 population with the high breast muscle rate (HB) and the low breast muscle rate (LB). A total of 14,522 genes were confirmed to be expressed in the breast muscle, and 173 differentially expressed genes (DEGs) were identified between the HB and LB groups. Functional analysis showed that these DEGs were mainly involved in biological processes and pathways of fat metabolism and muscle growth, especially the FABP3 and MYL4 involved in the PPAR signaling pathway and cardiac muscle contraction pathway. These findings deepened our understanding of the molecular mechanisms involved in muscle growth in ducks and provided a theoretical basis for improving duck production and breeding of ducks.

Transcriptome, proteome and metabolome analysis provide insights on fat deposition and meat quality in pig

Intramuscular fat (IMF) content, which is an important determinant of meat quality characteristics such as tenderness, juiciness and flavor, has long been a research hotspot. Chinese local pig breeds are famous for their excellent meat quality which is mainly reflected in the high IMF content, strong hydraulic system and et al. However, there are few analysis of meat quality by omics methods. In our study, we identified 12 different fatty acids, 6 different amino acids, 1,262 differentially expression genes (DEGs), 140 differentially abundant proteins (DAPs) and 169 differentially accumulated metabolites (DAMs) (p < 0.05) with metabolome, transcriptome, and proteome. It has been found that DEGs, DAPs and DAMs were enriched in the Wnt signaling pathway, PI3K-Akt signaling pathway, Rap1 signaling pathway, and Ras signaling pathway which were related to meat quality. Moreover, our Weighted genes co-expression network construction (WGCNA) showed RapGEF1 was the key gene related to IMF content and the RT-qPCR analysis was used to perform validation of the significant genes. In summary, our study provided both fundamental data and new insights to further uncover the secret of pig IMF content.

Malic Enzyme 1 (ME1) Promotes Adiposity and Hepatic Steatosis and Induces Circulating Insulin and Leptin in Obese Female Mice

Malic Enzyme 1 (ME1) supports lipogenesis, cholesterol synthesis, and cellular redox potential by catalyzing the decarboxylation of L-malate to pyruvate, and the concomitant reduction of NADP to NADPH. We examined the contribution of ME1 to the development of obesity by provision of an obesogenic diet to C57BL/6 wild type (WT) and MOD-1 (lack ME1 protein) female mice. Adiposity, serum hormone levels, and adipose, mammary gland, liver, and small intestine gene expression patterns were compared between experimental groups after 10 weeks on a diet. Relative to WT female mice, MOD-1 female mice exhibited lower body weights and less adiposity; decreased concentrations of insulin, leptin, and estrogen; higher concentrations of adiponectin and progesterone; smaller-sized mammary gland adipocytes; and reduced hepatosteatosis. MOD-1 mice had diminished expression of Lep gene in abdominal fat; Lep, Pparg, Klf9, and Acaca genes in mammary glands; Pparg and Cdkn1a genes in liver; and Tlr9 and Ffar3 genes in the small intestine. By contrast, liver expression of Cdkn2a and Lepr genes was augmented in MOD-1, relative to WT mice. Results document an integrative role for ME1 in development of female obesity, suggest novel linkages with specific pathways/genes, and further support the therapeutic targeting of ME1 for obesity, diabetes, and fatty liver disease.

The Effect of BSCL2 Gene on Fat Deposition Traits in Pigs

BSCL2 encodes seipin, a transmembrane endoplasmic reticulum protein associated with lipodystrophy and severe metabolic complications, including diabetes and hepatic steatosis. In pigs, BSCL2 expression increases during adipocyte differentiation. In the present study, we identified significant gene variants associated with fat deposition (FD)-related processes based on subcutaneous fat tissue RNA-seq data. In the association study, to prove our hypothesis, three Polish pig breeds were included: Złotnicka White (ZW, n = 72), Polish Landrace (PL, n = 201), and Polish Large White (PLW, n = 169). Based on variant calling analysis and χ² tests, BSCL2 mutations showing significantly different genotype/allele distribution between high- and low-fat pigs were selected for a comprehensive association study. Four interesting BSCL2 variants (rs346079334, rs341493267, rs330154033, and rs81333153) belonging to downstream and missense mutations were investigated. Our study showed a significant decrease in minor allele frequency for two BSCL2 variants (rs346079334 and rs341493267) in PL pigs in 2020-2021. In ZW, BSCL2 mutations significantly affected loin and ham fats, meat redness, and growth performance traits, such as feed conversion and daily feed intake. Similar observations were noted for PLW and PL, where BSCL2 mutations influenced fat depositions and meat traits, such as loin eye area, loin mass and fat, carcass yield, and growth performance traits. Based on the observation in pigs, our study supports the theory that BSCL2 expressed in subcutaneous fat is involved in the FD process.

Transcription Analysis of Liver and Muscle Tissues from Landrace Finishing Pigs with Different Feed Conversion Ratios

The efficiency of feed utilization determines the cost and economic benefits of pig production. In the present study, two pairs of full-sibling and two pairs of half-sibling female Landrace finishing pigs were selected, with each pair including individuals with different feed conversion rates, with liver and longissimus muscle tissue samples collected from each group for transcriptome analysis. A total of 561 differentially expressed genes (DEGs), among which 224 were up-regulated and 337 were down-regulated, were detected in the liver transcriptomes in the high-feed efficiency group compared to the low-feed efficiency group. The DEGs related to phosphorus and phosphate metabolism, arginine biosynthesis, chemical carcinogenesis, cytokine-cytokine receptor interaction, the biosynthesis of amino acids, and drug metabolism-cytochrome P450 in liver tissue were also associated with feed efficiency. In total, 215 DEGs were screened in the longissimus muscle tissue and were mainly related to disease and immune regulation, including complement and coagulation cascades, systemic lupus erythematosus, and prion diseases. The combination of gene expression and functional annotation results led to the identification of candidate feed efficiency-related biomarkers, such as ARG1, ARG2, GOT1, GPT2, ACAA2, ACADM, and ANGPTL4, members of cytochrome P450 family, and complement component family genes. Although the novel feed efficiency-related candidate genes need to be further evaluated by a larger sample size and functional studies, the present study identifies novel candidate biomarkers for the identification of functional SNPs underlying porcine feed efficiency.

Identification of circRNAs Associated with Adipogenesis Based on RNA-seq Data in Pigs

Adipocytes or fat cells play a vital role in the storage and release of energy in pigs, and many circular RNAs (circRNAs) have emerged as important regulators in various tissues and cell types in pigs. However, the spatio-temporal expression pattern of circRNAs between different adipose deposition breeds remains elusive. In this study, RNA sequencing (RNA-seq) produced transcriptome profiles of Western Landrace (lean-type) and Chinese Songliao black pigs (obese-type) with different thicknesses of subcutaneous fat tissues and were used to identify circRNAs involved in the regulation of adipogenesis. Gene expression analysis revealed 883 circRNAs, among which 26 and 11 circRNAs were differentially expressed between Landrace vs. Songliao pigs and high- vs. low-thickness groups, respectively. We also analyzed the interaction between circRNAs and microRNAs (miRNAs) and constructed their interaction network in adipogenesis; gene ontology classification and pathway analysis revealed two vital circRNAs, with the majority of their target genes enriched in biological functions such as fatty acids biosynthesis, fatty acid metabolism, and Wnt/TGF-β signaling pathways. These candidate circRNAs can be taken as potential targets for further experimental studies. Our results show that circRNAs are dynamically expressed and provide a valuable basis for understanding the molecular mechanism of circRNAs in pig adipose biology.

Variations in Fibrinogen-like 1 (FGL1) Gene Locus as a Genetic Marker Related to Fat Deposition Based on Pig Model and Liver RNA-Seq Data

The goal of this study was to evaluate the effects of mutations in the FGL1 gene associated with pig productive traits to enrich the genetic marker pool for further selection and to support the studies on FGL1 in the context of the fat deposition (FD) process. The variant calling and χ2 analyses of liver RNA-seq data were used to indicate genetic markers. FGL1 mutations were genotyped in the Złotnicka White (n = 72), Polish Large White (n = 208), Duroc (n = 72), Polish Landrace (PL) (n = 292), and Puławska (n = 178) pig breeds. An association study was performed using a general linear model (GLM) implemented in SAS® software. More than 50 crucial mutations were identified in the FGL1 gene. The association study showed a significant effect of the FGL1 on intramuscular fat (IMF), loin eye area, backfat thickness at the lumbar, ham mass (p = 0.0374), meat percentage (p = 0.0205), and loin fat (p = 0.0003). Alternate homozygotes and heterozygotes were found in the PL and Duroc, confirming the selective potential for these populations. Our study supports the theory that liver FGL1 is involved in the FD process. Moreover, since fat is the major determinant of flavor development in meat, the FGL1 rs340465447_A allele can be used as a target in pig selection focused on elevated fat levels.

Pre-Clinical Models in Implant Dentistry: Past, Present, Future

Biomedical research seeks to generate experimental results for translation to clinical settings. In order to improve the transition from bench to bedside, researchers must draw justifiable conclusions based on data from an appropriate model. Animal testing, as a prerequisite to human clinical exposure, is performed in a range of species, from laboratory mice to larger animals (such as dogs or non-human primates). Minipigs appear to be the animal of choice for studying bone surgery around intraoral dental implants. Dog models, well-known in the field of dental implant research, tend now to be used for studies conducted under compromised oral conditions (biofilm). Regarding small animal models, research studies mostly use rodents, with interest in rabbit models declining. Mouse models remain a reference for genetic studies. On the other hand, over the last decade, scientific advances and government guidelines have led to the replacement, reduction, and refinement of the use of all animal models in dental implant research. In new development strategies, some in vivo experiments are being progressively replaced by in vitro or biomaterial approaches. In this review, we summarize the key information on the animal models currently available for dental implant research and highlight (i) the pros and cons of each type, (ii) new levels of decisional procedures regarding study objectives, and (iii) the outlook for animal research, discussing possible non-animal options.

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 (n_high = 3, n_low = 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.

Comparison of long non-coding RNAs in adipose and muscle tissues between seven indigenous Chinese and the Yorkshire pig breeds

lncRNAs play crucial roles in fat metabolism in animals. Previously, we have compared the mRNA transcriptome profiles between seven fat-type Chinese pig breeds and one lean-type Western breed (Yorkshire, YY). The associations between differentially expressed (DE) genes and phenotypical traits were investigated. In the present study, to further explore the underlying regulatory mechanisms, lncRNAs were sequenced and compared between YY and Chinese indigenous breeds. The results showed 9114 and 7538 DE lncRNAs between at least one Chinese breed and the YY breed in the adipose and muscle tissue respectively. KEGG enrichment analysis revealed that the target genes of these DE lncRNAs mainly influenced the glucolipid metabolism, which is an important process affecting meat quality. Correlation analyses between the DE lncRNA and DE mRNA genes related to meat quality and growth traits were performed. The results showed that LTCONS_00073280 was associated with intramuscular fat content. Four lncRNAs (LTCONS_00101781, LTCONS_00037879, LTCONS_00088260 and LTCONS-00128343) might mediate backfat thickness. Overall, this study provides candidate lncRNAs that potentially affect meat quality, which might be useful for molecular breeding of pig breeds in future.

Candidate gene screening for lipid deposition using combined transcriptomic and proteomic data from Nanyang black pigs

Background

Lower selection intensities in indigenous breeds of Chinese pig have resulted in obvious genetic and phenotypic divergence. One such breed, the Nanyang black pig, is renowned for its high lipid deposition and high genetic divergence, making it an ideal model in which to investigate lipid position trait mechanisms in pigs. An understanding of lipid deposition in pigs might improve pig meat traits in future breeding and promote the selection progress of pigs through modern molecular breeding techniques. Here, transcriptome and tandem mass tag-based quantitative proteome (TMT)-based proteome analyses were carried out using longissimus dorsi (LD) tissues from individual Nanyang black pigs that showed high levels of genetic variation.

Results

A large population of Nanyang black pigs was phenotyped using multi-production trait indexes, and six pigs were selected and divided into relatively high and low lipid deposition groups. The combined transcriptomic and proteomic data identified 15 candidate genes that determine lipid deposition genetic divergence. Among them, FASN, CAT, and SLC25A20 were the main causal candidate genes. The other genes could be divided into lipid deposition-related genes (BDH2, FASN, CAT, DHCR24, ACACA, GK, SQLE, ACSL4, and SCD), PPARA-centered fat metabolism regulatory factors (PPARA, UCP3), transcription or translation regulators (SLC25A20, PDK4, CEBPA), as well as integrin, structural proteins, and signal transduction-related genes (EGFR).

Conclusions

This multi-omics data set has provided a valuable resource for future analysis of lipid deposition traits, which might improve pig meat traits in future breeding and promote the selection progress in pigs, especially in Nanyang black pigs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07764-2.

Selection and validation of differentially expressed metabolic and immune genes in weaned Ghurrah versus crossbred piglets

In the present investigation, differentially expressed genes (DEGs) were studied using RNA sequencing (RNA-seq) technique in porcine peripheral blood mononuclear cells (PBMC) of weaned Ghurrah and crossbred piglets at 3-month age. Transcriptomic analysis was done using three different packages, namely, EBSeq, DESeq2, and edgeR, to identify the DEGs between Ghurrah and crossbred piglets. Total 7717 DEGs were commonly identified by all three packages, out of which 4151 genes found to be up-regulated, and 3566 genes were down-regulated. Functional annotation of these DEGs indicated metabolism as the most commonly enriched category followed by the immune response. Genes related to metabolism and growth were up-regulated in crossbred piglets as compared with Ghurrah piglets, whereas immunity-related genes were up-regulated in Ghurrah piglets elucidating the disease resistance nature of this indigenous breed over crossbred counterparts. Further, eight DEGs, namely, LRP-1, ADCY4, ERRFI1, LDHD, ARG1, OASL, MGARP, and S100A8, were validated by qRT-PCR in a separate set of biological samples and found to be in concordance with RNA-seq results. Finding in the present study provides insight into genes and their molecular mechanisms governing difference in growth performance between Ghurrah and crossbred pigs.

A Transcriptome Analysis Reveals that Hepatic Glycolysis and Lipid Synthesis Are Negatively Associated with Feed Efficiency in DLY Pigs

Feed efficiency (FE) is an important trait in the porcine industry. Therefore, understanding the molecular mechanisms of FE is vital for the improvement of this trait. In this study, 6 extreme high-FE and 6 low-FE pigs were selected from 225 Duroc × (Landrace × Yorkshire) (DLY) pigs for transcriptomic analysis. RNA-seq analysis was performed to determine differentially expressed genes (DEGs) in the liver tissues of the 12 individuals, and 507 DEGs were identified between high-FE pigs (HE- group) and low-FE pigs (LE- group). A gene ontology (GO) enrichment and pathway enrichment analysis were performed and revealed that glycolytic metabolism and lipid synthesis-related pathways were significantly enriched within DEGs; all of these DEGs were downregulated in the HE- group. Moreover, Weighted gene co-expression analysis (WGCNA) revealed that oxidative phosphorylation, thermogenesis, and energy metabolism-related pathways were negatively related to HE- group, which might result in lower energy consumption in higher efficiency pigs. These results implied that the higher FE in the HE- group may be attributed to a lower glycolytic, energy consumption and lipid synthesizing potential in the liver. Furthermore, our findings suggested that the inhibition of lipid synthesis and glucose metabolic activity in the liver may be strategies for improving the FE of DLY pigs.

An integrated analysis of testis miRNA and mRNA transcriptome reveals important functional miRNA-targets in reproduction traits of roosters

The reproductive efficiency of roosters is an important trait in poultry production; however, the molecular mechanisms underlying this trait are not clearly understood. Here, we compared the mRNA and microRNA (miRNA) transcriptomes of testis from roosters with divergent sperm motility. A total of 302 differentially expressed genes (DEGs), including 182 upregulated genes and 120 downregulated genes, were identified in high sperm motility groups compared with low sperm motility groups. A subset of these DEGs related to steroid hormone biosynthesis and thus could be important for spermatogenesis. Additionally, we detected 13 differentially expressed miRNAs (DEMs) between two groups, and target gene prediction indicated seven of these could be associated with spermatogenesis. Based on a comprehensive analysis of these transcriptomes, miRNA-mRNA interaction networks were constructed. Six DEGs were predicted to be regulated by DEMs. Subsequently, we validated the negative regulation of family with sequence similarity 84, member A (FAM84A) by miR-215 using a dual-luciferase reporter system. These results provide new insights into the molecular profile of the testis and identify genes that may determine sperm motility in chickens.

Identification of Molecular Mechanisms Related to Pig Fatness at the Transcriptome and miRNAome Levels

Fat deposition and growth rate are closely related to pork quality and fattening efficiency. The next-generation sequencing (NGS) approach for transcriptome and miRNAome massive parallel sequencing of adipocyte tissue was applied to search for a molecular network related to fat deposition in pigs. Pigs were represented by three breeds (Large White, Pietrain, and Hampshire) that varied in fat content within each breed. The obtained results allowed for the detection of significant enrichment of Gene Ontology (GO) terms and pathways associated directly and indirectly with fat deposition via regulation of fatty acid metabolism, fat cell differentiation, inflammatory response, and extracellular matrix (ECM) organization and disassembly. Moreover, the results showed that adipocyte tissue content strongly affected the expression of leptin and other genes related to a response to excessive feed intake. The findings indicated that modification of genes and miRNAs involved in ECM rearrangements can be essential during fat tissue growth and development in pigs. The identified molecular network within genes and miRNAs that were deregulated depending on the subcutaneous fat level are proposed as candidate factors determining adipogenesis, fatness, and selected fattening characteristics in pigs.

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

Simple Summary

The role of microRNA in fat deposition is very important and not clearly understood. We detected 318 pig microRNAs (miRNAs), among high and low backfat tissue samples, by high throughput sequencing. Among them, 18 miRNAs were differentially expressed between the high and low backfat groups. Some of the differentially expressed miRNAs were involved mainly in lipid and carbohydrate metabolism, and glycan biosynthesis and metabolism. In addition, in silico analysis of the mRNA and miRNA transcriptomes, revealed possible regulatory relationships for fat deposition. In particular, three miRNA–mRNA pairs, miR-137–PPARGC1A, miR-141–FASN, and miR-122-5p–PKM, were identified as candidate key regulators of fat deposition. Our findings provide an important insight into miRNA expression patterns in backfat tissue of pig and new insights into the regulatory mechanisms of fat deposition in pig.

Abstract

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.

Comparative gene expression profiling of muscle reveals potential candidate genes affecting drip loss in pork

BACKGROUND

Drip loss is a key aspect of meat quality. Transcriptome profiles of muscle with divergent drip loss would offer important insight into the genetic factors responsible for the trait. In this study, drip loss and other meat quality traits of 28 purebred Duroc pigs were measured, muscles of these individuals were RNA sequenced, and eight individuals with extremely low and high drip loss were selected for analyzing their transcriptome differences and identifying potential candidate genes affecting drip loss.

RESULTS

As a result, 363 differentially expressed (DE) genes were detected in the comparative gene expression analysis, of which 239 were up-regulated and 124 were down-regulated in the low drip loss group. The DE genes were further filtered by correlation analysis between their expression and drip loss values in the 28 Duroc pigs measured and comparison of them with QTLs affecting drip loss. Consequently, of the 363 DE genes, 100 were identified as critical DE genes for drip loss. Functional analysis of these critical DE genes revealed some GO terms (extracellular matrix, cell adhesion mediated by integrin, heterotypic cell-cell adhesion), pathway (ECM-receptor interaction), and new potential candidate genes (TNC, ITGA5, ITGA11, THBS3 and CD44) which played an important role in regulating the variation of drip loss, and deserved to carry further studies to unravel their specific mechanism on drip loss.

CONCLUSIONS

Our study revealed some GO terms, pathways and potential candidate genes affecting drip loss. It provides crucial information to understand the molecular mechanism of drip loss, and would be of help for improving meat quality of pigs.

Optimal sequencing depth design for whole genome re-sequencing in pigs

BACKGROUND

As whole-genome sequencing is becoming a routine technique, it is important to identify a cost-effective depth of sequencing for such studies. However, the relationship between sequencing depth and biological results from the aspects of whole-genome coverage, variant discovery power and the quality of variants is unclear, especially in pigs. We sequenced the genomes of three Yorkshire boars at an approximately 20X depth on the Illumina HiSeq X Ten platform and downloaded whole-genome sequencing data for three Duroc and three Landrace pigs with an approximately 20X depth for each individual. Then, we downsampled the deep genome data by extracting twelve different proportions of 0.05, 0.1, 0.15, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8 and 0.9 paired reads from the original bam files to mimic the sequence data of the same individuals at sequencing depths of 1.09X, 2.18X, 3.26X, 4.35X, 6.53X, 8.70X, 10.88X, 13.05X, 15.22X, 17.40X, 19.57X and 21.75X to evaluate the influence of genome coverage, the variant discovery rate and genotyping accuracy as a function of sequencing depth. In addition, SNP chip data for Yorkshire pigs were used as a validation for the comparison of single-sample calling and multisample calling algorithms.

RESULTS

Our results indicated that 10X is an ideal practical depth for achieving plateau coverage and discovering accurate variants, which achieved greater than 99% genome coverage. The number of false-positive variants was increased dramatically at a depth of less than 4X, which covered 95% of the whole genome. In addition, the comparison of multi- and single-sample calling showed that multisample calling was more sensitive than single-sample calling, especially at lower depths. The number of variants discovered under multisample calling was 13-fold and 2-fold higher than that under single-sample calling at 1X and 22X, respectively. A large difference was observed when the depth was less than 4.38X. However, more false-positive variants were detected under multisample calling.

CONCLUSIONS

Our research will inform important study design decisions regarding whole-genome sequencing depth. Our results will be helpful for choosing the appropriate depth to achieve the same power for studies performed under limited budgets.

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.

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.

Comparing pig breeds with genetically low and high backfat thickness: differences in expression of adiponectin, its receptor, and blood metabolites

Here we characterized gene expressions in subcutaneous adipose tissue and blood metabolites of pigs with genetically low backfat (Landrace) and high backfat (Meishan). As pigs aged from 1 wk-to 3-mo old, mRNA levels of adipose-specific genes increased, although their gene expressions coding for major enzymes involved in lipid metabolism (lipoprotein lipase, fatty acid synthase, and hormone-sensitive lipase) did not differ between lean and fat pigs. Instead, there were significant effects for adiponectin and its receptor AdipoR1 mRNA levels between the two breeds of which respective expressions were lower and higher in Meishan by 3 mo of age. Contrary to changes in gene expressions, the concentrations of blood glucose, triglyceride (TG), and NEFA in both breeds decreased during growth, and 3-mo-old Meishan evidenced lower glucose with higher TG than the Landrace. The homeostasis model assessment insulin resistance (HOMA-IR) index was also calculated from the measurements of fasting glucose and insulin concentration, and Meishan showed a higher value than the Landrace. We next examined these differences in Landrace and Meishan crossbreds, which were phenotypically distinguishable by the backfat thickness as the former lean type and the latter fat type. As with the purebreds, high backfat Meishan crosses showed the characteristics of lower glucose and higher TG in circulating levels and also lower adiponectin transcripts in subcutaneous adipose tissue. Collectively, our results demonstrate that levels of adiponectin and its receptor gene expressions, blood glucose, blood lipids, and HOMA-IR in pigs vary between lean and fat. These observations strongly suggest the possibility that overall metabolic differences rather than adipocyte ability itself contribute to the fatness of genetically high backfat pigs.

Meta-analysis of genome-wide association studies for loin muscle area and loin muscle depth in two Duroc pig populations

Loin muscle area (LMA) and loin muscle depth (LMD) are important traits influencing the production performance of breeding pigs. However, the genetic architecture of these two traits is still poorly understood. To discern the genetic architecture of LMA and LMD, a material consisting of 6043 Duroc pigs belonging to two populations with different genetic backgrounds was collected and applied in genome-wide association studies (GWAS) with a genome-wide distributed panel of 50K single nucleotide polymorphisms (SNPs). To improve the power of detection for common SNPs, we conducted a meta-analysis in these two pig populations and uncovered additional significant SNPs. As a result, we identified 75 significant SNPs for LMA and LMD on SSC6, 7, 12, 16, and 18. Among them, 25 common SNPs were associated with LMA and LMD. One pleiotropic quantitative trait locus (QTL), which was located on SSC7 with a 283 kb interval, was identified to affect LMA and LMD. Marker ALGA0040260 is a key SNP for this QTL, explained 1.77% and 2.48% of the phenotypic variance for LMA and LMD, respectively. Another genetic region on SSC16 (709 kb) was detected and displayed prominent association with LMA and the peak SNP, WU_10.2_16_35829257, contributed 1.83% of the phenotypic variance for LMA. Further bioinformatics analysis determined eight promising candidate genes (GCLC, GPX8, DAXX, FGF21, TAF11, SPDEF, NUDT3, and PACSIN1) with functions in glutathione metabolism, adipose and muscle tissues development and lipid metabolism. This study provides the first GWAS for the LMA and LMD of Duroc breed to analyze the underlying genetic variants through a large sample size. The findings further advance our understanding and help elucidate the genetic architecture of LMA, LMD and growth-related traits in pigs.

Genome-Wide Profiling of the Microrna Transcriptome Regulatory Network to Identify Putative Candidate Genes Associated with Backfat Deposition in Pigs

Simple Summary

Backfat thickness is an important characteristic in pig breeding. In this study, the key microRNAs (miRNAs) and genes associated with pig backfat deposition were detected and characterized using RNA sequencing between adipose tissues of high-backfat and low-backfat pigs. Strong candidate mRNA‒miRNA interaction pairs were identified to affect backfat deposition through the regulation of target genes by miRNAs. These results provide novel insights into the backfat deposition mechanism in pigs.

Abstract

Backfat deposition is strongly related to carcass traits, growth rate, feed conversion rate, and reproductive performance in pig production. To understand the molecular mechanisms underlying porcine backfat thickness phenotypes, transcriptome and miRNA profiling of backfat from high-backfat thickness and low-backfat thickness pigs were performed by RNA sequencing. Twenty genes encoding for miRNAs and 126 genes encoding for protein-coding genes were found to be differentially expressed between the two libraries. After integrative analysis of DEMs targets and DEGs, a total of 33 mRNA‒miRNA interaction pairs were identified, and the regulatory networks of these pairs were determined. Among these genes, five (AQP9, DKK3, GLYCTK, GLIPR1, and DUSP2) related to fat deposition were found to be strong candidate genes, and mir-31-5p/AQP9 and mir-31-5p/GLIPR1 may play important roles in fat deposition. Additionally, potential adipogenesis-related genes and miRNAs were identified. These findings improve the current understanding of the molecular genetic mechanisms of subcutaneous fat deposition in pigs and provide a foundation for further studies.

Identifying SNPs and candidate genes for three litter traits using single-step GWAS across six parities in Landrace and Large White pigs

Total number born (TNB), number born alive (NBA), and litter weight born alive (LWB) are critically important traits in pig production. The sow's parity is one of the major factors influencing litter traits. Because of monogenic or polygenic contributions and the presence of temporal gene effects in different sows' parities, it is difficult to clarify the biological and genetic background. To systematically explore the genetic mechanism of litter traits, we conducted 18 GWASs using single-step GWAS (ssGWAS) based on two breeds (908 Landrace and 1,130 Large White sow litter records) for each litter trait in different parities. A total of 300 Landrace and 300 Large White sows were genotyped by sequencing (GBS). ssGWAS was performed separately for each breed and each parity due to population stratification and temporal gene effect. In summary, we identified 80 (15 for Landrace and 65 for Large White), 227 (52 for Landrace, 175 for Large White), and 187 (34 for Landrace, 153 for Large White) single nucleotide polymorphisms (SNPs) affecting TNB, NBA, and LWB, respectively. Of them, we suggest that a total of 22 loci (SSC1: 125098202, SSC1: 117560058, SSC14: 147794697, SSC8: 84823302, SSC9: 143554876, and SSC9: 138766097 for Landrace; SSC1: 4023577, SSC1: 3859573, SSC1: 4891063, SSC16: 5197665, SSC10: 32050819, SSC13: 13552924, SSC13: 92819, SSC17: 3579607, SSC13: 196698221, SSC7: 30918403, SSC16: 46221484, SSC16: 46169204, SSC2: 41988642, SSC2: 44475457, SSC2: 42521875, and SSC7: 58411951 for Large White) are shared by TNB, NBA, and LWB. These results indicate the existence of gene temporal effect in each parity. Furthermore, our findings suggest four interesting candidate genes (FBXL7, ALDH1A2, LEPR, and DDX1) associated with litter traits in different parities that have a major effect on embryonic development progression. In conclusion, 22 crucial SNPs and four interesting candidate genes were identified for three litter traits across six parities. These findings advance our understanding of the genetic architecture of litter traits and confirm the presence of temporal gene effects in different parities. Importantly, functional validation studies for findings of particular interest are recommended in litter traits.

Differences in gene expression profiles for subcutaneous adipose, liver, and skeletal muscle tissues between Meishan and Landrace pigs with different backfat thicknesses

Backfat thickness is one of the most important traits of commercially raised pigs. Meishan pigs are renowned for having thicker backfat than Landrace pigs. To examine the genetic factors responsible for the differences, we first produced female crossbred pig lines by mating Landrace (L) × Large White (W) × Duroc (D) females (LWD) with Landrace (L) or Meishan (M) boars (i.e., LWD × L = LWDL for Landrace offspring and LWD × M = LWDM for the Meishan offspring). We confirmed that LWDM pigs indeed had a thicker backfat than LWDL pigs. Next, we performed gene expression microarray analysis in both genetic lines to examine differentially expressed genes (DEGs) in energy metabolism-related tissues, subcutaneous adipose (fat), liver, and longissimus dorsi muscle tissues. We analyzed the annotation of DEGs (2-fold cutoff) to functionally categorize them by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways. The number of DEGs in muscle tissues of both lines was much less than that in fat and liver tissues, indicating that DEGs in muscle tissues may not contribute much to differences in backfat thickness. In contrast, several genes related to muscle (in fat tissue) and lipid metabolism (in liver tissue) were more upregulated in LWDM pigs than LWDL pigs, indicating that those DEGs might be responsible for differences in backfat thickness. The different genome-wide gene expression profiles in the fat, liver, and muscle tissues between genetic lines can provide useful information for pig breeders.

Genetic Architecture of Feeding Behavior and Feed Efficiency in a Duroc Pig Population

Increasing feed efficiency is a major goal of breeders as it can reduce production cost and energy consumption. However, the genetic architecture of feeding behavior and feed efficiency traits remains elusive. To investigate the genetic architecture of feed efficiency in pigs, three feeding behavior traits (daily feed intake, number of daily visits to feeder, and duration of each visit) and two feed efficiency traits (feed conversion ratio and residual feed intake) were considered. We performed genome-wide association studies (GWASs) of the five traits using a population of 1,008 Duroc pigs genotyped with an Illumina Porcine SNP50K BeadChip. A total of 9 genome-wide (P < 1.54E-06) and 35 suggestive (P < 3.08E-05) single nucleotide polymorphisms (SNPs) were detected. Two pleiotropic quantitative trait loci (QTLs) on SSC 1 and SSC 7 were found to affect more than one trait. Markers WU_10.2_7_18377044 and DRGA0001676 are two key SNPs for these two pleiotropic QTLs. Marker WU_10.2_7_18377044 on SSC 7 contributed 2.16 and 2.37% of the observed phenotypic variance for DFI and RFI, respectively. The other SNP DRGA0001676 on SSC 1 explained 3.22 and 5.46% of the observed phenotypic variance for FCR and RFI, respectively. Finally, functions of candidate genes and gene set enrichment analysis indicate that most of the significant pathways are associated with hormonal and digestive gland secretion during feeding. This study advances our understanding of the genetic mechanisms of feeding behavior and feed efficiency traits and provide an opportunity for increasing feeding efficiency using marker-assisted selection or genomic selection in pigs.

Transcriptome analysis reveals differential gene expression in intramuscular adipose tissues of Jinhua and Landrace pigs

Meat is a rich source of protein, fatty acids and carbohydrates for human needs. In addition to necessary nutrients, high fat contents in pork increase the tenderness and juiciness of the meat, featuring diverse application in various dishes. This study investigated the transcriptomic profiles of intramuscular adipose tissues in Jinhua and Landrace pigs by employing advanced RNA sequencing. Results showed significant interesting to note that there were significant differences in the expression of genes. 1,632 genes showed significant differential expression, 837 genes were up-regulated and 195 genes were down-regulated. Variations in genes responsible for cell aggregation, extracellular matrix formation, cellular lipid catabolic process, and fatty acid binding strongly supported that both pig breeds feature variable fat and muscle metabolism. Certain differentially expressed genes are included in the pathway of mitogen-activated protein kinase signaling pathway, Ras signaling pathway and insulin pathway. Results from real-time quantitative polymerase chain reaction also validated the differential expression of 17 mRNAs between meats of the two pig breeds. Overall, these findings reveal significant differences in fat and protein metabolism of intramuscular adipose tissues of two pig breeds at the transcriptomic level and suggest diversification at the genetic level between breeds of the same species.

Genome-Wide Association Study of Piglet Uniformity and Farrowing Interval

Piglet uniformity (PU) and farrowing interval (FI) are important reproductive traits related to production and economic profits in the pig industry. However, the genetic architecture of the longitudinal trends of reproductive traits still remains elusive. Herein, we performed a genome-wide association study (GWAS) to detect potential genetic variation and candidate genes underlying the phenotypic records at different parities for PU and FI in a population of 884 Large White pigs. In total, 12 significant SNPs were detected on SSC1, 3, 4, 9, and 14, which collectively explained 1–1.79% of the phenotypic variance for PU from parity 1 to 4, and 2.58–4.11% for FI at different stages. Of these, seven SNPs were located within 16 QTL regions related to swine reproductive traits. One QTL region was associated with birth body weight (related to PU) and contained the peak SNP MARC0040730, and another was associated with plasma FSH concentration (related to FI) and contained the SNP MARC0031325. Finally, some positional candidate genes for PU and FI were identified because of their roles in prenatal skeletal muscle development, fetal energy substrate, pre-implantation, and the expression of mammary gland epithelium. Identification of novel variants and candidate genes will greatly advance our understanding of the genetic mechanisms of PU and FI, and suggest a specific opportunity for improving marker assisted selection or genomic selection in pigs.

Differentially expressed genes in the caecal and colonic mucosa of Landrace finishing pigs with high and low food conversion ratios

The feed conversion ratio (FCR) is an essential economic trait for pig production, and is directly related to feed efficiency. Studies identifying the differential expression of functional genes involved in biological and molecular mechanisms in the intestine in relation to growth performance are rare. In this study, RNA-Seq was used to identify transcriptomes in caecal and colonic mucosal tissues in order to determine the differential expression of genes from two full-sibling pairs and two half-sibling pairs of Landrace finishing pigs with opposing FCR phenotypes. In total, 138 (comparison of high and low FCR in caecal mucosa), 64 (comparison of high and low FCR in colonic mucosa), and 165 (contrast between the caecal and colonic mucosa) differentially expressed genes were identified. Some of these genes were functionally related to energy and lipid metabolism, particularly short chain fatty acids metabolism, as well as gastrointestinal peristalsis and ion transport. Functional annotation were performed to identify differentially expressed genes, such as GUCA2A, GUCA2B, HSP70.2, NOS2, PCK1, SLCs, and CYPs, which may positively influence feed efficiency in Landrace pigs. These differentially expressed genes need to be further tested for candidate genes that are related to feed efficiency.

Dynamic transcriptome and DNA methylome analyses on longissimus dorsi to identify genes underlying intramuscular fat content in pigs

Background

The intramuscular fat content (IMF) refers to the amount of fat within muscles, including the sum of phospholipids mainly found in cell membranes, triglycerides and cholesterol, and is determined both by hyperplasia and hypertrophy of adipocyte during the development of pigs. The IMF content is an important economic trait that is genetically controlled by multiple genes. The Laiwu pig is an indigenous fatty pig breed distributed in North China, characterized by excessively higher level of IMF content (9%~12%), therefore, is suitable for the identification of genes controlling IMF variations. To identify genes underlying IMF deposition, we performed genome-wide transcriptome and methylome analyses on longissimus dorsi (LD) muscle in Laiwu pigs across four developmental stages.

Results

A total of 22,524 expressed genes were detected and 1158 differentially expressed genes (DEGs) were hierarchically clustered in the LD muscle over four developmental stages from 60 d to 400 d. These genes were significantly clustered into four temporal expression profiles, and genes participating in fat cell differentiation and lipid biosynthesis processes were identified. From 120 d to 240 d, the period with the maximum IMF deposition rate, the lipid biosynthesis related genes (FOSL1, FAM213B and G0S2), transcription factors (TFs) (EGR1, KLF5, SREBF2, TP53 and TWIST1) and enriched pathways (steroid biosynthesis and fatty acid biosynthesis) were revealed; and fat biosynthesis relevant genes showing differences in DNA methylation in gene body or intergenic region were detected, such as FASN, PVALB, ID2, SH3PXD2B and EGR1.

Conclusions

This study provides a comprehensive landscape of transcriptome of the LD muscle in Laiwu pigs ranging from 60 to 400 days old, and methylome of the LD muscle in 120 d and 240 d Laiwu pigs. A set of candidate genes and TFs involved in fat biosynthesis process were identified, which were probably responsible for IMF deposition. The results from this study would provide a reference for the identification of genes controlling IMF variation, and for exploring molecular mechanisms underlying IMF deposition in pigs.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4201-9) contains supplementary material, which is available to authorized users.

Differential regulation of mRNAs and lncRNAs related to lipid metabolism in two pig breeds

Long non-coding RNAs (lncRNAs) can regulate lipid metabolism and adipogenesis. However, there is little research on the role of lncRNAs in fat deposition in pig. In this study, RNA-seq technology was used to analyze the gene expression profiles of subcutaneous adipose tissue in Laiwu (LW) and Large White (LY) pigs. Then, key lncRNAs and genes associated with lipid metabolism and adipogenic differentiation were identified. Fifty four lncRNAs and 482 known mRNAs were differentially expressed in the two pig breeds. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses revealed that differentially expressed genes and the target genes of differentially expressed lncRNAs were significantly enriched in PPAR signaling pathway and biological processes including fat cell differentiation and fatty acid metabolism. Key lncRNAs might regulate adipogenic differentiation and fatty acid metabolism by regulating genes involved in above signaling pathway and biological processes. Specifically, XLOC_014379, XLOC_011279, XLOC_064871, XLOC_019518 and XLOC_013639 might target SCD, LPIN1, TRIB3, EGR2 and FABP3, respectively, and then play critical regulatory role. These results are useful for understanding fat deposition in pig, breeding livestock with high quality meat, and preventing and treating lipid metabolic disease.

Transcriptomic profiling in muscle and adipose tissue identifies genes related to growth and lipid deposition

Growth performance and meat quality are important traits for the pig industry and consumers. Adipose tissue is the main site at which fat storage and fatty acid synthesis occur. Therefore, we combined high-throughput transcriptomic sequencing in adipose and muscle tissues with the quantification of corresponding phenotypic features using seven Chinese indigenous pig breeds and one Western commercial breed (Yorkshire). We obtained data on 101 phenotypic traits, from which principal component analysis distinguished two groups: one associated with the Chinese breeds and one with Yorkshire. The numbers of differentially expressed genes between all Chinese breeds and Yorkshire were shown to be 673 and 1056 in adipose and muscle tissues, respectively. Functional enrichment analysis revealed that these genes are associated with biological functions and canonical pathways related to oxidoreductase activity, immune response, and metabolic process. Weighted gene coexpression network analysis found more coexpression modules significantly correlated with the measured phenotypic traits in adipose than in muscle, indicating that adipose regulates meat and carcass quality. Using the combination of differential expression, QTL information, gene significance, and module hub genes, we identified a large number of candidate genes potentially related to economically important traits in pig, which should help us improve meat production and quality.

Metagenomic Analysis of Cecal Microbiome Identified Microbiota and Functional Capacities Associated with Feed Efficiency in Landrace Finishing Pigs

Feed efficiency (FE) appears to vary even within closely related pigs, and may be partly affected by the diversity in the composition and function of gut microbes. To investigate the components and functional differences of gut microbiota of low and high FE pigs, high throughput sequencing and de novo metagenomics were performed on pig cecal contents. Pigs were selected in pairs with low and high feed conversion ratio. The microorganisms of individuals with different FE were clustered according to diversity. The genus Prevotella was the most enriched in both groups, and the abundance of species Prevotella sp. CAG:604 was significantly increased in low efficiency individuals compared to that in animals showing high efficiency. In contrast, other differential species, including lactic acid bacteria, were all enriched in the group with good feeding characteristics. Functional analysis based on the Kyoto Encyclopedia of Genes and Genomes databases demonstrated that differential genes for the metabolism of carbohydrates were most abundant in both groups, but pathways of pyruvate-related metabolism were more intense in pigs with higher FE. All these data indicated that the microbial environment was closely related to the growth traits of pigs, and regulating microbial composition could aid developing strategies to improve FE for pigs.

The comprehensive liver transcriptome of two cattle breeds with different intramuscular fat content

Intramuscular fat (IMF) content is an important determinant factor of meat quality in cattle. There is significant difference in IMF content between Jinnan and Simmental cattle. Here, to identify candidate genes and networks associated with IMF deposition, we deeply explored the transcriptome architecture of liver in these two cattle breeds. We sequenced the liver transcriptome of five Jinnan and three Simmental cattle, yielding about 413.9 million sequencing reads. 124 differentially expressed genes (DEGs) were detected, of which 53 were up-regulated and 71 were down-regulated in Jinnan cattle. 1282 potentially novel genes were also identified. Gene ontology analysis revealed these DEGs (including CYP21A2, PC, ACACB, APOA1, and FADS2) were significantly enriched in lipid biosynthetic process, regulation of cholesterol esterification, reverse cholesterol transport, and regulation of lipoprotein lipase activity. Genes involved in pyruvate metabolism pathway were also significantly overrepresented. Moreover, we identified an interaction network which related to lipid metabolism, which might be contributed to the IMF deposition in cattle. We concluded that the DEGs involved in the regulation of lipid metabolism could play an important role in IMF deposition. Overall, we proposed a new panel of candidate genes and interaction networks that can be associated with IMF deposition and used as biomarkers in cattle breeding.

Integrating genome and transcriptome profiling for elucidating the mechanism of muscle growth and lipid deposition in Pekin ducks

Muscle growth and lipid deposition are co-ordinately regulated processes. Cherry Valley Pekin duck is a lean-type duck breed with high growth rate, whereas the native Pekin duck of China has high lipid deposition. Phenotypic analysis showed that native Pekin ducks have smaller fibre diameter and larger density in the breast muscle at 3 weeks of age and higher intramuscular fat content at 6 weeks of age than those in Cherry Valley Pekin ducks. We detected 17 positively selected genes (PSGs) by comparing genes mainly involved with muscle organ development, muscle contraction, peroxisome proliferator activated receptor signalling pathway, and fatty acid metabolism. In all, 52 and 206 differentially expressed genes (DEGs) were identified in transcriptomic comparisons between the two breeds at 3 and 6 weeks of age, respectively, which could potentially affect muscle growth and lipid deposition. Based on the integration of PSGs and DEGs and their functional annotations, we found that 11 and 10 genes were correlated with muscle growth and lipid deposition, respectively. Identification of candidate genes controlling quantitative traits of duck muscle might aid in elucidating the mechanisms of muscle growth and lipid deposition and could help in improving duck breeding.

Transcriptome analyses of differential gene expression in the bursa of Fabricius between Silky Fowl and White Leghorn

Hyperpigmentation in Silky Fowl (SF) results in aberrant immune cell development. However, how melanocytes regulate B-cell proliferation in the bursa of Fabricius (BF) is unclear. To resolve this conundrum, we collected BFs from three-week-old SF and White Leghorn (WL) female chickens for RNA sequencing. The BF development was relatively weaker in SF than in WL. The transcriptome analyses identified 4848 differentially expressed genes, 326 long noncoding RNAs (lncRNAs), and 67 microRNAs in the BF of SF. The genes associated with melanogenesis was significantly higher, but that of the genes associated with the cytokine-cytokine receptor interactions and JAK-STAT signalling pathway was significantly lower in SF than in WL. Crucial biological processes, such as the receptor activity, cell communication, and cellular responses to stimuli, were clustered in SF. The predicted target lncRNAs genes were mainly associated with cell proliferation pathways such as JAK-STAT, WNT, MAPK, and Notch signalling pathways. Except for the above pathways, the target microRNA genes were related to the metabolism, melanogenesis, autophagy, and NOD-like and Toll-like receptor signalling pathways. The lncRNAs and microRNAs were predicted to regulate the JAK2, STAT3, and IL-15 genes. Thus, B-cell development in the BF of SF might be regulated and affected by noncoding RNAs.