Transcriptional analysis of intramuscular fatty acid composition in the longissimus thoracis muscle of Iberian × Landrace back-crossed pigs

Identification of population-informative markers from high-density genotyping data through combined feature selection and machine learning algorithms: Application to European autochthonous and cosmopolitan pig breeds

Large genotyping datasets, obtained from high-density single nucleotide polymorphism (SNP) arrays, developed for different livestock species, can be used to describe and differentiate breeds or populations. To identify the most discriminating genetic markers among thousands of genotyped SNPs, a few statistical approaches have been proposed. In this study, we applied the Boruta algorithm, a wrapper of the machine learning random forest algorithm, on a database of 23 European pig breeds (20 autochthonous and three cosmopolitan breeds) genotyped with a 70k SNP chip, to pre-select informative SNPs. To identify different sets of SNPs, these pre-selected markers were then ranked with random forest based on their mean decrease accuracy and mean decrease gene indexes. We evaluated the efficiency of these subsets for breed classification and the usefulness of this approach to detect candidate genes affecting breed-specific phenotypes and relevant production traits that might differ among breeds. The lowest overall classification error (2.3%) was reached with a subpanel including only 398 SNPs (ranked based on their mean decrease accuracy), with no classification error in seven breeds using up to 49 SNPs. Several SNPs of these selected subpanels were in genomic regions in which previous studies had identified signatures of selection or genes associated with morphological or production traits that distinguish the analysed breeds. Therefore, even if these approaches have not been originally designed to identify signatures of selection, the obtained results showed that they could potentially be useful for this purpose.

Integrating genome-wide association study with RNA-seq revealed DBI as a good candidate gene for intramuscular fat content in Beijing black pigs

Increasing intramuscular fat (IMF) content can enhance the sensory quality of meat, including tenderness, juiciness, flavor, and color. Genome-wide association study and RNA-sequencing (RNA-seq) analysis were used to identify candidate IMF genes in Beijing Black pigs, a popular species among consumers in northern China. Two and three single nucleotide polymorphisms were significantly associated with IMF in SSC13 and SSC15 respectively. Solute carrier family 4 member 7 (SLC4A7) on SSC13 and insulin induced gene 2 (INSIG2), coiled-coil domain containing 93 (CCDC93), and diazepam binding inhibitor acyl-CoA binding protein (DBI) on SSC15 are good candidate genes in this population. Furthermore, RNA-seq analysis was performed between high and low IMF groups, and 534 differentially expressed genes were identified. In addition, based on differentially expressed genes, Kyoto Encyclopedia of Genes and Genomes analysis revealed that peroxisome proliferator-activated receptors and FoxO signaling pathway pathways might contribute to IMF. Moreover, the DBI gene was identified as a candidate for IMF both by genome-wide association study and RNA-seq analysis, suggesting that it might be a crucial candidate gene for influencing IMF in Beijing Black pigs.

Exploring the growth trait molecular markers in two sheep breeds based on Genome-wide association analysis

Growth traits are quantitative traits controlled by multiple micro-effect genes. we identified molecular markers related to sheep growth traits, which formed the basis of molecular breeding. In this study, we randomly selected 100 Qira Black sheep and 84 German Merino sheep for the blood collection the jugular vein to genotype by using the Illumina Ovine SNP 50K Bead Chip. quality control criteria for statistical analysis were: rejection detection rate < 90% and minimum allele frequency (MAF) < 5%. Then, we performed Genome-wide association studies (GWAS) on sheep body weight, body height, body length, and chest circumference using mixed linear models. After getting 55 SNPs with significant correlation, they were annotated by reference genome of Ovis aries genome (Oar_v4.0) and We obtained a total of 84 candidate genes associated with production traits (BMPR1B, HSD17B3, TMEM63C, etc.). We selected BMPR1B for population validation and found a correlation between the FecB locus and body weight traits. Therefore, this study not only supplements the existing knowledge of molecular markers of sheep growth traits, but also has important theoretical significance and reference value for the mining of functional genes of sheep growth traits.

Transcriptome Analysis of Bovine Rumen Tissue in Three Developmental Stages

Rumen development is a crucial physiological challenge for ruminants. However, the molecular mechanism regulating rumen development has not been clearly elucidated. In this study, we investigated genes involved in rumen development in 13 rumen tissues from three developmental stages (birth, youth, and adult) using RNA sequencing. We identified that 6,048 genes were differentially expressed among three developmental stages. Using weighted correlation network analysis, we found that 12 modules were significantly associated with developmental stages. Functional annotation and protein–protein interaction (PPI) network analysis revealed that CCNB1, CCNB2, IGF1, IGF2, HMGCL, BDH1, ACAT1, HMGCS2, and CREBBP involved in rumen development. Integrated transcriptome with GWAS information of carcass weight (CW), stomach weight (SW), marbling score (MS), backfat thickness (BFT), ribeye area (REA), and lean meat weight (LMW), we found that upregulated DEGs (fold change 0∼1) in birth–youth comparison were significantly enriched with GWAS signals of MS, downregulated DEGs (fold change >3) were significantly enriched with GWAS signals of SW, and fold change 0∼1 up/downregulated DEGs in birth–adult comparison were significantly enriched with GWAS signals of CW, LMW, REA, and BFT. Furthermore, we found that GWAS signals for CW, LMW, and REA were enriched in turquoise module, and GWAS signals for CW was enriched in lightgreen module. Our study provides novel insights into the molecular mechanism underlying rumen development in cattle and highlights an integrative analysis for illustrating the genetic architecture of beef complex traits.

Trait correlated expression combined with eQTL and ASE analyses identified novel candidate genes affecting intramuscular fat

BACKGROUND

Intramuscular fat (IMF) content is a determining factor for meat taste. The Luchuan pig is a fat-type local breed in southern China that is famous for its desirable meat quality due to high IMF, however, the crossbred offspring of Luchuan sows and Duroc boars displayed within-population variation on meat quality, and the reason remains unknown.

RESULTS

In the present study, we identified 212 IMF-correlated genes (FDR ≤ 0.01) using correlation analysis between gene expression level and the value of IMF content. The IMF-correlated genes were significantly enriched in the processes of lipid metabolism and mitochondrial energy metabolism, as well as the AMPK/PPAR signaling pathway. From the IMF-correlated genes, we identified 99 genes associated with expression quantitative trait locus (eQTL) or allele-specific expression (ASE) signals, including 21 genes identified by both cis-eQTL and ASE analyses and 12 genes identified by trans-eQTL analysis. Genome-wide association study (GWAS) of IMF identified a significant QTL on SSC14 (p-value = 2.51E^-7), and the nearest IMF-correlated gene SFXN4 (r = 0.28, FDR = 4.00E^-4) was proposed as the candidate gene. Furthermore, we highlighted another three novel IMF candidate genes, namely AGT, EMG1, and PCTP, by integrated analysis of GWAS, eQTL, and IMF-gene correlation analysis.

CONCLUSIONS

The AMPK/PPAR signaling pathway together with the processes of lipid and mitochondrial energy metabolism plays a vital role in regulating porcine IMF content. Trait correlated expression combined with eQTL and ASE analysis highlighted a priority list of genes, which compensated for the shortcoming of GWAS, thereby accelerating the mining of causal genes of IMF.

Comparative Transcriptome Profile between Iberian Pig Varieties Provides New Insights into Their Distinct Fat Deposition and Fatty Acids Content

The high deposition of intramuscular fat and the content of oleic fatty acid are characteristic of the Iberian pig. These two parameters present great variability and are differentiated amongst the varieties that make up the Iberian pig population. Although previous studies generated evidence for causal genes and polymorphisms associated to the adipogenic potential of the Iberian pig, there is little information about how genetic expression influences this trait's variability. The aim of this study was to analyses the expression profile between two varieties of Iberian pig (Torbiscal and Retinto) and their reciprocal crosses differentiated in their intramuscular fat (IMF) content and fatty acid (FA) composition in the Longissimus thoracis muscle using an RNA-seq approach. Our results corroborate that the Retinto variety is the fattiest amongst all studied varieties as its upregulated genes, such as FABP3 and FABP5, SLC27A1 and VEGFA among others, contribute to increasing adiposity. In its turn, Torbiscal pigs showed an upregulation of genes associated with the inhibition of fat deposition such as ADIPOQ and CPT1A. Further genetic variation analysis in these Iberian varieties showed relevant associations for SNP located within the differentially expressed genes with IMF and FA content. Thus, the differences found in the genetic architecture and the muscle transcriptome of these Iberian varieties might explain the variability in their fat content and composition and hence, their meat quality.

Comparison of Growth Performance and Meat Quality Traits of Commercial Cross-Bred Pigs versus the Large Black Pig Breed

The meat quality of different pig breeds is associated with their different muscle tissue physiological processes, which involves a large variety of genes related with muscle fat and energy metabolism. Understanding the differences of biological processes of muscle after slaughter is helpful to reveal the meat quality development of different breeds. Therefore, eight native Large Black pigs (BP), with high fat content in meat, and seven cross-bred commercial pigs (CP), which had a high feed efficiency with high lean meat, were used to investigate the differences in their meat quality and RNA transcriptomes. The average daily gain (ADG) and hot carcass weight (HCW) of CP were higher than BP, but the back-fat thickness of BP was higher than CP (p < 0.05). The CP had higher a* (redness) but lower h (hue angle) than BP (p < 0.05). The metmyoglobin (MMb) percentage of CP was higher (p < 0.05) than BP. The fat content and oxygen consumption of longissimus dorsi (LD) muscles in BP were higher (p < 0.05) than CP. BP had higher monounsaturated fatty acids (MUFA) content, but CP had higher polyunsaturated fatty acids (PUFA) content (p < 0.05). The RNA-seq data highlighted 201 genes differentially expressed between the two groups (corrected false discovery rate (FDR) p < 0.05), with 75 up-regulated and 126 down-regulated genes in BP compared with CP using the fold change (FC). The real-time PCR was used to validate the results of RNA-seq for eight genes, and the genes related to lipid and energy metabolism were highly expressed in BP (p < 0.05). Based on the results, BP had superior intramuscular fat content to CP, while the growth performance of CP was better, and the transcriptomic differences between these two groups of pigs may cause the meat quality and growth performance variance.

Dynamic accumulation of fatty acids in duck (Anas platyrhynchos) breast muscle and its correlations with gene expression

Background

Fatty acid composition contributes greatly to the quality and nutritional value of meat. However, the molecular regulatory mechanisms underlying fatty acid accumulation in poultry have not yet been cleared. The aims of this study were to characterize the dynamics of fatty acid accumulation in duck breast muscle and investigate its correlations with gene expression.

Results

Here, we analyzed the fatty acid profile and transcriptome of breast muscle derived from Pekin ducks and mallards at the ages of 2 weeks, 4 weeks, 6 weeks and 8 weeks. Twenty fatty acids were detected in duck breast muscle, with palmitic acid (C16:0, 16.6%~ 21.1%), stearic acid (C18:0, 9.8%~ 17.7%), oleic acid (C18:1n-9, 15.7%~ 33.8%), linoleic acid (C18:2n-6, 10.8%~ 18.9%) and arachidonic acid (C20:4n-6, 11.7%~ 28.9%) as the major fatty acids. Our results showed that fatty acid composition was similar between the two breeds before 6 weeks, but the compositions diverged greatly after this point, mainly due to the stronger capacity for C16:0 and C18:1n-9 deposition in Pekin ducks. By comparing the multistage transcriptomes of Pekin ducks and mallards, we identified 2025 differentially expressed genes (DEGs). Cluster analysis of these DEGs revealed that the genes involved in oxidative phosphorylation, fatty acid degradation and the PPAR signaling pathway were upregulated in mallard at 8 weeks. Moreover, correlation analysis of the DEGs and fatty acid composition traits suggested that the DEGs involved in lipogenesis, lipolysis and fatty acid β-oxidation may interact to influence the deposition of fatty acids in duck breast muscle.

Conclusions

We reported the temporal progression of fatty acid accumulation and the dynamics of the transcriptome in breast muscle of Pekin ducks and mallards. Our results provide insights into the transcriptome regulation of fatty acid accumulation in duck breast muscle, and will facilitate improvements of fatty acid composition in duck breeding.

Longissimus dorsi muscle transcriptomic analysis of Yunling and Chinese simmental cattle differing in intramuscular fat content and fatty acid composition

Intramuscular fat (IMF) content and fatty acid (FA) composition vary significantly across beef cattle breeds, which play an important role in taste and nutritional value. However, the molecular mechanisms underlying these phenotypic differences remain unknown. The present study compared meat quality traits between Yunling cattle and Chinese Simmental cattle. Yunling cattle showed a lower IMF content and proportion of monounsaturated fatty acids (MUFA), as well as higher proportions of saturated fatty acids (SFA), polyunsaturated fatty acids (PUFA), and short-chain fatty acids (sc-FA) in the longissimus dorsi (LD) muscle than Chinese Simmental cattle. To further identify the candidate genes and pathways responsible for these phenotypic differences, the transcriptome of LD muscle from the two breeds were measured using RNA-seq. A total of 1347 differentially expressed genes were identified. The major metabolic pathways that were differentially modulated were lipolysis and glycometabolism. Yunling cattle showed a higher expression of lipolysis genes (ALDH9A1, ACSL5, ACADM, ACAT2, ACOT2) and a lower expression of genes related to glycometabolism (PGM1, GALM, PGM1, GPI, LDHA). This research identified candidate genes and pathways for IMF content and FA composition in the LD muscle of beef cattle, which may facilitate the design of new selection strategies to improve meat quality.

Deciphering the regulation of porcine genes influencing growth, fatness and yield-related traits through genetical genomics

Genetical genomics approaches aim at identifying quantitative trait loci for molecular traits, also known as intermediate phenotypes, such as gene expression, that could link variation in genetic information to physiological traits. In the current study, an expression GWAS has been carried out on an experimental Iberian × Landrace backcross in order to identify the genomic regions regulating the gene expression of those genes whose expression is correlated with growth, fat deposition, and premium cut yield measures in pig. The analyses were conducted exploiting Porcine 60K SNP BeadChip genotypes and Porcine Expression Microarray data hybridized on mRNA from Longissimus dorsi muscle. In order to focus the analysis on productive traits and reduce the number of analyses, only those probesets whose expression showed significant correlation with at least one of the seven phenotypes of interest were selected for the eGWAS. A total of 63 eQTL regions were identified with effects on 36 different transcripts. Those eQTLs overlapping with phenotypic QTLs on SSC4, SSC9, SSC13, and SSC17 chromosomes previously detected in the same animal material were further analyzed. Moreover, candidate genes and SNPs were analyzed. Among the most promising results, a long non-coding RNA, ALDBSSCG0000001928, was identified, whose expression is correlated with premium cut yield. Association analysis and in silico sequence domain annotation support TXNRD3 polymorphisms as candidate to regulate ALDBSSCG0000001928 expression, which can be involved in the transcriptional regulation of surrounding genes, affecting productive and meat quality traits.

The application of transcriptomic data in the authentication of beef derived from contrasting production systems

BACKGROUND

Differences between cattle production systems can influence the nutritional and sensory characteristics of beef, in particular its fatty acid (FA) composition. As beef products derived from pasture-based systems can demand a higher premium from consumers, there is a need to understand the biological characteristics of pasture produced meat and subsequently to develop methods of authentication for these products. Here, we describe an approach to authentication that focuses on differences in the transcriptomic profile of muscle from animals finished in different systems of production of practical relevance to the Irish beef industry. The objectives of this study were to identify a panel of differentially expressed (DE) genes/networks in the muscle of cattle raised outdoors on pasture compared to animals raised indoors on a concentrate based diet and to subsequently identify an optimum panel which can classify the meat based on a production system.

RESULTS

A comparison of the muscle transcriptome of outdoor/pasture-fed and Indoor/concentrate-fed cattle resulted in the identification of 26 DE genes. Functional analysis of these genes identified two significant networks (1: Energy Production, Lipid Metabolism, Small Molecule Biochemistry; and 2: Lipid Metabolism, Molecular Transport, Small Molecule Biochemistry), both of which are involved in FA metabolism. The expression of selected up-regulated genes in the outdoor/pasture-fed animals correlated positively with the total n-3 FA content of the muscle. The pathway and network analysis of the DE genes indicate that peroxisome proliferator-activated receptor (PPAR) and FYN/AMPK could be implicit in the regulation of these alterations to the lipid profile. In terms of authentication, the expression profile of three DE genes (ALAD, EIF4EBP1 and NPNT) could almost completely separate the samples based on production system (95 % authentication for animals on pasture-based and 100 % for animals on concentrate- based diet) in this context.

CONCLUSIONS

The majority of DE genes between muscle of the outdoor/pasture-fed and concentrate-fed cattle were related to lipid metabolism and in particular β-oxidation. In this experiment the combined expression profiles of ALAD, EIF4EBP1 and NPNT were optimal in classifying the muscle transcriptome based on production system. Given the overall lack of comparable studies and variable concordance with those that do exist, the use of transcriptomic data in authenticating production systems requires more exploration across a range of contexts and breeds.

Longissimus dorsi transcriptome analysis of purebred and crossbred Iberian pigs differing in muscle characteristics

BACKGROUND

The two main genetic types in Iberian pig production show important phenotypic differences in growth, fattening and tissue composition since early developmental stages. The objective of this work was the evaluation of muscle transcriptome profile in piglets of both genetic types, in order to identify genes, pathways and regulatory factors responsible for their phenotypic differences. Contemporary families coming from pure Iberian pigs (IB) or from crossing with Duroc boars (DU×IB) were generated. Piglets (14 from each genetic type) were slaughtered at weaning (28 days) and longissimus dorsi was sampled for composition and gene expression studies. RNA was obtained and hybridized to Affymetrix Porcine Genechip expression arrays.

RESULTS

Loin muscle chemical composition showed significant differences between genetic types in intramuscular fat content (6.1% vs. 4.3% in IB and DUxIB animals, respectively, P = 0.009) and in saturated (P = 0.019) and monounsaturated fatty acid proportions (P = 0.044). The statistical analysis of gene expression data allowed the identification of 256 differentially expressed (DE) genes between genetic types (FDR < 0.10), 102 upregulated in IB and 154 upregulated in DU×IB. Transcript differences were validated for a subset of DE genes by qPCR. We observed alteration in biological functions related to extracellular matrix function and organization, cellular adhesion, muscle growth, lipid metabolism and proteolysis. Candidate genes with known effects on muscle growth were found among the DE genes upregulated in DU×IB. Genes related to lipid metabolism and proteolysis were found among those upregulated in IB. Regulatory factors (RF) potentially involved in the expression differences were identified by calculating the regulatory impact factors. Twenty-nine RF were found, some of them with known relationship with tissue development (MSTN, SIX4, IRX3), adipogenesis (CEBPD, PPARGC1B), or extracellular matrix processes (MAX, MXI1). Correlation among the expression of these RF and DE genes show relevant differences between genetic types.

CONCLUSION

These results provide valuable information about genetic mechanisms determining the phenotypic differences on growth and meat quality between the genetic types studied, mainly related to the development and function of the extracellular matrix and also to some metabolic processes as proteolysis and lipid metabolism. Transcription factors and regulatory mechanisms are proposed for these altered biological functions.

A marker-derived gene network reveals the regulatory role of PPARGC1A, HNF4G, and FOXP3 in intramuscular fat deposition of beef cattle

High intramuscular fat (IMF) awards price premiums to beef producers and is associated with meat quality and flavor. Studying gene interactions and pathways that affect IMF might unveil causative physiological mechanisms and inform genomic selection, leading to increased accuracy of predictions of breeding value. To study gene interactions and pathways, a gene network was derived from genetic markers associated with direct measures of IMF, other fat phenotypes, feedlot performance, and a number of meat quality traits relating to body conformation, development, and metabolism that might be plausibly expected to interact with IMF biology. Marker associations were inferred from genomewide association studies (GWAS) based on high density genotypes and 29 traits measured on 10,181 beef cattle animals from 3 breed types. For the network inference, SNP pairs were assessed according to the strength of the correlation between their additive association effects across the 29 traits. The co-association inferred network was formed by 2,434 genes connected by 28,283 edges. Topological network parameters suggested a highly cohesive network, in which the genes are strongly functionally interconnected. Pathway and network analyses pointed towards a trio of transcription factors (TF) as key regulators of carcass IMF: PPARGC1A, HNF4G, and FOXP3. Importantly, none of these genes would have been deemed as significantly associated with IMF from the GWAS. Instead, a total of 313 network genes show significant co-association with the 3 TF. These genes belong to a wide variety of biological functions, canonical pathways, and genetic networks linked to IMF-related phenotypes. In summary, our GWAS and network predictions are supported by the current literature and suggest a cooperative role for the 3 TF and other interacting genes including CAPN6, STC2, MAP2K4, EYA1, COPS5, XKR4, NR2E1, TOX, ATF1, ASPH, TGS1, and TTPA as modulators of carcass and meat quality traits in beef cattle.