Investigating the genetic regulation of the expression of 63 lipid metabolism genes in the pig skeletal muscle

Genetic variations (eQTLs) in muscle transcriptome and mitochondrial genes, and trans-eQTL molecular pathways in feed efficiency from Danish breeding pigs

Feed efficiency (FE) is a key trait in pig production, as improvement in FE has positive economic and environmental impact. FE is a complex phenotype and testing animals for FE is costly. Therefore, there has been a desire to find functionally relevant single nucleotide polymorphisms (SNPs) as biomarkers, to improve our biological understanding of FE as well as accuracy of genomic prediction for FE. We have performed a cis- and trans- eQTL (expression quantitative trait loci) analysis, in a population of Danbred Durocs (N = 11) and Danbred Landrace (N = 27) using both a linear and ANOVA model based on muscle tissue RNA-seq. We analyzed a total of 1425x19179 or 2.7x10⁷ Gene-SNP combinations in eQTL detection models for FE. The 1425 genes were from RNA-Seq based differential gene expression analyses using 25880 genes related to FE and additionally combined with mitochondrial genes. The 19179 SNPs were from applying stringent quality control and linkage disequilibrium filtering on genotype data using a GGP Porcine HD 70k SNP array. We applied 1000 fold bootstrapping and enrichment analysis to further validate and analyze our detected eQTLs. We identified 13 eQTLs with FDR < 0.1, affecting several genes found in previous studies of commercial pig breeds. Examples include MYO19, CPT1B, ACSL1, IER5L, CPT1A, SUCLA2, CSRNP1, PARK7 and MFF. The bootstrapping results showed statistically significant enrichment (p-value<2.2x10^-16) of eQTLs with p-value < 0.01 in both cis and trans-eQTLs. Enrichment analysis of top trans-eQTLs revealed high enrichment for gene categories and gene ontologies associated with genomic context and expression regulation. This included transcription factors (p-value = 1.0x10^-13), DNA-binding (GO:0003677, p-value = 8.9x10^-14), DNA-binding transcription factor activity (GO:0003700,) nucleus gene (GO:0005634, p-value<2.2x10^-16), negative regulation of expression (GO:0010629, p-value<2.2x10^-16). These results would be useful for future genome assisted breeding of pigs to improve FE, and in the improved understanding of the functional mechanism of trans eQTLs.

Differentially expressed genes identified through RNA-seq with extreme values of principal components for beef fatty acid in Nelore cattle

The aim of this study was to identify differentially expressed genes (DEG) in the Longissimus thoracis muscle of Nelore cattle related to fatty acid (FA) profile through RNA sequencing and principal component analysis (PCA). Two groups of 10 animals each were selected containing PC1 and PC2 extreme DEG values (HIGH × LOW) for each FA group. The intramuscular fat (IMF) was compared between cluster groups by ANOVA, and only the sum of monounsaturated FA (MUFA) and ω3 showed significant differences (p < .05). Interestingly, the highest percentage (95%) of phenotypic variation explained by the sum of the first two PC was observed for ω3, which also displayed the lowest number of DEG (n = 1). The lowest percentage (59%) was observed for MUFA, which also revealed the largest number of DEG (n = 66). Since only MUFA and ω3 exhibited significant differences between cluster groups, we can conclude that the differences observed for the remaining groups are not due to the percentage of IMF. Several genes that have been previously associated with meat quality and FA traits were identified as DEG in this study. The functional analysis revealed one KEGG pathway and eight GO terms as significant (p < .05), in which we highlighted the purine metabolism, glycolytic process, adenosine triphosphate binding and bone development. These results strongly contribute to the knowledge of the biological mechanisms involved in meat FA profile of Nelore cattle.

Identification of eQTLs and sQTLs associated with meat quality in beef

BACKGROUND

Transcription has a substantial genetic control and genetic dissection of gene expression could help us understand the genetic architecture of complex phenotypes such as meat quality in cattle. The objectives of the present research were: 1) to perform eQTL and sQTL mapping analyses for meat quality traits in longissimus dorsi muscle; 2) to uncover genes whose expression is influenced by local or distant genetic variation; 3) to identify expression and splicing hot spots; and 4) to uncover genomic regions affecting the expression of multiple genes.

RESULTS

Eighty steers were selected for phenotyping, genotyping and RNA-seq evaluation. A panel of traits related to meat quality was recorded in longissimus dorsi muscle. Information on 112,042 SNPs and expression data on 8588 autosomal genes and 87,770 exons from 8467 genes were included in an expression and splicing quantitative trait loci (QTL) mapping (eQTL and sQTL, respectively). A gene, exon and isoform differential expression analysis previously carried out in this population identified 1352 genes, referred to as DEG, as explaining part of the variability associated with meat quality traits. The eQTL and sQTL mapping was performed using a linear regression model in the R package Matrix eQTL. Genotype and year of birth were included as fixed effects, and population structure was accounted for by including as a covariate the first PC from a PCA analysis on genotypic data. The identified QTLs were classified as cis or trans using 1 Mb as the maximum distance between the associated SNP and the gene being analyzed. A total of 8377 eQTLs were identified, including 75.6% trans, 10.4% cis, 12.5% DEG trans and 1.5% DEG cis; while 11,929 sQTLs were uncovered: 66.1% trans, 16.9% DEG trans, 14% cis and 3% DEG cis. Twenty-seven expression master regulators and 13 splicing master regulators were identified and were classified as membrane-associated or cytoskeletal proteins, transcription factors or DNA methylases. These genes could control the expression of other genes through cell signaling or by a direct transcriptional activation/repression mechanism.

CONCLUSION

In the present analysis, we show that eQTL and sQTL mapping makes possible positional identification of gene and isoform expression regulators.

Expression Quantitative Trait Loci in Equine Skeletal Muscle Reveals Heritable Variation in Metabolism and the Training Responsive Transcriptome

While over ten thousand genetic loci have been associated with phenotypic traits and inherited diseases in genome-wide association studies, in most cases only a relatively small proportion of the trait heritability is explained and biological mechanisms underpinning these traits have not been clearly identified. Expression quantitative trait loci (eQTL) are subsets of genomic loci shown experimentally to influence gene expression. Since gene expression is one of the primary determinants of phenotype, the identification of eQTL may reveal biologically relevant loci and provide functional links between genomic variants, gene expression and ultimately phenotype. Skeletal muscle (gluteus medius) gene expression was quantified by RNA-seq for 111 Thoroughbreds (47 male, 64 female) in race training at a single training establishment sampled at two time-points: at rest (n = 92) and four hours after high-intensity exercise (n = 77); n = 60 were sampled at both time points. Genotypes were generated from the Illumina Equine SNP70 BeadChip. Applying a False Discovery Rate (FDR) corrected P-value threshold (P_FDR < 0.05), association tests identified 3,583 cis-eQTL associated with expression of 1,456 genes at rest; 4,992 cis-eQTL associated with the expression of 1,922 genes post-exercise; 1,703 trans-eQTL associated with 563 genes at rest; and 1,219 trans-eQTL associated with 425 genes post-exercise. The gene with the highest cis-eQTL association at both time-points was the endosome-associated-trafficking regulator 1 gene (ENTR1; Rest: P_FDR = 3.81 × 10^-27, Post-exercise: P_FDR = 1.66 × 10^-24), which has a potential role in the transcriptional regulation of the solute carrier family 2 member 1 glucose transporter protein (SLC2A1). Functional analysis of genes with significant eQTL revealed significant enrichment for cofactor metabolic processes. These results suggest heritable variation in genomic elements such as regulatory sequences (e.g. gene promoters, enhancers, silencers), microRNA and transcription factor genes, which are associated with metabolic function and may have roles in determining end-point muscle and athletic performance phenotypes in Thoroughbred horses. The incorporation of the eQTL identified with genome and transcriptome-wide association may reveal useful biological links between genetic variants and their impact on traits of interest, such as elite racing performance and adaptation to training.