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

Association between mitochondrial DNA copy number and production traits in pigs

Mitochondria are essential organelles in the regulation of cellular energetic metabolism. Mitochondrial DNA copy number (mtDNA_CN) can be used as a proxy for mitochondria number, size, and activity. The aims of our study are to evaluate the effect of mtDNA_CN and mitochondrial haploblocks on production traits in pigs, and to identify the genetic background of this cellular phenotype. We collected performance data of 234 pigs and extracted DNA from skeletal muscle. Whole-genome sequencing data was used to determine mtDNA_CN. We found positive correlations of muscle mtDNA_CN with backfat thickness at 207 d (+0.14; p-value = 0.07) and negative correlations with carcase loin thickness (-0.14; p-value = 0.03). Pigs with mtDNA_CN values below the lower quartile had greater loin thickness (+4.1 mm; p-value = 0.01) and lower backfat thickness (-1.1 mm; p-value = 0.08), which resulted in greater carcase lean percentage (+2.4%; p-value = 0.04), than pigs with mtDNA_CN values above the upper quartile. These results support the hypothesis that a reduction of mitochondrial activity is associated with greater feed efficiency. Higher mtDNA_CN was also positively correlated with higher meat ultimate pH (+0.19; p-value <0.01) but we did not observe significant difference for meat ultimate pH between the two groups with extreme mtDNA_CN. We found no association of the most frequent mitochondrial haploblocks with mtDNA_CN or the production traits, but several genomic regions that harbour potential candidate genes with functions related to mitochondrial biogenesis and homeostasis were associated with mtDNA_CN. These regions provide new insights into the genetic background of this cellular phenotype but it is still uncertain if such associations translate into noticeable effects on the production traits.

Genetic analysis of the blood transcriptome of young healthy pigs to improve disease resilience

BACKGROUND

Disease resilience is the ability of an animal to maintain productive performance under disease conditions and is an important selection target. In pig breeding programs, disease resilience must be evaluated on selection candidates without exposing them to disease. To identify potential genetic indicators for disease resilience that can be measured on selection candidates, we focused on the blood transcriptome of 1594 young healthy pigs with subsequent records on disease resilience. Transcriptome data were obtained by 3'mRNA sequencing and genotype data were from a 650 K genotyping array.

RESULTS

Heritabilities of the expression of 16,545 genes were estimated, of which 5665 genes showed significant estimates of heritability (p < 0.05), ranging from 0.05 to 0.90, with or without accounting for white blood cell composition. Genes with heritable expression levels were spread across chromosomes, but were enriched in the swine leukocyte antigen region (average estimate > 0.2). The correlation of heritability estimates with the corresponding estimates obtained for genes expressed in human blood was weak but a sizable number of genes with heritable expression levels overlapped. Genes with heritable expression levels were significantly enriched for biological processes such as cell activation, immune system process, stress response, and leukocyte activation, and were involved in various disease annotations such as RNA virus infection, including SARS-Cov2, as well as liver disease, and inflammation. To estimate genetic correlations with disease resilience, 3205 genotyped pigs, including the 1594 pigs with transcriptome data, were evaluated for disease resilience following their exposure to a natural polymicrobial disease challenge. Significant genetic correlations (p < 0.05) were observed with all resilience phenotypes, although few exceeded expected false discovery rates. Enrichment analysis of genes ranked by estimates of genetic correlations with resilience phenotypes revealed significance for biological processes such as regulation of cytokines, including interleukins and interferons, and chaperone mediated protein folding.

CONCLUSIONS

These results suggest that expression levels in the blood of young healthy pigs for genes in biological pathways related to immunity and endoplasmic reticulum stress have potential to be used as genetic indicator traits to select for disease resilience.

Identification of eQTLs and differential gene expression associated with fetal programming in beef cattle

This study assessed differential gene expression and identified expression quantitative trait loci (eQTLs) from samples of Longissimus lumborum muscle from bulls at 15 months of age submitted to different prenatal nutrition. Upon confirmation of pregnancy, 126 dams were separated into three diet treatments varying the period of inclusion of energy protein supplementation (NP, PP, and FP). At calving, 63 males were genotyped with GGP LD BeadChip. The skeletal muscle of 15 bulls was sequenced (RNA-seq) at 15 months of age. The EdgeR package was used for differential gene expression and principal component analysis (PCA), and the Matrix eQTL package was used for the eQTLs analysis (R statistical). The functional enrichment analysis was performed using the MetaCore® software. No genes differentially expressed were found between treatments (FDR > 0.05); nevertheless, we found 179 cis-tag-eQTLs and 20,762 trans-tag-eQTLs (FDR < 0.05) after linkage disequilibrium analysis. The functional enrichment analysis identified terms from gene ontology related to genes associated to trans-eQTLs (FDR < 0.05) as well as metabolic pathways (> gScore). Most biological pathways and genes found had been previously associated to fetal programming. The different prenatal supplementation strategies did not impact on muscle transcriptome of bulls. Additionally, there is a link between genotype and gene expression levels related to developmental traits in Nellore cattle.

An Integrative Analysis of Transcriptome and GWAS Data to Identify Potential Candidate Genes Influencing Meat Quality Traits in Pigs

Understanding the genetic factors behind meat quality traits is of great significance to animal breeding and production. We previously conducted a genome-wide association study (GWAS) for meat quality traits in a White Duroc × Erhualian F2 pig population using Illumina porcine 60K SNP data. Here, we further investigate the functional candidate genes and their network modules associated with meat quality traits by integrating transcriptomics and GWAS information. Quantitative trait transcript (QTT) analysis, gene expression QTL (eQTL) mapping, and weighted gene co-expression network analysis (WGCNA) were performed using the digital gene expression (DGE) data from 493 F2 pig's muscle and liver samples. Among the quantified 20,108 liver and 23,728 muscle transcripts, 535 liver and 1,014 muscle QTTs corresponding to 416 and 721 genes, respectively, were found to be significantly (p < 5 × 10^-4) correlated with 22 meat quality traits measured on longissiums dorsi muscle (LM) or semimembranosus muscle (SM). Transcripts associated with muscle glycolytic potential (GP) and pH values were enriched for genes involved in metabolic process. There were 42 QTTs (for 32 genes) shared by liver and muscle tissues, of which 10 QTTs represent GP- and/or pH-related genes, such as JUNB, ATF3, and PPP1R3B. Furthermore, a genome-wide eQTL mapping revealed a total of 3,054 eQTLs for all annotated transcripts in muscle (p < 2.08 × 10^-5), including 1,283 cis-eQTLs and 1771 trans-eQTLs. In addition, WGCNA identified five modules relevant to glycogen metabolism pathway and highlighted the connections between variations in meat quality traits and genes involved in energy process. Integrative analysis of GWAS loci, eQTL, and QTT demonstrated GALNT15/GALNTL2 and HTATIP2 as strong candidate genes for drip loss and pH drop from postmortem 45 min to 24 h, respectively. Our findings provide valuable insights into the genetic basis of meat quality traits and greatly expand the number of candidate genes that may be valuable for future functional analysis and genetic improvement of meat quality.