A genome-wide analysis of the ultimate pH in swine

The differences in artificial and natural selection have been some of the factors contributing to phenotypic diversity between Chinese and western pigs. Here, 830 individuals from western and Chinese pig breeds were genotyped using the reduced-representation genotyping method. First, we identified the selection signatures for different pig breeds. By comparing Chinese pigs and western pigs along the first principal component, the growth gene IGF1R; the immune genes IL1R1, IL1RL1, DUSP10, RAC3 and SWAP70; the meat quality-related gene SNORA50 and the olfactory gene OR1F1 were identified as candidate differentiated targets. Further, along a principal component separating Pudong White pigs from others, a potential causal gene for coat colour (EDNRB) was discovered. In addition, the divergent signatures evaluated by Fst within Chinese pig breeds found genes associated with the phenotypic features of coat colour, meat quality and feed efficiency among these indigenous pigs. Second, admixture and genomic introgression analysis were performed. Shan pigs have introgressed genes from Berkshire, Yorkshire and Hongdenglong pigs. The results of introgression mapping showed that this introgression conferred adaption to the local environment and coat colour of Chinese pigs and the superior productivity of western pigs.

show abstract

“… 73 SYBU Meat quality Chung, et al . 101 EDNRB Coat color Ai, et al . 16 TDRD9 Conformation traits Le, et al .…”

Section: Resultsmentioning

confidence: 99%

Genomic analysis reveals genes affecting distinct phenotypes among different Chinese and western pig breeds

Zhang

Xiao

Zhang

et al. 2018

Sci Rep

View full text Add to dashboard Cite

show abstract

“…We also identified a gene associated with glucose metabolism (MGAT4A) (Ohtsubo et al, 2005). Two genes were associated with meat quality phenotypes in cattle and pig (MTRF1, KLH30) (Jiang et al, 2009;Chung et al, 2015;Dos Santos Silva et al, 2019). Perhaps the most interesting result, is that one of the genes found in the Duroc analysis, TRIM63, has been associated as a biomarker for differences in response to exercise induced muscle damage (Baumert et al, 2018), which ties into our comparison to human data.…”

Section: Differential Expression Analysis and Pathway Enrichmentmentioning

confidence: 64%

“…Notably, out of 4 genes in the joint breed analysis there are two genes with mitochondrial related Gene Ontologies -MRPS11, MTRM1. MTFR1 has been implicated in eating quality (measures of meat quality post-cooking) in cattle (Jiang et al, 2009) and as a meat PH QTL in pig (Chung et al, 2015). Also interesting to note that TRIM63 has been suggested as a biomarker for difference in response to exercise-induced muscle damage (Baumert et al, 2018), KLHL30 has been associated with intramuscular fat and muscle metabolism in Nelore Cattle (Dos Santos Silva et al, 2019).…”

Section: Enrichments Analysismentioning

confidence: 99%

Genome Regulation and Gene Interaction Networks Inferred From Muscle Transcriptome Underlying Feed Efficiency in Pigs

Carmelo

Kadarmideen

2020

Front. Genet.

View full text Add to dashboard Cite

Improvement of feed efficiency (FE) is key for Sustainability and cost reduction in pig production. Our aim was to characterize the muscle transcriptomic profiles in Danbred Duroc (Duroc; n = 13) and Danbred Landrace (Landrace; n = 28), in relation to FE for identifying potential biomarkers. RNA-seq data on the 41 pigs was analyzed employing differential gene expression methods, gene-gene interaction and network analysis, including pathway and functional analysis. We also compared the results with genome regulation in human exercise data, hypothesizing that increased FE mimics processes triggered in exercised muscle. In the differential expression analysis, 13 genes were differentially expressed, including: MRPS11, MTRF1, TRIM63, MGAT4A, KLH30. Based on a novel gene selection method, the divergent count, we performed pathway enrichment analysis. We found five significantly enriched pathways related to feed conversion ratio (FCR). These pathways were mainly related to mitochondria, and summarized in the mitochondrial translation elongation (MTR) pathway. In the gene interaction analysis, the most interesting genes included the mitochondrial genes: PPIF, MRPL35, NDUFS4 and the fat metabolism and obesity genes: AACS, SMPDL3B, CTNNBL1, NDUFS4, and LIMD2. In the network analysis, we identified two modules significantly correlated with FCR. Pathway enrichment of module genes identified MTR, electron transport chain and DNA repair as enriched pathways. The network analysis revealed the mitochondrial gene group NDUF as key network hub genes, showing their potential as biomarkers. Results show that genes related to human exercise were enriched in identified FCR related genes. We conclude that mitochondrial activity is a key driver for FCR in muscle tissue, and mitochondrial genes could be potential biomarkers for FCR in pigs.

show abstract

“…As animals were only sampled post conventional slaughter, no ethics approval was needed for the 571 study. 572 (Jiang, Michal et al 2009) and as a meat PH QTL in pig (Chung, Lee et al 2015). 767…”

Section: Conflict Of Interest 567mentioning

confidence: 99%

Genome regulation and gene interaction networks inferred from muscle transcriptome underlying feed efficiency in Pigs

Carmelo¹,

Kadarmideen

2020

Preprint

View full text Add to dashboard Cite

11Improvement of feed efficiency (FE) is key for sustainability and cost reduction in pig 12 production. Our aim was to characterize the muscle transcriptomic profiles in Danbred 13Duroc (Duroc) and Danbred Landrace (Landrace), in relation to FE for identifying 14 potential biomarkers. RNA-seq data was analyzed employing differential gene expression 15 methods, gene-gene interaction and network analysis, including pathway and functional 16 analysis. We compared the results with genome regulation in human exercise data. In the 17 differential expression analysis, 13 genes were differentially expressed, including: 18 MRPS11, MTRF1, TRIM63, MGAT4A, KLH30. Based on a novel gene selection method, 19the divergent count, we performed pathway enrichment analysis. We found 5 significantly 20 enriched pathways related to feed conversion ratio (FCR). These pathways were mainly 21 mitochondrial, and summarized in the mitochondrial translation elongation (MTR) 22pathway. In the gene interaction analysis, highlights include the mitochondrial genes: 23 PPIF, MRPL35, NDUFS4and the fat metabolism and obesity genes: AACS, SMPDL3B, 24 CTNNBL1, NDUFS4 and LIMD2. In the network analysis, we identified two modules 25 significantly correlated with FCR. Pathway enrichment of modules identified MTR, 26 electron transport chain and DNA repair as enriched pathways. In the network analysis, 27 the mitochondrial gene group NDUF was a key hub group, showing potential as 28 biomarkers. Comparing with human transcriptomic exercise studies, genes related to 29 exercise displayed enrichment in our FCR related genes. We conclude that mitochondrial 30 activity is a driver for FCR in muscle tissue, and mitochondrial genes could be potential 31 biomarkers for FCR in pigs. We hypothesize that increased FE mimics processes 32 triggered in exercised muscle. 33 34 35 calculation is dependent on individual population and production factors (Hoque, Kadowaki et al. 56 2009, Do, Strathe et al. 2013. However, in pig production, the side effects of FCR selection and 57 simplicity are desired traits, thus perhaps explaining why the pig population in Denmark and in 58 general pig production, FCR has been the main efficiency phenotype used for selection (Gilbert, 59 Billon et al. 2017). One can also hypothesize that FCR is more easily translatable between 60 breeds/populations, as it is a simple dimensionless ratio, which has a simple and generally 61 comparable interpretation. In contrast, it is more difficult to easily compare RFI values across 62 different populations or breeds. In regards to the biological and/or genetic background of FCR in 63 pigs, the results remain somewhat elusive (Ding, Yang et al. 2018), thus inviting for further analysis 64 on the topic. 65

show abstract

A genome-wide analysis of the ultimate pH in swine

Cited by 9 publications

References 21 publications

Genomic analysis reveals genes affecting distinct phenotypes among different Chinese and western pig breeds

Genomic analysis reveals genes affecting distinct phenotypes among different Chinese and western pig breeds

Genome Regulation and Gene Interaction Networks Inferred From Muscle Transcriptome Underlying Feed Efficiency in Pigs

Genome regulation and gene interaction networks inferred from muscle transcriptome underlying feed efficiency in Pigs

Contact Info

Product

Resources

About