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Genome-wide analysis of expression QTL (eQTL) and allele-specific expression (ASE) in pig muscle identifies candidate genes for meat quality traits
- Source :
- Genetics Selection Evolution, Vol 52, Iss 1, Pp 1-11 (2020)
- Publication Year :
- 2020
- Publisher :
- BMC, 2020.
-
Abstract
- Abstract Background Genetic analysis of gene expression level is a promising approach for characterizing candidate genes that are involved in complex economic traits such as meat quality. In the present study, we conducted expression quantitative trait loci (eQTL) and allele-specific expression (ASE) analyses based on RNA-sequencing (RNAseq) data from the longissimus muscle of 189 Duroc × Luchuan crossed pigs in order to identify some candidate genes for meat quality traits. Results Using a genome-wide association study based on a mixed linear model, we identified 7192 cis-eQTL corresponding to 2098 cis-genes (p ≤ 1.33e-3, FDR ≤ 0.05) and 6400 trans-eQTL corresponding to 863 trans-genes (p ≤ 1.13e-6, FDR ≤ 0.05). ASE analysis using RNAseq SNPs identified 9815 significant ASE-SNPs in 2253 unique genes. Integrative analysis between the cis-eQTL and ASE target genes identified 540 common genes, including 33 genes with expression levels that were correlated with at least one meat quality trait. Among these 540 common genes, 63 have been reported previously as candidate genes for meat quality traits, such as PHKG1 (q-value = 1.67e-6 for the leading SNP in the cis-eQTL analysis), NUDT7 (q-value = 5.67e-13), FADS2 (q-value = 8.44e-5), and DGAT2 (q-value = 1.24e-3). Conclusions The present study confirmed several previously published candidate genes and identified some novel candidate genes for meat quality traits via eQTL and ASE analyses, which will be useful to prioritize candidate genes in further studies.
- Subjects :
- Animal culture
SF1-1100
Genetics
QH426-470
Subjects
Details
- Language :
- German, English, French
- ISSN :
- 12979686
- Volume :
- 52
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Genetics Selection Evolution
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.7142cc8815c340aa93b3862b77c16a04
- Document Type :
- article
- Full Text :
- https://doi.org/10.1186/s12711-020-00579-x