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Whole transcriptome analyses of three Berkshire and three Korean native pig fat, liver and muscle tissue using RNA-Seq

ABSTRACT: We sequenced the whole mRNA of six pig (Sus scrofa) fat, liver and muscle tissues, generating a total of 1.3 billion short reads with 90-bp pair-end sequences from 24 samples. Comparing with current genome annotation, we identified 32,361 unigene clusters spanning 51.83 Mb that contained 11,933 (36.87%) annotated genes. More than 60% (20,428) unigene clusters did not match any current equine gene model. We identified 189,973 single nucleotide variations (SNVs) from the aligned sequences against the horse reference. Most SNVs (171,558 SNVs; 90.31%) were novel compared with over 1.1 million equine SNPs from two databases. Some genes have significantly different expression levels under different environment. We define those identical genes which have different expression levels are ‘differentially expressed’ and carried out differentially expressed gene analysis before and after exercise conditions. We discovered, 62 up- and 80 down-regulated genes in the blood and 878 up- and 285 down-regulated genes in the muscle from the 24 samples. Six out of 28 previously exercise-related known genes, HIF1A, ADRB2, PPARD, VEGF, TNC, and BDNF, were highly expressed in the muscle after exercise. We discovered 56 functionally unknown transcription factors that are probably associated with an early regulatory exercise mechanism from 91 differentially expressed transcription factors. We found interesting RNA expression patterns where different alternative splicing forms of the same gene showed reversed expressions before and after exercising.

ORGANISM(S): Sus scrofa

PROVIDER: GSE45204 | GEO | 2014/09/01

SECONDARY ACCESSION(S): PRJNA193204

REPOSITORIES: GEO

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Project description:Purpose. Insulin resistant muscle is resistant to gene expression changes induced by acute exercise. This study was undertaken to identify transcription factors that differentially respond to exercise in insulin resistance. Candidate transcription factors were identified from analysis of 5’-untranslated regions (5’-UTRs) of exercise responsive genes and from analysis of the 5’-UTRs of genes coding for proteins that differ in abundance in insulin resistance. Research design and methods. Muscle biopsies were obtained from lean and obese subjects before and after a single exercise bout. Euglycemic glucose clamps assessed insulin sensitivity. Global proteomics analysis identified differentially abundant proteins. The 5’-UTRs of genes coding for significant proteins were subjected to transcription factor enrichment analysis to identify candidate transcription factors. Q-rt-PCR to determine expression of candidate transcription factors was performed on RNA from resting and post-exercise muscle biopsies; immunoblots quantified protein abundance. Results. Obese subjects were insulin resistant compared to lean but performed exercise at the same intensity. Proteins involved in mitochondrial function, protein targeting and translation, and metabolism were among those significantly different between the groups. Transcription factor enrichment analysis of genes coding for these proteins revealed new candidate transcription factors. Q-rt-PCR analysis of RNA and immunoblot analysis from pre- and post-exercise muscle biopsies revealed several transcription and growth factors that had altered responses to exercise in insulin resistant subjects. Conclusions. These results confirm findings of an association between insulin sensitivity and transcription factor mRNA response to exercise and extend these results to show that obesity also may be a sufficient prerequisite for exercise resistance. Analysis of the muscle proteome together with determination of effects of exercise on expression of transcription factors suggests that abnormal responses of transcription factors to exercise may be responsible for differences in protein abundances in insulin resistant muscle.

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Whole transcriptome analyses of three Berkshire and three Korean native pig fat, liver and muscle tissue using RNA-Seq

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