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PLoS One. 2012;7(12):e52433. doi: 10.1371/journal.pone.0052433. Epub 2012 Dec 20.

A genome-wide investigation of expression characteristics of natural antisense transcripts in liver and muscle samples of pigs.

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Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, People's Republic of China.


Natural antisense transcripts are endogenous transcripts that are complementary to the sense-strand of DNA. These transcripts have been identified in various eukaryotic species and are involved in a broad range of regulatory events and biological processes. However, their general biological functions, expression characteristics and regulatory mechanisms are still unclear. In this study, 497 liver and 586 muscle samples were harvested from a White DurocĂ—Erhualian F(2) resource population. The expression profiles of sense and antisense transcripts were determined by tag-based RNA sequencing. We identified 33.7% and 20.4% of transcripts having both sense and antisense expression, and 12.5% and 6.1% of transcripts only expressing antisense transcripts in liver and muscle, respectively. More than 32.2% of imprinting or predicted imprinting genes in the geneimprint database were detected with both sense and antisense expression. The correlations between sense and antisense expression in sense-antisense pairs were diverse in both liver and muscle, showing positive, negative or absent correlation. Antisense expression increases gene expression variability. More interestingly, compared to eQTL mapping of sense transcripts in which more than one eQTL was mapped for a transcript, only one eQTL was identified for each antisense transcript, and the percentage of cis-eQTL in antisense eQTL was higher than that in sense eQTL. This suggests that the expressions of antisense transcripts tend to be cis-regulated by a single genomic locus. To our knowledge, this study is the first systematical investigation of antisense transcription in pigs. The findings improve our understanding of the complexity of porcine transcriptome.

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