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Detecting Endogenous Retrovirus-Driven Tissue-Specific Gene Transcription
- Pavlicev, Mihaela, Hiratsuka, Kaori, Swaggart, Kayleigh A., Dunn, Caitlin, Muglia, Louis
- Genome Biology and Evolution 2015 v.7 no.4 pp. 1082-1097
- RNA, carcinogenesis, evolution, gene expression, gene expression regulation, genes, humans, terminal repeat sequences, transcription (genetics), transposons
- Transposable elements (TEs) comprise approximately half of the human genome, and several independent lines of investigation have demonstrated their role in rewiring gene expression during development, evolution, and oncogenesis. The identification of their regulatory effects has largely been idiosyncratic, by linking activity with isolated genes. Their distribution throughout the genome raises critical questions—do these elements contribute to broad tissue- and lineage-specific regulation? If so, in what manner, as enhancers, promoters, RNAs? Here, we devise a novel approach to systematically dissect the genome-wide consequences of TE insertion on gene expression, and test the hypothesis that classes of endogenous retrovirus long terminal repeats (LTRs) exert tissue-specific regulation of adjacent genes. Using correlation of expression patterns across 18 tissue types, we reveal the tissue-specific uncoupling of gene expression due to 62 different LTR classes. These patterns are specific to the retroviral insertion, as the same genes in species without the LTRs do not exhibit the same effect. Although the LTRs can be transcribed themselves, the most highly transcribed TEs do not have the largest effects on adjacent regulation of coding genes, suggesting they function predominantly as enhancers. Moreover, the tissue-specific patterns of gene expression that are detected by our method arise from a limited number of genes, rather than as a general consequence of LTR integration. These findings identify basic principles of co-opting LTRs for genome evolution, and support the utility of our method for the analysis of TE, or other specific gene sets, in relation to the rest of the genome.