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bioRxiv · 10.1101/585125

Integrative analysis of epigenetics data identifies gene-specific regulatory elements

Schmidt, F.·Marx, A.·Hebel, M.·Wegner, M.·Baumgarten, N.·Kaulich, M.·Goeke, J.·Vreeken, J.·Schulz, M. H. H.
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Abstract

Understanding the complexity of transcriptional regulation is a major goal of computational biology. Because experimental linkage of regulatory sites to genes is challenging, computational methods considering epigenomics data have been proposed to create tissue-specific regulatory maps. However, we showed that these approaches are not well suited to account for the variations of the regulatory landscape between cell-types. To overcome these drawbacks, we developed a new method called SO_SCPCAPTITCHC_SCPCAPIO_SCPCAPTC_SCPCAP, that identifies and links putative regulatory sites to genes. Within SO_SCPCAPTITCHC_SCPCAPIO_SCPCAPTC_SCPCAP, we consider the chromatin accessibility signal of all samples jointly to identify regions exhibiting a signal variation related to the expression of a distinct gene. SO_SCPCAPTITCHC_SCPCAPIO_SCPCAPTC_SCPCAP outperforms previous approaches in various validation experiments and was used with a genome-wide CRISPR-Cas9 screen to prioritize novel doxorubicin-resistance genes and their associated non-coding regulatory regions. We believe that our work paves the way for a more refined understanding of transcriptional regulation at the gene-level.

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Schmidt, F., Marx, A., Hebel, M., Wegner, M., Baumgarten, N., Kaulich, M., Goeke, J., Vreeken, J., Schulz, M. H. H.. 2019-03-26. Integrative analysis of epigenetics data identifies gene-specific regulatory elements. https://doi.org/10.1101/585125

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