RT Journal Article
SR Electronic
T1 Integrative analysis of epigenetics data identifies gene-specific regulatory elements
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 585125
DO 10.1101/585125
A1 Florian Schmidt
A1 Alexander Marx
A1 Marie Hebel
A1 Martin Wegner
A1 Nina Baumgarten
A1 Manuel Kaulich
A1 Jonathan Göke
A1 Jilles Vreeken
A1 Marcel H. Schulz
YR 2019
UL http://biorxiv.org/content/early/2019/03/26/585125.abstract
AB 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 STITCHIT, that identifies and links putative regulatory sites to genes. Within STITCHIT, 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. STITCHIT 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.