Conserved epigenetic regulatory logic infers genes governing cell identity

Woo Jun Shim, Enakshi Sinniah, Jun Xu, Burcu Vitrinel, Michael Alexanian, Gaia Andreoletti, Sophie Shen, Brad Balderson, Guangdun Peng, Naihe Jing, Yuliangzi Sun, Yash Chhabra, Yuliang Wang, Patrick P L Tam, Aaron Smith, Michael Piper, Lionel Christiaen, Quan Nguyen, Mikael Bodén, Nathan J. Palpant

Aug 13, 2019

Received Date: 23rd July 19

We define a scalable and genome-wide metric based on the gene-repressive tri-methylation of histone 3 lysine 27 that strongly enriches for genes that drive cell diversification and determine their fates. Transcriptional Regulatory Inference Analysis from Gene Expression (TRIAGE) incorporates tendencies of H3K27me3 as deposited across over 100 representative cell states. As a consequence, inference of cell identity genes from expressed transcripts of any somatic cell type is made possible without also requiring its correlative epigenetic data. We combine more than 1 million genome-wide data sets from different omics platforms to identify and experimentally validate cell type-specific regulatory mechanisms for organ systems in health and disease. The success with which driver genes are recovered attests to a repression-based regulatory logic conserved in species across the animal kingdom, and suggests a simple but effective computational approach to determine causal factors from gene output alone.

Read in full at bioRxiv.

This is an abstract of a preprint hosted on an independent third party site. It has not been peer reviewed but is currently under consideration at Nature Communications.

Nature Communications

Nature Research, Springer Nature