Downloaded from genome.cshlp.org on October 5, 2021 - Published by Cold Spring Harbor Laboratory Press Chromatin module inference on cellular trajectories identifies key transition points and poised epigenetic states in diverse developmental processes Sushmita Roy1, 3, * and Rupa Sridharan2, 3, * 1. Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53715, USA 2. Department of Cell and Regenerative Biology, University of Wisconsin, Madison WI 53715, USA 3. Wisconsin Institute for Discovery, 330 N. Orchard Street, Madison, WI 53715, USA *Corresponding author
[email protected] [email protected] Downloaded from genome.cshlp.org on October 5, 2021 - Published by Cold Spring Harbor Laboratory Press Abstract Changes in chromatin state play important roles in cell fate transitions. Current computational approaches to analyze chromatin modifications across multiple cell types do not model how the cell types are related on a lineage or over time. To overcome this limitation, we have developed a method called CMINT (Chromatin Module INference on Trees), a probabilistic clustering approach to systematically capture chromatin state dynamics across multiple cell types. Compared to existing approaches, CMINT can handle complex lineage topologies, capture higher quality clusters, and reliably detect chromatin transitions between cell types. We applied CMINT to gain novel insights in two complex processes: reprogramming to induced pluripotent stem cells (iPSCs) and hematopoiesis. In reprogramming, chromatin changes could occur without large gene expression changes; different combinations of activating marks were associated with specific reprogramming factors; there was an order of acquisition of chromatin marks at pluripotency loci; and multivalent states, comprising previously undetermined combinations of activating and repressive histone modifications were enriched for CTCF.