Person: Montgomery, Robert K.
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Publication Differentiation-Specific Histone Modifications Reveal Dynamic Chromatin Interactions and Partners for the Intestinal Transcription Factor CDX2
(Elsevier BV, 2010) Verzi, Michael P.; Shin, Hyunjin; He, H. Hansen; Sulahian, Rita; Meyer, Clifford; Montgomery, Robert K.; Fleet, James C.; Brown, Myles; Liu, Xiaole; Shivdasani, RameshCell differentiation requires remodeling of tissue-specific gene loci and activities of key transcriptional regulators, which are recognized for their dominant control over cellular programs. Using epigenomic methods, we characterized enhancer elements specifically modified in differentiating intestinal epithelial cells and found enrichment of transcription factor-binding motifs corresponding to CDX2, a critical regulator of the intestine. Directed investigation revealed surprising lability in CDX2 occupancy of the genome, with redistribution from hundreds of sites occupied only in proliferating cells to thousands of new sites in differentiated cells. Knockout mice confirmed distinct Cdx2 requirements in dividing and mature adult intestinal cells, including responsibility for the active enhancer configuration associated with maturity. Dynamic CDX2 occupancy corresponds with condition-specific gene expression and, importantly, to differential co-occupancy with other tissue-restricted transcription factors such as GATA6 and HNF4A. These results reveal dynamic, context-specific functions and mechanisms of a prominent transcriptional regulator within a cell lineage.
Publication CellMapper: rapid and accurate inference of gene expression in difficult-to-isolate cell types
(BioMed Central, 2016) Nelms, Bradlee D.; Waldron, Levi; Barrera, Luis A.; Weflen, Andrew W.; Goettel, Jeremy; Guo, Guoji; Montgomery, Robert K.; Neutra, Marian; Breault, David; Snapper, Scott; Orkin, Stuart; Bulyk, Martha; Huttenhower, Curtis; Lencer, WayneWe present a sensitive approach to predict genes expressed selectively in specific cell types, by searching publicly available expression data for genes with a similar expression profile to known cell-specific markers. Our method, CellMapper, strongly outperforms previous computational algorithms to predict cell type-specific expression, especially for rare and difficult-to-isolate cell types. Furthermore, CellMapper makes accurate predictions for human brain cell types that have never been isolated, and can be rapidly applied to diverse cell types from many tissues. We demonstrate a clinically relevant application to prioritize candidate genes in disease susceptibility loci identified by GWAS. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-1062-5) contains supplementary material, which is available to authorized users.