Binding profiles for 961 Drosophila and C. elegans transcription factors reveal tissue-specific regulatory relationships.

Autor:	Kudron M; Yale University School of Medicine., Gewirtzman L; University of Washington School of Medicine., Victorsen A; University of Minnesota., Lear BC; Northwestern University., Vafeados D; University of Washington., Gao J; Yale University., Xu J; Howard University., Samanta S; Yale University., Frink E; University of Washington School of Medicine., Tran-Pearson A; University of Washington School of Medicine., Hyunh C; University of Washington School of Medicine., Hammonds A; Lawrence Berkeley National Laboratory., Fisher W; Lawrence Berkeley National Laboratory., Wall ML; University of Chicago., Wesseling G; Northwestern University., Hernandez V; Northwestern University., Lin Z; Northwestern University., Kasparian M; Northwestern University., White KP; National University of Singapore., Allada R; Northwestern University., Gerstein M; Yale University., Hillier L; University of Washington School of Medicine., Celniker SE; Lawrence Berkeley National Laboratory., Reinke V; Yale University; valerie.reinke@yale.edu., Waterston R; University of Washington School of Medicine.
Jazyk:	angličtina
Zdroj:	Genome research [Genome Res] 2024 Oct 22. Date of Electronic Publication: 2024 Oct 22.
DOI:	10.1101/gr.279037.124
Abstrakt:	A catalog of transcription factor (TF) binding sites in the genome is critical for deciphering regulatory relationships. Here we present the culmination of the efforts of the Model Organism ENCyclopedia Of DNA Elements (modENCODE) and the model organism Encyclopedia of Regulatory Networks (modERN) consortia to systematically assay TF binding events in vivo in two major model organisms, Drosophila melanogaster (fly) and Caenorhabditis elegans (worm). These datasets comprise 605 TFs identifying 3.6M sites in the fly and 356 TFs identifying 0.9 M sites in the worm and represent the majority of the regulatory space in each genome. We demonstrate that TFs associate with chromatin in clusters termed "metapeaks", that larger metapeaks have characteristics of high occupancy target (HOT) regions, and that the importance of consensus sequence motifs bound by TFs depends on metapeak size and complexity. Combining ChIP-seq data with single cell RNA-seq data in a machine learning model identifies TFs with a prominent role in promoting target gene expression in specific cell types, even differentiating between parent-daughter cells during embryogenesis. These data are a rich resource for the community that should fuel and guide future investigations into TF function. To facilitate data accessibility and utility, all strains expressing GFP-tagged TFs are available at the stock centers for each organism. The chromatin immunoprecipitation sequencing data are available through the ENCODE Data Coordinating Center, GEO, and through a direct interface that provides rapid access to processed data sets and summary analyses, as well as widgets to probe the cell type-specific TF-target relationships. (Published by Cold Spring Harbor Laboratory Press.)
Databáze:	MEDLINE
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