Literature DB >> 28957653

Identification of Human Lineage-Specific Transcriptional Coregulators Enabled by a Glossary of Binding Modules and Tunable Genomic Backgrounds.

Luca Mariani1, Kathryn Weinand1, Anastasia Vedenko1, Luis A Barrera2, Martha L Bulyk3.   

Abstract

Transcription factors (TFs) control cellular processes by binding specific DNA motifs to modulate gene expression. Motif enrichment analysis of regulatory regions can identify direct and indirect TF binding sites. Here, we created a glossary of 108 non-redundant TF-8mer "modules" of shared specificity for 671 metazoan TFs from publicly available and new universal protein binding microarray data. Analysis of 239 ENCODE TF chromatin immunoprecipitation sequencing datasets and associated RNA sequencing profiles suggest the 8mer modules are more precise than position weight matrices in identifying indirect binding motifs and their associated tethering TFs. We also developed GENRE (genomically equivalent negative regions), a tunable tool for construction of matched genomic background sequences for analysis of regulatory regions. GENRE outperformed four state-of-the-art approaches to background sequence construction. We used our TF-8mer glossary and GENRE in the analysis of the indirect binding motifs for the co-occurrence of tethering factors, suggesting novel TF-TF interactions. We anticipate that these tools will aid in elucidating tissue-specific gene-regulatory programs.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  ChIP-seq analysis; DNA binding specificity; ENCODE; background construction; motif enrichment; transcription factors

Mesh:

Substances:

Year:  2017        PMID: 28957653      PMCID: PMC5657590          DOI: 10.1016/j.cels.2017.06.015

Source DB:  PubMed          Journal:  Cell Syst        ISSN: 2405-4712            Impact factor:   10.304


  78 in total

1.  Compact, universal DNA microarrays to comprehensively determine transcription-factor binding site specificities.

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4.  A cluster separation measure.

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5.  Transcription factor AP1 potentiates chromatin accessibility and glucocorticoid receptor binding.

Authors:  Simon C Biddie; Sam John; Pete J Sabo; Robert E Thurman; Thomas A Johnson; R Louis Schiltz; Tina B Miranda; Myong-Hee Sung; Saskia Trump; Stafford L Lightman; Charles Vinson; John A Stamatoyannopoulos; Gordon L Hager
Journal:  Mol Cell       Date:  2011-07-08       Impact factor: 17.970

6.  Assessment of compositional heterogeneity within and between eukaryotic genomes.

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7.  Principles of dimer-specific gene regulation revealed by a comprehensive characterization of NF-κB family DNA binding.

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8.  A Network Model to Describe the Terminal Differentiation of B Cells.

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9.  An expansive human regulatory lexicon encoded in transcription factor footprints.

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10.  Goldmine integrates information placing genomic ranges into meaningful biological contexts.

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  18 in total

1.  Transcriptional Silencers in Drosophila Serve a Dual Role as Transcriptional Enhancers in Alternate Cellular Contexts.

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Journal:  Mol Cell       Date:  2019-11-05       Impact factor: 17.970

2.  Bispecific Forkhead Transcription Factor FoxN3 Recognizes Two Distinct Motifs with Different DNA Shapes.

Authors:  Julia M Rogers; Colin T Waters; Tom C M Seegar; Sanchez M Jarrett; Amelia N Hallworth; Stephen C Blacklow; Martha L Bulyk
Journal:  Mol Cell       Date:  2019-02-27       Impact factor: 17.970

3.  EP300 Selectively Controls the Enhancer Landscape of MYCN-Amplified Neuroblastoma.

Authors:  Adam D Durbin; Tingjian Wang; Virangika K Wimalasena; Mark W Zimmerman; Deyao Li; Neekesh V Dharia; Luca Mariani; Noha A M Shendy; Stephanie Nance; Anand G Patel; Ying Shao; Maya Mundada; Lily Maxham; Paul M C Park; Logan H Sigua; Ken Morita; Amy Saur Conway; Amanda L Robichaud; Antonio R Perez-Atayde; Melissa J Bikowitz; Taylor R Quinn; Olaf Wiest; John Easton; Ernst Schönbrunn; Martha L Bulyk; Brian J Abraham; Kimberly Stegmaier; A Thomas Look; Jun Qi
Journal:  Cancer Discov       Date:  2022-03-01       Impact factor: 39.397

4.  Anterior-posterior patterning of segments in Anopheles stephensi offers insights into the transition from sequential to simultaneous segmentation in holometabolous insects.

Authors:  Alys M Cheatle Jarvela; Catherine S Trelstad; Leslie Pick
Journal:  J Exp Zool B Mol Dev Evol       Date:  2021-11-03       Impact factor: 2.368

5.  Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework.

Authors:  Jinyu Yang; Anjun Ma; Adam D Hoppe; Cankun Wang; Yang Li; Chi Zhang; Yan Wang; Bingqiang Liu; Qin Ma
Journal:  Nucleic Acids Res       Date:  2019-09-05       Impact factor: 16.971

6.  Divergence in DNA Specificity among Paralogous Transcription Factors Contributes to Their Differential In Vivo Binding.

Authors:  Ning Shen; Jingkang Zhao; Joshua L Schipper; Yuning Zhang; Tristan Bepler; Dan Leehr; John Bradley; John Horton; Hilmar Lapp; Raluca Gordan
Journal:  Cell Syst       Date:  2018-03-28       Impact factor: 10.304

Review 7.  Diversification of transcription factor-DNA interactions and the evolution of gene regulatory networks.

Authors:  Julia M Rogers; Martha L Bulyk
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2018-04-25

8.  Common variants in signaling transcription-factor-binding sites drive phenotypic variability in red blood cell traits.

Authors:  Avik Choudhuri; Eirini Trompouki; Brian J Abraham; Leandro M Colli; Kian Hong Kock; William Mallard; Min-Lee Yang; Divya S Vinjamur; Alireza Ghamari; Audrey Sporrij; Karen Hoi; Barbara Hummel; Sonja Boatman; Victoria Chan; Sierra Tseng; Satish K Nandakumar; Song Yang; Asher Lichtig; Michael Superdock; Seraj N Grimes; Teresa V Bowman; Yi Zhou; Shinichiro Takahashi; Roby Joehanes; Alan B Cantor; Daniel E Bauer; Santhi K Ganesh; John Rinn; Paul S Albert; Martha L Bulyk; Stephen J Chanock; Richard A Young; Leonard I Zon
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9.  A Comprehensive Drosophila melanogaster Transcription Factor Interactome.

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Journal:  Cell Rep       Date:  2019-04-16       Impact factor: 9.423

10.  MEIRLOP: improving score-based motif enrichment by incorporating sequence bias covariates.

Authors:  Nathaniel P Delos Santos; Lorane Texari; Christopher Benner
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