Literature DB >> 31345953

Enhanced Maps of Transcription Factor Binding Sites Improve Regulatory Networks Learned from Accessible Chromatin Data.

Shubhada R Kulkarni1,2,3, D Marc Jones1,2,3, Klaas Vandepoele4,2,3.   

Abstract

Determining where transcription factors (TFs) bind in genomes provides insight into which transcriptional programs are active across organs, tissue types, and environmental conditions. Recent advances in high-throughput profiling of regulatory DNA have yielded large amounts of information about chromatin accessibility. Interpreting the functional significance of these data sets requires knowledge of which regulators are likely to bind these regions. This can be achieved by using information about TF-binding preferences, or motifs, to identify TF-binding events that are likely to be functional. Although different approaches exist to map motifs to DNA sequences, a systematic evaluation of these tools in plants is missing. Here, we compare four motif-mapping tools widely used in the Arabidopsis (Arabidopsis thaliana) research community and evaluate their performance using chromatin immunoprecipitation data sets for 40 TFs. Downstream gene regulatory network (GRN) reconstruction was found to be sensitive to the motif mapper used. We further show that the low recall of Find Individual Motif Occurrences, one of the most frequently used motif-mapping tools, can be overcome by using an Ensemble approach, which combines results from different mapping tools. Several examples are provided demonstrating how the Ensemble approach extends our view on transcriptional control for TFs active in different biological processes. Finally, a protocol is presented to effectively derive more complete cell type-specific GRNs through the integrative analysis of open chromatin regions, known binding site information, and expression data sets. This approach will pave the way to increase our understanding of GRNs in different cellular conditions.
© 2019 American Society of Plant Biologists. All Rights Reserved.

Entities:  

Mesh:

Substances:

Year:  2019        PMID: 31345953      PMCID: PMC6776849          DOI: 10.1104/pp.19.00605

Source DB:  PubMed          Journal:  Plant Physiol        ISSN: 0032-0889            Impact factor:   8.340


  63 in total

1.  Inference of transcriptional networks in Arabidopsis through conserved noncoding sequence analysis.

Authors:  Jan Van de Velde; Ken S Heyndrickx; Klaas Vandepoele
Journal:  Plant Cell       Date:  2014-07-02       Impact factor: 11.277

2.  A functional and evolutionary perspective on transcription factor binding in Arabidopsis thaliana.

Authors:  Ken S Heyndrickx; Jan Van de Velde; Congmao Wang; Detlef Weigel; Klaas Vandepoele
Journal:  Plant Cell       Date:  2014-10-31       Impact factor: 11.277

3.  RSAT matrix-clustering: dynamic exploration and redundancy reduction of transcription factor binding motif collections.

Authors:  Jaime Abraham Castro-Mondragon; Sébastien Jaeger; Denis Thieffry; Morgane Thomas-Chollier; Jacques van Helden
Journal:  Nucleic Acids Res       Date:  2017-07-27       Impact factor: 16.971

4.  Combining ATAC-seq with nuclei sorting for discovery of cis-regulatory regions in plant genomes.

Authors:  Zefu Lu; Brigitte T Hofmeister; Christopher Vollmers; Rebecca M DuBois; Robert J Schmitz
Journal:  Nucleic Acids Res       Date:  2017-04-07       Impact factor: 16.971

5.  MOODS: fast search for position weight matrix matches in DNA sequences.

Authors:  Janne Korhonen; Petri Martinmäki; Cinzia Pizzi; Pasi Rastas; Esko Ukkonen
Journal:  Bioinformatics       Date:  2009-09-22       Impact factor: 6.937

6.  Unraveling transcriptional control in Arabidopsis using cis-regulatory elements and coexpression networks.

Authors:  Klaas Vandepoele; Mauricio Quimbaya; Tine Casneuf; Lieven De Veylder; Yves Van de Peer
Journal:  Plant Physiol       Date:  2009-04-08       Impact factor: 8.340

7.  BLH1 and KNAT3 modulate ABA responses during germination and early seedling development in Arabidopsis.

Authors:  Dachan Kim; Young-Hyun Cho; Hojin Ryu; Yoonhee Kim; Tae-Houn Kim; Ildoo Hwang
Journal:  Plant J       Date:  2013-06-13       Impact factor: 6.417

8.  A transcription factor hierarchy defines an environmental stress response network.

Authors:  Liang Song; Shao-Shan Carol Huang; Aaron Wise; Rosa Castanon; Joseph R Nery; Huaming Chen; Marina Watanabe; Jerushah Thomas; Ziv Bar-Joseph; Joseph R Ecker
Journal:  Science       Date:  2016-11-04       Impact factor: 47.728

9.  Evolution of DNA-Binding Sites of a Floral Master Regulatory Transcription Factor.

Authors:  Jose M Muiño; Suzanne de Bruijn; Alice Pajoro; Koen Geuten; Martin Vingron; Gerco C Angenent; Kerstin Kaufmann
Journal:  Mol Biol Evol       Date:  2015-10-01       Impact factor: 16.240

10.  JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles.

Authors:  Anthony Mathelier; Oriol Fornes; David J Arenillas; Chih-Yu Chen; Grégoire Denay; Jessica Lee; Wenqiang Shi; Casper Shyr; Ge Tan; Rebecca Worsley-Hunt; Allen W Zhang; François Parcy; Boris Lenhard; Albin Sandelin; Wyeth W Wasserman
Journal:  Nucleic Acids Res       Date:  2015-11-03       Impact factor: 16.971

View more
  5 in total

1.  Prediction of condition-specific regulatory genes using machine learning.

Authors:  Qi Song; Jiyoung Lee; Shamima Akter; Matthew Rogers; Ruth Grene; Song Li
Journal:  Nucleic Acids Res       Date:  2020-06-19       Impact factor: 16.971

2.  Integrative inference of transcriptional networks in Arabidopsis yields novel ROS signalling regulators.

Authors:  Inge De Clercq; Jan Van de Velde; Xiaopeng Luo; Li Liu; Veronique Storme; Michiel Van Bel; Robin Pottie; Dries Vaneechoutte; Frank Van Breusegem; Klaas Vandepoele
Journal:  Nat Plants       Date:  2021-04-12       Impact factor: 15.793

3.  Single-Cell Transcriptome and Network Analyses Unveil Key Transcription Factors Regulating Mesophyll Cell Development in Maize.

Authors:  Shentong Tao; Peng Liu; Yining Shi; Yilong Feng; Jingjing Gao; Lifen Chen; Aicen Zhang; Xuejiao Cheng; Hairong Wei; Tao Zhang; Wenli Zhang
Journal:  Genes (Basel)       Date:  2022-02-20       Impact factor: 4.096

Review 4.  Considerations in the analysis of plant chromatin accessibility data.

Authors:  Kerry L Bubb; Roger B Deal
Journal:  Curr Opin Plant Biol       Date:  2020-02-26       Impact factor: 7.834

Review 5.  Beyond Trees: Regulons and Regulatory Motif Characterization.

Authors:  Xuhua Xia
Journal:  Genes (Basel)       Date:  2020-08-25       Impact factor: 4.096

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.