Literature DB >> 27128468

Mapping Transcriptional Networks in Plants: Data-Driven Discovery of Novel Biological Mechanisms.

Allison Gaudinier1, Siobhan M Brady1.   

Abstract

In plants, systems biology approaches have led to the generation of a variety of large data sets. Many of these data are created to elucidate gene expression profiles and their corresponding transcriptional regulatory mechanisms across a range of tissue types, organs, and environmental conditions. In an effort to map the complexity of this transcriptional regulatory control, several types of experimental assays have been used to map transcriptional regulatory networks. In this review, we discuss how these methods can be best used to identify novel biological mechanisms by focusing on the appropriate biological context. Translating network biology back to gene function in the plant, however, remains a challenge. We emphasize the need for validation and insight into the underlying biological processes to successfully exploit systems approaches in an effort to determine the emergent properties revealed by network analyses.

Keywords:  chromatin; genetics; regulation; systems biology; transcription factor

Mesh:

Year:  2016        PMID: 27128468     DOI: 10.1146/annurev-arplant-043015-112205

Source DB:  PubMed          Journal:  Annu Rev Plant Biol        ISSN: 1543-5008            Impact factor:   26.379


  16 in total

Review 1.  Phytopathogen-induced changes to plant methylomes.

Authors:  Tarek Hewezi; Vince Pantalone; Morgan Bennett; C Neal Stewart; Tessa M Burch-Smith
Journal:  Plant Cell Rep       Date:  2017-07-29       Impact factor: 4.570

2.  The G-Box Transcriptional Regulatory Code in Arabidopsis.

Authors:  Daphne Ezer; Samuel J K Shepherd; Anna Brestovitsky; Patrick Dickinson; Sandra Cortijo; Varodom Charoensawan; Mathew S Box; Surojit Biswas; Katja E Jaeger; Philip A Wigge
Journal:  Plant Physiol       Date:  2017-09-01       Impact factor: 8.340

3.  IndeCut evaluates performance of network motif discovery algorithms.

Authors:  Mitra Ansariola; Molly Megraw; David Koslicki
Journal:  Bioinformatics       Date:  2018-05-01       Impact factor: 6.937

Review 4.  Future Challenges in Plant Systems Biology.

Authors:  Mikaël Lucas
Journal:  Methods Mol Biol       Date:  2022

5.  Glucose-Induced Trophic Shift in an Endosymbiont Dinoflagellate with Physiological and Molecular Consequences.

Authors:  Tingting Xiang; Robert E Jinkerson; Sophie Clowez; Cawa Tran; Cory J Krediet; Masayuki Onishi; Phillip A Cleves; John R Pringle; Arthur R Grossman
Journal:  Plant Physiol       Date:  2017-12-07       Impact factor: 8.340

6.  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

7.  Tissue-specific transcriptome profiling of the Arabidopsis inflorescence stem reveals local cellular signatures.

Authors:  Dongbo Shi; Virginie Jouannet; Javier Agustí; Verena Kaul; Victor Levitsky; Pablo Sanchez; Victoria V Mironova; Thomas Greb
Journal:  Plant Cell       Date:  2021-04-17       Impact factor: 11.277

8.  The Construction and Exploration of a Comprehensive MicroRNA Centered Regulatory Network in Foxtail Millet (Setaria italica L.).

Authors:  Yang Deng; Haolin Zhang; Hailong Wang; Guofang Xing; Biao Lei; Zheng Kuang; Yongxin Zhao; Congcong Li; Shaojun Dai; Xiaozeng Yang; Jianhua Wei; Jiewei Zhang
Journal:  Front Plant Sci       Date:  2022-05-06       Impact factor: 5.753

9.  Reverse engineering highlights potential principles of large gene regulatory network design and learning.

Authors:  Clément Carré; André Mas; Gabriel Krouk
Journal:  NPJ Syst Biol Appl       Date:  2017-06-22

Review 10.  Network-based approaches for understanding gene regulation and function in plants.

Authors:  Dae Kwan Ko; Federica Brandizzi
Journal:  Plant J       Date:  2020-08-28       Impact factor: 6.417

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