Improving plant gene regulatory network inference by integrative analysis of multi-omics and high resolution data sets

Yichun Qian, Shao shan Carol Huang

Research output: Contribution to journalReview article

Abstract

Gene regulatory networks (GRNs) model the interactions between gene expression regulators and their targets that mediate a myriad of biological functions. Constructing GRNs that integrate multiple data types at increased resolution is improving our understanding of the complex regulatory mechanisms controlling different biological processes in plants. Going beyond transcription factor binding and transcriptome profiles, GRNs that incorporate multiple data types, including chromatin accessibility and long-range chromatin interaction, transcription factor binding site motifs, microRNA, ribosome-associated RNA, and proteomic profiles, were constructed for several cell types and multiple species. The rise of single-cell RNA-seq applications in plants opens up possibilities for studying cell type–specific GRNs in the processes of cell differentiation, development, and responses to the environment. Applications of high-throughput reporter assays and genome editing technologies allow large-scale validation of GRNs. Future advances in refining plant GRNs will most likely involve integration of multi-omics single-cell data and methods for cross-species model translation.

Original languageEnglish (US)
Pages (from-to)8-15
Number of pages8
JournalCurrent Opinion in Systems Biology
Volume22
DOIs
StatePublished - Aug 2020

Keywords

  • Data integration
  • Gene regulatory network
  • Plant genomics
  • Transcriptional regulation

ASJC Scopus subject areas

  • Modeling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Drug Discovery
  • Computer Science Applications
  • Applied Mathematics

Fingerprint Dive into the research topics of 'Improving plant gene regulatory network inference by integrative analysis of multi-omics and high resolution data sets'. Together they form a unique fingerprint.

Cite this