2021 journal article
Integrated omics networks reveal the temporal signaling events of brassinosteroid response in Arabidopsis
NATURE COMMUNICATIONS, 12(1).
MeSH headings : Arabidopsis / metabolism; Arabidopsis Proteins / genetics; Arabidopsis Proteins / metabolism; Brassinosteroids / metabolism; Cell Division; DNA-Binding Proteins / genetics; DNA-Binding Proteins / metabolism; Gene Expression Regulation, Plant; Nuclear Proteins / metabolism; Plant Growth Regulators / metabolism; Protein Kinases / genetics; Protein Kinases / metabolism; Proteomics; Seedlings / metabolism; Signal Transduction; Steroids, Heterocyclic; Transcription Factors / metabolism
TL;DR:
By integrating multiple omics datasets and inferring networks, the authors profile BR signaling in Arabidopsis and characterize BRONTOSAURUS, a BR-regulated transcription factor that impacts cell division in roots.
(via Semantic Scholar)
open access via www.nature.com (publisher PDF)
UN Sustainable Development Goal Categories
2. Zero Hunger
(Web of Science)
13. Climate Action
(Web of Science)
Source: Web Of Science
Added: October 26, 2021
AbstractBrassinosteroids (BRs) are plant steroid hormones that regulate cell division and stress response. Here we use a systems biology approach to integrate multi-omic datasets and unravel the molecular signaling events of BR response in Arabidopsis. We profile the levels of 26,669 transcripts, 9,533 protein groups, and 26,617 phosphorylation sites from Arabidopsis seedlings treated with brassinolide (BL) for six different lengths of time. We then construct a network inference pipeline called Spatiotemporal Clustering and Inference of Omics Networks (SC-ION) to integrate these data. We use our network predictions to identify putative phosphorylation sites on BES1 and experimentally validate their importance. Additionally, we identify BRONTOSAURUS (BRON) as a transcription factor that regulates cell division, and we show that BRON expression is modulated by BR-responsive kinases and transcription factors. This work demonstrates the power of integrative network analysis applied to multi-omic data and provides fundamental insights into the molecular signaling events occurring during BR response.