Behavior and possible function of <i>Arabidopsis</i> BES1/BZR1 homolog 2 in brassinosteroid signaling

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ABSTRACT

Two key transcription factors (TFs) in brassinosteroid (BR) signaling BRASSINOSTEROID INSENSITIVE 1-EMS-SUPPRESSOR 1 (BES1) and BRASSINAZOLE RESISTANT 1 (BZR1), belong to a small family with four BES1/BZR1 homologs (BEH1–4). To date, in contrast to the wealth of knowledge regarding BES1 and BZR1, little is known about BEH1–4. Here, we show that BEH2 was expressed preferentially in the roots and leaf margins including serrations, which was quite different from another member BEH4, and that BRs downregulated BEH2 through a module containing GSK3-like kinases and BES1/BZR1 TFs, among which BES1, rather than BZR1, contributed to this process. In addition, BEH2 consistently existed in the nucleus, suggesting that its subcellular localization is not under BR-dependent nuclear-cytoplasmic shuttling control. Furthermore, gene ontology analysis on RNA-seq data indicated that BEH2 may be implicated in stress response and photosynthesis. These findings might assist in the future elucidation of the molecular mechanisms underlying BR signaling.

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edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

Mark Robinson, Davis J. McCarthy, Gordon K. Smyth (2009)

Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au

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featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

Y. Liao, G K Smyth, W Shi (2014)

Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.

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g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update)

Uku Raudvere, Liis Kolberg, Ivan Kuzmin … (2019)

Abstract Biological data analysis often deals with lists of genes arising from various studies. The g:Profiler toolset is widely used for finding biological categories enriched in gene lists, conversions between gene identifiers and mappings to their orthologs. The mission of g:Profiler is to provide a reliable service based on up-to-date high quality data in a convenient manner across many evidence types, identifier spaces and organisms. g:Profiler relies on Ensembl as a primary data source and follows their quarterly release cycle while updating the other data sources simultaneously. The current update provides a better user experience due to a modern responsive web interface, standardised API and libraries. The results are delivered through an interactive and configurable web design. Results can be downloaded as publication ready visualisations or delimited text files. In the current update we have extended the support to 467 species and strains, including vertebrates, plants, fungi, insects and parasites. By supporting user uploaded custom GMT files, g:Profiler is now capable of analysing data from any organism. All past releases are maintained for reproducibility and transparency. The 2019 update introduces an extensive technical rewrite making the services faster and more flexible. g:Profiler is freely available at https://biit.cs.ut.ee/gprofiler.

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Author and article information

Journal

Journal ID (nlm-ta): Plant Signal Behav

Journal ID (iso-abbrev): Plant Signal Behav

Title: Plant Signaling & Behavior

Publisher: Taylor & Francis

ISSN (Print): 1559-2316

ISSN (Electronic): 1559-2324

Publication date (Electronic, pub): 13 June 2022

Publication date (Electronic, collection): 2022

Publication date PMC-release: 13 June 2022

Volume: 17

Issue: 1

Electronic Location Identifier: 2084277

Affiliations

[a ]The United Graduate School of Agricultural Sciences, Kagoshima University; , Kagoshima, Japan

[b ]Graduate School of Life and Environmental Sciences, Kyoto Prefectural University; , Kyoto, Japan

[c ]Department of Japanese Food Culture, Faculty of Letters, Kyoto Prefectural University; , Kyoto, Japan

Author notes

CONTACT Shigehisa Okamoto okamoto@ 123456agri.kagoshima-u.ac.jp The United Graduate School of Agricultural Sciences, Kagoshima University; , Kagoshima, Japan

Article

Publisher ID: 2084277

DOI: 10.1080/15592324.2022.2084277

PMC ID: 9196799

PubMed ID: 35695417

SO-VID: 08cf68d2-e9cd-4f56-bd76-858f5fcf0171

License:

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Behavior and possible function of Arabidopsis BES1/BZR1 homolog 2 in brassinosteroid signaling

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Arabidopsis genomics

Most cited references 50

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update)

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