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Title: Using co-expression analysis and stress-based screens to uncover Arabidopsis peroxisomal proteins involved in drought response

Abstract

Peroxisomes are essential organelles that house a wide array of metabolic reactions important for plant growth and development. However, our knowledge regarding the role of peroxisomal proteins in various biological processes, including plant stress response, is still incomplete. Recent proteomic studies of plant peroxisomes significantly increased the number of known peroxisomal proteins and greatly facilitated the study of peroxisomes at the systems level. The objectives of this study were to determine whether genes that encode peroxisomal proteins with related functions are co-expressed in Arabidopsis and identify peroxisomal proteins involved in stress response using in silico analysis and mutant screens. Using microarray data from online databases, we performed hierarchical clustering analysis to generate a comprehensive view of transcript level changes for Arabidopsis peroxisomal genes during development and under abiotic and biotic stress conditions. Many genes involved in the same metabolic pathways exhibited co-expression, some genes known to be involved in stress response are regulated by the corresponding stress conditions, and function of some peroxisomal proteins could be predicted based on their coexpression pattern. Since drought caused expression changes to the highest number of genes that encode peroxisomal proteins, we subjected a subset of Arabidopsis peroxisomal mutants to a drought stress assay.more » Mutants of the LON2 protease and the photorespiratory enzyme hydroxypyruvate reductase 1 (HPR1) showed enhanced susceptibility to drought, suggesting the involvement of peroxisomal quality control and photorespiration in drought resistance. Lastly, our study provided a global view of how genes that encode peroxisomal proteins respond to developmental and environmental cues and began to reveal additional peroxisomal proteins involved in stress response, thus opening up new avenues to investigate the role of peroxisomes in plant adaptation to environmental stresses.« less

Authors:
 [1];  [1];  [2]
  1. Michigan State Univ., East Lansing, MI (United States)
  2. Iowa State Univ., Ames, IA (United States)
Publication Date:
Research Org.:
Michigan State Univ., East Lansing, MI (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1324983
Grant/Contract Number:  
FG02-91ER20021
Resource Type:
Accepted Manuscript
Journal Name:
PLoS ONE
Additional Journal Information:
Journal Volume: 10; Journal Issue: 9; Journal ID: ISSN 1932-6203
Publisher:
Public Library of Science
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; plant resistance to abiotic stress; arabidopsis thaliana; peroxisomes; drought adaptation; fluorescence imaging; chlorophyll; gene expression; leaves

Citation Formats

Li, Jiying, Hu, Jianping, and Bassham, Diane. Using co-expression analysis and stress-based screens to uncover Arabidopsis peroxisomal proteins involved in drought response. United States: N. p., 2015. Web. doi:10.1371/journal.pone.0137762.
Li, Jiying, Hu, Jianping, & Bassham, Diane. Using co-expression analysis and stress-based screens to uncover Arabidopsis peroxisomal proteins involved in drought response. United States. https://doi.org/10.1371/journal.pone.0137762
Li, Jiying, Hu, Jianping, and Bassham, Diane. Mon . "Using co-expression analysis and stress-based screens to uncover Arabidopsis peroxisomal proteins involved in drought response". United States. https://doi.org/10.1371/journal.pone.0137762. https://www.osti.gov/servlets/purl/1324983.
@article{osti_1324983,
title = {Using co-expression analysis and stress-based screens to uncover Arabidopsis peroxisomal proteins involved in drought response},
author = {Li, Jiying and Hu, Jianping and Bassham, Diane},
abstractNote = {Peroxisomes are essential organelles that house a wide array of metabolic reactions important for plant growth and development. However, our knowledge regarding the role of peroxisomal proteins in various biological processes, including plant stress response, is still incomplete. Recent proteomic studies of plant peroxisomes significantly increased the number of known peroxisomal proteins and greatly facilitated the study of peroxisomes at the systems level. The objectives of this study were to determine whether genes that encode peroxisomal proteins with related functions are co-expressed in Arabidopsis and identify peroxisomal proteins involved in stress response using in silico analysis and mutant screens. Using microarray data from online databases, we performed hierarchical clustering analysis to generate a comprehensive view of transcript level changes for Arabidopsis peroxisomal genes during development and under abiotic and biotic stress conditions. Many genes involved in the same metabolic pathways exhibited co-expression, some genes known to be involved in stress response are regulated by the corresponding stress conditions, and function of some peroxisomal proteins could be predicted based on their coexpression pattern. Since drought caused expression changes to the highest number of genes that encode peroxisomal proteins, we subjected a subset of Arabidopsis peroxisomal mutants to a drought stress assay. Mutants of the LON2 protease and the photorespiratory enzyme hydroxypyruvate reductase 1 (HPR1) showed enhanced susceptibility to drought, suggesting the involvement of peroxisomal quality control and photorespiration in drought resistance. Lastly, our study provided a global view of how genes that encode peroxisomal proteins respond to developmental and environmental cues and began to reveal additional peroxisomal proteins involved in stress response, thus opening up new avenues to investigate the role of peroxisomes in plant adaptation to environmental stresses.},
doi = {10.1371/journal.pone.0137762},
journal = {PLoS ONE},
number = 9,
volume = 10,
place = {United States},
year = {Mon Sep 14 00:00:00 EDT 2015},
month = {Mon Sep 14 00:00:00 EDT 2015}
}

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