Cell-Type-Specific Profiling of the Arabidopsis thaliana Membrane Protein-Encoding Genes

Author:

Cervantes-Pérez Sergio Alan,Libault Marc

Abstract

Membrane proteins work in large complexes to perceive and transduce external signals and to trigger a cellular response leading to the adaptation of the cells to their environment. Biochemical assays have been extensively used to reveal the interaction between membrane proteins. However, such analyses do not reveal the unique and complex composition of the membrane proteins of the different plant cell types. Here, we conducted a comprehensive analysis of the expression of Arabidopsis membrane proteins in the different cell types composing the root. Specifically, we analyzed the expression of genes encoding membrane proteins interacting in large complexes. We found that the transcriptional profiles of membrane protein-encoding genes differ between Arabidopsis root cell types. This result suggests that different cell types are characterized by specific sets of plasma membrane proteins, which are likely a reflection of their unique biological functions and interactions. To further explore the complexity of the Arabidopsis root cell membrane proteomes, we conducted a co-expression analysis of genes encoding interacting membrane proteins. This study confirmed previously reported interactions between membrane proteins, suggesting that the co-expression of genes at the single cell-type level can be used to support protein network predictions.

Funder

National Science Foundation

United States Department of Agriculture

Publisher

MDPI AG

Subject

Filtration and Separation,Chemical Engineering (miscellaneous),Process Chemistry and Technology

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. FER meets the Nod factor pathway;Nature Plants;2023-09-25

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3