Evidence map›Paper›PMID 37719229›Full record

ArticleFrontiers in plant science2023

Comparative transcriptional and co-expression network analysis of two upland cotton accessions with extreme phenotypic differences reveals molecular mechanisms of fiber development.

Jiasen He, Zhongyang Xu, Muhammad Tehseen Azhar, Zhen Zhang, Pengtao Li, Juwu Gong, Xiao Jiang, Senmiao Fan, Qun Ge, Youlu Yuan and 1 more

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Article in Frontiers in plant science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Jiasen HeNational Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Zhengzhou University, Zhengzhou Henan, China.
Zhongyang XuNational Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Zhengzhou University, Zhengzhou Henan, China.
Muhammad Tehseen AzharNational Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Zhengzhou University, Zhengzhou Henan, China.
Zhen ZhangNational Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China.
Pengtao LiNational Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Anyang Institute of Technology, Anyang, China.
Juwu GongNational Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China.
Xiao JiangNational Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China.
Senmiao FanNational Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China.
Qun GeNational Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China.
Youlu YuanNational Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China.
Haihong ShangNational Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Zhengzhou University, Zhengzhou Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Upland cotton ( Methods: Comparative transcriptomes are used to analyze transcriptome data and to screen for differentially expressed genes. STEM and WGCNA were used to screen for key genes involved in fiber development. qRT-PCR was performed to verify gene expression of selected DEGs and hub genes. Results: Two accessions of upland cotton with extreme phenotypic differences, namely EZ60 and ZR014121, were used to carry out RNA sequencing (RNA-seq) on fiber samples from different fiber development stages. The results identified 704, 376, 141, 269, 761, and 586 genes that were upregulated, and 1,052, 476, 355, 259, 702, and 847 genes that were downregulated at 0, 5, 10, 15, 20, and 25 days post anthesis, respectively. Similar expression patterns of DEGs were monitored using short time-series expression miner (STEM) analysis, and associated pathways of DEGs within profiles were investigated. In addition, weighted gene co-expression network analysis (WGCNA) identified five key modules in fiber development and screened 20 hub genes involved in the development of fibers. Discussion: Through the annotation of the genes, it was found that the excessive expression of resistance-related genes in the early fiber development stages affects the fiber yield, whereas the sustained expression of cell elongation-related genes is critical for long fibers. This study provides new information that can be used to improve fibers in newly developed upland cotton genotypes.

Indexed as

DEGsfiber developmentGossypium hirsutumRNA-SeqWGCNA

Identifiers

PMID37719229
PMCPMC10502173

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