Literature DB >> 31200084

De novo transcriptome assembly and co-expression network analysis of Cynanchum thesioides: Identification of genes involved in resistance to drought stress.

Xiaoyan Zhang1, Zhongren Yang1, Zhi Li2, Fenglan Zhang3, Lizhen Hao1.   

Abstract

Cynanchum thesioides are upright, xerophytic shrubs that are widely distributed in arid and semi-arid areas of China, North Korea, Mongolia and Siberia. To date, little is known about the molecular mechanisms of drought resistance in C. thesioides. To better understand drought resistance, we used transcriptome analysis and Illumina sequencing technology on C. thesioides, to identify drought-responsive genes. Using de novo assembly 55,268 unigenes were identified from 207.58 Gb of clean data. Amongst these, 36,265 were annotated with gene descriptions, conserved domains, gene ontology terms and metabolic pathways. The sequencing results showed that genes that were differentially expressed (DEGs) under drought stress were enriched in pathways such as carbon metabolism, starch and sucrose metabolism, amino acid biosynthesis, phenylpropanoid biosynthesis and plant hormone signal transduction. Moreover, many functional genes were up-regulated under severe drought stress to enhance tolerance. Weighted gene co-expression network analysis showed that there were key hub genes related to drought stress. Hundreds of candidate genes were identified under severe drought stress, including transcriptional factors such as MYB, G2-like, ERF, C2H2, NAC, NF-X1, GRF, HD-ZIP, HB-other, HSF, C3H, GRAS, WRKY, bHLH and Trihelix. These data are a valuable resource for further investigation into the molecular mechanism for drought stress in C. thesioides and will facilitate exploration of drought resistance genes.
Copyright © 2019. Published by Elsevier B.V.

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Keywords:  Cynanchum thesioides (Freyn) K. Schum.; Cynanchum thesioides (Freyn) K. Schum. var. australe (maxim.) Tsiang et P. T. Li.; Differentially expressed genes; Drought resistance; Illumina sequencing; Weighted gene co-expression network

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Year:  2019        PMID: 31200084     DOI: 10.1016/j.gene.2019.05.055

Source DB:  PubMed          Journal:  Gene        ISSN: 0378-1119            Impact factor:   3.688


  4 in total

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