Transcriptomics and co-expression networks reveal tissue-specific responses and regulatory hubs under mild and severe drought in papaya (Carica papaya L.)

Abstract

Plants respond to drought stress through the ABA dependent and independent pathways, which in turn modulate transcriptional regulatory hubs. Here, we employed Illumina RNA-Seq to analyze a total of 18 cDNA libraries from leaves, sap, and roots of papaya plants under drought stress. Reference and de novo transcriptomic analyses identified 8,549 and 6,089 drought-responsive genes and unigenes, respectively. Core sets of 6 and 34 genes were simultaneously up- or down-regulated, respectively, in all stressed samples. Moreover, GO enrichment analysis revealed that under moderate drought stress, processes related to cell cycle and DNA repair were up-regulated in leaves and sap; while responses to abiotic stress, hormone signaling, sucrose metabolism, and suberin biosynthesis were up-regulated in roots. Under severe drought stress, biological processes related to abiotic stress, hormone signaling, and oxidation-reduction were up-regulated in all tissues. Moreover, similar biological processes were commonly down-regulated in all stressed samples. Furthermore, co-expression network analysis revealed three and eight transcriptionally regulated modules in leaves and roots, respectively. Seventeen stress-related TFs were identified, potentially serving as main regulatory hubs in leaves and roots. Our findings provide insight into the molecular responses of papaya plant to drought, which could contribute to the improvement of this important tropical crop.

Identification, evolution and alternative splicing profile analysis of Serine/Arginine-Rich Protein Splicing Factors (SR Proteins) in poplar, Arabidopsis, grape, and papaya

“…To explore the expression level characteristics of SR genes under different abiotic stresses in different tissues, we obtained the expression level data of the poplar and papaya SR genes from RNA-seq data [34,35], and Arabidopsis and grape chip data GSE5620, GSE5621, GSE5623, GSE5624, GSE5628 and GSE31594 were obtained from the NCBI GEO database. The log2-transformed fold-change values were used for creating the heatmap.…”

“…Since abiotic stress may adversely affect plant growth and development, stresstolerant gene studies of plants are important. We obtained microarray (Arabidopsis and grape) and RNA-seq (poplar and papaya) data under various stress conditions from different tissues of the four dicots [34,35]. The results showed that only the CpRSZ20 gene was not expressed, and the rest were expressed (Figure 7).…”

“…All authors read and approved the final manuscript. The expression level data of the poplar and papaya SR genes was obtained from RNA-seq data [34,35], and Arabidopsis and grape chip data GSE5620, GSE5621, GSE5623, GSE5624, GSE5628 and GSE31594 were obtained from the NCBI GEO database was similar to the SC subfamily but had an N-terminal extension that is rich in Arg, Pro, Ser, Gly and Tyr residues. Proteins of the plant-specific RS2Z subfamily had two Zn knuckles and an additional SP-rich region after the RS domain.…”

Gene co-expression network analysis to identify critical modules and candidate genes of drought-resistance in wheat

“…The cloned gl14 gene was confirmed responsible for epicuticular wax biogenesis. Through co-expression network analysis, Gamboa-Tuz [ 38 ] also identified several abiotic stress-related hub genes in papaya from roots and leaves under drought stress. However, WGCNA has not been adapted to systematically research hub genes correlated with drought stress in wheat.…”

Gene coexpression network analysis and tissue-specific profiling of gene expression in jute (Corchorus capsularis L.)

“…With the rapid development of high-throughput sequencing technology and bioinformatics, tissue-specific gene expression and regulation analyses have been carried out on many crops [9][10][11]. In particular, weighted gene coexpression network analysis (WGCNA) has recently been widely used to predict the functional roles of gene coexpression modules and individual genes underlying the differences between tissues [12][13][14]. For example, WGCNA or comparative transcriptomic analysis revealed coexpression modules and dynamics in gene expression involved in stress response [12], seed development [13], and floral bud development [14] in various tissues of crop plants, etc.. WGCNA has become a fascinating integrated and systematic genome-wide approach, focusing on elucidating biological networks and gene function [15].…”