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, 9 (1), 13917

RNAseq Analysis Reveals Drought-Responsive Molecular Pathways With Candidate Genes and Putative Molecular Markers in Root Tissue of Wheat

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RNAseq Analysis Reveals Drought-Responsive Molecular Pathways With Candidate Genes and Putative Molecular Markers in Root Tissue of Wheat

Mir Asif Iquebal et al. Sci Rep.

Abstract

Drought is one of the major impediments in wheat productivity. Traditional breeding and marker assisted QTL introgression had limited success. Available wheat genomic and RNA-seq data can decipher novel drought tolerance mechanisms with putative candidate gene and marker discovery. Drought is first sensed by root tissue but limited information is available about how roots respond to drought stress. In this view, two contrasting genotypes, namely, NI5439 41 (drought tolerant) and WL711 (drought susceptible) were used to generate ~78.2 GB data for the responses of wheat roots to drought. A total of 45139 DEGs, 13820 TF, 288 miRNAs, 640 pathways and 435829 putative markers were obtained. Study reveals use of such data in QTL to QTN refinement by analysis on two model drought-responsive QTLs on chromosome 3B in wheat roots possessing 18 differentially regulated genes with 190 sequence variants (173 SNPs and 17 InDels). Gene regulatory networks showed 69 hub-genes integrating ABA dependent and independent pathways controlling sensing of drought, root growth, uptake regulation, purine metabolism, thiamine metabolism and antibiotics pathways, stomatal closure and senescence. Eleven SSR markers were validated in a panel of 18 diverse wheat varieties. For effective future use of findings, web genomic resources were developed. We report RNA-Seq approach on wheat roots describing the drought response mechanisms under field drought conditions along with genomic resources, warranted in endeavour of wheat productivity.

Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Venn diagram showing shared and unique DEGs of wheat root transcriptome associated with drought.
Figure 2
Figure 2
(A) Quantitative real-time PCR analysis of selected transcripts; (B) Correlation between magnitude of gene expression by FPKM and qPCR method.
Figure 3
Figure 3
Gene regulatory network of wheat root transcriptome associated with drought. Figures A, B, C and D represents the network (TC:TD), (SD:TD), (SC:SD), and (SC:TC), respectively.
Figure 4
Figure 4
Validation of identified genic SSRs localized on differentially expressed transcripts in wheat genotypes: (A) pwtssr 3, (B) pwtssr 5, (C) pwtssr 6, (D) pwtssr 9, (E) pwtssr 10, (F) pwtssr 12, (G) pwtssr 14, (H) pwtssr 16, (I) pwtssr 17, (J) pwtssr 19, (K) pwtssr 20; M is 100 bp ladder used as a standard marker.
Figure 5
Figure 5
Venn diagram of common and unique variants obtained from (A) de novo transcriptome assembly and (B) wheat reference genome.
Figure 6
Figure 6
Chromosome wise SNP distribution over 21 chromosomes of wheat by circular plot. Grey dots (drought tolerant) and red dots (drought susceptible).
Figure 7
Figure 7
Web interface of WDRoTDb showing search option for candidate genes, variants, transcripts expression profile and miRNA targets.

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