Abstract

BackgroundBrassica juncea var. Varuna is an economically important oilseed crop of family Brassicaceae which is vulnerable to abiotic stresses at specific stages in its life cycle. Till date no attempts have been made to elucidate genome-wide changes in its transcriptome against high temperature or drought stress. To gain global insights into genes, transcription factors and kinases regulated by these stresses and to explore information on coding transcripts that are associated with traits of agronomic importance, we utilized a combinatorial approach of next generation sequencing and de-novo assembly to discover B. juncea transcriptome associated with high temperature and drought stresses.ResultsWe constructed and sequenced three transcriptome libraries namely Brassica control (BC), Brassica high temperature stress (BHS) and Brassica drought stress (BDS). More than 180 million purity filtered reads were generated which were processed through quality parameters and high quality reads were assembled de-novo using SOAPdenovo assembler. A total of 77750 unique transcripts were identified out of which 69,245 (89%) were annotated with high confidence. We established a subset of 19110 transcripts, which were differentially regulated by either high temperature and/or drought stress. Furthermore, 886 and 2834 transcripts that code for transcription factors and kinases, respectively, were also identified. Many of these were responsive to high temperature, drought or both stresses. Maximum number of up-regulated transcription factors in high temperature and drought stress belonged to heat shock factors (HSFs) and dehydration responsive element-binding (DREB) families, respectively. We also identified 239 metabolic pathways, which were perturbed during high temperature and drought treatments. Analysis of gene ontologies associated with differentially regulated genes forecasted their involvement in diverse biological processes.ConclusionsOur study provides first comprehensive discovery of B. juncea transcriptome under high temperature and drought stress conditions. Transcriptome resource generated in this study will enhance our understanding on the molecular mechanisms involved in defining the response of B. juncea against two important abiotic stresses. Furthermore this information would benefit designing of efficient crop improvement strategies for tolerance against conditions of high temperature regimes and water scarcity.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-014-0405-1) contains supplementary material, which is available to authorized users.

Highlights

  • Quality filtering and de-novo assembly Three transcriptome libraries were constructed using Poly A+ RNA isolated from hydroponically grown 7-day old whole seedlings that were kept under controlled conditions (BC) or challenged with high temperature (BHS) or drought (BDS)

  • High throughput sequencing of transcriptome libraries using Illumina GA IIx platform generated an aggregate of 183.7 million purity filtered reads amounting to 15.2 Gb of data

  • Maximum number of reads was obtained in control (BC; ~77.9 million) followed by high temperature stress (BHS; ~65.6 million) and drought stress (BDS; ~40.1 million) samples

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Summary

Introduction

To gain global insights into genes, transcription factors and kinases regulated by these stresses and to explore information on coding transcripts that are associated with traits of agronomic importance, we utilized a combinatorial approach of generation sequencing and de-novo assembly to discover B. juncea transcriptome associated with high temperature and drought stresses. Because of the multigenic nature of the trait, it is important to collate information on all the molecular factors that orchestrate together to constitute a cellular state of stress tolerance. Many of these factors are co-expressed in response to a stimulus and genomic scale investigations using either microarray or cDNA sequencing are often helpful in their identification. Because RNASeq is an open-ended approach, it has been widely used to sequence and assemble de-novo transcriptome of various organisms [7,8,9]

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