Dataset Information

Transcriptomics profiling of Indian mustard (Brassica juncea) under arsenate stress identifies key candidate genes and regulatory pathways.

ABSTRACT: Arsenic (As) is a non-essential element, a groundwater pollutant, whose uptake by plants produces toxic effects. The use of As-contaminated groundwater for irrigation can affect the crop productivity. Realizing the importance of the Brassica juncea as a crop plant in terms of oil-yield, there is a need to unravel mechanistic details of response to As stress and identify key functional genes and pathways. In this research, we studied time-dependent (4-96 h) transcriptome changes in roots and shoots of B. juncea under arsenate [As(V)] stress using Agilent platform. Among the whole transcriptome profiled genes, a total of 1,285 genes showed significant change in expression pattern upon As(V) exposure. The differentially expressed genes were categorized to various signaling pathways including hormones (jasmonate, abscisic acid, auxin, and ethylene) and kinases. Significant effects were also noticed on genes related to sulfur, nitrogen, CHO, and lipid metabolisms along with photosynthesis. Biochemical assays were conducted using specific inhibitors of glutathione and jasmonate biosynthesis, and kinases. The inhibitor studies revealed interconnection among sulfur metabolism, jasmonate, and kinase signaling pathways. In addition, various transposons also constituted a part of the altered transcriptome. Lastly, we profiled a set of key functional up- and down-regulated genes using real-time RT-PCR, which could act as an early indicators of the As stress.

SUBMITTER: Srivastava S

PROVIDER: S-EPMC4541038 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Transcriptomics profiling of Indian mustard (Brassica juncea) under arsenate stress identifies key candidate genes and regulatory pathways.

Srivastava Sudhakar S Srivastava Ashish K AK Sablok Gaurav G Deshpande Tejaswini U TU Suprasanna Penna P

Frontiers in plant science 20150819

Arsenic (As) is a non-essential element, a groundwater pollutant, whose uptake by plants produces toxic effects. The use of As-contaminated groundwater for irrigation can affect the crop productivity. Realizing the importance of the Brassica juncea as a crop plant in terms of oil-yield, there is a need to unravel mechanistic details of response to As stress and identify key functional genes and pathways. In this research, we studied time-dependent (4-96 h) transcriptome changes in roots and shoo ...[more]

PMID: 26347763

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Project description:Low temperature is a major abiotic stress that impedes plant growth and development. Brassica juncea is an economically important oil seed crop and is sensitive to freezing stress during pod filling subsequently leading to abortion of seeds. To understand the cold stress mediated global perturbations in gene expression, whole transcriptome of B. juncea siliques that were exposed to sub-optimal temperature was sequenced. Manually self-pollinated siliques at different stages of development were subjected to either short (6 h) or long (12 h) durations of chilling stress followed by construction of RNA-seq libraries and deep sequencing using Illumina's NGS platform. De-novo assembly of B. juncea transcriptome resulted in 133,641 transcripts, whose combined length was 117 Mb and N50 value was 1428 bp. We identified 13,342 differentially regulated transcripts by pair-wise comparison of 18 transcriptome libraries. Hierarchical clustering along with Spearman correlation analysis identified that the differentially expressed genes segregated in two major clusters representing early (5-15 DAP) and late stages (20-30 DAP) of silique development. Further analysis led to the discovery of sub-clusters having similar patterns of gene expression. Two of the sub-clusters (one each from the early and late stages) comprised of genes that were inducible by both the durations of cold stress. Comparison of transcripts from these clusters led to identification of 283 transcripts that were commonly induced by cold stress, and were referred to as "core cold-inducible" transcripts. Additionally, we found that 689 and 100 transcripts were specifically up-regulated by cold stress in early and late stages, respectively. We further explored the expression patterns of gene families encoding for transcription factors (TFs), transcription regulators (TRs) and kinases, and found that cold stress induced protein kinases only during early silique development. We validated the digital gene expression profiles of selected transcripts by qPCR and found a high degree of concordance between the two analyses. To our knowledge this is the first report of transcriptome sequencing of cold-stressed B. juncea siliques. The data generated in this study would be a valuable resource for not only understanding the cold stress signaling pathway but also for introducing cold hardiness in B. juncea.

Project description:Low temperature is a major abiotic stress that impedes plant growth and development. Brassica juncea is an economically important oil seed crop and is sensitive to freezing stress during pod filling subsequently leading to abortion of seeds. To understand the cold stress mediated global perturbations in gene expression, whole transcriptome of B. juncea siliques that were exposed to sub-optimal temperature was sequenced. Manually self-pollinated siliques at different stages of development were subjected to either short (6 h) or long (12 h) durations of chilling stress followed by construction of RNA-seq libraries and deep sequencing using Illumina’s NGS platform. De-novo assembly of B. juncea transcriptome resulted in 133641 transcripts, whose combined length was 117 Mb and N50 value was 1428 bp. We identified 13342 differentially regulated transcripts by pair-wise comparison of 18 transcriptome libraries. Hierarchical clustering along with Spearman correlation analysis identified that the differentially expressed genes segregated in two major clusters representing early (5-15 DAP) and late stages (20-30 DAP) of silique development. Further analysis led to the discovery of sub-clusters having similar patterns of gene expression. Two of the sub-clusters (one each from the early and late stages) comprised of genes that were inducible by both the durations of cold stress. Comparison of transcripts from these clusters led to identification of 283 transcripts that were commonly induced by cold stress, and were referred to as ‘core cold-inducible’ transcripts. Additionally, we found that 689 and 100 transcripts were specifically up regulated by cold stress in early and late stages, respectively. We further explored the expression patterns of gene families encoding for transcription factors (TFs), transcription regulators (TRs) and kinases, and found that cold stress induced protein kinases only during early silique development. We validated the digital gene expression profiles of selected transcripts by qPCR and found a high degree of concordance between the two analyses. To our knowledge this is the first report of transcriptome sequencing of cold-stressed B. juncea siliques. The data generated in this study would be a valuable resource for not only understanding the cold stress signaling pathway but also for introducing cold hardiness in B. juncea.

Project description:In this study, time dependent (4 h to 96 h) transcriptome changes in roots and shoots of Brassica juncea were analyzed under arsenate (AsV) stress by using Agilent platform. A total of 1285 genes showed significant change in expression pattern upon arsenate (AsV) exposure. The genes belonged to various signaling pathways including hormones (jasmonate, abscisic acid (ABA), auxin and ethylene) and kinases. Significant effects were also noticed on genes of sulfur, nitrogen, CHO, and lipid metabolisms along with photosynthesis. These studies indicated interconnections among sulfur metabolism, jasmonate and kinase signaling pathways. Transcriptome results and biochemical analyses highlight that signaling and metabolic pathways work in a dynamic coordination to perceive and respond to the stress. A set of 53939 sequences, which include EST and nucleotide sequences of Brassica sp., were downloaded from GenBank. These sequences were subjected to clustering and analyzed using CAP3/tgicl program and other in-house tools. A set of 26881 non-redundant sequences was created, which was used for probe design. This set included 1720 Brassica juncea, 15259 Brassica napus and 5075 Brassica rapa sequences; and 6456 from other species. Probes were designed for the non-redundant sequences using Agilent eArray tool. Best probe composition algorithm with the option to design multiple probes for each sequence was the main criteria used for the probe design. AgilentM-bM-^@M-^Ys 4x44 array was selected to print the oligos. A set of positive and negative controls were also added on to the microarray chip. A set of replicate probes were also added for calculating the intra-array reproducibility. The quantity and purity of the RNA was determined by absorbance at 260 nm and 260/280 absorbance ratio respectively. Each of the total RNA preparations was individually assessed for RNA quality based on the 28S/18S ratio and RIN measured on an Agilent 2100 Bioanalyzer system using the RNA 6000 Nano LabChip Kit .With the use of AgilentM-bM-^@M-^Ys 1-Color Quick Amp Labeling Kit, 500 ng of high quality total RNA was denatured in the presence of a T7 promoter primer and a 1-Color RNA Spike-In Kit. Reverse transcriptase was used to reverse-transcribe the mRNA. cDNA was used as a template for in vitro transcription where a T7 RNA polymerase simultaneously amplified target material and incorporated cyanine 3-labeled CTP. Labeled cRNA was purified using spin columns from the Qiagen RNeasy Mini Kit and the quantity and quality of the cRNA was determined by Nanodrop ND-1000 UV-VIS spectrophotometer. With the use of AgilentM-bM-^@M-^Ys Gene Expression Hybridization Kit, 1.65 M-BM-5g of cyanine 3-labeled linearly amplified cRNA was added to a hybridization cocktail and then fragmented. The hybridization cocktail was then dispensed into the wells of gasket slides on top of which a Brassica 4x44K Gene Expression Microarray was placed. This microarray M-bM-^@M-^\sandwichM-bM-^@M-^] was then sealed in a hybridization chamber. The microarrays were hybridized at 65M-BM-0C rotating at 10 RPMs for 17 hours. Slides were washed in AgilentM-bM-^@M-^Ys Gene Expression Wash Buffers according to manufacturer specifications. The microarrays were scanned on the Agilent Microarray Scanner. Scanner data extraction and analysis was performed using Agilent Technologies Feature Extraction software version 10.7.3.1.Microarray data quality was evaluated by reviewing ten standard QC metrics generated by the Feature Extraction Software [Consult the Agilent Technologies Feature Extraction Software version 10.7.3.1 reference guide for a full explanation of the QC metrics]. To determine if there was a large hybridization, staining, or wash artifacts, a visual examination of each array was performed by loading the array image into Feature Extraction Software. Microarrays were determined to be free of any large artifacts (M-bM-^IM-% 10% of total surface area) that could have affected the quality of the data.

Dataset Information

Transcriptomics profiling of Indian mustard (Brassica juncea) under arsenate stress identifies key candidate genes and regulatory pathways.

Publications

Transcriptomics profiling of Indian mustard (Brassica juncea) under arsenate stress identifies key candidate genes and regulatory pathways.

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