Chickpea shows genotype-specific nodulation responses across soil nitrogen environment and root disease resistance categories
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA681512 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13165835.fastq.gz | Fastqsanger.gz | |||
| SRR13165836.fastq.gz | Fastqsanger.gz | |||
| SRR13165837.fastq.gz | Fastqsanger.gz | |||
| SRR13165838.fastq.gz | Fastqsanger.gz | |||
| SRR13165839.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 36 |
Similar Datasets
Project description:The ability of chickpea to obtain sufficient nitrogen via its symbiotic relationship with Mesorhizobium ciceri is of critical importance in supporting growth and grain production. A number of factors can affect this symbiotic relationship including abiotic conditions, plant genotype, and disruptions to host signalling/perception networks. In order to support improved nodule formation in chickpea, we investigated how plant genotype and soil nutrient availability affect chickpea nodule formation and nitrogen fixation. Further, using transcriptomic profiling, we sought to identify gene expression patterns that characterize highly nodulated genotypes.
2021-07-07 | GSE162321 | GEO
Project description:BackgroundThe ability of chickpea to obtain sufficient nitrogen via its symbiotic relationship with Mesorhizobium ciceri is of critical importance in supporting growth and grain production. A number of factors can affect this symbiotic relationship including abiotic conditions, plant genotype, and disruptions to host signalling/perception networks. In order to support improved nodule formation in chickpea, we investigated how plant genotype and soil nutrient availability affect chickpea nodule formation and nitrogen fixation. Further, using transcriptomic profiling, we sought to identify gene expression patterns that characterize highly nodulated genotypes.ResultsA study involving six chickpea varieties demonstrated large genotype by soil nitrogen interaction effects on nodulation and further identified agronomic traits of genotypes (such as shoot weight) associated with high nodulation. We broadened our scope to consider 29 varieties and breeding lines to examine the relationship between soilborne disease resistance and the number of nodules developed and real-time nitrogen fixation. Results of this larger study supported the earlier genotype specific findings, however, disease resistance did not explain differences in nodulation across genotypes. Transcriptional profiling of six chickpea genotypes indicates that genes associated with signalling, N transport and cellular localization, as opposed to genes associated with the classical nodulation pathway, are more likely to predict whether a given genotype will exhibit high levels of nodule formation.ConclusionsThis research identified a number of key abiotic and genetic factors affecting chickpea nodule development and nitrogen fixation. These findings indicate that an improved understanding of genotype-specific factors affecting chickpea nodule induction and function are key research areas necessary to improving the benefits of rhizobial symbiosis in chickpea.
| S-EPMC8247157 | biostudies-literature
Project description:In this study, we aim to present a global view of transcriptome dynamics during flower development in chickpea. We generated around 234 million high-quality reads for eight flower development stages (ranging from 16 to 40 million reads for each stage) and 91 million high-quality reads from three vegetative tissues using Illumina high-throughput sequencing GAII platform. Because of non-availability of reference genome sequence, we mapped the reads to chickpea transcriptome comprised of 34,760 transcripts for estimation of their transcriptional activity in different tissue samples. The transcriptome dynamics was studied by comparison of gene expression during flower development stages with vegetative tissues. We collected different tissue samples used in this study and total RNA isolated was subjected to Illumina sequencing. The sequenced data was further filtered using NGS QC Toolkit to obtain high-quality reads. The filtered reads were mapped to 34760 chickpea transcripts and reads per kilobase per million (RPKM) was calculated for each gene in all the sample to measure their gene expression. Differential expression analysis was performed using DESeq software. The genes preferentially expression during various stages of flower development as compared to vegetative stages and those with speciifc expression were identified.
2014-01-09 | E-GEOD-42679 | biostudies-arrayexpress
Project description:The total RNA were extracted from pooled tissues of leaves and flowers from several plants of chickpea (Cicer arietinum) using TRIzol reagent (Invitrogen) according to the manufacturer's instructions. Then small RNAs ranging in 18–30 nucleotides were size fractionated electrophoretically, isolated from the gel, ligated with the 5′ and 3′ RNA adapters. The ligated product was reverse transcribed and subsequently amplified using 10–12 PCR cycles. The purified PCR product was sequenced using Illumina Genome Analyzer II. The qualified reads were used to predict microRNAs and phased small interfering RNAs from chickpea. Identification of microRNAs and phased small inferfering RNAs in chickpea (Cicer arietinum) by analyzing small RNA sequencing profiles of leaves and flowers using Illumina GAII.
2015-05-08 | E-GEOD-62216 | biostudies-arrayexpress
Project description:In this study, we sequenced small RNA content from seven major tissues/organs employing Illumina technology. More than 154 million reads were generated using Illumina high-throughput sequencing GAII platform, which represented more than 20 million distinct small RNA sequences. After pre-processing, several conserved and novel miRNAs were identified in chickpea. Further, the putative targets of chickpea miRNAs were identified and their functional categorization was analyzed. In addition, we identified miRNAs exhibitng differential and specific expression in various tissues/organs. We collected different tissue samples used in this study and total RNA isolated was subjected to Illumina sequencing. The sequenced data was further filtered using NGS QC Toolkit to obtain high-quality reads. The filtered reads were pre-processed using modified perl script provided in the miRTools software. After quality control, the identical reads were collapsed into a unique read and read count for each sequence was recorded. All the filtered unique reads from each sample were screened stepwise against annotated non-coding RNA sequences, including plant snoRNA, tRNA and rRNA. The remaining reads were screened against repeat sequences from RepBase and chickpea chloroplast sequence. Conserved miRNAs were identified based on similarity with miRBase database and novel miRNAs were identified using miRDeep-P pipeline. For differential expression analysis, the read count for each miRNA was normalized using DESeq software. The genes preferentially and specifically expressed in various tissues/organs were identified.
2014-09-08 | E-GEOD-51300 | biostudies-arrayexpress
Project description:In order to identify genes and pathways involved in drought tolerance, RNA was isolated from control and 15-days drought-stressed chickpea plants. Two chickpea genotypes, Desi PI598080 (“D”) and Kabuli Flip07 318C (“K”), respectively sensitive and tolerant to drought stresses were used. The 12 extracted RNAs (2 genotypes x 2 water regimes x 3 biological replicates) were sequenced, and the transcriptomic changes between the genotypes and water conditions were analysed. The genotype with higher drought sensitivity showed a generally higher change of gene transcripts than the genotype with less sensitivity, upregulating genes involved in photophosphorylation process (transferases, oxygen lyases and oxidoreductases), hormones (brassinosteroids, abscissic acid and gibberellin response), solute transporters, nutrient uptake and cell wall properties (cellulose synthases, hemicellulose synthases, poligalacturonases, pectate lyases). These results will be helpful for further studies aiming at identifying genes and molecular markers to develop chickpea cultivars resilient to water stress.
2023-09-03 | E-MTAB-13037 | biostudies-arrayexpress
Project description:Background The combination of high-throughput transcript profiling and next-generation sequencing technologies is a prerequisite for genome-wide comprehensive transcriptome analysis. Our recent innovation of deepSuperSAGE is based on an advanced SuperSAGE protocol and its combination with massively parallel pyrosequencing on RocheM-bM-^@M-^Ys 454 sequencing platform. As a demonstration of the power of this combination, we have chosen the salt stress transcriptomes of roots and nodules of the third most important legume crop chickpea (Cicer arietinum L.). While our report is more technology-oriented, it nevertheless addresses a major world-wide problem for crops generally: high salinity. Together with low temperatures and water stress, high salinity is responsible for crop losses of millions of tons of various legume (and other) crops. Continuously deteriorating environmental conditions will combine with salinity stress to further compromise crop yields. As a good example for such stress-exposed crop plants, we started to characterize salt stress responses of chickpeas on the transcriptome level. Results We used deepSuperSAGE to detect early global transcriptome changes in salt-stressed chickpea. The salt stress responses of 86,919 transcripts representing 17,918 unique 26bp deepSuperSAGE tags (UniTags) from roots of the salt-tolerant variety INRAT-93 two hours after treatment with 25 mM NaCl were characterized. Additionally, the expression of 57,281 transcripts representing 13,115 UniTags was monitored in nodules of the same plants. From a total of 144,200 analyzed 26bp tags in roots and nodules together, 21,401 unique transcripts were identified. Of these, only 363 and 106 specific transcripts, respectively, were commonly up- or down-regulated (>3.0-fold) under salt stress in both organs, witnessing a differential organ-specific response to stress. Profiting from recent pioneer works on massive cDNA sequencing in chickpea, more than 9,400 UniTags were able to be linked to UniProt entries. Additionally, gene ontology (GO) categories over-representation analysis enabled to filter out enriched biological processes among the differentially expressed UniTags. Subsequently, the gathered information was further cross-checked with stress-related pathways. From several filtered pathways, here we focus exemplarily on transcripts associated with the generation and scavenging of reactive oxygen species (ROS), as well as on transcripts involved in Na+ homeostasis. Although both processes are already very well characterized in other plants, the information generated in the present work is of high value. Information on expression profiles and sequence similarity for several hundreds of transcripts of potential interest is now available. Conclusions This report demonstrates, that the combination of the high-throughput transcriptome profiling technology SuperSAGE with one of the next-generation sequencing platforms allows deep insights into the first molecular reactions of a plant exposed to salinity. Cross validation with recent reports enriched the information about the salt stress dynamics of more than 9,000 chickpea ESTs, and enlarged their pool of alternative transcripts isoforms. As an example for the high resolution of the employed technology that we coin deepSuperSAGE, we demonstrate that ROS-scavenging and -generating pathways undergo strong global transcriptome changes in chickpea roots and nodules already 2 hours after onset of moderate salt stress (25mM NaCl). Additionally, a set of more than 15 candidate transcripts are proposed to be potential components of the salt overly sensitive (SOS) pathway in chickpea. Newly identified transcript isoforms are potential targets for breeding novel cultivars with high salinity tolerance. We demonstrate that these targets can be integrated into breeding schemes by micro-arrays and RT-PCR assays downstream of the generation of 26bp tags by SuperSAGE. SuperSAGE libraries from chickpea roots and nodules were constructed starting from hydro aeroponics-generated material. Control and stressed plants were grown in parallel Sequencing Instrument: First gerenration 454-Machine Place of sequencing: 454 Life Sciences, Branford, CT, USA
2011-02-01 | E-GEOD-26638 | biostudies-arrayexpress
Project description:We report small RNA data from the leaves of wild chickpea PI 489777. Small RNA library was prepared and sequencing was performed using Illumina platform. A total of 23 million reads were generated, which represented 0.95 million unique reads. These were mapped to the chickpea genome using Bowtie to obtain the non-redundant set of unique small RNA sequences.
2018-07-15 | GSE103571 | GEO
Project description:In this study, we aim to present a global view of transcriptome dynamics during salinity stress in different chickpea genotypes. We generated about 600 million high-quality reads from 16 libraries (control and stress samples for two chickpea genotypes for salinity stress at two developmental stages) using Illumina high-throughput sequencing platform. We mapped the reads to the kabuli chickpea genome for estimation of their transcript abundance in different tissue samples. The transcriptome dynamics was studied by differential gene expression analyses between stress treatment and control sample for each genotype.
2016-07-08 | GSE70377 | GEO
Project description:In this study, we aim to present a global view of transcriptome dynamics during drought stress in different chickpea genotypes. We generated about 800 million high-quality reads from 14 libraries (control and stress samples for two chickpea genotypes for drought stress at two developmental stages) using Illumina high-throughput sequencing platform. We mapped the reads to the kabuli chickpea genome for estimation of their transcript abundance in different tissue samples. The transcriptome dynamics was studied by differential gene expression analyses between stress treatment and control sample for each genotype.
2016-07-08 | GSE70274 | GEO