Soil microbiome of wheat and chickpea
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB30524 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR3029110_1.fastq.gz | Fastqsanger.gz | |||
| ERR3029110_2.fastq.gz | Fastqsanger.gz | |||
| ERR3029120_1.fastq.gz | Fastqsanger.gz | |||
| ERR3029120_2.fastq.gz | Fastqsanger.gz | |||
| ERR3029130_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 140 |
Similar Datasets
Project description:Background: The soil environment is responsible for sustaining most terrestrial plant life on earth, yet we know surprisingly little about the important functions carried out by diverse microbial communities in soil. Soil microbes that inhabit the channels of decaying root systems, the detritusphere, are likely to be essential for plant growth and health, as these channels are the preferred locations of new root growth. Understanding the microbial metagenome of the detritusphere and how it responds to agricultural management such as crop rotations and soil tillage will be vital for improving global food production. Methods: The rhizosphere soils of wheat and chickpea growing under + and - decaying root were collected for metagenomics sequencing. A gene catalogue was established by de novo assembling metagenomic sequencing. Genes abundance was compared between bulk soil and rhizosphere soils under different treatments. Conclusions: The study describes the diversity and functional capacity of a high-quality soil microbial metagenome. The results demonstrate the contribution of the microbiome from decaying root in determining the metagenome of developing root systems, which is fundamental to plant growth, since roots preferentially inhabit previous root channels. Modifications in root microbial function through soil management, can ultimately govern plant health, productivity and food security.
2020-03-06 | GSE146427 | GEO
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: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 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:As a broad group, hemibiotrophic pathogens cause significant losses within agriculture threatening the sustainability of food systems globally. The complex manner in which these microbes colonize their hosts, including an initial biotrophic phase of colonization followed by a biotrophic-to-necrotrophic switch (BNS) phase and ending with a necrotrophic mode of nutritional acquisition, renders their management more complex than pathogens which display a single nutritional strategy. Within model plant systems, typically each of these phases is characterized by both common and discrete transcriptional responses as the host modulates physiological processes in concert with changes in pathogen biology. Plant hormones also play an important role in these stages with classic models showing that salicylic acid accumulates during the biotrophic phase and jasmonic acid/ethylene responses occur during the necrotrophic phase. In this study, we use the interaction between the hemibiotroph Phytophthora medicaginis and the roots of its host Cicer arietinum (chickpea) to define the duration of the different life stages of P. medicaginis during the pathogenesis of chickpea. Using transcriptional profiling across all three stages of infection we demonstrate that chickpea displayed some similarities in response to P. medicaginis as has been previously documented in other model plant-pathogen hemibiotrophic interactions. However, our transcriptomic results suggest that chickpea does not conform to the phytohormone response model observed in leaf colonization, nor to that observed for roots of other plant species being colonised by soil-borne hemibiotrophs. We confirm these findings using targeted quantification of salicylic acid and jasmonic acid. The findings from this study demonstrate that a wider spectrum of plant species should be investigated in future to understand the physiological changes in plants during the different stages of colonization by hemibiotrophic soil-borne pathogens before we can better manage these economically important microbes in agronomically relevant conditions.
2022-01-30 | GSE182741 | GEO
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