Genome-wide gene expression analysis reveals major chickpea and lentil genes associated with branching
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ABSTRACT:
PROVIDER: PRJEB71630 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR12405167_1.fastq.gz | Fastqsanger.gz | |||
| ERR12405167_2.fastq.gz | Fastqsanger.gz | |||
| ERR12405168_1.fastq.gz | Fastqsanger.gz | |||
| ERR12405168_2.fastq.gz | Fastqsanger.gz | |||
| ERR12405169_1.fastq.gz | Fastqsanger.gz |
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Project description:Chickpea and lentil are two important pulse crops used for human consumption as sources of vegetable protein, rich in amino acids and bioactive compounds. The search for elite cultivars with better architecture has been a demand by farmers of these two crops, which aims to systematize their mechanized planting and harvesting on a large scale. Therefore, the identification of genes associated with the regulation of the branching and architecture of these plants has currently gained great importance. This work aimed to gain insight into transcriptomic changes of two contrasting chickpea and lentil cultivars in terms of branching pattern (little versus highly branched cultivars). In addition, we aimed to identify candidate genes involved in the regulation of shoot branching that could be used as future targets for molecular breeding. The axillary and apical buds of chickpea cultivars Blanco lechoso and FLIP07-318C, and lentil cultivars Castellana and Campisi, considered as little and highly branched, respectively, were harvested.
2024-05-31 | E-MTAB-13679 | biostudies-arrayexpress
Project description:The search for elite cultivars with better architecture has been a demand by farmers of the chickpea and lentil crops, which aims to systematize their mechanized planting and harvesting on a large scale. Therefore, the identification of genes associated with the regulation of the branching and architecture of these plants has currently gained great importance. Herein, this work aimed to gain insight into transcriptomic changes of two contrasting chickpea and lentil cultivars in terms of branching pattern (little versus highly branched cultivars). In addition, we aimed to identify candidate genes involved in the regulation of shoot branching that could be used as future targets for molecular breeding. The axillary and apical buds of chickpea cultivars Blanco lechoso and FLIP07-318C, and lentil cultivars Castellana and Campisi, considered as little and highly branched, respectively, were harvested. A total of 1,624 and 2,512 transcripts were identified as differentially expressed among different tissues and contrasting cultivars of chickpea and lentil, respectively. Several gene categories were significantly modulated such as cell cycle, DNA transcription, energy metabolism, hormonal biosynthesis and signaling, proteolysis, and vegetative development between apical and axillary tissues and contrasting cultivars of chickpea and lentil. Based on differential expression and branching-associated biological function, ten chickpea genes and seven lentil genes were considered the main players involved in differentially regulating the plant branching between contrasting cultivars. These collective data putatively revealed the general mechanism and high-effect genes associated with the regulation of branching in chickpea and lentil, which are potential targets for manipulation through genome editing and transgenesis aiming to improve plant architecture.
| S-EPMC11220206 | biostudies-literature
Project description:Using microarray technology and a set of chickpea (Cicer arietinum L.) unigenes, grasspea (Lathyrus sativus L.) ESTs and lentil (Lens culinaris Med.) resistance gene analogs, the ascochyta blight (Ascochyta rabiei (Pass.) L.) resistance response was studied in four chickpea genotypes, including resistant, moderately resistant, susceptible and wild relative (Cicer echinospermum L.) genotypes. The experimental system minimized environmental effects and was conducted in reference design, where samples from mock-inoculated controls acted as references against post-inoculation samples. Robust data quality was achieved through the use of three biological replicates (including a dye-swap), the inclusion of negative controls, and strict selection criteria for differentially expressed genes including a fold change cutoff determined by self-self hybridizations, Students t test and multiple testing correction (P<0.05). Microarray observations were also validated by quantitative RT-PCR. The time-course expression patterns of 756 microarray features resulted in differential expression of 97 genes in at least one genotype at one time-point. K-means clustering grouped the genes into clusters of similar observations for each genotype, and comparisons between A. rabiei-resistant and susceptible genotypes revealed potential gene 'signatures' predictive of effective A. rabiei resistance. These genes included several pathogenesis-related proteins, SNAKIN2 antimicrobial peptide, proline-rich protein, disease resistance response protein DRRG49-C, environmental stress-inducible protein, leucine-zipper protein, polymorphic antigen membrane protein, as well as several unknown proteins. The potential involvement of these genes and their pathways of induction are discussed. This study represents the first large-scale gene expression profiling in chickpea, and future work will focus on functional validation of the genes of interest. Keywords: time course disease state analysis
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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.
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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:Using microarray technology and a set of chickpea (Cicer arietinum L.) unigenes and grasspea (Lathyrus sativus L.) ESTs, chickpea responses to treatments with the defence signalling compounds salicylic acid (SA), methyl jasmonate (MeJA), and aminocyclopropane carboxylic acid (ACC) were studied in four chickpea genotypes with ranging levels of resistance to ascochyta blight (Ascochyta rabiei (Pass.) L.). The experimental system minimized environmental effects and was conducted in reference design, where samples from untreated controls acted as references against post-treatment samples. Robust data quality was achieved through the use of three biological replicates (including a dye-swap), the inclusion of negative controls, and strict selection criteria for differentially expressed genes including a fold change cut-off determined by self-to-self hybridizations, Students t test and multiple testing correction (P<0.05). Microarray observations were also validated by quantitative RT-PCR. The time-course expression patterns of 715 experimental microarray features resulted in differential expression of 425 genes in at least one condition. The A. rabiei resistant chickpea genotypes showed a more substantial range of defence-related gene induction by all treatments, indicating that they may possess stronger abilities to resist infection. Further, the involvement of SA, MeJA, and ACC signalling was identified for the regulation of some important A. rabiei responsive genes, as well as cross-talk between these pathways. This study also found evidence to suggest the involvement of A. rabiei-specific signalling mechanisms for the induction of several genes that were previously implicated in A. rabiei resistance. Overall, this study characterised the regulatory mechanisms of many chickpea genes that may be important in defence against various pathogens, as well as other cellular functions. Although the size of the microarray was limited, the results provided novel insights to the molecular control of chickpea cellular processes, which may assist the understanding of chickpea defence mechanisms and allow enhanced development of disease resistant cultivars. Keywords: time course defence-signalling teatment analysis
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