Chickpea Roots Undergoing Colonisation by Phytophthora medicaginis do not Display Hormone Accumulation nor Signalling Typically Associated with Model Leaf Hemibiotrophic Diseases
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ABSTRACT:
PROVIDER: PRJNA757692 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR15607726_1.fastq.gz | Fastqsanger.gz | |||
| SRR15607726_2.fastq.gz | Fastqsanger.gz | |||
| SRR15607727_1.fastq.gz | Fastqsanger.gz | |||
| SRR15607727_2.fastq.gz | Fastqsanger.gz | |||
| SRR15607728_1.fastq.gz | Fastqsanger.gz |
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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:Introduction: Hemibiotrophic Phytophthora are a group of agriculturally and ecologically important pathogenic oomycetes causing severe decline in plant growth and fitness. The lifestyle of these pathogens consists of an initial biotrophic phase followed by a switch to a necrotrophic phase in the latter stages of infection. Between these two phases is the biotrophic to necrotrophic switch (BNS) phase, the timing and controls of which are not well understood particularly in Phytophthora spp. where host resistance has a purely quantitative genetic basis. Methods: To investigate this we sequenced and annotated the genome of Phytophthora medicaginis, causal agent of root rot and substantial yield losses to Fabaceae hosts. We analysed the transcriptome of P. medicaginis across three phases of colonisation of a susceptible chickpea host (Cicer arietinum) and performed co-regulatory analysis to identify putative small secreted protein (SSP) effectors that influence timing of the BNS in a quantitative pathosystem. Results: The genome of P. medicaginis is ~78 Mb, comparable to P. fragariae and P. rubi which also cause root rot. Despite this, it encodes the second smallest number of RxLR (arginine-any amino acid-leucine-arginine) containing proteins of currently sequenced Phytophthora species. Only quantitative resistance is known in chickpea to P. medicaginis, however, we found that many RxLR, Crinkler (CRN), and Nep1-like protein (NLP) proteins and carbohydrate active enzymes (CAZymes) were regulated during infection. Characterisation of one of these, Phytmed_10271, which encodes an RxLR effector demonstrates that it plays a role in the timing of the BNS phase and root cell death. Discussion: These findings provide an important framework and resource for understanding the role of pathogenicity factors in purely quantitative Phytophthora pathosystems and their implications to the timing of the BNS phase.
2024-08-05 | GSE183604 | GEO
Project description:Hemibiotrophic pathogens cause significant losses within agriculture, threatening the sustainability of food systems globally. These microbes colonise plant tissues in three phases: a biotrophic phase followed by a biotrophic-to-necrotrophic switch phase and ending with necrotrophy. Each of these phases is characterized by both common and discrete host transcriptional responses. Plant hormones play an important role in these phases, with foliar models showing that salicylic acid accumulates during the biotrophic phase and jasmonic acid/ethylene responses occur during the necrotrophic phase. The appropriateness of this model to plant roots has been challenged in recent years. The need to understand root responses to hemibiotrophic pathogens of agronomic importance necessitates further research. In this study, using the root hemibiotroph Phytophthora medicaginis, we define the duration of each phase of pathogenesis in Cicer arietinum (chickpea) roots. Using transcriptional profiling, we demonstrate that susceptible chickpea roots display some similarities in response to disease progression as previously documented in leaf plant-pathogen hemibiotrophic interactions. However, our transcriptomic results also show that chickpea roots do not conform to the phytohormone responses typically found in leaf colonisation by hemibiotrophs. We found that quantified levels of salicylic acid concentrations in root tissues decreased significantly during biotrophy while jasmonic acid concentrations were significantly induced. This study demonstrated that a wider spectrum of plant species should be investigated in the future to understand the physiological changes in plants during colonisation by soil-borne hemibiotrophic pathogens before we can better manage these economically important microbes.
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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: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
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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.
2014-09-08 | E-GEOD-51300 | biostudies-arrayexpress