Dissecting transcriptomic signatures of genotype x genotype interactions during the initiation of plant-rhizobium symbiosis
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ABSTRACT:
PROVIDER: PRJNA637025 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11916700.fastq.gz | Fastqsanger.gz | |||
| SRR11916700_1.fastq.gz | Fastqsanger.gz | |||
| SRR11916700_2.fastq.gz | Fastqsanger.gz | |||
| SRR11916701.fastq.gz | Fastqsanger.gz | |||
| SRR11916701_1.fastq.gz | Fastqsanger.gz |
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Project description:Coevolutionary change requires reciprocal selection between interacting species, i.e., that the partner genotypes that are favored in one species depend on the genetic composition of the interacting species. Coevolutionary genetic variation is manifested as genotype ´ genotype (G ´ G) interactions for fitness from interspecific interactions. Although quantitative genetic approaches have revealed abundant evidence for G ´ G interactions in symbioses, the molecular basis of this variation remains unclear. Here we study the molecular basis of G ´ G interactions in a model legume-rhizobium mutualism using gene expression microarrays. We find that, like quantitative traits such as fitness, variation in the symbiotic transcriptome may be partitioned into additive and interactive genetic components. Our results suggest that plant genetic variation is the largest influence on nodule gene expression, and that plant genotype and the plant genotype ´ rhizobium genotype interaction determine global shifts in rhizobium gene expression that in turn feedback to influence plant fitness benefits. Moreover, the transcriptomic variation we uncover implicates regulatory changes in both species as drivers of symbiotic gene expression variation. Our study is the first to partition genetic variation in a symbiotic transcriptome, and illuminates potential molecular routes of coevolutionary change. We assayed gene expression using three biological replicates for each plant genotype × rhizobium genotype combination (4 combinations) for a total of 12 chips.
2012-05-01 | GSE29027 | GEO
Project description:Coevolutionary change requires reciprocal selection between interacting species, i.e., that the partner genotypes that are favored in one species depend on the genetic composition of the interacting species. Coevolutionary genetic variation is manifested as genotype ´ genotype (G ´ G) interactions for fitness from interspecific interactions. Although quantitative genetic approaches have revealed abundant evidence for G ´ G interactions in symbioses, the molecular basis of this variation remains unclear. Here we study the molecular basis of G ´ G interactions in a model legume-rhizobium mutualism using gene expression microarrays. We find that, like quantitative traits such as fitness, variation in the symbiotic transcriptome may be partitioned into additive and interactive genetic components. Our results suggest that plant genetic variation is the largest influence on nodule gene expression, and that plant genotype and the plant genotype ´ rhizobium genotype interaction determine global shifts in rhizobium gene expression that in turn feedback to influence plant fitness benefits. Moreover, the transcriptomic variation we uncover implicates regulatory changes in both species as drivers of symbiotic gene expression variation. Our study is the first to partition genetic variation in a symbiotic transcriptome, and illuminates potential molecular routes of coevolutionary change. We assayed gene expression using three biological replicates for each plant genotype × rhizobium genotype combination (4 combinations) for a total of 12 chips. We compared gene expression in each of four combinations of Medicago truncatula families and Sinorhizobium meliloti strains using Affymetrix Medicago GeneChips to study how the entire transcriptome and individual genes responded to differences between plant families, between rhizobium strains, and due to the plant family × rhizobium strain (G × G) interaction.
2012-04-30 | E-GEOD-29027 | biostudies-arrayexpress
Project description:plant genotype x rhizobium genotype interaction
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Project description:The NifA-RpoN complex is a master regulator of the nitrogen fixation genes in alpha-proteobacteria. Based on the complete Rhizobium etli genome sequence, we constructed the R. etli CFN42 oligonucleotide (70 mer) microarray, and utilized this tool to survey changes in gene expression in R. etli CFN42 wild type compared with NifA CFNX247 mutant strain in symbiosis with Phaseolus vulgaris. As expected, the genes associated with a NifA and RpoN binding sites were downregulated in the NifA mutant strain.
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Project description:A wide range of environmental stresses lead to an elevated production of reactive oxygen species (ROS) in plant cells thus resulting in oxidative stress. The biological nitrogen fixation in the legume - Rhizobium symbiosis is at high risk of damage from oxidative stress. Common bean (Phaseolus vulgaris) active nodules exposed to the herbicide Paraquat (1,1 '-Dimethyl-4, 4'-bipyridinium dichloride hydrate) that generates ROS accumulation, showed a reduced nitrogenase activity and ureide content. We analyzed the global gene response of stressed nodules using the Bean CombiMatrix Custom Array 90K, that includes probes from some 30,000 expressed sequence tags (EST). A total of 4,280 ESTs were differentially expressed in oxidative stressed bean nodules; of these 2,218 were repressed. These genes were grouped in 44 different biological processes as defined by Gene Onthology. Analysis with the PathExpress bioinformatic tool, adapted for bean, identified five significantly repressed metabolic path
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Project description:We report an small RNA sequencing (sRNA-seq) approach to identify host sRNAs involved in the nitrogen fixing symbiosis between Mesoamerican Phaseolus vulgaris and Rhizobium etli strains with different degrees in nodulation efficiency. This approach identified conserved and known microRNAs (miRNAs) differentially accumulated in Mesoamerican P. vulgaris roots in response to a highly efficient strain, to a less efficient one or to both strains.
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Project description:A wide range of environmental stresses lead to an elevated production of reactive oxygen species (ROS) in plant cells thus resulting in oxidative stress. The biological nitrogen fixation in the legume - Rhizobium symbiosis is at high risk of damage from oxidative stress. Common bean (Phaseolus vulgaris) active nodules exposed to the herbicide Paraquat (1,1 '-Dimethyl-4, 4'-bipyridinium dichloride hydrate) that generates ROS accumulation, showed a reduced nitrogenase activity and ureide content. We analyzed the global gene response of stressed nodules using the Bean CombiMatrix Custom Array 90K, that includes probes from some 30,000 expressed sequence tags (EST). A total of 4,280 ESTs were differentially expressed in oxidative stressed bean nodules; of these 2,218 were repressed. These genes were grouped in 44 different biological processes as defined by Gene Onthology. Analysis with the PathExpress bioinformatic tool, adapted for bean, identified five significantly repressed metabolic path This work presents the transcriptional profile of bean nodules, induced by strain Rhizobium tropici CIAT 899, under oxidative stress, generated experimentally by adding the herbicide Paraquat (1,1 '-Dimethyl-4, 4'-bipyridinium dichloride hydrate) for 48 hours. We analyzed the transcript profile, via microarray hybridization, using the Bean CombiMatrix Custom Array 90K, that includes probes from some 30,000 expressed sequence tags (EST). A total of 4,280 ESTs were differentially expressed in oxidative stressed bean nodules; of these 2,218 were repressed.
2012-06-30 | E-GEOD-37638 | biostudies-arrayexpress
Project description:Rhizobia are ecologically important, facultative plant-symbiotic microbes. In nature, there is a large variability in the association of rhizobial strains and host plants of the same species. Here, we evaluated whether plant and rhizobial genotypes influence the initial transcriptional response of rhizobium following perception of a host plant. RNA sequencing of the model rhizobium Sinorhizobium meliloti exposed to root exudates or luteolin (an inducer of nod genes, involved in the early steps of symbiotic interaction) was performed on a combination of three S. meliloti strains and three alfalfa varieties as host plants. The response to root exudates involved hundreds of changes in the rhizobium transcriptome. Of the differentially expressed genes, 35% were influenced by the strain genotype, 16% were influenced by the plant genotype, and 29% were influenced by strain-by-host plant genotype interactions. We also examined the response of a hybrid S. meliloti strain in which the symbiotic megaplasmid (∼20% of the genome) was mobilized between two of the above-mentioned strains. Dozens of genes were upregulated in the hybrid strain, indicative of nonadditive variation in the transcriptome. In conclusion, this study demonstrated that transcriptional responses of rhizobia upon perception of legumes are influenced by the genotypes of both symbiotic partners and their interaction, suggesting a wide spectrum of genetic determinants involved in the phenotypic variation of plant-rhizobium symbiosis.IMPORTANCE A sustainable way for meeting the need of an increased global food demand should be based on a holobiont perspective, viewing crop plants as intimately associated with their microbiome, which helps improve plant nutrition, tolerance to pests, and adverse climate conditions. However, the genetic repertoire needed for efficient association with plants by the microbial symbionts is still poorly understood. The rhizobia are an exemplary model of facultative plant symbiotic microbes. Here, we evaluated whether genotype-by-genotype interactions could be identified in the initial transcriptional response of rhizobium perception of a host plant. We performed an RNA sequencing study to analyze the transcriptomes of different rhizobial strains elicited by root exudates of three alfalfa varieties as a proxy of an early step of the symbiotic interaction. The results indicated strain- and plant variety-dependent variability in the observed transcriptional changes, providing fundamentally novel insights into the genetic basis of rhizobium-plant interactions. Our results provide genetic insights and perspective to aid in the exploitation of natural rhizobium variation for improvement of legume growth in agricultural ecosystems.
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