Plant-genotype effects on microbial communities
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB38150 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR4094400_1.fastq.gz | Fastqsanger.gz | |||
| ERR4094400_2.fastq.gz | Fastqsanger.gz | |||
| ERR4094410_1.fastq.gz | Fastqsanger.gz | |||
| ERR4094410_2.fastq.gz | Fastqsanger.gz | |||
| ERR4094420_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.
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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. 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.
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2024-06-05 | MSV000094943 | MassIVE
Project description:Plants in their natural and agricultural environments are continuously exposed to a plethora of diverse microorganisms resulting in microbial colonization of plants in the rhizosphere. This process is believed to be accompanied by an intricate network of ongoing simultaneous interactions. In this study, we compared transcriptional patterns of Arabidopsis thaliana roots and shoots in the presence and absence of whole microbial communities extracted from compost soil. The results show a clear growth promoting effect of Arabidopsis shoots in the presence of soil microbes compared to axenically grown plants under identical conditions. Element analyses showed that iron uptake was facilitated by these mixed microbial communities which also lead to transcriptional downregulation of genes required for iron transport. In addition, soil microbial communities suppressed the expression of marker genes involved in oxidative stress/redox signalling, cell wall modification and plant defense. While most previous studies have focussed on individual plant-microbe interactions, our data suggest that multi-species transcriptional profiling, using simultaneous plant and metatranscriptomics coupled to metagenomics may be required to further increase our understanding of the intricate networks underlying plant-microbe interactions in their diverse environments. Four samples were analysed in total. One corresponded to a pooled sample of RNA extracted from root tissues of 60 plants. The other three were biological replicates from shoot tissues, each of which contained 20 plants. Controls were used as reference and corresponded to tissues of plants grown in sterile conditions.
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