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

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data