Coevolutionary genetic variation in the legume-rhizobium transcriptome

Katy D. Heath, Patricia V. Burke, John R. Stinchcombe

Research output: Contribution to journalArticlepeer-review

Abstract

Coevolutionary change requires reciprocal selection between interacting species, where the partner genotypes that are favoured 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 in 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 had 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. See also the Perspective by Simms and Porter

Original languageEnglish (US)
Pages (from-to)4735-4747
Number of pages13
JournalMolecular ecology
Volume21
Issue number19
DOIs
StatePublished - Oct 2012

Keywords

  • G × G
  • coevolution
  • ecological genetics
  • genetic variation
  • genotype-by-genotype interaction
  • interaction
  • legume
  • mutualism
  • rhizobium
  • symbiosis

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Genetics

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