Project description:To examine how the Arabidopsis root development responds to the Rhizobium sp. IRBG74 treatment at the molecular level, we performed RNA-seq experiments. Our RNA-seq results suggest that expression of genes mainly involved in auxin signaling, cell wall and cell membrane integrity and transport is altered in response to colonization by Rhizobium sp. IRBG74.
Project description:89 small non-coding RNAs (ncRNAs) were identified in the soil-dwelling alpha-proteobacterium Rhizobium etli by comparing an extensive compilation of ncRNA predictions to intergenic expression data of a whole-genome tiling array. The differential expression levels of some of these ncRNAs during free-living growth and during interaction with the eukaryotic host plant may indicate a role in adaptation to changing environmental conditions.
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.
