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.
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.
Project description:Biological control is a promising approach to control diseases caused by Pythium species. Unusually for a single genus, the Pythium genus also includes species that can antagonise Pythium plant pathogens, such as Pythium oligandrum. These Pythium plant pathogens are commonly found in the soil such as the broad host-range pathogen Pythium myriotylum and cause various diseases of important crops. While P. oligandrum genes expressed in the interaction with oomycete plant pathogens have been identified previously, the transcriptional response of an oomycete plant pathogen to P. oligandrum has not been investigated. An isolate of P. oligandrum, GAQ1, recovered from soil could antagonise P. myriotylum in a plate-based confrontation assay. The P. oligandrum isolate had a strong disease control effect on soft-rot of ginger caused by P. myriotylum. We investigated the transcriptional interaction between P. myriotylum and P. oligandrum. As part of the transcriptional response of P. myriotylum to the presence of P. oligandrum, putative effector genes such as a sub-set of Kazal-type protease inhibitors were strongly upregulated. P. myriotylum cellulases and elicitin-like putative effectors were also upregulated. In P. oligandrum, cellulases, peroxidases, proteases and NLP effectors were upregulated. The transcriptional response of P. myriotylum suggests clear features of a counter-attacking strategy that may contribute to the variable success and durability of biological attempts to control diseases caused by Pythium species. Whether aspects of this counter-attack could inhibit aspects of this virulence of P. myriotylum is another interesting aspect for future studies.
Project description:An increasing amount of studies integrate mRNA sequencing data into MS-based proteomics to complement the translation product search space. We present the generation of a protein synthesis-based database from deep sequencing of ribosome-protected mRNA fragments. This approach increases the overall protein identification rates with 3% and 11% (improved and new identifications) for human and mouse respectively and enables proteome-wide detection of 5’-extended proteoforms, uORF translation and near-cognate translation start sites.
Project description:The aim of this study was to identify differentially expressed genes in peripheral blood mononuclear cells from MS patients that were responders or non-responders to the neuroantigen myelin basic protein. Using microarray we measured mRNA-expression levels in freshly isolated peripheral blood mononuclear cells from 17 untreated patients with multiple sclerosis. Based on studies, measuring the responses of blood derived T-cells to myelin basic protein ex vivo, these 17 untreated MS-patients can be divided into two groups: 4 of the untreated multiple sclerosis patients had T-cells that responded to myelin basic protein ex vivo whereas 13 untreated MS patients had T-cells that did not respond to myelin basic protein ex vivo.
Project description:In this study, we performed LC-QTOF-MS-based metabolomics and RNA-seq based transcriptome analysis using seven tissues of M. japonicus.