Project description:The individuals were assayed for genome-wide SNP genotypes using the Illumina Human Omni5 Bead Chip (Illumina), which surveys 4,284,426 single nucleotide markers regularly spaced across the genome
Project description:The present study was initiated to evaluate the quantitative proteomic profiling of Protothecazopfiigenotypes. The cells (P.zopfii genotype 1 –noninfectious and genotype 2 -infectious) were cultured in triplicates until the mid-logarithmic growth phase; the proteins were extracted after sonication on ice, followed by 2D DIGE separation as recommended by the manufacturer (GE Healthcare). The differentially expressed proteins spots were identified using Decodon software analysis (Delta 2D version 4.0 software). Protein identification was carried out by MALDI TOF MS/MS (Ultraflex III TOF/TOF, Bruker Daltonics, Bremen, Germany). The spectra was acquired using the automated option (AutoXecute ) of the Flex Analysis software version 3.3 (Bruker Daltonics, Leipzig, Germany), processed using Flex analysis software version 3.3 (Bruker Daltonics, Leipzig, Germany) and the database search was conducted using the MS/MS ion search (MASCOT, http://www.matrixscience.com) against all entries of NCBInr (GenBank)/Swissprot with subsequent parameters: trypsin digestion, up to one missed cleavage, fixed modifications: carbamidomethyl and with the following variable modifications: oxidation (M), peptide tol.: +- 1.2 Da, MS/MS tol.: +- 0.6 Da, peptide charge: +1. The results were assessed using MOWSE score, p- and E values and those possess positive hits with cRAP database were eliminated from the list.
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.