_I_T21_SXPsysbio

Short Name: T21_SXPsysbio Title: Use a systems biology approach to identify regulatory bottlenecks in SxPv1 Description: Samples from SXPv1.0 plants as well as sister nulls (progeny from the original transgenic event in which the transgene has segregated) and wild type will be grown and leaf samples taken for RNA extraction and profiling of primary metabolites and volatiles (target pheromones as well as potential derivatives) (P1, P5). Phenotypic and GC-MS data will be obtained and analysed from plants of the second and third generation of the SxP v1 (concretely SP4, SP5 and SP7 lines). RNA will also be extracted from a selection of SP5 T3 plants for RNA-seq experiments (NIB). Comparative metabolomics (GC-MS) and transcriptomics (Illumina RNAseq) studies will be performed and data analysed (P1, P4). Data will be mapped to the latest N. benthamiana gene model (http://benthgenome.qut.edu.au) and also to gene and metabolic models of well-annotated dicotyledouous plants (Arabidopsis, potato, tomato) using existing RNAseq data analysis pipelines for preprocessing, mapping, differential gene expression and enrichment analysis (P4). Results will be visualized in MapMan. The existing Arabidopsis comprehensive knowledge network (P4) will be expanded with metabolic pathways of pheromone production. Regulatory networks will be reverse engineered, superimposed with the prior knowledge network and analysed using different newtorwk analyses, e.g. graph centrality measures, to find gene nodes that differ between transgenic/non-transgenic lines. These will be used to identify potential bottlenecks of supply to the pathway. These data will be fed back to WP1.5 in which new versions of the biosynthesis pathway constructs will be produced with enzymes to steer precursor flux. Phenodata: ./Phenodata_SUPSHIRE_T21.xlsx Featuredata: Principal investigator: Diego Orzaez, Ĺ pela Baebler License: Creative Commons Attribution 4.0 Sharing permission: Private Upload to FAIRDOMHub: Yes