Abstract:
A study on transcriptional and metabolic response of S. cerevisiae cells toenvironmental and genetic perturbations was made. Deletion mutants with BY4743backgound were used. Homozygous deletion mutants ho/ho (reference strain), hap4/hap4, oxa1/oxa1, bcs1/bcs1, rip1/rip1, mig1/mig1, and mba1/mba1and heterozygous deletion mutants HAP4/hap4, RIP1/rip1 and RIP1/mig1 were grownaerobically in continuous chemostat reactors. The samples were collected after threeretension times and analysed for biomass, mRNA and metabolite contents. Transcriptional response of the yeast cells to gene deletions and growth conditionsenabled investigation of transcriptional regulation of central carbon metabolism. Novelregulation information was extracted using present data set.Integration of metabolic and transcriptome data was accomplished using partial least squares (PLS) method, which enables modelling of metabolic data using transcriptomedata. Results of PLS indicate the genes which may mediate the changes in metabolites dueto perturbations applied.Functional annotation to 17 unknown ORFs were annotated functions depending on the genes they are transcriptional correlated. A network among the genes wit h correlatedtranscription was constructed and its prediction power of existing annotations was tested.Data from other sources (amino-acid sequence similarity, protein-protein interaction,shared transcription factors) were combined with transcription data to improve the networkand prediction power. It was concluded that integration of information from varioussources enables better prediction of functions of known genes and allows more unknownORFs to be annotated.Results of this study revealed transcriptional regulation relations unknown previously, allowed functional annotation of more than 500 unknown ORFs and a linkbetween metabolome and transcriptome profiles of S. cerevisiae is constructed.
