Project description:The transcriptome, proteome and metabolome of 16 S.cerevisiae backgrounds, combinatorially perturbed in HIS3, LEU2, URA3 and MET15strains are compared. The project was jointly supervised by Kathryn Lilley and Markus Ralser. Transcriptome data has been deposited at ArrayExpress under accession <a href="http://www.ebi.ac.uk/microarray-as/aer/result?queryFor=Experiment&eAccession=E-MTAB-3991">E-MTAB-3991</a>. Metabolome data has been deposited at Metabolights with accession number <a href="http://www.ebi.ac.uk/metabolights/MTBLS168">MTBLS168</a>. The regulation of gene expression in response to nutrient availability is fundamental to the genotype–phenotype relationship. The metabolic–genetic make-up of the cell, as reflected in auxotrophy, is hence likely to be a determinant of gene expression. Here, we address the importance of the metabolic–genetic background by monitoring transcriptome, proteome and metabolome in a repertoire of 16 Saccharomyces cerevisiae laboratory backgrounds, combinatorially perturbed in histidine, leucine, methionine and uracil biosynthesis. The metabolic background affected up to 85% of the coding genome. Suggesting widespread confounding, these transcriptional changes show, on average, 83% overlap between unrelated auxotrophs and 35% with previously published transcriptomes generated for non-metabolic gene knockouts. Background-dependent gene expression correlated with metabolic flux and acted, predominantly through masking or suppression, on 88% of transcriptional interactions epistatically. As a consequence, the deletion of the same metabolic gene in a different background could provoke an entirely different transcriptional response. Propagating to the proteome and scaling up at the metabolome, metabolic background dependencies reveal the prevalence of metabolism-dependent epistasis at all regulatory levels. Urging a fundamental change of the prevailing laboratory practice of using auxotrophs and nutrient supplemented media, these results reveal epistatic intertwining of metabolism with gene expression on the genomic scale.
Project description:Co-expression networks and gene regulatory networks (GRNs) are emerging as important tools for predicting the functional roles of individual genes at a system-wide scale. To enable network reconstructions we built a large-scale gene expression atlas comprised of 62,547 mRNAs, 17,862 non-modified proteins, and 6,227 phosphoproteins harboring 31,595 phosphorylation sites quantified across maize development. There was little edge conservation in co-expression and GRNs reconstructed using transcriptome versus proteome data yet networks from either data type were enriched in ontological categories and effective in predicting known regulatory relationships. This integrated gene expression atlas provides a valuable community resource. The networks should facilitate plant biology research and they provide a conceptual framework for future systems biology studies highlighting the importance of studying gene regulation at several levels.
Project description:Co-expression networks and gene regulatory networks (GRNs) are emerging as important tools for predicting the functional roles of individual genes at a system-wide scale. To enable network reconstructions we built a large-scale gene expression atlas comprised of 62,547 mRNAs, 17,862 non-modified proteins, and 6,227 phosphoproteins harboring 31,595 phosphorylation sites quantified across maize development. There was little edge conservation in co-expression and GRNs reconstructed using transcriptome versus proteome data yet networks from either data type were enriched in ontological categories and effective in predicting known regulatory relationships. This integrated gene expression atlas provides a valuable community resource. The networks should facilitate plant biology research and they provide a conceptual framework for future systems biology studies highlighting the importance of studying gene regulation at several levels.
Project description:During in vitro differentiation, pluripotent stem cells undergo extensive remodeling of their gene expression profiles. While studied extensively at the transcriptome level, much less is known about protein dynamics, which might differ significantly from their mRNA counterparts. Here, we present deep proteome-wide measurements of protein levels during the differentiation of embryonic stem cells.
Project description:Intestinal organoids accurately recapitulate epithelial homeostasis in vivo, thereby representing a powerful in vitro system to investigate lineage specification and cellular differentiation. Here, we applied a multi-omics framework on stem cell enriched and -depleted mouse intestinal organoids to obtain a holistic view of the molecular mechanisms that drive differential gene expression during adult intestinal stem cell differentiation. Our data revealed a global rewiring of the transcriptome and proteome between intestinal stem cells and enterocytes, with the majority of dynamic protein expression being transcription-driven. Integrating absolute mRNA and protein copy numbers revealed post-transcriptional regulation of gene expression. Probing the epigenetic landscape identified a large number of cell-type specific regulatory elements, which revealed Hnf4g as a major driver of enterocyte differentiation. In summary, by applying an integrative systems biology approach we uncovered multiple layers of gene expression regulation, which contribute to lineage specification and plasticity of the mouse small intestinal epithelium.
Project description:The intestinal epithelium is replaced weekly by non-quiescent stem cells with kinetics that rely on a rapid loss of stemness and choice for secretory or absorptive lineage differentiation. To determine how the cellular transcriptome and proteome changes during these transitions, we developed a new cell sorting method to purify stem cells, secretory and absorptive progenitor cells, and mature, differentiated cells. Transcriptome analyses revealed that as stem cells transition to the progenitor stage, alternative mRNA splicing and polyadenylation dominate changes in the transcriptome. In contrast, as progenitors differentiate into mature cell types, alterations in gene expression and mRNA levels drive the changes. RNA processing targets mRNAs encoding regulators of cell cycle, RNA regulators, cell adhesion, SUMOylation, and Wnt and Notch signaling. Additionally, carrier-assisted mass spectrometry of sorted cell populations detected >2,800 proteins and revealed RNA:protein patterns of abundance and correlation. Paired together, these data highlight new potentials for autocrine and feedback regulation and provide new insights into cell state transitions in the crypt.