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Pervasive, coordinated protein level changes driven by transcript isoform switching during meiosis

ABSTRACT: To better understand the gene regulatory mechanisms that program developmental processes, we carried out simultaneous, genome-wide measurements of mRNA, translation and protein through meiotic differentiation in budding yeast. Surprisingly, we observed that the levels of several hundred mRNAs are anti-correlated with their corresponding protein products. We show that rather than arising from canonical forms of gene regulatory control, the regulation of at least 380 such cases—or over 8% of all measured genes—involves temporally regulated switching between production of a canonical, translatable transcript and a 5' extended isoform that is not efficiently translated into protein. By this pervasive mechanism for the modulation of protein levels through a natural developmental program, a single transcription factor can coordinately activate and repress protein synthesis for distinct sets of genes. The distinction is not based on whether an mRNA is induced or not, but rather based on the type of transcript produced.

ORGANISM(S): Saccharomyces cerevisiae

PROVIDER: GSE108778 | GEO | 2018/02/22

REPOSITORIES: GEO

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Project description:Hoppe2012 - Predicting changes in metabolic function using transcript profiles Measuring metabolite concentrations, reaction fluxes, and enzyme activities on large scale are tricky tasks in the study of cellular metabolism. Here, a method that predicts activity changes of metabolic functions based on relative transcript profiles, has been presented. It provides a ranked list of most regulated functions. The method has been applied to TGF-beta treatment of hepatocyte cultures. This stoichiometric model of the mouse hepatocyte is based on a corrected and extended version of HepatoNet1. This model is described in the article: ModeScore: A Method to Infer Changed Activity of Metabolic Function from Transcript Profiles Andreas Hoppe and Hermann-Georg Holzhütter German Conference on Bioinformatics 2012; Publ.13.09.2012 Abstract: Genome-wide transcript profiles are often the only available quantitative data for a particular perturbation of a cellular system and their interpretation with respect to the metabolism is a major challenge in systems biology, especially beyond on/off distinction of genes. We present a method that predicts activity changes of metabolic functions by scoring reference flux distributions based on relative transcript profiles, providing a ranked list of most regulated functions. Then, for each metabolic function, the involved genes are ranked upon how much they represent a specific regulation pattern. Compared with the naïve pathway-based approach, the reference modes can be chosen freely, and they represent full metabolic functions, thus, directly provide testable hypotheses for the metabolic study. In conclusion, the novel method provides promising functions for subsequent experimental elucidation together with outstanding associated genes, solely based on transcript profiles. This model is hosted on BioModels Database and identified by: MODEL1208060000 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. PMID: 20587024 . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to [CC0 Public Domain Dedication>http://creativecommons.org/publicdomain/zero/1.0/] for more information.

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Pervasive, coordinated protein level changes driven by transcript isoform switching during meiosis

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