Project Details
Projekt
Evolution of the AMP-activated protein kinase controlled gene regulatory network
Subject Area
Electronic Semiconductors, Components and Circuits, Integrated Systems, Sensor Technology, Theoretical Electrical Engineering
Evolutionary Cell and Developmental Biology (Zoology)
Evolutionary Cell and Developmental Biology (Zoology)
Term
from 2010 to 2017
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 151020581
Alterations in transcriptional regulation are considered major driving forces in divergent evolution. This is reflected in different species by the variable architecture of regulatory networks controlling highly conserved metabolic pathways. The regulatory proteins of such pathways are also surprisingly conserved. However, apparently, the wiring of these regulators has changed gradually during evolution. This project focuses on the adaptation to nutrient supply, which is controlled by a conserved set of protein kinases and their down-stream effectors. The goal is to uncover basic principles of adaptation and steps in the evolutionary process associated with regulatory network rearrangement. The results of the previous funding periods have unraveled that, in contrast to current belief, the regulators Sip4 and Cat8 control quite different sets of target genes in baker's yeast Saccharomyces cerevisiae and in the milk yeast Kluyveromyces lactis, and, even in case of orthologous target genes, they are surprisingly often regulated in opposite direction. Moreover, the presence or absence of potential binding sites for these regulators correlates only poorly with the transcriptional activity of such genes. The present project aims at improving the prediction of gene regulation by uncovering additional sequence features that contribute to regulation. For detecting und utilizing such additional features, we will extend Context Tree (CT) models and Parsimonious Context Tree (PCT) models and derive, implement, and apply the corresponding algorithms for extended Context Tree Maximization (CTM) and extended Parsimonious Context Tree Maximization (PCTM). These tools will also help to interpret histone acetylation pattern from planned ChIP-seq data to uncover potential epigenetic modes of regulation. Our main goal is to establish an iterative cycle of computational predictions and experimental validation, leading to improved algorithms in each cycle and to a growing set of experimentally verified and falsified predictions, finally allowing a deeper understanding of the evolution of the transcriptional regulatory network controlling adaptation to nutrient limitation, one of the most fundamental processes, conserved across all kingdoms of life.
DFG Programme
Priority Programmes
