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Identifying regulatory mechanisms using individual variation reveals key role for chromatin modification.

ABSTRACT: Sequence polymorphisms affect gene expression by perturbing the complex network of regulatory interactions. We propose a probabilistic method, called Geronemo, which directly aims to identify the mechanism by which genetic changes perturb the regulatory network. Geronemo automatically constructs a set of coregulated genes (modules), whose regulation can involve both sequence variations and expression of regulators. By exploiting the modularity of genetic regulatory systems, Geronemo reveals regulatory relationships that are indiscernible when genes are considered in isolation, allowing the recovery of intricate combinatorial regulation. By incorporating both expression and genotype of regulators, Geronemo captures cases where the effect of sequence variation on its targets is indirect. We applied Geronemo to a data set from the progeny generated by a cross between laboratory BY4716 (BY) and wild RM11-1a (RM) isolates of Saccharomyces cerevisiae. Geronemo produced previously undescribed hypotheses regarding genetic perturbations in the yeast regulatory network, including transcriptional regulation, signal transduction, and chromatin modification. In particular, we find a large number of modules that have both chromosomal characteristics and are regulated by chromatin modification proteins. Indeed, a large fraction of the variance in the expression can be explained by a small number of markers associated with chromatin modifiers. Additional analysis reveals positive selection for sequence evolution of elements in the Swi/Snf chromatin remodeling complex. Overall, our results suggest that a significant part of individual expression variation in yeast arises from evolution of a small number of chromatin structure modifiers.

SUBMITTER: Lee SI

PROVIDER: S-EPMC1599912 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Alterations in genetic and epigenetic landscapes are known to contribute to the development of different types of cancer. However, the mechanistic links between transcription factors and the epigenome which coordinate the deregulation of gene networks during cell transformation are largely unknown.We used an isogenic model of stepwise tumorigenic transformation of human primary cells to monitor the progressive deregulation of gene networks upon immortalization and oncogene-induced transformation. We applied a systems biology approach by combining transcriptome and epigenome data for each step during transformation and integrated transcription factor-target gene associations in order to reconstruct the gene regulatory networks that are at the basis of the transformation process.We identified 142 transcription factors and 24 chromatin remodelers/modifiers (CRMs) which are preferentially associated with specific co-expression pathways that originate from deregulated gene programming during tumorigenesis. These transcription factors are involved in the regulation of divers processes, including cell differentiation, the immune response, and the establishment/modification of the epigenome. Unexpectedly, the analysis of chromatin state dynamics revealed patterns that distinguish groups of genes which are not only co-regulated but also functionally related. Decortication of transcription factor targets enabled us to define potential key regulators of cell transformation which are engaged in RNA metabolism and chromatin remodeling.We reconstructed gene regulatory networks that reveal the alterations occurring during human cellular tumorigenesis. Using these networks we predicted and validated several transcription factors as key players for the establishment of tumorigenic traits of transformed cells. Our study suggests a direct implication of CRMs in oncogene-induced tumorigenesis and identifies new CRMs involved in this process. This is the first comprehensive view of the gene regulatory network that is altered during the process of stepwise human cellular tumorigenesis in a virtually isogenic system.

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Identifying regulatory mechanisms using individual variation reveals key role for chromatin modification.

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