Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Combinatorial cis-regulation in Saccharomyces species

ABSTRACT: Transcriptional control of gene expression is a result of complex interactions between the cis-regulatory elements (CRE) at gene promoters. To understand the regulatory logic of a cell, we need to identify the CRE combinations that regulate gene expression. We developed a sensitive computational method to identify phylogenetically conserved CRE combinations for any species of interest. In contrast to previous methods, we do not need to align genomes to identify these combinations. We applied the method in 7 sensu stricto and sensu lato Saccharomyces species. 80% of the predictions displayed some evidence of combinatorial transcriptional behavior in several existing datasets including 1) ChIP-chip data for co-localization of transcription factors, 2) gene expression data for co-expression of predicted regulatory targets, and 3) gene ontology databases for common pathway membership of predicted regulatory targets. To establish definitive evidence that these CRE interactions influence TF occupancy, we performed ChIPseq experiments on transcription factors in a wild-type strain and strains in which a predicted cofactor was deleted. Our experiments showed that TF occupancy at the promoters of the CRE combination target genes depends on the predicted cofactor while occupancy of other promoters is independent of the predicted cofactor. ChIP-seq of 6 myc-tagged Transcription factors in wild-type and predicted co-factor knockout yeast strains in triplicate

ORGANISM(S): Saccharomyces cerevisiae

SUBMITTER: Aaron Spivak

PROVIDER: E-GEOD-60281 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

Project description:It is widely believed that reorganization of nucleosomes result in availability of binding sites that engage transcription factors during eukaryotic gene regulation. Recent findings, on the other hand, suggest that transcription factors induced as a result of physiological perturbations directly (or in association with chromatin modifiers) may alter nucleosome occupancy to facilitate DNA binding. Although, together these suggest a close relationship between transcription factor binding and nucleosome reorganization, the nature of the inter-dependency, or to what extent it influences regulatory transcription is not clear. Moreover, since most studies used physiolgical pertubations that induced multiple transcription factor chromatin modifiers, the relatively local (or direct) effect of transcription factor binding on nucleosome occupancy remains unclear. With these in mind, we used a single transcription factor to induce physiological changes, representing metastatic (aggressive cancer) and the corresponding non-metastatic state, in human cancer cells. Following characterization of the two states (before and after induction of the transcription factor) we determined: (a) genome wide binding sites of the transcription factor, (b) promoter nucleosome occupancy and (c) transcriptome profiles, independently in both conditions. Interestingly, we find only ~20% of TF binding results from nucleosome reorganization - however, almost all corresponding genes were transcriptionally altered. Whereas, in cases where TF-occupancy was independent of nucleosome repositioning (in close vicinity), or co-occurred with nucleosomes, only a small fraction of the corresponding genes were expressed/repressed. Together, these indicate a model where TF occupancy only when coupled with nucleosome repositioning in close proximity is transcriptionally active. This, to our knowledge, for the first time also helps explain why genome wide TF occupancy (e.g., from ChIP-seq) is typically associated with only a small fraction of genes that change expression. For expression profiling of cells in NME2-induced conditions, A549 cells were transfected with pcDNA-NME2-MYC or pcDNA-MYC (control). RNA was isolated from the cells 48h after transfection using the trizol method (Sigma) as per manufacturerM-bM-^@M-^Ys protocol. Total RNA was processed to hybridize to Illumina Human HT-12 v4 Expression BeadChip as per manufacturerM-bM-^@M-^Ys instructions. Three biological replicates were averaged and data was analyzed using BeadStudio (P <0.05 of fold change).

Dataset Information

Combinatorial cis-regulation in Saccharomyces species

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure