Transcriptional regulatory code of a eukaryotic genome

Abstract

DNA-binding transcriptional regulators interpret the genome's regulatory code by binding to specific sequences to induce or repress gene expression 1 . Comparative genomics has recently been used to identify potential cis-regulatory sequences within the yeast genome on the basis of phylogenetic conservation 2-6 , but this information alone does not reveal if or when transcriptional regulators occupy these binding sites. We have constructed an initial map of yeast's transcriptional regulatory code by identifying the sequence elements that are bound by regulators under various conditions and that are conserved among Saccharomyces species. The organization of regulatory elements in promoters and the environment-dependent use of these elements by regulators are discussed. We find that environment-specific use of regulatory elements predicts mechanistic models for the function of a large population of yeast's transcriptional regulators.We used genome-wide location analysis 7-10 to determine the genomic occupancy of 203 DNA-binding transcriptional regulators in rich media conditions and, for 84 of these regulators, in at least 1 of 12 other environmental conditions (Supplementary Table 1, Supplementary Fig. 1; http://web.wi.mit.edu/young/regulatory_code). These 203 proteins are likely to include nearly all of the DNA-binding transcriptional regulators encoded in the yeast genome. Regulators were selected for profiling in an additional environment if they were essential for growth in that environment or if there was other evidence implicating them in the regulation of gene expression in that environment. The genome-wide location data identified 11,000 unique interactions between regulators and promoter regions at high confidence (P ≤ 0.001).

A genome-wide cis-regulatory element discovery method based on promoter sequences and gene co-expression networks

“…The comparison using the ChIP-chip co-binding network [6] shows that, when the recall is less than 0.025, our precision is better (Figure 1b). The advantage for the top predictions indicates that our method is better for species-specific predictions.…”

“…The first reference network, the annotated regulon network, is constructed by linking pairs of genes belonging to the same annotated regulon that have been proved by low-throughput experiments [41,42]. The second reference network, known as the co-binding network, is derived from high-throughput ChIP-chip data [6], where we link any pair of genes that are shown to be bound by at least one common TF in the ChIP-chip data (with p -value < 0.001). The annotated regulon network is smaller and less complete than the co-binding network, but probably more accurate.…”

“…The advance of experimental technology, including complete genome sequencing, high-throughput expression profiling [1-3] and binding-site mapping [4-6], has made the computational approach of studying the cis -regulatory networks (CRN) more attractive. A widely used model is to cluster genes based on their expression profile and then using motif finding algorithms [7-14] or motif enumerators to find the over-represented sequences within each cluster [15-18].…”

Imbalance of heterologous protein folding and disulfide bond formation rates yields runaway oxidative stress

“…TFs were scored by the modulation in expression level of genes that the TFs bind in the upstream region according to ChIP-chip data [24]. Therefore, the score is not indicative of change in the TF expression level itself, but of the genes under its influence.…”

Transcription factors in eukaryotic cells can functionally regulate gene expression by acting in oligomeric assemblies formed from an intrinsically disordered protein phase transition enabled by molecular crowding

“…In eukaryotic cells, TF localization fluctuates, often between cytoplasm and nucleus [7]. Although it has been observed that promoters can pool on the genome in clusters [8] it has not previously been seen that TFs themselves act in clusters, but instead are largely assumed to act as single molecules. Simulations which embody diffusion and binding suggest that multivalent TFs could, in principle, facilitate intersegment transfer [9].…”