Positional distribution of human transcription factor binding sites.

We developed a method for estimating the positional distribution of transcription factor (TF) binding sites using ChIP-chip data, and applied it to recently published experiments on binding sites of nine TFs: OCT4, SOX2, NANOG, HNF1A, HNF4A, HNF6, FOXA2, USF1 and CREB1. The data were obtained from a genome-wide coverage of promoter regions from 8-kb upstream of the transcription start site (TSS) to 2-kb downstream. The number of target genes of each TF ranges from few hundred to several thousand. We found that for each of the nine TFs the estimated binding site distribution is closely approximated by a mixture of two components: a narrow peak, localized within 300-bp upstream of the TSS, and a distribution of almost uniform density within the tested region. Using Gene Ontology (GO) and Enrichment analysis, we were able to associate (for each of the TFs studied) the target genes of both types of binding with known biological processes. Most GO terms were enriched either among the proximal targets or among those with a uniform distribution of binding sites. For example, the three stemness-related TFs have several hundred target genes that belong to 'development' and 'morphogenesis' whose binding sites belong to the uniform distribution.

Wide-scale analysis of human functional transcription factor binding reveals a strong bias towards the transcription start site.

BACKGROUND: Transcription factors (TF) regulate expression by binding to specific DNA sequences. A binding event is functional when it affects gene expression. Functionality of a binding site is reflected in conservation of the binding sequence during evolution and in over represented binding in gene groups with coherent biological functions. Functionality is governed by several parameters such as the TF-DNA binding strength, distance of the binding site from the transcription start site (TSS), DNA packing, and more. Understanding how these parameters control functionality of different TFs in different biological contexts is a must for identifying functional TF binding sites and for understanding regulation of transcription. METHODOLOGY/PRINCIPAL FINDINGS: We introduce a novel method to screen the promoters of a set of genes with shared biological function (obtained from the functional Gene Ontology (GO) classification) against a precompiled library of motifs, and find those motifs which are statistically over-represented in the gene set. More than 8,000 human (and 23,000 mouse) genes, were assigned to one of 134 GO sets. Their promoters were searched (from 200 bp downstream to 1,000 bp upstream the TSS) for 414 known DNA motifs. We optimized the sequence similarity score threshold, independently for every location window, taking into account nucleotide heterogeneity along the promoters of the target genes. The method, combined with binding sequence and location conservation between human and mouse, identifies with high probability functional binding sites for groups of functionally-related genes. We found many location-sensitive functional binding events and showed that they clustered close to the TSS. Our method and findings were tested experimentally. CONCLUSIONS/SIGNIFICANCE: We identified reliably functional TF binding sites. This is an essential step towards constructing regulatory networks. The promoter region proximal to the TSS is of central importance for regulation of transcription in human and mouse, just as it is in bacteria and yeast.

Nanog transforms NIH3T3 cells and targets cell-type restricted genes.

The transcription factor Nanog is uniquely expressed in embryonic stem (ES) cells and in germ cell tumors and is important for self-renewal. To understand the relation between this and cell transformation, we expressed Nanog in NIH3T3 cells, and these cells showed an increased growth rate and a transformed phenotype as demonstrated by foci formation and colony growth in soft agar. This suggests that Nanog possesses an oncogenic potential that may be related to the role it plays in germ cell tumors and to its function in self renewal of ES cells. We studied the transcription targets of Nanog using microarrays to identify Nanog regulated genes. The list of genes regulated by Nanog was unique for each cell type and more than 10% of the Nanog regulated genes, including transcription factors, are primary Nanog targets since their promoters bind Nanog in ES cells. Some of these target genes can explain the transformation of NIH3T3.