Isolation of a library of target-sites for sequence specific DNA binding proteins from chick embryonic heart: a potential tool for identifying novel transcriptional regulators involved in embryonic development

Enormity of the metazoan genomes and divergence in their regulation impose a serious constraint on the comprehensive understanding of context specific gene regulation. DNA elements located in the promoter, enhancer, and other regulatory regions of the genome dictate the temporal and spatial patterns of gene activities. However, owing to the diminutive and variable nature of the regulatory DNA elements, their identification and location remains a major challenge. We have developed an efficient strategy for isolating a repertoire of target sites for sequence specific DNA binding proteins from embryonic chick heart. A comprehensive library of such sequences was constructed and authenticated using various parameters including in silico determination of functional binding sites. This approach, therefore, for the first time, established an experimental and conceptual framework for defining the entire repertoire of functional DNA elements in any cellular context.     

Selection for unequal densities of sigma70 promoter-like signals in different regions of large bacterial genomes

The evolutionary processes operating in the DNA regions that participate in the regulation of gene expression are poorly understood. In Escherichia coli, we have established a sequence pattern that distinguishes regulatory from nonregulatory regions. The density of promoter-like sequences, that could be recognizable by RNA polymerase and may function as potential promoters, is high within regulatory regions, in contrast to coding regions and regions located between convergently transcribed genes. Moreover, functional promoter sites identified experimentally are often found in the subregions of highest density of promoter-like signals, even when individual sites with higher binding affinity for RNA polymerase exist elsewhere within the regulatory region. In order to see the generality of this pattern, we have analyzed 43 additional genomes belonging to most established bacterial phyla. Differential densities between regulatory and nonregulatory regions are detectable in most of the analyzed genomes, with the exception of those that have evolved toward extreme genome reduction. Thus, presence of this pattern follows that of genes and other genomic features that require weak selection to be effective in order to persist. On this basis, we suggest that the loss of differential densities in the reduced genomes of host-restricted pathogens and symbionts is an outcome of the process of genome degradation resulting from the decreased efficiency of purifying selection in highly structured small populations. This implies that the differential distribution of promoter-like signals between regulatory and nonregulatory regions detected in large bacterial genomes confers a significant, although small, fitness advantage. This study paves the way for further identification of the specific types of selective constraints that affect the organization of regulatory regions and the overall distribution of promoter-like signals through more detailed comparative analyses among closely related bacterial genomes.     

Identification of a binding motif specific to HNF4 by comparative analysis of multiple nuclear receptors

Nuclear receptors (NRs) regulate gene expression by binding specific DNA sequences consisting of AG[G/T]TCA or AGAACA half site motifs in a variety of configurations. However, those motifs/configurations alone do not adequately explain the diversity of NR function in vivo. Here, a systematic examination of DNA binding specificity by protein-binding microarrays (PBMs) of three closely related human NRs--HNF4α, retinoid X receptor alpha (RXRα) and COUPTF2--reveals an HNF4-specific binding motif (H4-SBM), xxxxCAAAGTCCA, as well as a previously unrecognized polarity in the classical DR1 motif (AGGTCAxAGGTCA) for HNF4α, RXRα and COUPTF2 homodimers. ChIP-seq data indicate that the H4-SBM is uniquely bound by HNF4α but not 10 other NRs in vivo, while NRs PXR, FXRα, Rev-Erbα appear to bind adjacent to H4-SBMs. HNF4-specific DNA recognition and transactivation are mediated by residues Asp69 and Arg76 in the DNA-binding domain; this combination of amino acids is unique to HNF4 among all human NRs. Expression profiling and ChIP data predict ≈ 100 new human HNF4α target genes with an H4-SBM site, including several Co-enzyme A-related genes and genes with links to disease. These results provide important new insights into NR DNA binding.     

Selection for Unequal Densities of σ70 Promoter-Like Signals in Different Regions of Large Bacterial Genomes

The evolutionary processes operating in the DNA regions that participate in the regulation of gene expression are poorly understood. In Escherichia coli, we have established a sequence pattern that distinguishes regulatory from nonregulatory regions. The density of promoter-like sequences, that could be recognizable by RNA polymerase and may function as potential promoters, is high within regulatory regions, in contrast to coding regions and regions located between convergently transcribed genes. Moreover, functional promoter sites identified experimentally are often found in the subregions of highest density of promoter-like signals, even when individual sites with higher binding affinity for RNA polymerase exist elsewhere within the regulatory region. In order to see the generality of this pattern, we have analyzed 43 additional genomes belonging to most established bacterial phyla. Differential densities between regulatory and nonregulatory regions are detectable in most of the analyzed genomes, with the exception of those that have evolved toward extreme genome reduction. Thus, presence of this pattern follows that of genes and other genomic features that require weak selection to be effective in order to persist. On this basis, we suggest that the loss of differential densities in the reduced genomes of host-restricted pathogens and symbionts is an outcome of the process of genome degradation resulting from the decreased efficiency of purifying selection in highly structured small populations. This implies that the differential distribution of promoter-like signals between regulatory and nonregulatory regions detected in large bacterial genomes confers a significant, although small, fitness advantage. This study paves the way for further identification of the specific types of selective constraints that affect the organization of regulatory regions and the overall distribution of promoter-like signals through more detailed comparative analyses among closely related bacterial genomes.     

Inferring gene regulatory relationships by combining target-target pattern recognition and regulator-specific motif examination

Although microarray data have been successfully used for gene clustering and classification, the use of time series microarray data for constructing gene regulatory networks remains a particularly difficult task. The challenge lies in reliably inferring regulatory relationships from datasets that normally possess a large number of genes and a limited number of time points. In addition to the numerical challenge, the enormous complexity and dynamic properties of gene expression regulation also impede the progress of inferring gene regulatory relationships. Based on the accepted model of the relationship between regulator and target genes, we developed a new approach for inferring gene regulatory relationships by combining target-target pattern recognition and examination of regulator-specific binding sites in the promoter regions of putative target genes. Pattern recognition was accomplished in two steps: A first algorithm was used to search for the genes that share expression profile similarities with known target genes (KTGs) of each investigated regulator. The selected genes were further filtered by examining for the presence of regulator-specific binding sites in their promoter regions. As we implemented our approach to 18 yeast regulator genes and their known target genes, we discovered 267 new regulatory relationships, among which 15% are rediscovered, experimentally validated ones. Of the discovered target genes, 36.1% have the same or similar functions to a KTG of the regulator. An even larger number of inferred genes fall in the biological context and regulatory scope of their regulators. Since the regulatory relationships are inferred from pattern recognition between target-target genes, the method we present is especially suitable for inferring gene regulatory relationships in which there is a time delay between the expression of regulating and target genes.     

基于转录调控模体的人不同组织基因差异性的统计分析

转录调控是基因表达调控的主要过程,而转录调控模体使用的差异性可能是导致基因组织特异性的因素之一.本文提出一种不同组织基因调控差异性的统计分析方法,首先结合泊松分布和主成分分析提取基因启动子中过表达模体作为潜在的转录因子结合位点.基于这些位点通过Wilcoxon秩和检验获得不同组织基因结构的差异性.再用超几何分布确定出现次数显著的模体作为组织基因的特有模体,并分析特有模体的碱基特征及在启动子序列中的位置分布.将特有模体与TRANSFAC数据库进行对照,得到潜在的调控组织特异性基因的转录因子结合位点.以人管家基因及30个组织特异性基因为分析对象,得到不同组织调控模体使用的差异性信息.