The segment-specific gene Krox-20 encodes a transcription factor with binding sites in the promoter region of the Hox-1.4 gene.

Abstract The glucocorticoid (GR) and androgen (AR) receptors execute unique functions in vivo, yet have nearly identical DNA binding specificities. To identify mechanisms that facilitate functional diversification among these transcription factor paralogs, we studied them in an equivalent cellular context. Analysis of chromatin and sequence suggest that divergent binding, and corresponding gene regulation, are driven by different abilities of AR and GR to interact with relatively inaccessible chromatin. Divergent genomic binding patterns can also be the result of subtle differences in DNA binding preference between AR and GR. Furthermore, the sequence composition of large regions (>10 kb) surrounding selectively occupied binding sites differs significantly, indicating a role for the sequence environment in guiding AR and GR to distinct binding sites. The comparison of binding sites that are shared shows that the specificity paradox can also be resolved by differences in the events that occur downstream of receptor binding. Specifically, shared binding sites display receptor-specific enhancer activity, cofactor recruitment and changes in histone modifications. Genomic deletion of shared binding sites demonstrates their contribution to directing receptor-specific gene regulation. Together, these data suggest that differences in genomic occupancy as well as divergence in the events that occur downstream of receptor binding direct functional diversification among transcription factor paralogs.

Download Full-text

Bioinformatics Analysis of SNPs in IL-6 Gene Promoter of Jinghai Yellow Chickens

Genes ◽

10.3390/genes9090446 ◽

2018 ◽

Vol 9 (9) ◽

pp. 446 ◽

Cited By ~ 3

Author(s):

Shijie Xin ◽

Xiaohui Wang ◽

Guojun Dai ◽

Jingjing Zhang ◽

Tingting An ◽

...

Keyword(s):

Gene Expression ◽

Transcription Factor ◽

Binding Sites ◽

Promoter Region ◽

Bioinformatics Analysis ◽

Cpg Islands ◽

Regulatory Region ◽

Transcription Factor Binding Sites ◽

Transcription Factor Binding ◽

Factor Binding

The proinflammatory cytokine, interleukin-6 (IL-6), plays a critical role in many chronic inflammatory diseases, particularly inflammatory bowel disease. To investigate the regulation of IL-6 gene expression at the molecular level, genomic DNA sequencing of Jinghai yellow chickens (Gallus gallus) was performed to detect single-nucleotide polymorphisms (SNPs) in the region −2200 base pairs (bp) upstream to 500 bp downstream of IL-6. Transcription factor binding sites and CpG islands in the IL-6 promoter region were predicted using bioinformatics software. Twenty-eight SNP sites were identified in IL-6. Four of these 28 SNPs, three [−357 (G > A), −447 (C > G), and −663 (A > G)] in the 5′ regulatory region and one in the 3′ non-coding region [3177 (C > T)] are not labelled in GenBank. Bioinformatics analysis revealed 11 SNPs within the promoter region that altered putative transcription factor binding sites. Furthermore, the C-939G mutation in the promoter region may change the number of CpG islands, and SNPs in the 5′ regulatory region may influence IL-6 gene expression by altering transcription factor binding or CpG methylation status. Genetic diversity analysis revealed that the newly discovered A-663G site significantly deviated from Hardy-Weinberg equilibrium. These results provide a basis for further exploration of the promoter function of the IL-6 gene and the relationships of these SNPs to intestinal inflammation resistance in chickens.

Download Full-text

SNP Diversity in CD14 Gene Promoter Suggests Adaptation Footprints in Trypanosome Tolerant N’Dama (Bos taurus) but not in Susceptible White Fulani (Bos indicus) Cattle

Genes ◽

10.3390/genes11010112 ◽

2020 ◽

Vol 11 (1) ◽

pp. 112 ◽

Cited By ~ 1

Author(s):

Olanrewaju B. Morenikeji ◽

Anna L. Capria ◽

Olusola Ojurongbe ◽

Bolaji N. Thomas

Keyword(s):

Genetic Diversity ◽

Immune Response ◽

Transcription Factor ◽

Binding Sites ◽

Promoter Region ◽

Gene Promoter ◽

Transcription Factor Binding Sites ◽

Factor Binding ◽

White Fulani ◽

Cd14 Gene

Immune response to infections has been shown to be mediated by genetic diversity in pattern recognition receptors, leading to disease tolerance or susceptibility. We elucidated naturally occurring variations within the bovine CD14 gene promoter in trypanosome-tolerant (N’Dama) and susceptible (White Fulani) cattle, with genomic and computational approaches. Blood samples were collected from White Fulani and N’Dama cattle, genomic DNA extracted and the entire promoter region of the CD14 gene amplified by PCR. We sequenced this region and performed in silico computation to identify SNP variants, transcription factor binding sites, as well as micro RNAs in the region. CD14 promoter sequences were compared with the reference bovine genome from the Ensembl database to identify various SNPs. Furthermore, we validated three selected N’Dama specific SNPs using custom Taqman SNP genotyping assay for genetic diversity. In all, we identified a total of 54 and 41 SNPs at the CD14 promoter for N’Dama and White Fulani respectively, including 13 unique SNPs present in N’Dama only. The significantly higher SNP density at the CD14 gene promoter region in N’Dama may be responsible for disease tolerance, possibly an evolutionary adaptation. Our genotype analysis of the three loci selected for validation show that mutant alleles (A/A, C/C, and A/A) were adaptation profiles within disease tolerant N’Dama. A similar observation was made for our haplotype analysis revealing that haplotypes H1 (ACA) and H2 (ACG) were significant combinations within the population. The SNP effect prediction revealed 101 and 89 new transcription factor binding sites in N’Dama and White Fulani, respectively. We conclude that disease tolerant N’Dama possessing higher SNP density at the CD14 gene promoter and the preponderance of mutant alleles potentially confirms the significance of this promoter in immune response, which is lacking in susceptible White Fulani. We, therefore, recommend further in vitro and in vivo study of this observation in infected animals, as the next step for understanding genetic diversity relating to varying disease phenotypes in both breeds.

Download Full-text

The TEA Transcription Factor Tec1 Confers Promoter-Specific Gene Regulation by Ste12-Dependent and -Independent Mechanisms

Eukaryotic Cell ◽

10.1128/ec.00251-09 ◽

2010 ◽

Vol 9 (4) ◽

pp. 514-531 ◽

Cited By ~ 20

Author(s):

Barbara Heise ◽

Julia van der Felden ◽

Sandra Kern ◽

Mario Malcher ◽

Stefan Brückner ◽

...

Keyword(s):

Gene Expression ◽

Transcription Factor ◽

Transcriptional Activation ◽

Binding Sites ◽

Target Genes ◽

Specific Gene ◽

Dependent Manner ◽

A Genome ◽

Regulated Gene Expression

ABSTRACT In Saccharomyces cerevisiae, the TEA transcription factor Tec1 is known to regulate target genes together with a second transcription factor, Ste12. Tec1-Ste12 complexes can activate transcription through Tec1 binding sites (TCSs), which can be further combined with Ste12 binding sites (PREs) for cooperative DNA binding. However, previous studies have hinted that Tec1 might regulate transcription also without Ste12. Here, we show that in vivo, physiological amounts of Tec1 are sufficient to stimulate TCS-mediated gene expression and transcription of the FLO11 gene in the absence of Ste12. In vitro, Tec1 is able to bind TCS elements with high affinity and specificity without Ste12. Furthermore, Tec1 contains a C-terminal transcriptional activation domain that confers Ste12-independent activation of TCS-regulated gene expression. On a genome-wide scale, we identified 302 Tec1 target genes that constitute two distinct classes. A first class of 254 genes is regulated by Tec1 in a Ste12-dependent manner and is enriched for genes that are bound by Tec1 and Ste12 in vivo. In contrast, a second class of 48 genes can be regulated by Tec1 independently of Ste12 and is enriched for genes that are bound by the stress transcription factors Yap6, Nrg1, Cin5, Skn7, Hsf1, and Msn4. Finally, we find that combinatorial control by Tec1-Ste12 complexes stabilizes Tec1 against degradation. Our study suggests that Tec1 is able to regulate TCS-mediated gene expression by Ste12-dependent and Ste12-independent mechanisms that enable promoter-specific transcriptional control.

Download Full-text

Identifying Transcription Regulatory Elements in the Human and Mouse Genomes Using Tissue-specific Gene Expression Profiles

Journal of Integrative Bioinformatics ◽

10.1515/jib-2007-59 ◽

2007 ◽

Vol 4 (2) ◽

pp. 1-23

Author(s):

Amitava Karmaker ◽

Kihoon Yoon ◽

Mark Doderer ◽

Russell Kruzelock ◽

Stephen Kwek

Keyword(s):

Gene Expression ◽

Transcription Factor ◽

Transcription Factors ◽

Binding Sites ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Regulatory Elements ◽

Specific Gene ◽

Tissue Specific Gene ◽

Human And Mouse

Summary Revealing the complex interaction between trans- and cis-regulatory elements and identifying these potential binding sites are fundamental problems in understanding gene expression. The progresses in ChIP-chip technology facilitate identifying DNA sequences that are recognized by a specific transcription factor. However, protein-DNA binding is a necessary, but not sufficient, condition for transcription regulation. We need to demonstrate that their gene expression levels are correlated to further confirm regulatory relationship. Here, instead of using a linear correlation coefficient, we used a non-linear function that seems to better capture possible regulatory relationships. By analyzing tissue-specific gene expression profiles of human and mouse, we delineate a list of pairs of transcription factor and gene with highly correlated expression levels, which may have regulatory relationships. Using two closely-related species (human and mouse), we perform comparative genome analysis to cross-validate the quality of our prediction. Our findings are confirmed by matching publicly available TFBS databases (like TRANFAC and ConSite) and by reviewing biological literature. For example, according to our analysis, 80% and 85.71% of the targets genes associated with E2F5 and RELB transcription factors have the corresponding known binding sites. We also substantiated our results on some oncogenes with the biomedical literature. Moreover, we performed further analysis on them and found that BCR and DEK may be regulated by some common transcription factors. Similar results for BTG1, FCGR2B and LCK genes were also reported.

Download Full-text

Functional classification of transcription factor binding sites: Information content as a metric

Journal of Integrative Bioinformatics ◽

10.1515/jib-2006-20 ◽

2006 ◽

Vol 3 (1) ◽

pp. 32-44 ◽

Cited By ~ 3

Author(s):

D. Ashok Reddy ◽

B. V. L. S. Prasad ◽

Chanchal K. Mitra

Keyword(s):

Transcription Factor ◽

Information Content ◽

Binding Sites ◽

Transcription Factor Binding Sites ◽

Transcription Factor Binding ◽

Protein Classification ◽

Specific Gene ◽

Functional Classification ◽

Factor Binding

Summary The information content (relative entropy) of transcription factor binding sites (TFBS) is used to classify the transcription factors (TFs). The TF classes are clustered based on the TFBS clustering using information content. Any TF belonging to the TF class cluster has a chance of binding to any TFBS of the clustered group. Thus, out of the 41 TFBS (in humans), perhaps only 5 -10 TFs may be actually needed and in case of mouse instead of 13 TFs, we may have actually 5 or so TFs. The JASPAR database of TFBS are used in this study. The experimental data on TFs of specific gene expression from TRRD database is also coinciding with our computational results. This gives us a new way to look at the protein classification- not based on their structure or function but by the nature of their TFBS.

Download Full-text

Identification of key tissue-specific, biological processes by integrating enhancer information in maize gene regulatory networks

10.1101/2020.06.16.155481 ◽

2020 ◽

Author(s):

Maud Fagny ◽

Marieke Lydia Kuijjer ◽

Maike Stam ◽

Johann Joets ◽

Olivier Turc ◽

...

Keyword(s):

Gene Expression ◽

Transcription Factor ◽

Binding Sites ◽

Regulatory Network ◽

Tissue Specificity ◽

Target Genes ◽

Specific Gene ◽

Tissue Specific ◽

Genome Wide ◽

Gene Regulatory

AbstractEnhancers are important regulators of gene expression during numerous crucial processes including tissue differentiation across development. In plants, their recent molecular characterization revealed their capacity to activate the expression of several target genes through the binding of transcription factors. Nevertheless, identifying these target genes at a genome-wide level remains a challenge, in particular in species with large genomes, where enhancers and target genes can be hundreds of kilobases away. Therefore, the contribution of enhancers to regulatory network is still poorly understood in plants. In this study, we investigate the enhancer-driven regulatory network of two maize tissues at different stages: leaves at seedling stage and husks (bracts) at flowering. Using a systems biology approach, we integrate genomic, epigenomic and transcriptomic data to model the regulatory relationship between transcription factors and their potential target genes. We identify regulatory modules specific to husk and V2-IST, and show that they are involved in distinct functions related to the biology of each tissue. We evidence enhancers exhibiting binding sites for two distinct transcription factor families (DOF and AP2/ERF) that drive the tissue-specificity of gene expression in seedling immature leaf and husk. Analysis of the corresponding enhancer sequences reveals that two different transposable element families (TIR transposon Mutator and MITE Pif/Harbinger) have shaped the regulatory network in each tissue, and that MITEs have provided new transcription factor binding sites that are involved in husk tissue-specificity.SignificanceEnhancers play a major role in regulating tissue-specific gene expression in higher eukaryotes, including angiosperms. While molecular characterization of enhancers has improved over the past years, identifying their target genes at the genome-wide scale remains challenging. Here, we integrate genomic, epigenomic and transcriptomic data to decipher the tissue-specific gene regulatory network controlled by enhancers at two different stages of maize leaf development. Using a systems biology approach, we identify transcription factor families regulating gene tissue-specific expression in husk and seedling leaves, and characterize the enhancers likely to be involved. We show that a large part of maize enhancers is derived from transposable elements, which can provide novel transcription factor binding sites crucial to the regulation of tissue-specific biological functions.

Download Full-text

PEAK2VEC ENABLES INFERRENCE OF TRANSCRIPTIONAL REGULATION FROM ATAC-SEQ

10.1101/2021.09.29.462455 ◽

2021 ◽

Author(s):

Lifan Liang ◽

Xinghua Lu ◽

Songjian Lu

Keyword(s):

Neural Network ◽

Transcription Factor ◽

Transcriptional Regulation ◽

Deep Learning ◽

Convolutional Neural Network ◽

Binding Sites ◽

Promoter Region ◽

Simulation Experiment ◽

Footprint Analysis

Transcription factor (TF) binding sites in ATAC-seq are typically determined by footprint analysis. However, the performance of footprint analysis remains unsatisfying and most TFs do not exhibit footprint patterns. In this study, we modified the convolutional neural network to project sequences into an embedding space. Sequences with similar nucleotide patterns will stay close together in the embedding. The dimensionality of this embedding space represents binding specificities of various TFs. In the simulation experiment, peak2vec accurately distinguished the three TFs in the embedding space while conventional deep learning cannot. When applied to the ATAC-seq profiles of hepatitis carcinoma, peak2vec recovered multiple motifs curated in database, while significant portion of sequences corresponding to the TF are located at the promoter region of its regulated genes.

Download Full-text

Search Method for Consensus Pattern of Transcription Factor Binding Sites in Promoter Region

Journal of the Korea Academia-Industrial cooperation Society ◽

10.5762/kais.2008.9.5.1218 ◽

2008 ◽

Vol 9 (5) ◽

pp. 1218-1224 ◽

Cited By ~ 1

Author(s):

Ki-Bong Kim

Keyword(s):

Transcription Factor ◽

Binding Sites ◽

Promoter Region ◽

Transcription Factor Binding Sites ◽

Transcription Factor Binding ◽

Search Method ◽

Factor Binding ◽

Consensus Pattern

Download Full-text

Transcriptional regulation of a mouse Clara cell-specific protein (mCC10) gene by the NKx transcription factor family members thyroid transciption factor 1 and cardiac muscle-specific homeobox protein (CSX).

Molecular and Cellular Biology ◽

10.1128/mcb.16.5.2056 ◽

1996 ◽

Vol 16 (5) ◽

pp. 2056-2064 ◽

Cited By ~ 81

Author(s):

M K Ray ◽

C Y Chen ◽

R J Schwartz ◽

F J DeMayo

Keyword(s):

Transcription Factor ◽

Cardiac Muscle ◽

Binding Site ◽

Binding Sites ◽

Promoter Region ◽

Target Genes ◽

Clara Cell ◽

Proximal Promoter ◽

Growth Hormone Gene ◽

Homeobox Protein

This report defines the elements between bp -800 and -166 that regulate the quantitative level of mouse CC10 (mCC10) transcription in the lungs. The elements in this promoter domain are the response elements for the NKx2.1 homeobox protein, thyroid transcription factor 1 (TTF1). DNase I footprint analysis identified five binding sites for TTF1 between bp -800 and - 166. These sites are located at bp -344 to -335, - 282 to -273, -268 to -263, -258 to -249, and - 199 to - 190. In addition to these enhancer elements, two TTF1 binding sites were identified in the proximal promoter region (bp - 166 to + 1), at bp -74 to -69 and -49 to -39. An identical footprint of the mCC10 promoter region was also observed with another member of the NKx family, NKx 2.5, the cardiac muscle-specific homeobox protein (CSX). Deletion and linker-scanner mutational analyses of the TTF1 binding sites in the mCC10 distal promoter region with transient cotransfection into CV1 cells with either TTF1 or CSX identified the site located between bp -282 and -273 as the major regulator of CC10 expression, with minor regulation by sites at bp -344 to -335 and -258 to -249. The importance of the NKx binding site at bp -282 to -273 was verified in vivo. Transgenic mice generated with the human growth hormone gene fused to 800 bp of the mCC10 promoter containing a mutation in the TTF1 binding site at bp -282 to -273 showed a reduction in transgene expression equal to that of the mice generated with only 166 bp of 5'-flanking DNA. This report emphasizes the importance of TTF1 or related factors as major regulators of pulmonary gene expression and demonstrates the potential of NKx proteins to bind and activate heterologous target genes.

Download Full-text