The Th1 cell regulatory circuitry is largely conserved between human and mouse

Gene expression programs controlled by lineage-determining transcription factors are often conserved between species. However, infectious diseases have exerted profound evolutionary pressure, and therefore the genes regulated by immune-specific transcription factors might be expected to exhibit greater divergence. T-bet (Tbx21) is the immune-specific, lineage-specifying transcription factor for T helper type I (Th1) immunity, which is fundamental for the immune response to intracellular pathogens but also underlies inflammatory diseases. We compared T-bet genomic targets between mouse and human CD4+ T cells and correlated T-bet binding patterns with species-specific gene expression. Remarkably, we found that the majority of T-bet target genes are conserved between mouse and human, either via preservation of binding sites or via alternative binding sites associated with transposon-linked insertion. Species-specific T-bet binding was associated with differences in transcription factor–binding motifs and species-specific expression of associated genes. These results provide a genome-wide cross-species comparison of Th1 gene regulation that will enable more accurate translation of genetic targets and therapeutics from pre-clinical models of inflammatory and infectious diseases and cancer into human clinical trials.

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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.

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The Th1 cell regulatory circuitry is largely conserved between human and mouse

10.1101/2021.01.11.426266 ◽

2021 ◽

Author(s):

Stephen Henderson ◽

Venu Pullabhatla ◽

Arnulf Hertweck ◽

Emanuele de Rinaldis ◽

Javier Herrero ◽

...

Keyword(s):

Gene Expression ◽

Transcription Factors ◽

Binding Site ◽

Inflammatory Diseases ◽

Specific Gene ◽

Type I ◽

Th1 Cell ◽

Specific Expression ◽

A Genome ◽

Species Specific

ABSTRACTGene expression programmes controlled by lineage-determining transcription factors are often conserved between species. However, infectious diseases have exerted profound evolutionary pressure, and therefore the genes regulated by immune-specific transcription factors might be expected to exhibit greater divergence due to exposure to species-specific pathogens. T-bet (Tbx21) is the immune-specific lineage-defining transcription factor for T helper type I (Th1) immunity, which is fundamental for the immune response to intracellular pathogens but also underlies inflammatory diseases. We therefore compared T-bet genomic targets between mouse and human CD4+ T cells and correlated T-bet binding patterns with species-specific gene expression. Remarkably, we show that the vast majority of T-bet regulated genes are conserved between mouse and human, either via preservation of a binding site or via an alternative binding site associated with transposon-linked insertion. We also identified genes that are specifically targeted by T-bet in humans or mice and which exhibited species-specific expression. These results provide a genome-wide cross-species comparison of T-bet target gene regulation that will enable more accurate translation of genetic targets and therapeutics from pre-clinical models of inflammatory disease into human clinical trials.

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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.

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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.

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Beyond the ENCODE project: using genomics and epigenomics strategies to study enhancer evolution

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2013.0022 ◽

2013 ◽

Vol 368 (1632) ◽

pp. 20130022 ◽

Cited By ~ 13

Author(s):

Noboru Jo Sakabe ◽

Marcelo A. Nobrega

Keyword(s):

Gene Expression ◽

Target Genes ◽

Expression Patterns ◽

Dna Interaction ◽

Regulatory Elements ◽

Specific Gene ◽

Genome Wide ◽

Identify Transcription Factor ◽

Specific Proteins ◽

Species Specific

The complex expression patterns observed for many genes are often regulated by distal transcription enhancers. Changes in the nucleotide sequences of enhancers may therefore lead to changes in gene expression, representing a central mechanism by which organisms evolve. With the development of the experimental technique of chromatin immunoprecipitation (ChIP), in which discrete regions of the genome bound by specific proteins can be identified, it is now possible to identify transcription factor binding events (putative cis -regulatory elements) in entire genomes. Comparing protein–DNA binding maps allows us, for the first time, to attempt to identify regulatory differences and infer global patterns of change in gene expression across species. Here, we review studies that used genome-wide ChIP to study the evolution of enhancers. The trend is one of high divergence of cis -regulatory elements between species, possibly compensated by extensive creation and loss of regulatory elements and rewiring of their target genes. We speculate on the meaning of the differences observed and discuss that although ChIP experiments identify the biochemical event of protein–DNA interaction, it cannot determine whether the event results in a biological function, and therefore more studies are required to establish the effect of divergence of binding events on species-specific gene expression.

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The GATA-4 transcription factor transactivates the cardiac muscle-specific troponin C promoter-enhancer in nonmuscle cells.

Molecular and Cellular Biology ◽

10.1128/mcb.14.11.7517 ◽

1994 ◽

Vol 14 (11) ◽

pp. 7517-7526 ◽

Cited By ~ 133

Author(s):

H S Ip ◽

D B Wilson ◽

M Heikinheimo ◽

Z Tang ◽

C N Ting ◽

...

Keyword(s):

Gene Expression ◽

Transcription Factor ◽

Transcription Factors ◽

Cardiac Muscle ◽

Binding Site ◽

Cardiac Myocytes ◽

Specific Binding ◽

Troponin C ◽

Specific Gene ◽

Cardiac Muscle Cells

The unique contractile phenotype of cardiac myocytes is determined by the expression of a set of cardiac muscle-specific genes. By analogy to other mammalian developmental systems, it is likely that the coordinate expression of cardiac genes is controlled by lineage-specific transcription factors that interact with promoter and enhancer elements in the transcriptional regulatory regions of these genes. Although previous reports have identified several cardiac muscle-specific transcriptional elements, relatively little is known about the lineage-specific transcription factors that regulate these elements. In this report, we demonstrate that the slow/cardiac muscle-specific troponin C (cTnC) enhancer contains a specific binding site for the lineage-restricted zinc finger transcription factor GATA-4. This GATA-4-binding site is required for enhancer activity in primary cardiac myocytes. Moreover, the cTnC enhancer can be transactivated by overexpression of GATA-4 in non-cardiac muscle cells such as NIH 3T3 cells. In situ hybridization studies demonstrate that GATA-4 and cTnC have overlapping patterns of expression in the hearts of postimplantation mouse embryos and that GATA-4 gene expression precedes cTnC expression. Indirect immunofluorescence reveals GATA-4 expression in cultured cardiac myocytes from neonatal rats. Taken together, these results are consistent with a model in which GATA-4 functions to direct tissue-specific gene expression during mammalian cardiac development.

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Expresso: A database and web server for exploring the interaction of transcription factors and their target genes in Arabidopsis thaliana using ChIP-Seq peak data

F1000Research ◽

10.12688/f1000research.10041.1 ◽

2017 ◽

Vol 6 ◽

pp. 372 ◽

Cited By ~ 7

Author(s):

Delasa Aghamirzaie ◽

Karthik Raja Velmurugan ◽

Shuchi Wu ◽

Doaa Altarawy ◽

Lenwood S. Heath ◽

...

Keyword(s):

Gene Expression ◽

Transcription Factor ◽

Transcription Factors ◽

Chromatin Immunoprecipitation ◽

Target Genes ◽

Regulation Of Gene Expression ◽

Data Sets ◽

Motif Analysis ◽

Chromatin Immunoprecipitation Sequencing

Motivation: The increasing availability of chromatin immunoprecipitation sequencing (ChIP-Seq) data enables us to learn more about the action of transcription factors in the regulation of gene expression. Even though in vivo transcriptional regulation often involves the concerted action of more than one transcription factor, the format of each individual ChIP-Seq dataset usually represents the action of a single transcription factor. Therefore, a relational database in which available ChIP-Seq datasets are curated is essential. Results: We present Expresso (database and webserver) as a tool for the collection and integration of available Arabidopsis ChIP-Seq peak data, which in turn can be linked to a user’s gene expression data. Known target genes of transcription factors were identified by motif analysis of publicly available GEO ChIP-Seq data sets. Expresso currently provides three services: 1) Identification of target genes of a given transcription factor; 2) Identification of transcription factors that regulate a gene of interest; 3) Computation of correlation between the gene expression of transcription factors and their target genes. Availability: Expresso is freely available at http://bioinformatics.cs.vt.edu/expresso/

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Gene expression evolution in pattern-triggered immunity within Arabidopsis thaliana and across Brassicaceae species

10.1101/2020.07.29.227397 ◽

2020 ◽

Author(s):

Thomas M. Winkelmüller ◽

Frederickson Entila ◽

Shajahan Anver ◽

Anna Piasecka ◽

Baoxing Song ◽

...

Keyword(s):

Gene Expression ◽

Arabidopsis Thaliana ◽

Binding Sites ◽

Microbial Control ◽

Purifying Selection ◽

Wrky Transcription Factor ◽

Specific Gene ◽

Specific Expression ◽

Brassicaceae Species ◽

Species Specific

AbstractPlants recognize surrounding microbes by sensing microbe-associated molecular patterns (MAMPs) to activate pattern-triggered immunity (PTI). Despite their significance for microbial control, the evolution of PTI responses remains largely uncharacterized. Employing comparative transcriptomics of six Arabidopsis thaliana accessions and three additional Brassicaceae species for PTI responses to the MAMP flg22, we identified a set of genes with expression changes under purifying selection in the Brassicaceae species and genes exhibiting species-specific expression signatures. Variation in flg22-triggered transcriptome and metabolome responses across Brassicaceae species was incongruent with their phylogeny while expression changes were strongly conserved within A. thaliana, suggesting directional selection for some species-specific gene expression. We found the enrichment of WRKY transcription factor binding sites in 5’-regulatory regions in conserved and species-specific responsive genes, linking the emergence of WRKY-binding sites with the evolution of gene responses in PTI. Our findings advance our understanding of transcriptome evolution during biotic stress.

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target: an R package to predict combined function of transcription factors

F1000Research ◽

10.12688/f1000research.52173.2 ◽

2021 ◽

Vol 10 ◽

pp. 344

Author(s):

Mahmoud Ahmed ◽

Deok Ryong Kim

Keyword(s):

Gene Expression ◽

Transcription Factor ◽

Transcription Factors ◽

Binding Sites ◽

R Package ◽

Expression Data ◽

Bioconductor Package ◽

Chip Experiment ◽

Binding Data ◽

Two Factors

Researchers use ChIP binding data to identify potential transcription factor binding sites. Similarly, they use gene expression data from sequencing or microarrays to quantify the effect of the factor overexpression or knockdown on its targets. Therefore, the integration of the binding and expression data can be used to improve the understanding of a transcription factor function. Here, we implemented the binding and expression target analysis (BETA) in an R/Bioconductor package. This algorithm ranks the targets based on the distances of their assigned peaks from the factor ChIP experiment and the signed statistics from gene expression profiling with factor perturbation. We further extend BETA to integrate two sets of data from two factors to predict their targets and their combined functions. In this article, we briefly describe the workings of the algorithm and provide a workflow with a real dataset for using it. The gene targets and the aggregate functions of transcription factors YY1 and YY2 in HeLa cells were identified. Using the same datasets, we identified the shared targets of the two factors, which were found to be, on average, more cooperatively regulated.

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