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

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.

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

2010 ◽  
Vol 9 (4) ◽  
pp. 514-531 ◽  
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.

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

2021 ◽  
Vol 4 (11) ◽  
pp. e202101075
Author(s):  
Stephen Henderson ◽  
Venu Pullabhatla ◽  
Arnulf Hertweck ◽  
Emanuele de Rinaldis ◽  
Javier Herrero ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Infectious Diseases ◽  
Binding Sites ◽  
Target Genes ◽  
Specific Gene ◽  
Type I ◽  
A Genome ◽  
Species Specific

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.

scholarly journals Deciphering the genetic links between NAFLD and co-occurring conditions using a liver gene regulatory network

2021 ◽  
Author(s):  
Sreemol Gokuladhas ◽  
William Schierding ◽  
Roan Eltigani Zaied ◽  
Tayaza Fadason ◽  
Murim Choi ◽  
...  
Keyword(s):  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Complex Traits ◽  
Target Genes ◽  
Specific Gene ◽  
Fat Percentage ◽  
Alcoholic Fatty Liver ◽  
Regulatory Interactions ◽  
Hepatic Diseases ◽  
Gene Regulatory

Background & Aims: Non-alcoholic fatty liver disease (NAFLD) is a multi-system metabolic disease that co-occurs with various hepatic and extra-hepatic diseases. The phenotypic manifestation of NAFLD is primarily observed in the liver. Therefore, identifying liver-specific gene regulatory interactions between variants associated with NAFLD and multimorbid conditions may help to improve our understanding of underlying shared aetiology. Methods: Here, we constructed a liver-specific gene regulatory network (LGRN) consisting of genome-wide spatially constrained expression quantitative trait loci (eQTLs) and their target genes. The LGRN was used to identify regulatory interactions involving NAFLD-associated genetic modifiers and their inter-relationships to other complex traits. Results and Conclusions: We demonstrate that MBOAT7 and IL32, which are associated with NAFLD progression, are regulated by spatially constrained eQTLs that are enriched for an association with liver enzyme levels. MBOAT7 transcript levels are also linked to eQTLs associated with cirrhosis, and other traits that commonly co-occur with NAFLD. In addition, genes that encode interacting partners of NAFLD-candidate genes within the liver-specific protein-protein interaction network were affected by eQTLs enriched for phenotypes relevant to NAFLD (e.g. IgG glycosylation patterns, OSA). Furthermore, we identified distinct gene regulatory networks formed by the NAFLD-associated eQTLs in normal versus diseased liver, consistent with the context-specificity of the eQTLs effects. Interestingly, genes targeted by NAFLD-associated eQTLs within the LGRN were also affected by eQTLs associated with NAFLD-related traits (e.g. obesity and body fat percentage). Overall, the genetic links identified between these traits expand our understanding of shared regulatory mechanisms underlying NAFLD multimorbidities.

scholarly journals Functional effects of variation in transcription factor binding highlight long-range gene regulation by epromoters

2019 ◽  
Author(s):  
Joanna Mitchelmore ◽  
Nastasiya Grinberg ◽  
Chris Wallace ◽  
Mikhail Spivakov
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Statistical Power ◽  
Target Genes ◽  
Allelic Variation ◽  
Regulatory Function ◽  
Regulatory Sequences ◽  
Distal Enhancer ◽  
Association Testing ◽  
Gene Regulatory

AbstractIdentifying DNA cis-regulatory modules (CRMs) that control the expression of specific genes is crucial for deciphering the logic of transcriptional control. Natural genetic variation can point to the possible gene regulatory function of specific sequences through their allelic associations with gene expression. However, comprehensive identification of causal regulatory sequences in brute-force association testing without incorporating prior knowledge is challenging due to limited statistical power and effects of linkage disequilibrium. Sequence variants affecting transcription factor (TF) binding at CRMs have a strong potential to influence gene regulatory function, which provides a motivation for prioritising such variants in association testing. Here, we generate an atlas of CRMs showing predicted allelic variation in TF binding affinity in human lymphoblastoid cell lines (LCLs) and test their association with the expression of their putative target genes inferred from Promoter Capture Hi-C and immediate linear proximity. We reveal over 1300 CRM TF-binding variants associated with target gene expression, the majority of them undetected with standard association testing. A large proportion of CRMs showing associations with the expression of genes they contact in 3D localise to the promoter regions of other genes, supporting the notion of ‘epromoters’: dual-action CRMs with promoter and distal enhancer activity.

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

2013 ◽  
Vol 368 (1632) ◽  
pp. 20130022 ◽  
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.

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

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.

scholarly journals Novel Mechanism of Positive versus Negative Regulation by Thyroid Hormone Receptor β1 (TRβ1) Identified by Genome-wide Profiling of Binding Sites in Mouse Liver

2013 ◽  
Vol 289 (3) ◽  
pp. 1313-1328 ◽  
Author(s):  
Preeti Ramadoss ◽  
Brian J. Abraham ◽  
Linus Tsai ◽  
Yiming Zhou ◽  
Ricardo H. Costa-e-Sousa ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcriptional Regulation ◽  
Thyroid Hormone ◽  
Binding Sites ◽  
Hormone Receptor ◽  
Target Genes ◽  
Thyroid Hormone Receptor ◽  
Negative Regulation ◽  
Genome Wide

Triiodothyronine (T3) regulates key metabolic processes in the liver through the thyroid hormone receptor, TRβ1. However, the number of known target genes directly regulated by TRβ1 is limited, and the mechanisms by which positive and especially negative transcriptional regulation occur are not well understood. To characterize the TRβ1 cistrome in vivo, we expressed a biotinylated TRβ1 in hypo- and hyperthyroid mouse livers, used ChIP-seq to identify genomic TRβ1 targets, and correlated these data with gene expression changes. As with other nuclear receptors, the majority of TRβ1 binding sites were not in proximal promoters but in the gene body of known genes. Remarkably, T3 can dictate changes in TRβ1 binding, with strong correlation to T3-induced gene expression changes, suggesting that differential TRβ1 binding regulates transcriptional outcome. Additionally, DR-4 and DR-0 motifs were significantly enriched at binding sites where T3 induced an increase or decrease in TRβ1 binding, respectively, leading to either positive or negative regulation by T3. Taken together, the results of this study provide new insights into the mechanisms of transcriptional regulation by TRβ1 in vivo.

scholarly journals Expansion of the circadian transcriptome in Brassica rapa and genome-wide diversification of paralog expression patterns

2020 ◽  
Author(s):  
Kathleen Greenham ◽  
Ryan C. Sartor ◽  
Stevan Zorich ◽  
Ping Lou ◽  
Todd C. Mockler ◽  
...  
Keyword(s):  
Gene Expression ◽  
Brassica Rapa ◽  
Regulatory Network ◽  
Time Course ◽  
Expression Patterns ◽  
Time Of Day ◽  
Circadian Regulation ◽  
Genome Wide ◽  
Circadian Control ◽  
Gene Regulatory

AbstractAn important challenge of crop improvement strategies is assigning function to paralogs in polyploid crops. Gene expression is one method for determining the activity of paralogs; however, the majority of transcript abundance data represents a static point that does not consider the spatial and temporal dynamics of the transcriptome. Studies in Arabidopsis have estimated up to 90% of the transcriptome to be under diel or circadian control depending on the condition. As a result, time of day effects on the transcriptome have major implications on how we characterize gene activity. In this study, we aimed to resolve the circadian transcriptome in the polyploid crop Brassica rapa and explore the fate of multicopy orthologs of Arabidopsis circadian regulated genes. We performed a high-resolution time course study with 2 h sampling density to capture the genes under circadian control. Strikingly, more than two-thirds of expressed genes exhibited rhythmicity indicative of circadian regulation. To compare the expression patterns of paralogous genes, we developed a program in R called DiPALM (Differential Pattern Analysis by Linear Models) that analyzes time course data to identify transcripts with significant pattern differences. Using DiPALM, we identified genome-wide divergence of expression patterns among retained paralogs. Cross-comparison with a previously generated diel drought experiment in B. rapa revealed evidence for differential drought response for these diverging paralog pairs. Using gene regulatory network models we compared transcription factor targets between B. rapa and Arabidopsis circadian networks to reveal additional evidence for divergence in expression between B. rapa paralogs that may be driven in part by variation in conserved non coding sequences. These findings provide new insight into the rapid expansion and divergence of the transcriptional network in a polyploid crop and offer a new method for assessing paralog activity at the transcript level.SignificanceThe circadian regulation of the transcriptome leads to time of day changes in gene expression that coordinates environmental conditions with physiological responses. Brassica rapa, a morphologically diverse crop species, has undergone whole genome triplication since diverging from Arabidopsis resulting in an expansion of gene copy number. To examine how this expansion has influenced the circadian transcriptome we developed a new method for comparing gene expression patterns. This method facilitated the discovery of genome-wide expansion of expression patterns for genes present in multiple copies and divergence in temporal abiotic stress response. We find support for conserved sequences outside the gene body contributing to these expression pattern differences and ultimately generating new connections in the gene regulatory network.

scholarly journals Predicting genotype-specific gene regulatory networks

2021 ◽  
Author(s):  
Deborah Weighill ◽  
Marouen Ben Guebila ◽  
Kimberly Glass ◽  
John Quackenbush ◽  
John Platig
Keyword(s):  
Gene Expression ◽  
Gene Regulatory Network ◽  
Gene Regulatory Networks ◽  
Genetic Variants ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Specific Gene ◽  
Disease Etiology ◽  
Gene Regulatory ◽  
The Impact

AbstractThe majority of disease-associated genetic variants are thought to have regulatory effects, including the disruption of transcription factor (TF) binding and the alteration of downstream gene expression. Identifying how a person’s genotype affects their individual gene regulatory network has the potential to provide important insights into disease etiology and to enable improved genotype-specific disease risk assessments and treatments. However, the impact of genetic variants is generally not considered when constructing gene regulatory networks. To address this unmet need, we developed EGRET (Estimating the Genetic Regulatory Effect on TFs), which infers a genotype-specific gene regulatory network (GRN) for each individual in a study population by using message passing to integrate genotype-informed TF motif predictions - derived from individual genotype data, the predicted effects of variants on TF binding and gene expression, and TF motif predictions - with TF protein-protein interactions and gene expression. Comparing EGRET networks for two blood-derived cell lines identified genotype-associated cell-line specific regulatory differences which were subsequently validated using allele-specific expression, chromatin accessibility QTLs, and differential TF binding from ChIP-seq. In addition, EGRET GRNs for three cell types across 119 individuals captured regulatory differences associated with disease in a cell-type-specific manner. Our analyses demonstrate that EGRET networks can capture the impact of genetic variants on complex phenotypes, supporting a novel fine-scale stratification of individuals based on their genetic background. EGRET is available through the Network Zoo R package (netZooR v0.9; netzoo.github.io).

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