scholarly journals Altered transcription factor binding events predict personalized gene expression and confer insight into functional cis-regulatory variants

2017 ◽  
Author(s):  
Wenqiang Shi ◽  
Oriol Fornes ◽  
Wyeth W. Wasserman
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
External Validation ◽  
Genetic Studies ◽  
Functional Roles ◽  
Regulatory Variants ◽  
Regulatory Variant ◽  
Using Data ◽  
The Impact ◽  
Insight Into

AbstractDeciphering the functional roles of cis-regulatory variants is a critical challenge in genome analysis and interpretation. We hypothesize that altered transcription factor (TF) binding events are a central mechanism by which cis-regulatory variants impact gene expression. We present TF2Exp, the first gene-based framework (to our knowledge) to predict the impact of altered TF binding on personalized gene expression based on cis-regulatory variants. Using data from lymphoblastoid cell lines, TF2Exp models achieved suitable performance for 3,060 genes. Alterations within DNase I hypersensitive, CTCF-bound, and tissue-specific TF-bound regions were the greatest contributors to the models. Our cis-regulatory variant-based TF2Exp models performed as well as the state-of-the-art SNP-based models, both in cross-validation and external validation. In addition, unlike SNP-based models, our TF2Exp models have the unique advantages to evaluate impact of uncommon variants and distinguish the functional roles of variants in linkage disequilibrium, showing broader utility for future human genetic studies.

scholarly journals Gene expression models based on transcription factor binding events confer insight into functional cis-regulatory variants

2018 ◽  
Vol 35 (15) ◽  
pp. 2610-2617 ◽  
Author(s):  
Wenqiang Shi ◽  
Oriol Fornes ◽  
Wyeth W Wasserman
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
External Validation ◽  
Model Performance ◽  
Supplementary Information ◽  
Expression Levels ◽  
Functional Roles ◽  
Regulatory Variants ◽  
The Impact ◽  
Gene Expression Levels

Abstract Motivation Deciphering the functional roles of cis-regulatory variants is a critical challenge in genome analysis and interpretation. It has been hypothesized that altered transcription factor (TF) binding events are a central mechanism by which cis-regulatory variants impact gene expression levels. However, we lack a computational framework to understand and quantify such mechanistic contributions. Results We present TF2Exp, a gene-based framework to predict the impact of altered TF-binding events on gene expression levels. Using data from lymphoblastoid cell lines, TF2Exp models were applied successfully to predict the expression levels of 3196 genes. Alterations within DNase I hypersensitive, CTCF-bound and tissue-specific TF-bound regions were the greatest contributing features to the models. TF2Exp models performed as well as models based on common variants, both in cross-validation and external validation. Combining TF alteration and common variant features can further improve model performance. Unlike variant-based models, TF2Exp models have the unique advantage to evaluate the functional impact of variants in linkage disequilibrium and uncommon variants. We find that adding TF-binding events altered only by uncommon variants could increase the number of predictable genes (R2 > 0.05). Taken together, TF2Exp represents a key step towards interpreting the functional roles of cis-regulatory variants in the human genome. Availability and implementation The code and model training results are publicly available at https://github.com/wqshi/TF2Exp. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Aberrant expression of USF2 in refractory rheumatoid arthritis and its regulation of proinflammatory cytokines in Th17 cells

2020 ◽  
Vol 117 (48) ◽  
pp. 30639-30648
Author(s):  
Dan Hu ◽  
Emily C. Tjon ◽  
Karin M. Andersson ◽  
Gabriela M. Molica ◽  
Minh C. Pham ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
T Cells ◽  
Transcription Factor ◽  
Proinflammatory Cytokines ◽  
Th17 Cells ◽  
Gene Set Enrichment Analysis ◽  
Aberrant Expression ◽  
Signature Genes ◽  
The Impact

IL-17–producing Th17 cells are implicated in the pathogenesis of rheumatoid arthritis (RA) and TNF-α, a proinflammatory cytokine in the rheumatoid joint, facilitates Th17 differentiation. Anti-TNF therapy ameliorates disease in many patients with rheumatoid arthritis (RA). However, a significant proportion of patients do not respond to this therapy. The impact of anti-TNF therapy on Th17 responses in RA is not well understood. We conducted high-throughput gene expression analysis of Th17-enriched CCR6+CXCR3−CD45RA−CD4+T (CCR6+T) cells isolated from anti-TNF–treated RA patients classified as responders or nonresponders to therapy. CCR6+T cells from responders and nonresponders had distinct gene expression profiles. Proinflammatory signaling was elevated in the CCR6+T cells of nonresponders, and pathogenic Th17 signature genes were up-regulated in these cells. Gene set enrichment analysis on these signature genes identified transcription factor USF2 as their upstream regulator, which was also increased in nonresponders. Importantly, short hairpin RNA targetingUSF2in pathogenic Th17 cells led to reduced expression of proinflammatory cytokines IL-17A, IFN-γ, IL-22, and granulocyte-macrophage colony-stimulating factor (GM-CSF) as well as transcription factor T-bet. Together, our results revealed inadequate suppression of Th17 responses by anti-TNF in nonresponders, and direct targeting of the USF2-signaling pathway may be a potential therapeutic approach in the anti-TNF refractory RA.

scholarly journals Validation of the BATT score for prehospital risk stratification of traumatic haemorrhagic death: usefulness for tranexamic acid treatment criteria

2021 ◽  
Vol 29 (1) ◽  
Author(s):  
Francois-Xavier Ageron ◽  
Timothy J. Coats ◽  
Vincent Darioli ◽  
Ian Roberts
Keyword(s):  
Tranexamic Acid ◽  
Acid Treatment ◽  
Injury Severity ◽  
External Validation ◽  
Research Network ◽  
Brier Score ◽  
Trauma Patients ◽  
Using Data ◽  
The Uk ◽  
The Impact

Abstract Background Tranexamic acid reduces surgical blood loss and reduces deaths from bleeding in trauma patients. Tranexamic acid must be given urgently, preferably by paramedics at the scene of the injury or in the ambulance. We developed a simple score (Bleeding Audit Triage Trauma score) to predict death from bleeding. Methods We conducted an external validation of the BATT score using data from the UK Trauma Audit Research Network (TARN) from 1st January 2017 to 31st December 2018. We evaluated the impact of tranexamic acid treatment thresholds in trauma patients. Results We included 104,862 trauma patients with an injury severity score of 9 or above. Tranexamic acid was administered to 9915 (9%) patients. Of these 5185 (52%) received prehospital tranexamic acid. The BATT score had good accuracy (Brier score = 6%) and good discrimination (C-statistic 0.90; 95% CI 0.89–0.91). Calibration in the large showed no substantial difference between predicted and observed death due to bleeding (1.15% versus 1.16%, P = 0.81). Pre-hospital tranexamic acid treatment of trauma patients with a BATT score of 2 or more would avoid 210 bleeding deaths by treating 61,598 patients instead of avoiding 55 deaths by treating 9915 as currently. Conclusion The BATT score identifies trauma patient at risk of significant haemorrhage. A score of 2 or more would be an appropriate threshold for pre-hospital tranexamic acid treatment.

scholarly journals Modeling transcriptional regulation using gene regulatory networks based on multi-omics data sources

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Neel Patel ◽  
William S. Bush
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Transcriptional Regulation ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Prediction Models ◽  
Long Distance ◽  
Chromatin Looping ◽  
Gene Regulatory ◽  
The Impact

Abstract Background Transcriptional regulation is complex, requiring multiple cis (local) and trans acting mechanisms working in concert to drive gene expression, with disruption of these processes linked to multiple diseases. Previous computational attempts to understand the influence of regulatory mechanisms on gene expression have used prediction models containing input features derived from cis regulatory factors. However, local chromatin looping and trans-acting mechanisms are known to also influence transcriptional regulation, and their inclusion may improve model accuracy and interpretation. In this study, we create a general model of transcription factor influence on gene expression by incorporating both cis and trans gene regulatory features. Results We describe a computational framework to model gene expression for GM12878 and K562 cell lines. This framework weights the impact of transcription factor-based regulatory data using multi-omics gene regulatory networks to account for both cis and trans acting mechanisms, and measures of the local chromatin context. These prediction models perform significantly better compared to models containing cis-regulatory features alone. Models that additionally integrate long distance chromatin interactions (or chromatin looping) between distal transcription factor binding regions and gene promoters also show improved accuracy. As a demonstration of their utility, effect estimates from these models were used to weight cis-regulatory rare variants for sequence kernel association test analyses of gene expression. Conclusions Our models generate refined effect estimates for the influence of individual transcription factors on gene expression, allowing characterization of their roles across the genome. This work also provides a framework for integrating multiple data types into a single model of transcriptional regulation.

scholarly journals RSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding

2019 ◽  
Vol 17 ◽  
pp. 1415-1428 ◽  
Author(s):  
Walter Santana-Garcia ◽  
Maria Rocha-Acevedo ◽  
Lucia Ramirez-Navarro ◽  
Yvon Mbouamboua ◽  
Denis Thieffry ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Transcription Factor Binding ◽  
Factor Binding ◽  
Regulatory Variants ◽  
Flexible Framework ◽  
The Impact

scholarly journals Direct and widespread role for the nuclear receptor EcR in mediating the response to ecdysone in Drosophila

2019 ◽  
Vol 116 (20) ◽  
pp. 9893-9902 ◽  
Author(s):  
Christopher M. Uyehara ◽  
Daniel J. McKay
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Nuclear Receptor ◽  
Binding Sites ◽  
Transcriptional Responses ◽  
Enhancer Activity ◽  
Developmental Transitions ◽  
Experimental Systems ◽  
The Impact

The ecdysone pathway was among the first experimental systems employed to study the impact of steroid hormones on the genome. In Drosophila and other insects, ecdysone coordinates developmental transitions, including wholesale transformation of the larva into the adult during metamorphosis. Like other hormones, ecdysone controls gene expression through a nuclear receptor, which functions as a ligand-dependent transcription factor. Although it is clear that ecdysone elicits distinct transcriptional responses within its different target tissues, the role of its receptor, EcR, in regulating target gene expression is incompletely understood. In particular, EcR initiates a cascade of transcription factor expression in response to ecdysone, making it unclear which ecdysone-responsive genes are direct EcR targets. Here, we use the larval-to-prepupal transition of developing wings to examine the role of EcR in gene regulation. Genome-wide DNA binding profiles reveal that EcR exhibits widespread binding across the genome, including at many canonical ecdysone response genes. However, the majority of its binding sites reside at genes with wing-specific functions. We also find that EcR binding is temporally dynamic, with thousands of binding sites changing over time. RNA-seq reveals that EcR acts as both a temporal gate to block precocious entry to the next developmental stage as well as a temporal trigger to promote the subsequent program. Finally, transgenic reporter analysis indicates that EcR regulates not only temporal changes in target enhancer activity but also spatial patterns. Together, these studies define EcR as a multipurpose, direct regulator of gene expression, greatly expanding its role in coordinating developmental transitions.

scholarly journals Insight into GATA1 transcriptional activity through interrogation of cis elements disrupted in human erythroid disorders

2016 ◽  
Vol 113 (16) ◽  
pp. 4434-4439 ◽  
Author(s):  
Aoi Wakabayashi ◽  
Jacob C. Ulirsch ◽  
Leif S. Ludwig ◽  
Claudia Fiorini ◽  
Makiko Yasuda ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Transcriptional Activity ◽  
Regulatory Elements ◽  
Binding Motif ◽  
Targeted Disruption ◽  
Altered Gene Expression ◽  
Whole Exome ◽  
Altered Gene ◽  
Insight Into

Whole-exome sequencing has been incredibly successful in identifying causal genetic variants and has revealed a number of novel genes associated with blood and other diseases. One limitation of this approach is that it overlooks mutations in noncoding regulatory elements. Furthermore, the mechanisms by which mutations in transcriptional cis-regulatory elements result in disease remain poorly understood. Here we used CRISPR/Cas9 genome editing to interrogate three such elements harboring mutations in human erythroid disorders, which in all cases are predicted to disrupt a canonical binding motif for the hematopoietic transcription factor GATA1. Deletions of as few as two to four nucleotides resulted in a substantial decrease (>80%) in target gene expression. Isolated deletions of the canonical GATA1 binding motif completely abrogated binding of the cofactor TAL1, which binds to a separate motif. Having verified the functionality of these three GATA1 motifs, we demonstrate strong evolutionary conservation of GATA1 motifs in regulatory elements proximal to other genes implicated in erythroid disorders, and show that targeted disruption of such elements results in altered gene expression. By modeling transcription factor binding patterns, we show that multiple transcription factors are associated with erythroid gene expression, and have created predictive maps modeling putative disruptions of their binding sites at key regulatory elements. Our study provides insight into GATA1 transcriptional activity and may prove a useful resource for investigating the pathogenicity of noncoding variants in human erythroid disorders.

scholarly journals RegVar: Tissue-specific Prioritization of Noncoding Regulatory Variants

2021 ◽  
Author(s):  
Hao Lu ◽  
Luyu Ma ◽  
Lei Li ◽  
Cheng Quan ◽  
Yiming Lu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Human Genetics ◽  
Computational Framework ◽  
Tissue Specific ◽  
Regulatory Variants ◽  
Regulatory Impact ◽  
Genome Variations ◽  
The Impact ◽  
Specific Impact

Noncoding genomic variants constitute the majority of trait-associated genome variations; however, identification of functional noncoding variants is still a challenge in human genetics, and a method systematically assessing the impact of regulatory variants on gene expression and linking them to potential target genes is still lacking. Here we introduce a deep neural network (DNN)-based computational framework, RegVar, that can accurately predict the tissue-specific impact of noncoding regulatory variants on target genes. We show that, by robustly learning the genomic characteristics of massive variant-gene expression associations in a variety of human tissues, RegVar vastly surpasses all current noncoding variants prioritization methods in predicting regulatory variants under different circumstances. The unique features of RegVar make it an excellent framework for assessing the regulatory impact of any variant on its putative target genes in a variety of tissues. RegVar is available as a webserver at http://regvar.cbportal.org/.

scholarly journals Genetic and neural relationships underpinning impulsivity

2013 ◽  
Vol 6 ◽  
pp. 80-93 ◽  
Author(s):  
Nichol Wong ◽  
Tatia Lee
Keyword(s):  
Decision Making ◽  
Psychological Functioning ◽  
Future Research ◽  
Social Psychological ◽  
Genetic Studies ◽  
Neural Underpinnings ◽  
Clinical Conditions ◽  
The Impact ◽  
Insight Into ◽  
The Continuum

Impulsivity refers to acting without forethought. It can be detrimental to daily social functioning and interaction, and is significantly implicated in several clinical conditions, e.g. violence and addiction. Evidence for the neural underpinnings of impulsivity from both healthy and clinical populations, integrated with the findings from genetic studies on the same topic, lend important insight into a neurobehavioral model of impulsivity. In this review, disinhibition and impulsive decision-making in the impulsivity construct are covered. Recent behavioral and imaging-genetic studies on the topic will also be reviewed and discussed. Findings from neuroimaging studies, clinical studies, and genetic studies converge to provide a better understanding of individual differences on the continuum. Future research efforts should continue to focus on the association approach to identify relevant neural-behavioral correlations in order for elucidating the impact from genes through neural to behavioral phenotypes. These potential findings, when being incorporated with physiological and immunological measures, would not only hasten understanding of impulsivity, but guide interventions development for ameliorating maladaptive social/psychological functioning disorders underpinned by it.

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