scholarly journals Passive and active DNA methylation and the interplay with genetic variation in gene regulation

eLife ◽  
2013 ◽  
Vol 2 ◽  
Author(s):  
Maria Gutierrez-Arcelus ◽  
Tuuli Lappalainen ◽  
Stephen B Montgomery ◽  
Alfonso Buil ◽  
Halit Ongen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Gene Regulation ◽  
Genetic Variation ◽  
Genomic Sequence ◽  
Expression Patterns ◽  
Active Role ◽  
Epigenetic Mark ◽  
Sequencing Data ◽  
Specific Expression

DNA methylation is an essential epigenetic mark whose role in gene regulation and its dependency on genomic sequence and environment are not fully understood. In this study we provide novel insights into the mechanistic relationships between genetic variation, DNA methylation and transcriptome sequencing data in three different cell-types of the GenCord human population cohort. We find that the association between DNA methylation and gene expression variation among individuals are likely due to different mechanisms from those establishing methylation-expression patterns during differentiation. Furthermore, cell-type differential DNA methylation may delineate a platform in which local inter-individual changes may respond to or act in gene regulation. We show that unlike genetic regulatory variation, DNA methylation alone does not significantly drive allele specific expression. Finally, inferred mechanistic relationships using genetic variation as well as correlations with TF abundance reveal both a passive and active role of DNA methylation to regulatory interactions influencing gene expression.

scholarly journals Methylation by multiple type I restriction modification systems avoids influencing gene regulation in uropathogenic Escherichia coli

2021 ◽  
Author(s):  
Kurosh S Mehershahi ◽  
Swaine Chen
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Dna Methylation ◽  
Gene Regulation ◽  
Detectable Effect ◽  
Epigenetic Mark ◽  
Type I ◽  
E Coli ◽  
Restriction Modification ◽  
Restriction Modification Systems

DNA methylation is a common epigenetic mark that influences transcriptional regulation, and therefore cellular phenotype, across all domains of life, extending also to bacterial virulence. Both orphan methyltransferases and those from restriction modification systems (RMSs) have been co-opted to regulate virulence epigenetically in many bacteria. However, the potential regulatory role of DNA methylation mediated by archetypal Type I systems in Escherichia coli has never been studied. We demonstrated that removal of DNA methylated mediated by three different Escherichia coli Type I RMSs in three distinct E. coli strains had no detectable effect on gene expression or growth in a screen of 1190 conditions. Additionally, deletion of the Type I RMS EcoUTI in UTI89, a prototypical cystitis strain of E. coli , which led to loss of methylation at >750 sites across the genome, had no detectable effect on virulence in a murine model of ascending urinary tract infection (UTI). Finally, introduction of two heterologous Type I RMSs into UTI89 also resulted in no detectable change in gene expression or growth phenotypes. These results stand in sharp contrast with many reports of RMSs regulating gene expression in other bacteria, leading us to propose the concept of “regulation avoidance” for these E. coli Type I RMSs. We hypothesize that regulation avoidance is a consequence of evolutionary adaptation of both the RMSs and the E. coli genome. Our results provide a clear and (currently) rare example of regulation avoidance for Type I RMSs in multiple strains of E. coli , further study of which may provide deeper insights into the evolution of gene regulation and horizontal gene transfer.

scholarly journals Can Forest Trees Cope with Climate Change?—Effects of DNA Methylation on Gene Expression and Adaptation to Environmental Change

2021 ◽  
Vol 22 (24) ◽  
pp. 13524
Author(s):  
Ewelina A. Klupczyńska ◽  
Ewelina Ratajczak
Keyword(s):  
Climate Change ◽  
Gene Expression ◽  
Dna Methylation ◽  
Global Climate ◽  
Regional Climate ◽  
Expression Patterns ◽  
Forest Tree ◽  
Epigenetic Modifications ◽  
Specific Expression ◽  
Epigenome Editing

Epigenetic modifications, including chromatin modifications and DNA methylation, play key roles in regulating gene expression in both plants and animals. Transmission of epigenetic markers is important for some genes to maintain specific expression patterns and preserve the status quo of the cell. This article provides a review of existing research and the current state of knowledge about DNA methylation in trees in the context of global climate change, along with references to the potential of epigenome editing tools and the possibility of their use for forest tree research. Epigenetic modifications, including DNA methylation, are involved in evolutionary processes, developmental processes, and environmental interactions. Thus, the implications of epigenetics are important for adaptation and phenotypic plasticity because they provide the potential for tree conservation in forest ecosystems exposed to adverse conditions resulting from global warming and regional climate fluctuations.

scholarly journals Assessing the Gene Regulatory Landscape in 1,188 Human Tumors

2017 ◽  
Author(s):  
C Calabrese ◽  
K Lehmann ◽  
L Urban ◽  
F Liu ◽  
S Erkek ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
Large Scale ◽  
Human Cancer ◽  
Expression Patterns ◽  
Regulatory Elements ◽  
Whole Genome ◽  
Somatic Variation ◽  
Specific Expression ◽  
Large Scale Assessment

AbstractCancer is characterised by somatic genetic variation, but the effect of the majority of non-coding somatic variants and the interface with the germline genome are still unknown. We analysed the whole genome and RNA-Seq data from 1,188 human cancer patients as provided by the Pan-cancer Analysis of Whole Genomes (PCAWG) project to map cis expression quantitative trait loci of somatic and germline variation and to uncover the causes of allele-specific expression patterns in human cancers. The availability of the first large-scale dataset with both whole genome and gene expression data enabled us to uncover the effects of the non-coding variation on cancer. In addition to confirming known regulatory effects, we identified novel associations between somatic variation and expression dysregulation, in particular in distal regulatory elements. Finally, we uncovered links between somatic mutational signatures and gene expression changes, including TERT and LMO2, and we explained the inherited risk factors in APOBEC-related mutational processes. This work represents the first large-scale assessment of the effects of both germline and somatic genetic variation on gene expression in cancer and creates a valuable resource cataloguing these effects.

scholarly journals Promoter and Terminator Optimization for DNA Methylation Targeting in Arabidopsis

Epigenomes ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 9
Author(s):  
Jason Gardiner ◽  
Jenny M. Zhao ◽  
Kendall Chaffin ◽  
Steven E. Jacobsen
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Arabidopsis Thaliana ◽  
Gene Regulation ◽  
Nicotiana Tabacum ◽  
New Technologies ◽  
Catalytic Domain ◽  
Epigenetic Mark ◽  
Phenotypic Changes ◽  
Promising Tool

DNA methylation is an important epigenetic mark involved in gene regulation and silencing of transposable elements. The presence or absence of DNA methylation at specific sites can influence nearby gene expression and cause phenotypic changes that remain stable over generations. Recently, development of new technologies has enabled the targeted addition or removal of DNA methylation at specific sites of the genome. Of these new technologies, the targeting of the catalytic domain of Nicotiana tabacum DOMAINS REARRANGED METHYLTRANSFERASE 2 (ntDRM2cd) offers a promising tool for the addition of DNA methylation as it can directly methylate DNA. However, the methylation targeting efficiency of constructs using ntDRM2cd thus far has been relatively low. Previous studies have shown that the use of different promoters or terminators can greatly improve genome-editing efficiencies. In this study, we systematically survey a variety of promoter and terminator combinations to identify optimal combinations to use when targeting the addition of DNA methylation in Arabidopsis thaliana.

scholarly journals Diverse transcriptomic signatures across human tissues identify functional rare genetic variation

2019 ◽  
Author(s):  
Nicole M. Ferraro ◽  
Benjamin J. Strober ◽  
Jonah Einson ◽  
Xin Li ◽  
Francois Aguet ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
Rare Variants ◽  
Sequencing Data ◽  
Specific Expression ◽  
Aberrant Gene Expression ◽  
Rare Genetic Variation ◽  
Allele Specific ◽  
The Uk ◽  
Aberrant Gene

AbstractRare genetic variation is abundant in the human genome, yet identifying functional rare variants and their impact on traits remains challenging. Measuring aberrant gene expression has aided in identifying functional, large-effect rare variants. Here, we expand detection of genetically driven transcriptome abnormalities by evaluating and integrating gene expression, allele-specific expression, and alternative splicing from multi-tissue RNA-sequencing data. We demonstrate that each signal informs unique classes of rare variants. We further develop Watershed, a probabilistic model that integrates multiple genomic and transcriptomic signals to predict variant function. Assessing rare variants prioritized by Watershed in the UK Biobank and Million Veterans Program, we identify large effects across 34 traits, and 33 rare variant-trait combinations with both high Watershed scores and large trait effect sizes. Together, we provide a comprehensive analysis of the transcriptomic impact of rare variation and a framework to prioritize functional rare variants and assess their trait relevance.One-sentence summaryIntegrating expression, allelic expression and splicing across tissues identifies rare variants with relevance to traits.

scholarly journals Exploring the Genetic Basis of Human Population Differences in DNA Methylation and their Causal Impact on Immune Gene Regulation

2018 ◽  
Author(s):  
Lucas T. Husquin ◽  
Maxime Rotival ◽  
Maud Fagny ◽  
Hélène Quach ◽  
Nora Zidane ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Gene Regulation ◽  
Complex Traits ◽  
Active Role ◽  
System Level ◽  
Immune Gene ◽  
Population Differences ◽  
Mediation Effects ◽  
Causal Impact

AbstractDNA methylation is influenced by both environmental and genetic factors and is increasingly thought to affect variation in complex traits and diseases. Yet, the extent of ancestry-related differences in DNA methylation, its genetic determinants, and their respective causal impact on immune gene regulation remain elusive. We report extensive population differences in DNA methylation between individuals of African and European descent — detected in primary monocytes that were used as a model of a major innate immunity cell type. Most of these differences (~70%) were driven by DNA sequence variants nearby CpG sites (meQTLs), which account for ~60% of the variance in DNA methylation. We also identify several master regulators of DNA methylation variation in trans, including a regulatory hub nearby the transcription factor-encoding CTCF gene, which contributes markedly to ancestry-related differences in DNA methylation. Furthermore, we establish that variation in DNA methylation is associated with varying gene expression levels following mostly, but not exclusively, a canonical model of negative associations, particularly in enhancer regions. Specifically, we find that DNA methylation highly correlates with transcriptional activity of 811 and 230 genes, at the basal state and upon immune stimulation, respectively. Finally, using a Bayesian approach, we estimate causal mediation effects of DNA methylation on gene expression in ~20% of the studied cases, indicating that DNA methylation can play an active role in immune gene regulation. Using a system-level approach, our study reveals substantial ancestry-related differences in DNA methylation and provides evidence for their causal impact on immune gene regulation.

scholarly journals Gene Regulation, Modulation, and Their Applications in Gene Expression Data Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Mario Flores ◽  
Tzu-Hung Hsiao ◽  
Yu-Chiao Chiu ◽  
Eric Y. Chuang ◽  
Yufei Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Regulation ◽  
Data Analysis ◽  
Expression Patterns ◽  
Preliminary Finding ◽  
Next Generation Sequencing Data ◽  
Regulation Mechanism ◽  
Sequencing Data ◽  
Rna Regulation ◽  
Network Construction

Common microarray and next-generation sequencing data analysis concentrate on tumor subtype classification, marker detection, and transcriptional regulation discovery during biological processes by exploring the correlated gene expression patterns and their shared functions. Genetic regulatory network (GRN) based approaches have been employed in many large studies in order to scrutinize for dysregulation and potential treatment controls. In addition to gene regulation and network construction, the concept of the network modulator that has significant systemic impact has been proposed, and detection algorithms have been developed in past years. Here we provide a unified mathematic description of these methods, followed with a brief survey of these modulator identification algorithms. As an early attempt to extend the concept to new RNA regulation mechanism, competitive endogenous RNA (ceRNA), into a modulator framework, we provide two applications to illustrate the network construction, modulation effect, and the preliminary finding from these networks. Those methods we surveyed and developed are used to dissect the regulated network under different modulators. Not limit to these, the concept of “modulation” can adapt to various biological mechanisms to discover the novel gene regulation mechanisms.

FC 011KIDNEYNETWORK: USING KIDNEY DERIVED GENE EXPRESSION DATA TO PREDICT AND PRIORITIZE NOVEL GENES INVOLVED IN KIDNEY DISEASE

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Floranne Boulogne ◽  
Laura Claus ◽  
Henry Wiersma ◽  
Roy Oelen ◽  
Floor Schukking ◽  
...  
Keyword(s):  
Gene Expression ◽  
Kidney Disease ◽  
Candidate Gene ◽  
Exome Sequencing ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Genetic Diagnosis ◽  
Specific Gene ◽  
Sequencing Data ◽  
Exome Sequencing Data

Abstract Background and Aims Genetic testing in patients with suspected hereditary kidney disease does not always reveal the genetic cause for the patient's disorder. Potentially pathogenic variants can reside in genes that are not known to be involved in kidney disease, which makes it difficult to prioritize and interpret the relevance of these variants. As such, there is a clear need for methods that predict the phenotypic consequences of gene expression in a way that is as unbiased as possible. To help identify candidate genes we have developed KidneyNetwork, in which tissue-specific expression is utilized to predict kidney-specific gene functions. Method We combined gene co-expression in 878 publicly available kidney RNA-sequencing samples with the co-expression of a multi-tissue RNA-sequencing dataset of 31,499 samples to build KidneyNetwork. The expression patterns were used to predict which genes have a kidney-related function, and which (disease) phenotypes might be caused when these genes are mutated. By integrating the information from the HPO database, in which known phenotypic consequences of disease genes are annotated, with the gene co-expression network we obtained prediction scores for each gene per HPO term. As proof of principle, we applied KidneyNetwork to prioritize variants in exome-sequencing data from 13 kidney disease patients without a genetic diagnosis. Results We assessed the prediction performance of KidneyNetwork by comparing it to GeneNetwork, a multi-tissue co-expression network we previously developed. In KidneyNetwork, we observe a significantly improved prediction accuracy of kidney-related HPO-terms, as well as an increase in the total number of significantly predicted kidney-related HPO-terms (figure 1). To examine its clinical utility, we applied KidneyNetwork to 13 patients with a suspected hereditary kidney disease without a genetic diagnosis. Based on the HPO terms “Renal cyst” and “Hepatic cysts”, combined with a list of potentially damaging variants in one of the undiagnosed patients with mild ADPKD/PCLD, we identified ALG6 as a new candidate gene. ALG6 bears a high resemblance to other genes implicated in this phenotype in recent years. Through the 100,000 Genomes Project and collaborators we identified three additional patients with kidney and/or liver cysts carrying a suspected deleterious variant in ALG6. Conclusion We present KidneyNetwork, a kidney specific co-expression network that accurately predicts what genes have kidney-specific functions and may result in kidney disease. Gene-phenotype associations of genes unknown for kidney-related phenotypes can be predicted by KidneyNetwork. We show the added value of KidneyNetwork by applying it to exome sequencing data of kidney disease patients without a molecular diagnosis and consequently we propose ALG6 as a promising candidate gene. KidneyNetwork can be applied to clinically unsolved kidney disease cases, but it can also be used by researchers to gain insight into individual genes to better understand kidney physiology and pathophysiology. Acknowledgments This research was made possible through access to the data and findings generated by the 100,000 Genomes Project; http://www.genomicsengland.co.uk.

Abstract 15: Glucose-Mediated Remodeling of Cardiac DNA Methylation

2017 ◽  
Vol 121 (suppl_1) ◽  
Author(s):  
Mark E Pepin ◽  
David K Crossman ◽  
Joseph P Barchue ◽  
Salpy V Pamboukian ◽  
Steven M Pogwizd ◽  
...  
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Dna Methylation ◽  
Diabetic Cardiomyopathy ◽  
Left Ventricular ◽  
Epigenetic Mark ◽  
Gene Transcript ◽  
Transcript Levels ◽  
Glycemic Memory

To identify the role of glucose in the development of diabetic cardiomyopathy, we had directly assessed glucose delivery to the intact heart on alterations of DNA methylation and gene expression using both an inducible heart-specific transgene (glucose transporter 4; mG4H) and streptozotocin-induced diabetes (STZ) mouse models. We aimed to determine whether long-lasting diabetic complications arise from prior transient exposure to hyperglycemia via a process termed “glycemic memory.” We had identified DNA methylation changes associated with significant gene expression regulation. Comparing our results from STZ, mG4H, and the modifications which persist following transgene silencing, we now provide evidence for cardiac DNA methylation as a persistent epigenetic mark contributing to glycemic memory. To begin to determine which changes contribute to human heart failure, we measured both RNA transcript levels and whole-genome DNA methylation in heart failure biopsy samples (n = 12) from male patients collected at left ventricular assist device placement using RNA-sequencing and Methylation450 assay, respectively. We hypothesized that epigenetic changes such as DNA methylation distinguish between heart failure etiologies. Our findings demonstrated that type 2 diabetic heart failure patients (n = 6) had an overall signature of hypomethylation, whereas patients listed as ischemic (n = 5) had a distinct hypermethylation signature for regulated transcripts. The focus of this initial analysis was on promoter-associated CpG islands with inverse changes in gene transcript levels, from which diabetes (14 genes; e.g. IGFBP4) and ischemic (12 genes; e.g. PFKFB3) specific targets emerged with significant regulation of both measures. By combining our mouse and human molecular analyses, we provide evidence that diabetes mellitus governs direct regulation of cellular function by DNA methylation and the corresponding gene expression in diabetic mouse and human hearts. Importantly, many of the changes seen in either mouse type 1 diabetes or human type 2 diabetes were similar supporting a consistent mechanism of regulation. These studies are some of the first steps at defining mechanisms of epigenetic regulation in diabetic cardiomyopathy.

scholarly journals Gene expression profiling of epigenetic chromatin modification enzymes and histone marks by cigarette smoke: implications for COPD and lung cancer

2016 ◽  
Vol 311 (6) ◽  
pp. L1245-L1258 ◽  
Author(s):  
Isaac K. Sundar ◽  
Irfan Rahman
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Dna Methylation ◽  
Cigarette Smoke ◽  
Histone Modifications ◽  
Expression Patterns ◽  
Chromatin Modification ◽  
Gene Expression Patterns ◽  
Validation Data ◽  
Histone Marks

Chromatin-modifying enzymes mediate DNA methylation and histone modifications on recruitment to specific target gene loci in response to various stimuli. The key enzymes that regulate chromatin accessibility for maintenance of modifications in DNA and histones, and for modulation of gene expression patterns in response to cigarette smoke (CS), are not known. We hypothesize that CS exposure alters the gene expression patterns of chromatin-modifying enzymes, which then affects multiple downstream pathways involved in the response to CS. We have, therefore, analyzed chromatin-modifying enzyme profiles and validated by quantitative real-time PCR (qPCR). We also performed immunoblot analysis of targeted histone marks in C57BL/6J mice exposed to acute and subchronic CS, and of lungs from nonsmokers, smokers, and patients with chronic obstructive pulmonary disease (COPD). We found a significant increase in expression of several chromatin modification enzymes, including DNA methyltransferases, histone acetyltransferases, histone methyltransferases, and SET domain proteins, histone kinases, and ubiquitinases. Our qPCR validation data revealed a significant downregulation of Dnmt1, Dnmt3a, Dnmt3b, Hdac2, Hdac4, Hat1, Prmt1, and Aurkb. We identified targeted chromatin histone marks (H3K56ac and H4K12ac), which are induced by CS. Thus CS-induced genotoxic stress differentially affects the expression of epigenetic modulators that regulate transcription of target genes via DNA methylation and site-specific histone modifications. This may have implications in devising epigenetic-based therapies for COPD and lung cancer.

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