scholarly journals Chromatin features define adaptive genomic regions in a fungal plant pathogen

2020 ◽  
Author(s):  
David E. Cook ◽  
Martin Kramer ◽  
Michael F. Seidl ◽  
Bart PHJ Thomma
Keyword(s):  
Dna Methylation ◽  
Repetitive Dna ◽  
Genetic Diseases ◽  
Machine Learning Algorithms ◽  
Chromatin State ◽  
Dna Accessibility ◽  
Complex Information ◽  
Determine Function ◽  
A Genome ◽  
Genomic Regions

ABSTRACTUnderstanding the complex information stored in a genome remains challenging since multiple connected regulatory mechanisms act at various scales to determine function. Increased comprehension of genome function at scales beyond contiguous nucleotides will help understand genetic diseases, the emergence of pathogenesis, and more broadly the genomics of adaptation. Here we report the analysis of DNA methylation, histone modification, and DNA accessibility in the plant pathogenic vascular wilt fungus Verticillium dahliae. Functional analysis details that DNA methylation is restricted to repetitive elements, such as transposable element DNA, but interestingly only some repetitive DNA is methylated. This incomplete DNA methylation is associated with repetitive DNA residing in specific compartments of the genome that were previously defined as Lineage-Specific (LS) regions. These regions are hypervariable between V. dahliae isolates and contain genes that support host colonization and adaptive traits. LS regions are associated with H3 Lys-27 methylated histones (H3K27me3), and repetitive DNA within LS regions are more transcriptionally active and have increased DNA accessibility, representing a hybrid chromatin state when compared to repetitive regions within the core genome. We used machine learning algorithms trained on epigenetic and DNA accessibility data to predict LS regions with high recall, identifying approximately twice as much LS DNA in the V. dahliae genome as previously recognized. Collectively, these results characterize LS regions in an intermediate chromatin state and provide evidence that links chromatin features and genome architecture to adaptive regions within the genome.

scholarly journals DNA methylation associated with postpartum depressive symptoms overlaps findings from a genome-wide association meta-analysis of depression

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Dana M. Lapato ◽  
Roxann Roberson-Nay ◽  
Robert M. Kirkpatrick ◽  
Bradley T. Webb ◽  
Timothy P. York ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Depressive Symptoms ◽  
Health Outcomes ◽  
Meta Analysis ◽  
Previous History ◽  
Depression Scale ◽  
Postpartum Depressive Symptoms ◽  
Genome Wide ◽  
A Genome ◽  
Genomic Regions

Abstract Background Perinatal depressive symptoms have been linked to adverse maternal and infant health outcomes. The etiology associated with perinatal depressive psychopathology is poorly understood, but accumulating evidence suggests that understanding inter-individual differences in DNA methylation (DNAm) patterning may provide insight regarding the genomic regions salient to the risk liability of perinatal depressive psychopathology. Results Genome-wide DNAm was measured in maternal peripheral blood using the Infinium MethylationEPIC microarray. Ninety-two participants (46% African-American) had DNAm samples that passed all quality control metrics, and all participants were within 7 months of delivery. Linear models were constructed to identify differentially methylated sites and regions, and permutation testing was utilized to assess significance. Differentially methylated regions (DMRs) were defined as genomic regions of consistent DNAm change with at least two probes within 1 kb of each other. Maternal age, current smoking status, estimated cell-type proportions, ancestry-relevant principal components, days since delivery, and chip position served as covariates to adjust for technical and biological factors. Current postpartum depressive symptoms were measured using the Edinburgh Postnatal Depression Scale. Ninety-eight DMRs were significant (false discovery rate < 5%) and overlapped 92 genes. Three of the regions overlap loci from the latest Psychiatric Genomics Consortium meta-analysis of depression. Conclusions Many of the genes identified in this analysis corroborate previous allelic, transcriptomic, and DNAm association results related to depressive phenotypes. Future work should integrate data from multi-omic platforms to understand the functional relevance of these DMRs and refine DNAm association results by limiting phenotypic heterogeneity and clarifying if DNAm differences relate to the timing of onset, severity, duration of perinatal mental health outcomes of the current pregnancy or to previous history of depressive psychopathology.

scholarly journals DNA Methylation Associated with Postpartum Depressive Symptoms Overlaps Findings from a Genome-wide Association Meta-Analysis of Depression

2019 ◽  
Author(s):  
Dana M. Lapato ◽  
Roxann Roberson-Nay ◽  
Robert M. Kirkpatrick ◽  
Bradley T. Webb ◽  
Timothy P. York ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Depressive Symptoms ◽  
Health Outcomes ◽  
Meta Analysis ◽  
Previous History ◽  
Depression Scale ◽  
Postpartum Depressive Symptoms ◽  
Genome Wide ◽  
A Genome ◽  
Genomic Regions

AbstractBackgroundPerinatal depressive symptoms have been linked to adverse maternal and infant health outcomes. The etiology associated with perinatal depressive psychopathology is poorly understood, but accumulating evidence suggests that understanding inter-individual differences in DNA methylation (DNAm) patterning may provide insight regarding the genomic regions salient to the risk liability of perinatal depressive psychopathology.ResultsGenome-wide DNAm was measured in maternal peripheral blood using the Infinium MethylationEPIC microarray. Ninety-two participants (46% African-American) had DNAm samples that passed all quality control metrics, and all participants were within seven months of delivery. Linear models were constructed to identify differentially methylated sites and regions, and permutation testing was utilized to assess significance. Differentially methylated regions (DMRs) were defined as genomic regions of consistent DNAm change with at least two probes within 1kb of each other. Maternal age, current smoking status, estimated cell-type proportions, ancestry-relevant principal components, days since delivery, and chip position served as covariates to adjust for technical and biological factors. Current postpartum depressive symptoms were measured using the Edinburgh Postnatal Depression Scale. Ninety-eight DMRs were significant (False Discovery Rate < 5%) and overlapped 92 genes. Synaptic signaling, neural development, and platelet formation were the most represented biological processes in gene set analysis, and comparison to the 44 loci discovered in the latest Psychiatric Genomics Consortium meta-analysis of depression revealed 3 overlapping regions and significant enrichment (p<0.03).ConclusionsMany of the genes identified in this analysis corroborate previous allelic, transcriptomic, and DNAm association results related to depressive phenotypes. Future work should integrate data from multi-omic platforms to understand the functional relevance of these DMRs and refine DNAm association results by limiting phenotypic heterogeneity and clarifying if DNAm differences relate to the timing of onset, severity, duration of perinatal mental health outcomes of the current pregnancy or to previous history of depressive psychopathology.

DNA methylation in satellite repeats disorders

2019 ◽  
Vol 63 (6) ◽  
pp. 757-771 ◽  
Author(s):  
Claire Francastel ◽  
Frédérique Magdinier
Keyword(s):  
Dna Methylation ◽  
Human Genome ◽  
Repetitive Dna ◽  
Dna Sequences ◽  
Satellite Repeats ◽  
Tremendous Progress ◽  
Genes Encoding ◽  
Dna Elements ◽  
Near Future

Abstract Despite the tremendous progress made in recent years in assembling the human genome, tandemly repeated DNA elements remain poorly characterized. These sequences account for the vast majority of methylated sites in the human genome and their methylated state is necessary for this repetitive DNA to function properly and to maintain genome integrity. Furthermore, recent advances highlight the emerging role of these sequences in regulating the functions of the human genome and its variability during evolution, among individuals, or in disease susceptibility. In addition, a number of inherited rare diseases are directly linked to the alteration of some of these repetitive DNA sequences, either through changes in the organization or size of the tandem repeat arrays or through mutations in genes encoding chromatin modifiers involved in the epigenetic regulation of these elements. Although largely overlooked so far in the functional annotation of the human genome, satellite elements play key roles in its architectural and topological organization. This includes functions as boundary elements delimitating functional domains or assembly of repressive nuclear compartments, with local or distal impact on gene expression. Thus, the consideration of satellite repeats organization and their associated epigenetic landmarks, including DNA methylation (DNAme), will become unavoidable in the near future to fully decipher human phenotypes and associated diseases.

scholarly journals Profile of copper-associated DNA methylation and its association with incident acute coronary syndrome

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Pinpin Long ◽  
Qiuhong Wang ◽  
Yizhi Zhang ◽  
Xiaoyan Zhu ◽  
Kuai Yu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Acute Coronary Syndrome ◽  
Methylation Level ◽  
Meta Analysis ◽  
Regulation Of Gene Expression ◽  
Density Lipoprotein ◽  
Blood Leukocytes ◽  
Coronary Syndrome ◽  
A Genome ◽  
Increased Risk

Abstract Background Acute coronary syndrome (ACS) is a cardiac emergency with high mortality. Exposure to high copper (Cu) concentration has been linked to ACS. However, whether DNA methylation contributes to the association between Cu and ACS is unclear. Methods We measured methylation level at > 485,000 cytosine-phosphoguanine sites (CpGs) of blood leukocytes using Human Methylation 450 Bead Chip and conducted a genome-wide meta-analysis of plasma Cu in a total of 1243 Chinese individuals. For plasma Cu-related CpGs, we evaluated their associations with the expression of nearby genes as well as major cardiovascular risk factors. Furthermore, we examined their longitudinal associations with incident ACS in the nested case-control study. Results We identified four novel Cu-associated CpGs (cg20995564, cg18608055, cg26470501 and cg05825244) within a 5% false discovery rate (FDR). DNA methylation level of cg18608055, cg26470501, and cg05825244 also showed significant correlations with expressions of SBNO2, BCL3, and EBF4 gene, respectively. Higher DNA methylation level at cg05825244 locus was associated with lower high-density lipoprotein cholesterol level and higher C-reactive protein level. Furthermore, we demonstrated that higher cg05825244 methylation level was associated with increased risk of ACS (odds ratio [OR], 1.23; 95% CI 1.02–1.48; P = 0.03). Conclusions We identified novel DNA methylation alterations associated with plasma Cu in Chinese populations and linked these loci to risk of ACS, providing new insights into the regulation of gene expression by Cu-related DNA methylation and suggesting a role for DNA methylation in the association between copper and ACS.

scholarly journals A machine learning case–control classifier for schizophrenia based on DNA methylation in blood

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chathura J. Gunasekara ◽  
Eilis Hannon ◽  
Harry MacKay ◽  
Cristian Coarfa ◽  
Andrew McQuillin ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Population Based ◽  
Case Control ◽  
Training Data ◽  
Polygenic Risk Score ◽  
Reverse Causality ◽  
Cell Type Specificity ◽  
Data Set ◽  
Human Genomic ◽  
Genomic Regions

AbstractEpigenetic dysregulation is thought to contribute to the etiology of schizophrenia (SZ), but the cell type-specificity of DNA methylation makes population-based epigenetic studies of SZ challenging. To train an SZ case–control classifier based on DNA methylation in blood, therefore, we focused on human genomic regions of systemic interindividual epigenetic variation (CoRSIVs), a subset of which are represented on the Illumina Human Methylation 450K (HM450) array. HM450 DNA methylation data on whole blood of 414 SZ cases and 433 non-psychiatric controls were used as training data for a classification algorithm with built-in feature selection, sparse partial least squares discriminate analysis (SPLS-DA); application of SPLS-DA to HM450 data has not been previously reported. Using the first two SPLS-DA dimensions we calculated a “risk distance” to identify individuals with the highest probability of SZ. The model was then evaluated on an independent HM450 data set on 353 SZ cases and 322 non-psychiatric controls. Our CoRSIV-based model classified 303 individuals as cases with a positive predictive value (PPV) of 80%, far surpassing the performance of a model based on polygenic risk score (PRS). Importantly, risk distance (based on CoRSIV methylation) was not associated with medication use, arguing against reverse causality. Risk distance and PRS were positively correlated (Pearson r = 0.28, P = 1.28 × 10−12), and mediational analysis suggested that genetic effects on SZ are partially mediated by altered methylation at CoRSIVs. Our results indicate two innate dimensions of SZ risk: one based on genetic, and the other on systemic epigenetic variants.

scholarly journals Epigenome-Wide Study Identified Methylation Sites Associated with the Risk of Obesity

Nutrients ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1984
Author(s):  
Majid Nikpay ◽  
Sepehr Ravati ◽  
Robert Dent ◽  
Ruth McPherson
Keyword(s):  
Quantitative Trait Locus ◽  
Quantitative Trait ◽  
Rare Variants ◽  
Genome Wide ◽  
A Genome ◽  
Genome Wide Search ◽  
Risk Snps ◽  
Trait Locus ◽  
Genomic Regions ◽  
Eqtl Data

Here, we performed a genome-wide search for methylation sites that contribute to the risk of obesity. We integrated methylation quantitative trait locus (mQTL) data with BMI GWAS information through a SNP-based multiomics approach to identify genomic regions where mQTLs for a methylation site co-localize with obesity risk SNPs. We then tested whether the identified site contributed to BMI through Mendelian randomization. We identified multiple methylation sites causally contributing to the risk of obesity. We validated these findings through a replication stage. By integrating expression quantitative trait locus (eQTL) data, we noted that lower methylation at cg21178254 site upstream of CCNL1 contributes to obesity by increasing the expression of this gene. Higher methylation at cg02814054 increases the risk of obesity by lowering the expression of MAST3, whereas lower methylation at cg06028605 contributes to obesity by decreasing the expression of SLC5A11. Finally, we noted that rare variants within 2p23.3 impact obesity by making the cg01884057 site more susceptible to methylation, which consequently lowers the expression of POMC, ADCY3 and DNAJC27. In this study, we identify methylation sites associated with the risk of obesity and reveal the mechanism whereby a number of these sites exert their effects. This study provides a framework to perform an omics-wide association study for a phenotype and to understand the mechanism whereby a rare variant causes a disease.

scholarly journals Identification of DNA methylation signatures associated with poor outcome in lower-risk Stage, Size, Grade and Necrosis (SSIGN) score clear cell renal cell cancer

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Louis Y. El Khoury ◽  
Shuang Fu ◽  
Ryan A. Hlady ◽  
Ryan T. Wagner ◽  
Liguo Wang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Renal Cell ◽  
Lower Risk ◽  
Clear Cell ◽  
Cell Cancer ◽  
Low Risk ◽  
Cell Renal Cell Carcinoma ◽  
A Genome ◽  
Size Grade ◽  
Prognostic Power

Abstract Background Despite using prognostic algorithms and standard surveillance guidelines, 17% of patients initially diagnosed with low risk clear cell renal cell carcinoma (ccRCC) ultimately relapse and die of recurrent disease, indicating additional molecular parameters are needed for improved prognosis. Results To address the gap in ccRCC prognostication in the lower risk population, we performed a genome-wide analysis for methylation signatures capable of distinguishing recurrent and non-recurrent ccRCCs within the subgroup classified as ‘low risk’ by the Mayo Clinic Stage, Size, Grade, and Necrosis score (SSIGN 0–3). This approach revealed that recurrent patients have globally hypermethylated tumors and differ in methylation significantly at 5929 CpGs. Differentially methylated CpGs (DMCpGs) were enriched in regulatory regions and genes modulating cell growth and invasion. A subset of DMCpGs stratified low SSIGN groups into high and low risk of recurrence in independent data sets, indicating that DNA methylation enhances the prognostic power of the SSIGN score. Conclusions This study reports a global DNA hypermethylation in tumors of recurrent ccRCC patients. Furthermore, DMCpGs were capable of discriminating between aggressive and less aggressive tumors, in addition to SSIGN score. Therefore, DNA methylation presents itself as a potentially strong biomarker to further improve prognostic power in patients with low risk SSIGN score (0–3).

scholarly journals Blood-Based Detection of Colorectal Cancer Using Cancer-Specific DNA Methylation Markers

Diagnostics ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 51
Author(s):  
Nam-Yun Cho ◽  
Ji-Won Park ◽  
Xianyu Wen ◽  
Yun-Joo Shin ◽  
Jun-Kyu Kang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Sensitivity And Specificity ◽  
Stage Iv ◽  
High Sensitivity ◽  
Liquid Biopsies ◽  
Blood Leukocytes ◽  
Marker Panel ◽  
A Genome ◽  
Methylight Assay

Cancer tissues have characteristic DNA methylation profiles compared with their corresponding normal tissues that can be utilized for cancer diagnosis with liquid biopsy. Using a genome-scale DNA methylation approach, we sought to identify a panel of DNA methylation markers specific for cell-free DNA (cfDNA) from patients with colorectal cancer (CRC). By comparing DNA methylomes between CRC and normal mucosal tissues or blood leukocytes, we identified eight cancer-specific methylated loci (ADGRB1, ANKRD13, FAM123A, GLI3, PCDHG, PPP1R16B, SLIT3, and TMEM90B) and developed a five-marker panel (FAM123A, GLI3, PPP1R16B, SLIT3, and TMEM90B) that detected CRC in liquid biopsies with a high sensitivity and specificity with a droplet digital MethyLight assay. In a set of cfDNA samples from CRC patients (n = 117) and healthy volunteers (n = 60), a panel of five markers on the platform of the droplet digital MethyLight assay detected stages I–III and stage IV CRCs with sensitivities of 45.9% and 95.7%, respectively, and a specificity of 95.0%. The number of detected markers was correlated with the cancer stage, perineural invasion, lymphatic emboli, and venous invasion. Our five-marker panel with the droplet digital MethyLight assay showed a high sensitivity and specificity for the detection of CRC with cfDNA samples from patients with metastatic CRC.

scholarly journals LncRNA:DNA triplex-forming sites are positioned at specific areas of genome organization and are predictors for Topologically Associated Domains

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Benjamin Soibam ◽  
Ayzhamal Zhamangaraeva
Keyword(s):  
Genome Organization ◽  
Chromatin Organization ◽  
Ctcf Binding ◽  
General Mechanism ◽  
Promoter Regions ◽  
Cellular Processes ◽  
A Genome ◽  
Topologically Associated Domains ◽  
Multiple Cell ◽  
Genomic Regions

Abstract Background Chromosomes are organized into units called topologically associated domains (TADs). TADs dictate regulatory landscapes and other DNA-dependent processes. Even though various factors that contribute to the specification of TADs have been proposed, the mechanism is not fully understood. Understanding the process for specification and maintenance of these units is essential in dissecting cellular processes and disease mechanisms. Results In this study, we report a genome-wide study that considers the idea of long noncoding RNAs (lncRNAs) mediating chromatin organization using lncRNA:DNA triplex-forming sites (TFSs). By analyzing the TFSs of expressed lncRNAs in multiple cell lines, we find that they are enriched in TADs, their boundaries, and loop anchors. However, they are evenly distributed across different regions of a TAD showing no preference for any specific portions within TADs. No relationship is observed between the locations of these TFSs and CTCF binding sites. However, TFSs are located not just in promoter regions but also in intronic, intergenic, and 3’UTR regions. We also show these triplex-forming sites can be used as predictors in machine learning models to discriminate TADs from other genomic regions. Finally, we compile a list of important “TAD-lncRNAs” which are top predictors for TADs identification. Conclusions Our observations advocate the idea that lncRNA:DNA TFSs are positioned at specific areas of the genome organization and are important predictors for TADs. LncRNA:DNA triplex formation most likely is a general mechanism of action exhibited by some lncRNAs, not just for direct gene regulation but also to mediate 3D chromatin organization.

Drosophila Gain-of-Function Mutant RTK Torso Triggers Ectopic Dpp and STAT Signaling

Genetics ◽  
2003 ◽  
Vol 164 (1) ◽  
pp. 247-258 ◽  
Author(s):  
Jinghong Li ◽  
Willis X Li
Keyword(s):  
Tyrosine Kinases ◽  
Target Genes ◽  
Tor Signaling ◽  
Gain Of Function ◽  
Essential Requirement ◽  
Downstream Target ◽  
Rtk Signaling ◽  
Genome Wide ◽  
A Genome ◽  
Genomic Regions

Abstract Overactivation of receptor tyrosine kinases (RTKs) has been linked to tumorigenesis. To understand how a hyperactivated RTK functions differently from wild-type RTK, we conducted a genome-wide systematic survey for genes that are required for signaling by a gain-of-function mutant Drosophila RTK Torso (Tor). We screened chromosomal deficiencies for suppression of a gain-of-function mutation tor (torGOF), which led to the identification of 26 genomic regions that, when in half dosage, suppressed the defects caused by torGOF. Testing of candidate genes in these regions revealed many genes known to be involved in Tor signaling (such as those encoding the Ras-MAPK cassette, adaptor and structural molecules of RTK signaling, and downstream target genes of Tor), confirming the specificity of this genetic screen. Importantly, this screen also identified components of the TGFβ (Dpp) and JAK/STAT pathways as being required for TorGOF signaling. Specifically, we found that reducing the dosage of thickveins (tkv), Mothers against dpp (Mad), or STAT92E (aka marelle), respectively, suppressed torGOF phenotypes. Furthermore, we demonstrate that in torGOF embryos, dpp is ectopically expressed and thus may contribute to the patterning defects. These results demonstrate an essential requirement of noncanonical signaling pathways for a persistently activated RTK to cause pathological defects in an organism.

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