scholarly journals Gene-Specific Methylation Profiles for Integrative Methylation-Expression Analysis in Cancer Research

2019 ◽  
Author(s):  
Yusha Liu ◽  
Keith A. Baggerly ◽  
Elias Orouji ◽  
Ganiraju Manyam ◽  
Huiqin Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Penalized Regression ◽  
Tissue Type ◽  
Specific Gene ◽  
Integrative Genomics ◽  
Tissue Specific ◽  
Cancer Subtypes ◽  
Shiny App ◽  
Gene Level

AbstractDNA methylation is a key epigenetic factor regulating gene expression. While promoter-associated methylation has been extensively studied, recent publications have revealed that functionally important methylation also occurs in intergenic and distal regions, and varies across genes and tissue types. Given the growing importance of inter-platform integrative genomic analyses, there is an urgent need to develop methods to construct gene-level methylation summaries that account for the potentially complex relationships between methylation and expression. We introduce a novel sequential penalized regression approach to construct gene-specific methylation profiles (GSMPs) which find for each gene and tissue type a sparse set of CpGs best explaining gene expression and weights indicating direction and strength of association. Using TCGA and MD Anderson colorectal cohorts to build and validate our models, we demonstrate our strategy better explains expression variability than standard approaches and produces gene-level scores showing key methylation differences across recently discovered colorectal cancer subtypes. We share an R Shiny app that presents GSMP results for colorectal, breast, and pancreatic cancer with plans to extend it to all TCGA cancer types. Our approach yields tissue-specific, gene-specific sparse lists of functionally important CpGs that can be used to construct gene-level methylation scores that are maximally correlated with gene expression for use in integrative models, and produce a tissue-specific summary of which genes appear to be strongly regulated by methylation. Our results introduce an important resource to the biomedical community for integrative genomics analyses involving DNA methylation.

scholarly journals Classification of topological domains based on gene expression and regulation

Genome ◽  
2013 ◽  
Vol 56 (7) ◽  
pp. 415-423 ◽  
Author(s):  
Jingjing Zhao ◽  
Hongbo Shi ◽  
Nadav Ahituv
Keyword(s):  
Gene Expression ◽  
Gene Ontology ◽  
Tissue Type ◽  
Specific Gene ◽  
Gene Expression And Regulation ◽  
Genome Chromosome ◽  
Chromosome Conformation ◽  
Topological Domains ◽  
Tissue Specific ◽  
Mouse Tissues

Tissue-specific gene expression is thought to be one of the major forces shaping mammalian gene order. A recent study that used whole-genome chromosome conformation assays has shown that the mammalian genome is divided into specific topological domains that are shared between different tissues and organisms. Here, we wanted to assess whether gene expression and regulation are involved in shaping these domains and can be used to classify them. We analyzed gene expression and regulation levels in these domains by using RNA-seq and enhancer-associated ChIP-seq datasets for 17 different mouse tissues. We found 162 domains that are active (high gene expression and regulation) in all 17 tissues. These domains are significantly shorter, contain less repeats, and have more housekeeping genes. In contrast, we found 29 domains that are inactive (low gene expression and regulation) in all analyzed tissues and are significantly longer, have more repeats, and gene deserts. Tissue-specific active domains showed some correlation with tissue-type and gene ontology. Domain temporal gene regulation and expression differences also displayed some gene ontology terms fitting their temporal function. Combined, our results provide a catalog of shared and tissue-specific topological domains and suggest that gene expression and regulation could have a role in shaping them.

scholarly journals CG methylation covaries with differential gene expression between leaf and floral bud tissues of Brachypodium distachyon

2015 ◽  
Author(s):  
Kyria Roessler ◽  
Shohei Takuno ◽  
Brandon Gaut
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Sequence Data ◽  
Brachypodium Distachyon ◽  
Grass Species ◽  
Specific Gene ◽  
Specific Expression ◽  
Tissue Specific ◽  
Model Grass ◽  
Floral Bud

DNA methylation has the potential to influence plant growth and development through its influence on gene expression. To date, however, the evidence from plant systems is mixed as to whether patterns of DNA methylation vary significantly among tissues and, if so, whether these differences affect tissue-specific gene expression. To address these questions, we analyzed both bisulfite sequence (BSseq) and transcriptomic sequence data from three biological replicates of two tissues (leaf and floral bud) from the model grass species Brachypodium distachyon. Our first goal was to determine whether tissues were more differentiated in DNA methylation than explained by variation among biological replicates. Tissues were more differentiated than biological replicates, but the analysis of replicated data revealed high (>50%) false positive rates for the inference of differentially methylated sites (DMSs) and differentially methylated regions (DMRs). Comparing methylation to gene expression, we found that differential CG methylation consistently covaried negatively with gene expression, regardless as to whether methylation was within genes, within their promoters or even within their closest transposable element. The relationship between gene expression and either CHG or CHH methylation was less consistent. In total, CG methylation in promoters explained 9% of the variation in tissue-specific expression across genes, suggesting that CG methylation is a minor but appreciable factor in tissue differentiation.

scholarly journals DNA Methylation Regulates Placental Lactogen I Gene Expression

Endocrinology ◽  
2001 ◽  
Vol 142 (8) ◽  
pp. 3389-3396 ◽  
Author(s):  
Jae-Hyeon Cho ◽  
Hiromichi Kimura ◽  
Tatsuya Minami ◽  
Jun Ohgane ◽  
Naka Hattori ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Promoter Region ◽  
Trichostatin A ◽  
Methylation Status ◽  
Placental Lactogen ◽  
Specific Gene ◽  
Tissue Specific ◽  
Reporter Activity ◽  
I Gene

Abstract Expression of rat placental lactogen I is specific to the placenta and never expressed in other tissues. To obtain insight into the mechanism of tissue-specific gene expression, we investigated the methylation status in 3.4 kb of the 5′-flanking region of the rat placental lactogen I gene. We found that the distal promoter region of the rat placental lactogen I gene had more potent promoter activity than that of the proximal area alone, which contains several possible cis-elements. Although there are only 17 CpGs in the promoter region, in vitro methylation of the reporter constructs caused severe suppression of reporter activity, and CpG sites in the placenta were more hypomethylated than other tissues. Coexpression of methyl-CpG-binding protein with reporter constructs elicited further suppression of the reporter activity, whereas treatment with trichostatin A, an inhibitor of histone deacetylase, reversed the suppression caused by methylation. Furthermore, treatment of rat placental lactogen I nonexpressing BRL cells with 5-aza-2′-deoxycytidine, an inhibitor of DNA methylation, or trichostatin A resulted in the de novo expression of rat placental lactogen I. These results provide evidence that change in DNA methylation is the fundamental mechanism regulating the tissue-specific expression of the rat placental lactogen I gene.

scholarly journals Prioritizing putative influential genes in early life cardiovascular disease susceptibility by applying tissue-specific Mendelian randomization

2018 ◽  
Author(s):  
Kurt Taylor ◽  
George Davey Smith ◽  
Caroline L Relton ◽  
Tom R Gaunt ◽  
Tom G Richardson
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Disease Susceptibility ◽  
Mendelian Randomization ◽  
Analytical Framework ◽  
Specific Gene ◽  
Multiple Trait ◽  
Trait Variation ◽  
Tissue Specific ◽  
Insight Into

AbstractBackgroundThe extent to which changes in gene expression can influence cardiovascular disease risk across different tissue types has not yet been systematically explored. We have developed an analytical framework that integrates tissue-specific gene expression, Mendelian randomization and multiple-trait colocalization to develop functional mechanistic insight into the causal pathway from genetic variant to complex trait.MethodsWe undertook a transcriptome-wide association study in a population of young individuals to uncover genetic variants associated with both nearby gene expression and cardiovascular traits. Two-sample Mendelian randomization was then applied using large-scale datasets to investigate whether changes in gene expression within certain tissue types may influence cardiovascular trait variation. We subsequently performed Bayesian multiple-trait colocalization to further interrogate findings and also gain insight into whether DNA methylation, as well as gene expression, may play a role in disease susceptibility.ResultsEight genetic loci were associated with changes in gene expression and early life measures of cardiovascular function. Our Mendelian randomization analysis provided evidence of tissue-specific effects at multiple loci, of which the effects at theADCY3andFADS1loci for body mass index and cholesterol respectively were particularly insightful. Multiple trait colocalization uncovered evidence which suggested that changes in DNA methylation at the promoter region upstream ofFADS1/TMEM258may also play a role in cardiovascular trait variation along with gene expression. Furthermore, colocalization analyses were able to uncover evidence of tissue-specificity, most prominantly betweenSORT1expression in liver tissue and cholesterol levels.ConclusionsDisease susceptibility can be influenced by differential changes in tissue-specific gene expression and DNA methylation. Our analytical framework should prove valuable in elucidating mechanisms in disease, as well as helping prioritize putative causal genes at associated loci where multiple nearby genes may be co-regulated. Future studies which continue to uncover quantitative trait loci for molecular traits across various tissue and cell typse will further improve our capability to understand and prevent disease.

scholarly journals Mapping eQTL by leveraging multiple tissues and DNA methylation

2016 ◽  
Author(s):  
Chaitanya R. Acharya ◽  
Kouros Owzar ◽  
Andrew S. Allen
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Specific Gene ◽  
Model Parameters ◽  
Eqtl Mapping ◽  
Joint Tissue ◽  
Tissue Specific ◽  
Cpg Sites ◽  
Micro Rnas ◽  
Mapping Techniques

AbstractBackgroundDNA methylation is an important tissue-specific epigenetic event that influences transcriptional regulation of gene expression. Differentially methylated CpG sites may act as mediators between genetic variation and gene expression, and this relationship can be exploited while mapping multi-tissue expression quantitative trait loci (eQTL). Current multi-tissue eQTL mapping techniques are limited to only exploiting gene expression patterns across multiple tissues either in a joint tissue or tissue-by-tissue frameworks. We present a new statistical approach that enables us to model the effect of germ-line variation on tissue-specific gene expression in the presence of effects due to DNA methylation.ResultsOur method efficiently models genetic and epigenetic variation to identify genomic regions of interest containing combinations of mRNA transcripts, CpG sites, and SNPs by jointly testing for genotypic effect and higher order interaction effects between genotype, methylation and tissues. We demonstrate using Monte Carlo simulations that our approach, in the presence of both genetic and DNA methylation effects, gives an improved performance (in terms of statistical power) to detect eQTLs over the current eQTL mapping approaches. When applied to an array-based dataset from 150 neuropathologically normal adult human brains, our method identifies eQTLs that were undetected using standard tissue-by-tissue or joint tissue eQTL mapping techniques. As an example, our method identifies eQTLs in a BAX inhibiting gene (TMBIM1), which may have a role in the pathogenesis of Alzheimer disease.ConclusionsOur score test-based approach does not need parameter estimation under the alternative hypothesis. As a result, our model parameters are estimated only once for each mRNA - CpG pair. Our model specifically studies the effects of non-coding regions of DNA (in this case, CpG sites) on mapping eQTLs. However, we can easily model micro-RNAs instead of CpG sites to study the effects of post-transcriptional events in mapping eQTL. Our model’s flexible framework also allows us to investigate other genomic events such as alternative gene splicing by extending our model to include gene isoform-specific data.

scholarly journals Methylation of the Cyclin A1 Promoter Correlates with Gene Silencing in Somatic Cell Lines, while Tissue-Specific Expression of Cyclin A1 Is Methylation Independent

2000 ◽  
Vol 20 (9) ◽  
pp. 3316-3329 ◽  
Author(s):  
Carsten Müller ◽  
Carol Readhead ◽  
Sven Diederichs ◽  
Gregory Idos ◽  
Rong Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Lines ◽  
Promoter Methylation ◽  
Cpg Island ◽  
Trichostatin A ◽  
Specific Gene ◽  
Cyclin A1 ◽  
Specific Expression ◽  
Tissue Specific ◽  
Tissue Specific Expression

ABSTRACT Gene expression in mammalian organisms is regulated at multiple levels, including DNA accessibility for transcription factors and chromatin structure. Methylation of CpG dinucleotides is thought to be involved in imprinting and in the pathogenesis of cancer. However, the relevance of methylation for directing tissue-specific gene expression is highly controversial. The cyclin A1 gene is expressed in very few tissues, with high levels restricted to spermatogenesis and leukemic blasts. Here, we show that methylation of the CpG island of the human cyclin A1 promoter was correlated with nonexpression in cell lines, and the methyl-CpG binding protein MeCP2 suppressed transcription from the methylated cyclin A1 promoter. Repression could be relieved by trichostatin A. Silencing of a cyclin A1 promoter-enhanced green fluorescent protein (EGFP) transgene in stable transfected MG63 osteosarcoma cells was also closely associated with de novo promoter methylation. Cyclin A1 could be strongly induced in nonexpressing cell lines by trichostatin A but not by 5-aza-cytidine. The cyclin A1 promoter-EGFP construct directed tissue-specific expression in male germ cells of transgenic mice. Expression in the testes of these mice was independent of promoter methylation, and even strong promoter methylation did not suppress promoter activity. MeCP2 expression was notably absent in EGFP-expressing cells. Transcription from the transgenic cyclin A1 promoter was repressed in most organs outside the testis, even when the promoter was not methylated. These data show the association of methylation with silencing of the cyclin A1 gene in cancer cell lines. However, appropriate tissue-specific repression of the cyclin A1 promoter occurs independently of CpG methylation.

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