scholarly journals Genome-wide DNA methylation and RNA expression profiles identified RIPK3 as a differentially methylated gene in Chlamydia pneumoniae infection lung carcinoma patients in China

2019 ◽  
Vol Volume 11 ◽  
pp. 5785-5797
Author(s):  
Wei-Min Xiong ◽  
Qiu-Ping Xu ◽  
Ren-Dong Xiao ◽  
Zhi-Jian Hu ◽  
Lin Cai ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Lung Carcinoma ◽  
Chlamydia Pneumoniae ◽  
Expression Profiles ◽  
Rna Expression ◽  
Genome Wide ◽  
Differentially Methylated Gene

scholarly journals Inference of Crosstalk Effects between DNA Methylation and lncRNA Regulation in NSCLC

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Binhua Tang
Keyword(s):  
Clinical Trial ◽  
Dna Methylation ◽  
Lung Carcinoma ◽  
Analytic Functions ◽  
Nsclc Tissue ◽  
Genome Wide Analysis ◽  
Clinical Trial Research ◽  
Omics Integration ◽  
Genome Wide ◽  
Tissue Profiling

Intercellular crosstalk effects between DNA methylation and lncRNA regulation remain elusive in lung carcinoma epigenetics. We present an application toolkit MetLnc in integration and annotation for group-wise NSCLC tissue-based DNA methylation and lncRNA profiling resources, to comprehensively analyze differentially methylated loci and lncRNAs through genome-wide analysis. Together with multiple analytic functions, MetLnc acts as an efficient approach on epigenetic omics integration and interrogation. Via the benchmark with group-wise NSCLC tissue profiling and TCGA cohort resources, we study differentially methylated CpG loci and lncRNAs as meaningful clues for inferring crosstalk effects between DNA methylation and lncRNA regulation; together we conclude with investigated biomarkers for further epigenetics and clinical trial research.

Genome-wide analysis of long non-coding RNA expression profiles in keratinocytes from psoriasis skin

2021 ◽  
Author(s):  
Longlong Luo ◽  
Nupur khera ◽  
Andor Pivarcsi ◽  
Ankit Srivastava ◽  
Lorenzo Pasquali ◽  
...  
Keyword(s):  
Expression Profiles ◽  
Rna Expression ◽  
Genome Wide Analysis ◽  
Non Coding Rna ◽  
Genome Wide ◽  
Long Non Coding Rna

scholarly journals Genome-wide characterization of DNA methylation, small RNA expression, and histone H3 lysine nine di-methylation in Brassica rapa L.

DNA Research ◽  
2018 ◽  
Vol 25 (5) ◽  
pp. 511-520 ◽  
Author(s):  
Satoshi Takahashi ◽  
Kenji Osabe ◽  
Naoki Fukushima ◽  
Shohei Takuno ◽  
Naomi Miyaji ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Brassica Rapa ◽  
Small Rna ◽  
Histone H3 ◽  
Rna Expression ◽  
Genome Wide

scholarly journals DNA hypermethylation associated with upregulated gene expression in prostate cancer demonstrates the diversity of epigenetic regulation

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Ieva Rauluseviciute ◽  
Finn Drabløs ◽  
Morten Beck Rye
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Dna Methylation ◽  
Epigenetic Regulation ◽  
Normal Tissue ◽  
Expression Profiles ◽  
Expression Data ◽  
Dna Hypermethylation ◽  
Genome Wide ◽  
A Genome

Abstract Background Prostate cancer (PCa) has the highest incidence rates of cancers in men in western countries. Unlike several other types of cancer, PCa has few genetic drivers, which has led researchers to look for additional epigenetic and transcriptomic contributors to PCa development and progression. Especially datasets on DNA methylation, the most commonly studied epigenetic marker, have recently been measured and analysed in several PCa patient cohorts. DNA methylation is most commonly associated with downregulation of gene expression. However, positive associations of DNA methylation to gene expression have also been reported, suggesting a more diverse mechanism of epigenetic regulation. Such additional complexity could have important implications for understanding prostate cancer development but has not been studied at a genome-wide scale. Results In this study, we have compared three sets of genome-wide single-site DNA methylation data from 870 PCa and normal tissue samples with multi-cohort gene expression data from 1117 samples, including 532 samples where DNA methylation and gene expression have been measured on the exact same samples. Genes were classified according to their corresponding methylation and expression profiles. A large group of hypermethylated genes was robustly associated with increased gene expression (UPUP group) in all three methylation datasets. These genes demonstrated distinct patterns of correlation between DNA methylation and gene expression compared to the genes showing the canonical negative association between methylation and expression (UPDOWN group). This indicates a more diversified role of DNA methylation in regulating gene expression than previously appreciated. Moreover, UPUP and UPDOWN genes were associated with different compartments — UPUP genes were related to the structures in nucleus, while UPDOWN genes were linked to extracellular features. Conclusion We identified a robust association between hypermethylation and upregulation of gene expression when comparing samples from prostate cancer and normal tissue. These results challenge the classical view where DNA methylation is always associated with suppression of gene expression, which underlines the importance of considering corresponding expression data when assessing the downstream regulatory effect of DNA methylation.

Long-term genome-wide blood RNA expression profiles yield novel molecular response candidates for IFN-β-1b treatment in relapsing remitting MS

2010 ◽  
Vol 11 (2) ◽  
pp. 147-161 ◽  
Author(s):  
Robert H Goertsches ◽  
Michael Hecker ◽  
Dirk Koczan ◽  
Pablo Serrano-Fernandez ◽  
Steffen Moeller ◽  
...  
Keyword(s):  
Expression Profiles ◽  
Rna Expression ◽  
Molecular Response ◽  
Genome Wide ◽  
Relapsing Remitting

scholarly journals DNA methylation and RNA expression profiles in lung adenocarcinomas of never-smokers

2015 ◽  
Vol 208 (5) ◽  
pp. 253-260 ◽  
Author(s):  
Aaron S. Mansfield ◽  
Liang Wang ◽  
Julie M. Cunningham ◽  
Jin Jen ◽  
Christopher P. Kolbert ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Expression Profiles ◽  
Rna Expression ◽  
Never Smokers ◽  
Lung Adenocarcinomas

COMPUTATIONAL STRATEGY FOR DISCOVERING DRUGGABLE GENE NETWORKS FROM GENOME-WIDE RNA EXPRESSION PROFILES

2005 ◽  
Author(s):  
SEIYA IMOTO ◽  
YOSHINORI TAMADA ◽  
HIROMITSU ARAKI ◽  
KAORI YASUDA ◽  
CRISTIN G. PRINT ◽  
...  
Keyword(s):  
Gene Networks ◽  
Expression Profiles ◽  
Rna Expression ◽  
Genome Wide ◽  
Computational Strategy
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