Lnc2Meth: a manually curated database of regulatory relationships between long non-coding RNAs and DNA methylation associated with human disease

Abstract

Lnc2Meth (http://www.bio-bigdata.com/Lnc2Meth/), an interactive resource to identify regulatory relationships between human long non-coding RNAs (lncRNAs) and DNA methylation, is not only a manually curated collection and annotation of experimentally supported lncRNAs-DNA methylation associations but also a platform that effectively integrates tools for calculating and identifying the differentially methylated lncRNAs and protein-coding genes (PCGs) in diverse human diseases. The resource provides: (i) advanced search possibilities, e.g. retrieval of the database by searching the lncRNA symbol of interest, DNA methylation patterns, regulatory mechanisms and disease types; (ii) abundant computationally calculated DNA methylation array profiles for the lncRNAs and PCGs; (iii) the prognostic values for each hit transcript calculated from the patients clinical data; (iv) a genome browser to display the DNA methylation landscape of the lncRNA transcripts for a specific type of disease; (v) tools to re-annotate probes to lncRNA loci and identify the differential methylation patterns for lncRNAs and PCGs with user-supplied external datasets; (vi) an R package (LncDM) to complete the differentially methylated lncRNAs identification and visualization with local computers. Lnc2Meth provides a timely and valuable resource that can be applied to significantly expand our understanding of the regulatory relationships between lncRNAs and DNA methylation in various human diseases.

Genome‑wide DNA methylation regulation analysis of long non‑coding RNAs in glioblastoma

“…Since the regulatory mechanism of lncRNA transcription is similar to the regulation of coding genes, 10 kb upstream from the transcriptional start site (TSS) was used for a relatively comprehensive range of lncRNA promoters (17). The 392,867 probes were mapped to the lncRNA promoter regions and only the probe closest to the TSS was used to determine the dNA methylation level of each lncRNA promoter (17,33).…”

Investigating the correlation between DNA methylation and immune‑associated genes of lung adenocarcinoma based on a competing endogenous RNA network

“…For the preprocessed dna methylation data, differential dna methylation regions and associated lncrnas were identified using the lncdM algorithm in a package in r 3.5.3 in March 11, 2019. lncdM is a novel computational method for identifying differentially methylated regions in specific diseases. LncDM uses the Illumina HumanMethylation450 Beadchip Gencode of all annotation information based on the reannotation method and obtains the cpG values of the differential transcript (18). The gene functional regions were used to calculate the patterns of differential methylation.…”

The Challenges and Opportunities of LncRNAs in Ovarian Cancer Research and Clinical Use

“…One reason why gene expression can be dysregulated is methylation status. This can be looked up easily in DiseaseMeth [171], which collects aberrant human methylomes; or more specifically for this topic, in Lnc2Meth [172], which includes regulatory relationships between human long non-coding RNAs and DNA methylation.…”