Evidence map›Paper›PMID 39702713›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

LncRNA Recognition-Associated CpG Island Detection and Methylation Analysis.

Yujie You, Ming Xiao, Le Zhang

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Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Yujie YouCollege of computer science, Sichuan University, Chengdu, China.
Ming XiaoCollege of computer science, Sichuan University, Chengdu, China.
Le ZhangCollege of computer science, Sichuan University, Chengdu, China. zhangle06@scu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

CpG islands (CGIs) are rare, interspersed DNA sequences, which possess a significant deviation from background genomic distribution by exhibiting patterns of GC-rich and CpG-rich sequence, the density of which provides a good classification feature for long noncoding RNA (lncRNA) promoters. By reviewing previous CpG-related studies, we consider that the transcription regulation of about half of the human genes, mostly housekeeping (HK) genes, involves CGIs, their methylation states, CpG spacing, and other chromosomal parameters. However, the precise CGI definition and positioning of CGIs within gene structures, as well as specific CGI-associated regulatory mechanisms, all remain to be elucidated at individual gene and gene family levels, together with consideration of species and lineage specificity. Although previous studies have already classified CGIs into high-CpG (HCGI), intermediate-CpG (ICGI), and low-CpG (LCGI) densities based on CpG density variation, the correlation between CGI density and gene expression regulation, such as co-regulation of CGIs and TATA-box on HK genes, is not clear. Here, we introduce such a problem-solving protocol for human genome annotation, which is based on a combination of GTEx, JBLA, and GO analysis. Next, we discuss why CGI-associated genes are most likely regulated by HCGI and tend to be HK genes; The HCGI/TATA± and LCGI/TATA± combinations show different GO enrichment, whereas the ICGI/TATA± combination is less characteristic than LCGI/TATA± based on GO enrichment analysis.

Indexed as

CpG IslandsDNA MethylationRNA, Long NoncodingComputational BiologyGene Expression RegulationGenome, HumanHumansMolecular Sequence AnnotationPromoter Regions, GeneticRNA, Long NoncodingCpG IslandGenome analysisGenome annotationLncRNAStatistical genetics

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.