Epigenetics
Genetics shapes methylation and expression
Open access · cc by · source: Europe PMC
In HapMap LCLs, promoter methylation associates with genetic variants and transcript levels.
Study at a glance
- Design
- Cross-sectional — Illumina 27K promoter methylation in Yoruba HapMap LCLs linked to genotypes and RNA-seq
- N
- N=77 · 77 LCLs; RNA-seq available for 69
- Population
- HapMap Yoruba lymphoblastoid cell lines
- Outcome
- Genetic and expression correlates of inter-individual DNA methylation
Structured fields used in claim comparison tables when every cited study has a complete layer.
Key findings
Inter-individual methylation variation tracks genetics and correlates with expression.
Methodology
Illumina 27K methylation in 77 Yoruba LCLs related to genotypes and RNA-seq.
Limitations
LCLs are transformed lines, so results may differ from primary tissues.
How this study connects
Role on claims
Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.
Multiple empirical papers in this library examine epigenetics with mechanistic biological findings.
Evidence for the claim as stated.
Inter-individual methylation variation tracks genetics and correlates with expression.
Evidence for the claim as stated.
Systems and scales differ across epigenetics studies (species, tissues, methods), so mechanisms should not be over-generalised.
Evidence for the claim as stated.
RNA-seq can be joined to genetics and to metabolites, still without proving causation. In 77 Yoruba LCLs, inter-individual methylation tracked genotypes and correlated with RNA-seq expression; in Panax ginseng, MEP-pathway expression patterns were taken to contribute to ginsenoside biosynthesis with IspD predicted as a key enzyme.
Evidence for the claim as stated.
Reference-guided counting and de novo assembly are not interchangeable products. CircRNA detection needed non-poly(A) libraries and back-splice calling; Aloe and sea bass papers assemble transcripts because a complete reference is missing or incomplete; LCL and tomato papers quantify against known genes. Treating every RNA-seq paper as a gene-count table hides those design choices.
Evidence for the claim as stated.
How far a transcriptome may be generalised is itself in dispute in these papers. Tomato red-light findings are not automatically all crops; mixed-yeast dilution rates are experimental; LCL methylation–expression links may not hold in primary tissues; coral DEGs do not settle field etiology.
Evidence for the claim as stated.
Expression and methylation can be treated as GWAS-style traits (eQTLs, mQTLs). Liver expression–genotype maps linked common variants to metabolic pathways; in 77 Yoruba LCLs, methylation variation tracked genetics and RNA-seq expression. Those maps are still associations, not proof that each variant causes a disease endpoint.
Evidence for the claim as stated.
Illumina 27K methylation in 77 Yoruba lymphoblastoid cell lines tracked genotypes and correlated with RNA-seq expression. LCLs are transformed lines, so primary-tissue methylation may differ.
Evidence for the claim as stated.
Bisulfite designs here are not one map. VTRNA2-1 is a multi-tissue epiallele stable ≥10 years and sensitive to periconceptional season; the ageing paper compresses 102 AR-CpGs into a 3-site blood clock (MAD 3.34 years); Yoruba 27K arrays link methylation to genetics and expression in 77 LCLs. A clock CpG is not an environment-set metastable epiallele.
Evidence for the claim as stated.
Illumina 27K methylation in 77 Yoruba LCLs related to genotypes and RNA-seq: inter-individual methylation variation tracks genetics and correlates with expression. That is a methylation array plus RNA-seq, not ChIP-seq; LCLs may differ from primary tissues.
Evidence for the claim as stated.
Only the rice histone-acylation paper is clearly genome-wide ChIP-seq of chromatin marks (Kbu/Kcr versus H3K9ac under stress). Foxp3 work is candidate-locus ChIP; FECR1 is CasIP of promoter RNAs; Yoruba data are 27K methylation arrays. Treating them as one ChIP-seq method overstates shared technology.
Evidence for the claim as stated.
Open questions
Tensions this paper is part of
From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.
Systems and scales differ across epigenetics studies (species, tissues, methods), so mechanisms should not be over-generalised.
- Supports · Epigenetic locking of Foxp3 in Tregs
- Supports · A DNA methylation clock for human age
Reference-guided counting and de novo assembly are not interchangeable products. CircRNA detection needed non-poly(A) libraries and back-splice calling; Aloe and sea bass papers assemble transcripts because a complete reference is missing or incomplete; LCL and tomato papers quantify against known genes. Treating every RNA-seq paper as a gene-count table hides those design choices.
- Supports · Cataloging mammalian circular RNAs
- Supports · Aloe vera medicinal pathway transcriptome
How far a transcriptome may be generalised is itself in dispute in these papers. Tomato red-light findings are not automatically all crops; mixed-yeast dilution rates are experimental; LCL methylation–expression links may not hold in primary tissues; coral DEGs do not settle field etiology.
- Supports · Does red light help tomatoes fight bacteria?
- Supports · What do co-fermenting yeasts express together?
- Supports · Coral gene expression in white syndromes
Bisulfite designs here are not one map. VTRNA2-1 is a multi-tissue epiallele stable ≥10 years and sensitive to periconceptional season; the ageing paper compresses 102 AR-CpGs into a 3-site blood clock (MAD 3.34 years); Yoruba 27K arrays link methylation to genetics and expression in 77 LCLs. A clock CpG is not an environment-set metastable epiallele.
- Supports · VTRNA2-1: an environment-sensitive human epiallele
- Supports · Three CpGs track blood aging
Only the rice histone-acylation paper is clearly genome-wide ChIP-seq of chromatin marks (Kbu/Kcr versus H3K9ac under stress). Foxp3 work is candidate-locus ChIP; FECR1 is CasIP of promoter RNAs; Yoruba data are 27K methylation arrays. Treating them as one ChIP-seq method overstates shared technology.
- Supports · Histone acylations respond to plant stress
- Supports · Epigenetic locking of Foxp3 in Tregs
- Supports · FLI1 circRNA FECR1 drives metastasis
Related papers in this topic
Same topic cluster — not a recommendation engine.