Evidence map›Paper›PMID 42902179›Full record

ArticleBMC genomics2026

DNA methylation defines lineage identity yet converges among functionally related cells and is cell‑specifically remodeled during in vitro passaging.

Lanlan Sun, Dongmei Chen, Xin Zhang, Hailang Fan, Yaqian Zhao, Yingdi Huang, Yang Wu, Yanni Lou, Dake Zhang

Abstract read
In one paragraph

Article in BMC genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Lanlan Sun *Key Laboratory of Biomechanics and Mechanobiology, Key Laboratory of Innovation and Transformation of Advanced Medical Devices, Ministry of Industry and Information Technology, National Medical Innovation Platform for Industry-Education Integration in Advanced Medical Devices (Interdiscipline of Medicine and Engineering), School of Engineering Medicine, Ministry of Education, Beihang University, Beijing, 100191, People's Republic of China.
Dongmei Chen *China-Japan Friendship Hospital, Beijing, China.
Xin Zhang *Department of Urology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, People's Republic of China.
Hailang FanKey Laboratory of Biomechanics and Mechanobiology, Key Laboratory of Innovation and Transformation of Advanced Medical Devices, Ministry of Industry and Information Technology, National Medical Innovation Platform for Industry-Education Integration in Advanced Medical Devices (Interdiscipline of Medicine and Engineering), School of Engineering Medicine, Ministry of Education, Beihang University, Beijing, 100191, People's Republic of China.
Yaqian ZhaoKey Laboratory of Biomechanics and Mechanobiology, Key Laboratory of Innovation and Transformation of Advanced Medical Devices, Ministry of Industry and Information Technology, National Medical Innovation Platform for Industry-Education Integration in Advanced Medical Devices (Interdiscipline of Medicine and Engineering), School of Engineering Medicine, Ministry of Education, Beihang University, Beijing, 100191, People's Republic of China.
Yingdi HuangKey Laboratory of Biomechanics and Mechanobiology, Key Laboratory of Innovation and Transformation of Advanced Medical Devices, Ministry of Industry and Information Technology, National Medical Innovation Platform for Industry-Education Integration in Advanced Medical Devices (Interdiscipline of Medicine and Engineering), School of Engineering Medicine, Ministry of Education, Beihang University, Beijing, 100191, People's Republic of China.
Yang WuKey Laboratory of Biomechanics and Mechanobiology, Key Laboratory of Innovation and Transformation of Advanced Medical Devices, Ministry of Industry and Information Technology, National Medical Innovation Platform for Industry-Education Integration in Advanced Medical Devices (Interdiscipline of Medicine and Engineering), School of Engineering Medicine, Ministry of Education, Beihang University, Beijing, 100191, People's Republic of China.
Yanni LouChina-Japan Friendship Hospital, Beijing, China. louyanni@zryhyy.com.cn.
Dake ZhangKey Laboratory of Biomechanics and Mechanobiology, Key Laboratory of Innovation and Transformation of Advanced Medical Devices, Ministry of Industry and Information Technology, National Medical Innovation Platform for Industry-Education Integration in Advanced Medical Devices (Interdiscipline of Medicine and Engineering), School of Engineering Medicine, Ministry of Education, Beihang University, Beijing, 100191, People's Republic of China. dakezhang@buaa.edu.cn.

Funding

Beijing Nova Program Grant NO.20240484538Higher Education Discipline Innovation Project 111 Project No. B13003Shenzhen Medical Research Fund B2502015
6 · The paper itself

Abstract

backgroundDNA methylation (DNAme) is used to define cellular identity, but its ability to distinguish closely related subpopulations and its stability during in vitro culture remain to be systematically evaluated.

resultsLineage-scale whole-genome bisulfite sequencing (WGBS) analysis of 40 cell types across 13 organs showed that DNAme separates major lineages but converges among functionally related populations. Endothelial cells, fibroblasts, and smooth muscle cells from different organs clustered primarily by lineage rather than tissue of origin, whereas epithelial cells retained stronger organ-associated methylation signatures. Lineage-restricted analysis of endothelial cells identified 700 tissue-specific differentially methylated regions (DMRs) across seven tissues that were masked in global comparisons, indicating residual tissue-of-origin information persists within highly similar lineages. In kidney cells, in vitro passaging induced systematic methylation remodeling without erasing lineage identity. Primary and subcultured glomerular endothelial and tubular epithelial cells formed separate subclusters within their lineage groups. Genome-wide analysis identified extensive differential methylation (~ 1.88 M differentially methylated CpG sites [DMCs] in glomerular endothelial; ~2.64 M in tubular epithelial), with promoters overrepresented among hypermethylated features. Shared hypermethylated promoters were enriched for core homeostatic functions; hypomethylated promoters were enriched for differentiation and tissue-specific pathways. Motif analysis showed enrichment of bZIP and GATA factor motifs in endothelial hypomethylated regions and ETS-family motifs in epithelial cells. Cross-cell-type array analysis confirmed reproducible methylation drift across fetal skin fibroblasts, adult vascular endothelial cells, and neonatal foreskin fibroblasts, with 7,434 shared hypomethylated DMCs and 1,347 shared hypermethylated DMCs. Drift onset was cell type-dependent: adult skin fibroblasts and vascular smooth muscle cells diverged by passage 3, whereas neonatal and fetal cells remained stable through passage 10. Shared hypomethylated DMCs were enriched in partially methylated domains (PMDs) and late-replicating domains (LRDs). Cross-platform comparison detected only 44 common hypomethylated DMCs and 24 common hypermethylated DMCs between array and WGBS data, with negligible regional overlap.

conclusionsDNAme robustly distinguishes major lineages but converges among closely related cell types, limiting fine subpopulation resolution. Lineage-restricted analysis recovers tissue-of-origin signals otherwise obscured, whereas in vitro passaging induces cell type-dependent remodeling and reproducible methylation drift that preserves lineage identity while attenuating tissue-specific programs. No universal passage threshold ensures phenotypic stability.

Indexed as

Cell LineageDNA MethylationAnimalsCells, CulturedCpG IslandsEndothelial CellsEpigenesis, GeneticEpithelial CellsFibroblastsHumansMiceOrgan SpecificityPromoter Regions, GeneticCell identityDNA methylationEpigenetic transformationin vitro passagingSubpopulation resolution

Identifiers

PMID42902179
PMCPMC13685235

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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.