Omics · study · 2026
Widespread transcriptional memory shapes heritable states and functional heterogeneity in cancer and stem cells [RNA-Seq]
Listed in NCBI GEO
Recent studies show that non-genetic heterogeneity, particularly through heritable cell states, shapes cancer evolution and developmental trajectories.
Description
However, single-cell snapshots lack temporal information to identify these states. We employ lineage-resolved single-cell transcriptomics to map heritable cell states that persist across divisions, distinguishing them from transient fluctuations.
We uncover that heritable states are underpinned by widespread transcriptional memory, whereby heritable gene expression defines two classes of states: clustered states, characterized by clustered gene expression, and latent states, marked by non-clustered gene expression. This memory shows conservation across cell types and conditions and appears to be maintained by robust epigenetic mechanisms resistant to environmental perturbations.
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Functionally, memory genes predict critical behaviors including metastatic potential and lineage commitment, with latent-state genes often outperforming clustered-state genes. Our findings establish transcriptional memory as a potential basis of heritable cellular heterogeneity, providing a framework for understanding functional cellular variations across biological systems. A record of this paper’s transparent peer review process is included in the supplemental information.
Links
Get the data
- GEO FTP directory ftp.ncbi.nlm.nih.gov/geo/series/GSE329nnn/GSE329159 ↗
download · from NCBI GEO
Where it is published
- GEO accession page ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE329159 ↗
landing page · from NCBI GEO
Documentation and papers
- PRJNA1458062 ncbi.nlm.nih.gov/bioproject/PRJNA1458062 ↗
project · from NCBI GEO
Topics
- Stated by source
- Expression profiling by high throughput sequencing · Homo sapiens
- From keywords
- Life Sciences
- Inferred from text
- Cancer 75% · Cell and nuclear division 76% · RNA sequencing 65%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NCBI GEO | GSE329159 | 13 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[disease].local:disease:cancer | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].anzsrc:field:310502 | enrichment · NCBI GEO | taxonomy-embedding@1.1.0 | title+keywords+description (76%) |
| concepts[field].local:field:life-sciences | mapping · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[method].geo_series_type:expression-profiling-by-high-throughput-sequencing | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /gdstype |
| concepts[modality].local:modality:rna-seq | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[organism].NCBITaxon:9606 | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /taxon |
| description | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /summary |
| publication_date | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| title | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /title |