Evidence map›Paper›PMID 41734818›Full record

ArticleNucleic acids research2026

Directing stem cell differentiation by chromatin state approximation.

Luis F Montano-Gutierrez, Sophie Müller, Ana P Kutschat, Igor Adameyko, Davide Seruggia, Florian Halbritter

Abstract read
In one paragraph

Article in Nucleic acids research, 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

6 authors.

Luis F Montano-GutierrezSt. Anna Children's Cancer Research Institute (CCRI), 1090 Vienna, Austria.ORCID 0000-0003-2383-1483
Sophie MüllerSt. Anna Children's Cancer Research Institute (CCRI), 1090 Vienna, Austria.ORCID 0000-0003-3527-6739
Ana P KutschatSt. Anna Children's Cancer Research Institute (CCRI), 1090 Vienna, Austria.ORCID 0000-0002-6360-873X
Igor AdameykoDepartment of Physiology and Pharmacology, Karolinska Institute, 17177 Solna, Sweden.ORCID 0000-0001-5471-0356
Davide SeruggiaSt. Anna Children's Cancer Research Institute (CCRI), 1090 Vienna, Austria.ORCID 0000-0001-5014-0499
Florian HalbritterSt. Anna Children's Cancer Research Institute (CCRI), 1090 Vienna, Austria.ORCID 0000-0003-2452-4784

Funding

FWF 10.55776/TAI732
6 · The paper itself

Abstract

A prime goal of regenerative medicine is to replace dysfunctional cells in the body. To design protocols for producing target cells in the laboratory, one may need to consider exponentially large combinations of culture components. Here, we investigated the potential of iteratively approximating the target phenotype by quantifying the distance between chromatin profiles (ATAC-seq) of differentiating cells in vitro and their in vivo counterparts. We tested this approach on the well-studied generation of erythroblasts from haematopoietic stem cells, evaluating a fixed number of components over two sequential differentiation rounds (8 × 8 protocols). We found that the most erythroblast-like cells upon the first round yielded the most erythroblast-like cells at the second round, suggesting that greedy selection by chromatin approximation can be a viable optimisation strategy. Furthermore, by analysing regulatory sequences in incompletely reprogrammed chromatin regions, we uncovered transcriptional regulators linked to roadblocks in differentiation and made a data-driven selection of ligands that further improved erythropoiesis. In future, our methodology can help craft notoriously difficult cells in vitro, such as B cells.

Indexed as

Cell DifferentiationChromatinHematopoietic Stem CellsAnimalsErythroblastsErythropoiesisHumansMiceChromatin

Identifiers

PMID41734818
PMCPMC12956330

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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.