Evidence map›Paper›PMID 41560697›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Single-Cell Mitochondrial Lineage Tracing Decodes Fate Decision and Spatial Clonal Architecture in Human Hematopoietic Organoids.

Yan Xue, Junhao Su, Yiming Chao, Lu Liu, Xinyi Lin, Yang Xiang, Mun Kay Ho, Zezhuo Su, Junyi Chen, Zhuojuan Luo and 8 more

Erratum issuedAbstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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

5 · Who and what money

Authors and funding

18 authors.

Yan XueSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.ORCID https://orcid.org/0000-0001-7691-718X
Junhao SuSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Yiming ChaoSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Lu LiuSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Xinyi LinSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Yang XiangSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Mun Kay HoSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Zezhuo SuDepartment of Orthopaedics and Traumatology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Junyi ChenLaboratory of Data Discovery For Health Limited (D24H), Hong Kong Science Park, Hong Kong, Hong Kong.
Zhuojuan LuoJiangsu Provincial Key Laboratory of Critical Care Medicine, Southeast University, Nanjing, China.
Chengqi LinJiangsu Province Hi-Tech Key Laboratory For Biomedical Research, Southeast University, Nanjing, China.
Ruibang LuoDepartment of Computer Science, School of Computing and Data Science, The University of Hong Kong, Hong Kong SAR, China.
Theo AurichSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Jianfeng WuDepartment of Diagnostic Radiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Kelvin Sin Chi CheungDepartment of Orthopaedics and Traumatology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Yuanhua HuangSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Joshua W K HoSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.ORCID https://orcid.org/0000-0003-2331-7011
Ryohichi SugimuraSchool of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.ORCID https://orcid.org/0000-0001-5701-3628

Funding

Guangdong Natural Science Fund 2023A1515011265Hong Kong Research Grant CouncilInnoHK initiative of the Innovation and Technology Commission of the Hong Kong Special Administrative Region GovernmentNSFC/RGC Joint Research Scheme N_HKU731/21Shenzhen-Hong Kong-Macau Technology Research Programme SGDX2021082310356025
6 · The paper itself

Abstract

Lineage tracing at single-cell resolution is vital for mapping cell fate decisions, yet synthetic barcoding faces limitations in precision, diversity, and toxicity-especially in human pluripotent stem cells (hPSCs). Here, we repurpose naturally occurring somatic mutations in mitochondrial transcripts from single-cell RNA sequencing as endogenous genetic barcodes. By enriching mitochondrial reads and applying a robust computational pipeline, we identified clonally informative variants to trace hematopoietic lineage emergence from hPSCs during early embryogenesis. Integrating mitochondrial barcoding with synthetic lineage tracing, we modeled embryonic tissue development and reconstructed the transcriptional logic and regulatory networks driving fate specification using a dynamical systems model. Extending this approach to spatial transcriptomics, we mapped the clonal architecture of human embryonic organoids, revealing spatial zonation orchestrated by NOTCH-mediated crosstalk between stromal cells and hematopoietic progenitors. This multimodal strategy links clonal dynamics with niche-driven fate decisions, offering a scalable, non-invasive method to dissect tissue organization in development and disease. Together, our work establishes a scalable, non-invasive multimodal framework that leverages endogenous mitochondrial DNA variants to reconstruct high-resolution spatiotemporal clonal dynamics and decode niche-driven fate decisions in a human stem cell-derived model. This approach provides a powerful strategy for dissecting tissue self-organization in development and disease.

Indexed as

HematopoiesisMitochondriaOrganoidsCell LineageChondrosarcomaClone CellsDNA, MitochondrialGene Regulatory NetworksHumansReceptors, NotchSignal TransductionSingle-Cell Gene Expression AnalysisDNA, MitochondrialReceptors, Notchcell fate decisionshematopoietic organoidsmitochondrial DNA variantsingle‐cell lineage tracingspatial transcriptomics

Identifiers

PMID41560697
PMCPMC13042525

What OpenQuestion holds

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Registered trials

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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.