Evidence map›Paper›PMID 29202695›Full record

ArticleBMC genomics2017

Single-cell RNA-Seq analysis reveals dynamic trajectories during mouse liver development.

Xianbin Su, Yi Shi, Xin Zou, Zhao-Ning Lu, Gangcai Xie, Jean Y H Yang, Chong-Chao Wu, Xiao-Fang Cui, Kun-Yan He, Qing Luo and 4 more

Abstract read
In one paragraph

Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.

0numbers the graph read from it
0cells of the map it votes in
56citing 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

56 citing papers in PubMed.

  1. Article
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  6. Primitive Hepatoblasts Driving Early Liver Development.bioRxiv : the preprint server for biology · 2025
    Article
  7. Article
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  17. Fetal liver development and implications for liver disease pathogenesis.Nature reviews. Gastroenterology & hepatology · 2023
    Review
  18. Article
  19. Monitoring Cultured Rat Hepatocytes Using RNA-Seq In Vitro.International journal of molecular sciences · 2023
    Article
  20. Article
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

14 authors.

Xianbin SuKey Laboratory of Systems Biomedicine (Ministry of Education) and Collaborative Innovation Center of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
Yi ShiKey Laboratory of Systems Biomedicine (Ministry of Education) and Collaborative Innovation Center of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
Xin ZouKey Laboratory of Systems Biomedicine (Ministry of Education) and Collaborative Innovation Center of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
Zhao-Ning LuKey Laboratory of Systems Biomedicine (Ministry of Education) and Collaborative Innovation Center of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
Gangcai XieKey Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, 320 Yueyang Road, Shanghai, China.
Jean Y H YangSchool of Mathematics and Statistics, The University of Sydney, Sydney, Australia.
Chong-Chao WuKey Laboratory of Systems Biomedicine (Ministry of Education) and Collaborative Innovation Center of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
Xiao-Fang CuiKey Laboratory of Systems Biomedicine (Ministry of Education) and Collaborative Innovation Center of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
Kun-Yan HeKey Laboratory of Systems Biomedicine (Ministry of Education) and Collaborative Innovation Center of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
Qing LuoKey Laboratory of Systems Biomedicine (Ministry of Education) and Collaborative Innovation Center of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
Yu-Lan QuKey Laboratory of Systems Biomedicine (Ministry of Education) and Collaborative Innovation Center of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
Na WangKey Laboratory of Systems Biomedicine (Ministry of Education) and Collaborative Innovation Center of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
Lan WangKey Laboratory of Systems Biomedicine (Ministry of Education) and Collaborative Innovation Center of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
Ze-Guang HanKey Laboratory of Systems Biomedicine (Ministry of Education) and Collaborative Innovation Center of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China. hanzg@sjtu.edu.cn.ORCID http://orcid.org/0000-0002-1018-1752

Funding

Medical and Engineering Crossover Fund of SJTU YG2014QN14Medical and Engineering Crossover Fund of SJTU YG2016MS05Medical and Engineering Crossover Fund of SJTU YG2016QN71National Natural Science Foundation of China 81402329National Natural Science Foundation of China 81472621National Natural Science Foundation of China 81672772National Program on Key Research Project of China 2016YFC0902701Shanghai Natural Science Foundation 16ZR1417900Shanghai Pujiang Program 16PJ1405200Shanghai Sailing Program 15YF1405800Start Funding for Young Teachers of SJTU 14X100040063
6 · The paper itself

Abstract

backgroundThe differentiation and maturation trajectories of fetal liver stem/progenitor cells (LSPCs) are not fully understood at single-cell resolution, and a priori knowledge of limited biomarkers could restrict trajectory tracking.

resultsWe employed marker-free single-cell RNA-Seq to characterize comprehensive transcriptional profiles of 507 cells randomly selected from seven stages between embryonic day 11.5 and postnatal day 2.5 during mouse liver development, and also 52 Epcam-positive cholangiocytes from postnatal day 3.25 mouse livers. LSPCs in developing mouse livers were identified via marker-free transcriptomic profiling. Single-cell resolution dynamic developmental trajectories of LSPCs exhibited contiguous but discrete genetic control through transcription factors and signaling pathways. The gene expression profiles of cholangiocytes were more close to that of embryonic day 11.5 rather than other later staged LSPCs, cuing the fate decision stage of LSPCs. Our marker-free approach also allows systematic assessment and prediction of isolation biomarkers for LSPCs.

conclusionsOur data provide not only a valuable resource but also novel insights into the fate decision and transcriptional control of self-renewal, differentiation and maturation of LSPCs.

Indexed as

Gene Expression Regulation, DevelopmentalAnimalsBiomarkersCells, CulturedEmbryonic Stem CellsGene Expression ProfilingLiverMiceMice, Inbred C57BLSequence Analysis, RNASingle-Cell AnalysisBiomarkersCholangiocyteDevelopmental trajectoryFate decisionLiver stem/progenitor cellsSingle-cell RNA-Seq

Identifiers

PMID29202695
PMCPMC5715535

What OpenQuestion holds

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LicenceCC BY
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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.