Evidence map›Paper›PMID 30789893›Full record

ArticlePLoS biology2019

Single-cell transcriptomics reveals gene expression dynamics of human fetal kidney development.

Mazène Hochane, Patrick R van den Berg, Xueying Fan, Noémie Bérenger-Currias, Esmée Adegeest, Monika Bialecka, Maaike Nieveen, Maarten Menschaart, Susana M Chuva de Sousa Lopes, Stefan Semrau

Abstract read
In one paragraph

Article in PLoS biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 94 papers.

0numbers the graph read from it
0cells of the map it votes in
94citing 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

94 citing papers in PubMed.

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  18. Spatiotemporal landscape of kidney in a mouse model of hyperuricemia at single-cell level.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025
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34 more citing papers are in PubMed but not listed here.

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

10 authors.

Mazène HochaneLeiden Institute of Physics, Leiden University, Leiden, The Netherlands.
Patrick R van den BergLeiden Institute of Physics, Leiden University, Leiden, The Netherlands.ORCID 0000-0001-6204-6037
Xueying FanDepartment of Anatomy and Embryology, Leiden University Medical Center, Leiden, The Netherlands.
Noémie Bérenger-CurriasLeiden Institute of Physics, Leiden University, Leiden, The Netherlands.ORCID 0000-0001-9716-5618
Esmée AdegeestLeiden Institute of Physics, Leiden University, Leiden, The Netherlands.ORCID 0000-0002-4829-9887
Monika BialeckaDepartment of Anatomy and Embryology, Leiden University Medical Center, Leiden, The Netherlands.
Maaike NieveenDepartment of Anatomy and Embryology, Leiden University Medical Center, Leiden, The Netherlands.
Maarten MenschaartLeiden Institute of Physics, Leiden University, Leiden, The Netherlands.ORCID 0000-0002-6512-4827
Susana M Chuva de Sousa LopesDepartment of Anatomy and Embryology, Leiden University Medical Center, Leiden, The Netherlands.ORCID 0000-0003-3866-2803
Stefan SemrauLeiden Institute of Physics, Leiden University, Leiden, The Netherlands.ORCID 0000-0002-4245-2246

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current understanding of mammalian kidney development is largely based on mouse models. Recent landmark studies revealed pervasive differences in renal embryogenesis between mouse and human. The scarcity of detailed gene expression data in humans therefore hampers a thorough understanding of human kidney development and the possible developmental origin of kidney diseases. In this paper, we present a single-cell transcriptomics study of the human fetal kidney. We identified 22 cell types and a host of marker genes. Comparison of samples from different developmental ages revealed continuous gene expression changes in podocytes. To demonstrate the usefulness of our data set, we explored the heterogeneity of the nephrogenic niche, localized podocyte precursors, and confirmed disease-associated marker genes. With close to 18,000 renal cells from five different developmental ages, this study provides a rich resource for the elucidation of human kidney development, easily accessible through an interactive web application.

Indexed as

Gene Expression Regulation, DevelopmentalTranscriptomeCell DifferentiationCell LineageDatasets as TopicFemaleFetal DevelopmentFetusGene Expression ProfilingGene OntologyGestational AgeHumansKidneyMaleMolecular Sequence AnnotationOrganogenesis

Identifiers

PMID30789893
PMCPMC6400406

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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.