Evidence map›Paper›PMID 32743779›Full record

ArticleCell regeneration (London, England)2020

Mapping a mammalian adult adrenal gland hierarchy across species by microwell-seq.

Shujing Lai, Lifeng Ma, Weigao E, Fang Ye, Haide Chen, Xiaoping Han, Guoji Guo

Open access · diamondAbstract read
In one paragraph

Article in Cell regeneration (London, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.7field-weighted citation impact, top 32% of its field
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

11 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Models of Congenital Adrenal Hyperplasia for Gene Therapies Testing.International journal of molecular sciences · 2023
    Review
  7. Development and function of the fetal adrenal.Reviews in endocrine & metabolic disorders · 2023
    Review
  8. Article
  9. Review
  10. Characterization of Aldosterone-producing Cell Cluster (APCC) at Single-cell Resolution.The Journal of clinical endocrinology and metabolism · 2022
    Article
  11. 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

7 authors at 2 institutions in 2 countries.

Shujing LaiCenter for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Lifeng MaCenter for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Weigao ECenter for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Fang YeCenter for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Haide ChenCenter for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China. hyde@zju.edu.cn.
Xiaoping HanCenter for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China. xhan@zju.edu.cn.
Guoji GuoCenter for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China. ggj@zju.edu.cn.ORCID http://orcid.org/0000-0002-1716-4621
Zhejiang University · CNInstitute for Stem Cell Biology and Regenerative Medicine · IN

Funding

National Key Program on Stem Cell and Translational Research 2017YFA0103401National Natural Science Foundation of China 31701290National Natural Science Foundation of China 31722027National Natural Science Foundation of China 81770188
6 · The paper itself

Abstract

Recently, single-cell RNA-seq technologies have been rapidly updated, leading to a revolution in biology. We previously developed Microwell-seq, a cost-effective and high-throughput single cell RNA sequencing(scRNA-seq) method with a very simple device. Most cDNA libraries are sequenced using an expensive Illumina platform. Here, we present the first report showing combined Microwell-seq and BGI MGISEQ2000, a less expensive sequencing platform, to profile the whole transcriptome of 11,883 individual mouse adult adrenal gland cells and identify 18 transcriptionally distinct clusters. Moreover, we performed a single-cell comparative analysis of human and mouse adult adrenal glands to reveal the conserved genetic networks in these mammalian systems. These results provide new insights into the sophisticated adrenal gland hierarchy and provide a benchmark, low-cost strategy for high-throughput single-cell RNA study.

Identifiers

PMID32743779
PMCPMC7396412
OpenAlexW3048298161

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.