Evidence map›Paper›PMID 32940008›Full record

ReviewWiley interdisciplinary reviews. Developmental biology2021

Single-cell RNA sequencing in Drosophila: Technologies and applications.

Hongjie Li

Open access · greenAbstract readReview
In one paragraph

Review in Wiley interdisciplinary reviews. Developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
3.9field-weighted citation impact, top 5% 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

33 citing papers in PubMed, 63 citations in OpenAlex.

  1. Article
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  4. The Power of Drosophila in Modeling Cancer Cachexia.Advances in experimental medicine and biology · 2025
    Review
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  11. Toward building a library of cell type-specific drivers across developmental stages.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  12. Review
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  15. Article
  16. Frontiers in molecular neuroscience · 2023
    Review
  17. Review
  18. Article
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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

1 author at 1 institution in 1 country.

Hongjie LiDepartment of Biology, Stanford University, Stanford, California, USA.ORCID 0000-0002-7332-7122
Stanford University · US

Funding

Characterizing age-related decline of neural circuits by single-cell profilingR00AG062746 · NIA · BAYLOR COLLEGE OF MEDICINE · PI LI, HONGJIE · 2021 to 2023
$996k
Characterizing the assembly and age-related decline of neural circuits in Drosophila by single-cell profilingK99AG062746 · NIA · STANFORD UNIVERSITY · PI LI, HONGJIE · 2019 to 2020
$254k
NIA NIH HHS K99 AG062746NIA NIH HHS R00 AG062746
6 · The paper itself

Abstract

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cell states and functions at the single-cell level. It has greatly revolutionized transcriptomic studies in many life science research fields, such as neurobiology, immunology, and developmental biology. With the fast development of both experimental platforms and bioinformatics approaches over the past decade, scRNA-seq is becoming economically feasible and experimentally practical for many biomedical laboratories. Drosophila has served as an excellent model organism for dissecting cellular and molecular mechanisms that underlie tissue development, adult cell function, disease, and aging. The recent application of scRNA-seq methods to Drosophila tissues has led to a number of exciting discoveries. In this review, I will provide a summary of recent scRNA-seq studies in Drosophila, focusing on technical approaches and biological applications. I will also discuss current challenges and future opportunities of making new discoveries using scRNA-seq in Drosophila. This article is categorized under:   Technologies > Analysis of the Transcriptome.

Indexed as

Gene Expression ProfilingSingle-Cell AnalysisAnimalsDrosophilaSequence Analysis, RNASoftwaredrosophilasingle-cell RNA sequencing

Identifiers

PMID32940008
PMCPMC7960577
OpenAlexW3087003196

What OpenQuestion holds

Textmetadata
LicenceTDM
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.