Evidence map›Paper›PMID 35360857›Full record

ArticleFrontiers in genetics2022

Single Cell Transcriptome Sequencing of Zebrafish Testis Revealed Novel Spermatogenesis Marker Genes and Stronger Leydig-Germ Cell Paracrine Interactions.

Peipei Qian, Jiahui Kang, Dong Liu, Gangcai Xie

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
8.1field-weighted citation impact, top 2% 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

27 citing papers in PubMed, 45 citations in OpenAlex.

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  18. Zebrafish as a model system for studying reproductive diseases.Frontiers in cell and developmental biology · 2024
    Review
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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

4 authors at 1 institution in 1 country.

Peipei QianInstitute of Reproductive Medicine, Medical School, Nantong University, Nantong, China.
Jiahui KangInstitute of Reproductive Medicine, Medical School, Nantong University, Nantong, China.
Dong LiuSchool of Life Sciences, Key Laboratory of Neuroregeneration of Jiangsu and Ministry of Education, Co-innovation Center of Neuroregeneration, Nantong University, Nantong, China.
Gangcai XieInstitute of Reproductive Medicine, Medical School, Nantong University, Nantong, China.
Nantong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spermatogenesis in testis is an important process for sexual reproduction, and worldwide about 10-15 percent of couples suffer from infertility. It is of importance to study spermatogenesis at single cell level in both of human and model organisms. Currently, single-cell RNA sequencing technologies (scRNA-seq) had been extensively applied to the study of cellular components and its gene regulations in the testes of different species, including human, monkey, mouse, and fly, but not in zebrafish. Zebrafish was a widely used model organism in biology and had been extensively used for the study of spermatogenesis in the previous studies. Therefore, it is also important to profile the transcriptome of zebrafish testis at single cell level. In this study, the transcriptomes of 14, 315 single cells from adult male zebrafish testes were profiled by scRNA-seq, and 10 cell populations were revealed, including Leydig cell, Sertoli cell, spermatogonia cell (SPG), spermatocyte, and spermatids. Notably, thousands of cell-type specific novel marker genes were identified, including

Indexed as

Leydig cellparacrinesingle cellspermatogenesistestistranscriptomezebrafish

Identifiers

PMID35360857
PMCPMC8961980
OpenAlexW4221110227

What OpenQuestion holds

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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.