Evidence map›Paper›PMID 37722727›Full record

ArticleLife science alliance2023

High-quality single-cell transcriptomics from ovarian histological sections during folliculogenesis.

Hiroki Ikeda, Shintaro Miyao, So Nagaoka, Tomoya Takashima, Sze-Ming Law, Takuya Yamamoto, Kazuki Kurimoto

Abstract read
In one paragraph

Article in Life science alliance, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Hiroki IkedaDepartment of Embryology, School of Medicine, Nara Medical University, Kashihara, Japan.ORCID https://orcid.org/0000-0001-7435-3237
Shintaro MiyaoDepartment of Embryology, School of Medicine, Nara Medical University, Kashihara, Japan.
So NagaokaDepartment of Embryology, School of Medicine, Nara Medical University, Kashihara, Japan.
Tomoya TakashimaDepartment of Embryology, School of Medicine, Nara Medical University, Kashihara, Japan.ORCID https://orcid.org/0000-0002-3648-1569
Sze-Ming LawDepartment of Embryology, School of Medicine, Nara Medical University, Kashihara, Japan.
Takuya YamamotoCenter for iPS Cell Research and Application (CiRA), Kyoto University, Kyoto, Japan.ORCID https://orcid.org/0000-0002-0022-3947
Kazuki KurimotoDepartment of Embryology, School of Medicine, Nara Medical University, Kashihara, Japan kurimoto@naramed-u.ac.jp.ORCID https://orcid.org/0000-0003-0206-414X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-quality, straightforward single-cell RNA sequencing (RNA-seq) with spatial resolution remains challenging. Here, we developed DRaqL (direct RNA recovery and quenching for laser capture microdissection), an experimental approach for efficient cell lysis of tissue sections, directly applicable to cDNA amplification. Single-cell RNA-seq combined with DRaqL allowed transcriptomic profiling from alcohol-fixed sections with efficiency comparable with that of profiling from freshly dissociated cells, together with effective exon-exon junction profiling. The combination of DRaqL with protease treatment enabled robust and efficient single-cell transcriptome analysis from formalin-fixed tissue sections. Applying this method to mouse ovarian sections, we were able to predict the transcriptome of oocytes by their size and identified an anomaly in the size-transcriptome relationship relevant to growth retardation of oocytes, in addition to detecting oocyte-specific splice isoforms. Furthermore, we identified differentially expressed genes in granulosa cells in association with their proximity to the oocytes, suggesting distinct epigenetic regulations and cell-cycle activities governing the germ-soma relationship. Thus, DRaqL is a versatile, efficient approach for high-quality single-cell RNA-seq from tissue sections, thereby revealing histological heterogeneity in folliculogenic transcriptome.

Indexed as

OvaryTranscriptomeAnimalsCell CycleFemaleGene Expression ProfilingMiceOocytes

Identifiers

PMID37722727
PMCPMC10507249

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.