Evidence map›Paper›PMID 39955438›Full record

ArticleScientific reports2025

A versatile and efficient method to isolate nuclei from low-input cryopreserved tissues for single-nuclei transcriptomics.

Cristopher Segovia, Vincent Desrosiers, Fatemeh Khadangi, Karine Robitaille, Victoria Saavedra Armero, Myreille D'Astous, Gabriel Khelifi, Alain Bergeron, Samer Hussein, Maxime Richer and 4 more

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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. Review
  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

14 authors.

Cristopher SegoviaCentre de recherche du CHU de Québec - Université Laval, Axe Oncologie, 1401, 18e rue, Québec, Québec, G1J 1Z4, Canada.
Vincent DesrosiersCentre de recherche du CHU de Québec - Université Laval, Axe Maladies Infectieuses Et Immunitaires, Québec, Québec, G1V 4G2, Canada.
Fatemeh KhadangiCentre de recherche du CHU de Québec - Université Laval, Axe Oncologie, 1401, 18e rue, Québec, Québec, G1J 1Z4, Canada.
Karine RobitailleCentre de recherche du CHU de Québec - Université Laval, Axe Oncologie, 1401, 18e rue, Québec, Québec, G1J 1Z4, Canada.
Victoria Saavedra ArmeroInstitut universitaire de cardiologie et de pneumologie de Québec - Université Laval, Québec, Québec, G1V 4G5, Canada.
Myreille D'AstousCHU de Québec - Université Laval, Québec, Québec, G1R 2J6, Canada.
Gabriel KhelifiCentre de recherche du CHU de Québec - Université Laval, Axe Oncologie, 1401, 18e rue, Québec, Québec, G1J 1Z4, Canada.
Alain BergeronCentre de recherche du CHU de Québec - Université Laval, Axe Oncologie, 1401, 18e rue, Québec, Québec, G1J 1Z4, Canada.
Samer HusseinCentre de recherche du CHU de Québec - Université Laval, Axe Oncologie, 1401, 18e rue, Québec, Québec, G1J 1Z4, Canada.
Maxime RicherCHU de Québec - Université Laval, Québec, Québec, G1R 2J6, Canada.
Yohan BosséInstitut universitaire de cardiologie et de pneumologie de Québec - Université Laval, Québec, Québec, G1V 4G5, Canada.
Yves FradetCentre de recherche du CHU de Québec - Université Laval, Axe Oncologie, 1401, 18e rue, Québec, Québec, G1J 1Z4, Canada.
Vincent FradetCentre de recherche du CHU de Québec - Université Laval, Axe Oncologie, 1401, 18e rue, Québec, Québec, G1J 1Z4, Canada.
Steve BilodeauCentre de recherche du CHU de Québec - Université Laval, Axe Oncologie, 1401, 18e rue, Québec, Québec, G1J 1Z4, Canada. Steve.Bilodeau@crchudequebec.ulaval.ca.

Funding

CIHR 451568Natural Sciences and Engineering Research Council of Canada 2019-06490
6 · The paper itself

Abstract

Clinical samples are vital for understanding diseases, but their scarcity requires refined research methods. Emerging single-cell technologies offer detailed views of tissue heterogeneity but need sufficient fully characterized tissues. We developed an optimized single-nuclei RNA sequencing (snRNA-seq) protocol to extract nuclei from just 15 mg of cryopreserved human tissue. Applied to four cancer tissues (brain, bladder, lung, prostate), it profiled 1550-7468 nuclei per tissue, revealing heterogeneity comparable to public single-cell atlases. This method enhances the use and sharing of rare, cryopreserved biospecimens, supporting research where sample quantity is limited and full tissue characterization is needed.

Indexed as

Cell NucleusCryopreservationGene Expression ProfilingSingle-Cell AnalysisTranscriptomeHumansMaleNeoplasmsSequence Analysis, RNACancerNuclei isolationNuclei sortingTissue heterogeneityTissue homogenizationTranscriptomics

Identifiers

PMID39955438
PMCPMC11829965

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.