Evidence map›Paper›PMID 31984226›Full record

ArticleBiology methods & protocols2020

Single-cell transcriptomics from human pancreatic islets: sample preparation matters.

Lori L Bonnycastle, Derek E Gildea, Tingfen Yan, Narisu Narisu, Amy J Swift, Tyra G Wolfsberg, Michael R Erdos, Francis S Collins

Abstract read
In one paragraph

Article in Biology methods & protocols, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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  17. Human Islets Contain a Beta Cell Type That Expresses Proinsulin But Not the Enzyme That Converts the Precursor to Insulin.The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society · 2020
    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

8 authors.

Lori L BonnycastleMedical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0003-0663-3944
Derek E GildeaBioinformatics and Scientific Programming Core, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
Tingfen YanMedical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
Narisu NarisuMedical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
Amy J SwiftMedical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
Tyra G WolfsbergBioinformatics and Scientific Programming Core, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
Michael R ErdosMedical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
Francis S CollinsMedical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0002-1023-7410

Funding

Genetic analysis of type II diabetes in Finnish populationZIAHG000024 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI ERDOS, MICHAEL · 2009 to 2025
$38.2M
Intramural NIH HHS ZIA HG000024
6 · The paper itself

Abstract

Single-cell RNA sequencing (scRNA-seq) of human primary tissues is a rapidly emerging tool for investigating human health and disease at the molecular level. However, optimal processing of solid tissues presents a number of technical and logistical challenges, especially for tissues that are only available at autopsy, which includes pancreatic islets, a tissue that is highly relevant to diabetes. To assess the possible effects of different sample preparation protocols on fresh islet samples, we performed a detailed comparison of scRNA-seq data generated with islets isolated from a human donor but processed according to four treatment strategies, including fixation and cryopreservation. We found significant and reproducible differences in the proportion of cell types identified, and more minor effects on cell-specific patterns of gene expression. Fresh islets from a second donor confirmed gene expression signatures of alpha and beta subclusters. These findings may well apply to other tissues, emphasizing the need for careful consideration when choosing processing methods, comparing results between different studies, and/or interpreting data in the context of multiple cell types from preserved tissue.

Indexed as

isletsscRNA-seqtissue processingtranscriptome

Identifiers

PMID31984226
PMCPMC6964677

What OpenQuestion holds

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Registered trials

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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.