Evidence map›Paper›PMID 28877962›Full record

ArticleGenome research2017

Toward the human cellular microRNAome.

Matthew N McCall, Min-Sik Kim, Mohammed Adil, Arun H Patil, Yin Lu, Christopher J Mitchell, Pamela Leal-Rojas, Jinchong Xu, Manoj Kumar, Valina L Dawson and 7 more

Open access · bronzeAbstract read
In one paragraph

Article in Genome research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 papers.

0numbers the graph read from it
0cells of the map it votes in
106citing 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

106 citing papers in PubMed, 163 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Article
  5. Article
  6. MicroRNAs and Their Profiling via Single-Cell Sequencing Technologies.Methods in molecular biology (Clifton, N.J.) · 2026
    Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Beyond the Bubble: A Debate on microRNA Sorting Into Extracellular Vesicles.Laboratory investigation; a journal of technical methods and pathology · 2025
    Review
  19. Article
  20. ncRNA Editing: Functional Characterization and Computational Resources.Methods in molecular biology (Clifton, N.J.) · 2025
    Article

46 more citing papers are in PubMed but not listed here.

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

17 authors at 5 institutions in 4 countries.

Matthew N McCallDepartment of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, New York 14642, USA.
Min-Sik KimDepartment of Applied Chemistry, Kyung Hee University, Yongin, Gyeonggi 17104, South Korea 3.
Mohammed AdilDepartment School of Life Sciences, B.S. Abdur Rahman University, Chennai, 600048, India.
Arun H PatilMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.
Yin LuDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.
Christopher J MitchellGinkgo Bioworks, Boston, Massachusetts 02210, USA.
Pamela Leal-RojasCenter of Excellence in Translational Medicine (CEMT) & Scientific and Technological Bioresource Nucleus (BIOREN), Universidad de La Frontera, 4810296 Temuco, Chile.
Jinchong XuNeuroregeneration and Stem Cell Programs, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.
Manoj KumarNeuroregeneration and Stem Cell Programs, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.
Valina L DawsonNeuroregeneration and Stem Cell Programs, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.ORCID 0000-0002-2915-3970
Ted M DawsonNeuroregeneration and Stem Cell Programs, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.ORCID 0000-0002-6459-0893
Alexander S BarasDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.ORCID 0000-0003-2397-3342
Avi Z RosenbergDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.ORCID 0000-0003-2356-950X
Dan E ArkingMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.ORCID 0000-0001-8980-8695
Kathleen H BurnsMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.
Akhilesh PandeyMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.ORCID 0000-0001-9943-6127
Marc K HalushkaDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.ORCID 0000-0002-7112-7389
Johns Hopkins University · USB.S. Abdur Rahman Crescent Institute of Science & Technology · INGinkgo Bioworks, Inc. (United States) · USUniversidad de La Frontera · CLUniversity of Rochester Medical Center · US

Funding

Vaccine FacilityP30CA016087 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ANIRBAN MAITRA · 1985 to 2026
$83.1M
The University of Rochester's Clinical and Translational Science InstituteUL1TR002001 · NCATS · UNIVERSITY OF ROCHESTER · PI WILSON, KAREN M., ZAND, MARTIN S · 2016 to 2024
$34.6M
Proteome Characterization Center: A Genoproteomics Pipeline for Cance ResearchU24CA160036 · NCI · JOHNS HOPKINS UNIVERSITY · PI CHAN, DANIEL WANYUI, ZHANG, HUI · 2011 to 2016
$10.7M
Poly (ADP-Ribose) and AIF in Neuronal InjuryR01NS067525 · NINDS · JOHNS HOPKINS UNIVERSITY · PI VALINA L. DAWSON, Ted M. Dawson · 2010 to 2026
$6.0M
Parthanatos, AIF and PAAN-1 in Neuronal InjuryR37NS067525 · NINDS · JOHNS HOPKINS UNIVERSITY · PI DAWSON, TED M., DAWSON, VALINA L. · 2015 to 2021
$5.3M
The Comprehensive Proteome Characterization Center at Johns Hopkins: High Precision Discovery and Confirmation of Genoproteomic TargetsU24CA210985 · NCI · JOHNS HOPKINS UNIVERSITY · PI CHAN, DANIEL WANYUI, ZHANG, HUI · 2016 to 2020
$5.3M
Preprocessing and Analysis Tools for High-Throughput TechnologiesR01GM083084 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI IRIZARRY, RAFAEL ANGEL · 2007 to 2018
$4.4M
The University of Rochester Clinical and Translational Science InstituteTL1TR000096 · NCATS · UNIVERSITY OF ROCHESTER · PI BENNETT, NANCY M, KIEBURTZ, KARL D. · 2012 to 2015
$930k
Statistical Methods for Estimation of Gene Regulatory NetworksR00HG006853 · NHGRI · UNIVERSITY OF ROCHESTER · PI MCCALL, MATTHEW NICHOLSON · 2014 to 2016
$726k
NCATS NIH HHS TL1 TR000096NCATS NIH HHS UL1 TR002001NCI NIH HHS P30 CA016087NCI NIH HHS U24 CA160036NCI NIH HHS U24 CA210985NHGRI NIH HHS R00 HG006853NIGMS NIH HHS R01 GM083084NINDS NIH HHS R01 NS067525NINDS NIH HHS R37 NS067525
6 · The paper itself

Abstract

MicroRNAs are short RNAs that serve as regulators of gene expression and are essential components of normal development as well as modulators of disease. MicroRNAs generally act cell-autonomously, and thus their localization to specific cell types is needed to guide our understanding of microRNA activity. Current tissue-level data have caused considerable confusion, and comprehensive cell-level data do not yet exist. Here, we establish the landscape of human cell-specific microRNA expression. This project evaluated 8 billion small RNA-seq reads from 46 primary cell types, 42 cancer or immortalized cell lines, and 26 tissues. It identified both specific and ubiquitous patterns of expression that strongly correlate with adjacent superenhancer activity. Analysis of unaligned RNA reads uncovered 207 unknown minor strand (passenger) microRNAs of known microRNA loci and 495 novel putative microRNA loci. Although cancer cell lines generally recapitulated the expression patterns of matched primary cells, their isomiR sequence families exhibited increased disorder, suggesting DROSHA- and DICER1-dependent microRNA processing variability. Cell-specific patterns of microRNA expression were used to de-convolute variable cellular composition of colon and adipose tissue samples, highlighting one use of these cell-specific microRNA expression data. Characterization of cellular microRNA expression across a wide variety of cell types provides a new understanding of this critical regulatory RNA species.

Indexed as

AdultCell Line, TransformedCell Line, TumorHumansMaleMicroRNAsOrgan SpecificityRNA Processing, Post-TranscriptionalMicroRNAs

Identifiers

PMID28877962
PMCPMC5630040
OpenAlexW2951861059

What OpenQuestion holds

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LicenceCC BY-NC
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.