Cited by 405MicroRNA in disease regulationPlant Molecular Biology ResearchChromosomal and Genetic Variations

The DOI matches its Crossref record; 77 of the 77 references it cites were found in a registry or an index; none of the 34 sources its claims cite is checked for support yet.

Analysis of 13 cell types reveals evidence for the expression of numerous novel primate- and tissue-specific microRNAs

Open access

Abstract

Significance: MicroRNAs (miRNAs) are small ∼22-nt RNAs that are important regulators of posttranscriptional gene expression. Since their initial discovery, they have been shown to be involved in many cellular processes, and their misexpression is associated with disease etiology. Currently, nearly 2,800 human miRNAs are annotated in public repositories. A key question in miRNA research is how many miRNAs are harbored by the human genome. To answer this question, we examined 1,323 short RNA sequence samples and identified 3,707 novel miRNAs, many of which are human-specific and tissue-specific. Our findings suggest that the human genome expresses a greater number of miRNAs than has previously been appreciated and that many more miRNA molecules may play key roles in disease etiology.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

Analyzing 1,323 short RNA-seq samples from 13 human cell types, this study identifies 3,707 novel mature miRNAs from 3,494 precursors at FDR ≤ 0.05, many of which are tissue-specific and primate-specific. The authors argue that public repositories substantially underrepresent the human miRNA repertoire.

Key findings

  • From >23 billion sequenced reads, ~8.2 billion mapped unambiguously; 3,707 novel mature miRNAs were identified, and 91.5% (3,392 of 3,707) were discovered independently in at least 10 samples.
  • Ago CLIP-seq supported 1,657 of 3,707 novel miRNAs (44.7%), compared with 1,517 of 2,772 miRBase release 20 miRNAs (54.7%).
  • Novel miRNAs showed strong tissue dependence: low intertissue Jaccard similarity, PCA clustering by tissue, and stem-loop RT-PCR confirmation of 20 novel miRNAs in 12 cell lines representing 5 tissues.
  • Conservation analysis found 56.7% of novel miRNAs human-specific and 94.4% primate lineage-specific; 2,140 (58.1%) precursor/mature combinations were human-specific, 476 (12.8%) shared across Hominidae, 109 (2.9%) present in mouse, and none in Drosophila or worm.

Methods

  • Analyzed 1,323 short RNA-seq samples (100 in-house, 1,223 public) from 13 human cell types; reads were mapped to hg19 with SHRiMP2, processed per sample with miRDeep2, and filtered to mature miRNAs with FDR ≤ 0.05 after removing known miRNAs, mirtrons, tRNAs, snRNAs, and rRNAs.
  • Used 43 Ago CLIP-seq samples (10 in-house, 33 public) to assess Argonaute loading, requiring complete coincidence with a CLIP-seq site, observation in at least one sample, and support by five or more reads.
  • Validated selected novel miRNAs by stem-loop RT-PCR in 12 cell lines, assessed DICER dependence in MCF7 knockdown data, performed GLSEARCH conservation analysis, seed-based clustering, and RNA22 target prediction.

Limitations

  • The paper states that the 43 Ago CLIP-seq samples represent only 3 of the 13 tissue types used for discovery, so not all novel or miRBase miRNAs are expected to be observed; lower Ago support for novel miRNAs is expected given their higher tissue specificity.
  • The paper states that the study focused only on canonical Dicer-dependent miRNAs, while bona fide miRNAs can arise through other mechanisms, suggesting an even larger miRNA-ome.
  • The paper states that RNA22 target predictions require additional experimental validation; only 20 novel miRNAs were experimentally tested by stem-loop RT-PCR.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1073/pnas.1420955112

Cites

77 of 77 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

31 Own result · 24 Sources not found · 12 Own interpretation · 6 Own method

Show all 39 claims

  • It may state two separate claims as one. 26
  • Probably not a substantial claim. 14
34 of 34
  • The authors state this as an assumption.

    The novel miRNAs will affect many pathways and exert their effects on a wide range of targets.

    “It is reasonable to assume that these novel miRNAs will affect many pathways and exert their effects on a wide range of targets.”
  • The authors state this as an assumption.

    miRNAs exhibit tissue-specific behavior similar to protein-coding genes.

    “Just as protein-coding genes display tissue-specific patterns of expression, it is reasonable to assume that miRNAs would exhibit a similar behavior.”
  • The paper relies on this without support.

    Many more miRNAs are present and can be identified through analysis of additional samples representing more diverse tissue types.

    “We reasoned that many more miRNAs are present and can be identified through the analysis of additional samples representing more diverse tissue types.”
  • The paper relies on this without support.

    There is no reason to think that there will not be lineage-specific adaptive evolution in regulatory sequences and regulatory molecules.

    “Indeed, there is no reason to think that there will not be lineage-specific adaptive evolution in regulatory sequences and regulatory molecules.”
  • The paper relies on this without support.

    MiRNAs loaded onto the Argonaute complex are capable of interacting with target RNAs.

    “MiRNAs exert their function through their association with the Argonaute complex, and, thus, those miRNAs loaded onto Ago are expected to be capable of interacting with target RNAs.”
  • The paper relies on this without support.

    The remainder of the miRNA sequence can assist in defining the eventual targetome.

    “Nonetheless, the remainder of the miRNA sequence can also assist in defining the eventual targetome.”
6 of 6

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

4 of 4

Citations

Cites

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Cited by

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Metadata

Authors
Londin, E., Loher, P., Telonis, A. G., Quann, K., Clark, P., Jing, Y., Hatzimichael, E., Kirino, Y., Honda, S., Lally, M., Ramratnam, B., Comstock, C. E. S., Knudsen, K. E., Gomella, L., Spaeth, G. L., Hark, L., Katz, L. J., Witkiewicz, A., Rostami, A., Jimenez, S. A., Hollingsworth, M. A., Yeh, J. J., Shaw, C. A., McKenzie, S. E., Bray, P., Nelson, P. T., Zupo, S., Van Roosbroeck, K., Keating, M. J., Calin, G. A., Yeo, C., Jimbo, M., Cozzitorto, J., Brody, J. R., Delgrosso, K., Mattick, J. S., Fortina, P., & Rigoutsos, I.
Affiliations
  • Thomas Jefferson University (US)
  • Computational Medicine Center, Sidney Kimmel Medical School at Thomas Jefferson University, Philadelphia, PA 19107;
  • Brown University (US)
  • American Association For Cancer Research (US)
  • Wills Eye Hospital (US)
  • The University of Texas Southwestern Medical Center (US)
  • Jefferson Institute of Molecular Medicine and The Scleroderma Center, Sidney Kimmel Medical School at Thomas Jefferson University, Philadelphia, PA 19107;
  • University of Nebraska Medical Center (US)
  • University of North Carolina at Chapel Hill (US)
  • Baylor College of Medicine (US)
  • University of Kentucky (US)
  • Ospedale Policlinico San Martino (IT)
  • Department of Experimental Therapeutics, University of Texas MD Anderson Cancer Center, Houston, TX 77030;
  • The University of Texas MD Anderson Cancer Center (US)
  • Leukemia Department, University of Texas MD Anderson Cancer Center, Houston, TX 77030;
  • Garvan Institute of Medical Research (AU)
Venue
Proceedings of the National Academy of Sciences
Published
2015-02-23
Volume
112
Issue
10
Pages
E1106-15
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2022326327
Cited by
404
References
74
Citations by year
2026: 6 · 2025: 16 · 2024: 10 · 2023: 22 · 2022: 22 · 2021: 22 · 2020: 27 · 2019: 51 · 2018: 49 · 2017: 76 · 2016: 75 · 2015: 28
FWCI
24.06
Type
journal article
Language
en
Open access
Locations
  • Proceedings of the National Academy of Sciences (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • IRIS Research product catalog (Sapienza University of Rome) (submittedVersion, other-oa)
  • UKnowledge (University of Kentucky) (submittedVersion)
Funders
  • U.S. Department of Defense
  • W. M. Keck Foundation
  • RGK Foundation
  • Hirshberg Foundation for Pancreatic Cancer Research
  • CLL Global Research Foundation
  • Thomas Jefferson University (P30CA56036)
  • Deutsches Krebsforschungszentrum
  • Laura and John Arnold Foundation
  • Weizmann Institute of Science
  • National Institutes of Health (#AG028383)
  • University of Texas MD Anderson Cancer Center
  • Center for AIDS Research, University of Washington
  • National Institute on Aging (P30AG028383, R01AG042419)
  • National Heart, Lung, and Blood Institute (R01HL116713, R01HL102482)
  • National Cancer Institute (R01CA140424, P50CA127297, R01CA099996, P30CA016672, P30CA056036, P30CA036727)
  • National Institute of General Medical Sciences (R01GM106047)
  • National Institute of Allergy and Infectious Diseases (U19AI056363, P30AI042853)
  • National Institute of Neurological Disorders and Stroke (R21NS085830)
  • National Institute of Arthritis and Musculoskeletal and Skin Diseases (R01AR019616)
  • National Institute on Minority Health and Health Disparities (R01MD007880)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant Molecular Biology Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Chromosomal and Genetic Variations
Keywords
microRNA, novel miRNA discovery, microRNA precursors, tissue-specific gene expression, miRNA clusters, RNA interference, human cell lines
MeSH terms
Animals, Base Sequence, Primates, Sequence Alignment, Genome, MicroRNAs, Ribonuclease III, Gene Knockdown Techniques

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