Evidence map›Paper›PMID 28475858›Full record

ArticleAmerican journal of human genetics2017

Systematic Computational Identification of Variants That Activate Exonic and Intronic Cryptic Splice Sites.

Melissa Lee, Patrick Roos, Neeraj Sharma, Melis Atalar, Taylor A Evans, Matthew J Pellicore, Emily Davis, Anh-Thu N Lam, Susan E Stanley, Sara E Khalil and 6 more

Open access · bronzeAbstract read
In one paragraph

Article in American journal of human genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
10.4field-weighted citation impact, top 1% of its field
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

42 citing papers in PubMed, 78 citations in OpenAlex.

  1. Trial
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  6. The genome of the black-footed cat: Revealing a rich natural history and urgent conservation priorities for small felids.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  7. Molecular and functional correction of a deep intronic splicing mutation inMolecular therapy. Methods & clinical development · 2023
    Article
  8. Article
  9. Article
  10. Article
  11. Telomere-mediated lung disease.Physiological reviews · 2022
    Review
  12. Article
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  14. Article
  15. Review
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  17. Article
  18. Article
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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

16 authors at 3 institutions in 1 country.

Melissa LeeMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Patrick RoosMiner & Kasch, Severna Park, MD 21146, USA.
Neeraj SharmaMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Melis AtalarMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Taylor A EvansMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Matthew J PellicoreMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Emily DavisMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Anh-Thu N LamMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Susan E StanleyDepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Sara E KhalilDepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
George M SolomonDivision of Pulmonary, Allergy, and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, AL 35233 USA.
Doug WalkerPediatric Pulmonary Medicine, Johns Hopkins University, Baltimore, MD 21205, USA.
Karen S RaraighMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Briana Vecchio-PaganMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Mary ArmaniosMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Garry R CuttingMcKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA. Electronic address: gcutting@jhmi.edu.
Johns Hopkins University · USJohns Hopkins Medicine · USUniversity of Alabama at Birmingham · US

Funding

UAB CF Research and Translation Core CenterP30DK072482 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI David M. Bedwell · 2007 to 2026
$23.0M
Predoctoral Training Program in Human GeneticsT32GM007814 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI VALLE, DAVID · 1985 to 2021
$10.6M
MOLECULAR GENETICS OF CYSTIC FIBROSISR01DK044003 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI Garry R Cutting · 1991 to 2026
$6.7M
Mechanisms of Telomere-Induced EmphysemaR01HL119476 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI ARMANIOS, MARY Y · 2014 to 2023
$4.5M
The Role of Telomere Shortening in MDS-AML Pathogenesis (resubmission)R01CA160433 · NCI · JOHNS HOPKINS UNIVERSITY · PI ARMANIOS, MARY Y · 2012 to 2016
$1.7M
NCI NIH HHS R01 CA160433NHLBI NIH HHS R01 HL119476NIDDK NIH HHS P30 DK072482NIDDK NIH HHS R01 DK044003NIGMS NIH HHS T32 GM007814
6 · The paper itself

Abstract

We developed a variant-annotation method that combines sequence-based machine-learning classification with a context-dependent algorithm for selecting splice variants. Our approach is distinctive in that it compares the splice potential of a sequence bearing a variant with the splice potential of the reference sequence. After training, classification accurately identified 168 of 180 (93.3%) canonical splice sites of five genes. The combined method, CryptSplice, identified and correctly predicted the effect of 18 of 21 (86%) known splice-altering variants in CFTR, a well-studied gene whose loss-of-function variants cause cystic fibrosis (CF). Among 1,423 unannotated CFTR disease-associated variants, the method identified 32 potential exonic cryptic splice variants, two of which were experimentally evaluated and confirmed. After complete CFTR sequencing, the method found three cryptic intronic splice variants (one known and two experimentally verified) that completed the molecular diagnosis of CF in 6 of 14 individuals. CryptSplice interrogation of sequence data from six individuals with X-linked dyskeratosis congenita caused by an unknown disease-causing variant in DKC1 identified two splice-altering variants that were experimentally verified. To assess the extent to which disease-associated variants might activate cryptic splicing, we selected 458 pathogenic variants and 348 variants of uncertain significance (VUSs) classified as high confidence from ClinVar. Splice-site activation was predicted for 129 (28%) of the pathogenic variants and 75 (22%) of the VUSs. Our findings suggest that cryptic splice-site activation is more common than previously thought and should be routinely considered for all variants within the transcribed regions of genes.

Indexed as

Computational BiologyGenetic VariationRNA Splice SitesAlgorithmsCell Cycle ProteinsCystic FibrosisCystic Fibrosis Transmembrane Conductance RegulatorDyskeratosis CongenitaExonsGene Expression RegulationGenetic LociGenomicsHEK293 CellsHumansIntronsMutation, MissenseCell Cycle ProteinsCFTR protein, humanCystic Fibrosis Transmembrane Conductance RegulatorDKC1 protein, humanNuclear ProteinsRNA Splice Sitescryptic splicingcystic fibrosismachine learningminigenepseudoexonsplice acceptorsplice donorsplice variantsplicing

Identifiers

PMID28475858
PMCPMC5420354
OpenAlexW2611720143

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.