Evidence map›Paper›PMID 30209399›Full record

ArticleNature2018

Accurate classification of BRCA1 variants with saturation genome editing.

Gregory M Findlay, Riza M Daza, Beth Martin, Melissa D Zhang, Anh P Leith, Molly Gasperini, Joseph D Janizek, Xingfan Huang, Lea M Starita, Jay Shendure

Abstract read
In one paragraph

Article in Nature, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 547 papers.

0numbers the graph read from it
0cells of the map it votes in
547citing 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

547 citing papers in PubMed.

  1. Review
  2. Article
  3. AlphaGenome Atlas:medRxiv : the preprint server for health sciences · 2026
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  6. Review
  7. Review
  8. Review
  9. Review
  10. Review
  11. Reclassification ofCurrent oncology (Toronto, Ont.) · 2026
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Gregory M FindlayDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Riza M DazaDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Beth MartinDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Melissa D ZhangDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Anh P LeithDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Molly GasperiniDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Joseph D JanizekDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Xingfan HuangDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Lea M StaritaDepartment of Genome Sciences, University of Washington, Seattle, WA, USA. lstarita@uw.edu.
Jay ShendureDepartment of Genome Sciences, University of Washington, Seattle, WA, USA. shendure@uw.edu.

Funding

University of Washington Medical Scientist Training Program: MD/PhDT32GM007266 · NIGMS · UNIVERSITY OF WASHINGTON · PI HORWITZ, MARSHALL S. · 1985 to 2023
$30.4M
INTERDISCIPLINARY TRAINING IN GENOMIC SCIENCEST32HG000035 · NHGRI · UNIVERSITY OF WASHINGTON · PI Bruce Colston Trapnell · 1995 to 2026
$24.2M
Interpreting Genetic Variants of Uncertain SignificanceDP1HG007811 · NHGRI · UNIVERSITY OF WASHINGTON · PI SHENDURE, JAY ASHOK · 2013 to 2017
$3.8M
Predictive Modeling of Alternative Splicing and Polyadenylation from Millions of Random SequencesR01HG009136 · NHGRI · UNIVERSITY OF WASHINGTON · PI SEELIG, GEORG, SHENDURE, JAY ASHOK · 2017 to 2020
$2.3M
Genome editing to determine functional consequences of thousands of potentially pathogenic variantsF30CA213728 · NCI · UNIVERSITY OF WASHINGTON · PI FINDLAY, GREGORY · 2017 to 2020
$130k
NCI NIH HHS F30 CA213728NHGRI NIH HHS DP1 HG007811NHGRI NIH HHS R01 HG009136NIGMS NIH HHS T32 GM007266
6 · The paper itself

Abstract

Variants of uncertain significance fundamentally limit the clinical utility of genetic information. The challenge they pose is epitomized by BRCA1, a tumour suppressor gene in which germline loss-of-function variants predispose women to breast and ovarian cancer. Although BRCA1 has been sequenced in millions of women, the risk associated with most newly observed variants cannot be definitively assigned. Here we use saturation genome editing to assay 96.5% of all possible single-nucleotide variants (SNVs) in 13 exons that encode functionally critical domains of BRCA1. Functional effects for nearly 4,000 SNVs are bimodally distributed and almost perfectly concordant with established assessments of pathogenicity. Over 400 non-functional missense SNVs are identified, as well as around 300 SNVs that disrupt expression. We predict that these results will be immediately useful for the clinical interpretation of BRCA1 variants, and that this approach can be extended to overcome the challenge of variants of uncertain significance in additional clinically actionable genes.

Indexed as

Gene EditingBRCA1 ProteinCell LineExonsFemaleGenes, EssentialGenetic Predisposition to DiseaseGenetic VariationGenome, HumanHereditary Breast and Ovarian Cancer SyndromeHumansLoss of Function MutationModels, MolecularPrognosisRecombinational DNA RepairRNA, MessengerBRCA1 ProteinBRCA1 protein, humanRNA, Messenger

Identifiers

PMID30209399
PMCPMC6181777

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.