Evidence map›Paper›PMID 37394429›Full record

ArticleGenome biology2023

An Atlas of Variant Effects to understand the genome at nucleotide resolution.

Douglas M Fowler, David J Adams, Anna L Gloyn, William C Hahn, Debora S Marks, Lara A Muffley, James T Neal, Frederick P Roth, Alan F Rubin, Lea M Starita and 1 more

Open access · goldAbstract readEditorial
In one paragraph

Article in Genome biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 94 papers.

0numbers the graph read from it
0cells of the map it votes in
94citing papers in PubMed
19.4field-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

94 citing papers in PubMed, 120 citations in OpenAlex.

  1. Article
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  10. Article
  11. Review
  12. MAVISp: A modular structure-based framework for protein variant effects.Protein science : a publication of the Protein Society · 2026
    Article
  13. Supervised learning of protein variant effects across large-scale mutagenesis datasets.Protein science : a publication of the Protein Society · 2026
    Article
  14. Article
  15. Article
  16. Review
  17. A scalable approach to resolving variants of uncertain significance.bioRxiv : the preprint server for biology · 2026
    Article
  18. Article
  19. Review
  20. Review

34 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

11 authors at 6 institutions in 5 countries.

Douglas M FowlerDepartment of Genome Sciences, University of Washington, Seattle, WA, USA. dfowler@uw.edu.ORCID 0000-0001-7614-1713
David J AdamsWellcome Sanger Institute, Hinxton, Cambridgeshire, UK.ORCID 0000-0001-9490-0306
Anna L GloynDepartment of Pediatrics & Department of Genetics, Division of Endocrinology, Stanford School of Medicine, Stanford University, Stanford, CA, USA. agloyn@stanford.edu.ORCID 0000-0003-1205-1844
William C HahnDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
Debora S MarksBroad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0001-9388-2281
Lara A MuffleyDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID 0000-0002-3035-3339
James T NealBroad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID 0000-0002-3962-8570
Frederick P RothDonnelly Centre and Departments of Molecular Genetics and Computer Science, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-6628-649X
Alan F RubinBioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia.ORCID 0000-0003-1474-605X
Lea M StaritaDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID 0000-0003-2870-5099
Matthew E HurlesWellcome Sanger Institute, Hinxton, Cambridgeshire, UK. meh@sanger.ac.uk.ORCID 0000-0002-2333-7015
Broad Institute · USUniversity of Washington · USWellcome Sanger Institute · GBStanford Medicine · USThe University of Melbourne · AUUniversity of Toronto · CA

Funding

Technology to understand genetic variant effects in contextRM1HG010461 · NHGRI · UNIVERSITY OF WASHINGTON · PI Douglas M Fowler, Bruce Colston Trapnell · 2019 to 2026
$18.9M
Molecular phenotyping of ~100,000 coding variants across Mendelian disease genesUM1HG011989 · NHGRI · DANA-FARBER CANCER INST · PI Marc Vidal · 2021 to 2026
$9.9M
Bridging the gap between type 2 diabetes GWAS and therapeutic targetsUM1DK126185 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI CLAUSSNITZER, MELINA C, GLOYN, ANNA LOUISE · 2020 to 2024
$9.5M
Making antibody generation rapid, scalable, and democratic through machine learning and continuous evolutionR01CA260415 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI KRUSE, ANDREW, LIU, CHANG C · 2020 to 2024
$8.4M
Systematically mapping variant effects for cardiovascular genesR01HL164675 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ASHLEY, EUAN A, RODEN, DAN M · 2022 to 2025
$8.1M
The Dana-Farber Cancer Institute Cancer Target Discovery and Development CenterU01CA176058 · NCI · DANA-FARBER CANCER INST · PI HAHN, WILLIAM C. · 2013 to 2021
$7.8M
Optical Functional GenomicsDP2GM146252 · NIGMS · BROAD INSTITUTE, INC. · PI NEAL, JAMES THOMAS · 2021 to 2024
$2.4M
Comprehensive Characterization of Missense Mutants in Factor IXR01HL152066 · NHLBI · UNIVERSITY OF WASHINGTON · PI FOWLER, DOUGLAS M, JOHNSEN, JILL MARIE · 2020 to 2023
$1.8M
Federated Analysis in Cancer Genomics: Surveying the Social, Ethical, and Regulatory LandscapeU01CA242954 · NCI · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI CLINE, MELISSA SUZANNE · 2019 to 2021
$1.5M
Cancer Research UKMedical Research Council MR/V000292/1NCI NIH HHS R01 CA260415NCI NIH HHS U01 CA176058NCI NIH HHS U01 CA242954NHGRI NIH HHS RM1 HG010461NHGRI NIH HHS UM1 HG011989NHLBI NIH HHS R01 HL152066NHLBI NIH HHS R01 HL164675NIDDK NIH HHS UM1 DK126185NIGMS NIH HHS DP2 GM146252Wellcome TrustWellcome Trust 200837/Z/16/Z
6 · The paper itself

Abstract

Sequencing has revealed hundreds of millions of human genetic variants, and continued efforts will only add to this variant avalanche. Insufficient information exists to interpret the effects of most variants, limiting opportunities for precision medicine and comprehension of genome function. A solution lies in experimental assessment of the functional effect of variants, which can reveal their biological and clinical impact. However, variant effect assays have generally been undertaken reactively for individual variants only after and, in most cases long after, their first observation. Now, multiplexed assays of variant effect can characterise massive numbers of variants simultaneously, yielding variant effect maps that reveal the function of every possible single nucleotide change in a gene or regulatory element. Generating maps for every protein encoding gene and regulatory element in the human genome would create an 'Atlas' of variant effect maps and transform our understanding of genetics and usher in a new era of nucleotide-resolution functional knowledge of the genome. An Atlas would reveal the fundamental biology of the human genome, inform human evolution, empower the development and use of therapeutics and maximize the utility of genomics for diagnosing and treating disease. The Atlas of Variant Effects Alliance is an international collaborative group comprising hundreds of researchers, technologists and clinicians dedicated to realising an Atlas of Variant Effects to help deliver on the promise of genomics.

Indexed as

Genetic VariationGenomicsGenome, HumanHigh-Throughput Nucleotide SequencingHumansPrecision MedicineFunctional genomicsGenome interpretationGlobal allianceMultiplexed assay of variant effectSaturation mutagenesisVariant effect

Identifiers

PMID37394429
PMCPMC10316620
OpenAlexW4382893389

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.