ArticleScience (New York, N.Y.)2020
Transcriptomic signatures across human tissues identify functional rare genetic variation.
Open access · greenAbstract read
In one paragraph
Article in Science (New York, N.Y.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 116 papers.
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116citing papers in PubMed
17.1field-weighted citation impact, top 1% of its field
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Who cites it
116 citing papers in PubMed, 159 citations in OpenAlex.
- Machine learning and statistical methods for molecular quantitative trait loci.Nature reviews. Genetics · 2026Review
- Alternative tandem transcription initiation links noncoding variants to human disease through translational control.Nature communications · 2026Article
- Massively parallel characterization and predictive modelling of neuronal regulatory variation.bioRxiv : the preprint server for biology · 2026Article
- Advancing risk gene discovery across the allele frequency spectrum.HGG advances · 2026Review
- Decoding common and rare noncoding variant effects across cellular and developmental contexts.Nature genetics · 2026Article
- Population-scale detection of methylation outliers from long-read genome sequencing.medRxiv : the preprint server for health sciences · 2026Article
- Detecting unannotated splicing events in short-read RNA-seq with SAMI, a UMI-aware Nextflow pipeline.Bioinformatics (Oxford, England) · 2026Article
- Large-scale analysis of temporal gene expression variation in peripheral blood.Nature communications · 2026Article
- Paired DNA and RNA sequencing uncovers common and rare variation regulating human retinal gene expression.Nature communications · 2026Article
- Fine-tuning sequence-to-expression models on personal genome and transcriptome data.Genome biology · 2026Article
- AXOLOTL: an accurate method for detecting aberrant gene expression in rare diseases using coexpression constraints.Bioinformatics (Oxford, England) · 2026Article
- Functional impact of genetic background on variable expressivity in neurodevelopmental disorders.Nature communications · 2026Article
- Tissue-specific gene dosage disruption is a key feature and pathogenic mechanism of structural variants in the human genome.Genome medicine · 2026Article
- Targeted long-read RNA sequencing for rare disease diagnosis and variant interpretation.Science advances · 2026Article
- Variant-resolved prediction of context-specific isoform variation with a graph-based attention model.Cell genomics · 2026Article
- Article
- saseR: juggling offsets unlocks RNA-seq tools for fast and scalable differential usage, aberrant splicing and expression retrieval.Genome biology · 2026Article
- Benchmarking RNA-seq Tools for Real-World Diagnostic Applications.Research square · 2026Article
- Benchmarking RNA-seq Tools for Real-World Diagnostic Applications.medRxiv : the preprint server for health sciences · 2026Article
- TSniffer: unbiased de novo identification of RNA editing sites and quantification of editing activity in RNA-seq data.Genome biology · 2026Article
56 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
39 authors at 14 institutions in 2 countries.
Nicole M Ferraro *Biomedical Informatics Training Program, Stanford University, Stanford, CA, USA.ORCID https://orcid.org/0000-0003-4291-193X
Benjamin J Strober *Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.ORCID https://orcid.org/0000-0003-2969-2808
Jonah EinsonDepartment of Biomedical Informatics, Columbia University, New York, NY, USA.ORCID https://orcid.org/0000-0002-5564-1003
Nathan S AbellDepartment of Genetics, Stanford University, Stanford, CA, USA.
Francois AguetBroad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID https://orcid.org/0000-0001-9414-300X
Alvaro N BarbeiraSection of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA.ORCID https://orcid.org/0000-0002-9153-6120
Margot BrandtNew York Genome Center, New York, NY, USA.ORCID https://orcid.org/0000-0002-9434-794X
Maja BucanDepartment of Genetics, University of Pennsylvania, Philadelphia, PA, USA.
Stephane E CastelNew York Genome Center, New York, NY, USA.ORCID https://orcid.org/0000-0002-0707-2133
Joe R DavisDepartment of Pathology, Stanford University, Stanford, CA, USA.ORCID https://orcid.org/0000-0003-2544-388X
Emily GreenwaldDepartment of Genetics, Stanford University, Stanford, CA, USA.ORCID https://orcid.org/0000-0001-9991-6489
Gaelen T HessDepartment of Genetics, Stanford University, Stanford, CA, USA.
Austin T HilliardPalo Alto Veterans Institute for Research, Palo Alto Epidemiology Research and Information Center for Genomics, VA Palo Alto Health Care System, Palo Alto, CA, USA.ORCID https://orcid.org/0000-0002-1289-4377
Rachel L KemberDepartment of Genetics, University of Pennsylvania, Philadelphia, PA, USA.ORCID https://orcid.org/0000-0001-8820-2659
Bence KotisDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA.
YoSon ParkDepartment of Systems Pharmacology and Translational Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA.ORCID https://orcid.org/0000-0002-0465-4744
Gina PelosoDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
Shweta RamdasDepartment of Genetics, University of Pennsylvania, Philadelphia, PA, USA.
Alexandra J ScottMcDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.ORCID https://orcid.org/0000-0002-1930-9265
Craig SmailBiomedical Informatics Training Program, Stanford University, Stanford, CA, USA.
Emily K TsangDepartment of Pathology, Stanford University, Stanford, CA, USA.ORCID https://orcid.org/0000-0001-7287-6448
Seyedeh M ZekavatMedical & Population Genomics, Yale School of Medicine and Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID https://orcid.org/0000-0003-4026-8944
Marcello ZiosiNew York Genome Center, New York, NY, USA.
AradhanaDepartment of Genetics, Stanford University, Stanford, CA, USA.
TOPMed Lipids Working Group
Kristin G ArdlieBroad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID https://orcid.org/0000-0003-4272-6283
Themistocles L AssimesPalo Alto Veterans Institute for Research, Palo Alto Epidemiology Research and Information Center for Genomics, VA Palo Alto Health Care System, Palo Alto, CA, USA.ORCID https://orcid.org/0000-0003-2349-0009
Michael C BassikDepartment of Genetics, Stanford University, Stanford, CA, USA.ORCID https://orcid.org/0000-0001-5185-8427
Christopher D BrownDepartment of Genetics, University of Pennsylvania, Philadelphia, PA, USA.
Adolfo CorreaUniversity of Mississippi Medical Center, Jackson, MS, USA.ORCID https://orcid.org/0000-0002-9501-600X
Ira HallMcDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.
Hae Kyung ImSection of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA.ORCID https://orcid.org/0000-0003-0333-5685
Xin LiDepartment of Pathology, Stanford University, Stanford, CA, USA.ORCID https://orcid.org/0000-0002-2122-7461
Pradeep NatarajanCardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.ORCID https://orcid.org/0000-0001-8402-7435
GTEx Consortium
Tuuli LappalainenNew York Genome Center, New York, NY, USA.ORCID https://orcid.org/0000-0002-7746-8109
Pejman Mohammadi *New York Genome Center, New York, NY, USA. pejman@scripps.edu smontgom@stanford.edu ajbattle@jhu.edu.ORCID https://orcid.org/0000-0003-4457-8552
Stephen B Montgomery *Department of Genetics, Stanford University, Stanford, CA, USA. pejman@scripps.edu smontgom@stanford.edu ajbattle@jhu.edu.ORCID https://orcid.org/0000-0002-5200-3903
Alexis Battle *Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA. pejman@scripps.edu smontgom@stanford.edu ajbattle@jhu.edu.ORCID https://orcid.org/0000-0002-5287-627X
Stanford University · USNew York Genome Center · USBroad Institute · USUniversity of Pennsylvania · USJohns Hopkins University · USScripps Research Institute · USUniversity of Chicago · USTranslational Therapeutics (United States) · USJames S. McDonnell Foundation · USShanghai Institutes for Biological Sciences · CNVA Palo Alto Health Care System · USBoston University · USJackson Memorial Hospital · USUniversity of North Carolina at Chapel Hill · US
Funding
Clinical and Translational Science AwardUL1TR001873 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI REILLY, MUREDACH P · 2016 to 2025
$99.0MNew York Center for Collaborative Research In Common Disease Genomics: Genome Aggregation and Joint Variant Calling for CCDG Freeze2UM1HG008901 · NHGRI · NEW YORK GENOME CENTER · PI MANIATIS, THOMAS P, WIGLER, MICHAEL H · 2016 to 2020
$56.6MThe UCSC Genome BrowserU41HG002371 · NHGRI · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI KENT, WILLIAM JAMES · 2012 to 2021
$36.6MINSTITUTIONAL TRAINING GRANT IN GENOME SCIENCET32HG000044 · NHGRI · STANFORD UNIVERSITY · PI MICHAEL P. SNYDER · 1995 to 2026
$32.2MScripps Translational Science InstituteUL1TR002550 · NCATS · SCRIPPS RESEARCH INSTITUTE, THE · PI TOPOL, ERIC JEFFREY · 2018 to 2022
$28.9MPOSTDOCTORAL TRAINING IN MEDICAL INFORMATION SCIENCEST15LM007033 · NLM · STANFORD UNIVERSITY · PI SYLVIA KATINA PLEVRITIS · 1985 to 2026
$25.5MScripps Translational Science InstituteUL1TR001114 · NCATS · SCRIPPS RESEARCH INSTITUTE, THE · PI TOPOL, ERIC JEFFREY · 2013 to 2017
$24.0MPilot and Feasibility ProgramP30DK020595 · NIDDK · UNIVERSITY OF CHICAGO · PI Matthew J Brady · 2013 to 2026
$20.9MPulmonary microvascular perfusion in the Multi-Ethnic Study of AtherosclerosisR01HL077612 · NHLBI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI R Graham BARR · 2004 to 2026
$18.8MStudies of Rare Genetic Variation in the Isolated Population of SardiniaR01HL117626 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ABECASIS, GONCALO · 2013 to 2016
$10.5MBIOMEDICAL ENGINEERING TRAINING PROGRAMT32GM007057 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI KANOLD, PATRICK O, KARCHIN, RACHEL · 1985 to 2023
$10.4MRare variants and NHLBI traits in deeply phenotyped cohortsR01HL120393 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M, RICE, KENNETH M. · 2014 to 2016
$8.9MBLRD VA I01 BX003340BLRD VA I01 BX003362CCR NIH HHS HHSN261200800001CNCATS NIH HHS UL1 TR001114NCATS NIH HHS UL1 TR001873NCATS NIH HHS UL1 TR002550NCI NIH HHS HHSN261200800001ENHGRI NIH HHS F32 HG009987NHGRI NIH HHS K99 HG009916NHGRI NIH HHS R01 HG002585NHGRI NIH HHS R01 HG006855NHGRI NIH HHS R01 HG008150NHGRI NIH HHS R01 HG009125NHGRI NIH HHS R01 HG010067NHGRI NIH HHS R01 HG010480NHGRI NIH HHS R35 HG010718NHGRI NIH HHS T32 HG000044NHGRI NIH HHS U01 HG007593NHGRI NIH HHS U01 HG007598NHGRI NIH HHS U01 HG009080NHGRI NIH HHS U01 HG009431NHGRI NIH HHS U41 HG002371NHGRI NIH HHS U41 HG009494NHGRI NIH HHS UM1 HG008901NHLBI NIH HHS HHSN268201000029CNHLBI NIH HHS HHSN268201100037CNHLBI NIH HHS HHSN268201800001CNHLBI NIH HHS HHSN268201800010INHLBI NIH HHS HHSN268201800011CNHLBI NIH HHS HHSN268201800011INHLBI NIH HHS HHSN268201800012CNHLBI NIH HHS HHSN268201800012INHLBI NIH HHS HHSN268201800014CNHLBI NIH HHS HHSN268201800014INHLBI NIH HHS HHSN268201800015INHLBI NIH HHS R01 HL077612NHLBI NIH HHS R01 HL117626NHLBI NIH HHS R01 HL120393NHLBI NIH HHS R01 HL142015NHLBI NIH HHS R01 HL142028NHLBI NIH HHS R01 HL142711NHLBI NIH HHS U01 HL120393NIA NIH HHS R01 AG066490NIDA NIH HHS R01 DA006227NIDDK NIH HHS P30 DK020595NIDDK NIH HHS T32 DK110919NIGMS NIH HHS R01 GM122924NIGMS NIH HHS R01 GM124486NIGMS NIH HHS T32 GM007057NIMHD NIH HHS HHSN268201800013INIMH NIH HHS R01 MH090936NIMH NIH HHS R01 MH090937NIMH NIH HHS R01 MH090941NIMH NIH HHS R01 MH090951NIMH NIH HHS R01 MH101814NIMH NIH HHS R01 MH101822NIMH NIH HHS R01 MH106842NIMH NIH HHS R01 MH107666NIMH NIH HHS R01 MH109905NIMH NIH HHS U01 MH104393NLM NIH HHS T15 LM007033NLM NIH HHS T32 LM012409
Abstract
Rare genetic variants are abundant across the human genome, and identifying their function and phenotypic impact is a major challenge. Measuring aberrant gene expression has aided in identifying functional, large-effect rare variants (RVs). Here, we expanded detection of genetically driven transcriptome abnormalities by analyzing gene expression, allele-specific expression, and alternative splicing from multitissue RNA-sequencing data, and demonstrate that each signal informs unique classes of RVs. We developed Watershed, a probabilistic model that integrates multiple genomic and transcriptomic signals to predict variant function, validated these predictions in additional cohorts and through experimental assays, and used them to assess RVs in the UK Biobank, the Million Veterans Program, and the Jackson Heart Study. Our results link thousands of RVs to diverse molecular effects and provide evidence to associate RVs affecting the transcriptome with human traits.
Indexed as
Genetic VariationGenome, HumanMultifactorial InheritanceTranscriptomeHumansOrgan Specificity
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