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NOBEL PRIZE 2026

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NIHNATIONAL HUMAN GENOME RESEARCH INSTITUTER01

Advancing rare disease discovery through technological and methodological approaches using an intuitive platform, seqr

Active
Institution
BROAD INSTITUTE, INC., MA
Principal investigator
Anne O'Donnell-Luria
Funding
$3.3M
Duration
2025–2029
Open portfolio

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Still being scored

Abstract

PROJECT SUMMARY / ABSTRACT Over half of all rare disease families remain undiagnosed following exome and genome sequencing analysis. Remarkable developments in genomic technologies, analytical tools, and innovative data sharing are advancing Mendelian gene discovery. However, the benefits of these novel advances will only become realized if they are integrated into widely accessible platforms for genomic analysis. The Broad Institute Center for Mendelian Genomics has supported the deployment and ongoing development of the seqr genomic analysis platform, which is freely available to the community either on the AnVIL platform or as an open-source tool that can be installed locally. This proposal seeks to advance the discovery rate for rare disease through ongoing development of the seqr platform, incorporating and evaluating the impact of three novel advances: 1) innovative data sharing through variant level matching by connecting seqr to a growing federated platform of rare disease and population genomic data with associated phenotype; 2) deployment of automated analytical tools on previously examined and unsolved cases to identify variation that is newly implicated as pathogenic in genes with known disease associations or in genes that are newly implicated in disease; and 3) incorporation of novel technologies such as long read DNA and RNA sequencing data that can be easily analyzed in a genome-wide manner. We will study the impact of these novel advances by analyzing the diagnostic yield of each approach. As seqr is freely available and open source, our proposal democratizes the process of genetic discovery, empowering researchers and clinicians to resolve diagnostic variants, and accelerate the rate of diagnosis for the global population of individuals with rare genetic disease.

Research team

  • Anne O'Donnell-LuriaPI
  • Heidi L RehmPI

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R01NATIONAL HUMAN GENOME RESEARCH INSTITUTEGenomics, Computational Biology and Technology Study Section[GCAT]freelygenomic analysisdata sharingrare diseaseanalytical toolsmendelianfreely availablerare

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