Active Genetics & Molecular Biology Brain & Nervous System

Primary Annotated Resources to Advance Discovery In Genomic Medicine (PARADIGM)

In plain English

AI plain-English summary

Whole genome sequencing fails to diagnose the majority of patients with rare diseases, leaving millions of families without answers. The problem is not the sequencing itself but the lack of clinically useful genome annotation—researchers cannot reliably classify which genetic changes cause disease because they lack detailed maps of how genes are expressed in different tissues. This project tackles that gap head-on. The team will generate long-read RNA sequencing data from fetal brain and adult heart samples to capture complete transcript isoforms, then combine these with machine learning and expert curation to build tissue-specific gene expression maps and new disease models. If successful, PARADIGM will provide a suite of openly available resources that clinical geneticists and researchers can use to re-analyse existing patient data. This could directly increase diagnostic rates for two contrasting rare disease areas—paediatric developmental disorders and adult cardiomyopathies—and accelerate the discovery of new disease-causing genes. The tools and datasets will be integrated into widely used genomic medicine databases, quietly improving the infrastructure that underpins rare disease diagnosis across the NHS and beyond.

View original technical description
Rare diseases affect around 6% of the population and are mostly caused by rare genetic changes. However, despite enormous investment in genomics, whole genome sequencing does not yield a diagnosis for the majority of patients. Lack of clinically-relevant genome annotation frequently prevents robust variant classification and identification of new disease-causing loci. Our proposal seeks to fulfil the bold vision of coupling functional genomics data with clinical and bioinformatics expertise to empower diagnosis and discovery in genomic medicine. We will apply machine learning and expert curation to provide new literature-derived disease models and tissue-specific gene expression maps. Focusing on two contrasting monogenic disease areas (paediatric developmental disorders and adult cardiomyopathies) we will generate long-read RNA sequencing data from fetal brain and adult heart samples to detect full-length transcript isoforms. We will then use these alongside other emerging datasets to find new causes of disease in existing patient cohorts through a combination of computational phenomics, novel pathogenic variant identification, and isoform-informed burden testing. Finally, we will provide a suite of Primary Annotated Resources to Advance Discovery In Genomic Medicine (PARADIGM), by integrating our novel high- resolution datasets into existing tools and databases that are widely used by the genomic medicine community.

View the original record at the funder ↗

Researchers

Helen Firth (EPMC Awardee)Matthew Hurles (EPMC Awardee)

Related Research

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Human functional genomics of post-translationally modifying clinical coding variants: FGx-PTMv
Translational genomics- maximising potential for NHS patient care.

Original classification

Discovery Award

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