A single RNA test could resolve thousands of ambiguous genetic results that currently leave patients and doctors without a clear diagnosis. Every person carries millions of genetic differences from the reference genome, and when a patient with a suspected rare disease or cancer has their DNA sequenced, many of these variants turn out to be "variants of unknown significance"—mutations that might cause disease, or might be harmless. The problem is that current DNA analysis alone cannot tell the difference. This research builds a diagnostic pipeline that analyses RNA—the molecule that carries instructions from DNA to make proteins—to check whether a suspicious genetic variant actually disrupts how genes are spliced and expressed. Between 15 and 50 percent of unclassified variants could affect RNA splicing, meaning a huge number of patients could receive a definitive diagnosis that is currently out of reach. If successful, the pipeline will become a national NHS resource that transforms ambiguous genetic results into actionable diagnoses. For patients with rare diseases, this means ending years of diagnostic odysseys and enabling family screening, prenatal testing, and targeted treatments. For cancer patients, it means matching the right therapy to the right tumour. The work also lays the foundation for a functional genomics hub that can prove whether newly discovered genes actually cause disease, accelerating the entire field of personalised medicine.
View original technical description
Genomics is the foundation of modern personalised medicine with the acknowledged potential to improve diagnostic accuracy, stratify disease and personalise treatment for immediate patient benefit. Projects to develop genomics in clinical practice are the epitome of the NIHR vision to improve the health and wealth of the nation through research and translation to patient care. Genomics England have kick-started a genomics industry with the 100,000 genomes project which targets patients with rare disease and cancer. One in seventeen people are born with or develop a rare disease during their lifetime and at least 80% of rare diseases have an identified genetic component; 50% of new cases are identified in children. Accurate diagnosis is fundamental in medicine enabling discussion of prognosis, screening, prenatal testing, family cascade testing and possible treatments. 1 in 3 people will get cancer and genomics transforms pathology to enhance the right treatment to the right patient. As implementation of high throughput sequencing into medicine escalates, the challenge remains to effectively translate these findings into diagnostic tests and future treatments. It is estimated that genomes will generate >10 million sequence variants between one individual and another. Each sequence variant must undergo functional verification, herein lies the bottleneck. l aim to use RNA to find missing mutations and provide a legacy for the interpretation of genetic variation in human disease, transforming clinical care. Many mutations in coding regions or introns may appear not to affect protein function but are still potentially causing disease through affecting pre-mRNA splicing. Between 15-50% of unclassified sequence variants (UVs) found at genomic analysis could influence RNA splicing.? Other forms of RNA have also been shown to be important in disease, e.g. non-codingRNA. Aim Development of a diagnostic RNA pipeline, maximising the impact of genome tests for patient benefit and provide a national resource for the NHS. Deliverables Short term- i) Construct RNA pipeline for testing. Medium term- i) Diagnostic uplift through variant verification in a known disease gene for clinical care (not possible without RNA pathway output). ii) Diagnostic uplift through discovery of new genomic causes of disease. iii) RNA based disease signatures. Long Term- Understand disease processes, for personalised medicine and therapies. The Southampton comprehensive RNA analysis diagnostic pipeline Pipeline overview- Figure 6 - will have 3 components Design and Methods? Strategic Patient cohorts i) 50 - Primary ciliary dyskinesia patients; exome sequencing of key PCD genes completed ii) 50 - Clinical immunology patients. RNA samples stored iii) 200 patients selected from the 100,000 genomes project where RNA is available and genome testing has identified variants of unknown significance [Genomics England supported] Optimisation of RNA tests to establish the pathway In silico/bioinformatic prediction of effect of sequence variants on both genome and transcriptome. In collaboration, research and development of bioinformatics computer software tools for genetic diagnostic testing with regards to splicing and RNA, including, machine learning and RNA Seq.? RNA analyses through patient RNA samples and minigene assays -measurement of RNA levels by RT-PCR or minigene analyses. Develop standard operating procedures for progress through bioinformatics to 'wet' lab. Transcriptome analysis (blood, tissue, single cell (immunology cohort); messenger RNA and non-coding RNA). Each sample will be sequenced at sufficient depth to be able to perform an accurate and exhaustive analysis of RNA splicing patterns as well as identification of long non-coding RNAs and fusion transcripts. Gene function hub. Ultimately this technology will be an integral arm to a functional genomics hub- in collaboration, to prove gene pathogenicity. Including cell assays, biochemical assay, in vivo studies, RNA or methylation assays. Figure 5 for network of facilities and support.
Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.
Is something wrong? Let us know