Research

We use computational approaches and large genomic datasets to understand gene regulation for better diagnosis and treatment of rare genetic disorders.

Improving diagnosis of rare disorders

Clinical genetic testing is common place for rare disease patients. Identifying the genetic cause of disease is of huge benefit to both patients and their families; allowing us to screen additional family members to identify those also at risk, return an accurate diagnosis to the patient, and enable personalised treatment. Through current approaches, however, we only find a genetic diagnosis in around half of all rare disease patients. We aim to find those ‘missing’ diagnoses.

We focus on non-coding regions of the genome.

Current clinical genetic testing focusses almost exclusively on the regions of the genome that code directly for proteins. We believe that a subset of the undiagnosed patients will have genetic variants in regions outside of this protein-coding sequence, that have crucial roles in regulating the amount of proteins that are produced. Our aim is to identify these disease-causing regulatory variants and determine how they lead to disease.

We have shown the importance of variants in untranslated regions (UTRs) in a wide variety of rare disorders (Whiffin et al. Nat Comms 2020, Wright et al. AJHG 2021, Martin-Geary et al. Genome Med 2025). These are the regions of a gene directly up- and down-stream of the protein coding region. They form part of the mRNA molecule, but are not translated into protein. These regions have very important regulatory roles: they control the stability of the RNA, the location of it within the cell, and the rate at which it is translated into protein. Variants within these regions that affect these regulatory processes can therefore have a large impact (Wieder et al. EJHG 2025). We have also studied the biology of UTRs and how they vary in known disease genes that are intolerant to changes in dosage (Wieder et al. Genome Bio 2024).

We have played an instrumental role in recent discoveries of variants in small nuclear RNAs (snRNAs) as a cause of neurodevelopmental disorders (NDDs). In 2024, we showed that de novo variants in RNU4-2 cause a highly prevalent NDD (Chen et al. Nature 2024), which is now known as ReNU syndrome. More recently, we used saturation genome editing (SGE; in collaboration with Greg Findlay, Crick Institute) to discover a recessive NDD also associated with RNU4-2 (De Jonghe et al. Nature 2026; Rius & Blakes et al. Nat Gen 2026).

We develop tools and resources to enable annotation and classification of non-coding variants in routine clinical care.

We believe that we can do more than just publishing papers. We try to build on our work to create the tools and resources that enable use of our research in clinical settings. To this end we have developed UTRannotator, to annotate variants in UTRs that could impact translational regulation, and VuTR, to visualise the impact of such variants.

We also brought together a group of experts to write a set of recommendations for clinical interpretation of variants in non-coding regions of the genome (Ellingford et al. 2022), enabling these variants to be classified in routine clinical genetic testing.

Identifying novel therapeutic targets for rare disorders

Currently, over 95% of rare disorders have no specific treatments, with the only therapies in use targeting specific symptoms rather than the root cause of the disorder. Dramatic recent technological developments are enabling CRISPR-based genome editing and oligonucleotide therapies to be used as personalised therapies for patients with rare disorders. We use computational approaches to identify treatable genes and patients.

An in-depth knowledge of gene regulation is critical to design of effective therapies.

Many successful therapies, including treatments for spinal muscular atrophy and cystic fibrosis, utilise in-depth knowledge of gene regulation. We use computational approach and ‘omics datasets to identify regulatory elements that could be modified to increase or decrease levels of an RNA or protein therapeutically.

For example, in recent work, we showed how exclusion of upstream open reading frames (uORFs), that are negative regulatory elements in 5’UTRs, through exon skipping could be a therapeutic approach for many rare disorder genes (Beer Wells et al. 2025).

We are also part of the MRC Centre of Research Excellence (CoRE) in Therapeutic Genomics, a large multinational collaborative effort to bring genetic therapies to patients with rare disorders, at scale.

Our research is powered by large-scale genomics data

We mainly analyse publicly available large-scale genomic datasets including:

We are also a highly collaborative team, working with many others around the world with access to additional datasets.

We use a diverse set of approaches

These include:

  • Using population cohorts to identify specific variants in functional non-coding elements that show signals of being under strong negative selection, indicating that they are likely deleterious.

  • Identifying disease-causing non-coding region variants in rare disease cases.

  • Harnessing diverse omics datasets including genomics, transcriptomics, and ribosome profiling (ribo-seq) data.

  • Discovering approaches through which gene regulation can be targeting therapeutically.

  • Creating tools and resources to improve annotation of functional non-coding variants.

  • Developing clinical guidelines to support interpretation of non-coding region variants.