Accurate and complete human gene annotation, defined as the genetic coordinates of all transcripts of a given gene, is fundamental to a huge range of genetic, transcriptomic and molecular analyses. Growing evidence suggests that human gene annotation remains incomplete and is most incomplete within the brain. However, it is unclear how this affects different loci and more specifically our understanding of neurological diseases, such as Parkinson’s disease (PD). To address this question, my group have used a combination of short-read, as well as targeted and untargeted long-read RNA-sequencing technologies and applied them to human brain and PD-relevant cell samples. This work has involved the development of a range of new software that enables improvements in the quality control and assessment of novel transcripts, visualisation of transcriptomic data and its integration with mass spectrometry data at scale. Together, these analyses have revealed an unexpectedly rich and complex transcriptomic landscape in human brain even within highly studied loci, such as SNCA and GBA1-GBAP1, with novel protein coding transcripts identified in both cases. While further work is required in the field, we believe these findings already have implications for how we understand and potentially even treat Parkinson’s disease.
Professor Mina Ryten began her medical training in Cambridge University and went on to complete an MBPhD at UCL. While her PhD focused on purinergic signalling in skeletal muscle development, she subsequently trained in bioinformatics through an MRC Post-doctoral Fellowship in Systems Biology. This experience led her to become a Clinical Geneticist, shaped her research interests and formed the basis of her application for an MRC Clinician Scientist Fellowship. Since 2017 Mina has led her own research group at the UCL Institute of Neurology, and later the UCL Institute of Child Health. In January 2024, she moved to join the Cambridge Dementia Research Institute as its new Director. At the core of her group’s research is the use of human brain transcriptomic data as a genome-wide functional read-out of an individual’s DNA – a read-out which can inform our understanding of the genetic origins of neurodegenerative diseases. For rare neurogenetic diseases this has meant using correlations in transcriptomic data to identify hidden gene-gene relationships amongst Mendelian genes. In the context of complex neurological diseases, Mina has generated and used regulatory data across the human brain to link disease risk positions to specific genes. Thus, over the last ten years, she has developed extensive expertise in the generation and use of human brain transcriptomic data with a specific focus on neurodegenerative diseases and particularly Lewy body disorders.
