WEHI PhD Completion Seminar hosted by Professor Melanie Bahlo

Jacob Munro
PhD Student – Bahlo Laboratory, Genetics and Gene Regulation division, WEHI

Scalable Variant Discovery in Rare Epilepsies: From DNA to RNA

Davis Auditorium

Join via TEAMS

Including Q&A session

Developmental and epileptic encephalopathies are severe, early-onset neurological disorders that are predominantly monogenic, yet most individuals remain without a molecular diagnosis after routine clinical testing. In this thesis, we aim to address this gap through scalable approaches to variant discovery in rare epilepsies, spanning analyses from DNA sequencing through to RNA-based interpretation.


We first apply genome sequencing to previously unsolved cases of developmental and epileptic encephalopathy to improve diagnostic yield, enabling detection of structural and non-coding variation that is not captured by standard clinical testing, as well as variants in newly implicated disease genes. This work highlights the value of extending variant discovery beyond conventional coding frameworks in clinically heterogeneous cohorts. Building on this, I investigate how transcriptomic data can support interpretation of genomic findings and resolve complex variant mechanisms, illustrated through analysis of a structural variant in FBRSL1, where RNA sequencing provides evidence consistent with a dominant-negative disease mechanism in a severe developmental epileptic encephalopathy.

To support scalable interpretation of sequencing data, I developed PanRank, a machine learning framework that integrates diverse biological evidence to prioritise candidate disease genes and reduce the search space for downstream validation in large genomic datasets. Finally, I developed EdiSetFlow, a scalable pipeline for transcriptome-wide analysis of RNA editing from bulk RNA sequencing data, and applied it to characterise RNA editing patterns across human brain regions.

Together, this work demonstrates a scalable framework for variant discovery in rare epilepsies, integrating genomic and transcriptomic data to improve diagnosis and gene discovery.

All welcome!