Computational tool reveals hidden genomic variability in the brain genome

The human genome has a wide range of variability, partly due to large scale mutations ("structural variants"). Sequencing DNA using "long" reads allows better detection of these, but still requires complex computational analysis.

Researchers, including Professor Christos Proukakis (UCL Queen Square Institute of Neurology) extensively updated a software tool called Sniffles which had been originally developed for genomic structural variant detection. It is now faster and more accurate, allowing more efficient analysis by labs around the world who are generating long read DNA sequencing data. It can also detect mutations which arose after fertilisation, ie were not inherited from the parents, and exist only in some cells within a tissue (mosaic).

They validated selected mosaic deletions in the brain of an individual who had multiple system atrophy as proof-of-principle. The tool is already being widely used for analysis of large scale DNA variants in long read DNA sequencing

“I am delighted that we worked with Fritz Sedlazeck and his group at Baylor in Texas to improve the Sniffles algorithm, particularly for the detection of mosaic variants. We are already using Sniffles2 to explore the hidden variability in the brain genome, and even starting to apply it to DNA amplified from single cells”. Professor Christos Proukakis (Professor of Neurology and Neurogenetics, Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology)

Links

• Smolka et al. Detection of mosaic and population-level structural variants with Sniffles2. Nature Biotechnology. Available online 2nd January 2024.
• Professor Christos Proukakis' academic profile

Image

Professor Proukakis with Dr Sedlazeck after reviewing the final version of Sniffles2 over oysters near London Bridge.