Dr. Burçak Otlu on Evaluating topography of mutational signatures using SigProfilerTopography

Dr. Burçak Otlu will give a seminar on “Evaluating topography of mutational signatures using SigProfilerTopography” on 24 May at 12:45. The abstract of the talk and a short bio is shared below.

Burçak Otlu is a computer scientist with several years of experience in computational biology. She has been working as a postdoctoral scholar in UC San Diego, Cellular and Molecular Medicine Department since March 2018. She is working on mutational signatures and topography of somatic mutations across the genome. She is an academic fellow at the Department of Health Informatics at Middle East Technical University. Formerly, she was a visiting scholar in UC San Diego, Computer Science, and Engineering Department between August 2017 and February 2018. She received her Ph.D. from Middle East Technical University, Computer Engineering Department where she focused on developing tools and techniques for assessing the functional relevance of genomic loci. Prior to coming to UC San Diego, she has worked as a teaching assistant in the same department for several years. Previously, she has also worked in the private sector as a software engineer.

Mutations are found on the genomes of all cancerous and normal somatic cells. These mutations were generated by the activities of endogenous and exogenous mutational processes which were operative throughout the cell lineage. Mutational processes imprint characteristic patterns of somatic mutations, termed, mutational signatures. To exemplify, mutational signature associated with tobacco smoking causes C>A mutations prominently on the transcribed strand, whereas mutational signature due to exposure to ultraviolet light results in C>T mutations on the untranscribed strand during DNA transcription. Previous analyses have demonstrated that somatic mutations in cancer are not uniformly distributed across the landscape of the genome. Importantly, mutational signatures imprinted by different mutational processes exhibit distinct topographical properties including to be located on (i) early or late replicating regions, (ii) genic or intergenic regions, (iii) transcribed strand or untranscribed strand of DNA with respect to the transcription process, (iv) leading or lagging strand of DNA in regard to DNA replication. Remarkably, mutational signatures may accumulate somatic mutations preferably at nucleosome occupied loci, chromatin accessible regions, transcription factor binding sites, and histone modification sites. Here, I present SigProfilerTopography, the most advanced tool for evaluating the topography of mutational signatures. SigProfilerTopography allows examining all types of mutational signatures and reveals topographical dependencies related to chromatin accessibility, nucleosome occupancy, histone modifications, transcription factor binding sites, replication timing, transcription strand bias, replication strand bias, and processivity. The tool also allows performing user-defined custom analysis based on custom assays. Having augmented with realistic simulated mutations, SigProfilerTopography assesses the significance of its findings which finally characterizes the mutational signatures and gives insight about their underlying biological mechanisms.