Susanne Bornelöv

Computational genomics and gene regulation. Gene regulation is a fundamental aspect of life, in which cells control when and to what extent specific genes are activated to produce a protein. This process is tightly controlled using both transcriptional and posttranscriptional mechanisms. The Bornelöv Group studies these molecular mechanisms using computational methods. Specifically, we are interested in how higher layers of information, such as codon usage, contribute to gene regulation and genome organisation over evolutionary time. To answer this, we combine analysis of omics data, artificial intelligence, and comparative genomics to elucidate the underlying mechanism of novel regulatory mechanisms, including codon optimality-mediated mRNA decay. For example, by analysing ribosome profiling data, we are able to study ribosome occupancy at single-codon levels, and by using AI-based methods, we aim to create an in-silico system to study fundamental principles underlying gene expression and protein production. We are also using fruit flies (Drosophila) as a model system to identify mechanisms that drive the evolution of codon usage bias.

Rafi AM, Nogina D, Penzar D, Lee D, Lee D, Kim N, Kim S, Shin Y, Kwek I-Y, Meshcheryakov G, Lando A, Zinkevich A, Kim B-C, Lee J, Kang T, Vaishnav ED, Yadollahpour P, Random Promoter DREAM Challenge Consortium (72 members including Bornelöv S), Kim S, Albrecht J, Regev A, Gong W, Kulakovskiy IV, Meyer P, de Boer CG (2024) A community effort to optimize sequence-based deep learning models of gene regulation. Nature Biotechnology s41587-024-02414-w https://doi.org/10.1038/s41587-024-02414-w van Lopik J, Alizada A, Trapotsi M-A, Hannon GJ, Bornelöv S§, Czech Nicholson B§ (2023) Unistrand piRNA clusters are an evolutionarily conserved mechanism to suppress endogenous retroviruses across the Drosophila genus. Nature Communications 14:7337 https://doi.org/10.1038/s41467-023-42787-1