Dr Susanne Bornelöv
Susanne's research is focused on using genomics and machine learning techniques to gain insights into genome function and organisation. Currently, she is leading a computational team within the Hannon lab working on fine-mapping how the piRNA pathway, a small RNA-based immune system, recognises and represses transposable elements in animal germ cells. Susanne has recently been awarded an 8-year Wellcome Career Development Award to launch a separate research programme. The goal of this programme is to use data-driven approaches to better understand genome regulation, with a specific focus on the role of hidden features, such as codon usage, in gene regulation.
Susanne has a MSci and a PhD in Bioinformatics from Uppsala University, Sweden. During her PhD, she developed expertise in machine learning methods for genomics data and focused on understanding the role of histone modifications in gene regulation. To gain more experience in genomic methods, she joined Prof Leif Andersson's group at Uppsala University as a postdoc. There, she worked on mapping genes to function in domesticated chickens using high-throughput sequencencing data. Susanne then moved to Cambridge and joined the Cambridge Stem Cell Institute where she spent for years at a position shared between the Bioinformatics team and Prof Michaela Frye's group, focusing primarily on RNA modifications and their impact on translation. When Prof Frye's lab relocated to Germany, Susanne joined Prof Greg Hannon's group at the neighbouring institute to support their efforts to develop markers for early stage breast cancer while continuing to strengthen her own skills in RNA biology and sequencing-based approaches through work on the piRNA pathway.
Senior Research Associate (Sep 2021 - now)
Senior Bioinformatics Analyst (Jan 2020 - Sep 2021)
Cancer Research UK Cambridge Institute, University of Cambridge, UK
Research Associate - Bioinformatician (Nov 2015 - Jan 2020)
Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, UK
Postdoctoral Researcher (Nov 2014 - Oct 2015)
Dept of Medical Biochemistry and Microbiology, Uppsala University, Sweden
PhD Candidate (May 2009 - Oct 2014)
Dept of Cell and Molecular Biology, Uppsala University, Sweden
Research Assistant (Feb 2009 - Apr 2009)
Linnaeus Centre for Bioinformatics, Uppsala University, Sweden
- PhD in Bioinformatics, Uppsala University, Sweden, Oct 2014
- MSc Engineering in Bioinformatics, Uppsala University, Sweden, May 2009
Honours and awards
- Fourth place in the DREAM 2022 challenge "Predicting gene expression using millions of random promoter sequences" (Sep 2022)
- Award for best poster at the EMBO PIWI proteins and piRNAs workshop 2022 (Apr 2022)
- Travel grant to attend the EMBO Codon Usage workshop 2022 (Feb 2022)
- Co-organising the monthly Cambridge AI Club for Biomedicine that was launched in February 2023.
- Reviewer for Bioinformatics, BMC Bioinformatics, Philosophical Transactions of the Royal Society B and other journals.
- International Society for Computational Biology (ISCB), postdoc member.
- van Lopik J#, Alizada A, Trapotsi M-A, Hannon GJ, Bornelöv S#,§, Czech Nicholson B§ (2023) Unistrand piRNA clusters are an evolutionary conserved mechanism to suppress endogenous retroviruses across the Drosophila genus. bioRxiv 2023.02.27.530199.
- Bornelöv S§, Czech B, Hannon GJ§ (2022) An evolutionarily conserved stop codon enrichment at the 5’ ends of mammalian piRNAs. Nature Communications 13:2118.
- Selmi T, Hussain S, Dietmann S, Heiß M, Borland K, Flad S, Carter J-M, Dennison R, Huang Y-L, Kellner S, Bornelöv S§ and Frye M§ (2021) Sequence- and structure-specific cytosine-5 mRNA methylation by NSUN6. Nucleic Acids Research 49:2:1006-1022.
- Bornelöv S#, Selmi T#, Flad S, Dietmann S and Frye M§ (2019) Codon usage optimization in pluripotent embryonic stem cells. Genome Biology 20:1:119.
- Bornelöv S, Seroussi E, Yosefi S, Pendavis K, Burgess SC, Grabherr M, Friedman-Einat M§ and Andersson L§ (2017) Correspondence on Lovell et al.: identification of chicken genes previously assumed to be evolutionarily lost. Genome Biology 18:1:112.