Genomic determinants of species-specific ageing phenotypes
Supervision
Dario Riccardo Valenzano
FLI, 1st Supervisor
Emma Teeling
UCD, 2nd Supervisor
Objectives
This project investigates the genomic determinants of ageing in African killifishes, which display striking natural variation in lifespan. By integrating population genetics, comparative genomics, and evolutionary modelling, the project aims to identify genetic variants and regulatory networks linked to ageing, uncovering how natural selection and genetic drift shape ageing traits with relevance to human health.
Methodology
The project combines population genetics, comparative genomics, and transcriptomics in African killifishes. The doctoral candidate will analyze genomic and transcriptomic datasets, perform evolutionary modelling to assess the role of natural selection and drift, and integrate bioinformatics with functional genomic data. Field-collected and laboratory-maintained populations will provide complementary material for comparative and mechanistic analyses.
Required Skills
Applicants should have a strong background in evolutionary biology, genetics, or bioinformatics, with enthusiasm for interdisciplinary research. Experience in genomics, statistics, or computational biology is advantageous but not mandatory. The candidate should be motivated to combine laboratory and computational approaches and be open to participating in fieldwork in Zimbabwe, studying wild killifish populations.
Expected results
The project will deliver an atlas of ageing-associated genomic regions in African killifish, new statistical genetic tools to detect causal variants in wild populations, and insights into the evolutionary dynamics of ageing. Additional outcomes include experimental targets for interventions, contributions to developing a molecular field laboratory in Zimbabwe, and advancing ageing research broadly.
Planned Secondment
UCD (Teeling) in year 2 (1 month) to complement training on genomics of ageing using bat as a model organism.
CNRS (Walczak) in year 2 (2 weeks) to receive training on mathematical modelling on collaborative killifish data.
UPF (Juan-Mateu) in year 3 (2 weeks) to complement research on transcriptomics of ageing-related disease.
Enrolment in doctoral program
The student will be enorolled at the Friedrich Schiller University Jena
References
Cui R, Medeiros T, Willemsen D, Iasi LNM, Collier GE, Graef M, Reichard M, Valenzano DR. (2019). Relaxed Selection Limits Lifespan by Increasing Mutation Load. Cell, Jul 11;178:1-15 (cover article).
Cui R, Willemsen D, Valenzano DR. (2020). Nothobranchius furzeri (African Turquoise Killifish). Trends In Genetics; https://doi.org/10.1016/j.tig.2020.01.012.
Bradshaw WJ, Valenzano DR. (2020). Extreme genomic volatility characterises the evolution of the immunoglobulin heavy chain locus in cyprinodontiform fishes. Proceedings of the Royal Society B, 287(1927) https://doi.org/10.1098/rspb.2020.0489.
Cui R, Tyers AM, Malubhoy ZJ, Wisotsky S, Valdesalici S, Henriette E, Kosakovsky Pond SL, Valenzano DR. (2021). Ancestral transoceanic colonization and recent population reduction in a non-annual killifish from the Seychelles archipelago. Molecular Ecology 30 (14); https://doi.org/10.1111/mec.15982.
Willemsen D, Cui R, Reichard M, Valenzano DR. (2020). Intra-species differences in population size shape life history and genome evolution. eLife 2020;9:e55794; https://doi.org/10.7554/eLife.55794.
Bradshaw WJ, Poeschla M, Placzek A, Kean S, Valenzano DR. (2022). Extensive age-dependent loss of antibody diversity in naturally short-lived turquoise killifish. eLife 2022;11:e65117 https://elifesciences.org/articles/65117.
Bagic M and Valenzano DR. (2022). Population size shapes the evolution of lifespan. bioRxiv 2022.12.17.520867; doi: https://doi.org/10.1101/2022.12.17.520867.
Bagic M, Šajina A, Bradshaw WJ, Valenzano DR. (2024). AEGIS: individual-based modeling of life history evolution. bioRxiv 2024.11.26.625408; doi: https://doi.org/10.1101/2024.11.26.625408.