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Investigating the recent evolution of human life history

Supervisor: Joachim Burger

Co-Supervisor: Yoan Diekmann


Scientific Background:
The life history (or cycle) of an organism is defined by its patterns of development, growth, maturation, reproduction, survival, and lifespan (D Fabian 2012). Many facets of the question what shaped us humans today can be phrased within the framework of life history theory, including for example health and disease, longevity, resilience, stature, and behaviour, as life history traits determine the major components of fitness—survival and reproduction—and are therefore key to understand adaptation. Biological and anthropological studies on the life history of humans are currently limited to living populations, as the informational content of human skeletal remains is limited in terms of relevant traits. Comparative studies therefore often use modern hunter-gatherers as proxies for ancient populations, limiting evolutionary inference and potentially even biassing conclusions.


PhD project: Investigating the recent evolution of human life history
Here, we propose to leverage and combine two transformative scientific developments to directly study life history in past human populations of the last 50,000 years: on one hand Palaeogenetics, that has deeply impacted archaeology and population genetics by opening a direct window into the genomic past, and on the other molecular Epigenetics, whose role in fundamental processes such as cellular differentiation and aging has already led to commercial applications for example in cancer medicine. Two recent breakthroughs provide the essential computational tools: first, prediction of methylation patterns from ancient DNA sequencing data (Hanghøj et al. 2019), and second, prediction of life history traits such as maximum lifespan, gestational time, and age at sexual maturity from methylation patterns (Li et al. 2021; Fig 1).
Our objectives are:
1) Setting up, validating and optimising the computational pipeline for predicting life history traits from ancient genomes.
2) Curate and apply the pipeline to an available dataset of ancient high coverage genomes from individuals with different subsistence strategies, cultures, from different periods and regions – representing the complete human genetic diversity after the “out of Africa” some 70.000 years ago.
3) Statistical analysis and evolutionary interpretation of results, i.e. what are the patterns, trends and discontinuities, link these to mechanisms such as trade-offs and constraints, demography and ecological drivers.
4) Identify regulatory networks underpinning evolutionary changes, for example by screening for selection on candidate genes Analogously to Palaeogenetics, which has revolutionised the study of human prehistory by opening up new aspects of it to direct observation, our proposal aims to establish the toolset for a new Palaeoanthropology, allowing to observe rather than infer the recent evolution of our species.


Publications relevant to this project:
D Fabian, T Flatt. 2012. “Life History Evolution.” Nature Education Knowledge 3: 24. Hanghøj, Kristian, Gabriel Renaud, Anders Albrechtsen, and Ludovic Orlando. 2019. “DamMet: Ancient Methylome Mapping Accounting for Errors, True Variants, and Post-Mortem DNA Damage.” GigaScience 8 (4). doi:10.1093/gigascience/giz025.
Li, C Z, A Haghani, T R Robeck, D Villar, A T Lu, J Zhang, C G Faulkes, et al. 2021. “Epigenetic Predictors of Maximum Lifespan and Other Life History Traits in Mammals.” bioRxiv. doi:10.1101/2021.05.16.444078.