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Evolution and function of adaptive immunogenetic diversity in humans


Pierini,  Federica
IMPRS for Evolutionary Biology, Max Planck Institute for Evolutionary Biology, Max Planck Society;
Emmy Noether Research Group Evolutionary Immunogenomics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Pierini, F. (2019). Evolution and function of adaptive immunogenetic diversity in humans. PhD Thesis, Christian-Albrechts-Universtität, Kiel.

Cite as: http://hdl.handle.net/21.11116/0000-0003-C9A7-E
The highly polymorphic HLA genes play a key role in adaptive immunity. The dynamic action of pathogen-mediated selection is proposed to be a major driver of HLA diversity, which involves parallel mechanisms acting at different time scales. Divergent HLA allelic lineages are proposed to be maintained over long evolutionary time in natural populations to facilitate immunity against the constant simultaneous barrage by many different pathogens. In contrast, specific HLA variants can be selected on a shorter time scale by the transient selection pressure imposed by specific pathogen. While the molecular signatures of continuous and directional selection on HLA genes might be intuitive and potentially detectable in natural populations, to identify signatures resulting from transient and fluctuating selection might be challenging. Nevertheless, both modes of past pathogen selection are suspected to have functional consequences detectable in present-day human populations. Here, we have established signatures of historical and potentially still ongoing selection for functional divergence in HLA allele pools, supporting the notion that pathogen selection has led to the persistence of divergent HLA allelic lineages. The further investigation of HLA allelic divergence in biomedical datasets revealed implications of this mechanism of pathogen-mediated selection on HIV disease progression as well as on cancer immunotherapy response. In order to study transient selection through time, reliable genotyping of the HLA genes in ancient samples is crucial. We have therefore established a semi-automated analysis pipeline for NGS-based genotyping of HLA genes from aDNA samples. The approach was applied successfully to a dataset of medieval Europeans, linking HLA variability with susceptibility to leprosy, and to a dataset of ancient and modern Mesoamerican human samples, suggesting its applicability to explore HLA gene variation through time.