Quantitative Human Paleogenetics: What can Ancient DNA Tell us About Complex Trait Evolution?
Publikation: Bidrag til tidsskrift › Review › Forskning › fagfællebedømt
Dokumenter
- Quantitative Human Paleogenetics
Forlagets udgivne version, 1,18 MB, PDF-dokument
Genetic association data from national biobanks and large-scale association studies have provided new prospects for understanding the genetic evolution of complex traits and diseases in humans. In turn, genomes from ancient human archaeological remains are now easier than ever to obtain, and provide a direct window into changes in frequencies of trait-associated alleles in the past. This has generated a new wave of studies aiming to analyse the genetic component of traits in historic and prehistoric times using ancient DNA, and to determine whether any such traits were subject to natural selection. In humans, however, issues about the portability and robustness of complex trait inference across different populations are particularly concerning when predictions are extended to individuals that died thousands of years ago, and for which little, if any, phenotypic validation is possible. In this review, we discuss the advantages of incorporating ancient genomes into studies of trait-associated variants, the need for models that can better accommodate ancient genomes into quantitative genetic frameworks, and the existing limits to inferences about complex trait evolution, particularly with respect to past populations.
Originalsprog | Engelsk |
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Artikelnummer | 703541 |
Tidsskrift | Frontiers in Genetics |
Vol/bind | 12 |
Antal sider | 11 |
ISSN | 1664-8021 |
DOI | |
Status | Udgivet - 2021 |
Bibliografisk note
Funding Information:
We thank the members of the Racimo group for their helpful advice and discussions, and thank the reviewers and editor for their constructive feedback. Figure 1 was created with Biorender.com. Funding. EI-P was supported by the Lundbeck Foundation (grant R302-2018-2155) and the Novo Nordisk Foundation (grant NNF18SA0035006). FR and RM were supported by a Villum Fonden Young Investigator award to FR (project no. 00025300). Additionally, FR was supported by the COREX ERC Synergy grant (ID 951385). MD was supported by the European Union through the Horizon 2020 Research and Innovation Programme under grant no. 810645 and the European Regional Development Fund Project No. MOBEC008.
Publisher Copyright:
© Copyright © 2021 Irving-Pease, Muktupavela, Dannemann and Racimo.
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