Summary
In the last decade, ancient DNA studies have increased their throughput from single samples to thousands of genomes published every year, giving us unprecedented data about human genetic history. However, tools and methods that efficiently use this wealth of data are sorely lacking, especially because DNA extracted from fossils is often scarce and contaminated. In this project, I develop population genetic theory and bioinformatic methods that use ancient DNA to refine estimates of when and where archaic and modern humans interbred, to characterize the historical, biological and functional consequences of this gene flow, and to learn about the differences between modern humans, Neandertals, and Denisovans.
The first aim of this project is to develop a robust and general genotype-likelihood approach for local ancestry inference that allows efficient use of contaminated, low-coverage data, and to establish approximate haplotype-based methods for inferring introgression tracts.
The second aim of the project is to develop the necessary population genetic theory and statistical methods to translate the inferred haplotypes into biological insights. The proposed theoretical, numerical and simulation-based approaches will link the inferred introgression patterns with the underlying population genetic processes.
The final aim is to apply these novel tools to study where and when gene flow between Neandertals, Denisovans, and modern humans occurred. I also aim to identify introgressed haplotypes that are a target of natural selection and to quantify the relative importance of positive, negative, and balancing selection on Neandertal and Denisovan gene flow.
As a result, this work will expand the tool set available for the analysis of ancient DNA, reveal the precise history of the interactions of Neandertals and modern humans, and provide answers to the key question of what genetic factors contributed to the survival of our species, while all other hominins went extinct.
The first aim of this project is to develop a robust and general genotype-likelihood approach for local ancestry inference that allows efficient use of contaminated, low-coverage data, and to establish approximate haplotype-based methods for inferring introgression tracts.
The second aim of the project is to develop the necessary population genetic theory and statistical methods to translate the inferred haplotypes into biological insights. The proposed theoretical, numerical and simulation-based approaches will link the inferred introgression patterns with the underlying population genetic processes.
The final aim is to apply these novel tools to study where and when gene flow between Neandertals, Denisovans, and modern humans occurred. I also aim to identify introgressed haplotypes that are a target of natural selection and to quantify the relative importance of positive, negative, and balancing selection on Neandertal and Denisovan gene flow.
As a result, this work will expand the tool set available for the analysis of ancient DNA, reveal the precise history of the interactions of Neandertals and modern humans, and provide answers to the key question of what genetic factors contributed to the survival of our species, while all other hominins went extinct.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101042421 |
| Start date: | 01-05-2022 |
| End date: | 30-04-2027 |
| Total budget - Public funding: | 1 498 750,00 Euro - 1 498 750,00 Euro |
Cordis data
Original description
In the last decade, ancient DNA studies have increased their throughput from single samples to thousands of genomes published every year, giving us unprecedented data about human genetic history. However, tools and methods that efficiently use this wealth of data are sorely lacking, especially because DNA extracted from fossils is often scarce and contaminated. In this project, I develop population genetic theory and bioinformatic methods that use ancient DNA to refine estimates of when and where archaic and modern humans interbred, to characterize the historical, biological and functional consequences of this gene flow, and to learn about the differences between modern humans, Neandertals, and Denisovans.The first aim of this project is to develop a robust and general genotype-likelihood approach for local ancestry inference that allows efficient use of contaminated, low-coverage data, and to establish approximate haplotype-based methods for inferring introgression tracts.
The second aim of the project is to develop the necessary population genetic theory and statistical methods to translate the inferred haplotypes into biological insights. The proposed theoretical, numerical and simulation-based approaches will link the inferred introgression patterns with the underlying population genetic processes.
The final aim is to apply these novel tools to study where and when gene flow between Neandertals, Denisovans, and modern humans occurred. I also aim to identify introgressed haplotypes that are a target of natural selection and to quantify the relative importance of positive, negative, and balancing selection on Neandertal and Denisovan gene flow.
As a result, this work will expand the tool set available for the analysis of ancient DNA, reveal the precise history of the interactions of Neandertals and modern humans, and provide answers to the key question of what genetic factors contributed to the survival of our species, while all other hominins went extinct.
Status
SIGNEDCall topic
ERC-2021-STGUpdate Date
09-02-2023
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