Summary
Dramatic biodiversity declines are driving Earth into a Sixth Mass Extinction. Drastic conservation plans such as genetic rescue have been proposed to mitigate the loss of genetic diversity, by introducing variation through admixture with closely related populations. However, the influx of new variation can also lead to an increase in genetic load, which can further compromise the survival of species. Since current studies of genetic rescue are based on few regions of the genome and lack a population genetics model, assessing the impact of these initiatives on the levels of genetic diversity and genetic load remains elusive. I propose to tackle this by studying the natural populations of European gray wolves in a temporal and spatial model, as their recent demographic history (strong bottleneck followed by a recovery in last decades) renders them an ideal case for exploring the dynamics of genetic rescue. In particular, I propose to leverage on an unprecedented dataset including >1,000 wolves genomes sampled across Eurasia at multiple time points (before and after population decline and the subsequent recovery) to generate the most comprehensive catalog of genomic diversity in European wolves to date. Taking advantage of recent developments in population genomics, computational biology, palaeogenomic sequencing and evolutionary modeling, I will reconstruct their recent demographic history, migrations patterns and adaptive potential, and determine the demographic parameters that predict a successful genetic rescue. This predictive modeling tool will be capable of guiding conservation management in wolves and applicable to other endangered populations. The combination of my host’s extensive experience in canid evolution, statistical methods and modeling, together with my background on population genomics ensures the successful implementation of this action and will enhance my set of essential skills on genomics methods for conservation.
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| Web resources: | https://cordis.europa.eu/project/id/101107083 |
| Start date: | 01-09-2024 |
| End date: | 31-08-2026 |
| Total budget - Public funding: | - 230 774,00 Euro |
Cordis data
Original description
Dramatic biodiversity declines are driving Earth into a Sixth Mass Extinction. Drastic conservation plans such as genetic rescue have been proposed to mitigate the loss of genetic diversity, by introducing variation through admixture with closely related populations. However, the influx of new variation can also lead to an increase in genetic load, which can further compromise the survival of species. Since current studies of genetic rescue are based on few regions of the genome and lack a population genetics model, assessing the impact of these initiatives on the levels of genetic diversity and genetic load remains elusive. I propose to tackle this by studying the natural populations of European gray wolves in a temporal and spatial model, as their recent demographic history (strong bottleneck followed by a recovery in last decades) renders them an ideal case for exploring the dynamics of genetic rescue. In particular, I propose to leverage on an unprecedented dataset including >1,000 wolves genomes sampled across Eurasia at multiple time points (before and after population decline and the subsequent recovery) to generate the most comprehensive catalog of genomic diversity in European wolves to date. Taking advantage of recent developments in population genomics, computational biology, palaeogenomic sequencing and evolutionary modeling, I will reconstruct their recent demographic history, migrations patterns and adaptive potential, and determine the demographic parameters that predict a successful genetic rescue. This predictive modeling tool will be capable of guiding conservation management in wolves and applicable to other endangered populations. The combination of my host’s extensive experience in canid evolution, statistical methods and modeling, together with my background on population genomics ensures the successful implementation of this action and will enhance my set of essential skills on genomics methods for conservation.Status
SIGNEDCall topic
HORIZON-MSCA-2022-PF-01-01Update Date
12-03-2024
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