| Project Detail |
A lifeline for endangered species
Dramatic biodiversity declines are pushing our planet into a sixth mass extinction, jeopardising countless species. Proposed solutions, like genetic rescue, offer hope by introducing variation through interbreeding closely related populations. With the support of the Marie Sklodowska-Curie Actions programme, the ResQ project now aims to harness advanced genomics and computational techniques to guide successful genetic rescue strategies, with European grey wolves as their crucial case study. Their unique history, with a significant population bottleneck followed by a recent recovery, makes them a perfect model for genetic rescue dynamics. With over 1 000 wolf genomes collected across Eurasia, spanning pre-decline, decline and recovery periods, ResQ assembles an unparalleled resource.
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. |
