ORCID Profile
0000-0001-6589-6635
Current Organisations
ETH Zurich
,
Wellcome Sanger Institute
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Publisher: Cold Spring Harbor Laboratory
Date: 15-09-2022
DOI: 10.1101/2022.09.13.507768
Abstract: Many species are facing unprecedented population size declines and deterioration of their environment. This exposes species to genomic erosion, which we define here as the damage inflicted to a species’ genome or gene pool due to a loss of genetic ersity, an increase in expressed genetic load, maladaptation, and/or genetic introgression. The International Union for Conservation of Nature (IUCN) bases its extinction risk assessments on direct threats to population size and habitat. However, it does not assess the long-term impacts of genomic erosion, and hence, it is likely to underestimate the extinction risk of many species. High-quality whole genome sequence data that is currently being generated could help improve extinction risk assessments. Genomic data contains information about a species’ past demography, its genome-wide genetic ersity, the incidence of genetic introgression, as well as the genetic load of deleterious mutations. Computer modelling of these data enables forecasting of population trajectories under different management scenarios. In this Perspective, we discuss the threats posed by genomic erosion. Using evolutionary genomic simulations, we argue that whole genome sequence data provides critical information for assessing the extinction risk and recovery potential of species. Genomics-informed assessments of the extinction risk complement the IUCN Red List, and such genomics-informed conservation is invaluable in guiding species recovery programs in the UN’s Decade on Ecosystem Restoration and beyond.
Publisher: Springer Science and Business Media LLC
Date: 08-02-2022
DOI: 10.1038/S41576-022-00448-X
Abstract: Genetic variation, which is generated by mutation, recombination and gene flow, can reduce the mean fitness of a population, both now and in the future. This 'genetic load' has been estimated in a wide range of animal taxa using various approaches. Advances in genome sequencing and computational techniques now enable us to estimate the genetic load in populations and in iduals without direct fitness estimates. Here, we review the classic and contemporary literature of genetic load. We describe approaches to quantify the genetic load in whole-genome sequence data based on evolutionary conservation and annotations. We show that splitting the load into its two components - the realized load (or expressed load) and the masked load (or inbreeding load) - can improve our understanding of the population genetics of deleterious mutations.
Location: France
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: No location found
No related grants have been discovered for Chiara Bortoluzzi.