Population genomics of the ecological model species Daphnia magna

Research output: Contribution to conference (unpublished)Posterpeer-review

Abstract

Advances in high-throughput sequencing technology have markedly improved our understanding of global patterns of genetic variation in model species. The application of this technology to dense geographic samples of ecological model species has the potential to reveal the genetic structure of closely spaced populations and to identify the genetic basis of phenotypes evolved in response to environmental selection. However, identifying the genetic underpinning of adaptation and assigning causes of natural selection is challenging because natural populations are confronted with multiple selection pressures resulting in a mosaic of environmental stressors at the landscape level.

Here, we investigate adaptation to a multifarious environment of 19 natural populations of the model organism in ecological, physiological, and ecotoxicological research, the aquatic crustacean Daphnia magna. These populations are distributed along three orthogonal gradients of selection, known to induce evolutionary responses in D. magna - predation, parasitism and land-use. D. magna has a cyclical parthenogenetic life cycle that provides the advantages of scoring life history traits of the same genotype under different experimental conditions. Taking advantage of this property, we measure life history traits under non-stressful conditions and after exposure to predation, one of the key stressors in the landscape. We characterize the genome-wide polymorphism and structural variation of 191 individuals from the 19 populations and perform genome-wide association analyses. Our results show that whereas neutral genetic variation mirrors geography, lineage-specific genes associated with fitness traits mirror environmental gradients of selection. We identify genes underlying evolutionary differences in life history traits among populations, as well as plasticity genes underlying response to predation. Our study identifies repeatable patterns of local adaptation in a geographic mosaic of environmental stressors fuelled by standing genetic variation
Original languageEnglish
Publication statusUnpublished - 2017
EventGordon conference Ecological & Evolutionary Genomics - University of New England in Biddeford, Maine, Biddeford, United States
Duration: 16 Jul 201721 Jul 2017
https://www.grc.org/ecological-and-evolutionary-genomics-conference/2017/

Conference

ConferenceGordon conference Ecological & Evolutionary Genomics
Country/TerritoryUnited States
CityBiddeford
Period16/07/1721/07/17
Internet address

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