EARLY HEARING DETECTION AND INTERVENTION VIRTUAL CONFERENCE
MARCH 2-5, 2021
(Virtually the same conference, without elevators, airplane tickets, or hotel room keys)
5/24/2021 | 2:00 PM - 3:30 PM | Beyond presence-absence: Using environmental DNA to detect population genetic structure of an invasive species with nuclear markers | Virtual Platform
Beyond presence-absence: Using environmental DNA to detect population genetic structure of an invasive species with nuclear markers
Environmental DNA (eDNA) has been established as a noninvasive and efficient approach to sample genetic material from aquatic environments. Although most commonly used to determine species presence and measure biodiversity, eDNA may also hold great potential to uncover population genetic information from water samples. In this study, we sequenced a panel of multiallelic microsatellite markers from eDNA and tissue samples to characterize intraspecific diversity of the round goby (Neogobius melanostomus) at 15 locations across their invaded range. We tested the similarity between eDNA-based and individual genotype-based estimates of allele frequencies and demonstrate a novel approach to estimate genetic diversity and differentiation from eDNA samples. eDNA approaches detected alleles at similar frequencies to genotyped tissues, with correlations of up to r = 0.89 between the relative frequencies of eDNA sequences and the relative frequencies of alleles in sampled individuals. Genetic variability within and between populations was also detected from eDNA in patterns that were consistent with individual tissue-based estimates of genetic diversity and differentiation. Our study demonstrates the potential for eDNA-based population genetics to characterize key population parameters required to effectively monitor, manage, and sustain aquatic species.
- Monitoring
- Genomics
- Conservation
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Presenters/Authors
Kara Andres
(), Cornell University, kja68@cornell.edu;
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David Lodge
(), Cornell University, dml356@cornell.edu;
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Jose Andrés
(), Cornell University, jaa53@cornell.edu;
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