Andres KA, Sethi SA, Lodge D, Andres J. (2021) Nuclear eDNA estimates population allele frequencies and abundance in experimental mesocosms and field samples. Molecular Ecology, 30:658-697.
Advances in environmental DNA (eDNA) methodologies have led to improvements in the ability to detect species and communities in aquatic environments, yet the majority of studies emphasize biological diversity at the species level by targeting variable sites within the mitochondrial genome. Here, we demonstrate that eDNA approaches also have the capacity to detect intraspecific diversity in the nuclear genome, allowing for assessments of population-level genetic diversity and estimates of the number of genetic contributors in a sample. Using a panel of microsatellite loci, we evaluated intraspecific genetic diversity in the round goby (Neogobius melanostomus) using eDNA samples from experimental mesocosms. First, we tested the similarity between eDNA and individual tissue-based estimates of allele frequencies. Subsequently, we used a likelihood-based DNA mixture framework to estimate the number of unique genetic contributors in mesocosm eDNA samples and in simulated mixtures of alleles. Allele frequencies from eDNA accurately reflected allele frequencies from genotyped round goby tissue samples, indicating nuclear markers can be reliably amplified from water samples under controlled conditions. DNA mixture analyses were able to estimate the number of genetic contributors from eDNA samples and simulated mixtures of DNA from up to 58 individuals, with the degree of positive or negative bias dependent on the filtering scheme of low-frequency alleles. This study is the first to document the application of eDNA and multiple amplicon-based methods to obtain intraspecific nuclear genetic information and estimate the absolute abundance of a species in mesocosms. With proper validation, this approach has the potential to advance non-invasive survey methods to characterize populations and broadens the application of eDNA methodologies to inform population-level management objectives.