2025/07/04 by Pedro F. P. Brandão‐Dias, Gledis Guri, Megan Shaffer +2 · 1 voice · 1 citation
Chemistry · Environmental Science · #Abundance (ecology) #Biodiversity #Biology #Chemistry #Ecology #Environmental DNA #Environmental DNA in Biodiversity Studies #Environmental science #Gene #Genetics #Haplotype #Microbial Community Ecology and Physiology #Organism #Sample (material)
paper · pdf · doi:10.1101/2025.06.30.662414
published in bioRxiv (Cold Spring Harbor Laboratory) (Cold Spring Harbor Laboratory)
openalex publication_date 2025/07/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
ABSTRACT Environmental DNA (eDNA) metabarcoding provides powerful insights into species presence and community composition, but remains limited in its ability to quantify species abundance or structure. Here, we show that deviation between observed haplotype frequencies within a given sample and the population haplotype frequencies can be used to infer the number of individual contributors to an eDNA sample. We also lay out the theory for how population haplotype frequencies can be approximated from eDNA data alone, enabling broad applicability even in the absence of tissue-based references. We then present an estimator to derive the number of individual contributors to a given eDNA sample and validate its performance using simulations with variable allele frequencies and noise. Our framework demonstrates that differences between expected and observed frequencies carry meaningful biological information in eDNA data. Our results show that the number of contributors can be recovered under a range of conditions, particularly with hypervariable markers and sufficient sampling. This approach complements existing molecular methods and opens a new avenue for inferring abundance from eDNA metabarcoding datasets.