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Comparing accuracy and biases of DNA metabarcoding, hybridization capture, and metagenomic sequencing for quantifying herbivore diets

Eriksson, Charlotte1; Shipley, Lisa2; Clark, Darren3; Levi, Taal1

Published Jul 10, 2026 on Dryad. https://doi.org/10.5061/dryad.np5hqc06j

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Abstract

DNA metabarcoding using relative read abundance (RRA) is commonly applied to estimate herbivore diet composition, yet its quantitative accuracy remains uncertain. We assessed taxonomic resolution and quantitative performance of RRA from DNA metabarcoding compared to metagenomic sequencing and hybridization capture, using deer scats from feeding trials and recreated diet samples using plant tissues. All methods recovered plant composition in recreated diets (R² = 0.59-0.82), indicating accurate scaling with biomass in the absence of digestion, with only minor bias from amplicon length in DNA metabarcoding. In contrast, RRA from scat samples performed poorly (R² < 0.01) across all methods largely due to differential plant digestibility. Correcting for digestibility, measured with acid detergent lignin and acid-insoluble ash, was strongly supported in mixed-effects models and improved prediction of dietary composition, although species-level variation remained. For metagenomic sequencing and hybridization capture, we also evaluated Relative Genome Coverage (RGC), a novel relative abundance metric quantifying the proportion of each plant’s chloroplast genome covered by mapped reads, normalized for genome length. RGC further improved correlations in recreated diets (R² = 0.82-0.84) and, with hybridization capture, largely overcame digestibility-related biases in scat samples (R² = 0.57) without correction. When such corrections are infeasible, hybridization capture with uncorrected RGC may achieve higher quantitative accuracy in scat samples. Our results provide practical guidance for improving molecular herbivore diet analysis and highlight the importance of accounting for digestion-related biases.