Applicability of DNA barcoding-based analyses on the diet of the gray brocket deer (Subulo gouazoubira) in xeric hillside forests

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Abstract
In this study, we explore the applicability of DNA barcoding, specifically targeting the chloroplast DNA (cpDNA) sequences, particularly the trnL (UAA) intron region, to analyze the diet of gray brocket deer. This approach offers improved taxonomic resolution and the ability to identify species with greater precision compared to traditional methods. The study was conducted in the "Reserva Natural Salus" in Uruguay, covering a range of vegetation types, where gray brocket deer coexist with other exotic ungulates. A local reference database of trnL (UAA) sequences was established, incorporating both GenBank data and sequences obtained from native species in the study area. Fecal samples were collected in summer and winter, and DNA was extracted and amplified for metabarcoding analysis in pooled samples for each season. For each sample 28,229 and 33,588 reads were obtained respectively, which together corresponded to 25 Operational Taxonomic Units (OTUs). The species Rubus ulmifolius and Schinus engleri were the most represented in the diet with 69.6 % of the summer reads, whereas in winter, 68.7 % of the reads corresponded only to Schinus engleri. These findings indicate that gray brocket deer consume species that have higher nutritional value, which may be linked to their capacity to thrive in young and productive ecosystems. This study demonstrates the feasibility of DNA barcoding for dietary analysis in gray brocket deer and provides valuable insights into their food habits in the "Reserva Natural Salus". Further improvements to increase the reference databases of native species and the exploration of additional genetic markers are recommended for enhanced species-level discrimination in dietary analysis studies. This methodology is promising for future research as diet studies have an impact on species management, habitat conservation and biodiversity conservation efforts.

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