Ms Eldridge Wisely1
1Genetics Graduate Interdisciplinary Program, University of Arizona, Tucson, United States
Biography:
Eldridge Wisely anticipates graduating with a PhD in Genetics from the University of Arizona in December of 2024. She is interested in non-invasive genetic monitoring of threatened and endangered species, and drivers of community structure and biodiversity in threatened ecosystems. She has studied genomic diversity of jaguars, diets of juvenile scalloped hammerheads, and marine biodiversity in the Galápagos archipelago. She enjoys incorporating her love of scuba diving with her work. Eldridge is currently looking for a post-doctoral position in Australia or New Zealand. She would be happy to discuss any of these topics over the course of this conference.
Abstract:
Taxonomic assignment of environmental DNA sequences is often a problematic undertaking, particularly when working in areas of high biodiversity or environments underrepresented in genetic databases. There are several current methods for taxonomic assignment which can be classified as global or local database approaches. Common taxonomic assignment workflows may include downgrading of taxonomic level by percent sequence similarity cutoffs, or manual removal of sequences assigned to taxa that the researcher deems spurious. In order to avoid these types of subjective filtering steps which negatively impact reproducibility of analyses, I designed an R program “Reconciling Global Assignments with Taxa checklists to curate Taxonomic Assignment” (REGATTA) which downloads taxonomic checklists from the Ocean Biodiversity and Information System (OBIS) and the Global Biodiversity Information Facility (GBIF) to acquire a list of taxa with occurrence records in the study area. These biodiversity databases curate records from museum collections, scientific literature, eDNA datasets, and citizen science programs. By including both OBIS and GBIF data, REGATTA can create local taxa checklists for marine, terrestrial, or aquatic systems anywhere in the world. This local taxa checklist can then be fed into software to build a local database for taxonomic assignment or to guide primer choices, and a different module of REGATTA can be used to reconcile taxonomic assignment results with the local checklist using a lowest common ancestor (LCA) algorithm. REGATTA outperformed local database assignments of marine fish and crustaceans and terrestrial mammals with a greater number of local taxa assigned while improving workflow reproducibility, transparency, and efficiency.