Population genetic data is often essential to inform conservation management. Understanding the distribution of genetic variants within and between populations can reveal novel insights into genetic connectivity and evolutionary processes. However, obtaining such data using invasive approaches such as tissue sampling may negatively affect the very species we are seeking to protect. Thus, interest in using non-invasive environmental DNA (eDNA) techniques for identifying genetic variation within target species populations has grown. Along with this interest comes the desire to expand the amount of population genetic information that can be obtained from eDNA to increasingly large fragments of the genome, such as entire mitogenomes. Here, we introduce an eDNA hybridisation capture approach to sequencing complete mitochondrial genomes of New Zealand fur seals (Arctocephalus forsteri) (Māori: kekeno) from marine water samples. We show that our approach can recover up to 99% of the fur seal mitogenome. Furthermore, we present a pipeline to extract haplotype diversity from such eDNA population genetic data. Haplotypic variation identified using this approach matches previously identified patterns of intraspecific genetic variation from fur seal tissue samples, suggesting that eDNA methods can accurately identify mitochondrial variation. Our study demonstrates that whole mitogenomes can be recovered using hybridisation capture enrichment of eDNA and indicates that eDNA may be a promising tool for population genetics. Within this context, we discuss some of the key challenges that must be overcome before the promise of eDNA can be fully realized.

The measurement of biodiversity is an integral aspect of life science research. With the establishment of second- and third-generation sequencing technologies, an increasing amount of metabarcoding data is being generated as we seek to describe the extent and patterns of biodiversity in multiple contexts. The reliability and accuracy of taxonomically assigning metabarcoding sequencing data has been shown to be critically influenced by the quality and completeness of reference databases. Custom, curated, eukaryotic reference databases, however, are scarce, as are the software programs for generating them. Here, we present CRABS (Creating Reference databases for Amplicon-Based Sequencing), a software package to create custom reference databases for metabarcoding studies. CRABS includes tools to download sequences from multiple online repositories (i.e., NCBI, BOLD, EMBL, MitoFish), retrieve amplicon regions through in silico PCR analysis and pairwise global alignments, curate the database through multiple filtering parameters (e.g., dereplication, sequence length, sequence quality, unresolved taxonomy), export the reference database in multiple formats for the immediate use in taxonomy assignment software, and investigate the reference database through implemented visualizations for diversity, primer efficiency, reference sequence length, and taxonomic resolution. CRABS is a versatile tool for generating curated reference databases of user-specified genetic markers to aid taxonomy assignment from metabarcoding sequencing data. CRABS is available for download as a conda package and via GitHub (https://github.com/gjeunen/reference_database_creator).