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The volcano rabbit  Romerolagus diazi  is an endemic neotropical species restricted to the central part of the Trans-Mexican Volcanic Belt and considered ‘endangered’ by the International Union for Conservation of Nature Red List of Threatened Species. This study formally tested whether complete mitochondrial genomes of  R. diazi  can be assembled from non-enriched metagenomic libraries generated from eDNA (field droppings) using Illumina 300 bp pair-end reads. Using a direct assembly strategy, the mitogenome of  R. diazi  was assembled and circularised using the pipeline GetOrganelle with a coverage of 18.5× from one eDNA sample. A second strategy in which reads were first mapped to a reference mitochondrial genome and then assembled using the software SPAdes retrieved a second nearly complete mitogenome (2.7×) of  R. diazi  from a second eDNA sample. Complete or nearly complete mitochondrial genomes were not retrieved from two other eDNA samples. The organisation of the complete or nearly complete mitochondrial genomes recovered from eDNA samples is identical to that already described for the studied species. A phylomitogenomic analysis based on all protein coding genes (PCGs) demonstrated that the mitochondrial genomes assembled from eDNA can and do reliably identify the sequenced samples as belonging to  R. diazi  and distinguished the same samples from closely and distantly related cofamilial species. This study demonstrates the feasibility of retrieving fully accurate whole and nearly complete mitochondrial chromosomes of host species from eDNA without enrichment strategies and using straightforward bioinformatics pipelines. This new genomic resource developed for  R. diazi  represents a new tool to boost conservation strategies (bioprospecting and/or biomonitoring) and improve our understanding of the evolutionary history of this endemic and endangered species.

journal of natural history

Whole and nearly complete mitochondrial genomes of an endemic and endangered neotropical rabbit ( Romerolagus diazi ) assembled using non-invasive eDNA metagenomics (field droppings)