A large scale temporal and spatial environmental DNA biodiversity survey of marine vertebrates in Brazil following the Fundão tailings dam failure.

Seawater contains a wealth of genetic information, representing the biodiversity of numerous species residing within a particular marine habitat. Environmental DNA (eDNA) metabarcoding offers a cost effective, non-destructive method for large scale monitoring of environments, as diverse taxonomic groups are detected using metabarcoding assays. A large-scale eDNA monitoring program of marine vertebrates was conducted across three sampling seasons (Spring 2018, Autumn 2019; Spring 2019) in coastal waters of Brazil. The program was designed to investigate eDNA as a testing method for long term monitoring of marine vertebrates following the Fundão tailings dam failure in November 2015. While no baseline samples were available prior to the dam failure there is still value in profiling the taxa that use the impacted area and the trajectory of recovery. A total of 40 sites were sampled around the mouths of eight river systems, covering approximately 500 km of coastline. Metabarcoding assays targeting the mitochondrial genes 16S rRNA and COI were used to detect fish, marine mammals and elasmobranchs. We detected temporal differences between seasons and spatial differences between rivers/estuaries sampled. Overall, the largest eDNA survey in Brazil to date revealed 69 families from Class Actinopterygii (fish), 15 species from Class Chondrichthyes (sharks and rays), 4 species of marine and estuarine mammals and 23 species of conservation significance including 2 species of endangered dolphin. Our large-scale study reinforces the value eDNA metabarcoding can bring when monitoring the biodiversity of coastal environments and demonstrates the importance of collection of time-stamped environmental samples to better understand the impacts of anthropogenic activities.

eDNAFlow, an automated, reproducible and scalable workflow for analysis of environmental DNA sequences exploiting Nextflow and Singularity.

Metabarcoding of environmental DNA (eDNA) when coupled with high throughput sequencing is revolutionising the way biodiversity can be monitored across a wide range of applications. However, the large number of tools deployed in downstream bioinformatic analyses often places a challenge in configuration and maintenance of a workflow, and consequently limits the research reproducibility. Furthermore, scalability needs to be considered to handle the growing amount of data due to increase in sequence output and the scale of project. Here, we describe eDNAFlow, a fully automated workflow that employs a number of state-of-the-art applications to process eDNA data from raw sequences (single-end or paired-end) to generation of curated and noncurated zero-radius operational taxonomic units (ZOTUs) and their abundance tables. This pipeline is based on Nextflow and Singularity which enable a scalable, portable and reproducible workflow using software containers on a local computer, clouds and high-performance computing (HPC) clusters. Finally, we present an in-house Python script to assign taxonomy to ZOTUs based on user specified thresholds for assigning lowest common ancestor (LCA). We demonstrate the utility and efficiency of the pipeline using an example of a published coral diversity biomonitoring study. Our results were congruent with the aforementioned study. The scalability of the pipeline is also demonstrated through analysis of a large data set containing 154 samples. To our knowledge, this is the first automated bioinformatic pipeline for eDNA analysis using two powerful tools: Nextflow and Singularity. This pipeline addresses two major challenges in the analysis of eDNA data; scalability and reproducibility.