Metabarcoding From Microbes to Mammals: Comprehensive Bioassessment on a Global Scale

Abstract

Global biodiversity loss is unprecedented, and threats to existing biodiversity are growing. Given pervasive global change, a major challenge facing resource managers is a lack of scalable tools to rapidly and consistently measure Earth's biodiversity. Environmental genomic tools provide some hope in the face of this crisis, and DNA metabarcoding, in particular, is a powerful approach for biodiversity assessment at large spatial scales. However, metabarcoding studies are variable in their taxonomic, temporal, or spatial scope, investigating individual species, specific taxonomic groups, or targeted communities at local or regional scales. With the advent of modern, ultra-high throughput sequencing platforms, conducting deep sequencing metabarcoding surveys with multiple DNA markers will enhance the breadth of biodiversity coverage, enabling comprehensive, rapid bioassessment of all the organisms in a sample. Here, we report on a systematic literature review of 1,563 articles published about DNA metabarcoding and summarize how this approach is rapidly revolutionizing global bioassessment efforts. Specifically, we quantify the stakeholders using DNA metabarcoding, the dominant applications of this technology, and the taxonomic groups assessed in these studies. We show that while DNA metabarcoding has reached global coverage, few studies deliver on its promise of near-comprehensive biodiversity assessment. We then outline how DNA metabarcoding can help us move toward real-time, global bioassessment, illustrating how different stakeholders could benefit from DNA metabarcoding. Next, we address barriers to widespread adoption of DNA metabarcoding, highlighting the need for standardized sampling protocols, experts and computational resources to handle the deluge of genomic data, and standardized, open-source bioinformatic pipelines. Finally, we explore how technological and scientific advances will realize the promise of total biodiversity assessment in a sample—from microbes to mammals—and unlock the rich information genomics exposes, opening new possibilities for merging whole-system DNA metabarcoding with (1) abundance and biomass quantification, (2) advanced modeling, such as species occupancy models, to improve species detection, (3) population genetics, (4) phylogenetics, and (5) food web and functional gene analysis. While many challenges need to be addressed to facilitate widespread adoption of environmental genomic approaches, concurrent scientific and technological advances will usher in methods to supplement existing bioassessment tools reliant on morphological and abiotic data. This expanded toolbox will help ensure that the best tool is used for the job and enable exciting integrative techniques that capitalize on multiple tools. Collectively, these new approaches will aid in addressing the global biodiversity crisis we now face.

To denoise or to cluster, that is not the question: optimizing pipelines for COI metabarcoding and metaphylogeography

“…The field of eukaryotic metabarcoding is witnessing an exponential growth, both in the number of communities and substrates studied and the applications reported (reviewed in [ 1 – 4 ]). In parallel, technical and conceptual issues are being discussed (e.g., [ 5 , 6 ]) and new methods and pipelines generated.…”

Environmental DNA gives comparable results to morphology-based indices of macroinvertebrates in a large-scale ecological assessment

“…Technical biases of the metabarcoding data (e.g., PCR bias, sequencing errors) restrict the comparability to traditional count data [ 32 , 33 ] and limit the implementation in frameworks of existing biotic indices. Novel approaches to fully exploit and interpret molecular data are thus in demand [ 34 , 35 ]. A promising approach in the era of big data, machine learning has emerged for the analysis of high-dimensional and complex data [ 36 ] and recent studies have demonstrated the use of these approaches, such as random forest model [ 37 ], also in an ecological context (e.g., [ 38 – 41 ]).…”

To denoise or to cluster? That is not the question. Optimizing pipelines for COI metabarcoding and metaphylogeography

“…The field of eukaryotic metabarcoding is witnessing an exponential growth, both in the number of communities and substrates studied and the applications reported (reviewed in Deiner et al 2017, Aylagas et al 2018, Bani et al 2020, Compson et al 2020. In parallel, technical and conceptual issues are being discussed (e.g., Mathieu et al 2020, Rodriguez-Ezpeleta et al 2020 and new methods and pipelines generated.…”