Benchmarking DNA Metabarcoding for Biodiversity-Based Monitoring and Assessment

By Eva Aylagas, Á. Borja, Xabier Irigoien, N. Rodríguez‐Ezpeleta. Frontiers in Marine Science, 2016

206 citations recorded by the source corpus.

Characterization of biodiversity has been extensively used to confidently monitor and assess environmental status. Yet, visual morphology, traditionally and widely used for species identification in coastal and marine ecosystem communities, is tedious and entails limitations. Metabarcoding coupled with high-throughput sequencing represents an alternative to rapidly, accurately and cost-effectively analyze thousands of environmental samples simultaneously, and this method is increasingly used to characterize the metazoan taxonomic composition of a wide variety of environments. However, a comprehensive study benchmarking visual and metabarcoding-based taxonomic inferences that validates this technique for environmental monitoring is still lacking. Here we compare taxonomic inferences of benthic macroinvertebrate samples of known taxonomic composition obtained using alternative metabarcoding protocols based on a combination of different DNA sources, barcodes of the mitochondrial cytochrome oxidase I gene and amplification conditions. Our results highlight the influence of the metabarcoding protocol in the obtained taxonomic composition and suggest the better performance of an alternative 313 bp length barcode to the traditionally 658 bp length one used for metazoan metabarcoding. Additionally, we show that a biotic index inferred from the list of macroinvertebrate taxa obtained using DNA-based taxonomic assignments is comparable to that inferred using morphological identification. Thus, our analyses prove metabarcoding valid for environmental status assessment and will contribute to accelerating the implementation of this technique to regular monitoring programs.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/90fa03ffd44314b18cee17034ff4f8248d39bbfe

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

  1. B. Duarte
  2. Joao Marques
  3. A. Thompson
  4. Mehrdad Hajibabaei
  5. Mya Breitbart
  6. Luke R. Thompson
  7. Ian A. DICKIE
  8. Gregory A. C. Singer

In Molecular Biology

  1. S. Morales
  2. B. Duarte
  3. Joao Marques
  4. A. Thompson
  5. Mehrdad Hajibabaei
  6. Mya Breitbart
  7. Luke R. Thompson
  8. Ian A. DICKIE

Citations in the corpus