From metabarcoding to metaphylogeography: separating the wheat from the chaff

Abstract

Metabarcoding is by now a well‐established method for biodiversity assessment in terrestrial, freshwater, and marine environments. Metabarcoding data sets are usually used for α‐ and β‐diversity estimates, that is, interspecies (or inter‐MOTU [molecular operational taxonomic unit]) patterns. However, the use of hypervariable metabarcoding markers may provide an enormous amount of intraspecies (intra‐MOTU) information—mostly untapped so far. The use of cytochrome oxidase (COI) amplicons is gaining momentum in metabarcoding studies targeting eukaryote richness. COI has been for a long time the marker of choice in population genetics and phylogeographic studies. Therefore, COI metabarcoding data sets may be used to study intraspecies patterns and phylogeographic features for hundreds of species simultaneously, opening a new field that we suggest to name metaphylogeography. The main challenge for the implementation of this approach is the separation of erroneous sequences from true intra‐MOTU variation. Here, we develop a cleaning protocol based on changes in entropy of the different codon positions of the COI sequence, together with co‐occurrence patterns of sequences. Using a data set of community DNA from several benthic littoral communities in the Mediterranean and Atlantic seas, we first tested by simulation on a subset of sequences a two‐step cleaning approach consisting of a denoising step followed by a minimal abundance filtering. The procedure was then applied to the whole data set. We obtained a total of 563 MOTUs that were usable for phylogeographic inference. We used semiquantitative rank data instead of read abundances to perform AMOVAs and haplotype networks. Genetic variability was mainly concentrated within samples, but with an important between seas component as well. There were intergroup differences in the amount of variability between and within communities in each sea. For two species, the results could be compared with traditional Sanger sequence data available for the same zones, giving similar patterns. Our study shows that metabarcoding data can be used to infer intra‐ and interpopulation genetic variability of many species at a time, providing a new method with great potential for basic biogeography, connectivity and dispersal studies, and for the more applied fields of conservation genetics, invasion genetics, and design of protected areas.

Can metabarcoding resolve intraspecific genetic diversity changes to environmental stressors? A test case using river macrozoobenthos

“…Furthermore, as outlined in previous studies (Elbrecht et al, 2018; Tsuji et al, 2019; Turon et al, 2019), the main challenge in extracting haplotypes from metabarcoding datasets is the separation of ‘real’ environmental sequences from those produced by PCR or sequencing errors. New programs enable the denoising of datasets with the optimisation of filtering steps, to efficiently separate real sequences from erroneous ones.…”

“…In comparison, a lower filtering increases the number of rare real sequences, but also includes a higher number of erroneous sequences into diversity analysis. For the present study, we followed denoising as recommended in Elbrecht et al, 2018, where the genetic variability of benthic macroinvertebrates in Finland streams was investigated, implementing an α-value of 5, which was also applied in Turon et al, 2019. The additional percentual abundance threshold filtering for OTUs and haplotypes was set after suggestions in Elbrecht et al, 2018 and applied in Laini et al, in review.…”

“…Here, additional bioinformatic filtering steps are used, that allow to separate biological template sequences from noisy reads caused by PCR and sequencing errors. With ESVs it is possible to explore intraspecific genetic diversity patterns in eukaryotes (Elbrecht et al, 2018; Tsuji et al, 2019; Turon et al, 2019). For animals, commonly a 658-bp fragment of the mitochondrial cytochrome c oxidase I gene (COI) is used for DNA barcoding and a shorter part of this for metabarcoding (Hebert et al, 2003).…”

HACSim: an R package to estimate intraspecific sample sizes for genetic diversity assessment using haplotype accumulation curves

“…That is, unlike in traditional Sanger-based sequencing, there is not a one-to-one correspondence between specimen and sequence (Wares & Pappalardo, 2015;Adams et al, 2019). Second, obtaining reliable haplotype information from noisy HTS datasets is challenging without first having strict quality filtering criteria in place to minimize the occurrence of rare, low-copy sequence variants which may reflect artifacts stemming from the Polymerase Chain Reaction (PCR) amplification step or sequencing process (Elbrecht et al, 2018;Braukmann et al, 2019;Turon et al, 2019). Turning to molecular population genetics theory might be the answer (Adams et al, 2019).…”

Peer Review #2 of "HACSim: an R package to estimate intraspecific sample sizes for genetic diversity assessment using haplotype accumulation curves (v0.2)"

“…That is, unlike in traditional Sanger-based sequencing, there is not a one-to-one correspondence between specimen and sequence (Wares and Pappalardo, 2015;Adams et al, 2019). Second, obtaining reliable haplotype information from noisy HTS datasets is challenging without first having strict quality filtering criteria in place to minimize the occurrence of rare, low-copy sequence variants which may reflect artifacts stemming from the Polymerase Chain Reaction (PCR) amplification step or sequencing process (Elbrecht et al, 2018;Braukmann et al, 2019;Turon et al, 2019). Turning to molecular population genetics theory might be the answer (Adams et al, 2019).…”