4. Discussion
Deep-sea biodiversity assessments are one of the major gaps in marine
ecology and evolution and are strongly needed for international policy
and management (Costa, Fanelli, Marini, Danovaro, & Aguzzi, 2020).
Metagenomics (MTG) allows high-resolution inventories relying on strong
phylogenetic reconstructions but is still too expensive and time
consuming, as well as biased toward prokaryotes that represent most
biomass in sediment samples (Danovaro, Snelgrove, & Tyler, 2014).
Although metabarcoding (MTB) is relatively fast and less expensive, it
suffers biases and restricts resolution to the species level.
In this study, we show that capture by hybridization (CBH) can offer a
good balance between MTG and MTB, allowing the detection of a broader
spectrum of phyla than MTB, and the reconstruction of full-length
barcodes of up to 2000 bp allows the potential for robust phylogenetic
reconstruction to improve the resolution of taxonomic assignments of
poorly studied taxa (Wilson, Brandon-Mong, Gan, & Sing, 2018).
The approach applied here, initially developed for prokaryotes by Gasc
and Peyret (2018), confirms that CBH can be adapted to describe
bacterial communities in the marine realm. Furthermore, the first assay
of transfer of this methodology to deep-sea metazoan communities proved
successful, with five more phyla (upon 16) detected with CBH than MTB.
This is in line with other recent CBH studies targeting more restrictive
sets of metazoan phyla from bulk DNA, their conservative ethanol or eDNA
samples (here freshwater and sediment; Gauthier et al., 2020; Shokralla
et al., 2016; Wilcox et al., 2018). All these studies also demonstrated
the ability of CBH to overcome biases due to PCR steps in MTB and
enhance detection rates, leading not only to a more reliable
representation of the species present in the samples but also of their
relative biomasses, highlighting possibilities for quantitative
analyses. Here, CBH results confirmed the improvement of biodiversity
inventories allowed by direct taxonomic identification using Kraken2,
which is based on exact k-mer matches and clustering of detected taxa to
the lowest common ancestor (Wood & Salzberg, 2014). The sequence reads
included different fragments within the 18S gene and were not merged.
One must thus keep in mind this may contribute to a larger amount of
taxa detected with CBH than with MTB, where sequences are merged
pairwise, filtered, clustered and are all from identical positions, yet
this clearly does not explain the broadest spectra of diversity with 5
(>30%) more phyla detected with CBH than MTB.
The second aim of this study was the reconstruction of full barcodes to
detect a broader spectrum of diversity and to enable robust phylogenetic
reconstruction with long sequences. This has been proven feasible and
underlines that a much greater sequencing depth than the one used in
this first assay will be required. An example of successful
reconstruction of long fragments and increased resolution is the case of
Porifera taxa in sample 1A. While MTB detected only 3 taxa, 20
identifications assigned to distinct taxa were recorded with CBH short,
resulting in 29 long sequences with CBH long, assigned to 12 clearly
identified species. The different hypervariable regions of 18S used for
MTB vary in their resolution for the different phyla and nucleotide
positions (Machida & Knowlton, 2012); using a full barcode thus clearly
improves the number and quality of detected taxa, as exemplified in
sample 1A for Porifera . The full 18S should thus be targeted to
obtain the best out of the two objectives of CBH: i) increase the
breadth of phyla detected and improve their taxonomic identification and
ii) enable several robust phylogenetic and phylogeographic approaches to
describe and unravel the biodiversity of deep-sea communities. In
addition, focusing on longer fragments will limit sources of
“contamination” and focus on contemporary communities by limiting the
contribution of extracellular DNA from marine sediments (Torti, Lever,
& Jørgensen, 2015).