Gap analysis for DNA-based biomonitoring of aquatic ecosystems in China

Li, Feilong; Zhang, Yuan; Altermatt, Florian; Zhang, Xiaowei; Cai, Yanpeng; Zhang, Yang

doi:10.1016/j.ecolind.2022.108732

Cited by 15 publications

(25 citation statements)

References 52 publications

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“…In accordance with our observations, there are several other studies pointing out considerable gaps in the reference libraries for different taxa [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 ]. However, there are not many gap-analysis studies focusing on phytoplankton taxa.…”

Section: Discussionsupporting

confidence: 93%

“…Their deficiency has been investigated for different aquatic taxonomic groups and geographic regions. Significant absence of DNA barcodes was quantified for macroinvertebrate species [ 20 , 21 , 22 ], for ascidians and cnidarians [ 23 ], for some major invertebrate macrofauna phyla [ 24 ], and recently for freshwater fish, aquatic insects and molluscs [ 25 ]. Yet, to our knowledge, there is only one study that investigated the DNA barcodes availability for phytoplankton species and it revealed a considerably low coverage [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

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DNA Barcode Gap Analysis for Multiple Marker Genes for Phytoplankton Species Biodiversity in Mediterranean Aquatic Ecosystems

Tzafesta

Saccomanno

Zangaro

et al. 2022

Biology

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The implementation of DNA metabarcoding and environmental DNA (eDNA) to the biodiversity assessment and biomonitoring of aquatic ecosystems has great potential worldwide. However, DNA metabarcoding and eDNA are highly reliant on the coverage of the DNA barcode reference libraries that are currently hindered by the substantial lack of reference sequences. The main objective of this study was to analyze the current coverage of DNA barcode reference libraries for phytoplankton species of the aquatic Mediterranean ecoregion in the southeast of Italy (Apulia Region) in order to assess the applicability of DNA metabarcoding and eDNA in this area. To do so, we investigated three main DNA barcode reference libraries, BOLD Systems, GenBank and SILVA, for the availability of DNA barcodes of the examined phytoplankton species. The gap analysis was conducted for three molecular gene markers, 18S, 16S and COI. The results showed a considerable lack of barcodes for all three markers. However, among the three markers, 18S had a greater coverage in the reference libraries. For the 18S gene marker, the barcode coverage gap across the three types of ecosystems examined was 32.21–39.68%, 60.12–65.19% for the 16S marker gene, and 72.44–80.61 for the COI marker gene. Afterwards, the interspecific genetic distance examined on the most represented molecular marker, 18S, was able to distinguish 80% of the species mined for lakes and 70% for both marine and transitional waters. Conclusively, this work highlights the importance of filling the gaps in the reference libraries, and constitutes the basis towards the advancement of DNA metabarcoding and eDNA application for biodiversity assessment and biomonitoring.

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Section: Discussionsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

DNA Barcode Gap Analysis for Multiple Marker Genes for Phytoplankton Species Biodiversity in Mediterranean Aquatic Ecosystems

Tzafesta

Saccomanno

Zangaro

et al. 2022

Biology

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“…Firstly, a list of the target species within the study area should be made and the correct sequences available (in terms of length and marker) found for those species should be assembled (Blackman et al, 2021). This allows any gaps to be identified and therefore an immediate understanding of the limitation of your reference database and data interpretation (Li et al, 2022; Weigand et al, 2019). Secondly, multiple sequences should be used for each species to ensure haplotypic diversity (Leite et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…Unfortunately, the perfect reference database does not exist (yet), and databases are scarce for large organismal groups. Often, studies are forced to use incomplete reference databases, which sometimes have inaccurate or mis‐labelled sequences (Somervuo et al, 2017) that can ultimately prohibit detection or assignment of species level identification to a cluster or zOTUs (Blackman et al, 2021; Li et al, 2022; Weigand et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Perhaps, the most widely used database of open access sequences is GenBank (Benson et al, 2013). Until recently, it was widely thought to have a high proportion of errors, yet analysis suggests that—although discrepancies are present—when examining taxonomic assignment above species level these errors are less than previously thought (Leray et al, 2019; Locatelli et al, 2020), yet geographic biases still exist (Li et al, 2022). These findings are encouraging; but similarly other studies have conversely highlighted issues when examining species level annotation, such as Conte‐Grande and colleagues (2017) who found 16.3% of all snakehead (Channidae) sequences ( COI ) on GenBank were in fact incorrect.…”

Section: Introductionmentioning

confidence: 99%

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General principles for assignments of communities from eDNA: Open versus closed taxonomic databases

et al. 2022

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Metabarcoding of environmental DNA (eDNA) is a powerful tool for describing biodiversity, such as finding keystone species or detecting invasive species in environmental samples. Continuous improvements in the method and the advances in sequencing platforms over the last decade have meant this approach is now widely used in biodiversity sciences and biomonitoring. For its general use, the method hinges on a correct identification of taxa. However, past studies have shown how this crucially depends on important decisions during sampling, sample processing, and subsequent handling of sequencing data. With no clear consensus as to the best practice, particularly the latter has led to varied bioinformatic approaches and recommendations for data preparation and taxonomic identification. In this study, using a large freshwater fish eDNA sequence dataset, we compared the frequently used zero-radius Operational Taxonomic Unit (zOTU) approach of our raw reads and assigned it taxonomically (i) in combination with publicly available reference sequences (open databases) or (ii) with an OSU (Operational Sequence Units) database approach, using a curated database of reference sequences generated from specimen barcoding (closed database). We show both approaches gave comparable results for common species. However, the commonalities between the approaches decreased with read abundance and were thus less reliable and not comparable for rare species. The success of the zOTU approach depended on the suitability, rather than the size, of a reference database.Contrastingly, the OSU approach used reliable DNA sequences and thus often enabled species-level identifications, yet this resolution decreased with the recent phylogenetic age of the species. We show the need to include target group coverage, outgroups and full taxonomic annotation in reference databases to avoid misleading annotations that can occur when using short amplicon sizes as commonly used in eDNA metabarcoding studies. Finally, we make general suggestions to improve the construction and use of reference databases for metabarcoding studies in the future.

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Opportunities and inherent limits of using environmental DNA for population genetics

Couton,

Viard,

Altermatt

2023

Environmental DNA

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Molecular techniques using DNA retrieved from community or environmental samples, in particular environmental DNA (eDNA), are becoming increasingly popular for detecting individual species, assessing biodiversity, and quantifying ecological indices. More recently, eDNA has also been proposed as a template for population genetics, and several studies have already tested the feasibility of this approach, mostly looking at vertebrate species. Their results along with general opportunities offered by these types of “community‐based” samples, such as the possibility to target multiple species at the same time, have generated great enthusiasm and expectations for using eDNA in population genetics. However, not every aspect of population genetics can be addressed by eDNA‐based data and some inherent limitations may challenge its conclusions. Here, we firstly review the state of current knowledge of DNA retrieved from environmental and community samples for population genetics. Then, focusing on eDNA, we summarize the opportunities but also detail four main limitations of its use for population‐level inferences, namely, (1) the difficulty to retrieve a species‐specific dataset, (2) the potential lack of correlation between observed and true allelic frequencies, (3) the loss of individual information in multi‐locus genotyping and linkage between loci, and (4) the uncertainty about the individuals contributing to the sampled DNA pool (e.g., number, life‐stage, or sex). Some of these limitations might be overcome with the development of new technologies or models that account for the specificities of eDNA. Others, however, are inherent, and their effect on the inferences must be thoroughly evaluated. The possibility of gaining insights into genetic diversity and population structure from DNA retrieved from community and environmental samples is appealing for scientists, conservation managers, and other practitioners. Yet, to avoid false expectations and incorrect inferences, it is imperative that these limitations are known and considered alongside the opportunities and advantages.

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Gap analysis for DNA-based biomonitoring of aquatic ecosystems in China

Cited by 15 publications

References 52 publications

DNA Barcode Gap Analysis for Multiple Marker Genes for Phytoplankton Species Biodiversity in Mediterranean Aquatic Ecosystems

DNA Barcode Gap Analysis for Multiple Marker Genes for Phytoplankton Species Biodiversity in Mediterranean Aquatic Ecosystems

General principles for assignments of communities from eDNA: Open versus closed taxonomic databases

Opportunities and inherent limits of using environmental DNA for population genetics

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