Next-Generation identification tools for Nee Soon freshwater swamp forest, Singapore

Taxonomic identification accuracy from BOLD and GenBank databases using over a thousand insect DNA barcodes from Colombia

Recent declines of insect populations at high rates have resulted in the need to develop a quick method to determine their diversity and to process massive data for the identification of species of highly diverse groups. A short sequence of DNA from COI is widely used for insect identification by comparing it against sequences of known species. Repositories of sequences are available online with tools that facilitate matching of the sequences of interest to a known individual. However, the performance of these tools can differ. Here we aim to assess the accuracy in identification of insect taxonomic categories from two repositories, BOLD Systems and GenBank. This was done by comparing the sequence matches between the taxonomist identification and the suggested identification from the platforms. We used 1,160 COI sequences representing eight orders of insects from Colombia. After the comparison, we reanalyzed the results from a representative subset of the data from the subfamily Scarabaeinae (Coleoptera). Overall, BOLD systems outperformed GenBank, and the performance of both engines differed by orders and other taxonomic categories (species, genus and family). Higher rates of accurate identification were obtained at family and genus levels. The accuracy was higher in BOLD for the order Coleoptera at family level, for Coleoptera and Lepidoptera at genus and species level. Other orders performed similarly in both repositories. Moreover, the Scarabaeinae subset showed that species were correctly identified only when BOLD match percentage was above 93.4% and a total of 85% of the samples were correctly assigned to a taxonomic category. These results accentuate the great potential of the identification engines to place insects accurately into their respective taxonomic categories based on DNA barcodes and highlight the reliability of BOLD Systems for insect identification in the absence of a large reference database for a highly diverse country.

Current State of DNA Barcoding of Sciaroidea (Diptera)—Highlighting the Need to Build the Reference Library

Simple Summary

DNA barcoding is a method by which a specific region of the mitochondrial genome is used to quantify genetic distances within and between animal species. Most DNA barcodes of the world are assembled on the Barcode of Life online database BoldSystems (BOLD). There, machine-generated barcode index numbers (BINs) are automatically assigned to clusters of specimens thought to represent species. I review the current state of DNA barcoding of the superfamily Sciaroidea, a diverse insect group consisting of close to 16,000 described fly species in eight families. To date, over 1.2 million specimens of Sciaroidea have been barcoded and the 56,648 assigned BINs on BOLD already represent 3.5 times the number of described species. Still, 95% of the BINs have currently no associated scientific name and very little effort has been put into building a quality-checked reference library where named species are linked to the BINs on BOLD. In the Nordic region, however, substantial progress is made towards building a complete reference library. While DNA barcoding has tremendous potential for advancing the knowledge for many diverse groups of insects, its potential will never be fully reached absent more engagement of trained taxonomists to build voucher collections, curate the reference libraries, and describe new species.

Abstract

DNA barcoding has tremendous potential for advancing species knowledge for many diverse groups of insects, potentially paving way for machine identification and semi-automated monitoring of whole insect faunas. Here, I review the current state of DNA barcoding of the superfamily Sciaroidea (Diptera), a diverse group consisting of eight understudied fly families where the described species in the world makes up some 10% (≈16,000 species) of all Diptera. World data of Sciaroidea were extracted from the Barcode of Life online database BoldSystems (BOLD) and contrasted with results and experiences from a Nordic project to build the reference library. Well over 1.2 million (1,224,877) Sciaroidea specimens have been submitted for barcoding, giving barcode-compliant sequences resulting in 56,648 so-called barcode index numbers (BINs, machine-generated proxies for species). Although the BINs on BOLD already represent 3.5 times the number of described species, merely some 2850 named species (described or interim names, 5% of the BINs) currently have been assigned a BIN. The other 95% remain as dark taxa figuring in many frontier publications as statistics representing proxies for species diversity within a family. In the Nordic region, however, substantial progress has been made towards building a complete reference library, currently making up 55% of all named Sciaroidea BINs on BOLD. Another major source (31%) of named Sciaroidea BINs on BOLD comes from COI sequences mined from GenBank, generated through phylogenetic and integrative studies outside of BOLD. Building a quality reference library for understudied insects such as Sciaroidea requires heavy investment, both pre sequence and post sequence, by trained taxonomists to build and curate voucher collections, to continually improve the quality of the data and describe new species. Only when the BINs are properly calibrated by a rigorously quality-checked reference library can the great potential of both classical taxonomic barcoding, metabarcoding, and eDNA ecology be realized.

NGS barcoding reveals high resistance of a hyperdiverse chironomid (Diptera) swamp fauna against invasion from adjacent freshwater reservoirs

BACKGROUND

Macroinvertebrates such as non-biting midges (Chironomidae: Diptera) are important components of freshwater ecosystems. However, they are often neglected in biodiversity and conservation research because invertebrate species richness is difficult and expensive to quantify with traditional methods. We here demonstrate that Next Generation Sequencing barcodes ("NGS barcodes") can provide relief because they allow for fast and large-scale species-level sorting of large samples at low cost.

RESULTS

We used NGS barcoding to investigate the midge fauna of Singapore's swamp forest remnant (Nee Soon Swamp Forest). Based on > 14.000 barcoded specimens, we find that the swamp forest maintains an exceptionally rich fauna composed of an observed number of 289 species (estimated 336 species) in a very small area (90 ha). We furthermore barcoded the chironomids from three surrounding reservoirs that are located in close proximity. Although the swamp forest remnant is much smaller than the combined size of the freshwater reservoirs in the study (90 ha vs. > 450 ha), the latter only contains 33 (estimated 61) species. We show that the resistance of the swamp forest species assemblage is high because only 8 of the 314 species are shared despite the close proximity. Moreover, shared species are not very abundant (3% of all specimens). A redundancy analysis revealed that ~ 21% of the compositional variance of midge communities within the swamp forest was explained by a range of variables with conductivity, stream order, stream width, temperature, latitude (flow direction), and year being significant factors influencing community structure. An LME analysis demonstrates that the total species richness decreased with increasing conductivity.

CONCLUSION

Our study demonstrates that midge diversity of a swamp forest can be so high that it questions global species diversity estimates for Chironomidae, which are an important component of many freshwater ecosystems. We furthermore demonstrate that small and natural habitat remnants can have high species turnover and can be very resistant to the invasion of species from neighboring reservoirs. Lastly, the study shows how NGS barcodes can be used to integrate specimen- and species-rich invertebrate taxa in biodiversity and conservation research.