DNA barcode data accurately assign higher spider taxa

Introduction

Accurate identification of biological specimens has always limited the application of biological data to important societal problems. Obstacles are well-known and difficult: the vast majority of species are undescribed scientifically (Erwin, 1982; May, 1992; Mora et al., 2011); some unknown but large fraction of higher taxa are not monophyletic (Goloboff et al., 2009; Pyron & Wiens, 2011); many species can only be identified if certain life stages are available, e.g., adults (Coddington & Levi, 1991), classical data sources such as morphology imperfectly track species identity; the discipline of taxonomy continues to dwindle (Agnarsson & Kuntner, 2007); the classical process of taxonomic identification is mostly manual and cannot scale to provide the amounts of data required for real-time decisions such as environmental monitoring, invasive species, climate change, etc.

DNA sequence data potentially can eliminate most of these obstacles. DNA barcoding uses a fragment of the mitochondrial gene cytochrome c oxidase subunit I (CO1) as a unique species diagnosis/identification tool in the animal kingdom (Hebert et al., 2003), with analogous single to several locus protocols applied for vascular plants, ferns, mosses, algae and fungi (Saunders, 2005; Kress & Erickson, 2007; Nitta, 2008; Chase & Fay, 2009; Liu et al., 2010), protists (Scicluna, Tawari & Clark, 2006), and prokaryotes (Barraclough et al., 2009). Due to relative ease and inexpensive sequencing, DNA barcoding is a popular tool in species identification and taxonomic applications (e.g., Doña et al., 2015; Xu et al., 2015; see also Collins & Cruickshank, 2013), and the method is no longer fundamentally controversial at the species level (Pentinsaari, Hebert & Mutanen, 2014; Lopardo & Uhl, 2014; Čandek & Kuntner, 2015; Anslan & Tedersoo, 2015; Wang et al., 2015).

While most species remain undescribed, the situation is not so dire for larger monophyletic groups such as clades accorded the Linnaean ranks of genus or family. In assessing the state of knowledge about biodiversity, it is important to distinguish between the first scientific discovery of an exemplar of a lineage, and phylogenetic understanding of that lineage. Phylogenetic understanding—both tree topology and consequent taxonomic changes, are research programs with no clear end in sight. Linnaean rank is partially arbitrary, and one expects that the number of higher taxa will probably increase over time as understanding improves. Discovery, however, can have an objective definition: the year of the earliest formal taxonomic description of a member of the lineage or taxonomic group in which it is currently included. By this definition the earliest possible discovery of an animal lineage is 1758 (Linnaeus, 1758), or in the case of spiders, 1757 (Clerck, 1757).

More illuminating are the latest discoveries of lineages with the rank of family within larger clades, because the data tell us something about progress towards broad scale knowledge of biodiversity. The species representing the most recent discovery of a family of birds, for example, is the Broad-billed Sapayoa, Sapayoa aenigma Hunt, 1903 (Sapayoaidae). The species representing the most recently discovered mammal family is Kitti’s hog-nosed bat, Craseonycteris thonglongyai Hill, 1974 (Craseonycteridae). For flowering plants, it is Gomortega keule (Molina) Baill, 1972 (Gomertegaceae). For bees, it is Stenotritus elegans Smith, 1853 (Stenotritidae). For spiders, a megadiverse and poorly known group, it is Trogloraptor marchingtoni Griswold, Audisio & Ledford, 2012 (Trogloraptoridae), but the second most recent discovery of an unambiguously new spider family was in 1955, Gradungulidae (Forster, 1955). Figure 1 illustrates the tempo of first discovery of families for these five well-known clades. At the family level, these curves are essentially asymptotic, implying that science is close to completing the inventory of clades ranked as families for these large lineages. On the other hand, for Bacteria and Archaea (Fig. 1), as one would expect, the curve is not asymptotic at all but sharply increasing; prokaryote discovery and understanding is obviously just beginning.

In fact, although many new eukaryote families are named every year, the vast majority of these new names result from advances in phylogenetic understanding, not biological discovery of major new forms of life. The last ten years of Zoological Record suggests that roughly 5–10 truly new families are discovered per year.

In the context of the above question—approximate taxonomic assignment of organisms using DNA sequences—these data suggest that our knowledge of major clades of life is approaching completion. The Global Genome Initiative (GGI; http://ggi.si.edu/) of the Smithsonian Institution via the GGI Knowledge Portal (http://ggi.eol.org/) has tabulated a complete list of families of life, which total 9,650—on the whole a surprisingly small number. 10,000 barcodes, more or less, seems like a feasible goal. If we were able to assemble a complete database of DNA sequences at the family level, would it suffice to identify any eukaryote on Earth to the family level?

While the literature on species identification success of DNA barcodes comprises thousands of studies, only a few have tested their effectiveness at the level of higher taxonomic units. In the seminal paper on DNA barcodes, Hebert et al. (2003) established that animal CO1 sequences can roughly assign taxa to phyla (96% success) or orders (100% success). However, their test was based on a neighbor joining tree-building approach, and it remained unknown if sequence data itself, i.e., percent identity among taxa, can be used in this way. Similarly, Nagy et al. (2012) showed that DNA barcoding in reptiles usually correctly assigned barcodes to species, genus and family. Their approach was phylogenetic: they tested whether including a sequence in tree building rendered the higher group non-monophyletic, which would imply failure. Finally, Wilson et al. (2011) provided a similar tree based test in sphingid moths, and established reliabilities of correct generic and subfamily taxonomic assignments between 74 and 90% using a liberal, and only 66–84% using a strict, tree-based criterion. These authors argued that tree-based methods perform better than sequence comparison methods, but that reliability, of course, depends on the library completeness.

Our project not only contributes original DNA barcode data for Central European spiders, but also works in synergy with the GGI towards a permanent preservation of genomic biodiversity: the formation of a collection of deeply frozen spider tissues and their DNA. We provide: (1) cryo-preserved tissues of reliably identified species of Central European spiders, and their vouchers photographed and deposited in public museums; (2) permanently frozen genomic DNA of these species; (3) publicly accessible DNA barcodes for these species (genetic sequence of cytochrome oxidase I—CO1) as public identification tool (Hebert et al., 2003) to facilitate organism identification, taxonomy, ecology and conservation.

In addition, this project addresses to what extent higher level taxonomic units can be reliably identified using barcodes of unknown spiders, and specifically asks what percent sequence identity in BLAST results is necessary to correctly identify unknown taxa to the Linnaean genus and/or family. Other methods for classification of higher-level taxonomies such as RDP (Wang et al., 2007), UTAX (Edgar, 2010) and MEGAN (Huson et al., 2007) have primarily been developed for studies of microorganisms, using genetic markers for these groups, but less is known about using the CO1 barcoding gene in metazoans. We examine empirical data from Araneae barcode data to ask what is the percent sequence identity value above which 5% or less of higher level (genus/family) taxonomic identifications are incorrect and the extent to which frequency of correct identifications correlated with the number of taxa in this dataset, as would be expected given the dependence of BLAST on the reference database.

Materials & Methods

Results

The 816 query sequences returned 8,159 total hits with one query only returning nine hits and all others ten (Table S1). PIdent scores ranged from 75% to 100%. We also examined the length of the sequence matched compared to the entire sequence length. 8,114 hits (>99%) matched to 90% or more of the query sequence length indicating that these results represent matches to large portions of the query validating the use of Percent Sequence Identity in the BLAST hits rather than computing the value for a global alignment between sequences. Figure 2 shows the frequency distributions of PIdent values of correct and incorrect identifications at the genus and family rank.

• 1.

  95% of incorrect genus identifications were below PIdent = 95 when all hits for all queries are included, which suggests the latter value as a heuristic threshold to delimit incorrect from correct identifications (for these data). For only the highest rank hits whose PIdent ≥95, 98% of genus identifications were correct.

• 2.

  95% of incorrect family identifications were below PIdent = 91 when all hits for all queries are included, which suggests the latter value as a heuristic threshold to delimit incorrect from correct identifications (for these data). For only the highest rank hits whose PIdent ≥91, 97% of family identifications were correct.

• 3.

  Library accuracy is crucial, but sequencing, labelling, and identification errors are difficult to detect a priori. The highest ranked incorrect family identification was Meta menardi (Tetragnathidae) to Steatoda grossa (Theridiidae), at PIdent = 96. Further study of the M. menardi sequence shows that the BOLD record is probably a mislabeled Steatoda. The first true incorrect family identification occurs at a PIdent value of 88; the best hit for Octonoba (Uloboridae) is Amaurobius (Amaurobiidae).

• 4.

  For the 136 genera with at least two species in the library, 76% (n = 103) best matched congeners. Thirty-three failed, perhaps because sequences were incorrectly identified taxonomically, or the sequence itself may be erroneous, or perhaps due to non-monophyly of genera.

• 5.

  The distributions of PIdents for correct family and genus identifications differ significantly from the distributions of incorrect identifications (Fig. 2).

• 6.

  Plotted against increasing numbers of species/genus, and genera/family, the proportion of top ten PIdent values that exceed the above suggested threshold values increases. Roughly speaking, 15 species per genus, and 5 genera per family, are sufficient to ensure that best hits represent correct identifications (Fig. 3).

Discussion

We show that standard DNA barcodes can accurately assign unknown specimens to genus and family given sufficient sequence identity and sufficient taxonomic representation in the database. Accurate identification (PIdent above which less than 5% of identifications were incorrect) occurred for genera at PIdent values > 95 and families at PIdent values ≥91, suggesting these as heuristic thresholds for generic and familial identifications in spiders (shaded in Fig. 2). Accuracy of identification increases with numbers of species/genus and genera/family; above five genera per family and 15 species per genus all identifications were correct (Fig. 3).

The accurate identification of specimens remains a critical challenge for megadiverse groups such as arthropods, most other invertebrates, plants, fungi, protists etc. Morphological identification to species, or even more inclusive taxonomic ranks like genera and families, in many cases requires extensive training, and for most groups taxonomic expertise is limited and dwindling—the so called ‘taxonomic impediment’ (Rodman & Cody, 2003; Agnarsson & Kuntner, 2007). DNA barcodes have been proposed as convenient tools to overcome this impediment by making identification a purely technical procedure available to any interested researcher or even ‘citizen scientists.’ However, the accuracy of such a tool strongly depends on the scope and quality of the barcode library (Smit, Reijnen & Stokvis, 2013). Currently available data on databanks like BOLD and GenBank are extensive for some groups, yet the vast majority of species on earth have not yet been barcoded, much less discovered and described taxonomically—each of these tasks is enormous. Even for existing barcoding data, numerous sequences lack accurate taxonomic identification (Collins & Cruickshank, 2013), limiting their utility (e.g., only 58% of Araneae in BOLD are identified to species, and of those many are not correctly identified, as shown in our results; see also Shen, Chen & Murphy, 2013; Blagoev et al., 2016). Therefore, the identification of unknown specimens through blasting against BOLD or GenBank will be inaccurate if the databases lack close hits or contain errors. While the ideal database would allow species-level identification by containing barcodes from expertly identified and vouchered specimens of all species, we hypothesized that rapid surveys of well-known biotas can help quickly to build valuable tools allowing identification of larger clades such as genera and families.

Although we were careful to screen available barcode sequences from BOLD to produce a test library with as few errors as possible, it is certainly possible that errors remained, either due to mistakes in the lab or taxonomic identifications of vouchers. For example, Meta menardi (Tetragnathidae) blasted to Steatoda grossa (Theridiidae) at PIdent = 96, and BLAST searches on GenBank suggest this Meta sequence is actually a Steatoda. Likewise, the linyphiids Agyneta orites and Incestophantes frigidus sequences were identical; one of these records is probably wrong. These sorts of errors bias identifications and limit utility of barcodes. Other examples of identical barcode sequences were all congeners, and therefore are less likely to involve errors but could indicate faults in taxonomy: Arctosa maculata and A. fulvolineata, Bolyphantes luteolus and B. alticeps, Pardosa alacris and P. trifrons, and Pityohyphantes tacoma and P. cristatus. Likewise, the genus Neriene (Linyphiidae) seems non-monophyletic and identifications were thus not accurate.

Conclusions

These results suggest that accurate assignment of unknown taxa to genus and family is feasible through DNA barcoding. Database quality is crucial. Numbers of potential matches at generic and familial ranks also affect the probability that an unknown sequence will blast best to the correct family or genus. Unlike the inventory of species, biological discovery of family-level clades of life also seems far advanced—few eukaryotic families, apparently, remain to be discovered. Taken together, these results suggest that barcode-targeted sequencing of exemplars from all families of life (and most genera, if possible) should be an important scientific priority. It would enable approximate taxonomic identification of any organism anywhere on Earth by rapid, cheap, purely technical procedures requiring no specialist knowledge—certainly an important milestone in the on-going attempt to discover, classify, and understand the Earth’s biota.

Supplemental Information