News

What lives in soil? In August 2009 Pesq Agropec Bras (open access) an international cohort of 10 researchers from Canada, France, US, Taiwan, and Russia examine prospects for speeding assessment of soil animal diversity with COI DNA barcoding. As test sets, Rougerie and colleagues explore taxonomic and sequence diversity in earthworms and collembolans (springtails). These two groups comprise a similar number of named species (earthworms, 6000; springtails, 7900), but these totals likely underestimate true diversity, particularly for springtails, which are tiny (0.2 – 6.0 mm), challenging collecting and morphology.

For earthworms, the researchers analyzed COI sequences from 457 specimens collected in 13 countries around the world (including North America, South America, Caribbean, Europe, Middle East, Southeast Asia, and Australia); these represented at least 49 genera in 8 families. 87 species were identified by morphology, representing about 1/2 of specimens; the remainder, mostly those from Philippines and Brazil, could not be identified to species. Applying a threshold approach, the researchers found 192 (10% cutoff) and 211 (4% cutoff) genetic clusters, including two or more divergent clusters in 13 (15%) of named species. None of species showed sequence sharing or overlaps.

For springtails, 695 specimens from a similar global distribution of sites were analyzed, representing 88 genera in 16 familes; only 44 species were formally identified with morphologic characters, consistent with the “difficult and poorly known taxonomy of these organisms.” Of note, the authors report that “a specific protocol was developed for [collembolans] so that voucher specimens could be recollected after DNA extraction and thus be used for further morphological examination.” Sequence comparisons showed a “typical…bimodal distribution of intra- versus interspecific divergences such as the one also reported in earthworms.” Applying distance thresholds as above gave 215 (10% cutoff) and 227 (4% cutoff) genetic clusters. In conclusion, efficient assessment of soil animal diversity calls out for DNA barcoding.

On a separate note, soil animals may be useful for understanding mitochondrial evolution. Even factoring in species diversity, these animals appear to have enormous population sizes, given densities up to 4 x 10³ earthworms/m² and 1.8 x 10⁶ collembolans/m³, yet show typical bimodal pattern of intra- << inter-specific variation noted above. Along these lines, in November 2009 Nature Nick Lane explores whys of mitochondrial evolution and speciation, including a possible “radically new picture of mitochondrial genes being tightly regulated by selection.” Stay tuned!

In current Aquatic Conserv Marine Freshwater Ecosys, researchers from Muséum national d’Histoire naturelle, France, report on 80 years of taxonomic confusion that has contributed to near extinction for a once abundant north Atlantic skate. Iglésias and colleagues found that two forms, lumped together in 1926 as European common skate (Dipturus batis, Linnaeus 1798), in fact represent distinct species with morphologic, genetic (in mitochondrial genome), and life history differences.

As the researchers report, this taxonomic oversight obscured the disappearance of one species, the flapper skate (D. cf. intermedia) because it was confused with the less threatened  blue skate (D. cf. flossada).  Iglesias and colleagues marketplace survey revealed additional sources of confusion. They analyzed 4,110 skates landed over a 2 year period from 103 fishing cruises in four main French ports by 41 different French commercial trawlers, and found that five skate species (included the two named above) from two genera are variously lumped together under just two marketplace names, the aforementioned “European common skate (D. batis)” and “longnose skate (D. oxyrinchus);” according to their analysis the latter species, formerly common, is also locally extirpated, and most specimens with this name represent other species.

For newly rediscovered blue and flapper skates, the researchers report 20 diagnostic substitutions in approximately 2600-nucleotide segment spanning 12s and 16s RNA. Other than the 10 mitochondrial sequences included in this report, I find only two other D. batis sequences in GenBank (and none as yet under either of two resurrected names). It is remarkable that so little genetic information has been collected for such recently abundant, commercially important (annual landings in 1000’s of tons), and now threatened species. To aid standardized application of molecular identification techniques, I hope the authors will also analyze COI barcode sequences for their specimens. Then I look forward to school children aiding conservation and helping find new species by DNA barcoding specimens from their local fish markets!

Bluefin tuna are enormous (up to 15 ft/4.5 m, 680 kg/1500 lbs), high-speed (up to 54 km/h, as fast as racehorses) creatures that roam across oceans and return to ancestral waters to spawn. High demand has fueled intensive fishing by international fleets, resulting in 90% population declines heading towards extinction for all three species, Southern (Thunnus maccoyii), Northern (T. thynnus), and Pacific bluefin (T. orientalis). This week in PLoS ONE researchers from the American Museum of Natural History describe DNA-based identification of bluefin and other tuna species using character analysis of COI barcode sequences. Lowenstein and colleagues’ report provides a basis for routine identification of marketplace items to inform consumers and enable enforcement of regulations, including a proposed listing as endangered under Convention of International Trade in Endangered Species (CITES).

The eight species in genus Thunnus are not discriminated by regularly used nuclear loci and differ by about 1% or less in mitochondrial coding regions (e.g., Ward et al 2005 Phil Trans R Soc B), challenging DNA-based identification. To construct a diagnostic key, Lowenstein and colleagues analyzed 89 COI sequences in GenBank representing the eight tuna species and by visual inspection found 14 sites that provided 17 “compound characteristic attributes (CAs)” (terminology from Sarkar et al 2008 Mol Ecol Res). Turning marketplace detectives, the AMNH team collected 68 sushi samples from 31 establishments in New York and Denver over 6 month period in 2008. Nearly one-third (22; 32%) of samples were sold as species contradicted by the molecular data, including items from over half (19; 61%) of the restaurants.

Lowenstein found their character-based identifications were more accurate and precise than those provided by BOLD ID engine (www.barcodinglife.org), largely reflecting that the ID engine uses a 2% cutoff for assigning specimens to species, which encompasses all eight Thunnus sp.  In addition, BOLD is a workbench for researchers and so contains many as yet unpublished sequences from ongoing studies; these need to be viewed as provisional data. Indeed, in constructing their key Lowenstein and colleagues set aside 2 of the 89 GenBank tuna sequences as these grouped with other species. These anomalous sequences might reflect hybridization or introgression which is reported to occur in 2-3% of Atlantic bluefin, for example (Viñas and Tudela 2009 PLoS ONE). In this study, researchers from Universitat de Girona, Spain and World Wildlife Fund describe a DNA-based method for distinguishing tuna species using mitochondrial control region and nuclear ITS. Here again the method is validated using published data, in this case 42 GenBank records representing the 8 species.  As an aside, I find it remarkable there are so few records that might enable identification of such commercially-important and now endangered species. These two studies establish a scientific and possible legal standard for tuna identification. Now we begin.