The Effect of Geographical Scale of Sampling on DNA Barcoding

Abstract

Eight years after DNA barcoding was formally proposed on a large scale, CO1 sequences are rapidly accumulating from around the world. While studies to date have mostly targeted local or regional species assemblages, the recent launch of the global iBOL project (International Barcode of Life), highlights the need to understand the effects of geographical scale on Barcoding's goals. Sampling has been central in the debate on DNA Barcoding, but the effect of the geographical scale of sampling has not yet been thoroughly and explicitly tested with empirical data. Here, we present a CO1 data set of aquatic predaceous diving beetles of the tribe Agabini, sampled throughout Europe, and use it to investigate how the geographic scale of sampling affects 1) the estimated intraspecific variation of species, 2) the genetic distance to the most closely related heterospecific, 3) the ratio of intraspecific and interspecific variation, 4) the frequency of taxonomically recognized species found to be monophyletic, and 5) query identification performance based on 6 different species assignment methods. Intraspecific variation was significantly correlated with the geographical scale of sampling (R-square = 0.7), and more than half of the species with 10 or more sampled individuals (N = 29) showed higher intraspecific variation than 1% sequence divergence. In contrast, the distance to the closest heterospecific showed a significant decrease with increasing geographical scale of sampling. The average genetic distance dropped from > 7% for samples within 1 km, to < 3.5% for samples up to > 6000 km apart. Over a third of the species were not monophyletic, and the proportion increased through locally, nationally, regionally, and continentally restricted subsets of the data. The success of identifying queries decreased with increasing spatial scale of sampling; liberal methods declined from 100% to around 90%, whereas strict methods dropped to below 50% at continental scales. The proportion of query identifications considered uncertain (more than one species < 1% distance from query) escalated from zero at local, to 50% at continental scale. Finally, by resampling the most widely sampled species we show that even if samples are collected to maximize the geographical coverage, up to 70 individuals are required to sample 95% of intraspecific variation. The results show that the geographical scale of sampling has a critical impact on the global application of DNA barcoding. Scale-effects result from the relative importance of different processes determining the composition of regional species assemblages (dispersal and ecological assembly) and global clades (demography, speciation, and extinction). The incorporation of geographical information, where available, will be required to obtain identification rates at global scales equivalent to those in regional barcoding studies. Our result hence provides an impetus for both smarter barcoding tools and sprouting national barcoding initiatives—smaller geographical scales deliver higher a...

Whole-community DNA barcoding reveals a spatio-temporal continuum of biodiversity at species and genetic levels

“…Hence the data reflect the evolutionary history of the target taxa as inferred from a single locus, but any inconsistencies that may result from gene tree-species tree incongruence presumably are avoided due to the very large number of lineages sampled and the relatively rare occurrence of incongruence 25 . Note that with only the mtDNA sequenced, gene tree incongruence could only be assessed indirectly against the morphological species limits; where such incongruence with the mtDNA groups was evident, this usually affected only some portions of the species ranges 26 , that is, any resulting error would affect the details of geographic turnover but not the discovery of species-level groups per se.…”

“…A small proportion (1.2%) of sequences with indels and in-frame stop codons were removed as putative pseudogenes. A subset of sequences for the subfamily Agabinae was already used in a previous study after manual editing 26 , but the raw data were recompiled here using the automated editing, to make them compatible with all other data.…”

The probability of monophyly of a sample of gene lineages on a species tree

“…This limitation has forced investigators to either group multiple species together into a single clade (23,26)-a choice that our tree-pooling experiment shows can overestimate monophyly probabilities-or to consider pairwise comparisons when multispecies analyses would be preferable (25,34,39). By identifying a bias that occurs when pooling distinct species in monophyly probability computations, our experiment suggests that pooling should be avoided when possible.…”

“…Although this two-species computation has contributed to various insights about empirical monophyly patterns (21)(22)(23)(32)(33)(34), many scenarios deal with more than two species. Because multispecies monophyly probability computations have been unavailableexcept in limited cases with up to four species (4, 35-38)-multispecies studies have been forced to rely on two-species models, restricting attention to species pairs (25,34,39) or pooling disparate lineages and disregarding their taxonomic distinctiveness (23,26).…”

“…Because multispecies monophyly probability computations have been unavailableexcept in limited cases with up to four species (4, 35-38)-multispecies studies have been forced to rely on two-species models, restricting attention to species pairs (25,34,39) or pooling disparate lineages and disregarding their taxonomic distinctiveness (23,26).…”