DOI: 10.5061/dryad.st467
title: Data from: A preliminary framework for DNA barcoding, incorporating the multispecies coalescent

description: The capacity to identify an unknown organism using the DNA sequence from a
 single gene has many applications. These include the development of
 biodiversity inventories (Janzen et al. 2005), forensics (Meiklejohn et
 al. 2011), biosecurity (Armstrong and Ball 2005), and the identification
 of cryptic species (Smith et al. 2006). The popularity and widespread use
 (Teletchea 2010) of the DNA barcoding approach (Hebert et al. 2003),
 despite broad misgivings (e.g., Smith 2005; Will et al. 2005; Rubinoff et
 al. 2006), attest to this. However, one major shortcoming to the standard
 barcoding approach is that it assumes that gene trees and species trees
 are synonymous, an assumption that is known not to hold in many cases
 (Pamilo and Nei 1988; Funk and Omland 2003). Biological processes that
 violate this assumption include incomplete lineage sorting and
 interspecific hybridization (Funk and Omland 2003). Indeed, simulation
 studies indicate that the concatenation approach (in which these two
 processes are ignored) can lead to statistically inconsistent estimation
 of the species tree (Kubatko and Degnan 2007). However, recent
 developments make a barcoding approach that utilizes a single locus
 outdated. The cost of sequencing multiple gene fragments is no longer
 inhibitory, but more importantly, a range of analytical approaches have
 been developed that account for incomplete lineage sorting (Degnan and
 Salter 2005; Edwards et al. 2007; Liu et al. 2008; Kubatko et al. 2009;
 Heled and Drummond 2010; Yang and Rannala 2010). These approaches
 incorporate coalescent theory into the analysis of species trees and
 species delimitation (Fujita et al. 2012) and are conveniently accessible
 as software programs (e.g., BEST, BPP, *BEAST, MrBayes v. 3.2, STEM, and
 COAL). Although the general mixed Yule coalescent (GMYC) approach has also
 been developed for species delimitation (Pons et al. 2006), we do not
 consider it further here. It operates quite differently to the approaches
 outlined above (i.e., BEST, BPP, *BEAST, MrBayes v. 3.2, STEM, and COAL).
 The GMYC approach seeks to identify the shift in the rate of lineage
 branching that should be evident when interspecific evolutionary processes
 switch to population-level processes (Pons et al. 2006). Both empirical
 (Esselstyn et al. 2012) and simulation studies (Esselstyn et al. 2012;
 Fujisawa and Barraclough 2013) report that it performs poorly when
 effective population sizes and speciation rates are high, but within
 biologically relevant ranges. Ideally, a “next-generation” barcoding
 approach would (1) identify a minimal set of barcoding genes (perhaps
 specific to certain lineages), (2) generate a large and cladistically
 divergent database for comparisons, and (3) identify species using species
 delimitation approaches that incorporate the multispecies coalescent. The
 first two of these conditions are straightforward and require only
 discussion (requirement 1) and resources (requirement 2). However, the
 third requirement is much more problematic. Some of the recently developed
 approaches for species delimitation could not be used alone; for example,
 BPP requires a user-specified guide tree (Yang and Rannala 2010). All of
 the recently developed approaches are computationally intensive (Degnan
 and Rosenberg 2009), with many having practical limitations on the number
 of individuals that can be compared. By contrast, the current barcoding
 approach is able to compare enormous numbers of sequences in a very short
 time, primarily because the approach is analytically simple; a single
 sequence is compared with all sequences in the database by calculating all
 possible pairwise K2P distances. As long as exemplars exist within the
 database that have K2P distances below some predetermined threshold
 (usually 4%), the species is considered identified. The speed of analysis
 is due primarily to the use of distance-based measures. The purpose of
 this article is to initiate the development of a framework for “next-gen
 barcoding”: one that incorporates the multispecies coalescent, but does so
 by comparing multiple gene sequences from an unknown taxon with a database
 of sequences.
description: COI and CAD
 sequencesnexus formatted sequence
 dataCOI_CAD_SystBiol.nex