DNA barcoding is a taxonomic method that uses a short genetic marker in an organism's DNA to identify it as belonging to a particular species. It differs from molecular phylogeny in that the main goal is not to determine patterns of relationship but to identify an unknown sample in terms of a preexisting classification. Although barcodes are sometimes used in an effort to identify unknown species or assess whether species should be combined or separated, the utility of DNA barcoding for these purposes is subject to debate. The most commonly used barcode region for animals and some protists is a segment of approximately 600 base pairs of the mitochondrial gene cytochrome oxidase I (COI or COX1). This differs in the case of fungi, where part of Internal Transcribed Spacer 2 (ITS2) between rRNA genes is used, and again in plants, where multiple regions are used.
Applications include, for example, identifying plant leaves even when flowers or fruit are not available, identifying pollen collected on the bodies of pollinating animals, identifying insect larvae (which may have fewer diagnostic characters than adults and are frequently less well-known), identifying the diet of an animal, based on its stomach contents or faeces and identifying products in commerce (for example, herbal supplements, wood, or skins and other animal parts).
- 1 Background
- 2 Choice of locus
- 3 Vouchered specimens
- 4 Case studies
- 5 Initial criticism and current status
- 6 Software
- 7 See also
- 8 References
- 9 External links
Although the use of nucleotide sequence variations to investigate evolutionary relationships is not a new concept (Carl Woese used sequence differences in ribosomal RNA (rRNA) to discover archaea, which in turn led to the redrawing of the evolutionary tree, and molecular markers (e.g., allozymes, rDNA, and mtDNA sequences) have been successfully used in molecular systematics for decades), the modern concept of DNA barcoding as a proposed standardized method for identifying species, as well as potentially allocating unknown sequences to higher taxa such as orders and phyla, originates from a 2003 paper by Paul D.N. Hebert and co-workers from the University of Guelph, Ontario, Canada. Hebert and his colleagues demonstrated the utility of a 648 base pair region of the cytochrome c oxidase I (COI) gene, first utilized by O. Folmer and co-workers at Rutgers University in 1994 as a tool for phylogenetic analyses at the species and higher taxonomic levels, as a suitable discriminatory tool between metazoan animal species. The study authors created a COI "profile" for eight of the most diverse orders of insects, based on a single representative from each of 100 different families, and showed that this profile assigned each of 50 newly analysed taxa to its correct order; they then created a COI profile for 200 closely allied species of the insect order Lepidoptera, and employed the method to successfully assign 150 newly analysed individuals to species.
Calling the profiles "barcodes", Hebert et al. envisaged the development of a COI database that could serve as the basis for a "global bioidentification system", and wrote: "When fully developed, a COI identification system will provide a reliable, cost-effective and accessible solution to the current problem of species identification. Its assembly will also generate important new insights into the diversification of life and the rules of molecular evolution." In a follow-up paper, Hebert and different co-authors tested COI differences in congeneric species pairs (2,238 species) from 11 phyla of animals plus the four dominant orders of insects (Coleoptera, Diptera, Lepidoptera and Hymenoptera) as well as "other insects" and concluded that species level discrimination was satisfactory using the proposed COI gene region in all the groups studied with the exception of Cnidaria, which they ascribed to the exceptionally low rates of mitochondrial evolution in the latter group.
Since that time, DNA barcoding has been widely adopted in numerous studies of animals in particular, using the initially proposed "Folmer region" of the COI gene, based on its patterns of variation at the DNA level, the relative ease of retrieving the sequence, and its characteristic of being sufficiently conserved within species, yet sufficiently variable between species to enable reliable identification of each taxon. Global DNA barcoding was initially regarded as a "big science" programme and even as the renaissance of taxonomy. However, the COI sequence, which has been developed as a universal barcode in animals, does not discriminate most plants or fungi because of a much slower mutation rate in those groups; barcoding of protists also presents some challenges, as documented by Pawlowski et al., 2012.
Coordination of global activities in DNA Barcoding is now managed via the Consortium for the Barcode of Life (CBOL). Vouchered DNA sequences are deposited in the publicly accessible Barcode of Life Data Systems (BOLD) database which, as of June 2017, contained nearly 5,500,000 barcode sequences from over 265,000 species of animals, plants, and fungi.
Choice of locus
A desirable locus for DNA barcoding should be standardized (so that large databases of sequences for that locus can be developed), present in most of the taxa of interest and sequenceable without species-specific PCR primers, short enough to be easily sequenced with current technology, and provide a large variation between species yet a relatively small amount of variation within a species.
Although several loci have been suggested, a common set of standardized regions were selected by the respective committees of COBOL:
- For animals and many other eukaryotes, the mitochondrial COI gene
- For plants, the concatenation of the rbcL and matK chloroplast genes. These provide poor resolution for land plants, and a call was made for regions to be assessed that could complement rbcL and matK.
- For fungi, the internal transcribed spacer (ITS) region
For protists, a final recommendation has not yet been made; a 2012 Working Group report suggests that a 2-stage approach will most likely be required, using a "pre-barcode" based on 18S rDNA followed by a yet to be defined second test according to the result of the first (additional details given below).
DNA barcoding of animals is based on a relatively simple concept. All eukaryote cells contain mitochondria, and animal mitochondrial DNA (mtDNA) has a relatively fast mutation rate, resulting in the generation of diversity within and between populations over relatively short evolutionary timescales (thousands of generations). Typically, in animals, a single mtDNA genome is transmitted to offspring by each breeding female, and the genetic effective population size is proportional to the number of breeding females. This contrasts with the nuclear genome, which is around 100 000 times larger, where males and females each contribute two full genomes to the gene pool and effective size is therefore proportional to twice the total population size. This reduction in effective population size leads to more rapid sorting of mtDNA gene lineages within and among populations through time, due to variance in fecundity among individuals (the principle of coalescence). The combined effect of higher mutation rates and more rapid sorting of variation usually results in divergence of mtDNA sequences among species and a comparatively small variance within species.
Exceptions, where mtDNA fails as a test of species identity, can occur through occasional recombination (direct evidence for recombination in mtDNA is available in some bivalves such as Mytilus but it is suspected that it may be more widespread) and through occurrences of hybridization. Male-killing microorganisms, cytoplasmic incompatibility-inducing symbionts (e.g., Wolbachia), as well as heteroplasmy, where an individual carries two or more mtDNA sequences, may affect patterns of mtDNA diversity within species, although these do not necessarily result in bar-coding failure. Occasional horizontal gene transfer (such as via cellular symbionts), or other "reticulate" evolutionary phenomena in a lineage can lead to misleading results (i.e., it is possible for two different species to share mtDNA). In particular, mtDNA seems to be particularly prone to interspecific introgression  probably due to difference between sexes in mate-choice and dispersal. Additionally, some species may carry divergent mtDNA lineages segregating within populations, often due to historical geographic structure, where these divergent lineages do not reflect species boundaries.
A 2017 study by Rach et al. in the dragonflies and the damselflies (Odonata), a basal group of insects, found that the "standard" (Folmer) region of the COI gene was sub-optimal for species resolution in that group, and that a different portion of the same gene, which they termed COIB, showed higher success in discriminating sister taxa at different taxonomic levels. These authors therefore suggested that a layered barcode approach, i.e. adding a second, a third or even more additional markers to enhance the discrimination potential, may be desirable, particularly in metabarcoding studies where the taxonomic composition within the samples may not be known in advance.
In Cnidaria, where the COI gene has been found to be unsuitable on account of its slow rate of evolution in that group, more success has been reported using a combination of COI plus a short, adjacent intergenic region (igr1) plus a fragment of the octocoral‐specific mitochondrial protein‐coding gene, msh1 in octocorals, and the 16S mitochondrial ribosomal RNA gene in pelagic forms. In sponges, the other major non-Bilaterian animal group, congeneric species are difficult to amplify or separate with the standard COI barcoding fragment, and data compilation and study is presently focussed on the ribosomal RNA 28S C-Region.
Barcoding flowering plants
The use of the COI sequence is not appropriate in plants because of slower rate of cytochrome c oxidase I gene evolution in higher plants than in animals. A series of experiments was then conducted to find a more suitable region of the genome for use in the DNA barcoding of flowering plants (or the larger group of land plants). Nuclear internal transcribed spacer region and the plastid trnH-psbA intergenic spacer; other researchers advocated other regions such as matK.
Two chloroplast genes, the combination of rbcL and matK have been proposed as a barcode for plants. Adding the nuclear internal transcribed spacer ITS2 region was proposed to provide better resolution between species. The chloroplast region ycf1 may be a more suitable gene.
As noted above, the current, officially approved barcoding locus for fungi is the ITS region, chosen from a group of six candidates (SSU, LSU, ITS, RPB1, RPB2, MCM7) as the most broadly applicable across major fungal lineages. However, the ITS region has been noted as not working well in some highly speciose genera such as Aspergillus, Cladosporium, Fusarium, Penicillium and Trichoderma, since these taxa have narrow or no barcode gaps in their ITS regions; it may therefore be necessary to sequence one or more single-copy protein-coding genes as a secondary barcode marker for certain fungal genera and/or lineages in order to obtain the most precise identifications at the species level. Stielow et al. (2015) also discuss the applicability of a number of potential secondary fungal DNA barcodes including TEF1α, TOPI, PGK and LNS2 in particular groups.
The Protist Working Group (ProWG) of the Consortium for the Barcode of Life (CBOL) reported that for protists—a "convenience" group of mainly single-celled eukaryotes representing many diverse lineages presently characterized as a range of "supergroups"—a 2-stage strategy is recommended: first, a preliminary identification using a universal eukaryotic barcode, called the pre-barcode, proposed to be the ∼500 base pair variable V4 region of 18S rDNA, followed by a second, group-specific barcode yet to be fully defined, for which stated possibilities include 28S rDNA, ITS rDNA, 18S rDNA, COI, rbcL, SL RNA and perhaps more.
DNA sequence databases like GenBank contain many sequences that are not tied to vouchered specimens (for example, herbarium specimens, cultured cell lines, or sometimes images). This is problematic in the face of taxonomic issues such as whether several species should be split or combined, or whether past identifications were sound. Therefore, best practice for DNA barcoding is to sequence vouchered specimens.
Identification of birds
In an effort to find a relationship between traditional species boundaries established by taxonomy and those inferred by DNA barcoding, Hebert and co-workers sequenced DNA barcodes of 260 of the 667 bird species that breed in North America (Hebert et al. 2004a). They found that every single one of the 260 species had a different COI sequence. 130 species were represented by two or more specimens; in all of these species, COI sequences were either identical or were most similar to sequences of the same species. COI variations between species averaged 7.93%, whereas variation within species averaged 0.43%. In four cases there were deep intraspecific divergences, indicating possible new species. Three out of these four polytypic species are already split into two by some taxonomists. Hebert et al.'s (2004a) results reinforce these views and strengthen the case for DNA barcoding. Hebert et al. also proposed a standard sequence threshold to define new species, this threshold, the so-called "barcoding gap", was defined as 10 times the mean intraspecific variation for the group under study.
Identification of fish
The Fish Barcode of Life Initiative (FISH-BOL), is a global effort to coordinate an assembly of a standardised DNA barcode library for all fish species, one that is derived from voucher specimens with authoritative taxonomic identifications. The benefits of barcoding fishes include facilitating species identification for all potential users, including taxonomists; highlighting specimens that represent a range expansion of known species; flagging previously unrecognized species; and perhaps most importantly, enabling identifications where traditional methods are not applicable. An example is the possible identification of groupers causing Ciguatera fish poisoning from meal remnants.
Since its inception in 2005 FISH-BOL has been creating a valuable public resource in the form of an electronic database containing DNA barcodes for almost 10000 species, images, and geospatial coordinates of examined specimens. The database contains linkages to voucher specimens, information on species distributions, nomenclature, authoritative taxonomic information, collateral natural history information and literature citations. FISH-BOL thus complements and enhances existing information resources, including the Catalog of Fishes, FishBase and various genomics databases .
Delimiting cryptic species
The next major study into the efficacy of DNA barcoding was focused on the neotropical skipper butterfly, Astraptes fulgerator at the Area de Conservación de Guanacaste (ACG) in north-western Costa Rica. This species was already known as a cryptic species complex, due to subtle morphological differences, as well as an unusually large variety of caterpillar food plants. However, several years would have been required for taxonomists to completely delimit species. Hebert et al. (2004b) sequenced the COI gene of 484 specimens from the ACG. This sample included "at least 20 individuals reared from each species of food plant, extremes and intermediates of adult and caterpillar color variation, and representatives" from the three major ecosystems where Astraptes fulgerator is found. Hebert et al. (2004b) concluded that Astraptes fulgerator consists of 10 different species in north-western Costa Rica. These results, however, were subsequently challenged by Brower (2006), who pointed out numerous serious flaws in the analysis, and concluded that the original data could support no more than the possibility of three to seven cryptic taxa rather than ten cryptic species. This highlights that the results of DNA barcoding analyses can be dependent upon the choice of analytical methods used by the investigators, so the process of delimiting cryptic species using DNA barcodes can be as subjective as any other form of taxonomy.
A more recent example used DNA barcoding for the identification of cryptic species included in the ongoing long-term database of tropical caterpillar life generated by Dan Janzen and Winnie Hallwachs in Costa Rica at the ACG. In 2006 Smith et al. examined whether a COI DNA barcode could function as a tool for identification and discovery for the 20 morphospecies of Belvosia  parasitoid flies (Tachinidae) that have been reared from caterpillars in ACG. Barcoding not only discriminated among all 17 highly host-specific morphospecies of ACG Belvosia, but it also suggested that the species count could be as high as 32 by indicating that each of the three generalist species might actually be arrays of highly host-specific cryptic species.
In 2007 Smith et al. expanded on these results by barcoding 2,134 flies belonging to what appeared to be the 16 most generalist of the ACG tachinid morphospecies. They encountered 73 mitochondrial lineages separated by an average of 4% sequence divergence and, as these lineages are supported by collateral ecological information, and, where tested, by independent nuclear markers (28S and ITS1), the authors therefore viewed these lineages as provisional species. Each of the 16 initially apparent generalist species were categorized into one of four patterns: (i) a single generalist species, (ii) a pair of morphologically cryptic generalist species, (iii) a complex of specialist species plus a generalist, or (iv) a complex of specialists with no remaining generalist. In sum, there remained 9 generalist species classified among the 73 mitochondrial lineages analyzed.
However, also in 2007, Whitworth et al. reported that flies in the related family Calliphoridae could not be discriminated by barcoding. They investigated the performance of barcoding in the fly genus Protocalliphora, known to be infected with the endosymbiotic bacteria Wolbachia. Assignment of unknown individuals to species was impossible for 60% of the species, and if the technique had been applied, as in the previous study, to identify new species, it would have underestimated the species number in the genus by 75%. They attributed the failure of barcoding to the non-monophyly of many of the species at the mitochondrial level; in one case, individuals from four different species had identical barcodes. The authors went on to state:
The pattern of Wolbachia infection strongly suggests that the lack of within-species monophyly results from introgressive hybridization associated with Wolbachia infection. Given that Wolbachia is known to infect between 15 and 75% of insect species, we conclude that identification at the species level based on mitochondrial sequence might not be possible for many insects.
Mwabvu et al. (2013) observed a high level of divergence (19.09% for CO1, 520 base pairs) between two morphologically indistinguishable populations of Bicoxidens flavicollis millipedes in Zimbabwe, and suggested the presence of cryptic species in Bicoxidens flavicollis.
Marine biologists have also considered the value of the technique in identifying cryptic and polymorphic species and have suggested that the technique may be helpful when associations with voucher specimens are maintained, though cases of "shared barcodes" (e.g., non-unique) have been documented in cichlid fishes and cowries
Cataloguing ancient life
Lambert et al. (2005) examined the possibility of using DNA barcoding to assess the past diversity of the Earth's biota. The COI gene of a group of extinct ratite birds, the moa, were sequenced using 26 subfossil moa bones. As with Hebert's results, each species sequenced had a unique barcode and intraspecific COI sequence variance ranged from 0 to 1.24%. To determine new species, a standard sequence threshold of 2.7% COI sequence difference was set. This value is 10 times the average intraspecies difference of North American birds, which is inconsistent with Hebert's recommendation that the threshold value be based on the group under study. Using this value, the group detected six moa species. In addition, a further standard sequence threshold of 1.24% was also used. This value resulted in 10 moa species which corresponded with the previously known species with one exception. This exception suggested a possible complex of species which was previously unidentified. Given the slow rate of growth and reproduction of moa, it is probable that the interspecies variation is rather low. On the other hand, there is no set value of molecular difference at which populations can be assumed to have irrevocably started to undergo speciation. It is safe to say, however, that the 2.7% COI sequence difference initially used was far too high.
The Moorea Biocode Project
The Moorea Biocode Project is a barcoding initiative to create the first comprehensive inventory of all non-microbial life in a complex tropical ecosystem, the island of Moorea in Tahiti. Supported by a grant from the Gordon and Betty Moore Foundation, the Moorea Biocode Project is a 3-year project that brings together researchers from the Smithsonian Institution, UC Berkeley, France’s National Center for Scientific Research (CNRS), and other partners. The outcome of the project is a library of genetic markers and physical identifiers for every species of plant, animal and fungi on the island that will be provided as a publicly available database resource for ecologists and evolutionary biologists around the world.
The software back-end to the Moore Biocode Project is Geneious Pro and two custom-developed plugins from the New Zealand-based company, Biomatters. The Biocode LIMS and Genbank Submission plugins have been made freely available to the public and users of the free Geneious Basic software will be able to access and view the Biocode database upon completion of the project, while a commercial copy of Geneious Pro is required for researchers involved in data creation and analysis.
Initial criticism and current status
In the initial years following its proposal, DNA barcoding met with spirited reaction from scientists, especially systematists, ranging from enthusiastic endorsement to vociferous opposition. For example, some stressed the fact that DNA barcoding does not provide reliable information above the species level, while others opined that it was inapplicable at the species level, but may still have merit for higher-level groups. Others resented what they saw as a gross oversimplification of the science of taxonomy. And, more practically, some suggested that recently diverged species might not be distinguishable on the basis of their COI sequences. In an early study, Funk & Omland (2003) found that some 23% of animal species were polyphyletic if their mtDNA data were accurate, indicating that using an mtDNA barcode to assign a species name to an animal would be ambiguous or erroneous in those cases (see also Meyer & Paulay, 2005). Some studies with insects suggested an equal or even greater error rate, due to the frequent lack of correlation between the mitochondrial genome and the nuclear genome or the lack of a barcoding gap (e.g., Hurst and Jiggins, 2005, Whitworth et al., 2007, Wiemers & Fiedler, 2007).
Moritz and Cicero (2004) questioned the efficacy of DNA barcoding by suggesting that other avian data is inconsistent with Hebert et al.'s interpretation, namely, Johnson and Cicero's (2004) finding that 74% of sister species comparisons fall below the 2.7% threshold suggested by Hebert et al. These criticisms are somewhat misleading considering that, of the 39 species comparisons reported by Johnson and Cicero, only 8 actually use COI data to arrive at their conclusions. Johnson and Cicero (2004) have also claimed to have detected bird species with identical DNA barcodes, however, these 'barcodes' refer to an unpublished 723-bp sequence of ND6 which has never been suggested as a likely candidate for DNA barcoding.
The criticisms given above date from the first few years following Hebert's initial (2003) papers in which the method was proposed. Writing in 2016, with 13 years elapsed since their initial proposal, Hebert and co-workers wrote:
[In animals,] DNA barcodes typically discriminate about 95% of known species; cases of compromised resolution involve sister taxa, often species that hybridize. In the many taxa where geographical variation in barcode sequences is small, a few records per species are sufficient to create an effective identification system. However, the analysis of more specimens is advantageous because it often reveals discordances that indicate misidentifications or cryptic taxa, and it also provides insights into the extent of geographical variation in barcode sequences. There are two animal phyla in which COI often fails to deliver species-level resolution, sponges and some benthic cnidarians, apparently because of their slowed rates of mitochondrial evolution. Barcoding also fails to distinguish a small fraction of species in other groups, typically sister taxa or those whose status is uncertain.
In a more recent (2018) review, M. Stoeckle and D. Thaler write:
The current field of COI barcodes is no longer fragile but neither is it complete. As of late 2016 there were close to five million COI barcodes between the GenBank and BOLD databases. Objections can now be seen in the cumulative light of these data and more than a decade’s experience. There is no longer any doubt that DNA barcodes are useful and practical. The agreement with specialists encompasses most cases in several important animal domains. Many cases where DNA barcodes and domain specialists do not agree reflect geographic splits within species or hybridization between species. Others upon further investigation been attributed to mislabeling or sequence error. Some may represent bona fide exceptions to the rule that mitochondrial sequence clusters coincide with species defined by other means. In the great majority of cases COI barcodes yield a close approximation of what specialists come up with after a lot of study. Birds are one of the best characterized of all animal groups and COI barcode clusters have been tabulated as agreeing with expert taxonomy for 94% of species.
As noted above, the current status of barcoding for vascular plants is presently both less settled and less effective than for animals. In a recent study covering most (96%) of the 5108 vascular plant species known from Canada, the three barcode markers tested (matK, ITS2 and rbcL) were all effective at discriminating genera (98%, 97% and 91%, respectively); at species level, matK delivered the highest discrimination (81%) followed by ITS2 (72%) and rbcL (44%), however the effectiveness of matK was also variable by biogeographic region, varying from 69%-87% according to the geographic origin of the plants concerned. Resolution also varied by family, with the poorest species discrimination within Canadian species of Salicaceae, Asteraceae and Fabaceae. The authors of this study did not report on the combined efficacy of either any two, or all three markers, in part due to sampling limitations, but commented that although ITS2 showed slightly lower performance, it had two important advantages (its short length making it suitable for high-throughput sequencing (HTS)-based applications, and it is readily recovered from diverse taxa, including vascular plants and fungi), and looked forward to the development of more comprehensive reference libraries of both matK and ITS2 to further assist in the identification of unknown samples.
Software for DNA barcoding requires integration of a field information management system (FIMS), laboratory information management system (LIMS), sequence analysis tools, workflow tracking to connect field data and laboratory data, database submission tools and pipeline automation for scaling up to eco-system scale projects. Geneious Pro can be used for the sequence analysis components, and the two plugins made freely available through the Moorea Biocode Project, the Biocode LIMS and Genbank Submission plugins handle integration with the FIMS, the LIMS, workflow tracking and database submission.
The Barcode of Life Data Systems (BOLD) is a web based workbench and database supporting the acquisition, storage, analysis, and publication of DNA barcode records. By assembling molecular, morphological, and distributional data, it bridges a traditional bioinformatics chasm. BOLD is the most prominently used barcoding software and is freely available to any researcher with interests in DNA barcoding. By providing specialized services, it aids the assembly of records that meet the standards needed to gain BARCODE designation in the global sequence databases. Because of its web-based delivery and flexible data security model, it is also well positioned to support projects that involve broad research alliances.
- Hebert PD, Cywinska A, Ball SL, deWaard JR (February 2003). "Biological identifications through DNA barcodes". Proceedings. Biological Sciences. 270 (1512): 313–21. doi:10.1098/rspb.2002.2218. PMC 1691236. PMID 12614582.
- Kress WJ, Wurdack KJ, Zimmer EA, Weigt LA, Janzen DH (June 2005). "Use of DNA barcodes to identify flowering plants". Proceedings of the National Academy of Sciences of the United States of America. 102 (23): 8369–74. doi:10.1073/pnas.0503123102. PMC 1142120. PMID 15928076.
- Koch, H. (2010). "Combining morphology and DNA barcoding resolves the taxonomy of Western Malagasy Liotrigona Moure, 1961" (PDF). African Invertebrates. 51 (2): 413–421. doi:10.5733/afin.051.0210.
- Seberg O, Petersen G (2009). Stout JC, ed. "How many loci does it take to DNA barcode a crocus?". PLOS One. 4 (2): e4598. doi:10.1371/journal.pone.0004598. PMC 2643479. PMID 19240801.
- Soininen EM, Valentini A, Coissac E, Miquel C, Gielly L, Brochmann C, Brysting AK, Sønstebø JH, Ims RA, Yoccoz NG, Taberlet P (August 2009). "Analysing diet of small herbivores: the efficiency of DNA barcoding coupled with high-throughput pyrosequencing for deciphering the composition of complex plant mixtures". Frontiers in Zoology. 6: 16. doi:10.1186/1742-9994-6-16. PMC 2736939. PMID 19695081.
- Folmer O, Black M, Hoeh W, Lutz R, Vrijenhoek R (October 1994). "DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates" (PDF). Molecular Marine Biology and Biotechnology. 3 (5): 294–9. PMID 7881515.
- Hebert PD, Ratnasingham S, deWaard JR (August 2003). "Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species". Proceedings. Biological Sciences. 270 Suppl 1 (Suppl 1): S96–9. doi:10.1098/rsbl.2003.0025. PMC 1698023. PMID 12952648.
- Pentinsaari M, Salmela H, Mutanen M, Roslin T (October 2016). "Molecular evolution of a widely-adopted taxonomic marker (COI) across the animal tree of life". Scientific Reports. 6: 35275. doi:10.1038/srep35275. PMID 27734964.
- Gregory TR (April 2005). "DNA barcoding does not compete with taxonomy". Nature. 434 (7037): 1067. doi:10.1038/4341067b. PMID 15858548.
- Miller SE (March 2007). "DNA barcoding and the renaissance of taxonomy". Proceedings of the National Academy of Sciences of the United States of America. 104 (12): 4775–6. doi:10.1073/pnas.0700466104. PMC 1829212. PMID 17363473.
- Pawlowski J, et al. (CBOL Protist Working Group) (2012). "Barcoding Eukaryotic Richness beyond the Animal, Plant, and Fungal Kingdoms". PLoS Biology. 10 (11): e1001419. doi:10.1371/journal.pbio.1001419. PMID 23139639.
- Chase MW, Soltis DE, Olmstead RG, Morgan D, Les DH, Mishler BD, et al. (1993). "Phylogenetics of Seed Plants: An Analysis of Nucleotide Sequences from the Plastid Gene rbcL". Annals of the Missouri Botanical Garden. 80 (3): 528. doi:10.2307/2399846. JSTOR 2399846.
- Kress WJ, Erickson DL (February 2008). "DNA barcodes: genes, genomics, and bioinformatics". Proceedings of the National Academy of Sciences of the United States of America. 105 (8): 2761–2. doi:10.1073/pnas.0800476105. PMC 2268532. PMID 18287050.
- Lahaye R, van der Bank M, Bogarin D, Warner J, Pupulin F, et al. (February 2008). "DNA barcoding the floras of biodiversity hotspots". Proceedings of the National Academy of Sciences of the United States of America. 105 (8): 2923–8. doi:10.1073/pnas.0709936105. PMC 2268561. PMID 18258745.
- Hollingsworth PM, et al. (CBOL Plant Working Group) (August 2009). "A DNA barcode for land plants". Proceedings of the National Academy of Sciences of the United States of America. 106 (31): 12794–7. doi:10.1073/pnas.0905845106. PMC 2722355. PMID 19666622.
- Dong W, Xu C, Li C, Sun J, Zuo Y, Shi S, Cheng T, Guo J, Zhou S (February 2015). "ycf1, the most promising plastid DNA barcode of land plants". Scientific Reports. 5: 8348. doi:10.1038/srep08348. PMC 4325322. PMID 25672218.
- Li DZ, Gao LM, Li HT, Wang H, Ge XJ, Liu JQ, et al. (December 2011). "Comparative analysis of a large dataset indicates that internal transcribed spacer (ITS) should be incorporated into the core barcode for seed plants". Proceedings of the National Academy of Sciences of the United States of America. 108 (49): 19641–6. doi:10.1073/pnas.1104551108. PMC 3241788. PMID 22100737.
- Schoch CL, Seifert KA, Huhndorf S, Robert V, Spouge JL, Levesque CA, Chen W (April 2012). "Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi". Proceedings of the National Academy of Sciences of the United States of America. 109 (16): 6241–6. doi:10.1073/pnas.1117018109. PMC 3341068. PMID 22454494.
- Ladoukakis ED, Zouros E (July 2001). "Direct evidence for homologous recombination in mussel (Mytilus galloprovincialis) mitochondrial DNA". Molecular Biology and Evolution. 18 (7): 1168–75. doi:10.1093/oxfordjournals.molbev.a003904. PMID 11420358.
- Tsaousis AD, Martin DP, Ladoukakis ED, Posada D, Zouros E (April 2005). "Widespread recombination in published animal mtDNA sequences". Molecular Biology and Evolution. 22 (4): 925–33. doi:10.1093/molbev/msi084. PMID 15647518.
- Melo-Ferreira J, Boursot P, Suchentrunk F, Ferrand N, Alves PC (July 2005). "Invasion from the cold past: extensive introgression of mountain hare (Lepus timidus) mitochondrial DNA into three other hare species in northern Iberia". Molecular Ecology. 14 (8): 2459–64. doi:10.1111/j.1365-294X.2005.02599.x. PMID 15969727.
- Johnstone RA, Hurst GD (1996). "Maternally inherited male-killing microorganisms may confound interpretation of mitochondrial DNA variability". Biol. J. Linn. Soc. 58 (4): 453–70. doi:10.1111/j.1095-8312.1996.tb01446.x.
- Hurst GD, Jiggins FM (August 2005). "Problems with mitochondrial DNA as a marker in population, phylogeographic and phylogenetic studies: the effects of inherited symbionts". Proceedings. Biological Sciences. 272 (1572): 1525–34. doi:10.1098/rspb.2005.3056. PMC 1559843. PMID 16048766.
- Croucher PJ, Oxford GS, Searle JB (2004). "Mitochondrial differentiation, introgression and phylogeny of species in the Tegenaria atrica group (Araneae: Agelenidae)". Biological Journal of the Linnean Society. 81: 79–89. doi:10.1111/j.1095-8312.2004.00280.x.
- Whitworth TL, Dawson RD, Magalon H, Baudry E (July 2007). "DNA barcoding cannot reliably identify species of the blowfly genus Protocalliphora (Diptera: Calliphoridae)". Proceedings. Biological Sciences. 274 (1619): 1731–9. doi:10.1098/rspb.2007.0062. PMC 2493573. PMID 17472911.
- Meier R (2008). "DNA sequences in taxonomy: Opportunities and challenges". In Wheeler Q. The new taxonomy. Boca Raton: CRC Press. pp. 85–127. ISBN 978-0-8493-9088-3.
- Rach J, Bergmann T, Paknia O, DeSalle R, Schierwater B, Hadrys H (2017). "The marker choice: Unexpected resolving power of an unexplored CO1 region for layered DNA barcoding approaches". PLOS One. 12 (4): e0174842. doi:10.1371/journal.pone.0174842. PMID 28406914.
- McFadden CS, Benayahu Y, Pante E, Thoma JN, Nevarez PA, France SC (January 2011). "Limitations of mitochondrial gene barcoding in Octocorallia". Molecular Ecology Resources. 11 (1): 19–31. doi:10.1111/j.1755-0998.2010.02875.x. PMID 21429097.
- Lindsay DJ, Grossmann MM, Nishikawa J, Bentlage B, Collins AG (2015). "DNA barcoding of pelagic cnidarians: current status and future prospects". Bulletin of the Plankton Society of Japan. 62 (1): 39–43. hdl:10088/29737.
- "Approach". The Sponge Barcoding Project. Retrieved 6 August 2018.
- Chen S, Yao H, Han J, Liu C, Song J, Shi L, Zhu Y, Ma X, Gao T, Pang X, Luo K, Li Y, Li X, Jia X, Lin Y, Leon C (January 2010). "Validation of the ITS2 region as a novel DNA barcode for identifying medicinal plant species". PLOS One. 5 (1): e8613. doi:10.1371/journal.pone.0008613. PMC 2799520. PMID 20062805.
- Raja HA, Miller AN, Pearce CJ, Oberlies NH (March 2017). "Fungal Identification Using Molecular Tools: A Primer for the Natural Products Research Community". Journal of Natural Products. 80 (3): 756–770. doi:10.1021/acs.jnatprod.6b01085. PMID 28199101.
- Stielow JB, Lévesque CA, Seifert KA, Meyer W, Iriny L, Smits D, et al. (December 2015). "One fungus, which genes? Development and assessment of universal primers for potential secondary fungal DNA barcodes". Persoonia. 35: 242–63. doi:10.3767/003158515X689135. PMID 26823635.
- Schander C, Willassen E (2005). "What can Biological Barcoding do for Marine Biology?" (PDF). Marine Biology Research. 1 (1): 79–83. doi:10.1080/17451000510018962. Archived from the original (PDF) on 2006-06-20.
- Hebert PD, Stoeckle MY, Zemlak TS, Francis CM (October 2004). "Identification of Birds through DNA Barcodes". PLoS Biology. 2 (10): e312. doi:10.1371/journal.pbio.0020312. PMID 15455034.
- Ward RD, Hanner R, Hebert PD (February 2009). "The campaign to DNA barcode all fishes, FISH-BOL". Journal of Fish Biology. 74 (2): 329–56. doi:10.1111/j.1095-8649.2008.02080.x. PMID 20735564.
- Steinke D, Hanner R (October 2011). "The FISH-BOL collaborators' protocol". Mitochondrial DNA. 22 Suppl 1: 10–4. doi:10.3109/19401736.2010.536538. PMID 21261495.
- Schoelinck C, Hinsinger DD, Dettaï A, Cruaud C, Justine JL (2014). "A phylogenetic re-analysis of groupers with applications for ciguatera fish poisoning". PLOS One. 9 (8): e98198. doi:10.1371/journal.pone.0098198. PMID 25093850.
- Becker S, Hanner R, Steinke D (October 2011). "Five years of FISH-BOL: brief status report". Mitochondrial DNA. 22 Suppl 1: 3–9. doi:10.3109/19401736.2010.535528. PMID 21271850.
- Hebert PD, Penton EH, Burns JM, Janzen DH, Hallwachs W (October 2004). "Ten species in one: DNA barcoding reveals cryptic species in the neotropical skipper butterfly Astraptes fulgerator". Proceedings of the National Academy of Sciences of the United States of America. 101 (41): 14812–7. doi:10.1073/pnas.0406166101. PMC 522015. PMID 15465915.
- Brower AVZ (2006). "Problems with DNA barcodes for species delimitation: 'ten species' of Astraptes fulgerator reassessed (Lepidoptera: Hesperiidae)". Systematics and Biodiversity. 4 (2): 127–32. doi:10.1017/S147720000500191X.
- Janzen DH, Hallwachs W (2009). "Dynamic database for an inventory of the macrocaterpillar fauna, and its food plants and parasitoids". Area de Conservacion Guanacaste (ACG), northwestern Costa Rica. Retrieved 2018-09-09.
- Smith MA, Woodley NE, Janzen DH, Hallwachs W, Hebert PD (March 2006). "DNA barcodes reveal cryptic host-specificity within the presumed polyphagous members of a genus of parasitoid flies (Diptera: Tachinidae)". Proceedings of the National Academy of Sciences of the United States of America. 103 (10): 3657–62. doi:10.1073/pnas.0511318103. PMID 16505365.
- Smith MA, Wood DM, Janzen DH, Hallwachs W, Hebert PD (March 2007). "DNA barcodes affirm that 16 species of apparently generalist tropical parasitoid flies (Diptera, Tachinidae) are not all generalists". Proceedings of the National Academy of Sciences of the United States of America. 104 (12): 4967–72. doi:10.1073/pnas.0700050104. PMID 17360352.
- Mwabvu T, Lamb J, Slotow R, Hamer M, Barraclough D (2013). "Is millipede taxonomy based on gonopod morphology too inclusive? Observations on genetic variation and cryptic speciation in Bicoxidens flavicollis (Diplopoda: Spirostreptida: Spirostreptidae)". African Invertebrates. 54 (2): 349–356. Archived from the original on 2013-10-21.
- Lambert DM, Baker A, Huynen L, Haddrath O, Hebert PD, Millar CD (2005). "Is a large-scale DNA-based inventory of ancient life possible?" (PDF fulltext). The Journal of Heredity. 96 (3): 279–84. doi:10.1093/jhered/esi035. PMID 15731217.
- Allison Proffitt (November 30, 2010). "LIMS Made Freely Available to DNA Barcoding Community". Bio-IT World.
- Rubinoff D, Cameron S, Will K (2006). "A genomic perspective on the shortcomings of mitochondrial DNA for "barcoding" identification". The Journal of Heredity. 97 (6): 581–94. doi:10.1093/jhered/esl036. PMID 17135463.
- Ebach MC, Carvalho MR (2010). "Anti-intellectualism in the DNA Barcoding Enterprise". Zoologia (Curitiba). 27 (2): 165–178. doi:10.1590/s1984-46702010000200003.
- Kerr KC, Stoeckle MY, Dove CJ, Weigt LA, Francis CM, Hebert PD (July 2007). "Comprehensive DNA barcode coverage of North American birds" (PDF). Molecular Ecology Notes. 7 (4): 535–543. doi:10.1111/j.1471-8286.2007.01670.x. PMC 2259444. PMID 18784793.
- Funk DJ, Omland KE (2003). "Species-level paraphyly and polyphyly: frequency, causes, and consequences, with insights from animal mitochondrial DNA". Annu Rev Ecol Syst. 34: 397–423. doi:10.1146/annurev.ecolsys.34.011802.132421.
- Meyer CP, Paulay G (December 2005). "DNA barcoding: error rates based on comprehensive sampling". PLoS Biology. 3 (12): e422. doi:10.1371/journal.pbio.0030422. PMC 1287506. PMID 16336051.
- Wiemers M, Fiedler K (March 2007). "Does the DNA barcoding gap exist? - a case study in blue butterflies (Lepidoptera: Lycaenidae)". Frontiers in Zoology. 4 (1): 8. doi:10.1186/1742-9994-4-8. PMC 1838910. PMID 17343734.
- Moritz C, Cicero C (October 2004). "DNA barcoding: promise and pitfalls". PLoS Biology. 2 (10): e354. doi:10.1371/journal.pbio.0020354. PMC 519004. PMID 15486587.
- Johnson NK, Cicero C (May 2004). "New mitochondrial DNA data affirm the importance of Pleistocene speciation in North American birds". Evolution; International Journal of Organic Evolution. 58 (5): 1122–30. doi:10.1554/03-283. PMID 15212392.
- Hebert PD, Hollingsworth PM, Hajibabaei M (September 2016). "From writing to reading the encyclopedia of life". Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 371 (1702): 20150321. doi:10.1098/rstb.2015.0321. PMID 27481778.
- Stoeckle MY, Thaler DS (2018). "Why should mitochondria define species?". Human Evolution. 33 (1–2): 1–30. doi:10.14673/HE2018121037.
- Braukmann TW, Kuzmina ML, Sills J, Zakharov EV, Hebert PD (2017). "Testing the Efficacy of DNA Barcodes for Identifying the Vascular Plants of Canada". PLOS One. 12 (1): e0169515. doi:10.1371/journal.pone.0169515. PMC 5224991. PMID 28072819.