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{{Hatnote|Not to be confused with the DNA barcode involved in [[optical mapping]] of DNA, nor with the [[antibody barcoding]] used to identify proteins}}
''Not to be confused with the DNA barcode involved in [[optical mapping]] of DNA.''
{{short description|A taxonomic method that uses a short genetic marker in an organism's DNA to identify it as belonging to a particular species}}
'''DNA barcoding''' is a [[Taxonomy (biology)|taxonomic]] method that uses a designated portion of a specific gene or genes (proposed to be analogous to a [[barcode]]) to identify an organism to [[species]].<ref name="Hebert2003">{{cite journal | vauthors = Hebert PD, Cywinska A, Ball SL, deWaard JR | title = Biological identifications through DNA barcodes | journal = Proceedings of the Royal Society of London. Series B: Biological Sciences| volume = 270 | issue = 1512 | pages = 313–21 | date = February 2003 | pmid = 12614582 | pmc = 1691236 | doi = 10.1098/rspb.2002.2218 }}</ref> These "barcodes" are sometimes used in an effort to identify unknown species, parts of an organism, or simply to catalog as many extant taxa as possible.<ref>{{cite journal | last1 = Koch | first1 = H. | year = 2010 | title = Combining morphology and DNA barcoding resolves the taxonomy of Western Malagasy ''Liotrigona'' Moure, 1961 | url = http://www.africaninvertebrates.org.za/Koch_2010_51_2_474.aspx][http://www.tb1.ethz.ch/PublicationsEO/PDFpapers/Koch_AFRICAN_INVERTEBRATES_2010_51_413-421.pdf | journal = [[African Invertebrates]] | volume = 51 | issue = 2| pages = 413–421 | doi=10.5733/afin.051.0210}}</ref>


<br />''<nowiki/>''
The most commonly used barcode region for animals and some [[protist]]s is found in mtDNA, a segment 658 [[base pair]] portion of the [[Cytochrome c oxidase subunit I|cytochrome oxidase I]] (COI or [[Cytochrome c oxidase subunit I|COX1]]) gene. In plants, the cytochrome c oxidase I gene evolves too slowly to be of value for barcoding, so [[RuBisCO|rbcL]] and others are used instead.<ref>{{cite journal | title = A DNA barcode for land plants | journal = Proceedings of the National Academy of Sciences| volume = 106 | issue = 31 | pages = 12794–7 | date = August 2009 | pmid = 19666622 | pmc = 2722355 | doi = 10.1073/pnas.0905845106 | last1 = Hollingsworth | first1 = P. M. | last2 = Forrest | first2 = L. L. | last3 = Spouge | first3 = J. L. | last4 = Hajibabaei | first4 = M. | last5 = Ratnasingham | first5 = S. | last6 = Van Der Bank | first6 = M. | last7 = Chase | first7 = M. W. | last8 = Cowan | first8 = R. S. | last9 = Erickson | first9 = D. L. | last10 = Fazekas | first10 = A. J. | last11 = Graham | first11 = S. W. | last12 = James | first12 = K. E. | last13 = Kim | first13 = K.-J. | last14 = Kress | first14 = W. J. | last15 = Schneider | first15 = H. | last16 = Van Alphenstahl | first16 = J. | last17 = Barrett | first17 = S. C.H. | last18 = Van Den Berg | first18 = C. | last19 = Bogarin | first19 = D. | last20 = Burgess | first20 = K. S. | last21 = Cameron | first21 = K. M. | last22 = Carine | first22 = M. | last23 = Chacon | first23 = J. | last24 = Clark | first24 = A. | last25 = Clarkson | first25 = J. J. | last26 = Conrad | first26 = F. | last27 = Devey | first27 = D. S. | last28 = Ford | first28 = C. S. | last29 = Hedderson | first29 = T. A.J. | last30 = Hollingsworth | first30 = M. L. | displayauthors = 29 }}</ref> The [[Internal transcribed spacer]] (ITS) [[Ribosomal RNA|rRNA]] gene is often used to create barcodes for fungi and more recently in plants.<ref>{{cite journal | vauthors = Schoch CL, Seifert KA, Huhndorf S, Robert V, Spouge JL, Levesque CA, Chen W | collaboration = Fungal Barcoding Consortium | title = Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi | journal = Proceedings of the National Academy of Sciences| volume = 109 | issue = 16 | pages = 6241–6 | date = April 2012 | pmid = 22454494 | pmc = 3341068 | doi = 10.1073/pnas.1117018109 }}</ref><ref name=plant-nrits2/> Barcoding of [[protists]] is challenging, as documented by Pawlowski ''et al.'', 2012.<ref name="Pawlowski_et_al">{{cite journal | vauthors = Pawlowski J, Audic S, Adl S, Bass D, Belbahri L, Berney C, Bowser SS, Cepicka I, Decelle J, Dunthorn M, Fiore-Donno AM, Gile GH, Holzmann M, Jahn R, Jirků M, Keeling PJ, Kostka M, Kudryavtsev A, Lara E, Lukeš J, Mann DG, Mitchell EA, Nitsche F, Romeralo M, Saunders GW, Simpson AG, Smirnov AV, Spouge JL, Stern RF, Stoeck T, Zimmermann J, Schindel D, de Vargas C | display-authors = 6 | title = CBOL protist working group: barcoding eukaryotic richness beyond the animal, plant, and fungal kingdoms | journal = PLoS Biology | volume = 10 | issue = 11 | pages = e1001419 | year = 2012 | pmid = 23139639 | pmc = 3491025 | doi = 10.1371/journal.pbio.1001419 | collaboration = CBOL Protist Working Group }}</ref>


'''DNA barcoding''' is a method of species identification using a short section of [[DNA]] from a specific [[gene]] or genes. That DNA section (also called "[[DNA sequence|sequence]]") can be used to identify an organism; in the same way as a supermarket scanner uses the familiar black stripes of the [[Universal Product Code|UPC barcode]] to identify a purchase<ref>{{Cite web|url=http://www.ibol.org/phase1/about-us/what-is-dna-barcoding/|title=What is DNA Barcoding? – iBOL|website=www.ibol.org|access-date=2019-03-26}}</ref>. These "barcodes" are sometimes used in an effort to identify unknown [[species]], parts of an organism, or simply to catalog as many [[Taxon|taxa]] as possible.
Applications of DNA barcoding include: identifying plant leaves even when flowers or fruit are not available, identifying [[Pollen DNA barcoding|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<ref>{{cite journal | vauthors = Soininen EM, Valentini A, Coissac E, Miquel C, Gielly L, Brochmann C, Brysting AK, Sønstebø JH, Ims RA, Yoccoz NG, Taberlet P | title = Analysing diet of small herbivores: the efficiency of DNA barcoding coupled with high-throughput pyrosequencing for deciphering the composition of complex plant mixtures | journal = Frontiers in Zoology | volume = 6 | pages = 16 | date = August 2009 | pmid = 19695081 | pmc = 2736939 | doi = 10.1186/1742-9994-6-16 }}</ref> and identifying products in commerce (for example, herbal supplements, wood, or skins and other animal parts).<ref name="Kress" />


Different gene regions are used to identify the different organismal groups using barcoding. The most commonly used barcode region for animals and some [[Protist|protists]] is a portion of the [[Cytochrome c oxidase subunit I|cytochrome oxidase I]] (COI or [[Cytochrome c oxidase subunit I|COX1]]) gene, found in [[mitochondrial DNA]]. Other genes suitable for DNA barcoding are the [[Internal transcribed spacer]] (ITS) [[Ribosomal RNA|rRNA]] often used for fungi and [[RuBisCO]] used for plants<ref>{{Cite journal|last=Schoch|first=C. L.|last2=Seifert|first2=K. A.|last3=Huhndorf|first3=S.|last4=Robert|first4=V.|last5=Spouge|first5=J. L.|last6=Levesque|first6=C. A.|last7=Chen|first7=W.|last8=Fungal Barcoding Consortium|last9=Fungal Barcoding Consortium Author List|date=2012-04-17|title=Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi|url=http://www.pnas.org/cgi/doi/10.1073/pnas.1117018109|journal=Proceedings of the National Academy of Sciences|language=en|volume=109|issue=16|pages=6241–6246|doi=10.1073/pnas.1117018109|issn=0027-8424|pmc=PMC3341068|pmid=22454494}}</ref><ref>{{Cite journal|last=CBOL Plant Working Group|last2=Hollingsworth|first2=P. M.|last3=Forrest|first3=L. L.|last4=Spouge|first4=J. L.|last5=Hajibabaei|first5=M.|last6=Ratnasingham|first6=S.|last7=van der Bank|first7=M.|last8=Chase|first8=M. W.|last9=Cowan|first9=R. S.|date=2009-08-04|title=A DNA barcode for land plants|url=http://www.pnas.org/cgi/doi/10.1073/pnas.0905845106|journal=Proceedings of the National Academy of Sciences|language=en|volume=106|issue=31|pages=12794–12797|doi=10.1073/pnas.0905845106|issn=0027-8424}}</ref>. [[Microorganism|Microorganisms]] are detected using different gene regions. The [[16S RNA|16S rRNA]] gene for example is widely used in identification of prokaryotes, whereas the [[18S ribosomal RNA|18S rRNA]] gene is mostly used for detecting microbial [[Eukaryote|eukaryotes]]. These gene regions are chosen because they have less intraspecific (within species) variation than interspecific (between species) variation, which is known as the "Barcoding Gap" <ref>{{Cite journal|last=Paulay|first=Gustav|last2=Meyer|first2=Christopher P.|date=2005-11-29|title=DNA Barcoding: Error Rates Based on Comprehensive Sampling|url=https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.0030422|journal=PLOS Biology|language=en|volume=3|issue=12|pages=e422|doi=10.1371/journal.pbio.0030422|issn=1545-7885|pmc=PMC1287506|pmid=16336051}}</ref>.
==Background==
DNA barcoding was proposed as a standardized method for identifying species, as well as potentially allocating unknown sequences to higher taxa such as orders and phyla, in a 2003 paper by [[Paul D.N. Hebert]] et al. from the [[University of Guelph]], [[Ontario]], [[Canada]]. Hebert and his colleagues demonstrated the utility of the cytochrome ''c'' oxidase I (COI) gene, first utilized by Folmer et al. in 1994, using their published [[Primer (molecular biology)|DNA primers]] as a tool for phylogenetic analyses at the species levels,<ref name="pmid7881515">{{cite journal | vauthors = Folmer O, Black M, Hoeh W, Lutz R, Vrijenhoek R | title = DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates | journal = Molecular Marine Biology and Biotechnology | volume = 3 | issue = 5 | pages = 294–9 | date = October 1994 | pmid = 7881515 | doi = | url = https://www.mbari.org/wp-content/uploads/2016/01/Folmer_94MMBB.pdf }}</ref> as a suitable discriminatory tool between metazoans.<ref name="Hebert2003" /> 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.


Some applications of DNA barcoding include: identifying plant leaves even when flowers or fruits are not available; identifying [[Pollen DNA barcoding|pollen]] collected on the bodies of pollinating animals; identifying insect larvae which may have fewer diagnostic characters than adults; or investigating the diet of an animal based on its stomach content, saliva or feces<ref>{{Cite journal|last=Soininen|first=Eeva M|last2=Valentini|first2=Alice|last3=Coissac|first3=Eric|last4=Miquel|first4=Christian|last5=Gielly|first5=Ludovic|last6=Brochmann|first6=Christian|last7=Brysting|first7=Anne K|last8=Sønstebø|first8=Jørn H|last9=Ims|first9=Rolf A|date=2009|title=Analysing diet of small herbivores: the efficiency of DNA barcoding coupled with high-throughput pyrosequencing for deciphering the composition of complex plant mixtures|url=http://frontiersinzoology.biomedcentral.com/articles/10.1186/1742-9994-6-16|journal=Frontiers in Zoology|language=en|volume=6|issue=1|pages=16|doi=10.1186/1742-9994-6-16|issn=1742-9994|pmc=PMC2736939|pmid=19695081}}</ref>. When barcoding is used to identify organisms from a sample containing DNA from more than one organism, the term [[DNA metabarcoding]] is used<ref>{{Cite journal|last=Creer|first=Simon|last2=Deiner|first2=Kristy|last3=Frey|first3=Serita|last4=Porazinska|first4=Dorota|last5=Taberlet|first5=Pierre|last6=Thomas|first6=W. Kelley|last7=Potter|first7=Caitlin|last8=Bik|first8=Holly M.|date=2016|editor-last=Freckleton|editor-first=Robert|title=The ecologist's field guide to sequence-based identification of biodiversity|url=http://doi.wiley.com/10.1111/2041-210X.12574|journal=Methods in Ecology and Evolution|language=en|volume=7|issue=9|pages=1008–1018|doi=10.1111/2041-210X.12574|via=}}</ref><ref>{{Cite web|url=https://www.sciencedirect.com/science/article/pii/S0065250418300011?via%3Dihub|title=ScienceDirect|website=www.sciencedirect.com|doi=10.1016/bs.aecr.2018.01.001|access-date=2019-03-29}}</ref>, e.g. [[Algae DNA barcoding|DNA metabarcoding]] of diatom communities in rivers and streams, which is used to assess water quality<ref>{{Cite journal|last=Vasselon|first=Valentin|last2=Rimet|first2=Frédéric|last3=Tapolczai|first3=Kálmán|last4=Bouchez|first4=Agnès|date=2017|title=Assessing ecological status with diatoms DNA metabarcoding: Scaling-up on a WFD monitoring network (Mayotte island, France)|url=http://dx.doi.org/10.1016/j.ecolind.2017.06.024|journal=Ecological Indicators|volume=82|pages=1–12|doi=10.1016/j.ecolind.2017.06.024|issn=1470-160X|via=}}</ref>.
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."<ref name="Hebert2003" />
[[File:DNA_Barcoding.png|thumb|614x614px|DNA barcoding scheme]]


== Background ==
The "Folmer region" of the COI gene is commonly used to distinction taxa based on its patterns of variation at the DNA level, the relative ease of retrieving the sequence, and variability mixed with conservation between species.<ref>{{cite journal | vauthors = Pentinsaari M, Salmela H, Mutanen M, Roslin T | title = Molecular evolution of a widely-adopted taxonomic marker (COI) across the animal tree of life | journal = Scientific Reports | volume = 6 | pages = 35275 | date = October 2016 | pmid = 27734964 | pmc = 5062346 | doi = 10.1038/srep35275 | bibcode = 2016NatSR...635275P }}</ref> Global DNA barcoding was initially regarded as a "big science" programme<ref name="Gregory2005">{{cite journal | vauthors = Gregory TR | title = DNA barcoding does not compete with taxonomy | journal = Nature | volume = 434 | issue = 7037 | pages = 1067 | date = April 2005 | pmid = 15858548 | doi = 10.1038/4341067b | bibcode = 2005Natur.434.1067G }}</ref> and even as the renaissance of taxonomy.<ref name="miller2007" />


DNA barcoding techniques were developed from early DNA sequencing work on microbial communities using the 5S [[Ribosomal RNA|rRNA]] gene<ref>{{Cite book|url=http://worldcat.org/oclc/678728346|title=Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya.|last=L|first=Woese, C R Kandler, O Wheelis, M|oclc=678728346}}</ref>. In 2003, specific methods and terminology of modern DNA barcoding were proposed as a standardized method for identifying species, as well as potentially allocating unknown sequences to higher taxa such as orders and phyla, in a paper by [[Paul D.N. Hebert]] et al. from the [[University of Guelph]], [[Ontario]], [[Canada]]<ref name=":11">{{Cite journal|last=Hebert|first=Paul D. N.|last2=Cywinska|first2=Alina|last3=Ball|first3=Shelley L.|last4=deWaard|first4=Jeremy R.|date=2003-02-07|title=Biological identifications through DNA barcodes|url=http://www.royalsocietypublishing.org/doi/10.1098/rspb.2002.2218|journal=Proceedings of the Royal Society of London. Series B: Biological Sciences|language=en|volume=270|issue=1512|pages=313–321|doi=10.1098/rspb.2002.2218|issn=1471-2954|pmc=PMC1691236|pmid=12614582}}</ref>. Hebert and his colleagues demonstrated the utility of the cytochrome ''c''oxidase I (COI) gene, first utilized by Folmer et al. in 1994, using their published [[Primer (molecular biology)|DNA primers]] as a tool for phylogenetic analyses at the species levels<ref name=":11" /> as a suitable discriminatory tool between metazoan invertebrates<ref>{{Cite journal|last=Folmer|first=O.|last2=Black|first2=M.|last3=Hoeh|first3=W.|last4=Lutz|first4=R.|last5=Vrijenhoek|first5=R.|date=1994-10|title=DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates|url=https://www.ncbi.nlm.nih.gov/pubmed/7881515|journal=Molecular Marine Biology and Biotechnology|volume=3|issue=5|pages=294–299|issn=1053-6426|pmid=7881515}}</ref>. The "Folmer region" of the COI gene is commonly used for distinction between taxa based on its patterns of variation at the DNA level. The relative ease of retrieving the sequence, and variability mixed with conservation between species, are some of the benefits of COI. 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".
Global activities in DNA Barcoding are coordinated by the [http://ibol.org/ International Barcode of Life Consortium] (iBOL). The primary analytical unit for the iBOL consortium is the [http://ccdb.ca/ Canadian Centre for DNA Barcoding] (CCDB) having generated over 75% of all available DNA barcode records<ref>{{Cite web|url=http://ibol.org/resources/sequencing-facility/|title=Sequencing Facility|website=International Barcode of Life|language=en-US|access-date=2019-01-24}}</ref> while the [[Barcode of Life Data Systems]] (BOLD)<ref>{{Cite journal|last=Ratnasingham|first=Sujeevan|last2=Hebert|first2=Paul D. N.|date=2007|title=bold: The Barcode of Life Data System (http://www.barcodinglife.org)|journal=Molecular Ecology Notes|language=en|volume=7|issue=3|pages=355–364|doi=10.1111/j.1471-8286.2007.01678.x|issn=1471-8286|pmc=1890991|pmid=18784790}}</ref>, their primary Informatics unit, contains nearly 6.6M barcode sequences representing over 600K BINs (proxy for species<ref>{{Cite journal|last=Hebert|first=Paul D. N.|last2=Ratnasingham|first2=Sujeevan|date=2013-07-08|title=A DNA-Based Registry for All Animal Species: The Barcode Index Number (BIN) System|journal=PLOS ONE|language=en|volume=8|issue=7|pages=e66213|doi=10.1371/journal.pone.0066213|issn=1932-6203|pmc=3704603|pmid=23861743|bibcode=2013PLoSO...866213R}}</ref>) of animals, plants, and fungi, and [[National Center for Biotechnology Information|NCBI]]. Both these units are housed at the [http://biodiversitygenomics.net/ Centre for Biodiversity Genomics] in Guelph, Ontario, Canada.


*
==Methodology==
===Barcoding Metazoans ===
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 [[proportionality (mathematics)|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 (genetics)|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. [[Cytochrome c oxidase subunit I]] (COX1/COI) is the main barcode used since 2003.<ref>{{cite journal |last1=Hebert |first1=PD |last2=Cywinska |first2=A |last3=Ball |first3=SL |last4=deWaard |first4=JR |title=Biological identifications through DNA barcodes. |journal= Proceedings of the Royal Society of London. Series B: Biological Sciences|date=7 February 2003 |volume=270 |issue=1512 |pages=313–21 |doi=10.1098/rspb.2002.2218 |pmid=12614582|pmc=1691236 }}</ref>


== Methodology ==
The barcoding for animals all began with insects. In a follow-up paper to his initial 2003 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.<ref>{{cite journal | vauthors = Hebert PD, Ratnasingham S, deWaard JR | title = Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species | journal = Proceedings of the Royal Society of London. Series B: Biological Sciences| volume = 270 Suppl 1 | issue = Suppl 1 | pages = S96–9 | date = August 2003 | pmid = 12952648 | pmc = 1698023 | doi = 10.1098/rsbl.2003.0025 }}</ref> Since, success has been found barcoding field and museum specimens alike, such as in the Zahiri et al. (2014) study of 1541 species of Canadian [[Noctuoidea]] (<ref>{{cite journal | vauthors = Zahiri R, Lafontaine JD, Schmidt BC, Dewaard JR, Zakharov EV, Hebert PD | title = A transcontinental challenge--a test of DNA barcode performance for 1,541 species of Canadian Noctuoidea (Lepidoptera) | journal = PLOS ONE | volume = 9 | issue = 3 | pages = e92797 | date = 2014-03-25 | pmid = 24667847 | pmc = 3965468 | doi = 10.1371/journal.pone.0092797 | bibcode = 2014PLoSO...992797Z }}</ref>[[Lepidoptera]]). Genetic identification of aquatic insects, especially [[Mayfly|Ephemeroptera]], [[Caddisfly|Trichoptera]], and [[Plecoptera]], have been successful and are useful to distinguish subtleties among immature forms of each family as well as for to aid in bioassessment.<ref>{{cite journal | vauthors = Zhou X, Jacobus LM, DeWalt RE, Adamowicz SJ, Hebert PD | title = Ephemeroptera, Plecoptera, and Trichoptera fauna of Churchill (Manitoba, Canada): insights into biodiversity patterns from DNA barcoding. | journal = Journal of the North American Benthological Society | date = June 2010 | volume = 29 | issue = 3| pages = 814–37 | doi = 10.1899/09-121.1 |url= https://www.researchgate.net/publication/216186296 }}</ref> Barcoding of insects and other organisms have significant potential as conservation, biodiversity, and broad environmental tools.<ref>{{Cite journal | vauthors = Thomsen PF, Willerslev E |date=2015-03-01|title=Environmental DNA – An emerging tool in conservation for monitoring past and present biodiversity |journal=Biological Conservation |volume=183|pages=4–18|doi=10.1016/j.biocon.2014.11.019 }}</ref>
=== Sampling and preservation ===
Barcoding can be done from tissue from a target specimen, from a mixture of organisms (bulk sample), or from DNA present in environmental samples (e.g. water or soil). The methods for sampling, preservation or analysis differ between those different types of sample.


'''Tissue samples'''
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 [[bivalve]]s such as ''Mytilus''<ref>{{cite journal | vauthors = Ladoukakis ED, Zouros E | title = Direct evidence for homologous recombination in mussel (Mytilus galloprovincialis) mitochondrial DNA | journal = Molecular Biology and Evolution | volume = 18 | issue = 7 | pages = 1168–75 | date = July 2001 | pmid = 11420358 | doi = 10.1093/oxfordjournals.molbev.a003904 }}</ref> but it is suspected that it may be more widespread<ref>{{cite journal | vauthors = Tsaousis AD, Martin DP, Ladoukakis ED, Posada D, Zouros E | title = Widespread recombination in published animal mtDNA sequences | journal = Molecular Biology and Evolution | volume = 22 | issue = 4 | pages = 925–33 | date = April 2005 | pmid = 15647518 | doi = 10.1093/molbev/msi084 }}</ref>) and through occurrences of [[Hybrid (biology)|hybridization]].<ref>{{cite journal | vauthors = Melo-Ferreira J, Boursot P, Suchentrunk F, Ferrand N, Alves PC | title = Invasion from the cold past: extensive introgression of mountain hare (Lepus timidus) mitochondrial DNA into three other hare species in northern Iberia | journal = Molecular Ecology | volume = 14 | issue = 8 | pages = 2459–64 | date = July 2005 | pmid = 15969727 | doi = 10.1111/j.1365-294X.2005.02599.x }}</ref> Male-killing microorganisms,<ref name="JohnstoneHurst">{{cite journal |vauthors=Johnstone RA, Hurst GD |title=Maternally inherited male-killing microorganisms may confound interpretation of mitochondrial DNA variability |journal=Biol. J. Linn. Soc. |volume=58 |issue= 4|pages=453–70 |year=1996 |doi=10.1111/j.1095-8312.1996.tb01446.x}}</ref> cytoplasmic incompatibility-inducing symbionts (e.g., ''[[Wolbachia]]''<ref name="JohnstoneHurst" />), as well as [[heteroplasmy]], may affect patterns of mtDNA diversity within species, although these do not necessarily result in barcoding failure. Occasional [[horizontal gene transfer]] (such as via cellular symbionts<ref name="Hurstetal">{{cite journal | vauthors = Hurst GD, Jiggins FM | title = Problems with mitochondrial DNA as a marker in population, phylogeographic and phylogenetic studies: the effects of inherited symbionts | journal = Proceedings of the Royal Society B: Biological Sciences| volume = 272 | issue = 1572 | pages = 1525–34 | date = August 2005 | pmid = 16048766 | pmc = 1559843 | doi = 10.1098/rspb.2005.3056 }}</ref>), 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]] <ref>{{cite journal |vauthors=Croucher PJ, Oxford GS, Searle JB |title=Mitochondrial differentiation, introgression and phylogeny of species in the ''Tegenaria atrica'' group (Araneae: Agelenidae) |journal=Biological Journal of the Linnean Society |volume=81 |pages=79–89 |year=2004 |doi=10.1111/j.1095-8312.2004.00280.x |title-link=Tegenaria atrica }}</ref> 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.<ref name="Whitworthetal">{{cite journal | vauthors = Whitworth TL, Dawson RD, Magalon H, Baudry E | title = DNA barcoding cannot reliably identify species of the blowfly genus Protocalliphora (Diptera: Calliphoridae) | journal = Proceedings of the Royal Society B: Biological Sciences| volume = 274 | issue = 1619 | pages = 1731–9 | date = July 2007 | pmid = 17472911 | pmc = 2493573 | doi = 10.1098/rspb.2007.0062 }}</ref><ref name="Meier">{{cite book |last1=Meier |first1=Rudolf |chapter=DNA sequences in taxonomy: Opportunities and challenges |chapterurl={{Google books|Ykf8RALCGyUC|page=95|plainurl=yes}} |pages=85–127 |editor1-last=Wheeler |editor1-first=Quentin | name-list-format = vanc |title=The new taxonomy |publisher=CRC Press |location=Boca Raton |year=2008 |isbn=978-0-8493-9088-3 }}</ref>


To barcode a tissue sample from the target specimen, a small piece of skin, a scale, a leg or antennae is sufficient. To avoid contamination, it is necessary to sterilize used tools between samples. It is recommended to collect two samples from one specimen, one to archive, and one for the barcoding process. Sample preservation is crucial to avoid DNA degradation.
A 2017 study by Rach ''et al.'' on [[Odonata|Odonates]], specifically dragonflies ([[Dragonfly|Anisoptera]]) and the damselflies ([[Damselfly|Zygoptera]]), 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.<ref>{{cite journal | vauthors = Rach J, Bergmann T, Paknia O, DeSalle R, Schierwater B, Hadrys H | title = The marker choice: Unexpected resolving power of an unexplored CO1 region for layered DNA barcoding approaches | journal = PLOS ONE | volume = 12 | issue = 4 | pages = e0174842 | year = 2017 | pmid = 28406914 | pmc = 5390999 | doi = 10.1371/journal.pone.0174842 | bibcode = 2017PLoSO..1274842R }}</ref> These authors therefore suggested that a layered barcode approach, i.e. adding additional markers to enhance the discrimination potential in metabarcoding studies where the taxonomic composition within the samples may not be known in advance.


'''Bulk samples'''
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,<ref>{{cite journal | vauthors = McFadden CS, Benayahu Y, Pante E, Thoma JN, Nevarez PA, France SC | title = Limitations of mitochondrial gene barcoding in Octocorallia | journal = Molecular Ecology Resources | volume = 11 | issue = 1 | pages = 19–31 | date = January 2011 | pmid = 21429097 | doi = 10.1111/j.1755-0998.2010.02875.x }}</ref> and the 16S mitochondrial ribosomal RNA gene in pelagic forms.<ref>{{cite journal |last1=Lindsay |first1=Dhugal J. |last2=Grossmann |first2=Mary M. |last3=Nishikawa |first3=Jun |last4=Bentlage |first4=Bastian |last5=Collins |first5=Allen G. | name-list-format = vanc |year=2015 |hdl=10088/29737 |title=DNA barcoding of pelagic cnidarians: current status and future prospects |journal=Bulletin of the Plankton Society of Japan |volume=62 |issue=1 |pages=39–43 }}</ref> In [[sponges]], the other major non-[[Bilateria]]n 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.<ref>{{cite web |url=https://www.spongebarcoding.org/approach.php |website=The Sponge Barcoding Project |title=Approach |access-date=6 August 2018}}</ref>


A bulk sample is a type of environmental sample containing several organisms from the [[taxonomic group]] under study. The difference between bulk samples (in the sense used here) and other environmental samples is that the bulk sample usually provides good-quality and quantity of DNA<ref name=":15" />. Examples of bulk samples are aquatic macroinvertebrate sample collected by kick-net, or insect samples collected with a Malaise trap. Filtered or size-fractionated water samples containing whole organisms like unicellular eukaryotes are also sometimes defined as bulk samples. Such samples can be collected by the same techniques as used to obtain traditional samples for morphology-based identification.
=== Barcoding flowering plants ===


'''eDNA samples'''
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.<ref name="Kress">{{cite journal | vauthors = Kress WJ, Wurdack KJ, Zimmer EA, Weigt LA, Janzen DH | title = Use of DNA barcodes to identify flowering plants | journal = Proceedings of the National Academy of Sciences| volume = 102 | issue = 23 | pages = 8369–74 | date = June 2005 | pmid = 15928076 | pmc = 1142120 | doi = 10.1073/pnas.0503123102 | bibcode = 2005PNAS..102.8369K }}</ref> A series of experiments was conducted to find a more suitable region of the [[genome]] for use in the DNA barcoding of [[flowering plant]]s (or the larger group of [[land plant]]s).<ref name="kress2008">{{cite journal|vauthors=Kress WJ, Erickson DL|date=February 2008|title=DNA barcodes: genes, genomics, and bioinformatics|journal=Proceedings of the National Academy of Sciences|volume=105|issue=8|pages=2761–2|doi=10.1073/pnas.0800476105|pmc=2268532|pmid=18287050|bibcode=2008PNAS..105.2761K}}</ref>


The [[environmental DNA]] (eDNA) method is a non-invasive approach to detect and identify species through cellular debris or extracellular DNA present in environmental samples (e.g. water or soil) through barcoding or metabarcoding. The approach is based on the fact that every living organism leave DNA in the environment, and this environmental DNA can be detected even in very low abundance. Thus, for field sampling, the most crucial part is to use DNA-free material and tools on each sampling site or sample to avoid contamination, if the DNA of the target organism(s) is probably present in low quantity. On the other hand, an eDNA sample always include the DNA of whole-cell, living microorganisms, often present in large quantities. Therefore, microorganism samples taken in the natural anvironment also are called eDNA samples, but here contamination is less problematic due to the high quantity of the target organisms. The eDNA method is applied on most sample types, like water, sediment, soil, animal feces, stomach content or blood from e.g. leeches.<ref>{{Citation|last=Jelger Herder|title=Environmental DNA - a review of the possible applications for the detection of (invasive) species.|date=2014|url=http://rgdoi.net/10.13140/RG.2.1.4002.1208|publisher=RAVON|language=en|doi=10.13140/rg.2.1.4002.1208|access-date=2019-05-14|last2=A. Valentini|last3=E. Bellemain|last4=T. Dejean|last5=J.J.C.W. Van Delft|last6=P.F. Thomsen|last7=P. Taberlet}}</ref> 
Many chloroplast sequences or their combinations have been proposed as a barcode, including the trnH-psbA intergenic region<ref name="Kress"/> and the [[RuBisCO large subunit|rbcL]] + [[Maturase K|matK]] combination.<ref name="chase1993">{{cite journal | vauthors = Chase MW, Soltis DE, Olmstead RG, Morgan D, Les DH, Mishler BD, Duvall MR, Price RA, Hills HG, Qiu YL, Kron KA | display-authors = 6 | title = Phylogenetics of seed plants: an analysis of nucleotide sequences from the plastid gene rbcL. | journal = Annals of the Missouri Botanical Garden | date = January 1993 | volume = 80 | issue = 3 | pages = 528–80 | doi=10.2307/2399846 |jstor=2399846 }}</ref> Adding the nuclear internal transcribed spacer 2 (nrITS2) region was proposed to provide better resolution between species.<ref name=plant-nrits2>{{cite journal | vauthors = 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 | display-authors = 6 | title = Validation of the ITS2 region as a novel DNA barcode for identifying medicinal plant species | journal = PLOS ONE | volume = 5 | issue = 1 | pages = e8613 | date = January 2010 | pmid = 20062805 | pmc = 2799520 | doi = 10.1371/journal.pone.0008613 | bibcode = 2010PLoSO...5.8613C }}</ref> The chloroplast gene ''ycf1'' may be a more suitable source of variable regions.<ref name="Dong">{{cite journal | vauthors = Dong W, Xu C, Li C, Sun J, Zuo Y, Shi S, Cheng T, Guo J, Zhou S | title = ycf1, the most promising plastid DNA barcode of land plants | journal = Scientific Reports | volume = 5 | pages = 8348 | date = February 2015 | pmid = 25672218 | pmc = 4325322 | doi = 10.1038/srep08348 | bibcode = 2015NatSR...5E8348D }}</ref>


=== DNA extraction, amplification and sequencing ===
===Barcoding fungi===
DNA barcoding requires that DNA in the sample is extracted. Several different [[DNA extraction]] methods exist, and factors like cost, time, sample type and yield affect the selection of the optimal method.
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.<ref>{{cite journal | vauthors = Raja HA, Miller AN, Pearce CJ, Oberlies NH | title = Fungal Identification Using Molecular Tools: A Primer for the Natural Products Research Community | journal = Journal of Natural Products | volume = 80 | issue = 3 | pages = 756–770 | date = March 2017 | pmid = 28199101 | pmc = 5368684 | doi = 10.1021/acs.jnatprod.6b01085 }}</ref> 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.<ref>{{cite journal | vauthors = Stielow JB, Lévesque CA, Seifert KA, Meyer W, Iriny L, Smits D, Renfurm R, Verkley GJ, Groenewald M, Chaduli D, Lomascolo A, Welti S, Lesage-Meessen L, Favel A, Al-Hatmi AM, Damm U, Yilmaz N, Houbraken J, Lombard L, Quaedvlieg W, Binder M, Vaas LA, Vu D, Yurkov A, Begerow D, Roehl O, Guerreiro M, Fonseca A, Samerpitak K, van Diepeningen AD, Dolatabadi S, Moreno LF, Casaregola S, Mallet S, Jacques N, Roscini L, Egidi E, Bizet C, Garcia-Hermoso D, Martín MP, Deng S, Groenewald JZ, Boekhout T, de Beer ZW, Barnes I, Duong TA, Wingfield MJ, de Hoog GS, Crous PW, Lewis CT, Hambleton S, Moussa TA, Al-Zahrani HS, Almaghrabi OA, Louis-Seize G, Assabgui R, McCormick W, Omer G, Dukik K, Cardinali G, Eberhardt U, de Vries M, Robert V | display-authors = 6 | title = One fungus, which genes? Development and assessment of universal primers for potential secondary fungal DNA barcodes | journal = Persoonia | volume = 35 | issue = | pages = 242–63 | date = December 2015 | pmid = 26823635 | pmc = 4713107 | doi = 10.3767/003158515X689135 }}</ref>


Organismal or eDNA samples often contain inhibitor molecules that can affect the PCR negatively when DNA is amplified in [[polymerase chain reaction]] (PCR)<ref name=":8">{{Cite journal|last=Schrader|first=C.|last2=Schielke|first2=A.|last3=Ellerbroek|first3=L.|last4=Johne|first4=R.|date=2012|title=PCR inhibitors – occurrence, properties and removal|url=https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-2672.2012.05384.x|journal=Journal of Applied Microbiology|language=en|volume=113|issue=5|pages=1014–1026|doi=10.1111/j.1365-2672.2012.05384.x|issn=1365-2672}}</ref>. Removal of these inhibitors is crucial to ensure that high quality DNA is available for subsequent analyzing.
===Barcoding protists===
[[Protists]] is a "convenience" group of mainly single-celled eukaryotes representing many diverse lineages presently characterized as a range of "supergroups". The Protist Working Group (ProWG) of the Consortium for the Barcode of Life (CBOL) reported that for protists, 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 ribosomal RNA|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.<ref name="Pawlowski_et_al" />


[[Gene amplification|Amplification]] of the extracted DNA is a required step in DNA barcoding. Typically. only a small fragment of the total DNA material is [[Sequencing|sequenced]] (typically 400–800 [[Base pair|base pairs]])<ref name=":9">{{Cite journal|last=Savolainen|first=Vincent|last2=Cowan|first2=Robyn S|last3=Vogler|first3=Alfried P|last4=Roderick|first4=George K|last5=Lane|first5=Richard|date=2005-10-29|title=Towards writing the encyclopaedia of life: an introduction to DNA barcoding|url=http://www.royalsocietypublishing.org/doi/10.1098/rstb.2005.1730|journal=Philosophical Transactions of the Royal Society B: Biological Sciences|language=en|volume=360|issue=1462|pages=1805–1811|doi=10.1098/rstb.2005.1730|issn=0962-8436}}</ref> to obtain the DNA barcode. Amplification of eDNA material is usually focused on smaller fragment sizes (<200 base pairs), as eDNA is more likely to be fragmented than DNA material from other sources. However, some studies argue that there is no relationship between amplicon size and detection rate of eDNA<ref>{{Cite journal|last=Piggott|first=Maxine P.|date=2016|title=Evaluating the effects of laboratory protocols on eDNA detection probability for an endangered freshwater fish|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/ece3.2083|journal=Ecology and Evolution|language=en|volume=6|issue=9|pages=2739–2750|doi=10.1002/ece3.2083|issn=2045-7758|pmc=PMC4798829|pmid=27066248}}</ref><ref>{{Cite journal|last=Ma|first=Hongjuan|last2=Stewart|first2=Kathryn|last3=Lougheed|first3=Stephen|last4=Zheng|first4=Jinsong|last5=Wang|first5=Yuxiang|last6=Zhao|first6=Jianfu|date=2016|title=Characterization, optimization, and validation of environmental DNA (eDNA) markers to detect an endangered aquatic mammal|url=http://link.springer.com/10.1007/s12686-016-0597-9|journal=Conservation Genetics Resources|language=en|volume=8|issue=4|pages=561–568|doi=10.1007/s12686-016-0597-9|issn=1877-7252|via=}}</ref>.
==Vouchered specimens==
[[File:HiSeq sequencers at SciLifeLab in Uppsala.jpg|thumb|HiSeq sequencers at SciLIfeLab in Uppsala, Sweden. The picture has been taken during the excursion of SLU course PNS0169 in March 2019.]]
DNA sequence databases like GenBank contain many sequences that are not tied to [[Zoological specimen#Voucher_specimens|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.<ref name="schander2005"/><ref name="miller2007">{{cite journal | vauthors = Miller SE | title = DNA barcoding and the renaissance of taxonomy | journal = Proceedings of the National Academy of Sciences| volume = 104 | issue = 12 | pages = 4775–6 | date = March 2007 | pmid = 17363473 | pmc = 1829212 | doi = 10.1073/pnas.0700466104 | bibcode = 2007PNAS..104.4775M }}</ref>
When the DNA barcode marker region has been amplified, the next step is to sequence the marker region using [[DNA sequencing]] methods.<ref>{{Cite journal|last=Hodzic|first=Jasin|last2=Gurbeta|first2=Lejla|last3=OmanovicMiklicanin|first3=Enisa|last4=Badnjevic|first4=Almir|date=2017|title=Overview of Next-generation Sequencing Platforms Used in Published Draft Plant Genomes in Light of Genotypization of Immortelle Plant (Helichrysium Arenarium)|url=http://www.ejmanager.com/fulltextpdf.php?mno=274817|journal=Medical Archives|volume=71|issue=4|pages=288|doi=10.5455/medarh.2017.71.288-292|issn=0350-199X|pmc=PMC5585786|pmid=28974852}}</ref><ref>{{Cite journal|last=D’Amore|first=Rosalinda|last2=Ijaz|first2=Umer Zeeshan|last3=Schirmer|first3=Melanie|last4=Kenny|first4=John G.|last5=Gregory|first5=Richard|last6=Darby|first6=Alistair C.|last7=Shakya|first7=Migun|last8=Podar|first8=Mircea|last9=Quince|first9=Christopher|date=2016-01-14|title=A comprehensive benchmarking study of protocols and sequencing platforms for 16S rRNA community profiling|url=https://doi.org/10.1186/s12864-015-2194-9|journal=BMC Genomics|volume=17|issue=1|pages=55|doi=10.1186/s12864-015-2194-9|issn=1471-2164|pmc=PMC4712552|pmid=26763898}}</ref>. Many different sequencing platforms are available, and the technical development is fast.


=== Marker selection ===
==Case studies==
[[File:16S region variability.jpg|thumb|600x600px|A schematic view of primers and target region, demonstrated on 16S rRNA gene in ''Pseudomonas''. As primers, one typically selects short conserved sequences with low variability, which can thus amplify most or all species in the chosen target group. The primers are used to amplify a highly variable target region in between the two primers, which is then used for species discrimination. ''Modified from »Variable Copy Number, Intra-Genomic Heterogeneities and Lateral Transfers of the 16S rRNA Gene in Pseudomonas« by Bodilis, Josselin; Nsigue-Meilo, Sandrine; Besaury, Ludovic; Quillet, Laurent, used under CC BY, available from: <nowiki>https://www.researchgate.net/figure/Hypervariable-regions-within-the-16S-rRNA-gene-in-Pseudomonas-The-plotted-line-reflects_fig2_224832532</nowiki>.'' ]]
Markers used for DNA barcoding are called barcodes. In order to succesfully characterize species based on DNA barcodes, selection of informative DNA regions is crucial. A good DNA barcode should have low intra-specific and high inter-specific [[Genetic variability|variability]]<ref name=":11" /> and possess [[Conserved sequence|conserved]] flanking sites for developing universal [[Polymerase chain reaction|PCR]] [[Primer (molecular biology)|primers]] for wide [[Taxonomy (biology)|taxonomic]] application. The goal is to design primers that will target most or all the species in the studied group of organisms (high taxonomic resolution). The length of the barcode sequence should be short enough to be used with current sampling source, [[DNA extraction]], [[Polymerase chain reaction|amplification]] and [[DNA sequencing|sequencing]] methods<ref>{{Cite journal|last=Kress|first=W. J.|last2=Erickson|first2=D. L.|date=2008-02-26|title=DNA barcodes: Genes, genomics, and bioinformatics|url=http://www.pnas.org/cgi/doi/10.1073/pnas.0800476105|journal=Proceedings of the National Academy of Sciences|language=en|volume=105|issue=8|pages=2761–2762|doi=10.1073/pnas.0800476105|issn=0027-8424|pmc=PMC2268532|pmid=18287050}}</ref>.


Ideally, one [[gene]] sequence would be used for all taxonomic groups, from [[Virus|viruses]] to [[Plant|plants]] and [[Animal|animals]]. However, no such gene region has been found yet, so different barcodes are used for different groups of organisms<ref name=":2">{{Cite journal|last=Purty RS, Chatterjee S|first=|date=|title=DNA Barcoding: An Effective Technique in Molecular Taxonomy|url=|journal=Austin Journal of Biotechnology & Bioengineering|volume=3(1)|pages=1059|via=}}</ref>, or depending on the study question.
===Identification of birds===


For '''animals''', the most widely used barcode is [[Mitochondrion|mitochondrial]] [[Cytochrome c oxidase subunit I|cytochrome C oxidase I]] (''COI'') locus<ref name=":3">{{Cite journal|last=Hebert|first=Paul D.N.|last2=Ratnasingham|first2=Sujeevan|last3=de Waard|first3=Jeremy R.|date=2003-08-07|title=Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species|url=http://www.royalsocietypublishing.org/doi/10.1098/rsbl.2003.0025|journal=Proceedings of the Royal Society of London. Series B: Biological Sciences|language=en|volume=270|issue=suppl_1|doi=10.1098/rsbl.2003.0025|issn=1471-2954|pmc=PMC1698023|pmid=12952648}}</ref>. Additionally, other mitochondrial genes, such as [[Cytochrome b|Cytb]], [[12S ribosomal RNA|12S]] or [[16S ribosomal RNA|16S]] are also used. [[Mitochondrial DNA|Mitochondrial genes]] are preferred over [[Nuclear gene|nuclear genes]] because of their lack of [[Intron|introns]], their [[Ploidy|haploid]] mode of [[Heredity|inheritance]] and their limited [[Genetic recombination|recombination]]<ref name=":3" /><ref>{{Cite journal|last=Blaxter|first=Mark L.|date=2004-04-29|editor-last=Godfray|editor-first=H. C. J.|editor2-last=Knapp|editor2-first=S.|title=The promise of a DNA taxonomy|url=http://www.royalsocietypublishing.org/doi/10.1098/rstb.2003.1447|journal=Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences|language=en|volume=359|issue=1444|pages=669–679|doi=10.1098/rstb.2003.1447|issn=1471-2970|pmc=PMC1693355|pmid=15253352}}</ref>. Moreover, each [[Cell (biology)|cell]] has various [[Mitochondrion|mitochondria]] (up to several thousand) and each of them contains several [[circular DNA]] molecules. Mitochondria can therefore offer abundant source of DNA even when sample tissue is limited<ref name=":2" />.
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<ref name=HebertBirds>{{cite journal | vauthors = Hebert PD, Stoeckle MY, Zemlak TS, Francis CM | title = Identification of Birds through DNA Barcodes | journal = PLoS Biology | volume = 2 | issue = 10 | pages = e312 | date = October 2004 | pmid = 15455034 | pmc = 518999 | doi = 10.1371/journal.pbio.0020312 }}</ref>). 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 taxon|polytypic]] species are already split into two by some taxonomists. Hebert ''et al.'''s (2004a<ref name=HebertBirds/>) 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.


In '''plants''', however, mitochondrial genes are not appropriate for DNA barcoding because they exhibit low [[mutation rate|mutation rates]]<ref>{{Cite journal|last=Fazekas|first=Aron J.|last2=Burgess|first2=Kevin S.|last3=Kesanakurti|first3=Prasad R.|last4=Graham|first4=Sean W.|last5=Newmaster|first5=Steven G.|last6=Husband|first6=Brian C.|last7=Percy|first7=Diana M.|last8=Hajibabaei|first8=Mehrdad|last9=Barrett|first9=Spencer C. H.|date=2008-07-30|editor-last=DeSalle|editor-first=Robert|title=Multiple Multilocus DNA Barcodes from the Plastid Genome Discriminate Plant Species Equally Well|url=https://dx.plos.org/10.1371/journal.pone.0002802|journal=PLoS ONE|language=en|volume=3|issue=7|pages=e2802|doi=10.1371/journal.pone.0002802|issn=1932-6203}}</ref>. A few candidate genes have been found in the [[chloroplast]] genome, the most promising being [[maturase K]] gene (''matK'') alone or in association with other genes. Multi-[[Locus (genetics)|locus]] markers such as ribosomal [[Internal transcribed spacer|internal transcribed spacers]] (ITS DNA) along with ''matK'', ''[[RuBisCO|rbcL]]'', ''trnH'' or other genes have also been used for species identification<ref name=":2" />. The best discrimination between plant species has been achieved when using two or more chloroplast barcodes<ref>{{Cite journal|last=Kress|first=W. John|last2=Erickson|first2=David L.|date=2007-06-06|editor-last=Shiu|editor-first=Shin-Han|title=A Two-Locus Global DNA Barcode for Land Plants: The Coding rbcL Gene Complements the Non-Coding trnH-psbA Spacer Region|url=https://dx.plos.org/10.1371/journal.pone.0000508|journal=PLoS ONE|language=en|volume=2|issue=6|pages=e508|doi=10.1371/journal.pone.0000508|issn=1932-6203|pmc=PMC1876818|pmid=17551588}}</ref>.
===Identification of fish===
The [http://www.fishbol.org Fish Barcode of Life Initiative (FISH-BOL)],<ref name=WardFishBOL>{{cite journal | vauthors = Ward RD, Hanner R, Hebert PD | title = The campaign to DNA barcode all fishes, FISH-BOL | journal = Journal of Fish Biology | volume = 74 | issue = 2 | pages = 329–56 | date = February 2009 | pmid = 20735564 | doi = 10.1111/j.1095-8649.2008.02080.x }}</ref> is a global effort to coordinate the assembly of a standardised DNA barcode library for all fish species, one that is derived from voucher specimens with authoritative taxonomic identifications.<ref name=SteinkeFishBOL>{{cite journal | vauthors = Steinke D, Hanner R | title = The FISH-BOL collaborators' protocol | journal = Mitochondrial DNA | volume = 22 Suppl 1 | pages = 10–4 | date = October 2011 | pmid = 21261495 | doi = 10.3109/19401736.2010.536538 }}</ref> The benefits of [[Fish DNA barcoding|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 [[grouper]]s causing [[Ciguatera]] fish poisoning from meal remnants.<ref>{{cite journal | vauthors = Schoelinck C, Hinsinger DD, Dettaï A, Cruaud C, Justine JL | title = A phylogenetic re-analysis of groupers with applications for ciguatera fish poisoning | journal = PLOS ONE | volume = 9 | issue = 8 | pages = e98198 | year = 2014 | pmid = 25093850 | pmc = 4122351 | doi = 10.1371/journal.pone.0098198 | bibcode = 2014PLoSO...998198S }}</ref>


For '''[[bacteria]]''', the small subunit of ribosomal RNA ([[16S ribosomal RNA|16S]]) gene can be used for different taxa, as it is highly conserved<ref>{{Cite journal|last=Janda|first=J. M.|last2=Abbott|first2=S. L.|date=2007-09-01|title=16S rRNA Gene Sequencing for Bacterial Identification in the Diagnostic Laboratory: Pluses, Perils, and Pitfalls|url=http://jcm.asm.org/cgi/doi/10.1128/JCM.01228-07|journal=Journal of Clinical Microbiology|language=en|volume=45|issue=9|pages=2761–2764|doi=10.1128/JCM.01228-07|issn=0095-1137|pmc=PMC2045242|pmid=17626177}}</ref>. Some studies suggest ''[[Cytochrome c oxidase subunit I|COI]]''<ref name=":4">{{Cite journal|last=Smith|first=M. Alex|last2=Bertrand|first2=Claudia|last3=Crosby|first3=Kate|last4=Eveleigh|first4=Eldon S.|last5=Fernandez-Triana|first5=Jose|last6=Fisher|first6=Brian L.|last7=Gibbs|first7=Jason|last8=Hajibabaei|first8=Mehrdad|last9=Hallwachs|first9=Winnie|date=2012-05-02|editor-last=Badger|editor-first=Jonathan H.|title=Wolbachia and DNA Barcoding Insects: Patterns, Potential, and Problems|url=http://dx.plos.org/10.1371/journal.pone.0036514|journal=PLoS ONE|language=en|volume=7|issue=5|pages=e36514|doi=10.1371/journal.pone.0036514|issn=1932-6203|pmc=PMC3342236|pmid=22567162}}</ref>, type II [[chaperonin]] (''cpn60'')<ref name=":5">{{Cite journal|last=Links|first=Matthew G.|last2=Dumonceaux|first2=Tim J.|last3=Hemmingsen|first3=Sean M.|last4=Hill|first4=Janet E.|date=2012-11-26|editor-last=Neufeld|editor-first=Josh|title=The Chaperonin-60 Universal Target Is a Barcode for Bacteria That Enables De Novo Assembly of Metagenomic Sequence Data|url=https://dx.plos.org/10.1371/journal.pone.0049755|journal=PLoS ONE|language=en|volume=7|issue=11|pages=e49755|doi=10.1371/journal.pone.0049755|issn=1932-6203|pmc=PMC3506640|pmid=23189159}}</ref> or β subunit of [[RNA polymerase]] (''rpoB'')<ref name=":6">{{Cite journal|last=Case|first=R. J.|last2=Boucher|first2=Y.|last3=Dahllof|first3=I.|last4=Holmstrom|first4=C.|last5=Doolittle|first5=W. F.|last6=Kjelleberg|first6=S.|date=2007-01-01|title=Use of 16S rRNA and rpoB Genes as Molecular Markers for Microbial Ecology Studies|url=http://aem.asm.org/cgi/doi/10.1128/AEM.01177-06|journal=Applied and Environmental Microbiology|language=en|volume=73|issue=1|pages=278–288|doi=10.1128/AEM.01177-06|issn=0099-2240|pmc=PMC1797146|pmid=17071787}}</ref> also could serve as bacterial DNA barcodes.
Since its inception in 2005 [http://www.fishbol.org 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.<ref name=BeckerFishBOL>{{cite journal | vauthors = Becker S, Hanner R, Steinke D | title = Five years of FISH-BOL: brief status report | journal = Mitochondrial DNA | volume = 22 Suppl 1 | pages = 3–9 | date = October 2011 | pmid = 21271850 | doi = 10.3109/19401736.2010.535528 }}</ref> 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 [http://research.calacademy.org/ichthyology/catalog Catalog of Fishes], [http://www.fishbase.org FishBase] and various genomics databases .


Barcoding '''[[Fungus|fungi]]''' is more challenging, and more than one primer combination might be required<ref>{{Cite journal|last=Bellemain|first=Eva|last2=Carlsen|first2=Tor|last3=Brochmann|first3=Christian|last4=Coissac|first4=Eric|last5=Taberlet|first5=Pierre|last6=Kauserud|first6=Håvard|date=2010|title=ITS as an environmental DNA barcode for fungi: an in silico approach reveals potential PCR biases|url=http://bmcmicrobiol.biomedcentral.com/articles/10.1186/1471-2180-10-189|journal=BMC Microbiology|language=en|volume=10|issue=1|pages=189|doi=10.1186/1471-2180-10-189|issn=1471-2180}}</ref>. ''[[Cytochrome c oxidase subunit I|COI]]'' marker performs well in certain fungi groups<ref>{{Cite journal|last=Seifert|first=K. A.|last2=Samson|first2=R. A.|last3=deWaard|first3=J. R.|last4=Houbraken|first4=J.|last5=Levesque|first5=C. A.|last6=Moncalvo|first6=J.-M.|last7=Louis-Seize|first7=G.|last8=Hebert|first8=P. D. N.|date=2007-03-06|title=Prospects for fungus identification using CO1 DNA barcodes, with Penicillium as a test case|url=http://www.pnas.org/cgi/doi/10.1073/pnas.0611691104|journal=Proceedings of the National Academy of Sciences|language=en|volume=104|issue=10|pages=3901–3906|doi=10.1073/pnas.0611691104|issn=0027-8424|pmc=PMC1805696|pmid=17360450}}</ref>, but not equally well in others<ref>{{Cite journal|last=Dentinger|first=Bryn T. M.|last2=Didukh|first2=Maryna Y.|last3=Moncalvo|first3=Jean-Marc|date=2011-09-22|editor-last=Schierwater|editor-first=Bernd|title=Comparing COI and ITS as DNA Barcode Markers for Mushrooms and Allies (Agaricomycotina)|url=https://dx.plos.org/10.1371/journal.pone.0025081|journal=PLoS ONE|language=en|volume=6|issue=9|pages=e25081|doi=10.1371/journal.pone.0025081|issn=1932-6203|pmc=PMC3178597|pmid=21966418}}</ref>. Therefore, additional markers are being used, such as [[Internal transcribed spacer|ITS]] rDNA and the [[28S ribosomal RNA|large subunit of nuclear ribosomal RNA]] (LSU)<ref name=":7">{{Cite journal|last=Khaund|first=Polashree|last2=Joshi|first2=S.R.|date=2014-10|title=DNA barcoding of wild edible mushrooms consumed by the ethnic tribes of India|url=https://linkinghub.elsevier.com/retrieve/pii/S0378111914009536|journal=Gene|language=en|volume=550|issue=1|pages=123–130|doi=10.1016/j.gene.2014.08.027}}</ref>.
===Delimiting cryptic species===


Within the group of '''[[Protist|protists]]''', various barcodes have been proposed, such as the D1–D2 or D2–D3 regions of [[28S ribosomal RNA|28S rDNA]], V4 subregion of [[18S ribosomal RNA|18S rRNA]] gene, [[Internal transcribed spacer|ITS]] rDNA and ''[[Cytochrome c oxidase subunit I|COI]]''. Additionally, some specific barcodes can be used for [[Photosynthesis|photosynthetic]] protists, for example the large subunit of [[RuBisCO|ribulose-1,5-bisphosphate carboxylase-oxygenase]] gene (''rbcL'') and the [[Chloroplast DNA|chloroplastic]] [[23S ribosomal RNA|23S rRNA]] gene<ref name=":2" />.
The next major study into the efficacy of DNA barcoding was focused on the [[neotropical]] skipper butterfly, ''[[Astraptes fulgerator]]'' at the [[Area de Conservación Guanacaste World Heritage Site|Area de Conservación de Guanacaste]] (ACG) in north-western [[Costa Rica]]. This species was already known as a [[cryptic species complex]], due to subtle [[morphology (biology)|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<ref name=HebertAstraptes>{{cite journal | vauthors = Hebert PD, Penton EH, Burns JM, Janzen DH, Hallwachs W | title = Ten species in one: DNA barcoding reveals cryptic species in the neotropical skipper butterfly Astraptes fulgerator | journal = Proceedings of the National Academy of Sciences| volume = 101 | issue = 41 | pages = 14812–7 | date = October 2004 | pmid = 15465915 | pmc = 522015 | doi = 10.1073/pnas.0406166101 | bibcode = 2004PNAS..10114812H }}</ref>) 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<ref name=HebertAstraptes/>) concluded that ''Astraptes fulgerator'' consists of 10 different species in north-western Costa Rica. These results, however, were subsequently challenged by Brower (2006<ref name=Brower>{{cite journal |author=Brower AVZ |title=Problems with DNA barcodes for species delimitation: 'ten species' of ''Astraptes fulgerator'' reassessed (Lepidoptera: Hesperiidae) |journal=Systematics and Biodiversity |volume=4 |issue=2 |pages=127–32 |year=2006 |doi=10.1017/S147720000500191X }}</ref>), 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.
{| class="wikitable"
|+Markers that have been used for DNA barcoding in different organism groups, modified from Purty and Chatterjee (1).
!Organism group
!Marker gene/locus
|-
|Animals
|''COI''<ref>{{Cite journal|last=Lobo|first=Jorge|last2=Costa|first2=Pedro M|last3=Teixeira|first3=Marcos AL|last4=Ferreira|first4=Maria SG|last5=Costa|first5=Maria H|last6=Costa|first6=Filipe O|date=2013|title=Enhanced primers for amplification of DNA barcodes from a broad range of marine metazoans|url=http://bmcecol.biomedcentral.com/articles/10.1186/1472-6785-13-34|journal=BMC Ecology|language=en|volume=13|issue=1|pages=34|doi=10.1186/1472-6785-13-34|issn=1472-6785|pmc=PMC3846737|pmid=24020880}}</ref>, Cytb<ref>{{Cite journal|last=Yacoub|first=Haitham A.|last2=Fathi|first2=Moataz M.|last3=Sadek|first3=Mahmoud A.|date=2015-03-04|title=Using cytochrome b gene of mtDNA as a DNA barcoding marker in chicken strains|url=http://www.tandfonline.com/doi/full/10.3109/19401736.2013.825771|journal=Mitochondrial DNA|language=en|volume=26|issue=2|pages=217–223|doi=10.3109/19401736.2013.825771|issn=1940-1736}}</ref>, 12S<ref>{{Cite journal|last=Siddappa|first=Chandra Mohan|last2=Saini|first2=Mohini|last3=Das|first3=Asit|last4=Doreswamy|first4=Ramesh|last5=Sharma|first5=Anil K.|last6=Gupta|first6=Praveen K.|date=2013|title=Sequence Characterization of Mitochondrial 12S rRNA Gene in Mouse Deer ( Moschiola indica ) for PCR-RFLP Based Species Identification|url=https://www.hindawi.com/archive/2013/783925/|journal=Molecular Biology International|language=en|volume=2013|pages=1–6|doi=10.1155/2013/783925|issn=2090-2182|pmc=PMC3885226|pmid=24455258}}</ref>, 16S<ref>{{Cite journal|last=Vences|first=Miguel|last2=Thomas|first2=Meike|last3=van der Meijden|first3=Arie|last4=Chiari|first4=Ylenia|last5=Vieites|first5=David R.|date=2005-03-16|title=Comparative performance of the 16S rRNA gene in DNA barcoding of amphibians|url=https://doi.org/10.1186/1742-9994-2-5|journal=Frontiers in Zoology|volume=2|issue=1|pages=5|doi=10.1186/1742-9994-2-5|issn=1742-9994|pmc=PMC555853|pmid=15771783}}</ref>
|-
|Plants
|''matK''<ref>{{Cite journal|last=Chen|first=Shilin|last2=Yao|first2=Hui|last3=Han|first3=Jianping|last4=Liu|first4=Chang|last5=Song|first5=Jingyuan|last6=Shi|first6=Linchun|last7=Zhu|first7=Yingjie|last8=Ma|first8=Xinye|last9=Gao|first9=Ting|date=2010-01-07|editor-last=Gilbert|editor-first=M. Thomas P|title=Validation of the ITS2 Region as a Novel DNA Barcode for Identifying Medicinal Plant Species|url=https://dx.plos.org/10.1371/journal.pone.0008613|journal=PLoS ONE|language=en|volume=5|issue=1|pages=e8613|doi=10.1371/journal.pone.0008613|issn=1932-6203|pmc=PMC2799520|pmid=20062805}}</ref>, ''rbcL''<ref>{{Cite journal|last=Theodoridis|first=Spyros|last2=Stefanaki|first2=Anastasia|last3=Tezcan|first3=Meltem|last4=Aki|first4=Cuneyt|last5=Kokkini|first5=Stella|last6=Vlachonasios|first6=Konstantinos E.|date=2012-7|title=DNA barcoding in native plants of the Labiatae (Lamiaceae) family from Chios Island (Greece) and the adjacent Çeşme-Karaburun Peninsula (Turkey)|url=http://doi.wiley.com/10.1111/j.1755-0998.2012.03129.x|journal=Molecular Ecology Resources|language=en|volume=12|issue=4|pages=620–633|doi=10.1111/j.1755-0998.2012.03129.x}}</ref>, ''psbA-trnH''<ref>{{Cite journal|last=Yang|first=Ying|last2=Zhai|first2=Yanhong|last3=Liu|first3=Tao|last4=Zhang|first4=Fangming|last5=Ji|first5=Yunheng|date=2011-1|title=Detection of Valeriana jatamansi as an Adulterant of Medicinal Paris by Length Variation of Chloroplast psb A -trn H Region|url=http://www.thieme-connect.de/DOI/DOI?10.1055/s-0030-1250072|journal=Planta Medica|language=en|volume=77|issue=01|pages=87–91|doi=10.1055/s-0030-1250072|issn=0032-0943}}</ref>, ''ITS''<ref>{{Cite journal|last=Gao|first=Ting|last2=Yao|first2=Hui|last3=Song|first3=Jingyuan|last4=Liu|first4=Chang|last5=Zhu|first5=Yingjie|last6=Ma|first6=Xinye|last7=Pang|first7=Xiaohui|last8=Xu|first8=Hongxi|last9=Chen|first9=Shilin|date=2010-7|title=Identification of medicinal plants in the family Fabaceae using a potential DNA barcode ITS2|url=https://linkinghub.elsevier.com/retrieve/pii/S0378874110002576|journal=Journal of Ethnopharmacology|language=en|volume=130|issue=1|pages=116–121|doi=10.1016/j.jep.2010.04.026}}</ref>
|-
|Bacteria
|''COI''<ref name=":4" />, ''rpoB''<ref name=":6" />, 16S<ref>{{Cite journal|last=|first=Weisburg WG, Barns SM, Pelletier DA, Lane DJ|date=|title=16S ribosomal DNA amplification for phylogenetic study|url=|journal=Journal of Bacteriology|volume=173(2)|pages=697-703|via=}}</ref>, ''cpn60''<ref name=":5" />, ''tuf''<ref>{{Cite journal|last=Makarova|first=Olga|last2=Contaldo|first2=Nicoletta|last3=Paltrinieri|first3=Samanta|last4=Kawube|first4=Geofrey|last5=Bertaccini|first5=Assunta|last6=Nicolaisen|first6=Mogens|date=2012-12-18|editor-last=Woo|editor-first=Patrick CY.|title=DNA Barcoding for Identification of ‘Candidatus Phytoplasmas’ Using a Fragment of the Elongation Factor Tu Gene|url=http://dx.plos.org/10.1371/journal.pone.0052092|journal=PLoS ONE|language=en|volume=7|issue=12|pages=e52092|doi=10.1371/journal.pone.0052092|issn=1932-6203|pmc=PMC3525539|pmid=23272216}}</ref>, ''RIF''<ref>{{Cite journal|last=Schneider|first=Kevin L.|last2=Marrero|first2=Glorimar|last3=Alvarez|first3=Anne M.|last4=Presting|first4=Gernot G.|date=2011-04-21|editor-last=Bereswill|editor-first=Stefan|title=Classification of Plant Associated Bacteria Using RIF, a Computationally Derived DNA Marker|url=https://dx.plos.org/10.1371/journal.pone.0018496|journal=PLoS ONE|language=en|volume=6|issue=4|pages=e18496|doi=10.1371/journal.pone.0018496|issn=1932-6203|pmc=PMC3080875|pmid=21533033}}</ref>, ''gnd''<ref>{{Cite journal|last=Liu|first=Lin|last2=Huang|first2=Xiaolei|last3=Zhang|first3=Ruiling|last4=Jiang|first4=Liyun|last5=Qiao|first5=Gexia|date=2013-1|title=Phylogenetic congruence between Mollitrichosiphum (Aphididae: Greenideinae) and Buchnera indicates insect-bacteria parallel evolution|url=http://doi.wiley.com/10.1111/j.1365-3113.2012.00647.x|journal=Systematic Entomology|language=en|volume=38|issue=1|pages=81–92|doi=10.1111/j.1365-3113.2012.00647.x}}</ref>
|-
|Fungi
|''ITS''<ref>{{Cite journal|last=Gao|first=Ruifang|last2=Zhang|first2=Guiming|date=2013-11|title=Potential of DNA Barcoding for Detecting Quarantine Fungi|url=http://apsjournals.apsnet.org/doi/10.1094/PHYTO-12-12-0321-R|journal=Phytopathology|language=en|volume=103|issue=11|pages=1103–1107|doi=10.1094/PHYTO-12-12-0321-R|issn=0031-949X}}</ref>, ''RPB1'' (LSU), ''RPB2'' (LSU), ''18S'' (SSU)<ref name=":7" />
|-
|Protists
|''ITS''<ref>{{Cite journal|last=Gile|first=Gillian H.|last2=Stern|first2=Rowena F.|last3=James|first3=Erick R.|last4=Keeling|first4=Patrick J.|date=2010-8|title=DNA barcoding of Chlorarachniophytes using nucleomorph ITS sequences|url=http://doi.wiley.com/10.1111/j.1529-8817.2010.00851.x|journal=Journal of Phycology|language=en|volume=46|issue=4|pages=743–750|doi=10.1111/j.1529-8817.2010.00851.x|via=}}</ref>, ''COI''<ref>{{Cite journal|last=Strüder-Kypke|first=Michaela C.|last2=Lynn|first2=Denis H.|date=2010-03-25|title=Comparative analysis of the mitochondrial cytochrome c oxidase subunit I (COI) gene in ciliates (Alveolata, Ciliophora) and evaluation of its suitability as a biodiversity marker|url=http://www.tandfonline.com/doi/abs/10.1080/14772000903507744|journal=Systematics and Biodiversity|language=en|volume=8|issue=1|pages=131–148|doi=10.1080/14772000903507744|issn=1477-2000}}</ref>, ''rbcL''<ref name=":12">{{Cite journal|last=Hamsher|first=Sarah E.|last2=LeGresley|first2=Murielle M.|last3=Martin|first3=Jennifer L.|last4=Saunders|first4=Gary W.|date=2013-10-09|editor-last=Crandall|editor-first=Keith A.|title=A Comparison of Morphological and Molecular-Based Surveys to Estimate the Species Richness of Chaetoceros and Thalassiosira (Bacillariophyta), in the Bay of Fundy|url=https://dx.plos.org/10.1371/journal.pone.0073521|journal=PLoS ONE|language=en|volume=8|issue=10|pages=e73521|doi=10.1371/journal.pone.0073521|issn=1932-6203|pmc=PMC3794052|pmid=24130665}}</ref>, ''18S''<ref>{{Cite journal|last=Kaczmarska|first=Irena|last2=Ehrman|first2=James Michael|last3=Moniz|first3=Monica Barros Joyce|last4=Davidovich|first4=Nikolai|date=2009-9|title=Phenotypic and genetic structure of interbreeding populations of the diatom Tabularia fasciculata (Bacillariophyta)|url=https://www.tandfonline.com/doi/full/10.2216/08-74.1|journal=Phycologia|language=en|volume=48|issue=5|pages=391–403|doi=10.2216/08-74.1|issn=0031-8884}}</ref>, ''28S''<ref name=":12" />
|}


== Reference libraries and bioinformatics ==
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.<ref name=caterpillar>{{cite web |vauthors=Janzen DH, Hallwachs W |url=http://janzen.sas.upenn.edu/caterpillars/database.lasso |title=Dynamic database for an inventory of the macrocaterpillar fauna, and its food plants and parasitoids |year=2009 |website=Area de Conservacion Guanacaste (ACG), northwestern Costa Rica |access-date=2018-09-09}}</ref> In 2006 Smith ''et al.''<ref name=Smith2006>{{cite journal | vauthors = Smith MA, Woodley NE, Janzen DH, Hallwachs W, Hebert PD | title = DNA barcodes reveal cryptic host-specificity within the presumed polyphagous members of a genus of parasitoid flies (Diptera: Tachinidae) | journal = Proceedings of the National Academy of Sciences| volume = 103 | issue = 10 | pages = 3657–62 | date = March 2006 | pmid = 16505365 | pmc = 1383497 | doi = 10.1073/pnas.0511318103 }}</ref> examined whether a COI DNA barcode could function as a tool for identification and discovery for the 20 morphospecies of ''[[Belvosia]]'' [https://www.itis.gov/servlet/SingleRpt/SingleRpt?search_topic=TSN&search_value=650659] [[parasitoid]] flies ([[Tachinidae]]) that have been reared from [[caterpillar]]s 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.
Reference libraries are used for the taxonomic identification, also alled annotation, of sequences obtained from barcoding or metabarcoding. These databases contain the DNA barcodes assigned to previously identified taxa. Most reference libraries do not have a complete setup of all species within an organism group, and new entries are continuesly created. In the case of macro- and many microorganisms (such as algae), the procedure requires detailed documentation (sampling location and date, person who collected it, image, etc.) and authoritative taxonomic identification of the voucher specimen, and well as submission of sequences in a particular format. The process also requires the storage of voucher specimens in museum collections and other collaborating institutions. Both taxonomically comprehensive coverage and content quality are important for identification accuracy<ref>{{Cite journal|last=Weigand|first=Hannah|last2=Beermann|first2=Arne J.|last3=Čiampor|first3=Fedor|last4=Costa|first4=Filipe O.|last5=Csabai|first5=Zoltán|last6=Duarte|first6=Sofia|last7=Geiger|first7=Matthias F.|last8=Grabowski|first8=Michał|last9=Rimet|first9=Frédéric|date=2019-03-14|title=DNA barcode reference libraries for the monitoring of aquatic biota in Europe: Gap-analysis and recommendations for future work|url=http://biorxiv.org/lookup/doi/10.1101/576553|journal=bioRxiv|doi=10.1101/576553}}</ref>. Several reference databases exist depending on the organism group and the genetic marker used. There are smaller, national databases (e.g. FinBOL), and large consortia like the International Barcode of Life Project (iBOL)<ref>{{Citation|last=Rdmpage|title=International Barcode of Life project (iBOL)|date=2016|url=http://www.gbif.org/dataset/040c5662-da76-4782-a48e-cdea1892d14c|publisher=Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow|doi=10.15468/inygc6|access-date=2019-05-14}}</ref>.


'''[http://v4.boldsystems.org/index.php/Public_BINSearch?searchtype=records BOLD]'''
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.<ref name=Smith2007>{{cite journal | vauthors = Smith MA, Wood DM, Janzen DH, Hallwachs W, Hebert PD | title = DNA barcodes affirm that 16 species of apparently generalist tropical parasitoid flies (Diptera, Tachinidae) are not all generalists | journal = Proceedings of the National Academy of Sciences| volume = 104 | issue = 12 | pages = 4967–72 | date = March 2007 | pmid = 17360352 | pmc = 1821123 | doi = 10.1073/pnas.0700050104 }}</ref> 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.


Launched in 2007, the [[Barcode of Life Data System]] (BOLD)<ref>{{Cite journal|last=Ratnasingham|first=Sujeevan|last2=Hebert|first2=Paul D. N.|date=2007-01-24|title=BARCODING: bold: The Barcode of Life Data System (http://www.barcodinglife.org): BARCODING|url=http://doi.wiley.com/10.1111/j.1471-8286.2007.01678.x|journal=Molecular Ecology Notes|language=en|volume=7|issue=3|pages=355–364|doi=10.1111/j.1471-8286.2007.01678.x|pmc=PMC1890991|pmid=18784790}}</ref> is one of the biggest databases, containing more than 450 000 BINs (Barcode index numbers) in 2019. It is a freely accessible repository for the specimen and sequence records for barcode studies, and it is also a workbench aiding the management, quality assurance and analysis of barcode data. The database mainly contains BIN records of animals using the COI genetic marker.
However, also in 2007, Whitworth ''et al.'' reported that flies in the related family [[Calliphoridae]] could not be discriminated by barcoding.<ref name=Whitworthetal/> 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: {{quote|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.<ref name=Whitworthetal/>}}


'''[https://unite.ut.ee/ UNITE]'''
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'' [[millipede]]s in [[Zimbabwe]], and suggested the presence of cryptic species in ''Bicoxidens flavicollis''.<ref>{{cite journal | vauthors = Mwabvu T, Lamb J, Slotow R, Hamer M, Barraclough D | date = 2013 | title = Is millipede taxonomy based on gonopod morphology too inclusive? Observations on genetic variation and cryptic speciation in ''Bicoxidens flavicollis'' (Diplopoda: Spirostreptida: Spirostreptidae). | journal = [[African Invertebrates]] | volume = 54 | issue = 2 | pages = 349–356 | url = http://africaninvertebrates.org/ojs/index.php/AI/article/view/282 | archive-url = https://web.archive.org/web/20131021010712/http://africaninvertebrates.org/ojs/index.php/AI/article/view/282 | archive-date = 2013-10-21 | dead-url = yes | doi = 10.5733/afin.054.0203 }}</ref>


The UNITE database<ref>{{Cite journal|last=Nilsson|first=Rolf Henrik|last2=Larsson|first2=Karl-Henrik|last3=Taylor|first3=Andy F S|last4=Bengtsson-Palme|first4=Johan|last5=Jeppesen|first5=Thomas S|last6=Schigel|first6=Dmitry|last7=Kennedy|first7=Peter|last8=Picard|first8=Kathryn|last9=Glöckner|first9=Frank Oliver|date=2019-01-08|title=The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications|url=https://academic.oup.com/nar/article/47/D1/D259/5146189|journal=Nucleic Acids Research|language=en|volume=47|issue=D1|pages=D259–D264|doi=10.1093/nar/gky1022|issn=0305-1048|pmc=PMC6324048|pmid=30371820}}</ref> was launched in 2003 and is a reference database for the molecular identification of fungal species with the internal transcribed spacer (ITS) genetic marker region. This database is based on the concept of species hypothesis: you choose the % at which you want to work, and the sequences are sorted in comparison to sequences obtained from voucher specimens identified by experts.
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,<ref name="schander2005">{{cite journal |vauthors=Schander C, Willassen E |title=What can Biological Barcoding do for Marine Biology? |journal=Marine Biology Research |volume=1 |issue=1 |pages=79–83 |year=2005 |doi=10.1080/17451000510018962 |url=http://www.bolinfonet.org/pdf/schander&willassen_2005.pdf |deadurl=yes |archive-url=https://web.archive.org/web/20060620165057/http://www.bolinfonet.org/pdf/schander%26willassen_2005.pdf |archive-date=2006-06-20 |df= }}</ref> though cases of "shared barcodes" (e.g., non-unique) have been documented in [[cichlid]] fishes and [[cowries]]<ref name =Meier/>


'''[https://www6.inra.fr/carrtel-collection/Barcoding-database Diat.barcode]'''
===Cataloguing ancient life===


Diat.barcode<ref>{{Cite journal|last=Rimet|first=Frederic|last2=Gusev|first2=Evgenuy|last3=Kahlert|first3=Maria|last4=Kelly|first4=Martyn|last5=Kulikovskiy|first5=Maxim|last6=Maltsev|first6=Yevhen|last7=Mann|first7=David|last8=Pfannkuchen|first8=Martin|last9=Trobajo|first9=Rosa|date=2019-02-14|title=Diat.barcode, an open-access barcode library for diatoms|url=https://data.inra.fr/dataset.xhtml?persistentId=doi:10.15454/TOMBYZ|language=en|doi=10.15454/TOMBYZ}}</ref> database was first published under the name R-syst::diatom<ref>{{Cite journal|last=Rimet|first=Frédéric|last2=Chaumeil|first2=Philippe|last3=Keck|first3=François|last4=Kermarrec|first4=Lenaïg|last5=Vasselon|first5=Valentin|last6=Kahlert|first6=Maria|last7=Franc|first7=Alain|last8=Bouchez|first8=Agnès|date=2016|title=R-Syst::diatom: an open-access and curated barcode database for diatoms and freshwater monitoring|url=https://academic.oup.com/database/article-lookup/doi/10.1093/database/baw016|journal=Database|language=en|volume=2016|pages=baw016|doi=10.1093/database/baw016|issn=1758-0463|pmc=PMC4795936|pmid=26989149}}</ref> in 2016 starting with data from two sources: the Thonon culture collection (TCC) in the hydrobiological station of the French National Institute for Agricultural Research (INRA), and from the NCBI (National Center for Biotechnology Information) nucleotide database. Diat.barcode provides data for two genetic markers, ''rbc''L (Ribulose-1,5-bisphosphate carboxylase/oxygenase) and 18S (18S ribosomal RNA). The database also involves additional, trait information of species, like morphological characteristics (biovolume, size dimensions, etc.), life-forms (mobility, colony-type, etc.) or ecological features (pollution sensitivity, etc.).
Lambert ''et al.'' (2005<ref>{{cite journal | vauthors = Lambert DM, Baker A, Huynen L, Haddrath O, Hebert PD, Millar CD | title = Is a large-scale DNA-based inventory of ancient life possible? | journal = The Journal of Heredity | volume = 96 | issue = 3 | pages = 279–84 | year = 2005 | pmid = 15731217 | doi = 10.1093/jhered/esi035 | url = http://jhered.oxfordjournals.org/cgi/reprint/96/3/279.pdf | format = PDF fulltext }}</ref>) examined the possibility of using DNA barcoding to assess the past diversity of the Earth's [[biota (ecology)|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.


=== '''Bioinformatic analysis''' ===
===The Moorea Biocode Project===
In order to obtain well structured, clean and interpretable data, raw sequencing data must be processed through bioinformatics analysis. The fastq file with the sequencing data contains two types of information: the sequences detected in the sample (fasta file) and a quality file with quality scores (PHRED scores) associated to each nucleotide of each DNA sequence. The PHRED scores indicate the probability with which the associated nucleotide has been correctly scored.
{| class="wikitable"
|+PHRED quality score and the associated certainty level
|10
|90%
|-
|20
|99%
|-
|30
|99.9%
|-
|40
|99.99%
|-
|50
|99.999%
|}
In general, the PHRED score is decreasing towards the end of the DNA sequences, thus some bioinformatics pipelines simply cut the end of the sequences.


Some sequencing technologies, like Miseq, use paired-end sequencing during which sequencing is carried out from both directions producing better quality. The overlapping sequences are then aligned into contigs and merged. Usually, several samples are pooled in one run, and each sample is characterized by a short DNA fragment, the tag. In a demultiplexing step, sequences are sorted after their tags into samples again. For further analysis, tags and other adapters are removed from the barcoding sequence DNA fragment. During trimming, the bad quality sequences (low PHRED scores), or sequences that are much shorter or longer than the targeted DNA barcode, are removed. The following dereplication step is the process where all of the quality-filtered sequences are collapsed into a set of unique reads (individual sequence units ISUs) with the information of their abundance in the samples. After that, chimeras (i.e. compund sequences formed from pieces of mixed origin) are detected and removed. Finally, the sequences are clustered into OTUs (Operational Taxonomic Units), using one of many clustering strategies. The most frequently used bioinformatic softwares are e.g. Mothur<ref>{{Cite book|url=http://worldcat.org/oclc/780918718|title=Introducing mothur : open-source, platform-independent, community-supported software for describing and comparing microbial communities|last=Schloss, Patrick D. Westcott, Sarah L. Ryabin, Thomas. Hall, Justine R. Hartmann, Martin, mikrobiolog. Hollister, Emily B. Lesniewski, Ryan A. Oakley, Brian B. Parks, Donovan H. Robinson, Courtney J. Sahl, Jason W. Stres, Blaž. Thallinger, Gerhard G. Horn, David J. van. Weber, Caroly F.|oclc=780918718}}</ref>, Uparse<ref>{{Cite journal|last=Edgar|first=Robert C|date=2013-08-18|title=UPARSE: highly accurate OTU sequences from microbial amplicon reads|url=http://dx.doi.org/10.1038/nmeth.2604|journal=Nature Methods|volume=10|issue=10|pages=996–998|doi=10.1038/nmeth.2604|issn=1548-7091}}</ref>, Qiime<ref>{{Cite journal|last=Caporaso|first=J Gregory|last2=Kuczynski|first2=Justin|last3=Stombaugh|first3=Jesse|last4=Bittinger|first4=Kyle|last5=Bushman|first5=Frederic D|last6=Costello|first6=Elizabeth K|last7=Fierer|first7=Noah|last8=Peña|first8=Antonio Gonzalez|last9=Goodrich|first9=Julia K|date=2010-5|title=QIIME allows analysis of high-throughput community sequencing data|url=http://www.nature.com/articles/nmeth.f.303|journal=Nature Methods|language=en|volume=7|issue=5|pages=335–336|doi=10.1038/nmeth.f.303|issn=1548-7091|pmc=PMC3156573|pmid=20383131}}</ref>, Galaxy<ref>{{Cite journal|last=Afgan|first=Enis|last2=Baker|first2=Dannon|last3=Batut|first3=Bérénice|last4=van den Beek|first4=Marius|last5=Bouvier|first5=Dave|last6=Čech|first6=Martin|last7=Chilton|first7=John|last8=Clements|first8=Dave|last9=Coraor|first9=Nate|date=2018-07-02|title=The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update|url=https://academic.oup.com/nar/article/46/W1/W537/5001157|journal=Nucleic Acids Research|language=en|volume=46|issue=W1|pages=W537–W544|doi=10.1093/nar/gky379|issn=0305-1048|pmc=PMC6030816|pmid=29790989}}</ref>, Obitools<ref>{{Cite journal|last=Boyer|first=Frédéric|last2=Mercier|first2=Céline|last3=Bonin|first3=Aurélie|last4=Le Bras|first4=Yvan|last5=Taberlet|first5=Pierre|last6=Coissac|first6=Eric|date=2015-05-26|title=obitools: aunix-inspired software package for DNA metabarcoding|url=http://dx.doi.org/10.1111/1755-0998.12428|journal=Molecular Ecology Resources|volume=16|issue=1|pages=176–182|doi=10.1111/1755-0998.12428|issn=1755-098X}}</ref>, JAMP<ref>{{Citation|last=Elbrecht|first=Vasco|title=JAMP: Just Another Metabarcoding Pipeline. Contribute to VascoElbrecht/JAMP development by creating an account on GitHub|date=2019-04-30|url=https://github.com/VascoElbrecht/JAMP|access-date=2019-05-14}}</ref>, DADA2<ref>{{Cite journal|last=Callahan|first=Benjamin J|last2=McMurdie|first2=Paul J|last3=Rosen|first3=Michael J|last4=Han|first4=Andrew W|last5=Johnson|first5=Amy Jo A|last6=Holmes|first6=Susan P|date=2016-7|title=DADA2: High-resolution sample inference from Illumina amplicon data|url=http://www.nature.com/articles/nmeth.3869|journal=Nature Methods|language=en|volume=13|issue=7|pages=581–583|doi=10.1038/nmeth.3869|issn=1548-7091|pmc=PMC4927377|pmid=27214047}}</ref>.
The [http://www.mooreabiocode.org/ Moorea Biocode Project] was a barcoding initiative in 2008 - 2010 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 3-year project brought together researchers from the [[Smithsonian Institution]], [[UC Berkeley]], France’s [[CNRS|National Center for Scientific Research]] (CNRS), and other partners. The outcome of the project was a library of genetic markers and physical identifiers for every species of plant, animal and fungi on the island that is provided as a publicly available database resource for ecologists and evolutionary biologists around the world.


Comparing the abundance of reads, i.e. sequences, between different samples is still a challenge because both the total number of reads in a sample as well as the relative amount of reads for a species can vary between samples, methods, or other variables. For comparison, one may then reduce the number of reads of each sample to the minimal number of reads of the samples to be compared – a process called rarefaction. Another way is to use the relative abundance of reads<ref>{{Cite journal|last=|first=|date=|title=|url=https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003531|journal=|volume=|pages=|via=}}</ref>.
The software back-end to the Moore Biocode Project is [[Geneious|Geneious Pro]] and two custom-developed plugins from the [[New Zealand]]-based company, [[Biomatters]]. The [http://software.mooreabiocode.org/index.php?title=Main_Page|Geneious Biocode LIMS and Genbank Submission] plugins have been made freely available to the public<ref>{{cite web |url=http://www.bio-itworld.com/2010/11/30/biomatters-moorea-LIMS.html |author=Allison Proffitt |date=November 30, 2010 |title=LIMS Made Freely Available to DNA Barcoding Community |website=Bio-IT World}}</ref> and users of the free Geneious Basic software should be able to access and view the Biocode database, while a commercial copy of Geneious Pro was required for researchers involved in data creation and analysis.


<br />
==Initial criticism and current status==
=== Species identification and taxonomic assignment ===
In the initial years following its proposal, DNA barcoding met with spirited reaction from scientists, especially [[systematics|systematists]], ranging from enthusiastic endorsement to vociferous opposition.<ref>{{cite journal | vauthors = Rubinoff D, Cameron S, Will K | title = A genomic perspective on the shortcomings of mitochondrial DNA for "barcoding" identification | journal = The Journal of Heredity | volume = 97 | issue = 6 | pages = 581–94 | year = 2006 | pmid = 17135463 | doi = 10.1093/jhered/esl036 }}</ref><ref>{{cite journal | vauthors = Ebach MC, Carvalho MR |year=2010 |title=Anti-intellectualism in the DNA Barcoding Enterprise |journal=Zoologia (Curitiba) |volume=27 |issue=2 |pages=165–178 |url=http://scielo.br/scielo.php?script=sci_arttext&pid=S1984-46702010000200003 |doi=10.1590/s1984-46702010000200003}}</ref> For example, some stressed the fact that DNA barcoding does not provide reliable information above the species level{{citation needed|date=October 2015}}, while others opined that it was inapplicable at the species level, but may still have merit for higher-level groups.<ref name = Whitworthetal/> 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.<ref name="pmid18784793">{{cite journal | vauthors = Kerr KC, Stoeckle MY, Dove CJ, Weigt LA, Francis CM, Hebert PD | title = Comprehensive DNA barcode coverage of North American birds | journal = Molecular Ecology Notes | volume = 7 | issue = 4 | pages = 535–543 | date = July 2007 | pmid = 18784793 | pmc = 2259444 | doi = 10.1111/j.1471-8286.2007.01670.x | url = https://repository.si.edu/bitstream/handle/10088/21643/vz_men0007-0535.PMC2259444.pdf }}</ref> In an early study, Funk & Omland (2003<ref>{{cite journal |vauthors=Funk DJ, Omland KE |title=Species-level paraphyly and polyphyly: frequency, causes, and consequences, with insights from animal mitochondrial DNA |journal=Annu Rev Ecol Syst |volume=34 |pages=397–423 |year=2003 |doi=10.1146/annurev.ecolsys.34.011802.132421 }}</ref>) 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<ref>{{cite journal | vauthors = Meyer CP, Paulay G | title = DNA barcoding: error rates based on comprehensive sampling | journal = PLoS Biology | volume = 3 | issue = 12 | pages = e422 | date = December 2005 | pmid = 16336051 | pmc = 1287506 | doi = 10.1371/journal.pbio.0030422 }} {{open access}}</ref>). 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,<ref name=Hurstetal/> Whitworth ''et al.'', 2007,<ref name=Whitworthetal/> Wiemers & Fiedler, 2007<ref>{{cite journal | vauthors = Wiemers M, Fiedler K | title = Does the DNA barcoding gap exist? - a case study in blue butterflies (Lepidoptera: Lycaenidae) | journal = Frontiers in Zoology | volume = 4 | issue = 1 | pages = 8 | date = March 2007 | pmid = 17343734 | pmc = 1838910 | doi = 10.1186/1742-9994-4-8 }}</ref>).
The taxonomic assignment of the OTUs to species is achieved by matching of sequences to reference libraries. [[BLAST|The Basic Local Alignment Search Tool (BLAST)]] is commonly used to identify regions of similarity between sequences by comparing sequence reads from the sample to sequences in reference databases<ref>{{Cite journal|last=Valiente|first=Gabriel|last2=Jansson|first2=Jesper|last3=Clemente|first3=Jose Carlos|last4=Alonso-Alemany|first4=Daniel|date=2011-10-10|title=Taxonomic Assignment in Metagenomics with TANGO|url=http://journal.embnet.org/index.php/embnetjournal/article/view/237|journal=EMBnet.journal|language=en|volume=17|issue=2|pages=16–20|doi=10.14806/ej.17.2.237|issn=2226-6089}}</ref>. If the reference database contains sequences of the relevant species, then the sample sequences can be identified to species level. If a sequences cannot be matched to an existing reference library entry, DNA barcoding can be used to create a new entry.


In some cases, due to the incompleteness of reference databases, identification can only be done to higher taxonomic categories, such as assignment to a family or class. However, in some organism groups such as bacteria, taxonomic assignment to species level is often not possible. In such cases, a sample may be assigned to a particular [[Operational taxonomic unit|operational taxonomic unit (OTU)]].
Moritz and Cicero (2004<ref>{{cite journal | vauthors = Moritz C, Cicero C | title = DNA barcoding: promise and pitfalls | journal = PLoS Biology | volume = 2 | issue = 10 | pages = e354 | date = October 2004 | pmid = 15486587 | pmc = 519004 | doi = 10.1371/journal.pbio.0020354 }} {{open access}}</ref>) 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<ref name=JohnsonCicero>{{cite journal | vauthors = Johnson NK, Cicero C | title = New mitochondrial DNA data affirm the importance of Pleistocene speciation in North American birds | journal = Evolution; International Journal of Organic Evolution | volume = 58 | issue = 5 | pages = 1122–30 | date = May 2004 | pmid = 15212392 | doi = 10.1554/03-283 }}</ref>) 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<ref name=JohnsonCicero/>) 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.


<br />
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:
<blockquote>[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.<ref>{{cite journal | vauthors = Hebert PD, Hollingsworth PM, Hajibabaei M | title = From writing to reading the encyclopedia of life | journal = Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences | volume = 371 | issue = 1702 | pages = 20150321 | date = September 2016 | pmid = 27481778 | pmc = 4971178 | doi = 10.1098/rstb.2015.0321 }}</ref></blockquote>


== Applications ==
In a more recent (2018) review, M. Stoeckle and D. Thaler write:
Applications of DNA barcoding include identification of new [[species]], safety assessment of food, identification and assessment of cryptic species, detection of alien species, identification of endangered and [[threatened species]]<ref name=":10">{{Cite journal|last=Schnell|first=Ida Bærholm|last2=Thomsen|first2=Philip Francis|last3=Wilkinson|first3=Nicholas|last4=Rasmussen|first4=Morten|last5=Jensen|first5=Lars R.D.|last6=Willerslev|first6=Eske|last7=Bertelsen|first7=Mads F.|last8=Gilbert|first8=M. Thomas P.|date=2012-4|title=Screening mammal biodiversity using DNA from leeches|url=https://linkinghub.elsevier.com/retrieve/pii/S0960982212002096|journal=Current Biology|language=en|volume=22|issue=8|pages=R262–R263|doi=10.1016/j.cub.2012.02.058}}</ref>, linking egg and larval stages to adult species, securing intellectual property rights for bioresources, framing global management plans for conservation strategies and elucidate feeding niches.<ref>{{Cite book|url=https://www.worldcat.org/oclc/958384953|title=DNA Barcoding in Marine Perspectives : Assessment and Conservation of Biodiversity.|last=Subrata.|first=Trivedi,|date=2016|publisher=Springer International Publishing|others=Ansari, Abid Ali., Ghosh, Sankar K., Rehman, Hasibur.|isbn=9783319418407|location=Cham|oclc=958384953}}</ref> DNA barcode markers can be applied on basic questions in systematics, [[ecology]], [[evolutionary biology]] and [[Conservation biology|conservation]], including community assembly, [[Biological interaction|species interaction]] networks, taxonomic discovery, and assessing priority areas for [[environmental protection]].
<blockquote>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.<ref>{{cite journal | vauthors = Stoeckle MY, Thaler DS | title = Why should mitochondria define species? | journal = Human Evolution | volume = 33 | issue = 1–2 | pages = 1–30 | date = 2018 |doi=10.14673/HE2018121037 }}</ref></blockquote>


==== Identification 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.<ref>{{cite journal | vauthors = Braukmann TW, Kuzmina ML, Sills J, Zakharov EV, Hebert PD | title = Testing the Efficacy of DNA Barcodes for Identifying the Vascular Plants of Canada | journal = PLOS ONE | volume = 12 | issue = 1 | pages = e0169515 | year = 2017 | pmid = 28072819 | pmc = 5224991 | doi = 10.1371/journal.pone.0169515 | bibcode = 2017PLoSO..1269515B }}</ref> 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.
Specific short DNA sequences or markers from a standardized region of the genome can provide a DNA barcode for identifying species.<ref name=":1">{{Cite journal|last=Hebert|first=Paul D. N.|last2=Stoeckle|first2=Mark Y.|last3=Zemlak|first3=Tyler S.|last4=Francis|first4=Charles M.|date=2004-10|title=Identification of Birds through DNA Barcodes|url=https://www.ncbi.nlm.nih.gov/pubmed/15455034|journal=PLoS biology|volume=2|issue=10|pages=e312|doi=10.1371/journal.pbio.0020312|issn=1545-7885|pmc=PMC518999|pmid=15455034}}</ref> Molecular methods are especially useful when traditional methods are not applicable. DNA barcoding has great applicability in identification of larvae for which there are generally few diagnostic characters available, and in association of different life stages (e.g. larval and adult) in many animals.<ref>{{Cite journal|last=Costa|first=Filipe O|last2=Carvalho|first2=Gary R|date=2007-12|title=The Barcode of Life Initiative: synopsis and prospective societal impacts of DNA barcoding of Fish|url=https://lsspjournal.biomedcentral.com/articles/10.1186/1746-5354-3-2-29|journal=Genomics, Society and Policy|language=en|volume=3|issue=2|doi=10.1186/1746-5354-3-2-29|issn=1746-5354|pmc=PMC5425017}}</ref> Identification of species listed in the Convention of the International Trade of Endangered Species ([[CITES]]) appendixes using barcoding techniques is used in monitoring of illegal trade<ref>{{Cite journal|last=Lahaye|first=R.|last2=van der Bank|first2=M.|last3=Bogarin|first3=D.|last4=Warner|first4=J.|last5=Pupulin|first5=F.|last6=Gigot|first6=G.|last7=Maurin|first7=O.|last8=Duthoit|first8=S.|last9=Barraclough|first9=T. G.|date=2008-02-26|title=DNA barcoding the floras of biodiversity hotspots|url=http://www.pnas.org/cgi/doi/10.1073/pnas.0709936105|journal=Proceedings of the National Academy of Sciences|language=en|volume=105|issue=8|pages=2923–2928|doi=10.1073/pnas.0709936105|issn=0027-8424|pmc=PMC2268561|pmid=18258745}}</ref>.


==== Detection of invasive species ====
==Software==
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|Geneious Pro]] can be used for the sequence analysis components, and the two plugins made freely available through the Moorea Biocode Project, the [http://software.mooreabiocode.org/index.php?title=Main_Page|Geneious Biocode LIMS and Genbank Submission] plugins handle integration with the FIMS, the LIMS, workflow tracking and database submission.


[[Introduced species|Alien specie]]<nowiki/>s can be detected via barcoding<ref name=":13">{{Cite journal|last=Xu|first=Song-Zhi|last2=Li|first2=Zhen-Yu|last3=Jin|first3=Xiao-Hua|date=2018-1|title=DNA barcoding of invasive plants in China: A resource for identifying invasive plants|url=http://doi.wiley.com/10.1111/1755-0998.12715|journal=Molecular Ecology Resources|language=en|volume=18|issue=1|pages=128–136|doi=10.1111/1755-0998.12715}}</ref><ref>{{Cite journal|last=Liu|first=Junning|last2=Jiang|first2=Jiamei|last3=Song|first3=Shuli|last4=Tornabene|first4=Luke|last5=Chabarria|first5=Ryan|last6=Naylor|first6=Gavin J. P.|last7=Li|first7=Chenhong|date=2017-12|title=Multilocus DNA barcoding – Species Identification with Multilocus Data|url=http://www.nature.com/articles/s41598-017-16920-2|journal=Scientific Reports|language=en|volume=7|issue=1|doi=10.1038/s41598-017-16920-2|issn=2045-2322|pmc=PMC5709489|pmid=29192249}}</ref>. Barcoding can be suitable for detection of species in e.g. border control, where rapid and accurate morphological identification is often not possible due to several similar specimens, lack of sufficient diagnostic characteristics<ref name=":13" /> and/or lack of taxonomic expertise. Barcoding and metabarcoding can also be used to screen [[Ecosystem|ecosystems]] for invasive species, and to distinguish between an invasive species and native, morphologically similar, species<ref>{{Cite journal|last=Nagoshi|first=Rodney N.|last2=Brambila|first2=Julieta|last3=Meagher|first3=Robert L.|date=2011-11|title=Use of DNA Barcodes to Identify Invasive Armyworm Spodoptera Species in Florida|url=https://academic.oup.com/jinsectscience/article-lookup/doi/10.1673/031.011.15401|journal=Journal of Insect Science|language=en|volume=11|issue=154|pages=1–11|doi=10.1673/031.011.15401|issn=1536-2442|pmc=PMC3391933|pmid=22239735}}</ref>.
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.
==== Phylogenetic construction ====
DNA barcoding is a useful tool for species identification, with less information on phylogenetic relatedness. Still, barcodes can provide insights into evolution, for example COI barcodes illustrate molecular evolution and protein function in animals at different taxonomic levels. COI is informative on recent divergence, however but not useful for estimating evolutionary relationships<sup>[[User:Maria Kahlert (SLU)/sandbox#cite%20note-79|[79]]]</sup>.


==== Delimiting cryptic species ====
== See also ==
{{col div|colwidth=18em}}
*[[DNA taxonomy]]
*[[Pollen DNA barcoding]]
*[[Consortium for the Barcode of Life]]
*[[Identification (biology)]]
*[[Applied Food Technologies]]
*[[DNA profiling]]
*[[Taxonomic impediment]]
{{colend}}


DNA barcoding enables the identification and recognition of [[cryptic species]]<ref>{{Cite journal|last=Thongtam na Ayudhaya|first=Pradipunt|last2=Muangmai|first2=Narongrit|last3=Banjongsat|first3=Nuwadee|last4=Singchat|first4=Worapong|last5=Janekitkarn|first5=Sommai|last6=Peyachoknagul|first6=Surin|last7=Srikulnath|first7=Kornsorn|date=2017-6|title=Unveiling cryptic diversity of the anemonefish genera Amphiprion and Premnas (Perciformes: Pomacentridae) in Thailand with mitochondrial DNA barcodes|url=https://linkinghub.elsevier.com/retrieve/pii/S2452316X17303411|journal=Agriculture and Natural Resources|language=en|volume=51|issue=3|pages=198–205|doi=10.1016/j.anres.2017.07.001}}</ref>. The results of DNA barcoding analyses depend however upon the choice of analytical methods, so the process of delimiting cryptic species using DNA barcodes can be as subjective as any other form of [[Taxonomy (biology)|taxonomy]]. Hebert ''et al.''(2004) concluded that the butterfly ''Astraptes fulgerator'' in north-western Costa Rica actually consists of 10 different species<ref>{{Cite journal|last=Hebert|first=P. D. N.|last2=Penton|first2=E. H.|last3=Burns|first3=J. M.|last4=Janzen|first4=D. H.|last5=Hallwachs|first5=W.|date=2004-10-12|title=Ten species in one: DNA barcoding reveals cryptic species in the neotropical skipper butterfly Astraptes fulgerator|url=http://www.pnas.org/cgi/doi/10.1073/pnas.0406166101|journal=Proceedings of the National Academy of Sciences|language=en|volume=101|issue=41|pages=14812–14817|doi=10.1073/pnas.0406166101|issn=0027-8424|pmc=PMC522015|pmid=15465915}}</ref>. 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<ref>{{Cite journal|last=Brower|first=Andrew V.Z.|date=2006-6|title=Problems with DNA barcodes for species delimitation: ‘Ten species’ of Astraptes fulgerator reassessed (Lepidoptera: Hesperiidae)|url=http://www.tandfonline.com/doi/abs/10.1017/S147720000500191X|journal=Systematics and Biodiversity|language=en|volume=4|issue=2|pages=127–132|doi=10.1017/S147720000500191X|issn=1477-2000}}</ref>. Smith et al. (2007) used cytochrome ''c'' oxidase I DNA barcodes for species identification of the 20 morphospecies of ''Belvosia'' parasitoid flies ([[Fly|Diptera]]: [[Tachinidae]]) reared from caterpillars ([[Lepidoptera]]) in Area de Conservación Guanacaste (ACG), northwestern Costa Rica. These authors discovered that barcoding raises the species count to 32, by revealing that each of the three [[parasitoid]] species, previously considered as generalists, actually are arrays of highly host-specific cryptic species<ref>{{Cite journal|last=Smith|first=M. A.|last2=Woodley|first2=N. E.|last3=Janzen|first3=D. H.|last4=Hallwachs|first4=W.|last5=Hebert|first5=P. D. N.|date=2006-03-07|title=DNA barcodes reveal cryptic host-specificity within the presumed polyphagous members of a genus of parasitoid flies (Diptera: Tachinidae)|url=http://www.pnas.org/cgi/doi/10.1073/pnas.0511318103|journal=Proceedings of the National Academy of Sciences|language=en|volume=103|issue=10|pages=3657–3662|doi=10.1073/pnas.0511318103|issn=0027-8424|pmc=PMC1383497|pmid=16505365}}</ref>. For 15 morphospecies of [[polychaete]]<nowiki/>s within the deep [[Antarctic]] [[benthos]] studied through DNA barcoding, cryptic diversity was found in 50% of the cases. Furthermore 10 previously overlooked morphospecies were detected, increasing the total [[species richness]] in the sample by 233%<ref>{{Cite journal|last=Brasier|first=Madeleine J.|last2=Wiklund|first2=Helena|last3=Neal|first3=Lenka|last4=Jeffreys|first4=Rachel|last5=Linse|first5=Katrin|last6=Ruhl|first6=Henry|last7=Glover|first7=Adrian G.|date=2016-11|title=DNA barcoding uncovers cryptic diversity in 50% of deep-sea Antarctic polychaetes|url=http://rsos.royalsocietypublishing.org/lookup/doi/10.1098/rsos.160432|journal=Royal Society Open Science|language=en|volume=3|issue=11|pages=160432|doi=10.1098/rsos.160432|issn=2054-5703|pmc=PMC5180122|pmid=28018624}}</ref> .
== References ==
<nowiki/>[[File:DNA-strekkoding av julemat - DNA barcoding of Christmas food (16008786266).jpg|thumb|327x327px|Barcoding is a tool to vouch for food quality. Here, DNA from traditional Norwegian Christmas food is extracted at the molecular systematic lab at NTNU University Museum.]]
{{Reflist|32em}}


==== Diet analysis and food web application ====
== Further reading ==
DNA barcoding and metabarcoding can be useful in diet analysis studies<ref>{{Cite journal|last=Pompanon|first=Francois|last2=Deagle|first2=Bruce E.|last3=Symondson|first3=William O. C.|last4=Brown|first4=David S.|last5=Jarman|first5=Simon N.|last6=Taberlet|first6=Pierre|date=2012-4|title=Who is eating what: diet assessment using next generation sequencing: NGS DIET ANALYSIS|url=http://doi.wiley.com/10.1111/j.1365-294X.2011.05403.x|journal=Molecular Ecology|language=en|volume=21|issue=8|pages=1931–1950|doi=10.1111/j.1365-294X.2011.05403.x}}</ref>, and is typically used if prey specimens cannot be identified based on morphological characters<ref>{{Cite journal|last=Valentini|first=Alice|last2=Pompanon|first2=François|last3=Taberlet|first3=Pierre|date=2009-2|title=DNA barcoding for ecologists|url=https://linkinghub.elsevier.com/retrieve/pii/S0169534708003443|journal=Trends in Ecology & Evolution|language=en|volume=24|issue=2|pages=110–117|doi=10.1016/j.tree.2008.09.011}}</ref><ref name=":14">{{Cite journal|last=Kaunisto|first=Kari M.|last2=Roslin|first2=Tomas|last3=Sääksjärvi|first3=Ilari E.|last4=Vesterinen|first4=Eero J.|date=2017-10|title=Pellets of proof: First glimpse of the dietary composition of adult odonates as revealed by metabarcoding of feces|url=http://doi.wiley.com/10.1002/ece3.3404|journal=Ecology and Evolution|language=en|volume=7|issue=20|pages=8588–8598|doi=10.1002/ece3.3404|pmc=PMC5648679|pmid=29075474}}</ref>. There is a range of sampling approaches in diet analysis: DNA metabarcoding can be conducted on stomach contents<ref>{{Cite journal|last=Harms-Tuohy|first=Ca|last2=Schizas|first2=Nv|last3=Appeldoorn|first3=Rs|date=2016-10-25|title=Use of DNA metabarcoding for stomach content analysis in the invasive lionfish Pterois volitans in Puerto Rico|url=http://www.int-res.com/abstracts/meps/v558/p181-191/|journal=Marine Ecology Progress Series|language=en|volume=558|pages=181–191|doi=10.3354/meps11738|issn=0171-8630}}</ref>, feces<ref name=":14" /><ref>{{Cite journal|last=Kowalczyk|first=Rafał|last2=Taberlet|first2=Pierre|last3=Coissac|first3=Eric|last4=Valentini|first4=Alice|last5=Miquel|first5=Christian|last6=Kamiński|first6=Tomasz|last7=Wójcik|first7=Jan M.|date=2011-2|title=Influence of management practices on large herbivore diet—Case of European bison in Białowieża Primeval Forest (Poland)|url=https://linkinghub.elsevier.com/retrieve/pii/S0378112710006961|journal=Forest Ecology and Management|language=en|volume=261|issue=4|pages=821–828|doi=10.1016/j.foreco.2010.11.026}}</ref>, saliva<ref>{{Cite journal|last=Nichols|first=Ruth V.|last2=Cromsigt|first2=Joris P. G. M.|last3=Spong|first3=Göran|date=2015-12|title=Using eDNA to experimentally test ungulate browsing preferences|url=http://www.springerplus.com/content/4/1/489|journal=SpringerPlus|language=en|volume=4|issue=1|doi=10.1186/s40064-015-1285-z|issn=2193-1801|pmc=PMC4565800|pmid=26380165}}</ref> or whole body analysis<ref name=":10" /><ref>{{Cite journal|last=Agusti|first=N.|last2=Shayler|first2=S. P.|last3=Harwood|first3=J. D.|last4=Vaughan|first4=I. P.|last5=Sunderland|first5=K. D.|last6=Symondson|first6=W. O. C.|date=2003-12|title=Collembola as alternative prey sustaining spiders in arable ecosystems: prey detection within predators using molecular markers|url=http://doi.wiley.com/10.1046/j.1365-294X.2003.02014.x|journal=Molecular Ecology|language=en|volume=12|issue=12|pages=3467–3475|doi=10.1046/j.1365-294X.2003.02014.x|issn=0962-1083}}</ref>. In fecal samples or highly digested stomach contents, it is often not possible to distinguish tissue from single species, and therefore metabarcoding can be applied instead<ref name=":14" /><ref>{{Cite journal|last=Valentini|first=Alice|last2=Miquel|first2=Christian|last3=Nawaz|first3=Muhammad Ali|last4=Bellemain|first4=Eva|last5=Coissac|first5=Eric|last6=Pompanon|first6=François|last7=Gielly|first7=Ludovic|last8=Cruaud|first8=Corinne|last9=Nascetti|first9=Giuseppe|date=2009-1|title=New perspectives in diet analysis based on DNA barcoding and parallel pyrosequencing: the trn L approach|url=http://doi.wiley.com/10.1111/j.1755-0998.2008.02352.x|journal=Molecular Ecology Resources|language=en|volume=9|issue=1|pages=51–60|doi=10.1111/j.1755-0998.2008.02352.x}}</ref>. Feces or saliva represent non-invasive sampling approaches, while whole body analysis often means that the individual needs to be killed first. For smaller organisms, sequencing for stomach content is then often done by sequencing the entire animal.


==== Barcoding for food safety ====
* {{Doi|10.1038/s41592-018-0185-x}} Kebschull JM and Zador AM. "Cellular barcoding: lineage tracing, screening and beyond" (Review article), ''Nature Methods'', November 2018. {{Paywall}}
DNA barcoding represents an essential tool to evaluate the quality of food products. The purpose is to guarantee food traceability, to minimize food piracy, and to valuate local and typical agro-food production. Another purpose is to safeguard public health; for example, metabarcoding offers the possibility to identify [[Grouper|groupers]] causing [[Ciguatera]] fish poisoning from meal remnants<ref>{{Cite journal|last=Friedman|first=Melissa|last2=Fernandez|first2=Mercedes|last3=Backer|first3=Lorraine|last4=Dickey|first4=Robert|last5=Bernstein|first5=Jeffrey|last6=Schrank|first6=Kathleen|last7=Kibler|first7=Steven|last8=Stephan|first8=Wendy|last9=Gribble|first9=Matthew|date=2017-03-14|title=An Updated Review of Ciguatera Fish Poisoning: Clinical, Epidemiological, Environmental, and Public Health Management|url=http://www.mdpi.com/1660-3397/15/3/72|journal=Marine Drugs|language=en|volume=15|issue=3|pages=72|doi=10.3390/md15030072|issn=1660-3397|pmc=PMC5367029|pmid=28335428}}</ref>, or to separate poisonous mushrooms from edible ones (Ref).


==== Biomonitoring and ecological assessment ====
== External links ==
DNA barcoding can be used to assess the presence of endangered species for conservation efforts (Ref), or the presence of indicator species reflective to specific ecological conditions (Ref), for example excess nutrients or low oxygen levels.
* [http://www.fishbol.org Fish Barcode of Life Initiative (FISH-BOL)]
* [http://barcoding.si.edu/AllBirds.htm All Birds Barcoding Initiative (ABBI)]
* [http://www.polarbarcoding.org Polar Flora and Fauna Barcoding website] (Latest outpost in the Canadian Arctic in the field)
*[http://www.barcoding.si.edu/PDF/Guidelines%20for%20non-CO1%20selection%20-%204%20June.pdf Guidelines for non COI gene selection]


== Potentials and shortcomings ==
{{Phylogenetics}}


=== Potentials ===
{{DEFAULTSORT:Dna Barcoding}}
Traditional bioassessment methods are well established internationally, and serve biomonitoring well, as for example for aquatic bioassessment within the EU Directives [[Water Framework Directive|WFD]] and [[Marine Strategy Framework Directive|MSFD]]. However, DNA barcoding could improve traditional methods for the following reasons; DNA barcoding (i) can increase taxonomic resolution and harmonize the identification of taxa which are difficult to identify or lack experts, (ii) can more accurately/precisely relate environmental factors to specific taxa (iii) can increase comparability among regions, (iv) allows for the inclusion of early life stages and fragmented specimens, (v) allows delimitation of [[Species complex|cryptic]]/rare species (vi) allows for development of new indices e.g. rare/cryptic species which may be sensitive/tolerant to [[Stressor|stressors]], (vii) increases the number of samples which can be processed and reduces processing time resulting in increased knowledge of species ecology, (viii) is a non-invasive way of monitoring when using [[Environmental DNA|eDNA]] methods <ref name=":0">{{Cite journal|last=Pawlowski|first=Jan|last2=Kelly-Quinn|first2=Mary|last3=Altermatt|first3=Florian|last4=Apothéloz-Perret-Gentil|first4=Laure|last5=Beja|first5=Pedro|last6=Boggero|first6=Angela|last7=Borja|first7=Angel|last8=Bouchez|first8=Agnès|last9=Cordier|first9=Tristan|date=2018|title=The future of biotic indices in the ecogenomic era: Integrating (e)DNA metabarcoding in biological assessment of aquatic ecosystems|url=https://linkinghub.elsevier.com/retrieve/pii/S0048969718316322|journal=Science of The Total Environment|language=en|volume=637-638|pages=1295–1310|doi=10.1016/j.scitotenv.2018.05.002|via=}}</ref>.
[[Category:Authentication methods]]

[[Category:Bioinformatics]]
==== Time and cost ====
[[Category:Biometrics]]
DNA Barcoding is faster than traditional morphological methods all the way from training through to taxonomic assignment. It takes less time to gain expertise in DNA methods than becoming an expert in taxonomy. In addition, the DNA barcoding workflow (i.e. from sample to result) is generally quicker than traditional morphological workflow and allows the processing of more samples.
[[Category:Molecular genetics]]

[[Category:Taxonomy (biology)]]
==== Taxonomic resolution ====
DNA Barcoding allows the resolution of taxa from higher (e.g. family) to lower (e.g. species) taxonomic levels, that are otherwise too difficult to identify using traditional morphological methods, like e.g. identification via microscopy. For example, [[Chironomidae]] (the non-biting midge) are widely distributed in both terrestrial and freshwater ecosystems. Their richness and abundance make them important for ecological processes and networks, and they are one of many invertebrate groups used in biomonitoring. Invertebrate samples can contain as many as 100 species of chironomids which often make up as much as 50% of a sample. Despite this, they are usually not identified below the family level because of the taxonomic expertise and time required <ref>{{Cite book|url=http://link.springer.com/10.1007/978-94-011-0715-0|title=The Chironomidae|date=1995|publisher=Springer Netherlands|isbn=9789401043083|editor-last=Armitage|editor-first=Patrick D.|location=Dordrecht|language=en|doi=10.1007/978-94-011-0715-0|editor-last2=Cranston|editor-first2=Peter S.|editor-last3=Pinder|editor-first3=L. C. V.}}</ref>. This may result in different chironomid species with different ecological preferences grouped together, resulting in potential assessment of water quality.

DNA Barcoding provides the opportunity to resolve taxa, and directly relate stressor effects to specific taxa such as individual chironomid species. For example, Beermann et al. (2018) DNA barcoded Chironomidae to investigate their response to multiple stressors; reduced flow, increased fine-sediment and increased salinity <ref>{{Cite journal|last=Beermann|first=Arne J.|last2=Zizka|first2=Vera M. A.|last3=Elbrecht|first3=Vasco|last4=Baranov|first4=Viktor|last5=Leese|first5=Florian|date=2018-07-24|title=DNA metabarcoding reveals the complex and hidden responses of chironomids to multiple stressors|url=https://doi.org/10.1186/s12302-018-0157-x|journal=Environmental Sciences Europe|volume=30|issue=1|pages=26|doi=10.1186/s12302-018-0157-x|issn=2190-4715}}</ref>. After barcoding, it was found that the chironomid sample consisted of 183 [[Operational taxonomic unit|Operational Taxonomic Units]] (OTUs; barcodes (sequences) that are often equivalent to morphological species. These 183 OTUs displayed 15 response types rather than the previously reported <ref>{{Cite journal|last=Beermann|first=Arne J.|last2=Elbrecht|first2=Vasco|last3=Karnatz|first3=Svenja|last4=Ma|first4=Li|last5=Matthaei|first5=Christoph D.|last6=Piggott|first6=Jeremy J.|last7=Leese|first7=Florian|date=2018|title=Multiple-stressor effects on stream macroinvertebrate communities: A mesocosm experiment manipulating salinity, fine sediment and flow velocity|url=https://linkinghub.elsevier.com/retrieve/pii/S0048969717320818|journal=Science of The Total Environment|language=en|volume=610-611|pages=961–971|doi=10.1016/j.scitotenv.2017.08.084|via=}}</ref> two response types recorded when all chironomids were grouped together in the same multiple stressor study. A similar trend was discovered in a study by Macher et al. (2016) which discovered cryptic diversity within the New Zealand mayfly species ''[http://www.terrain.net.nz/friends-of-te-henui-group/invertebrates-freshwater-new-zealand/mayfly-nymph-genus-deleatidium.html Deleatidium sp]'''.''''' This study found different response patterns of 12 molecular distinct OTUs to stressors which may change the consensus that this mayfly is sensitive to pollution <ref>{{Cite journal|last=Macher|first=Jan N.|last2=Salis|first2=Romana K.|last3=Blakemore|first3=Katie S.|last4=Tollrian|first4=Ralph|last5=Matthaei|first5=Christoph D.|last6=Leese|first6=Florian|date=2016|title=Multiple-stressor effects on stream invertebrates: DNA barcoding reveals contrasting responses of cryptic mayfly species|url=https://linkinghub.elsevier.com/retrieve/pii/S1470160X15004458|journal=Ecological Indicators|language=en|volume=61|pages=159–169|doi=10.1016/j.ecolind.2015.08.024|via=}}</ref>.
=== Shortcomings ===
Despite the advantages offered by DNA barcoding, it has also been suggested that DNA barcoding is best used as a complement to traditional morphological methods <ref name=":0" />. This recommendation is based on multiple perceived challenges.

'''Population parameters'''

DNA barcoding methods do not offer all information about the abundance of species, and cannot provide all information about population parameters. For example, DNA barcoding cannot provide data about fish population structure, condition, size age, or sex, which are key parameters which can only be obtained using capture-based methods <sup>[[User:Maria Kahlert (SLU)/sandbox#cite%20note-99|[99]]]</sup>.

==== Physical parameters ====
It is not completely straightforward to connect DNA barcodes with ecological preferences of the barcoded taxon in question, as need if barcoding should be used for biomonitoring. For example, detecting target DNA in aquatic systems depends for once on the concentration of DNA molecules at a site, which in turn can be affected by many factors. The presence of DNA molecules also depends on dispersion at a site, e.g. direction or strength of currents. It is not really known how DNA moves around in streams and lakes, which makes sampling difficult. Another factor might be the behavior of the target species, e.g. fish can have seasonal changes of movements, crayfish or mussels will release DNA in larger amounts just at certain times of their life (moulting, spawning). For DNA in soil, even less is known about distribution, quantity or quality.

==== Incomplete barcode reference libraries ====
The major limitation of the barcoding method is that it relies on barcode reference libraries for the taxonomic identification of the sequences. The taxonomic identification is accurate only if a reliable reference is available. However, most databases are still incomplete, especially for smaller organisms e.g. fungi, phytoplankton, nematoda etc. In addition, current databases contain misidentifications, spelling mistakes and other errors. There is massive curation and completion effort around the databases for all organisms necessary, involving large barcoding projects (for example the iBOL project for the Barcode of Life Data Systems (BOLD) reference database) <ref>{{Cite web|url=http://ibol.org/|title=The International Barcode of Life Consortium|website=International Barcode of Life|language=en-US|access-date=2019-03-29}}</ref><ref>{{Cite web|url=http://www.boldsystems.org/|title=Bold Systems v4|website=www.boldsystems.org|access-date=2019-04-02}}</ref>. However, completion and curation are difficult and time-consuming. Without vouchered specimens, there can be no certainty about whether the sequence used as a reference is correct. DNA sequence databases like GenBank contain many sequences that are not tied to [[Zoological specimen#Voucher%20specimens|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 <ref>{{Cite journal|last=Schander|first=Christoffer|last2=Willassen|first2=Endre|date=2005|title=What can biological barcoding do for marine biology?|url=http://www.tandfonline.com/doi/abs/10.1080/17451000510018962|journal=Marine Biology Research|language=en|volume=1|issue=1|pages=79–83|doi=10.1080/17451000510018962|issn=1745-1000|via=}}</ref><ref>{{Cite journal|last=Miller|first=S. E.|date=2007-03-20|title=DNA barcoding and the renaissance of taxonomy|url=http://www.pnas.org/cgi/doi/10.1073/pnas.0700466104|journal=Proceedings of the National Academy of Sciences|language=en|volume=104|issue=12|pages=4775–4776|doi=10.1073/pnas.0700466104|issn=0027-8424|pmc=PMC1829212|pmid=17363473}}</ref>. For many taxa, it can be however difficult to obtain reference specimens, for example with specimens that are difficult to catch, available specimens are poorly conserved, or adequate taxonomic expertise is lacking. Importantly, DNA barcodes can also be used to create interim taxonomy, in which case OTUs can be used as substitutes for traditional Latin binomials – thus significantly reducing dependency on fully-populated reference databases<ref>{{Cite journal|last=Ratnasingham|first=S.|date=2013|title=A DNA-based registry for all animal species: the Barcode Index Number (BIN) system|url=|journal=PloS one|volume=8(7)|pages=e66213|via=}}</ref>.

==== Technological bias ====
DNA barcoding also carries methodological bias, from sampling to [[bioinformatics]] data analysis. Beside the risk of contamination of the DNA sample by PCR inhibitors, primer bias is one of the major sources of errors in DNA barcoding <ref>{{Cite journal|last=Leese|first=Florian|last2=Elbrecht|first2=Vasco|date=2015-07-08|title=Can DNA-Based Ecosystem Assessments Quantify Species Abundance? Testing Primer Bias and Biomass—Sequence Relationships with an Innovative Metabarcoding Protocol|url=https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130324|journal=PLOS ONE|language=en|volume=10|issue=7|pages=e0130324|doi=10.1371/journal.pone.0130324|issn=1932-6203|pmc=PMC4496048|pmid=26154168}}</ref><ref>{{Cite journal|last=Elbrecht|first=Vasco|last2=Vamos|first2=Ecaterina Edith|last3=Meissner|first3=Kristian|last4=Aroviita|first4=Jukka|last5=Leese|first5=Florian|date=2017|title=Assessing strengths and weaknesses of DNA metabarcoding-based macroinvertebrate identification for routine stream monitoring|url=https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.12789|journal=Methods in Ecology and Evolution|language=en|volume=8|issue=10|pages=1265–1275|doi=10.1111/2041-210X.12789|issn=2041-210X}}</ref>. The isolation of an efficient DNA marker and the design of primers is a complex process and considerable effort has been made to develop primers for DNA barcoding in different taxonomic groups <ref>{{Cite web|url=https://www.sciencedirect.com/science/article/pii/S0048969718316322?via%3Dihub|title=ScienceDirect|website=www.sciencedirect.com|doi=10.1016/j.scitotenv.2018.05.002|access-date=2019-03-29}}</ref>. However, primers will often bind preferentially to some sequences, leading to differential primer efficiency and specificity and unrepresentative communities’ assessment and richness inflation <ref>{{Cite journal|last=Quince|first=Christopher|last2=Sloan|first2=William T.|last3=Hall|first3=Neil|last4=D'Amore|first4=Rosalinda|last5=Ijaz|first5=Umer Z.|last6=Schirmer|first6=Melanie|date=2015-03-31|title=Insight into biases and sequencing errors for amplicon sequencing with the Illumina MiSeq platform|url=https://academic.oup.com/nar/article/43/6/e37/2453415|journal=Nucleic Acids Research|language=en|volume=43|issue=6|pages=e37–e37|doi=10.1093/nar/gku1341|issn=0305-1048|pmc=PMC4381044|pmid=25586220}}</ref>. Thus, the composition of the sample’s communities sequences is mainly altered at the PCR step.  Besides, PCR replication is often required, but leads to an exponential increase in the risk of contamination. Several studies have highlighted the possibility to use mitochondria-enriched samples <ref>{{Cite journal|last=Huang|first=Quanfei|last2=Li|first2=Jiguang|last3=Fu|first3=Ribei|last4=Tang|first4=Min|last5=Zhou|first5=Lili|last6=Su|first6=Xu|last7=Yang|first7=Qing|last8=Liu|first8=Shanlin|last9=Li|first9=Yiyuan|date=2013-12-01|title=Ultra-deep sequencing enables high-fidelity recovery of biodiversity for bulk arthropod samples without PCR amplification|url=https://academic.oup.com/gigascience/article/2/1/2047-217X-2-4/2656120|journal=GigaScience|language=en|volume=2|issue=1|doi=10.1186/2047-217X-2-4|pmc=PMC3637469|pmid=23587339}}</ref><ref>{{Cite journal|last=Macher|first=Jan-Niklas|last2=Zizka|first2=Vera Marie Alida|last3=Weigand|first3=Alexander Martin|last4=Leese|first4=Florian|date=2018|title=A simple centrifugation protocol for metagenomic studies increases mitochondrial DNA yield by two orders of magnitude|url=https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.12937|journal=Methods in Ecology and Evolution|language=en|volume=9|issue=4|pages=1070–1074|doi=10.1111/2041-210X.12937|issn=2041-210X}}</ref> or PCR-free approaches to avoid these biases, but as of today, the DNA metabarcoding technique is still based on the sequencing of amplicons <ref>{{Cite web|url=https://www.sciencedirect.com/science/article/pii/S0048969718316322?via%3Dihub|title=ScienceDirect|website=www.sciencedirect.com|doi=10.1016/j.scitotenv.2018.05.002|access-date=2019-03-29}}</ref>. Other bias enter the picture during the sequencing and during the bioinformatic processing of the sequences, like the creation of chimeras,

==== Lack of standardization ====
Even as DNA barcoding is more widely used and applied, there is no agreement concerning the methods for DNA preservation or extraction, the choices of DNA markers and primers set, or PCR protocols. The parameters of bioinformatics [[Bioinformatics workflow management system|pipelines]] (for example OTU clustering, taxonomic assignment algorithms or thresholds etc.) are at the origin of much debate among DNA barcoding users <ref>{{Cite web|url=https://www.sciencedirect.com/science/article/pii/S0048969718316322?via%3Dihub|title=ScienceDirect|website=www.sciencedirect.com|doi=10.1016/j.scitotenv.2018.05.002|access-date=2019-03-29}}</ref>. Sequencing technologies are also rapidly evolving, together with the tools for the analysis of the massive amounts of DNA data generated, and standardization of the methods is urgently needed to enable collaboration and data sharing at greater spatial and time-scale. This standardisation of barcoding methods at the European scale is part of the objectives of the European COST Action DNAqua-net <ref>{{Cite web|url=https://dnaqua.net/|title=DNAquaNet|last=|first=|date=|website=|language=en-US|archive-url=|archive-date=|dead-url=|access-date=2019-03-29}}</ref> and is also addressed by CEN (the European Committee for Standardization)<ref>CEN (2018) CEN/TC 230/WORKING GROUP 2 – Proposal for a new Working Group WG28 ''“DNA and eDNA methods” A plan to fulfil the DNA and eDNA standardization needs of EU legislation in Water Policy'' (Proposal following decisions of the 2017 Berlin Meeting of CEN/TC 230, its Working Groups and eDNA COST representatives)</ref>.

Another criticism of DNA barcoding is its limited efficiency for accurate discrimination below species level (for example, to distinguish between varieties), for hybrid detection, and that it can be affected by evolutionary rates (Ref needed).

==== Mismatches between conventional (morphological) and barcode based identification ====
It is important to know that taxa lists derived by conventional (morphological) identification are not, and maybe never will be, directly comparable to taxa lists derived from barcode based iendtification because of several reasons. The most important cause is probably the incompleteness and lack of accuracy of the molecular reference databases preventing a correct taxonomic assignment of eDNA sequences. Taxa not present in reference databases will not be found by eDNA, and sequences linked to a wrong name will lead to incorrect identification<ref name=":0" />. Other known causes are a different sampling scale and size between a traditional and a molecular sample, the possible analysis of dead organisms, which can happen in different ways for both methods depending on organism group, and the specific selection of identification in either method, i.e. varying taxonomical expertise or possibility to idnetify certain orhgansim groups, respectively primer bias leading also to a potential biased analysis of taxa<ref name=":0" />.

==== Estimates of richness/diversity ====
DNA Barcoding can result in an over or underestimate of species richness and diversity. Some studies suggest that artifacts (identification of species not present in a community) are a major cause of inflated biodiversity <ref>{{Cite journal|last=Sloan|first=William T.|last2=Read|first2=L. Fiona|last3=Head|first3=Ian M.|last4=Neil Hall|last5=Davenport|first5=Russell J.|last6=Curtis|first6=Thomas P.|last7=Lanzén|first7=Anders|last8=Quince|first8=Christopher|date=2009|title=Accurate determination of microbial diversity from 454 pyrosequencing data|url=https://www.nature.com/articles/nmeth.1361|journal=Nature Methods|language=en|volume=6|issue=9|pages=639–641|doi=10.1038/nmeth.1361|issn=1548-7105|via=}}</ref> <ref>{{Cite journal|last=Kunin|first=Victor|last2=Engelbrektson|first2=Anna|last3=Ochman|first3=Howard|last4=Hugenholtz|first4=Philip|date=2010|title=Wrinkles in the rare biosphere: pyrosequencing errors can lead to artificial inflation of diversity estimates|url=https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1462-2920.2009.02051.x|journal=Environmental Microbiology|language=en|volume=12|issue=1|pages=118–123|doi=10.1111/j.1462-2920.2009.02051.x|issn=1462-2920}}</ref>. The most problematic issue are taxa represented by low numbers of sequencing reads. These reads are usually removed during the data filtering process, since different studies suggest that most of these low-frequency reads may be artifacts <ref>{{Cite journal|last=Rob Knight|first=|last2=Reeder|first2=Jens|date=2009|title=The 'rare biosphere': a reality check|url=https://www.nature.com/articles/nmeth0909-636|journal=Nature Methods|language=en|volume=6|issue=9|pages=636–637|doi=10.1038/nmeth0909-636|issn=1548-7105|via=}}</ref>. However, real rare taxa may exist among these low-abundance reads <ref>{{Cite journal|last=Zhan|first=Aibin|last2=Hulák|first2=Martin|last3=Sylvester|first3=Francisco|last4=Huang|first4=Xiaoting|last5=Adebayo|first5=Abisola A.|last6=Abbott|first6=Cathryn L.|last7=Adamowicz|first7=Sarah J.|last8=Heath|first8=Daniel D.|last9=Cristescu|first9=Melania E.|date=2013|title=High sensitivity of 454 pyrosequencing for detection of rare species in aquatic communities|url=https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.12037|journal=Methods in Ecology and Evolution|language=en|volume=4|issue=6|pages=558–565|doi=10.1111/2041-210X.12037|issn=2041-210X}}</ref>. Rare sequences can reflect unique lineages in communities which make them informative and valuable sequences. Thus, there is a strong need for more robust bioinformatics algorithms that allow the differentiation between informative reads and artifacts. Complete reference libraries would also allow a better testing of bioinformatics algorithms, by permitting a better filtering of artifacts (i.e. the removal of sequences alcking a counterpart among extant species) and therefore, it would be possible obtain a more accurate species assignment <ref>{{Cite journal|last=Zhan|first=Aibin|last2=He|first2=Song|last3=Brown|first3=Emily A.|last4=Chain|first4=Frédéric J. J.|last5=Therriault|first5=Thomas W.|last6=Abbott|first6=Cathryn L.|last7=Heath|first7=Daniel D.|last8=Cristescu|first8=Melania E.|last9=MacIsaac|first9=Hugh J.|date=2014|title=Reproducibility of pyrosequencing data for biodiversity assessment in complex communities|url=https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.12230|journal=Methods in Ecology and Evolution|language=en|volume=5|issue=9|pages=881–890|doi=10.1111/2041-210X.12230|issn=2041-210X}}</ref>. Cryptic diversity can also result in inflated biodiversity as one morphological species may actually split into many distinct molecular sequences <ref name=":0" />.

== DNA metabarcoding ==
[[File:DNA_(meta)barcoding_differences.pdf|alt=|thumb|Differences in the standard methods for DNA barcoding & metabarcoding. While DNA barcoding points to find a specific species, metabarcoding looks for the whole community.|478x478px]]DNA metabarcoding is defined as the barcoding of [[DNA]] or [[Environmental DNA|eDNA]] (environmental DNA) that allows for simultaneous identification of many taxa within the same (environmental) sample, however often within the same organism group. The main difference between the approaches is that metabarcoding, in contrast to barcoding, does not focus on one specific organism, but instead aims to determine species composition within a sample.

=== Methodology ===
The metabarcoding procedure, like general barcoding, covers the steps of [[DNA extraction]], [[Polymerase chain reaction|PCR amplification]], [[sequencing]] and [[data analysis]]. A barcode consists of a short variable [[gene]] region (for example, see [[Algae DNA barcoding#Target regions|different markers/barcodes]]) which is useful for taxonomic assignment flanked by highly conserved gene regions which can be used for [[Primer (molecular biology)|primer]] design<ref name=":15">{{Cite book|url=https://www.worldcat.org/oclc/1021883023|title=Environmental DNA : for biodiversity research and monitoring|last=Pierre,|first=Taberlet,|publisher=|others=Bonin, Aurelie, 1979-|year=|isbn=9780191079993|location=Oxford|pages=|oclc=1021883023}}</ref>. Different genes are used depending if the aim is to barcode single species or metabarcoding several species. In the latter case, a more universal gene is used. Metabarcoding does not use single species DNA/RNA as a starting point, but DNA/RNA from several different organisms derived from one environmental or bulk sample.

=== Applications ===
Metabarcoding has the potential to complement biodiversity measures, and even replace them in some instances, especially as the technology advances and procedures gradually become cheaper and more optimized and widespread.<ref>{{Cite journal|last=Ruppert|first=Krista M.|last2=Kline|first2=Richard J.|last3=Rahman|first3=Md Saydur|date=2019-1|title=Past, present, and future perspectives of environmental DNA (eDNA) metabarcoding: A systematic review in methods, monitoring, and applications of global eDNA|url=https://linkinghub.elsevier.com/retrieve/pii/S2351989418303500|journal=Global Ecology and Conservation|language=en|volume=17|pages=e00547|doi=10.1016/j.gecco.2019.e00547}}</ref><ref>{{Cite journal|last=Stoeck|first=Thorsten|last2=Frühe|first2=Larissa|last3=Forster|first3=Dominik|last4=Cordier|first4=Tristan|last5=Martins|first5=Catarina I.M.|last6=Pawlowski|first6=Jan|date=2018-2|title=Environmental DNA metabarcoding of benthic bacterial communities indicates the benthic footprint of salmon aquaculture|url=https://linkinghub.elsevier.com/retrieve/pii/S0025326X17310226|journal=Marine Pollution Bulletin|language=en|volume=127|pages=139–149|doi=10.1016/j.marpolbul.2017.11.065}}</ref>.

DNA metabarcoding applications include:

* Biodiversity monitoring in terrestrial and aquatic environments
* [[Paleontology]] and ancient ecosystems
* [[Pollen DNA barcoding|Plant-pollinator interactions]]
* Diet analysis
*Food safety

=== Advantages and challenges ===
The general advantages and shortcomings for barcoding reviewed above are valid also for metabarcoding. One particular drawback for metabarcoding studies is that there is no consensus yet regarding the optimal experimental design and bioinformatics criteria to be applied in eDNA metabarcoding<ref>{{Cite journal|last=Evans|first=Darren M.|last2=Kitson|first2=James J. N.|last3=Lunt|first3=David H.|last4=Straw|first4=Nigel A.|last5=Pocock|first5=Michael J. O.|date=2016|title=Merging DNA metabarcoding and ecological network analysis to understand and build resilient terrestrial ecosystems|url=https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/1365-2435.12659|journal=Functional Ecology|language=en|volume=30|issue=12|pages=1904–1916|doi=10.1111/1365-2435.12659|issn=1365-2435}}</ref>. However, there are current joined attempts, like e.g. the EU COST network [https://dnaqua.net/ DNAqua-Net], to move forward by exchanging experience and knowledge to establish best-practice standards for biomonitoring.<ref name=":0" />

<br />

== Further reading ==
Detailed information on DNA barcoding of different organisms can be found here:

*[[Microbial DNA barcoding]]
*[[Algae DNA barcoding]]
*[[Fish DNA barcoding]]
*[[Pollen DNA barcoding]]
*[[DNA barcoding in diet assessment]]
*[[DNA profiling]]
*Animal DNA barcoding
*Higher Plants DNA barcoding
*Fungi DNA barcoding
*Protozoan DNA barcoding
*[http://swebol.org/ SweBOL]
*[http://www.finbol.org/ FinBOL]
*[http://ibol.org/ International Barcode of Life Project (iBOL)]
*[[Consortium for the Barcode of Life]]
*[http://v4.boldsystems.org/index.php/Public_BINSearch?searchtype=records BOLD]
*[https://unite.ut.ee/ UNITE]
*[https://www6.inra.fr/carrtel-collection/Barcoding-database Diat.barcode]

== References ==

Revision as of 07:41, 23 May 2019

Not to be confused with the DNA barcode involved in optical mapping of DNA.


DNA barcoding is a method of species identification using a short section of DNA from a specific gene or genes. That DNA section (also called "sequence") can be used to identify an organism; in the same way as a supermarket scanner uses the familiar black stripes of the UPC barcode to identify a purchase[1]. These "barcodes" are sometimes used in an effort to identify unknown species, parts of an organism, or simply to catalog as many taxa as possible.

Different gene regions are used to identify the different organismal groups using barcoding. The most commonly used barcode region for animals and some protists is a portion of the cytochrome oxidase I (COI or COX1) gene, found in mitochondrial DNA. Other genes suitable for DNA barcoding are the Internal transcribed spacer (ITS) rRNA often used for fungi and RuBisCO used for plants[2][3]. Microorganisms are detected using different gene regions. The 16S rRNA gene for example is widely used in identification of prokaryotes, whereas the 18S rRNA gene is mostly used for detecting microbial eukaryotes. These gene regions are chosen because they have less intraspecific (within species) variation than interspecific (between species) variation, which is known as the "Barcoding Gap" [4].

Some applications of DNA barcoding include: identifying plant leaves even when flowers or fruits are not available; identifying pollen collected on the bodies of pollinating animals; identifying insect larvae which may have fewer diagnostic characters than adults; or investigating the diet of an animal based on its stomach content, saliva or feces[5]. When barcoding is used to identify organisms from a sample containing DNA from more than one organism, the term DNA metabarcoding is used[6][7], e.g. DNA metabarcoding of diatom communities in rivers and streams, which is used to assess water quality[8].

DNA barcoding scheme

Background

DNA barcoding techniques were developed from early DNA sequencing work on microbial communities using the 5S rRNA gene[9]. In 2003, specific methods and terminology of modern DNA barcoding were proposed as a standardized method for identifying species, as well as potentially allocating unknown sequences to higher taxa such as orders and phyla, in a paper by Paul D.N. Hebert et al. from the University of Guelph, Ontario, Canada[10]. Hebert and his colleagues demonstrated the utility of the cytochrome coxidase I (COI) gene, first utilized by Folmer et al. in 1994, using their published DNA primers as a tool for phylogenetic analyses at the species levels[10] as a suitable discriminatory tool between metazoan invertebrates[11]. The "Folmer region" of the COI gene is commonly used for distinction between taxa based on its patterns of variation at the DNA level. The relative ease of retrieving the sequence, and variability mixed with conservation between species, are some of the benefits of COI. 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".

Methodology

Sampling and preservation

Barcoding can be done from tissue from a target specimen, from a mixture of organisms (bulk sample), or from DNA present in environmental samples (e.g. water or soil). The methods for sampling, preservation or analysis differ between those different types of sample.

Tissue samples

To barcode a tissue sample from the target specimen, a small piece of skin, a scale, a leg or antennae is sufficient. To avoid contamination, it is necessary to sterilize used tools between samples. It is recommended to collect two samples from one specimen, one to archive, and one for the barcoding process. Sample preservation is crucial to avoid DNA degradation.

Bulk samples

A bulk sample is a type of environmental sample containing several organisms from the taxonomic group under study. The difference between bulk samples (in the sense used here) and other environmental samples is that the bulk sample usually provides good-quality and quantity of DNA[12]. Examples of bulk samples are aquatic macroinvertebrate sample collected by kick-net, or insect samples collected with a Malaise trap. Filtered or size-fractionated water samples containing whole organisms like unicellular eukaryotes are also sometimes defined as bulk samples. Such samples can be collected by the same techniques as used to obtain traditional samples for morphology-based identification.

eDNA samples

The environmental DNA (eDNA) method is a non-invasive approach to detect and identify species through cellular debris or extracellular DNA present in environmental samples (e.g. water or soil) through barcoding or metabarcoding. The approach is based on the fact that every living organism leave DNA in the environment, and this environmental DNA can be detected even in very low abundance. Thus, for field sampling, the most crucial part is to use DNA-free material and tools on each sampling site or sample to avoid contamination, if the DNA of the target organism(s) is probably present in low quantity. On the other hand, an eDNA sample always include the DNA of whole-cell, living microorganisms, often present in large quantities. Therefore, microorganism samples taken in the natural anvironment also are called eDNA samples, but here contamination is less problematic due to the high quantity of the target organisms. The eDNA method is applied on most sample types, like water, sediment, soil, animal feces, stomach content or blood from e.g. leeches.[13] 

DNA extraction, amplification and sequencing

DNA barcoding requires that DNA in the sample is extracted. Several different DNA extraction methods exist, and factors like cost, time, sample type and yield affect the selection of the optimal method.

Organismal or eDNA samples often contain inhibitor molecules that can affect the PCR negatively when DNA is amplified in polymerase chain reaction (PCR)[14]. Removal of these inhibitors is crucial to ensure that high quality DNA is available for subsequent analyzing.

Amplification of the extracted DNA is a required step in DNA barcoding. Typically. only a small fragment of the total DNA material is sequenced (typically 400–800 base pairs)[15] to obtain the DNA barcode. Amplification of eDNA material is usually focused on smaller fragment sizes (<200 base pairs), as eDNA is more likely to be fragmented than DNA material from other sources. However, some studies argue that there is no relationship between amplicon size and detection rate of eDNA[16][17].

HiSeq sequencers at SciLIfeLab in Uppsala, Sweden. The picture has been taken during the excursion of SLU course PNS0169 in March 2019.

When the DNA barcode marker region has been amplified, the next step is to sequence the marker region using DNA sequencing methods.[18][19]. Many different sequencing platforms are available, and the technical development is fast.

Marker selection

A schematic view of primers and target region, demonstrated on 16S rRNA gene in Pseudomonas. As primers, one typically selects short conserved sequences with low variability, which can thus amplify most or all species in the chosen target group. The primers are used to amplify a highly variable target region in between the two primers, which is then used for species discrimination. Modified from »Variable Copy Number, Intra-Genomic Heterogeneities and Lateral Transfers of the 16S rRNA Gene in Pseudomonas« by Bodilis, Josselin; Nsigue-Meilo, Sandrine; Besaury, Ludovic; Quillet, Laurent, used under CC BY, available from: https://www.researchgate.net/figure/Hypervariable-regions-within-the-16S-rRNA-gene-in-Pseudomonas-The-plotted-line-reflects_fig2_224832532.

Markers used for DNA barcoding are called barcodes. In order to succesfully characterize species based on DNA barcodes, selection of informative DNA regions is crucial. A good DNA barcode should have low intra-specific and high inter-specific variability[10] and possess conserved flanking sites for developing universal PCR primers for wide taxonomic application. The goal is to design primers that will target most or all the species in the studied group of organisms (high taxonomic resolution). The length of the barcode sequence should be short enough to be used with current sampling source, DNA extraction, amplification and sequencing methods[20].

Ideally, one gene sequence would be used for all taxonomic groups, from viruses to plants and animals. However, no such gene region has been found yet, so different barcodes are used for different groups of organisms[21], or depending on the study question.

For animals, the most widely used barcode is mitochondrial cytochrome C oxidase I (COI) locus[22]. Additionally, other mitochondrial genes, such as Cytb, 12S or 16S are also used. Mitochondrial genes are preferred over nuclear genes because of their lack of introns, their haploid mode of inheritance and their limited recombination[22][23]. Moreover, each cell has various mitochondria (up to several thousand) and each of them contains several circular DNA molecules. Mitochondria can therefore offer abundant source of DNA even when sample tissue is limited[21].

In plants, however, mitochondrial genes are not appropriate for DNA barcoding because they exhibit low mutation rates[24]. A few candidate genes have been found in the chloroplast genome, the most promising being maturase K gene (matK) alone or in association with other genes. Multi-locus markers such as ribosomal internal transcribed spacers (ITS DNA) along with matK, rbcL, trnH or other genes have also been used for species identification[21]. The best discrimination between plant species has been achieved when using two or more chloroplast barcodes[25].

For bacteria, the small subunit of ribosomal RNA (16S) gene can be used for different taxa, as it is highly conserved[26]. Some studies suggest COI[27], type II chaperonin (cpn60)[28] or β subunit of RNA polymerase (rpoB)[29] also could serve as bacterial DNA barcodes.

Barcoding fungi is more challenging, and more than one primer combination might be required[30]. COI marker performs well in certain fungi groups[31], but not equally well in others[32]. Therefore, additional markers are being used, such as ITS rDNA and the large subunit of nuclear ribosomal RNA (LSU)[33].

Within the group of protists, various barcodes have been proposed, such as the D1–D2 or D2–D3 regions of 28S rDNA, V4 subregion of 18S rRNA gene, ITS rDNA and COI. Additionally, some specific barcodes can be used for photosynthetic protists, for example the large subunit of ribulose-1,5-bisphosphate carboxylase-oxygenase gene (rbcL) and the chloroplastic 23S rRNA gene[21].

Markers that have been used for DNA barcoding in different organism groups, modified from Purty and Chatterjee (1).
Organism group Marker gene/locus
Animals COI[34], Cytb[35], 12S[36], 16S[37]
Plants matK[38], rbcL[39], psbA-trnH[40], ITS[41]
Bacteria COI[27], rpoB[29], 16S[42], cpn60[28], tuf[43], RIF[44], gnd[45]
Fungi ITS[46], RPB1 (LSU), RPB2 (LSU), 18S (SSU)[33]
Protists ITS[47], COI[48], rbcL[49], 18S[50], 28S[49]

Reference libraries and bioinformatics

Reference libraries are used for the taxonomic identification, also alled annotation, of sequences obtained from barcoding or metabarcoding. These databases contain the DNA barcodes assigned to previously identified taxa. Most reference libraries do not have a complete setup of all species within an organism group, and new entries are continuesly created. In the case of macro- and many microorganisms (such as algae), the procedure requires detailed documentation (sampling location and date, person who collected it, image, etc.) and authoritative taxonomic identification of the voucher specimen, and well as submission of sequences in a particular format. The process also requires the storage of voucher specimens in museum collections and other collaborating institutions. Both taxonomically comprehensive coverage and content quality are important for identification accuracy[51]. Several reference databases exist depending on the organism group and the genetic marker used. There are smaller, national databases (e.g. FinBOL), and large consortia like the International Barcode of Life Project (iBOL)[52].

BOLD

Launched in 2007, the Barcode of Life Data System (BOLD)[53] is one of the biggest databases, containing more than 450 000 BINs (Barcode index numbers) in 2019. It is a freely accessible repository for the specimen and sequence records for barcode studies, and it is also a workbench aiding the management, quality assurance and analysis of barcode data. The database mainly contains BIN records of animals using the COI genetic marker.

UNITE

The UNITE database[54] was launched in 2003 and is a reference database for the molecular identification of fungal species with the internal transcribed spacer (ITS) genetic marker region. This database is based on the concept of species hypothesis: you choose the % at which you want to work, and the sequences are sorted in comparison to sequences obtained from voucher specimens identified by experts.

Diat.barcode

Diat.barcode[55] database was first published under the name R-syst::diatom[56] in 2016 starting with data from two sources: the Thonon culture collection (TCC) in the hydrobiological station of the French National Institute for Agricultural Research (INRA), and from the NCBI (National Center for Biotechnology Information) nucleotide database. Diat.barcode provides data for two genetic markers, rbcL (Ribulose-1,5-bisphosphate carboxylase/oxygenase) and 18S (18S ribosomal RNA). The database also involves additional, trait information of species, like morphological characteristics (biovolume, size dimensions, etc.), life-forms (mobility, colony-type, etc.) or ecological features (pollution sensitivity, etc.).

Bioinformatic analysis

In order to obtain well structured, clean and interpretable data, raw sequencing data must be processed through bioinformatics analysis. The fastq file with the sequencing data contains two types of information: the sequences detected in the sample (fasta file) and a quality file with quality scores (PHRED scores) associated to each nucleotide of each DNA sequence. The PHRED scores indicate the probability with which the associated nucleotide has been correctly scored.

PHRED quality score and the associated certainty level
10 90%
20 99%
30 99.9%
40 99.99%
50 99.999%

In general, the PHRED score is decreasing towards the end of the DNA sequences, thus some bioinformatics pipelines simply cut the end of the sequences.

Some sequencing technologies, like Miseq, use paired-end sequencing during which sequencing is carried out from both directions producing better quality. The overlapping sequences are then aligned into contigs and merged. Usually, several samples are pooled in one run, and each sample is characterized by a short DNA fragment, the tag. In a demultiplexing step, sequences are sorted after their tags into samples again. For further analysis, tags and other adapters are removed from the barcoding sequence DNA fragment. During trimming, the bad quality sequences (low PHRED scores), or sequences that are much shorter or longer than the targeted DNA barcode, are removed. The following dereplication step is the process where all of the quality-filtered sequences are collapsed into a set of unique reads (individual sequence units ISUs) with the information of their abundance in the samples. After that, chimeras (i.e. compund sequences formed from pieces of mixed origin) are detected and removed. Finally, the sequences are clustered into OTUs (Operational Taxonomic Units), using one of many clustering strategies. The most frequently used bioinformatic softwares are e.g. Mothur[57], Uparse[58], Qiime[59], Galaxy[60], Obitools[61], JAMP[62], DADA2[63].

Comparing the abundance of reads, i.e. sequences, between different samples is still a challenge because both the total number of reads in a sample as well as the relative amount of reads for a species can vary between samples, methods, or other variables. For comparison, one may then reduce the number of reads of each sample to the minimal number of reads of the samples to be compared – a process called rarefaction. Another way is to use the relative abundance of reads[64].


Species identification and taxonomic assignment

The taxonomic assignment of the OTUs to species is achieved by matching of sequences to reference libraries. The Basic Local Alignment Search Tool (BLAST) is commonly used to identify regions of similarity between sequences by comparing sequence reads from the sample to sequences in reference databases[65]. If the reference database contains sequences of the relevant species, then the sample sequences can be identified to species level. If a sequences cannot be matched to an existing reference library entry, DNA barcoding can be used to create a new entry.

In some cases, due to the incompleteness of reference databases, identification can only be done to higher taxonomic categories, such as assignment to a family or class. However, in some organism groups such as bacteria, taxonomic assignment to species level is often not possible. In such cases, a sample may be assigned to a particular operational taxonomic unit (OTU).


Applications

Applications of DNA barcoding include identification of new species, safety assessment of food, identification and assessment of cryptic species, detection of alien species, identification of endangered and threatened species[66], linking egg and larval stages to adult species, securing intellectual property rights for bioresources, framing global management plans for conservation strategies and elucidate feeding niches.[67] DNA barcode markers can be applied on basic questions in systematics, ecology, evolutionary biology and conservation, including community assembly, species interaction networks, taxonomic discovery, and assessing priority areas for environmental protection.

Identification of species

Specific short DNA sequences or markers from a standardized region of the genome can provide a DNA barcode for identifying species.[68] Molecular methods are especially useful when traditional methods are not applicable. DNA barcoding has great applicability in identification of larvae for which there are generally few diagnostic characters available, and in association of different life stages (e.g. larval and adult) in many animals.[69] Identification of species listed in the Convention of the International Trade of Endangered Species (CITES) appendixes using barcoding techniques is used in monitoring of illegal trade[70].

Detection of invasive species

Alien species can be detected via barcoding[71][72]. Barcoding can be suitable for detection of species in e.g. border control, where rapid and accurate morphological identification is often not possible due to several similar specimens, lack of sufficient diagnostic characteristics[71] and/or lack of taxonomic expertise. Barcoding and metabarcoding can also be used to screen ecosystems for invasive species, and to distinguish between an invasive species and native, morphologically similar, species[73].

Phylogenetic construction

DNA barcoding is a useful tool for species identification, with less information on phylogenetic relatedness. Still, barcodes can provide insights into evolution, for example COI barcodes illustrate molecular evolution and protein function in animals at different taxonomic levels. COI is informative on recent divergence, however but not useful for estimating evolutionary relationships[79].

Delimiting cryptic species

DNA barcoding enables the identification and recognition of cryptic species[74]. The results of DNA barcoding analyses depend however upon the choice of analytical methods, so the process of delimiting cryptic species using DNA barcodes can be as subjective as any other form of taxonomy. Hebert et al.(2004) concluded that the butterfly Astraptes fulgerator in north-western Costa Rica actually consists of 10 different species[75]. 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[76]. Smith et al. (2007) used cytochrome c oxidase I DNA barcodes for species identification of the 20 morphospecies of Belvosia parasitoid flies (Diptera: Tachinidae) reared from caterpillars (Lepidoptera) in Area de Conservación Guanacaste (ACG), northwestern Costa Rica. These authors discovered that barcoding raises the species count to 32, by revealing that each of the three parasitoid species, previously considered as generalists, actually are arrays of highly host-specific cryptic species[77]. For 15 morphospecies of polychaetes within the deep Antarctic benthos studied through DNA barcoding, cryptic diversity was found in 50% of the cases. Furthermore 10 previously overlooked morphospecies were detected, increasing the total species richness in the sample by 233%[78] .

Barcoding is a tool to vouch for food quality. Here, DNA from traditional Norwegian Christmas food is extracted at the molecular systematic lab at NTNU University Museum.

Diet analysis and food web application

DNA barcoding and metabarcoding can be useful in diet analysis studies[79], and is typically used if prey specimens cannot be identified based on morphological characters[80][81]. There is a range of sampling approaches in diet analysis: DNA metabarcoding can be conducted on stomach contents[82], feces[81][83], saliva[84] or whole body analysis[66][85]. In fecal samples or highly digested stomach contents, it is often not possible to distinguish tissue from single species, and therefore metabarcoding can be applied instead[81][86]. Feces or saliva represent non-invasive sampling approaches, while whole body analysis often means that the individual needs to be killed first. For smaller organisms, sequencing for stomach content is then often done by sequencing the entire animal.

Barcoding for food safety

DNA barcoding represents an essential tool to evaluate the quality of food products. The purpose is to guarantee food traceability, to minimize food piracy, and to valuate local and typical agro-food production. Another purpose is to safeguard public health; for example, metabarcoding offers the possibility to identify groupers causing Ciguatera fish poisoning from meal remnants[87], or to separate poisonous mushrooms from edible ones (Ref).

Biomonitoring and ecological assessment

DNA barcoding can be used to assess the presence of endangered species for conservation efforts (Ref), or the presence of indicator species reflective to specific ecological conditions (Ref), for example excess nutrients or low oxygen levels.

Potentials and shortcomings

Potentials

Traditional bioassessment methods are well established internationally, and serve biomonitoring well, as for example for aquatic bioassessment within the EU Directives WFD and MSFD. However, DNA barcoding could improve traditional methods for the following reasons; DNA barcoding (i) can increase taxonomic resolution and harmonize the identification of taxa which are difficult to identify or lack experts, (ii) can more accurately/precisely relate environmental factors to specific taxa (iii) can increase comparability among regions, (iv) allows for the inclusion of early life stages and fragmented specimens, (v) allows delimitation of cryptic/rare species (vi) allows for development of new indices e.g. rare/cryptic species which may be sensitive/tolerant to stressors, (vii) increases the number of samples which can be processed and reduces processing time resulting in increased knowledge of species ecology, (viii) is a non-invasive way of monitoring when using eDNA methods [88].

Time and cost

DNA Barcoding is faster than traditional morphological methods all the way from training through to taxonomic assignment. It takes less time to gain expertise in DNA methods than becoming an expert in taxonomy. In addition, the DNA barcoding workflow (i.e. from sample to result) is generally quicker than traditional morphological workflow and allows the processing of more samples.

Taxonomic resolution

DNA Barcoding allows the resolution of taxa from higher (e.g. family) to lower (e.g. species) taxonomic levels, that are otherwise too difficult to identify using traditional morphological methods, like e.g. identification via microscopy. For example, Chironomidae (the non-biting midge) are widely distributed in both terrestrial and freshwater ecosystems. Their richness and abundance make them important for ecological processes and networks, and they are one of many invertebrate groups used in biomonitoring. Invertebrate samples can contain as many as 100 species of chironomids which often make up as much as 50% of a sample. Despite this, they are usually not identified below the family level because of the taxonomic expertise and time required [89]. This may result in different chironomid species with different ecological preferences grouped together, resulting in potential assessment of water quality.

DNA Barcoding provides the opportunity to resolve taxa, and directly relate stressor effects to specific taxa such as individual chironomid species. For example, Beermann et al. (2018) DNA barcoded Chironomidae to investigate their response to multiple stressors; reduced flow, increased fine-sediment and increased salinity [90]. After barcoding, it was found that the chironomid sample consisted of 183 Operational Taxonomic Units (OTUs; barcodes (sequences) that are often equivalent to morphological species. These 183 OTUs displayed 15 response types rather than the previously reported [91] two response types recorded when all chironomids were grouped together in the same multiple stressor study. A similar trend was discovered in a study by Macher et al. (2016) which discovered cryptic diversity within the New Zealand mayfly species Deleatidium sp. This study found different response patterns of 12 molecular distinct OTUs to stressors which may change the consensus that this mayfly is sensitive to pollution [92].

Shortcomings

Despite the advantages offered by DNA barcoding, it has also been suggested that DNA barcoding is best used as a complement to traditional morphological methods [88]. This recommendation is based on multiple perceived challenges.

Population parameters

DNA barcoding methods do not offer all information about the abundance of species, and cannot provide all information about population parameters. For example, DNA barcoding cannot provide data about fish population structure, condition, size age, or sex, which are key parameters which can only be obtained using capture-based methods [99].

Physical parameters

It is not completely straightforward to connect DNA barcodes with ecological preferences of the barcoded taxon in question, as need if barcoding should be used for biomonitoring. For example, detecting target DNA in aquatic systems depends for once on the concentration of DNA molecules at a site, which in turn can be affected by many factors. The presence of DNA molecules also depends on dispersion at a site, e.g. direction or strength of currents. It is not really known how DNA moves around in streams and lakes, which makes sampling difficult. Another factor might be the behavior of the target species, e.g. fish can have seasonal changes of movements, crayfish or mussels will release DNA in larger amounts just at certain times of their life (moulting, spawning). For DNA in soil, even less is known about distribution, quantity or quality.

Incomplete barcode reference libraries

The major limitation of the barcoding method is that it relies on barcode reference libraries for the taxonomic identification of the sequences. The taxonomic identification is accurate only if a reliable reference is available. However, most databases are still incomplete, especially for smaller organisms e.g. fungi, phytoplankton, nematoda etc. In addition, current databases contain misidentifications, spelling mistakes and other errors. There is massive curation and completion effort around the databases for all organisms necessary, involving large barcoding projects (for example the iBOL project for the Barcode of Life Data Systems (BOLD) reference database) [93][94]. However, completion and curation are difficult and time-consuming. Without vouchered specimens, there can be no certainty about whether the sequence used as a reference is correct. 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 [95][96]. For many taxa, it can be however difficult to obtain reference specimens, for example with specimens that are difficult to catch, available specimens are poorly conserved, or adequate taxonomic expertise is lacking. Importantly, DNA barcodes can also be used to create interim taxonomy, in which case OTUs can be used as substitutes for traditional Latin binomials – thus significantly reducing dependency on fully-populated reference databases[97].

Technological bias

DNA barcoding also carries methodological bias, from sampling to bioinformatics data analysis. Beside the risk of contamination of the DNA sample by PCR inhibitors, primer bias is one of the major sources of errors in DNA barcoding [98][99]. The isolation of an efficient DNA marker and the design of primers is a complex process and considerable effort has been made to develop primers for DNA barcoding in different taxonomic groups [100]. However, primers will often bind preferentially to some sequences, leading to differential primer efficiency and specificity and unrepresentative communities’ assessment and richness inflation [101]. Thus, the composition of the sample’s communities sequences is mainly altered at the PCR step.  Besides, PCR replication is often required, but leads to an exponential increase in the risk of contamination. Several studies have highlighted the possibility to use mitochondria-enriched samples [102][103] or PCR-free approaches to avoid these biases, but as of today, the DNA metabarcoding technique is still based on the sequencing of amplicons [104]. Other bias enter the picture during the sequencing and during the bioinformatic processing of the sequences, like the creation of chimeras,

Lack of standardization

Even as DNA barcoding is more widely used and applied, there is no agreement concerning the methods for DNA preservation or extraction, the choices of DNA markers and primers set, or PCR protocols. The parameters of bioinformatics pipelines (for example OTU clustering, taxonomic assignment algorithms or thresholds etc.) are at the origin of much debate among DNA barcoding users [105]. Sequencing technologies are also rapidly evolving, together with the tools for the analysis of the massive amounts of DNA data generated, and standardization of the methods is urgently needed to enable collaboration and data sharing at greater spatial and time-scale. This standardisation of barcoding methods at the European scale is part of the objectives of the European COST Action DNAqua-net [106] and is also addressed by CEN (the European Committee for Standardization)[107].

Another criticism of DNA barcoding is its limited efficiency for accurate discrimination below species level (for example, to distinguish between varieties), for hybrid detection, and that it can be affected by evolutionary rates (Ref needed).

Mismatches between conventional (morphological) and barcode based identification

It is important to know that taxa lists derived by conventional (morphological) identification are not, and maybe never will be, directly comparable to taxa lists derived from barcode based iendtification because of several reasons. The most important cause is probably the incompleteness and lack of accuracy of the molecular reference databases preventing a correct taxonomic assignment of eDNA sequences. Taxa not present in reference databases will not be found by eDNA, and sequences linked to a wrong name will lead to incorrect identification[88]. Other known causes are a different sampling scale and size between a traditional and a molecular sample, the possible analysis of dead organisms, which can happen in different ways for both methods depending on organism group, and the specific selection of identification in either method, i.e. varying taxonomical expertise or possibility to idnetify certain orhgansim groups, respectively primer bias leading also to a potential biased analysis of taxa[88].

Estimates of richness/diversity

DNA Barcoding can result in an over or underestimate of species richness and diversity. Some studies suggest that artifacts (identification of species not present in a community) are a major cause of inflated biodiversity [108] [109]. The most problematic issue are taxa represented by low numbers of sequencing reads. These reads are usually removed during the data filtering process, since different studies suggest that most of these low-frequency reads may be artifacts [110]. However, real rare taxa may exist among these low-abundance reads [111]. Rare sequences can reflect unique lineages in communities which make them informative and valuable sequences. Thus, there is a strong need for more robust bioinformatics algorithms that allow the differentiation between informative reads and artifacts. Complete reference libraries would also allow a better testing of bioinformatics algorithms, by permitting a better filtering of artifacts (i.e. the removal of sequences alcking a counterpart among extant species) and therefore, it would be possible obtain a more accurate species assignment [112]. Cryptic diversity can also result in inflated biodiversity as one morphological species may actually split into many distinct molecular sequences [88].

DNA metabarcoding

Differences in the standard methods for DNA barcoding & metabarcoding. While DNA barcoding points to find a specific species, metabarcoding looks for the whole community.

DNA metabarcoding is defined as the barcoding of DNA or eDNA (environmental DNA) that allows for simultaneous identification of many taxa within the same (environmental) sample, however often within the same organism group. The main difference between the approaches is that metabarcoding, in contrast to barcoding, does not focus on one specific organism, but instead aims to determine species composition within a sample.

Methodology

The metabarcoding procedure, like general barcoding, covers the steps of DNA extraction, PCR amplification, sequencing and data analysis. A barcode consists of a short variable gene region (for example, see different markers/barcodes) which is useful for taxonomic assignment flanked by highly conserved gene regions which can be used for primer design[12]. Different genes are used depending if the aim is to barcode single species or metabarcoding several species. In the latter case, a more universal gene is used. Metabarcoding does not use single species DNA/RNA as a starting point, but DNA/RNA from several different organisms derived from one environmental or bulk sample.

Applications

Metabarcoding has the potential to complement biodiversity measures, and even replace them in some instances, especially as the technology advances and procedures gradually become cheaper and more optimized and widespread.[113][114].

DNA metabarcoding applications include:

Advantages and challenges

The general advantages and shortcomings for barcoding reviewed above are valid also for metabarcoding. One particular drawback for metabarcoding studies is that there is no consensus yet regarding the optimal experimental design and bioinformatics criteria to be applied in eDNA metabarcoding[115]. However, there are current joined attempts, like e.g. the EU COST network DNAqua-Net, to move forward by exchanging experience and knowledge to establish best-practice standards for biomonitoring.[88]


Further reading

Detailed information on DNA barcoding of different organisms can be found here:

References

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