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. 2019 Nov 6;9(23):13515–13520. doi: 10.1002/ece3.5808

Distinguishing Anuran species by high‐resolution melting analysis of the COI barcode (COI‐HRM)

Steven Everman 1, Shiao Y Wang 1,✉
PMCID: PMC6912877  PMID: 31871662

Abstract

Taxonomic identification can be difficult when two or more species appear morphologically similar. DNA barcoding based on the sequence of the mitochondrial cytochrome c oxidase 1 gene (COI) is now widely used in identifying animal species. High‐resolution melting analysis (HRM) provides an alternative method for detecting sequence variations among amplicons without having to perform DNA sequencing. The purpose of this study was to determine whether HRM of the COI barcode can be used to distinguish animal species. Using anurans as a model, we found distinct COI melting profiles among three congeners of both Lithobates spp. and Hyla spp. Sequence variations within species shifted the melting temperature of one or more melting domains slightly but do not affect the distinctness of the melting profiles for each species. An NMDS ordination plot comparing melting peak profiles among eight Anuran species showed overlapping profiles for Lithobates sphenocephala and Gastrophryne carolinensis. The COI amplicon for both species contained two melting domains with melting temperatures that were similar between the two species. The two species belong to two different families, highlighting the fact that COI melting profiles do not reveal phylogenetic relationships but simply reflect DNA sequence differences among stretches of DNA within amplicons. This study suggests that high‐resolution melting analysis of COI barcodes (COI‐HRM) may be useful as a simple and rapid method to distinguish animal species that appear morphologically similar.

Keywords: COI, DGGE, high‐resolution melting analysis, HRM, species identification

Taxonomic identification can be difficult when two or more species appear morphologically similar. DNA barcoding based on the mitochondrial cytochrome c oxidase 1 gene (COI) is widely used in identifying animal species. High‐resolution melting analysis of COI barcodes (COI‐HRM) provides a simple and rapid method to identify or distinguish animal species without the need to sequence DNA.

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1. INTRODUCTION

Taxonomic identification can be difficult when two or more species appear morphologically similar. For example, the frogs Hyla versicolor and Hyla chrysoscelis share breeding ponds (Harding, 1997) but appear identical and can only be differentiated by their mating calls and karyotype (Collins & Conant, 1998; Jaslow & Vogt, 1977). Among five species of Radix snails, intraspecific variability in shell morphology and anatomy overlap among species (Glöer, 2002). For many species, the difficulty is more acute for early life stages such as embryos and juveniles when definitive morphological characteristics are not yet established. DNA‐based species identification, however, is extremely reliable. One widely used approach is DNA barcoding using a region of the mitochondrial cytochrome oxidase subunit I (COI) gene for animal species (Hebert, Cywinska, & Ball, 2003). The gene is PCR‐amplified, sequenced, and then compared to a sequence database for species identification.

An alternative to DNA sequencing for detecting variations among PCR amplicon sequences is high‐resolution melting analysis (HRM). During HRM, the fluorescence of PCR amplicons in the presence of a dsDNA saturating dye is continuously monitored as temperature increases at predetermined increments. Because there is a loss in fluorescence when double‐stranded DNA denatures and the temperature at which DNA melts is sequence‐dependent, unique amplicons produce a unique melting curve. The first derivative of each melting curve can then be plotted against temperature to produce unique melting peak profiles that may be useful for species identification.

The effectiveness of HRM for distinguishing related species is unclear. Of concern is the effect of amplicon size. With primers LCO1490 and HC02198, frequently used to DNA barcode animals, a 658‐bp region of interest within the COI gene is amplified (Folmer, Black, Hoeh, Lutz, & Vrijenhoek, 1994). For screening single‐nucleotide polymorphism, sensitivity and specificity is greater for PCR products of 300 bp or less compared to larger products (Reed & Wittwer, 2004). However, large PCR products can produce melting peak profiles with multiple melting peaks (Lilliebridge, Tong, Giffard, & Holt, 2011; Rasmussen, Saint, & Monis, 2007) that aid in differentiating sequence variants. Indeed, detection of virus serotypes using HRM analysis of a ~600 bp PCR product has been reported (Steer, Kirkpatrick, O'Rourke, & Noormohammadi, 2009).

The goal of the present study was to test the usefulness of high‐resolution melting analysis of the COI barcode (COI‐HRM) to distinguish species using anurans as a model. The sequence of the COI gene has been shown to be effective for identifying anurans to species (Perl et al., 2014; Smith, Poyarkov, & Hebert, 2008; Vences, Thomas, Bonett, & Vieites, 2005). Using DNA collected from eight different species in Hattiesburg, Mississippi, we found that PCR‐HRM of the COI barcode produced melting peak profiles that were highly reproducible and useful for distinguishing species.

2. MATERIALS AND METHODS

2.1. Tissue collection/DNA extraction

Tissue samples from three adult frogs of each species (Table 1) were collected from a freshwater pond in Hattiesburg, Mississippi, USA (31.20 N 89.22 W). Total DNA was extracted using the DNeasy Tissue Kit (Qiagen) following the manufacturer's protocol. Extracted DNA was diluted using UV‐sterilized DNase/RNase‐free water to a concentration of 10 ng/μl. Tissue sample collection was approved by the Mississippi Department of Wildlife, Fisheries, and Parks (Permit No. 0623151).

Table 1.

Anuran taxa used in the study

Family Species
Ranidae Lithobates catesbeianus, Lithobates clamitans, Lithobates sphenocespala
Hylidae Acris gryllus, Hyla cinerea, Hyla gratiosa, Hyla versicolor
Microhylidae Gastrophryne carolinensis
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2.2. PCR/HRM

PCR and HRM, using the Rotor‐Gene 6000 (Corbett Life Sciences, now Qiagen), was performed in a 25 μl reaction volume containing 12.5 μl of EconoTaq PLUS 2X Master Mix (Lucigen), 5 μl of 10 ng/μl extracted DNA, 2 μl each of 5 μM forward and reverse primers Chmf4 and Chmr4 described by Che et al. (2012), 1.75 μl of DNase/RNase‐free water, 1.25 μl of 20x EvaGreen (Biotium), and 0.5 μl of 25 mM MgCl2 to adjust the final magnesium concentration to 2 mM. The utility of the primers has been confirmed by Chambers and Hebert (2016) in a comprehensive study of North American amphibians.

Initial melting took place at 95°C for 5 min followed by 35 cycles of melting at 94°C for 1 min, annealing at 46°C for 1 min, extension at 72°C for 1 min, and a final extension at 72°C for 10 min. High‐resolution melting analysis was performed immediately after completion of PCR. Sample fluorescence was acquired from 65°C to 95°C at 0.2°C increments, five seconds after each temperature increase had been reached. To better visualize the effect of temperature on DNA melting and the possible presence of multiple melting domains, first derivatives of the change in sample fluorescence over time (−dF/dT) were calculated using the Rotor‐Gene 6000 Series Software (version 1.7) at each 0.2°C increment and plotted against temperature.

2.3. PERMANOVA/NMDS

To compare the DNA melting profiles statistically, the relative first derivative of sample fluorescence at each temperature increment between 75°C and 90°C was used to construct dissimilarity matrices based on the Euclidean distance metric. Permutation analysis of variance (PERMANOVA) (Anderson, 2001) with 10,000 permutations was used to test for significant differences among the melting peak profiles of members of both the genus Lithobates and Hyla. PERMANOVAs were performed using the adonis function of the vegan package (Oksanen et al., 2015) in R. p‐values < .05 were considered significant. Nonmetric multidimensional scaling (NMDS), retaining two dimensions, was performed using the metaMDS function of the vegan package in R. Confidence ellipses were drawn at the 50% level to aid in visualizing clusters using the car package (Fox & Weisberg, 2011) in R.

2.4. DNA sequencing

PCR products were sequenced commercially (Eurofins MWG Operon LLC) using the Sanger sequencing. Unincorporated nucleotides and primers remaining in PCR products were digested prior to sequencing using ExoSAP‐IT (Affymetrix) according to the manufacturer's protocol. PCR products were sequenced in both directions with primers used during PCR. Primer sequences were removed, and the number of nucleotide mismatches was calculated using the ape package (Paradis & Schliep, 2018) in R (version 3.3.3). Sequences were deposited into GenBank under accession numbers (KT388385–KT388408).

3. RESULTS

A single amplicon, 706 bp in length, was amplified from each species collected (data not shown). The amplicons contained up to three melting domains that produced melting profiles that can be used to clearly distinguish congeneric Lithobates (Figure 1a) and Hyla species (Figure 1b). The melting peak profiles were significantly different among Lithobates species (df = 2, pseudo‐F = 92.24 and p = .0038) and among Hyla species (df = 2, pseudo‐F = 52.82 and p = .0031).

Figure 1.

Figure 1

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COI barcode melting peak profiles of conspecific Anurans. (a) Lithobates species. (b) Hyla species. N = 3 with technical replicates shown

The sequence of the COI barcode was identical among conspecifics for two (Lithobates catesbeianus and Lithobates clamitans) of the eight Anuran species (data not shown). Sequence variations in the six other species shifted the melting temperature of some peaks but do not affect the utility of HRM analysis for distinguishing species. For example, sequence differences among Lithobates sphenocephala individuals produced a melting temperature difference of approximately 1.5°C for one of the domains but the amplicon melting profile remains distinct compared to those of two congeners (Figure 1a). The degree of shift seems to correlate with the amount of sequence variation. For example, the shift in melting temperature of one of the melting domains for Acris gryllus, with variation between two and four positions, was approximately 1°C whereas for Hyla cinerea, with variation at only two positions, the shift was approximately 0.5°C (Figure 2a,b).

Figure 2.

Figure 2

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Effect of sequence variation within the COI barcode on melting peak profiles within Anuran species. (a) Acris gryllus. (b) Hyla cinerea. Numbers represent the position within the amplicon where sequence variation was observed. N = 3 with technical replicates shown

An NMDS ordination plot (Stress: 0.0567) summarizing the differences in melting peak profiles among the eight Anuran species revealed only six distinct clusters. Clusters containing L. sphenocephala and Gastrophryne carolinensis specimens overlapped (Figure 3). The amplicon for each species has two melting domains with similar melting temperatures but the melting profiles appear distinguishable due to a distinct valley between melting peaks for G. carolinensis (Figure 4).

Figure 3.

Figure 3

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Nonmetric multidimensional scaling ordination plot, using Euclidean distance as the distance metric, summarizing the difference in melting peak profiles among the eight anuran species. Euclidean distance was calculated after technical duplicates were averaged and the relative first derivative values of fluorescence (−dF/dT) were obtained for each specimen. Squares denote sequence identity within the species

Figure 4.

Figure 4

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COI melting peak profiles of Lithobates sphenocespala and Gastrophryne carolinensis. N = 3 with technical replicates shown

4. DISCUSSION

Accurate species identification is essential in fields such as community ecology and conservation biology. For some animals, the task is not possible based on appearance either because morphological differences overlap or because of morphological variability. For example, the earthworms Lumbricus terrestris and Lumbricus herculeus appear to differ in segment number, body mass, and body length but identification is not reliable because their measurements overlap (James et al., 2010). Snails in the genus Radix cannot be distinguished based on shell morphology because it is variable, overlapping among species and is phenotypically plastic depending on environmental conditions (Pfenninger, Cordellier, & Streit, 2006). The problem is especially acute among embryonic and larval forms before the development of morphological characteristics that distinguish adults.

To distinguish morphologically similar species, DNA barcodes based on the sequence of the mitochondrial cytochrome oxidase subunit I (COI) gene (Hebert et al., 2003) are now widely used. The present study examines the utility of an alternative method to detect sequence variations for the same purpose. High‐resolution melting (HRM) analysis reveals sequence variation based on the melting temperature of PCR amplicons. The melting temperature is determined post‐PCR by monitoring the fluorescence of amplicons in relationship to temperature in the presence of a dsDNA saturating dye. Sequence variation is most obvious in short amplicons for which small changes can significantly affect the melting temperature. At approximately 700 base pairs, it was unclear whether differences in the melting temperature of the amplified fragment of the COI gene would be useful for distinguishing animal species.

The melting peak profiles of the COI amplicon appeared highly distinguishable among species for both Lithobates (Figure 1a) and Hyla (Figure 1b) suggesting that HRM analysis may be a useful way to distinguish related species. Different regions of the COI amplicon melted at different temperatures, forming melting domains that together created unique melting peak profiles. Sequence variation within a species shifted the melting temperature slightly of one or more melting domains but does not appear to affect the distinctiveness of the melting peak profiles. Greater sequence variation among species, however, does affect the distinctiveness of the melting peak profiles, demonstrating the usefulness of this method.

The melting profile of amplified DNA depends on sequence, length, GC content, and heterozygosity (Farrar & Wittwer, 2017; Reed, Kent & Wittwer, 2007; Steer et al., 2009) and the melting profiles of two species can be similar by happenstance. This was observed in the similarity between the COI melting profiles of the frogs Lithobates sphenocespala and G. carolinensis. The two frogs belong to different families (Ranidae and Microhylidae, respectively) with sequence differences in the COI barcode up to 145 nt between individuals of the two families (data not shown) yet have similar COI melting profiles. On the other hand, congeners of both Lithobates and Hyla frogs have distinguishable COI melting profiles. This highlights the point that COI melting profiles are simply an easy way to reveal COI sequence differences but convey no phylogenetic information.

We think HRM analysis can be useful in two ways, either to distinguish morphologically similar species or to confirm species identity. To distinguish morphologically similar species when some discriminatory criteria are available (e.g., eye and spiracle position in larval anurans), melting peak profiles can be used to confirm species distinction as performed in the present study. For species confirmation, melting profiles of samples can be compared to those of reference species in a database. Alternatively, sample DNA (e.g., from a juvenile for which morphological characteristics are ambiguous) can be spiked with an equivalent amount of reference DNA (e.g., from an adult of certain identity) before performing PCR‐HRM. If both samples can be amplified with similar efficiency, a single melting profile would confirm species identity. This later approach was used successfully in this study to confirm the identity of L. catesbeianus and L. sphenocephala tadpoles (data not shown).

In conclusion, we used anurans to show that HRM analysis of the COI barcode can be used to distinguish related species. COI‐HRM analysis offers no advantage over traditional sequencing. However, it is much faster because there is no need to do sequencing. It is a closed‐tube method by which the PCR and HRM steps are performed in the same reaction tube thereby eliminating the need for any post‐PCR manipulations. Although the cost of DNA sequencing is now relatively low, it can be a barrier for laboratories that are not well funded or for laboratories with large numbers of samples to study. After DNA extraction, the analysis only takes a few hours to complete and species differentiation relies only on visual comparison of the melting peak profiles. The only requirement is that the user has access to a thermal cycler capable of real‐time fluorescence measurements.

CONFLICT OF INTEREST

None declared.

AUTHOR CONTRIBUTIONS

S.E. and S.Y.W. conceived the study. S.E. obtained specimens and performed the DNA extractions and high‐resolution melting analysis of amplicons. S.E. and S.Y.W. wrote and approved the final manuscript.

ACKNOWLEDGEMENTS

The authors would like to thank Dr. Jennifer Lamb for her assistance in collecting and confirming the identity of anuran specimens.

Everman S, Wang SY. Distinguishing Anuran species by high‐resolution melting analysis of the COI barcode (COI‐HRM). Ecol Evol. 2019;9:13515–13520. 10.1002/ece3.5808

DATA AVAILABILITY STATEMENT

PCR amplicon sequences are available via GenBank (ascension numbers KT388385–KT388408).

REFERENCES

  1. Anderson, M. J. (2001). A new method for non-parametric multivariate analysis of variance. Austral Ecology, 26(1), 32–46. [Google Scholar]
  2. Chambers, E. A. , & Hebert, P. D. N. (2016). Assessing DNA barcodes for species identification in North American reptiles and amphibians in natural history collections. PLoS ONE, 11(4), e0154363 10.1371/journal.pone.0154363 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Che, J. , Chen, H. M. , Yang, J. X. , Jin, J. Q. , Jiang, K. E. , Yuan, Z. Y. , … Zhang, Y. P. (2012). Universal COI primers for DNA barcoding amphibians. Molecular Ecology Resources, 12(2), 247–258. 10.1111/j.1755-0998.2011.03090.x [DOI] [PubMed] [Google Scholar]
  4. Collins, J. , & Conant, R. (1998). A field guide to reptiles and amphibians of east central North America (3rd ed.). New York, NY: Houghton Mifflin Co. [Google Scholar]
  5. Farrar, J. S. , & Wittwer, C. T. (2017). High-resolution melting curve analysis for molecular diagnostics In Molecular Diagnostics (pp. 79–102). Academic Press; 10.1016/B978-0-12-802971-8.00006-7 [DOI] [Google Scholar]
  6. Folmer, O. , Black, M. , Hoeh, W. , Lutz, R. , & Vrijenhoek, R. (1994). DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Molecular Marine Biology and Biotechnology, 3, 294–299. [PubMed] [Google Scholar]
  7. Fox, J. , & Weisberg, S. (2011). Multivariate linear models in R. An R Companion to Applied Regression. Los Angeles: Thousand Oaks. [Google Scholar]
  8. Glöer, P. (2002). Die Süßwassergastropoden Nord‐ und Mitteleuropas. Bestimmungsschlüssel, Lebensweise, Verbreitung. Die Tierwelt Deutschlands, 73. Hackenheim, Germany: ConchBooks. [Google Scholar]
  9. Harding, J. H. (1997). Amphibians and Reptiles of the Great Lakes Region. Ann Arbor, MI: University of Michigan Press. [Google Scholar]
  10. Hebert, P. D. , Cywinska, A. , & Ball, S. L. (2003). Biological identifications through DNA barcodes. Proceedings of the Royal Society of London B: Biological Sciences, 270(1512), 313–321. 10.1098/rspb.2002.2218 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. James, S. W. , Porco, D. , Decaëns, T. , Richard, B. , Rougerie, R. , & Erséus, C. (2010). DNA barcoding reveals cryptic diversity in Lumbricus terrestris L., 1758 (Clitellata): Resurrection of L. herculeus (Savigny, 1826). PLoS ONE, 5(12), e15629 10.1371/journal.pone.0015629 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Jaslow, A. P. , & Vogt, R. C. (1977). Identification and distribution of Hyla versicolor and Hyla chrysoscelis in Wisconsin. Herpetologica, 33, 201–205. [Google Scholar]
  13. Lilliebridge, R. A. , Tong, S. Y. , Giffard, P. M. , & Holt, D. C. (2011). The utility of high‐resolution melting analysis of SNP nucleated PCR amplicons—An MLST based Staphylococcus aureus typing scheme. PLoS ONE, 6(6), e19749 10.1371/journal.pone.0019749 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Oksanen, J. , Blanchet, F. G. , Kindt, R. , Legendre, P. , Minchin, P. R. , O'Hara, R. B. , … Wagner, H. (2015). vegan: Community ecology package. R package version 2.3‐1. Retrieved from http://CRAN.R-project.org/package=vegan [Google Scholar]
  15. Paradis, E. , & Schliep, K. (2018). ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics, 35, 526–528. 10.1093/bioinformatics/bty633 [DOI] [PubMed] [Google Scholar]
  16. Perl, R. B. , Nagy, Z. T. , Sonet, G. , Glaw, F. , Wollenberg, K. C. , & Vences, M. (2014). DNA barcoding Madagascar's amphibian fauna. Amphibia‐Reptilia, 35(2), 197–206. 10.1163/15685381-00002942 [DOI] [Google Scholar]
  17. Pfenninger, M. , Cordellier, M. , & Streit, B. (2006). Comparing the efficacy of morphologic and DNA‐based taxonomy in the freshwater gastropod genus Radix (Basommatophora, Pulmonata). BMC Evolutionary Biology, 6(1), 100 10.1186/1471-2148-6-100 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Rasmussen, J. P. , Saint, C. P. , & Monis, P. T. (2007). Use of DNA melting simulation software for in silico diagnostic assay design: Targeting regions with complex melting curves and confirmation by real‐time PCR using intercalating dyes. BMC Bioinformatics, 8(1), 107 10.1186/1471-2105-8-107 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Reed, G. H. , Kent, J. O. , & Wittwer, C. T. (2007). High-resolution DNA melting analysis for simple and efficient molecular diagnostics. Pharmacogenomics, 8, 597–608. [DOI] [PubMed] [Google Scholar]
  20. Reed, G. H. , & Wittwer, C. T. (2004). Sensitivity and specificity of single‐nucleotide polymorphism scanning by high‐resolution melting analysis. Clinical Chemistry, 50(10), 1748–1754. 10.1373/clinchem.2003.029751 [DOI] [PubMed] [Google Scholar]
  21. Smith, M. A. , Poyarkov, N. A. , & Hebert, P. D. N. (2008). DNA barcoding: CO1 DNA barcoding amphibians: Take the chance, meet the challenge. Molecular Ecology Resources, 8(2), 235–246. 10.1111/j.1471-8286.2007.01964.x [DOI] [PubMed] [Google Scholar]
  22. Steer, P. A. , Kirkpatrick, N. C. , O'Rourke, D. , & Noormohammadi, A. H. (2009). Classification of fowl adenovirus serotypes by use of high‐resolution melting‐curve analysis of the hexon gene region. Journal of Clinical Microbiology, 47(2), 311–321. 10.1128/JCM.01567-08 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Vences, M. , Thomas, M. , Bonett, R. M. , & Vieites, D. R. (2005). Deciphering amphibian diversity through DNA barcoding: Chances and challenges. Philosophical Transactions of the Royal Society B: Biological Sciences, 360(1462), 1859–1868. 10.1098/rstb.2005.1717 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

PCR amplicon sequences are available via GenBank (ascension numbers KT388385–KT388408).

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