Species identification in meat products: A new screening method based on high resolution melting analysis of cyt b gene

López-Oceja, A.; Núñez, Carolina; Baeta, Miriam; Gamarra, David; Pancorbo, Marian M. de

doi:10.1016/j.foodchem.2017.06.004

Cited by 42 publications

(25 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The statistical analysis was carried out using normalized curves from the analysis of the cyt b gene in eight species (five mammals and three birds, with ten and eight individuals, respectively) and five mixtures of meat species, as studied by Lopez‐Oceja et al. ().…”

Section: Resultsmentioning

confidence: 99%

“…The statistical analysis was carried out on the normalized melting curves from a set of samples from eight different animal species, which were previously analyzed for the cyt b gene by PCR‐HRM in a study by Lopez‐Oceja et al. from . More specifically, data from 10 individuals from five mammal species, that is, cow, sheep, pig, horse, and rabbit ( Bos taurus, Ovis aries, Sus scrofa domestica, Equus caballus, and Oryctolagus cuniculus , respectively), as well as eight individuals of three bird species common in alimentation, that is, chicken, turkey, and quail ( Gallus gallus domesticus, Meleagris gallopavo , and Coturnix coturnix , respectively) were analyzed (Table A).…”

Section: Methodsmentioning

confidence: 99%

“…High‐resolution melting (HRM) analysis has been proven to be a reliable, fast, and inexpensive technique for the analysis of PCR amplicons with variants in their sequences, for example, genotyping of single or multiple SNPs and mutation scanning. This advanced method has been successfully implemented in a wide range of new applications, including biomedicine diagnostics (Erali, Voelkerding, & Wittwer, ; Montgomery, Sanford, & Wittwer, ; Reed, Kent, & Wittwer, ; Vossen, Aten, Roos, & den Dunnen, ), forensic population studies (Valverde et al., ; Villaescusa et al., ), and species identification in food analysis (Druml & Cichna‐Markl, ; Galimberti et al., ; Lopez‐Oceja, Nuñez, Baeta, Gamarra, & de Pancorbo, ), to detect food contaminants or adulterations with closely related species.…”

Section: Introductionmentioning

confidence: 99%

“…Nonetheless, control over the clustering process is very important since small differences between similar curves may lead to clustering errors, and it does not always allow differentiating samples that are genetically similar, as can be seen in a study by Lopez‐Oceja et al. from . These misclassifications can be more frequent if intersections appear along the trajectories of the melting curves.…”

Section: Introductionmentioning

confidence: 99%

“…More specifically, this method should increase the robustness of the procedure to statistically differentiate among analytical PCR‐HRM curves from sequences with multiple SNPs of interest, for example, in the analysis of different species or different haplotypes, in contrast to the visual comparison of plots offered by current software. To evaluate the usefulness of the FDA method in real‐world datasets, this methodology has been implemented to analyze previously obtained HRM data from meat species (five mammal and three bird species) common in alimentation, as well as some mixtures of these species used for human consumption (Lopez‐Oceja et al., ).…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A Statistical Method to Enhance the Analysis of the Differences Among High‐Resolution Melting (HRM) Curves of PCR‐Amplified DNA Fragments

Ibarrondo

López-Oceja

Baeta

et al. 2019

Journal of Food Science

View full text Add to dashboard Cite

Consistent differences among melting curves of PCR‐amplified DNA fragments are treated by normalizing the relative fluorescence units (RFU) and performing a clustering analysis, but statistically significant differences among curves are not usually determined. In the present study, an analysis based on functional data analysis (FDA) was implemented to evaluate the existence of statistically significant differences between normalized RFU curves obtained from PCR‐HRM (high‐resolution melting) analysis by using ANOVA for functional data. The effectiveness of the FDA method was analyzed with data from a set of samples of eight animal species of interest in food analysis, as well as mixtures of DNA from these species, analyzed by PCR‐HRM to differentiate them. The statistical method described in this study has been demonstrated to be a robust and precise tool to discriminate among melting curves derived from HRM analysis. This method has advantages over the current comparison methods. Practical Application As long as food fraud and mislabeling exist, new techniques for species identification are needed. High‐resolution melting (HRM) has been shown to be a rapid, reliable and inexpensive species identification method. In the present study, functional data analysis (FDA) was applied to HRM curves of DNA from eight animal species used for food, as well as to mixtures of these species in different proportions. FDA has advantages over the usual methods, providing a deeper statistical analysis and facilitating the data interpretation as shown by the HRM analysis for a clearer comparison among individual species and mixtures of species.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%