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Taxonomical Evaluation of Plant Chloroplastic Markers by Bayesian Classifier

DNA barcodes are standardized sequences that range between 400 and 800 bp, vary at different taxonomic levels, and make it possible to assign sequences to species that have been previously taxonomically characterized. Several DNA barcodes have been postulated for plants, nonetheless, their classific...

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Detalles Bibliográficos
Autores principales: Matiz-Ceron, Luisa, Reyes, Alejandro, Anzola, Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8850773/
https://www.ncbi.nlm.nih.gov/pubmed/35185949
http://dx.doi.org/10.3389/fpls.2021.782663
Descripción
Sumario:DNA barcodes are standardized sequences that range between 400 and 800 bp, vary at different taxonomic levels, and make it possible to assign sequences to species that have been previously taxonomically characterized. Several DNA barcodes have been postulated for plants, nonetheless, their classification potential has not been evaluated for metabarcoding, and as a result, it would appear as none of them excels above the others in this area. One tool that has been widely used and served as a baseline when evaluating new approaches is Naïve Bayesian Classifiers (NBC). The present study aims at evaluating the classification power of several plant chloroplast genetic markers that have been proposed as barcodes (trnL, rpoB, rbcL, matK, psbA-trnH, and psbK) using an NBC. We performed the classification at different taxonomic levels, and identified problematic genera when resolution was desired. We propose matK and trnL as potential candidate markers with resolution up to genus level. Some problematic genera within certain families could lead to the misclassification no matter which marker is used (i.e., Aegilops, Gueldenstaedtia, Helianthus, Oryza, Shorea, Thysananthus, and Triticum). Finally, we suggest recommendations for the taxonomic identification of plants in samples with potential mixtures.