Towards plant species identification in complex samples: A bioinformatics pipeline for the identification of novel nuclear barcode candidates

Alexandre Angers-Loustau, Mauro Petrillo, Valentina Paracchini, Dafni M. Kagkli, Patricia E. Rischitor, Antonio Puertas Gallardo, Alex Patak, Maddalena Querci, Joachim Kreysa

Research output: Contribution to journalArticlepeer-review

Abstract

Monitoring of the food chain to fight fraud and protect consumer health relies on the availability of methods to correctly identify the species present in samples, for which DNA barcoding is a promising candidate. The nuclear genome is a rich potential source of barcode targets, but has been relatively unexploited until now. Here, we show the development and use of a bioinformatics pipeline that processes available genome sequences to automatically screen large numbers of input candidates, identifies novel nuclear barcode targets and designs associated primer pairs, according to a specific set of requirements. We applied this pipeline to identify novel barcodes for plant species, a kingdom for which the currently available solutions are known to be insufficient. We tested one of the identified primer pairs and show its capability to correctly identify the plant species in simple and complex samples, validating the output of our approach.

Original languageEnglish
Article numbere0147692
JournalPLoS One
Volume11
Issue number1
DOIs
Publication statusPublished - Jan 1 2016

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

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