Open AccessTowards Plant Species Identification in Complex Samples: A Bioinformatics Pipeline for the Identification of Novel Nuclear Barcode Candidates
Author(s) -
Alexandre Angers-Loustau,
Mauro Petrillo,
Valentina Paracchini,
Dafni Maria Kagkli,
Patricia E. Rischitor,
Antonio Puertas-Gallardo,
Alex Patak,
Maddalena Querci,
Kreysa Joachim
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0147692
Subject(s) - barcode , pipeline (software) , identification (biology) , computational biology , genome , dna barcoding , primer (cosmetics) , biology , computer science , bioinformatics , genetics , evolutionary biology , gene , ecology , chemistry , organic chemistry , programming language , operating system
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.