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Identification of species by multiplex analysis of variable-length sequences

The quest for a universal and efficient method of identifying species has been a longstanding challenge in biology. Here, we show that accurate identification of species in all domains of life can be accomplished by multiplex analysis of variable-length sequences containing multiple insertion/deleti...

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Autores principales: Pereira, Filipe, Carneiro, João, Matthiesen, Rune, van Asch, Barbara, Pinto, Nádia, Gusmão, Leonor, Amorim, António
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001097/
https://www.ncbi.nlm.nih.gov/pubmed/20923781
http://dx.doi.org/10.1093/nar/gkq865
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author Pereira, Filipe
Carneiro, João
Matthiesen, Rune
van Asch, Barbara
Pinto, Nádia
Gusmão, Leonor
Amorim, António
author_facet Pereira, Filipe
Carneiro, João
Matthiesen, Rune
van Asch, Barbara
Pinto, Nádia
Gusmão, Leonor
Amorim, António
author_sort Pereira, Filipe
collection PubMed
description The quest for a universal and efficient method of identifying species has been a longstanding challenge in biology. Here, we show that accurate identification of species in all domains of life can be accomplished by multiplex analysis of variable-length sequences containing multiple insertion/deletion variants. The new method, called SPInDel, is able to discriminate 93.3% of eukaryotic species from 18 taxonomic groups. We also demonstrate that the identification of prokaryotic and viral species with numeric profiles of fragment lengths is generally straightforward. A computational platform is presented to facilitate the planning of projects and includes a large data set with nearly 1800 numeric profiles for species in all domains of life (1556 for eukaryotes, 105 for prokaryotes and 130 for viruses). Finally, a SPInDel profiling kit for discrimination of 10 mammalian species was successfully validated on highly processed food products with species mixtures and proved to be easily adaptable to multiple screening procedures routinely used in molecular biology laboratories. These results suggest that SPInDel is a reliable and cost-effective method for broad-spectrum species identification that is appropriate for use in suboptimal samples and is amenable to different high-throughput genotyping platforms without the need for DNA sequencing.
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spelling pubmed-30010972010-12-13 Identification of species by multiplex analysis of variable-length sequences Pereira, Filipe Carneiro, João Matthiesen, Rune van Asch, Barbara Pinto, Nádia Gusmão, Leonor Amorim, António Nucleic Acids Res Methods Online The quest for a universal and efficient method of identifying species has been a longstanding challenge in biology. Here, we show that accurate identification of species in all domains of life can be accomplished by multiplex analysis of variable-length sequences containing multiple insertion/deletion variants. The new method, called SPInDel, is able to discriminate 93.3% of eukaryotic species from 18 taxonomic groups. We also demonstrate that the identification of prokaryotic and viral species with numeric profiles of fragment lengths is generally straightforward. A computational platform is presented to facilitate the planning of projects and includes a large data set with nearly 1800 numeric profiles for species in all domains of life (1556 for eukaryotes, 105 for prokaryotes and 130 for viruses). Finally, a SPInDel profiling kit for discrimination of 10 mammalian species was successfully validated on highly processed food products with species mixtures and proved to be easily adaptable to multiple screening procedures routinely used in molecular biology laboratories. These results suggest that SPInDel is a reliable and cost-effective method for broad-spectrum species identification that is appropriate for use in suboptimal samples and is amenable to different high-throughput genotyping platforms without the need for DNA sequencing. Oxford University Press 2010-12 2010-10-04 /pmc/articles/PMC3001097/ /pubmed/20923781 http://dx.doi.org/10.1093/nar/gkq865 Text en © The Author(s) 2010. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods Online
Pereira, Filipe
Carneiro, João
Matthiesen, Rune
van Asch, Barbara
Pinto, Nádia
Gusmão, Leonor
Amorim, António
Identification of species by multiplex analysis of variable-length sequences
title Identification of species by multiplex analysis of variable-length sequences
title_full Identification of species by multiplex analysis of variable-length sequences
title_fullStr Identification of species by multiplex analysis of variable-length sequences
title_full_unstemmed Identification of species by multiplex analysis of variable-length sequences
title_short Identification of species by multiplex analysis of variable-length sequences
title_sort identification of species by multiplex analysis of variable-length sequences
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001097/
https://www.ncbi.nlm.nih.gov/pubmed/20923781
http://dx.doi.org/10.1093/nar/gkq865
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