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DNA Barcodes

Ed. by Mitchell, Andrew

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Emerging Science

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2299-1077
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A test of sequence-matching algorithms for a DNA barcode database of invasive grasses

A.E. Syme
  • National Herbarium of Victoria, Royal Botanic Gardens Melbourne, Birdwood Avenue, South Yarra, Victoria, 3141, Australia
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/ F. Udovicic
  • National Herbarium of Victoria, Royal Botanic Gardens Melbourne, Birdwood Avenue, South Yarra, Victoria, 3141, Australia
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/ V. Stajsic
  • National Herbarium of Victoria, Royal Botanic Gardens Melbourne, Birdwood Avenue, South Yarra, Victoria, 3141, Australia
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/ D.J. Murphy
  • National Herbarium of Victoria, Royal Botanic Gardens Melbourne, Birdwood Avenue, South Yarra, Victoria, 3141, Australia
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Published Online: 2013-01-21 | DOI: https://doi.org/10.2478/dna-2012-0002

Abstract

Stipoid grasses (Poaceae, tribe Stipeae) include many species that are highly invasive. In Australia, several species are problematic environmental and economic weeds, degrading pastures, injuring livestock, and invading native grasslands. An accurate means of identification is the first line of defense against importation and establishment of potentially invasive stipoid grasses. Traditional morphological identification relies on floret characters, and because these characters are rarely available in juvenile or fragmentary material, DNA barcodes provide an alternative and rapid means of identification. Although barcodes themselves are tested to ensure appropriate discriminatory variation for identifying query sequences, there are few studies that report the testing of sequence matching algorithms. This limits the utility of sequence databases for DNA barcoding purposes. Therefore, in this study, we tested the efficacy of three sequence matching algorithms for stipoid grasses to determine the method and barcode that worked best. Using several sequence matching algorithms - BLAST, Neighbour Joining and Bayesian Likelihood - we assessed the success of identifying an “unknown” query sequence against a reference database of 206 specimens. The highest accuracy was achieved using the ITS (internal transcribed spacers) barcode region and the BLAST algorithm. The poorest performing barcode and analysis were rbcL and the Bayesian Likelihood analysis. However, the BLAST method was only slightly more successful than Neighbour Joining. Increasing the number of query sequences would further indicate whether this trend is significant for stipoid grasses.

This article offers supplementary material which is provided at the end of the article.

Keywords: Stipoid grasses; Invasive; Weed; Stipeae; Barcoding; BLAST; DNA barcodes

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About the article


Received: 2012-08-13

Accepted: 2012-11-22

Published Online: 2013-01-21


Citation Information: DNA Barcodes, ISSN (Online) 2299-1077, DOI: https://doi.org/10.2478/dna-2012-0002.

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©2013 Versita Sp. z o.o.. This content is open access.

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