Analysis of the Performance of Putative Barcodes

National Library Of Medicine

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Abstract

Originally, Dr. Spouge was invited to the 2009 Edinburgh Conference Selecting Barcode Loci for Plants, a gathering of a subset of the Plant Working Group within the Consortium for the Barcode of Life, to help select a plant barcode. The other conference participants sequenced 7 candidate barcode loci across a broad range of land plants, so Dr Spouge and Damon Little of the New York Botanical Garden could analyze the resulting data, to permit the conference participants to select markers for a plant barcode. The Edinburgh Conference selected rbcL and matK as the 2 plant barcode markers, from 7 choices. Later, Dr. Spouge performed a similar data analysis for the Fungal Barcode Working Group in Amsterdam (2011), which selected ITS (the Internal Transcribed Spacer between structural ribosomal RNAs) from 4 choices. He offered similar services to the Protist Barcode Working Group in Berlin (2011), but insufficient data prevented a decisive analysis. He had made implementations of his analysis publicly available in user-friendly programs, to permit barcode researchers to carry out their own analyses. More recently, in collaboration with Dr. Martin, he has analyzed the efficacy of barcodes in identifying South-East Asian fungi. Such analyses are likely to be particularly important in selecting secondary markers in different fungal clades. Dr. Spouge collaborated with the Database Working Group, Consortium for the Barcode of Life to produce a Barcode Validator, a web interface to automate the collection of barcodes. Using coalescent theory, he has also developed some theoretical results relating age of divergence of a species to its probability of correct identification with DNA barcodes. The results suggest species sampling strategies to improve the efficacy of DNA barcoding. He is also working with Dr Martin to test web tools for automating the evaluation of barcode efficacy. The collaboration is producing statistical tools for the objective evaluation of the accuracy of taxonomic classification.