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Principal components analysis - K-means transposon element based foxtail millet core collection selection method

BACKGROUND: Core collections are important tools in genetic resources research and administration. At present, most core collection selection criteria are based on one of the following item characteristics: passport data, genetic markers, or morphological traits, which may lead to inadequate represe...

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Autores principales: Borrayo, Ernesto, Machida-Hirano, Ryoko, Takeya, Masaru, Kawase, Makoto, Watanabe, Kazuo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4754896/
https://www.ncbi.nlm.nih.gov/pubmed/26880119
http://dx.doi.org/10.1186/s12863-016-0343-z
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author Borrayo, Ernesto
Machida-Hirano, Ryoko
Takeya, Masaru
Kawase, Makoto
Watanabe, Kazuo
author_facet Borrayo, Ernesto
Machida-Hirano, Ryoko
Takeya, Masaru
Kawase, Makoto
Watanabe, Kazuo
author_sort Borrayo, Ernesto
collection PubMed
description BACKGROUND: Core collections are important tools in genetic resources research and administration. At present, most core collection selection criteria are based on one of the following item characteristics: passport data, genetic markers, or morphological traits, which may lead to inadequate representations of variability in the complete collection. The development of a comprehensive methodology that includes as much element data as possible has been explored poorly. Using a collection of (Setaria italica sbsp. italica (L.) P. Beauv.) as a model, we developed a method for core collection construction based on genotype data and numerical representations of agromorphological traits, thereby improving the selection process. RESULTS: Principal component analysis allows the selection of the most informative discriminators among the various elements evaluated, regardless of whether they are genetic or morphological, thereby providing an adequate criterion for further K-mean clustering. Overall, the core collections of S. italica constructed using only genotype data demonstrated overall better validation scores than other core collections that we generated. However, core collection based on both genotype and agromorphological characteristics represented the overall diversity adequately. CONCLUSIONS: The inclusion of both genotype and agromorphological characteristics as a comprehensive dataset in this methodology ensures that agricultural traits are considered in the core collection construction. This approach will be beneficial for genetic resources management and research activities for S. italica as well as other genetic resources. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12863-016-0343-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-47548962016-02-17 Principal components analysis - K-means transposon element based foxtail millet core collection selection method Borrayo, Ernesto Machida-Hirano, Ryoko Takeya, Masaru Kawase, Makoto Watanabe, Kazuo BMC Genet Methodology Article BACKGROUND: Core collections are important tools in genetic resources research and administration. At present, most core collection selection criteria are based on one of the following item characteristics: passport data, genetic markers, or morphological traits, which may lead to inadequate representations of variability in the complete collection. The development of a comprehensive methodology that includes as much element data as possible has been explored poorly. Using a collection of (Setaria italica sbsp. italica (L.) P. Beauv.) as a model, we developed a method for core collection construction based on genotype data and numerical representations of agromorphological traits, thereby improving the selection process. RESULTS: Principal component analysis allows the selection of the most informative discriminators among the various elements evaluated, regardless of whether they are genetic or morphological, thereby providing an adequate criterion for further K-mean clustering. Overall, the core collections of S. italica constructed using only genotype data demonstrated overall better validation scores than other core collections that we generated. However, core collection based on both genotype and agromorphological characteristics represented the overall diversity adequately. CONCLUSIONS: The inclusion of both genotype and agromorphological characteristics as a comprehensive dataset in this methodology ensures that agricultural traits are considered in the core collection construction. This approach will be beneficial for genetic resources management and research activities for S. italica as well as other genetic resources. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12863-016-0343-z) contains supplementary material, which is available to authorized users. BioMed Central 2016-02-16 /pmc/articles/PMC4754896/ /pubmed/26880119 http://dx.doi.org/10.1186/s12863-016-0343-z Text en © Borrayo et al. 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology Article
Borrayo, Ernesto
Machida-Hirano, Ryoko
Takeya, Masaru
Kawase, Makoto
Watanabe, Kazuo
Principal components analysis - K-means transposon element based foxtail millet core collection selection method
title Principal components analysis - K-means transposon element based foxtail millet core collection selection method
title_full Principal components analysis - K-means transposon element based foxtail millet core collection selection method
title_fullStr Principal components analysis - K-means transposon element based foxtail millet core collection selection method
title_full_unstemmed Principal components analysis - K-means transposon element based foxtail millet core collection selection method
title_short Principal components analysis - K-means transposon element based foxtail millet core collection selection method
title_sort principal components analysis - k-means transposon element based foxtail millet core collection selection method
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4754896/
https://www.ncbi.nlm.nih.gov/pubmed/26880119
http://dx.doi.org/10.1186/s12863-016-0343-z
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