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A proposal for a multivariate quantitative approach to infer karyological relationships among taxa

Abstract. Until now, basic karyological parameters have been used in different ways by researchers to infer karyological relationships among organisms. In the present study, we propose a standardized approach to this aim, integrating six different, not redundant, parameters in a multivariate PCoA an...

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Detalles Bibliográficos
Autores principales: Peruzzi, Lorenzo, Altınordu, Fahim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Pensoft Publishers 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4296720/
https://www.ncbi.nlm.nih.gov/pubmed/25610547
http://dx.doi.org/10.3897/CompCytogen.v8i4.8564
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author Peruzzi, Lorenzo
Altınordu, Fahim
author_facet Peruzzi, Lorenzo
Altınordu, Fahim
author_sort Peruzzi, Lorenzo
collection PubMed
description Abstract. Until now, basic karyological parameters have been used in different ways by researchers to infer karyological relationships among organisms. In the present study, we propose a standardized approach to this aim, integrating six different, not redundant, parameters in a multivariate PCoA analysis. These parameters are chromosome number, basic chromosome number, total haploid chromosome length, M(CA) (Mean Centromeric Asymmetry), CV(CL) (Coefficient of Variation of Chromosome Length) and CV(CI) (Coefficient of Variation of Centromeric Index). The method is exemplified with the application to several plant taxa, and its significance and limits are discussed in the light of current phylogenetic knowledge of these groups.
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spelling pubmed-42967202015-01-21 A proposal for a multivariate quantitative approach to infer karyological relationships among taxa Peruzzi, Lorenzo Altınordu, Fahim Comp Cytogenet Research Articles Abstract. Until now, basic karyological parameters have been used in different ways by researchers to infer karyological relationships among organisms. In the present study, we propose a standardized approach to this aim, integrating six different, not redundant, parameters in a multivariate PCoA analysis. These parameters are chromosome number, basic chromosome number, total haploid chromosome length, M(CA) (Mean Centromeric Asymmetry), CV(CL) (Coefficient of Variation of Chromosome Length) and CV(CI) (Coefficient of Variation of Centromeric Index). The method is exemplified with the application to several plant taxa, and its significance and limits are discussed in the light of current phylogenetic knowledge of these groups. Pensoft Publishers 2014-12-10 /pmc/articles/PMC4296720/ /pubmed/25610547 http://dx.doi.org/10.3897/CompCytogen.v8i4.8564 Text en Lorenzo Peruzzi, Fahim Altınordu http://creativecommons.org/licenses/by/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Articles
Peruzzi, Lorenzo
Altınordu, Fahim
A proposal for a multivariate quantitative approach to infer karyological relationships among taxa
title A proposal for a multivariate quantitative approach to infer karyological relationships among taxa
title_full A proposal for a multivariate quantitative approach to infer karyological relationships among taxa
title_fullStr A proposal for a multivariate quantitative approach to infer karyological relationships among taxa
title_full_unstemmed A proposal for a multivariate quantitative approach to infer karyological relationships among taxa
title_short A proposal for a multivariate quantitative approach to infer karyological relationships among taxa
title_sort proposal for a multivariate quantitative approach to infer karyological relationships among taxa
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4296720/
https://www.ncbi.nlm.nih.gov/pubmed/25610547
http://dx.doi.org/10.3897/CompCytogen.v8i4.8564
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