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Multivariate analysis reveals phenotypic diversity of Euscaphis japonica population
Fruit traits affect population genetic diversity by affecting seed protection and dispersal strategies, thereby comprising important components of phenotypic variation. Understanding of the phenotypic variation is an indispensable first step for developing breeding strategies. However, little inform...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6634381/ https://www.ncbi.nlm.nih.gov/pubmed/31310621 http://dx.doi.org/10.1371/journal.pone.0219046 |
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author | Sun, Weihong Yuan, Xueyan Liu, Zhong-Jian Lan, Siren Tsai, Wen-chieh Zou, Shuang-Quan |
author_facet | Sun, Weihong Yuan, Xueyan Liu, Zhong-Jian Lan, Siren Tsai, Wen-chieh Zou, Shuang-Quan |
author_sort | Sun, Weihong |
collection | PubMed |
description | Fruit traits affect population genetic diversity by affecting seed protection and dispersal strategies, thereby comprising important components of phenotypic variation. Understanding of the phenotypic variation is an indispensable first step for developing breeding strategies. However, little information is known about the genetic variation in E. japonica—a monotypic species with abundant phenotypes that is mainly distributed in southern China. In this study, we evaluated the phenotypic diversity of 67 E. japonica using 23 phenotypic traits. Our results showed that the Shannon–Wiener (I) index of qualitative traits ranged from 0.55 to 1.26, and the color traits had a relatively high I. The average coefficient of variation of compound leaf traits (14.74%) was higher than that of fruit and seed traits (12.77% and 11.47%, respectively). Principal component analysis also showed that compound leaf and fruit traits were important components of total variation. Furthermore, correlation analysis revealed a significant difference in elevation and fruit color, irregular ribs, leaf margin and texture. The F value within populations was smaller than among populations, indicating the variation in phenotypic traits among populations was much greater than within populations. Dehua and Zunyi populations had the highest coefficients of variation, whereas Wenzhou population had the smallest—which may be attributed to habitat destruction. According to Q-type clustering, 67 samples clustered into four groups, with those having similar phenotypes clustering into the same group. In general, leaf and fruit traits had abundant phenotypic diversity, representing the main sources of phenotypic variation. Combined with clustering results and field surveys, this study suggests that the phenotypes of E. japonica are classified into two main categories: The deciduous E. japonica present at high altitudes; and the evergreen E. japonica present at low altitudes. Excavating E. japonica variations provides a theoretical reference for its classification and diversity, and is of great significance for planning genetic resources and establishing conservation strategies. |
format | Online Article Text |
id | pubmed-6634381 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-66343812019-07-25 Multivariate analysis reveals phenotypic diversity of Euscaphis japonica population Sun, Weihong Yuan, Xueyan Liu, Zhong-Jian Lan, Siren Tsai, Wen-chieh Zou, Shuang-Quan PLoS One Research Article Fruit traits affect population genetic diversity by affecting seed protection and dispersal strategies, thereby comprising important components of phenotypic variation. Understanding of the phenotypic variation is an indispensable first step for developing breeding strategies. However, little information is known about the genetic variation in E. japonica—a monotypic species with abundant phenotypes that is mainly distributed in southern China. In this study, we evaluated the phenotypic diversity of 67 E. japonica using 23 phenotypic traits. Our results showed that the Shannon–Wiener (I) index of qualitative traits ranged from 0.55 to 1.26, and the color traits had a relatively high I. The average coefficient of variation of compound leaf traits (14.74%) was higher than that of fruit and seed traits (12.77% and 11.47%, respectively). Principal component analysis also showed that compound leaf and fruit traits were important components of total variation. Furthermore, correlation analysis revealed a significant difference in elevation and fruit color, irregular ribs, leaf margin and texture. The F value within populations was smaller than among populations, indicating the variation in phenotypic traits among populations was much greater than within populations. Dehua and Zunyi populations had the highest coefficients of variation, whereas Wenzhou population had the smallest—which may be attributed to habitat destruction. According to Q-type clustering, 67 samples clustered into four groups, with those having similar phenotypes clustering into the same group. In general, leaf and fruit traits had abundant phenotypic diversity, representing the main sources of phenotypic variation. Combined with clustering results and field surveys, this study suggests that the phenotypes of E. japonica are classified into two main categories: The deciduous E. japonica present at high altitudes; and the evergreen E. japonica present at low altitudes. Excavating E. japonica variations provides a theoretical reference for its classification and diversity, and is of great significance for planning genetic resources and establishing conservation strategies. Public Library of Science 2019-07-16 /pmc/articles/PMC6634381/ /pubmed/31310621 http://dx.doi.org/10.1371/journal.pone.0219046 Text en © 2019 Sun et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Sun, Weihong Yuan, Xueyan Liu, Zhong-Jian Lan, Siren Tsai, Wen-chieh Zou, Shuang-Quan Multivariate analysis reveals phenotypic diversity of Euscaphis japonica population |
title | Multivariate analysis reveals phenotypic diversity of Euscaphis japonica population |
title_full | Multivariate analysis reveals phenotypic diversity of Euscaphis japonica population |
title_fullStr | Multivariate analysis reveals phenotypic diversity of Euscaphis japonica population |
title_full_unstemmed | Multivariate analysis reveals phenotypic diversity of Euscaphis japonica population |
title_short | Multivariate analysis reveals phenotypic diversity of Euscaphis japonica population |
title_sort | multivariate analysis reveals phenotypic diversity of euscaphis japonica population |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6634381/ https://www.ncbi.nlm.nih.gov/pubmed/31310621 http://dx.doi.org/10.1371/journal.pone.0219046 |
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