Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Sun, Weihong, Yuan, Xueyan, Liu, Zhong-Jian, Lan, Siren, Tsai, Wen-chieh, Zou, Shuang-Quan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
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
_version_ 1783435775248957440
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
work_keys_str_mv AT sunweihong multivariateanalysisrevealsphenotypicdiversityofeuscaphisjaponicapopulation
AT yuanxueyan multivariateanalysisrevealsphenotypicdiversityofeuscaphisjaponicapopulation
AT liuzhongjian multivariateanalysisrevealsphenotypicdiversityofeuscaphisjaponicapopulation
AT lansiren multivariateanalysisrevealsphenotypicdiversityofeuscaphisjaponicapopulation
AT tsaiwenchieh multivariateanalysisrevealsphenotypicdiversityofeuscaphisjaponicapopulation
AT zoushuangquan multivariateanalysisrevealsphenotypicdiversityofeuscaphisjaponicapopulation