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Constructing a Core Collection of the Medicinal Plant Angelica biserrata Using Genetic and Metabolic Data

Angelica biserrata is an important medicinal plant in Chinese traditional medicine. Its roots, which are known as Duhuo in Chinese, are broadly applied to treat inflammation, arthritis, and headache. With increasing market demand, the wild resources of A. biserrata have been overexploited, and conse...

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Autores principales: Liu, Man, Hu, Xin, Wang, Xu, Zhang, Jingjing, Peng, Xubing, Hu, Zhigang, Liu, Yifei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785966/
https://www.ncbi.nlm.nih.gov/pubmed/33424898
http://dx.doi.org/10.3389/fpls.2020.600249
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author Liu, Man
Hu, Xin
Wang, Xu
Zhang, Jingjing
Peng, Xubing
Hu, Zhigang
Liu, Yifei
author_facet Liu, Man
Hu, Xin
Wang, Xu
Zhang, Jingjing
Peng, Xubing
Hu, Zhigang
Liu, Yifei
author_sort Liu, Man
collection PubMed
description Angelica biserrata is an important medicinal plant in Chinese traditional medicine. Its roots, which are known as Duhuo in Chinese, are broadly applied to treat inflammation, arthritis, and headache. With increasing market demand, the wild resources of A. biserrata have been overexploited, and conservation, assessment of genetic resources and breeding for this species is needed. Here, we sequenced the transcriptome of A. biserrata and developed simple sequence repeat (SSR) markers from it to construct a core collection based on 208 samples collected from Changyang-related regions. A total of 132 alleles were obtained for 17 SSR loci used with the polymorphic information content (PIC) ranging from 0.44 to 0.83. Abundant genetic diversity was inferred by Shannon’s information index (1.51), observed (0.57) and expected heterozygosity (0.72). The clustering analysis resulted into two sample groups and analysis of molecular variance (AMOVA) showed only 6% genetic variation existed among populations. A further metabolic analysis of these samples revealed the main coumarin contents, such as osthole and columbianadin. According to the genetic and metabolic data, we adopted the least distance stepwise sampling strategy to construct seven preliminary core collections, of which the 20CC collection, which possessed 42 A. biserrata individuals accounting for 90.20% of the genetic diversity of the original germplasm, represented the best core collection. This study will contribute to the conservation and management of A. biserrata wild germplasm resources and provide a material basis for future selection and breeding of this medicinal plant.
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spelling pubmed-77859662021-01-07 Constructing a Core Collection of the Medicinal Plant Angelica biserrata Using Genetic and Metabolic Data Liu, Man Hu, Xin Wang, Xu Zhang, Jingjing Peng, Xubing Hu, Zhigang Liu, Yifei Front Plant Sci Plant Science Angelica biserrata is an important medicinal plant in Chinese traditional medicine. Its roots, which are known as Duhuo in Chinese, are broadly applied to treat inflammation, arthritis, and headache. With increasing market demand, the wild resources of A. biserrata have been overexploited, and conservation, assessment of genetic resources and breeding for this species is needed. Here, we sequenced the transcriptome of A. biserrata and developed simple sequence repeat (SSR) markers from it to construct a core collection based on 208 samples collected from Changyang-related regions. A total of 132 alleles were obtained for 17 SSR loci used with the polymorphic information content (PIC) ranging from 0.44 to 0.83. Abundant genetic diversity was inferred by Shannon’s information index (1.51), observed (0.57) and expected heterozygosity (0.72). The clustering analysis resulted into two sample groups and analysis of molecular variance (AMOVA) showed only 6% genetic variation existed among populations. A further metabolic analysis of these samples revealed the main coumarin contents, such as osthole and columbianadin. According to the genetic and metabolic data, we adopted the least distance stepwise sampling strategy to construct seven preliminary core collections, of which the 20CC collection, which possessed 42 A. biserrata individuals accounting for 90.20% of the genetic diversity of the original germplasm, represented the best core collection. This study will contribute to the conservation and management of A. biserrata wild germplasm resources and provide a material basis for future selection and breeding of this medicinal plant. Frontiers Media S.A. 2020-12-23 /pmc/articles/PMC7785966/ /pubmed/33424898 http://dx.doi.org/10.3389/fpls.2020.600249 Text en Copyright © 2020 Liu, Hu, Wang, Zhang, Peng, Hu and Liu. 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). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Liu, Man
Hu, Xin
Wang, Xu
Zhang, Jingjing
Peng, Xubing
Hu, Zhigang
Liu, Yifei
Constructing a Core Collection of the Medicinal Plant Angelica biserrata Using Genetic and Metabolic Data
title Constructing a Core Collection of the Medicinal Plant Angelica biserrata Using Genetic and Metabolic Data
title_full Constructing a Core Collection of the Medicinal Plant Angelica biserrata Using Genetic and Metabolic Data
title_fullStr Constructing a Core Collection of the Medicinal Plant Angelica biserrata Using Genetic and Metabolic Data
title_full_unstemmed Constructing a Core Collection of the Medicinal Plant Angelica biserrata Using Genetic and Metabolic Data
title_short Constructing a Core Collection of the Medicinal Plant Angelica biserrata Using Genetic and Metabolic Data
title_sort constructing a core collection of the medicinal plant angelica biserrata using genetic and metabolic data
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785966/
https://www.ncbi.nlm.nih.gov/pubmed/33424898
http://dx.doi.org/10.3389/fpls.2020.600249
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