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An Analysis of Genetic Variability and Population Structure in Wheat Germplasm Using Microsatellite and Gene-Based Markers

Knowledge of the natural patterns of genetic variation and their evolutionary basis is required for sustainable management and conservation of wheat germplasm. In the current study, the genetic diversity and population structure of 100 individuals from four Triticum and Aegilops species (including T...

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Autores principales: Pour-Aboughadareh, Alireza, Poczai, Peter, Etminan, Alireza, Jadidi, Omid, Kianersi, Farzad, Shooshtari, Lia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9103345/
https://www.ncbi.nlm.nih.gov/pubmed/35567205
http://dx.doi.org/10.3390/plants11091205
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author Pour-Aboughadareh, Alireza
Poczai, Peter
Etminan, Alireza
Jadidi, Omid
Kianersi, Farzad
Shooshtari, Lia
author_facet Pour-Aboughadareh, Alireza
Poczai, Peter
Etminan, Alireza
Jadidi, Omid
Kianersi, Farzad
Shooshtari, Lia
author_sort Pour-Aboughadareh, Alireza
collection PubMed
description Knowledge of the natural patterns of genetic variation and their evolutionary basis is required for sustainable management and conservation of wheat germplasm. In the current study, the genetic diversity and population structure of 100 individuals from four Triticum and Aegilops species (including T. aestivum, Ae. tauschii, Ae. cylindrica, and Ae. crassa) were investigated using two gene-based markers (start codon targeted (SCoT) polymorphism and CAAT-box derived polymorphism (CBDP)) and simple-sequence repeats (SSRs). The SCoT, CBDP, and SSR markers yielded 76, 116, and 48 polymorphism fragments, respectively. The CBDP marker had greater efficiency than the SCoT and SSR markers due to its higher polymorphism content information (PIC), resolving power (Rp), and marker index (MI). Based on an analysis of molecular variance (AMOVA) performed using all marker systems and combined data, there was a higher distribution of genetic variation within species than among them. Ae. cylindrica and Ae. tauschii had the highest values for all genetic variation parameters. A cluster analysis using each marker system and combined data showed that the SSR marker had greater efficiency in grouping of tested accessions, such that the results of principal coordinate analysis (PCoA) and population structure confirmed the obtained clustering patterns. Hence, combining the SCoT and CBDP markers with polymorphic SSR markers may be useful in genetic fingerprinting and fine mapping and for association analysis in wheat and its germplasm for various agronomic traits or tolerance mechanisms to environmental stresses.
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spelling pubmed-91033452022-05-14 An Analysis of Genetic Variability and Population Structure in Wheat Germplasm Using Microsatellite and Gene-Based Markers Pour-Aboughadareh, Alireza Poczai, Peter Etminan, Alireza Jadidi, Omid Kianersi, Farzad Shooshtari, Lia Plants (Basel) Article Knowledge of the natural patterns of genetic variation and their evolutionary basis is required for sustainable management and conservation of wheat germplasm. In the current study, the genetic diversity and population structure of 100 individuals from four Triticum and Aegilops species (including T. aestivum, Ae. tauschii, Ae. cylindrica, and Ae. crassa) were investigated using two gene-based markers (start codon targeted (SCoT) polymorphism and CAAT-box derived polymorphism (CBDP)) and simple-sequence repeats (SSRs). The SCoT, CBDP, and SSR markers yielded 76, 116, and 48 polymorphism fragments, respectively. The CBDP marker had greater efficiency than the SCoT and SSR markers due to its higher polymorphism content information (PIC), resolving power (Rp), and marker index (MI). Based on an analysis of molecular variance (AMOVA) performed using all marker systems and combined data, there was a higher distribution of genetic variation within species than among them. Ae. cylindrica and Ae. tauschii had the highest values for all genetic variation parameters. A cluster analysis using each marker system and combined data showed that the SSR marker had greater efficiency in grouping of tested accessions, such that the results of principal coordinate analysis (PCoA) and population structure confirmed the obtained clustering patterns. Hence, combining the SCoT and CBDP markers with polymorphic SSR markers may be useful in genetic fingerprinting and fine mapping and for association analysis in wheat and its germplasm for various agronomic traits or tolerance mechanisms to environmental stresses. MDPI 2022-04-29 /pmc/articles/PMC9103345/ /pubmed/35567205 http://dx.doi.org/10.3390/plants11091205 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pour-Aboughadareh, Alireza
Poczai, Peter
Etminan, Alireza
Jadidi, Omid
Kianersi, Farzad
Shooshtari, Lia
An Analysis of Genetic Variability and Population Structure in Wheat Germplasm Using Microsatellite and Gene-Based Markers
title An Analysis of Genetic Variability and Population Structure in Wheat Germplasm Using Microsatellite and Gene-Based Markers
title_full An Analysis of Genetic Variability and Population Structure in Wheat Germplasm Using Microsatellite and Gene-Based Markers
title_fullStr An Analysis of Genetic Variability and Population Structure in Wheat Germplasm Using Microsatellite and Gene-Based Markers
title_full_unstemmed An Analysis of Genetic Variability and Population Structure in Wheat Germplasm Using Microsatellite and Gene-Based Markers
title_short An Analysis of Genetic Variability and Population Structure in Wheat Germplasm Using Microsatellite and Gene-Based Markers
title_sort analysis of genetic variability and population structure in wheat germplasm using microsatellite and gene-based markers
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9103345/
https://www.ncbi.nlm.nih.gov/pubmed/35567205
http://dx.doi.org/10.3390/plants11091205
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