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Genetic Diversity, Population Structure and Subset Development in a Sesbania sesban Collection

Sesbania sesban (L.) Merr. is a multipurpose legume tree grown primarily for fodder and forage in the tropical and subtropical world. In this study, the Sesbania sesban collection maintained in the International Livestock Research Institute (ILRI) forage Genebank was studied using genome-wide marker...

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Autores principales: Negawo, Alemayehu Teressa, Akinmade, Habib Olumide, Muktar, Meki S., Habte, Ermias, Assefa, Yilikal, Muchugi, Alice, Sartie, Alieu M., Jones, Chris S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823922/
https://www.ncbi.nlm.nih.gov/pubmed/36616142
http://dx.doi.org/10.3390/plants12010013
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author Negawo, Alemayehu Teressa
Akinmade, Habib Olumide
Muktar, Meki S.
Habte, Ermias
Assefa, Yilikal
Muchugi, Alice
Sartie, Alieu M.
Jones, Chris S.
author_facet Negawo, Alemayehu Teressa
Akinmade, Habib Olumide
Muktar, Meki S.
Habte, Ermias
Assefa, Yilikal
Muchugi, Alice
Sartie, Alieu M.
Jones, Chris S.
author_sort Negawo, Alemayehu Teressa
collection PubMed
description Sesbania sesban (L.) Merr. is a multipurpose legume tree grown primarily for fodder and forage in the tropical and subtropical world. In this study, the Sesbania sesban collection maintained in the International Livestock Research Institute (ILRI) forage Genebank was studied using genome-wide markers generated on the DArTseq platform. Genotyping produced 84,673 and 60,626 SNP and SilicoDArT markers with a mean polymorphic information content of 0.153 and 0.123, respectively. From the generated markers, 7587 and 15,031 highly informative SNP and SilicoDArT markers, respectively, were filtered and used for genetic diversity analysis and subset development. Analysis of molecular variance (AMOVA) revealed higher variability ‘within’ (52.73% for SNP markers and 67.36% for SilicoDArT markers) than ‘between’ accessions. Hierarchical cluster analysis showed the presence of four main clusters in the collection. Mantel correlation analysis showed a lack of relationship between genetic variation of the germplasm and their geographical origin. A representative subset of 34 accessions containing germplasm from diverse origins and agro-ecologies was developed using SNP markers. The genetic diversity information generated in this study could be used for marker-assisted screening for stress tolerance, gap analysis and identification and acquisition of new distinct genotype(s) to broaden the genetic basis of the collection for future improvement programs to develop high-yielding, stress-tolerant varieties for enhancing food and environmental security in crop–livestock-based production systems.
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spelling pubmed-98239222023-01-08 Genetic Diversity, Population Structure and Subset Development in a Sesbania sesban Collection Negawo, Alemayehu Teressa Akinmade, Habib Olumide Muktar, Meki S. Habte, Ermias Assefa, Yilikal Muchugi, Alice Sartie, Alieu M. Jones, Chris S. Plants (Basel) Article Sesbania sesban (L.) Merr. is a multipurpose legume tree grown primarily for fodder and forage in the tropical and subtropical world. In this study, the Sesbania sesban collection maintained in the International Livestock Research Institute (ILRI) forage Genebank was studied using genome-wide markers generated on the DArTseq platform. Genotyping produced 84,673 and 60,626 SNP and SilicoDArT markers with a mean polymorphic information content of 0.153 and 0.123, respectively. From the generated markers, 7587 and 15,031 highly informative SNP and SilicoDArT markers, respectively, were filtered and used for genetic diversity analysis and subset development. Analysis of molecular variance (AMOVA) revealed higher variability ‘within’ (52.73% for SNP markers and 67.36% for SilicoDArT markers) than ‘between’ accessions. Hierarchical cluster analysis showed the presence of four main clusters in the collection. Mantel correlation analysis showed a lack of relationship between genetic variation of the germplasm and their geographical origin. A representative subset of 34 accessions containing germplasm from diverse origins and agro-ecologies was developed using SNP markers. The genetic diversity information generated in this study could be used for marker-assisted screening for stress tolerance, gap analysis and identification and acquisition of new distinct genotype(s) to broaden the genetic basis of the collection for future improvement programs to develop high-yielding, stress-tolerant varieties for enhancing food and environmental security in crop–livestock-based production systems. MDPI 2022-12-20 /pmc/articles/PMC9823922/ /pubmed/36616142 http://dx.doi.org/10.3390/plants12010013 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
Negawo, Alemayehu Teressa
Akinmade, Habib Olumide
Muktar, Meki S.
Habte, Ermias
Assefa, Yilikal
Muchugi, Alice
Sartie, Alieu M.
Jones, Chris S.
Genetic Diversity, Population Structure and Subset Development in a Sesbania sesban Collection
title Genetic Diversity, Population Structure and Subset Development in a Sesbania sesban Collection
title_full Genetic Diversity, Population Structure and Subset Development in a Sesbania sesban Collection
title_fullStr Genetic Diversity, Population Structure and Subset Development in a Sesbania sesban Collection
title_full_unstemmed Genetic Diversity, Population Structure and Subset Development in a Sesbania sesban Collection
title_short Genetic Diversity, Population Structure and Subset Development in a Sesbania sesban Collection
title_sort genetic diversity, population structure and subset development in a sesbania sesban collection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823922/
https://www.ncbi.nlm.nih.gov/pubmed/36616142
http://dx.doi.org/10.3390/plants12010013
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