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Metabolic-GWAS provides insights into genetic architecture of seed metabolome in buckwheat
BACKGROUND: Buckwheat (Fagopyrum spp.), belonging to the Polygonaceae family, is an ancient pseudo-cereal with high nutritional and nutraceutical properties. Buckwheat proteins are gluten-free and show balanced amino acid and micronutrient profiles, with higher content of health-promoting bioactive...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10375682/ https://www.ncbi.nlm.nih.gov/pubmed/37501129 http://dx.doi.org/10.1186/s12870-023-04381-x |
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author | Zargar, Sajad Majeed Manzoor, Madhiya Bhat, Basharat Wani, Amir Bashir Sofi, Parvaze Ahmad Sudan, Jebi Ebinezer, Leonard Barnabas Dall’Acqua, Stefano Peron, Gregorio Masi, Antonio |
author_facet | Zargar, Sajad Majeed Manzoor, Madhiya Bhat, Basharat Wani, Amir Bashir Sofi, Parvaze Ahmad Sudan, Jebi Ebinezer, Leonard Barnabas Dall’Acqua, Stefano Peron, Gregorio Masi, Antonio |
author_sort | Zargar, Sajad Majeed |
collection | PubMed |
description | BACKGROUND: Buckwheat (Fagopyrum spp.), belonging to the Polygonaceae family, is an ancient pseudo-cereal with high nutritional and nutraceutical properties. Buckwheat proteins are gluten-free and show balanced amino acid and micronutrient profiles, with higher content of health-promoting bioactive flavonoids that make it a golden crop of the future. Plant metabolome is increasingly gaining importance as a crucial component to understand the connection between plant physiology and environment and as a potential link between the genome and phenome. However, the genetic architecture governing the metabolome and thus, the phenome is not well understood. Here, we aim to obtain a deeper insight into the genetic architecture of seed metabolome in buckwheat by integrating high throughput metabolomics and genotyping-by-sequencing applying an array of bioinformatics tools for data analysis. RESULTS: High throughput metabolomic analysis identified 24 metabolites in seed endosperm of 130 diverse buckwheat genotypes. The genotyping-by-sequencing (GBS) of these genotypes revealed 3,728,028 SNPs. The Genome Association and Prediction Integrated Tool (GAPIT) assisted in the identification of 27 SNPs/QTLs linked to 18 metabolites. Candidate genes were identified near 100 Kb of QTLs, providing insights into several metabolic and biosynthetic pathways. CONCLUSIONS: We established the metabolome inventory of 130 germplasm lines of buckwheat, identified QTLs through marker trait association and positions of potential candidate genes. This will pave the way for future dissection of complex economic traits in buckwheat. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12870-023-04381-x. |
format | Online Article Text |
id | pubmed-10375682 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-103756822023-07-29 Metabolic-GWAS provides insights into genetic architecture of seed metabolome in buckwheat Zargar, Sajad Majeed Manzoor, Madhiya Bhat, Basharat Wani, Amir Bashir Sofi, Parvaze Ahmad Sudan, Jebi Ebinezer, Leonard Barnabas Dall’Acqua, Stefano Peron, Gregorio Masi, Antonio BMC Plant Biol Research Article BACKGROUND: Buckwheat (Fagopyrum spp.), belonging to the Polygonaceae family, is an ancient pseudo-cereal with high nutritional and nutraceutical properties. Buckwheat proteins are gluten-free and show balanced amino acid and micronutrient profiles, with higher content of health-promoting bioactive flavonoids that make it a golden crop of the future. Plant metabolome is increasingly gaining importance as a crucial component to understand the connection between plant physiology and environment and as a potential link between the genome and phenome. However, the genetic architecture governing the metabolome and thus, the phenome is not well understood. Here, we aim to obtain a deeper insight into the genetic architecture of seed metabolome in buckwheat by integrating high throughput metabolomics and genotyping-by-sequencing applying an array of bioinformatics tools for data analysis. RESULTS: High throughput metabolomic analysis identified 24 metabolites in seed endosperm of 130 diverse buckwheat genotypes. The genotyping-by-sequencing (GBS) of these genotypes revealed 3,728,028 SNPs. The Genome Association and Prediction Integrated Tool (GAPIT) assisted in the identification of 27 SNPs/QTLs linked to 18 metabolites. Candidate genes were identified near 100 Kb of QTLs, providing insights into several metabolic and biosynthetic pathways. CONCLUSIONS: We established the metabolome inventory of 130 germplasm lines of buckwheat, identified QTLs through marker trait association and positions of potential candidate genes. This will pave the way for future dissection of complex economic traits in buckwheat. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12870-023-04381-x. BioMed Central 2023-07-28 /pmc/articles/PMC10375682/ /pubmed/37501129 http://dx.doi.org/10.1186/s12870-023-04381-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Zargar, Sajad Majeed Manzoor, Madhiya Bhat, Basharat Wani, Amir Bashir Sofi, Parvaze Ahmad Sudan, Jebi Ebinezer, Leonard Barnabas Dall’Acqua, Stefano Peron, Gregorio Masi, Antonio Metabolic-GWAS provides insights into genetic architecture of seed metabolome in buckwheat |
title | Metabolic-GWAS provides insights into genetic architecture of seed metabolome in buckwheat |
title_full | Metabolic-GWAS provides insights into genetic architecture of seed metabolome in buckwheat |
title_fullStr | Metabolic-GWAS provides insights into genetic architecture of seed metabolome in buckwheat |
title_full_unstemmed | Metabolic-GWAS provides insights into genetic architecture of seed metabolome in buckwheat |
title_short | Metabolic-GWAS provides insights into genetic architecture of seed metabolome in buckwheat |
title_sort | metabolic-gwas provides insights into genetic architecture of seed metabolome in buckwheat |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10375682/ https://www.ncbi.nlm.nih.gov/pubmed/37501129 http://dx.doi.org/10.1186/s12870-023-04381-x |
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