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Genome-wide association mapping reveals genes underlying population-level metabolome diversity in a fungal crop pathogen
BACKGROUND: Fungi produce a wide range of specialized metabolites (SMs) involved in biotic interactions. Pathways for the production of SMs are often encoded in clusters of tightly arranged genes identified as biosynthetic gene clusters. Such gene clusters can undergo horizontal gene transfers betwe...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9548119/ https://www.ncbi.nlm.nih.gov/pubmed/36209159 http://dx.doi.org/10.1186/s12915-022-01422-z |
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author | Singh, Nikhil Kumar Tralamazza, Sabina Moser Abraham, Leen Nanchira Glauser, Gaétan Croll, Daniel |
author_facet | Singh, Nikhil Kumar Tralamazza, Sabina Moser Abraham, Leen Nanchira Glauser, Gaétan Croll, Daniel |
author_sort | Singh, Nikhil Kumar |
collection | PubMed |
description | BACKGROUND: Fungi produce a wide range of specialized metabolites (SMs) involved in biotic interactions. Pathways for the production of SMs are often encoded in clusters of tightly arranged genes identified as biosynthetic gene clusters. Such gene clusters can undergo horizontal gene transfers between species and rapid evolutionary change within species. The acquisition, rearrangement, and deletion of gene clusters can generate significant metabolome diversity. However, the genetic basis underlying variation in SM production remains poorly understood. RESULTS: Here, we analyzed the metabolite production of a large population of the fungal pathogen of wheat, Zymoseptoria tritici. The pathogen causes major yield losses and shows variation in gene clusters. We performed untargeted ultra-high performance liquid chromatography-high resolution mass spectrometry to profile the metabolite diversity among 102 isolates of the same species. We found substantial variation in the abundance of the detected metabolites among isolates. Integrating whole-genome sequencing data, we performed metabolite genome-wide association mapping to identify loci underlying variation in metabolite production (i.e., metabolite-GWAS). We found that significantly associated SNPs reside mostly in coding and gene regulatory regions. Associated genes encode mainly transport and catalytic activities. The metabolite-GWAS identified also a polymorphism in the 3′UTR region of a virulence gene related to metabolite production and showing expression variation. CONCLUSIONS: Taken together, our study provides a significant resource to unravel polymorphism underlying metabolome diversity within a species. Integrating metabolome screens should be feasible for a range of different plant pathogens and help prioritize molecular studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12915-022-01422-z. |
format | Online Article Text |
id | pubmed-9548119 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-95481192022-10-10 Genome-wide association mapping reveals genes underlying population-level metabolome diversity in a fungal crop pathogen Singh, Nikhil Kumar Tralamazza, Sabina Moser Abraham, Leen Nanchira Glauser, Gaétan Croll, Daniel BMC Biol Research Article BACKGROUND: Fungi produce a wide range of specialized metabolites (SMs) involved in biotic interactions. Pathways for the production of SMs are often encoded in clusters of tightly arranged genes identified as biosynthetic gene clusters. Such gene clusters can undergo horizontal gene transfers between species and rapid evolutionary change within species. The acquisition, rearrangement, and deletion of gene clusters can generate significant metabolome diversity. However, the genetic basis underlying variation in SM production remains poorly understood. RESULTS: Here, we analyzed the metabolite production of a large population of the fungal pathogen of wheat, Zymoseptoria tritici. The pathogen causes major yield losses and shows variation in gene clusters. We performed untargeted ultra-high performance liquid chromatography-high resolution mass spectrometry to profile the metabolite diversity among 102 isolates of the same species. We found substantial variation in the abundance of the detected metabolites among isolates. Integrating whole-genome sequencing data, we performed metabolite genome-wide association mapping to identify loci underlying variation in metabolite production (i.e., metabolite-GWAS). We found that significantly associated SNPs reside mostly in coding and gene regulatory regions. Associated genes encode mainly transport and catalytic activities. The metabolite-GWAS identified also a polymorphism in the 3′UTR region of a virulence gene related to metabolite production and showing expression variation. CONCLUSIONS: Taken together, our study provides a significant resource to unravel polymorphism underlying metabolome diversity within a species. Integrating metabolome screens should be feasible for a range of different plant pathogens and help prioritize molecular studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12915-022-01422-z. BioMed Central 2022-10-08 /pmc/articles/PMC9548119/ /pubmed/36209159 http://dx.doi.org/10.1186/s12915-022-01422-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Singh, Nikhil Kumar Tralamazza, Sabina Moser Abraham, Leen Nanchira Glauser, Gaétan Croll, Daniel Genome-wide association mapping reveals genes underlying population-level metabolome diversity in a fungal crop pathogen |
title | Genome-wide association mapping reveals genes underlying population-level metabolome diversity in a fungal crop pathogen |
title_full | Genome-wide association mapping reveals genes underlying population-level metabolome diversity in a fungal crop pathogen |
title_fullStr | Genome-wide association mapping reveals genes underlying population-level metabolome diversity in a fungal crop pathogen |
title_full_unstemmed | Genome-wide association mapping reveals genes underlying population-level metabolome diversity in a fungal crop pathogen |
title_short | Genome-wide association mapping reveals genes underlying population-level metabolome diversity in a fungal crop pathogen |
title_sort | genome-wide association mapping reveals genes underlying population-level metabolome diversity in a fungal crop pathogen |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9548119/ https://www.ncbi.nlm.nih.gov/pubmed/36209159 http://dx.doi.org/10.1186/s12915-022-01422-z |
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