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Crop genetic diversity uncovers metabolites, elements, and gene networks predicted to be associated with high plant biomass yields in maize
Rapid population growth and increasing demand for food, feed, and bioenergy in these times of unprecedented climate change require breeding for increased biomass production on the world's croplands. To accelerate breeding programs, knowledge of the relationship between biomass features and unde...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9896949/ https://www.ncbi.nlm.nih.gov/pubmed/36741443 http://dx.doi.org/10.1093/pnasnexus/pgac068 |
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author | Hajheidari, Mohsen Gerlach, Nina Dorau, Kristof Omidbakhshfard, M Amin Pesch, Lina Hofmann, Jörg Hallab, Asis Ponce-Soto, Gabriel Y Kuhalskaya, Anastasiya Medeiros, David B Bourceret, Amélia Usadel, Björn Mayer, Jochen Fernie, Alisdair Mansfeldt, Tim Sonnewald, Uwe Bucher, Marcel |
author_facet | Hajheidari, Mohsen Gerlach, Nina Dorau, Kristof Omidbakhshfard, M Amin Pesch, Lina Hofmann, Jörg Hallab, Asis Ponce-Soto, Gabriel Y Kuhalskaya, Anastasiya Medeiros, David B Bourceret, Amélia Usadel, Björn Mayer, Jochen Fernie, Alisdair Mansfeldt, Tim Sonnewald, Uwe Bucher, Marcel |
author_sort | Hajheidari, Mohsen |
collection | PubMed |
description | Rapid population growth and increasing demand for food, feed, and bioenergy in these times of unprecedented climate change require breeding for increased biomass production on the world's croplands. To accelerate breeding programs, knowledge of the relationship between biomass features and underlying gene networks is needed to guide future breeding efforts. To this end, large-scale multiomics datasets were created with genetically diverse maize lines, all grown in long-term organic and conventional cropping systems. Analysis of the datasets, integrated using regression modeling and network analysis revealed key metabolites, elements, gene transcripts, and gene networks, whose contents during vegetative growth substantially influence the build-up of plant biomass in the reproductive phase. We found that S and P content in the source leaf and P content in the root during the vegetative stage contributed the most to predicting plant performance at the reproductive stage. In agreement with the Gene Ontology enrichment analysis, the cis-motifs and identified transcription factors associated with upregulated genes under phosphate deficiency showed great diversity in the molecular response to phosphate deficiency in selected lines. Furthermore, our data demonstrate that genotype-dependent uptake, assimilation, and allocation of essential nutrient elements (especially C and N) during vegetative growth under phosphate starvation plays an important role in determining plant biomass by controlling root traits related to nutrient uptake. These integrative multiomics results revealed key factors underlying maize productivity and open new opportunities for efficient, rapid, and cost-effective plant breeding to increase biomass yield of the cereal crop maize under adverse environmental factors. |
format | Online Article Text |
id | pubmed-9896949 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98969492023-02-04 Crop genetic diversity uncovers metabolites, elements, and gene networks predicted to be associated with high plant biomass yields in maize Hajheidari, Mohsen Gerlach, Nina Dorau, Kristof Omidbakhshfard, M Amin Pesch, Lina Hofmann, Jörg Hallab, Asis Ponce-Soto, Gabriel Y Kuhalskaya, Anastasiya Medeiros, David B Bourceret, Amélia Usadel, Björn Mayer, Jochen Fernie, Alisdair Mansfeldt, Tim Sonnewald, Uwe Bucher, Marcel PNAS Nexus Biological, Health, and Medical Sciences Rapid population growth and increasing demand for food, feed, and bioenergy in these times of unprecedented climate change require breeding for increased biomass production on the world's croplands. To accelerate breeding programs, knowledge of the relationship between biomass features and underlying gene networks is needed to guide future breeding efforts. To this end, large-scale multiomics datasets were created with genetically diverse maize lines, all grown in long-term organic and conventional cropping systems. Analysis of the datasets, integrated using regression modeling and network analysis revealed key metabolites, elements, gene transcripts, and gene networks, whose contents during vegetative growth substantially influence the build-up of plant biomass in the reproductive phase. We found that S and P content in the source leaf and P content in the root during the vegetative stage contributed the most to predicting plant performance at the reproductive stage. In agreement with the Gene Ontology enrichment analysis, the cis-motifs and identified transcription factors associated with upregulated genes under phosphate deficiency showed great diversity in the molecular response to phosphate deficiency in selected lines. Furthermore, our data demonstrate that genotype-dependent uptake, assimilation, and allocation of essential nutrient elements (especially C and N) during vegetative growth under phosphate starvation plays an important role in determining plant biomass by controlling root traits related to nutrient uptake. These integrative multiomics results revealed key factors underlying maize productivity and open new opportunities for efficient, rapid, and cost-effective plant breeding to increase biomass yield of the cereal crop maize under adverse environmental factors. Oxford University Press 2022-07-04 /pmc/articles/PMC9896949/ /pubmed/36741443 http://dx.doi.org/10.1093/pnasnexus/pgac068 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the National Academy of Sciences. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Biological, Health, and Medical Sciences Hajheidari, Mohsen Gerlach, Nina Dorau, Kristof Omidbakhshfard, M Amin Pesch, Lina Hofmann, Jörg Hallab, Asis Ponce-Soto, Gabriel Y Kuhalskaya, Anastasiya Medeiros, David B Bourceret, Amélia Usadel, Björn Mayer, Jochen Fernie, Alisdair Mansfeldt, Tim Sonnewald, Uwe Bucher, Marcel Crop genetic diversity uncovers metabolites, elements, and gene networks predicted to be associated with high plant biomass yields in maize |
title | Crop genetic diversity uncovers metabolites, elements, and gene networks predicted to be associated with high plant biomass yields in maize |
title_full | Crop genetic diversity uncovers metabolites, elements, and gene networks predicted to be associated with high plant biomass yields in maize |
title_fullStr | Crop genetic diversity uncovers metabolites, elements, and gene networks predicted to be associated with high plant biomass yields in maize |
title_full_unstemmed | Crop genetic diversity uncovers metabolites, elements, and gene networks predicted to be associated with high plant biomass yields in maize |
title_short | Crop genetic diversity uncovers metabolites, elements, and gene networks predicted to be associated with high plant biomass yields in maize |
title_sort | crop genetic diversity uncovers metabolites, elements, and gene networks predicted to be associated with high plant biomass yields in maize |
topic | Biological, Health, and Medical Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9896949/ https://www.ncbi.nlm.nih.gov/pubmed/36741443 http://dx.doi.org/10.1093/pnasnexus/pgac068 |
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