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Large root cortical cells and reduced cortical cell files improve growth under suboptimal nitrogen in silico

Suboptimal nitrogen availability is a primary constraint to plant growth. We used OpenSimRoot, a functional-structural plant/soil model, to test the hypothesis that larger root cortical cell size (CCS), reduced cortical cell file number (CCFN), and their interactions with root cortical aerenchyma (R...

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Autores principales: Lopez-Valdivia, Ivan, Yang, Xiyu, Lynch, Jonathan P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10315315/
https://www.ncbi.nlm.nih.gov/pubmed/37040571
http://dx.doi.org/10.1093/plphys/kiad214
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author Lopez-Valdivia, Ivan
Yang, Xiyu
Lynch, Jonathan P
author_facet Lopez-Valdivia, Ivan
Yang, Xiyu
Lynch, Jonathan P
author_sort Lopez-Valdivia, Ivan
collection PubMed
description Suboptimal nitrogen availability is a primary constraint to plant growth. We used OpenSimRoot, a functional-structural plant/soil model, to test the hypothesis that larger root cortical cell size (CCS), reduced cortical cell file number (CCFN), and their interactions with root cortical aerenchyma (RCA) and lateral root branching density (LRBD) are useful adaptations to suboptimal soil nitrogen availability in maize (Zea mays). Reduced CCFN increased shoot dry weight over 80%. Reduced respiration, reduced nitrogen content, and reduced root diameter accounted for 23%, 20%, and 33% of increased shoot biomass, respectively. Large CCS increased shoot biomass by 24% compared with small CCS. When simulated independently, reduced respiration and reduced nutrient content increased the shoot biomass by 14% and 3%, respectively. However, increased root diameter resulting from large CCS decreased shoot biomass by 4% due to an increase in root metabolic cost. Under moderate N stress, integrated phenotypes with reduced CCFN, large CCS, and high RCA improved shoot biomass in silt loam and loamy sand soils. In contrast, integrated phenotypes composed of reduced CCFN, large CCS, and reduced LRBD had the greatest growth in silt loam, while phenotypes with reduced CCFN, large CCS, and high LRBD were the best performers in loamy sands. Our results support the hypothesis that larger CCS, reduced CCFN, and their interactions with RCA and LRBD could increase nitrogen acquisition by reducing root respiration and root nutrient demand. Phene synergisms may exist between CCS, CCFN, and LRBD. CCS and CCFN merit consideration for breeding cereal crops with improved nitrogen acquisition, which is critical for global food security.
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spelling pubmed-103153152023-07-04 Large root cortical cells and reduced cortical cell files improve growth under suboptimal nitrogen in silico Lopez-Valdivia, Ivan Yang, Xiyu Lynch, Jonathan P Plant Physiol Research Article Suboptimal nitrogen availability is a primary constraint to plant growth. We used OpenSimRoot, a functional-structural plant/soil model, to test the hypothesis that larger root cortical cell size (CCS), reduced cortical cell file number (CCFN), and their interactions with root cortical aerenchyma (RCA) and lateral root branching density (LRBD) are useful adaptations to suboptimal soil nitrogen availability in maize (Zea mays). Reduced CCFN increased shoot dry weight over 80%. Reduced respiration, reduced nitrogen content, and reduced root diameter accounted for 23%, 20%, and 33% of increased shoot biomass, respectively. Large CCS increased shoot biomass by 24% compared with small CCS. When simulated independently, reduced respiration and reduced nutrient content increased the shoot biomass by 14% and 3%, respectively. However, increased root diameter resulting from large CCS decreased shoot biomass by 4% due to an increase in root metabolic cost. Under moderate N stress, integrated phenotypes with reduced CCFN, large CCS, and high RCA improved shoot biomass in silt loam and loamy sand soils. In contrast, integrated phenotypes composed of reduced CCFN, large CCS, and reduced LRBD had the greatest growth in silt loam, while phenotypes with reduced CCFN, large CCS, and high LRBD were the best performers in loamy sands. Our results support the hypothesis that larger CCS, reduced CCFN, and their interactions with RCA and LRBD could increase nitrogen acquisition by reducing root respiration and root nutrient demand. Phene synergisms may exist between CCS, CCFN, and LRBD. CCS and CCFN merit consideration for breeding cereal crops with improved nitrogen acquisition, which is critical for global food security. Oxford University Press 2023-04-11 /pmc/articles/PMC10315315/ /pubmed/37040571 http://dx.doi.org/10.1093/plphys/kiad214 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of American Society of Plant Biologists. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Lopez-Valdivia, Ivan
Yang, Xiyu
Lynch, Jonathan P
Large root cortical cells and reduced cortical cell files improve growth under suboptimal nitrogen in silico
title Large root cortical cells and reduced cortical cell files improve growth under suboptimal nitrogen in silico
title_full Large root cortical cells and reduced cortical cell files improve growth under suboptimal nitrogen in silico
title_fullStr Large root cortical cells and reduced cortical cell files improve growth under suboptimal nitrogen in silico
title_full_unstemmed Large root cortical cells and reduced cortical cell files improve growth under suboptimal nitrogen in silico
title_short Large root cortical cells and reduced cortical cell files improve growth under suboptimal nitrogen in silico
title_sort large root cortical cells and reduced cortical cell files improve growth under suboptimal nitrogen in silico
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10315315/
https://www.ncbi.nlm.nih.gov/pubmed/37040571
http://dx.doi.org/10.1093/plphys/kiad214
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