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Functional phenomics and genetics of the root economics space in winter wheat using high‐throughput phenotyping of respiration and architecture

The root economics space is a useful framework for plant ecology but is rarely considered for crop ecophysiology. In order to understand root trait integration in winter wheat, we combined functional phenomics with trait economic theory, utilizing genetic variation, high‐throughput phenotyping, and...

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Autores principales: Guo, Haichao, Ayalew, Habtamu, Seethepalli, Anand, Dhakal, Kundan, Griffiths, Marcus, Ma, Xue‐Feng, York, Larry M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8518983/
https://www.ncbi.nlm.nih.gov/pubmed/33683730
http://dx.doi.org/10.1111/nph.17329
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author Guo, Haichao
Ayalew, Habtamu
Seethepalli, Anand
Dhakal, Kundan
Griffiths, Marcus
Ma, Xue‐Feng
York, Larry M.
author_facet Guo, Haichao
Ayalew, Habtamu
Seethepalli, Anand
Dhakal, Kundan
Griffiths, Marcus
Ma, Xue‐Feng
York, Larry M.
author_sort Guo, Haichao
collection PubMed
description The root economics space is a useful framework for plant ecology but is rarely considered for crop ecophysiology. In order to understand root trait integration in winter wheat, we combined functional phenomics with trait economic theory, utilizing genetic variation, high‐throughput phenotyping, and multivariate analyses. We phenotyped a diversity panel of 276 genotypes for root respiration and architectural traits using a novel high‐throughput method for CO(2) flux and the open‐source software rhizovision explorer to analyze scanned images. We uncovered substantial variation in specific root respiration (SRR) and specific root length (SRL), which were primary indicators of root metabolic and structural costs. Multiple linear regression analysis indicated that lateral root tips had the greatest SRR, and the residuals from this model were used as a new trait. Specific root respiration was negatively correlated with plant mass. Network analysis, using a Gaussian graphical model, identified root weight, SRL, diameter, and SRR as hub traits. Univariate and multivariate genetic analyses identified genetic regions associated with SRR, SRL, and root branching frequency, and proposed gene candidates. Combining functional phenomics and root economics is a promising approach to improving our understanding of crop ecophysiology. We identified root traits and genomic regions that could be harnessed to breed more efficient crops for sustainable agroecosystems.
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spelling pubmed-85189832021-10-21 Functional phenomics and genetics of the root economics space in winter wheat using high‐throughput phenotyping of respiration and architecture Guo, Haichao Ayalew, Habtamu Seethepalli, Anand Dhakal, Kundan Griffiths, Marcus Ma, Xue‐Feng York, Larry M. New Phytol Research The root economics space is a useful framework for plant ecology but is rarely considered for crop ecophysiology. In order to understand root trait integration in winter wheat, we combined functional phenomics with trait economic theory, utilizing genetic variation, high‐throughput phenotyping, and multivariate analyses. We phenotyped a diversity panel of 276 genotypes for root respiration and architectural traits using a novel high‐throughput method for CO(2) flux and the open‐source software rhizovision explorer to analyze scanned images. We uncovered substantial variation in specific root respiration (SRR) and specific root length (SRL), which were primary indicators of root metabolic and structural costs. Multiple linear regression analysis indicated that lateral root tips had the greatest SRR, and the residuals from this model were used as a new trait. Specific root respiration was negatively correlated with plant mass. Network analysis, using a Gaussian graphical model, identified root weight, SRL, diameter, and SRR as hub traits. Univariate and multivariate genetic analyses identified genetic regions associated with SRR, SRL, and root branching frequency, and proposed gene candidates. Combining functional phenomics and root economics is a promising approach to improving our understanding of crop ecophysiology. We identified root traits and genomic regions that could be harnessed to breed more efficient crops for sustainable agroecosystems. John Wiley and Sons Inc. 2021-04-26 2021-10 /pmc/articles/PMC8518983/ /pubmed/33683730 http://dx.doi.org/10.1111/nph.17329 Text en © 2021 The Authors. New Phytologist © 2021 New Phytologist Foundation https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Guo, Haichao
Ayalew, Habtamu
Seethepalli, Anand
Dhakal, Kundan
Griffiths, Marcus
Ma, Xue‐Feng
York, Larry M.
Functional phenomics and genetics of the root economics space in winter wheat using high‐throughput phenotyping of respiration and architecture
title Functional phenomics and genetics of the root economics space in winter wheat using high‐throughput phenotyping of respiration and architecture
title_full Functional phenomics and genetics of the root economics space in winter wheat using high‐throughput phenotyping of respiration and architecture
title_fullStr Functional phenomics and genetics of the root economics space in winter wheat using high‐throughput phenotyping of respiration and architecture
title_full_unstemmed Functional phenomics and genetics of the root economics space in winter wheat using high‐throughput phenotyping of respiration and architecture
title_short Functional phenomics and genetics of the root economics space in winter wheat using high‐throughput phenotyping of respiration and architecture
title_sort functional phenomics and genetics of the root economics space in winter wheat using high‐throughput phenotyping of respiration and architecture
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8518983/
https://www.ncbi.nlm.nih.gov/pubmed/33683730
http://dx.doi.org/10.1111/nph.17329
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