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Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency

In recent years developments in plant phenomic approaches and facilities have gradually caught up with genomic approaches. An opportunity lies ahead to dissect complex, quantitative traits when both genotype and phenotype can be assessed at a high level of detail. This is especially true for the stu...

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Autores principales: van Bezouw, Roel F. H. M., Keurentjes, Joost J. B., Harbinson, Jeremy, Aarts, Mark G. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6850172/
https://www.ncbi.nlm.nih.gov/pubmed/30548574
http://dx.doi.org/10.1111/tpj.14190
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author van Bezouw, Roel F. H. M.
Keurentjes, Joost J. B.
Harbinson, Jeremy
Aarts, Mark G. M.
author_facet van Bezouw, Roel F. H. M.
Keurentjes, Joost J. B.
Harbinson, Jeremy
Aarts, Mark G. M.
author_sort van Bezouw, Roel F. H. M.
collection PubMed
description In recent years developments in plant phenomic approaches and facilities have gradually caught up with genomic approaches. An opportunity lies ahead to dissect complex, quantitative traits when both genotype and phenotype can be assessed at a high level of detail. This is especially true for the study of natural variation in photosynthetic efficiency, for which forward genetics studies have yielded only a little progress in our understanding of the genetic layout of the trait. High‐throughput phenotyping, primarily from chlorophyll fluorescence imaging, should help to dissect the genetics of photosynthesis at the different levels of both plant physiology and development. Specific emphasis should be directed towards understanding the acclimation of the photosynthetic machinery in fluctuating environments, which may be crucial for the identification of genetic variation for relevant traits in food crops. Facilities should preferably be designed to accommodate phenotyping of photosynthesis‐related traits in such environments. The use of forward genetics to study the genetic architecture of photosynthesis is likely to lead to the discovery of novel traits and/or genes that may be targeted in breeding or bio‐engineering approaches to improve crop photosynthetic efficiency. In the near future, big data approaches will play a pivotal role in data processing and streamlining the phenotype‐to‐gene identification pipeline.
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spelling pubmed-68501722019-11-18 Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency van Bezouw, Roel F. H. M. Keurentjes, Joost J. B. Harbinson, Jeremy Aarts, Mark G. M. Plant J Si Genome to Phenome In recent years developments in plant phenomic approaches and facilities have gradually caught up with genomic approaches. An opportunity lies ahead to dissect complex, quantitative traits when both genotype and phenotype can be assessed at a high level of detail. This is especially true for the study of natural variation in photosynthetic efficiency, for which forward genetics studies have yielded only a little progress in our understanding of the genetic layout of the trait. High‐throughput phenotyping, primarily from chlorophyll fluorescence imaging, should help to dissect the genetics of photosynthesis at the different levels of both plant physiology and development. Specific emphasis should be directed towards understanding the acclimation of the photosynthetic machinery in fluctuating environments, which may be crucial for the identification of genetic variation for relevant traits in food crops. Facilities should preferably be designed to accommodate phenotyping of photosynthesis‐related traits in such environments. The use of forward genetics to study the genetic architecture of photosynthesis is likely to lead to the discovery of novel traits and/or genes that may be targeted in breeding or bio‐engineering approaches to improve crop photosynthetic efficiency. In the near future, big data approaches will play a pivotal role in data processing and streamlining the phenotype‐to‐gene identification pipeline. John Wiley and Sons Inc. 2019-01-12 2019-01 /pmc/articles/PMC6850172/ /pubmed/30548574 http://dx.doi.org/10.1111/tpj.14190 Text en © 2018 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Si Genome to Phenome
van Bezouw, Roel F. H. M.
Keurentjes, Joost J. B.
Harbinson, Jeremy
Aarts, Mark G. M.
Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency
title Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency
title_full Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency
title_fullStr Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency
title_full_unstemmed Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency
title_short Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency
title_sort converging phenomics and genomics to study natural variation in plant photosynthetic efficiency
topic Si Genome to Phenome
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6850172/
https://www.ncbi.nlm.nih.gov/pubmed/30548574
http://dx.doi.org/10.1111/tpj.14190
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