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Identification and utilization of genetic determinants of trait measurement errors in image-based, high-throughput phenotyping
The accuracy of trait measurements greatly affects the quality of genetic analyses. During automated phenotyping, trait measurement errors, i.e. differences between automatically extracted trait values and ground truth, are often treated as random effects that can be controlled by increasing populat...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8408462/ https://www.ncbi.nlm.nih.gov/pubmed/34015121 http://dx.doi.org/10.1093/plcell/koab134 |
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author | Zhou, Yan Kusmec, Aaron Mirnezami, Seyed Vahid Attigala, Lakshmi Srinivasan, Srikant Jubery, Talukder Z. Schnable, James C. Salas-Fernandez, Maria G. Ganapathysubramanian, Baskar Schnable, Patrick S. |
author_facet | Zhou, Yan Kusmec, Aaron Mirnezami, Seyed Vahid Attigala, Lakshmi Srinivasan, Srikant Jubery, Talukder Z. Schnable, James C. Salas-Fernandez, Maria G. Ganapathysubramanian, Baskar Schnable, Patrick S. |
author_sort | Zhou, Yan |
collection | PubMed |
description | The accuracy of trait measurements greatly affects the quality of genetic analyses. During automated phenotyping, trait measurement errors, i.e. differences between automatically extracted trait values and ground truth, are often treated as random effects that can be controlled by increasing population sizes and/or replication number. In contrast, there is some evidence that trait measurement errors may be partially under genetic control. Consistent with this hypothesis, we observed substantial nonrandom, genetic contributions to trait measurement errors for five maize (Zea mays) tassel traits collected using an image-based phenotyping platform. The phenotyping accuracy varied according to whether a tassel exhibited “open” versus. “closed” branching architecture, which is itself under genetic control. Trait-associated SNPs (TASs) identified via genome-wide association studies (GWASs) conducted on five tassel traits that had been phenotyped both manually (i.e. ground truth) and via feature extraction from images exhibit little overlap. Furthermore, identification of TASs from GWASs conducted on the differences between the two values indicated that a fraction of measurement error is under genetic control. Similar results were obtained in a sorghum (Sorghum bicolor) plant height dataset, demonstrating that trait measurement error is genetically determined in multiple species and traits. Trait measurement bias cannot be controlled by increasing population size and/or replication number. |
format | Online Article Text |
id | pubmed-8408462 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-84084622021-09-02 Identification and utilization of genetic determinants of trait measurement errors in image-based, high-throughput phenotyping Zhou, Yan Kusmec, Aaron Mirnezami, Seyed Vahid Attigala, Lakshmi Srinivasan, Srikant Jubery, Talukder Z. Schnable, James C. Salas-Fernandez, Maria G. Ganapathysubramanian, Baskar Schnable, Patrick S. Plant Cell Research Articles The accuracy of trait measurements greatly affects the quality of genetic analyses. During automated phenotyping, trait measurement errors, i.e. differences between automatically extracted trait values and ground truth, are often treated as random effects that can be controlled by increasing population sizes and/or replication number. In contrast, there is some evidence that trait measurement errors may be partially under genetic control. Consistent with this hypothesis, we observed substantial nonrandom, genetic contributions to trait measurement errors for five maize (Zea mays) tassel traits collected using an image-based phenotyping platform. The phenotyping accuracy varied according to whether a tassel exhibited “open” versus. “closed” branching architecture, which is itself under genetic control. Trait-associated SNPs (TASs) identified via genome-wide association studies (GWASs) conducted on five tassel traits that had been phenotyped both manually (i.e. ground truth) and via feature extraction from images exhibit little overlap. Furthermore, identification of TASs from GWASs conducted on the differences between the two values indicated that a fraction of measurement error is under genetic control. Similar results were obtained in a sorghum (Sorghum bicolor) plant height dataset, demonstrating that trait measurement error is genetically determined in multiple species and traits. Trait measurement bias cannot be controlled by increasing population size and/or replication number. Oxford University Press 2021-05-20 /pmc/articles/PMC8408462/ /pubmed/34015121 http://dx.doi.org/10.1093/plcell/koab134 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of American Society of Plant Biologists. 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 (http://creativecommons.org/licenses/by-nc-nd/4.0/ (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 | Research Articles Zhou, Yan Kusmec, Aaron Mirnezami, Seyed Vahid Attigala, Lakshmi Srinivasan, Srikant Jubery, Talukder Z. Schnable, James C. Salas-Fernandez, Maria G. Ganapathysubramanian, Baskar Schnable, Patrick S. Identification and utilization of genetic determinants of trait measurement errors in image-based, high-throughput phenotyping |
title | Identification and utilization of genetic determinants of trait measurement errors in image-based, high-throughput phenotyping |
title_full | Identification and utilization of genetic determinants of trait measurement errors in image-based, high-throughput phenotyping |
title_fullStr | Identification and utilization of genetic determinants of trait measurement errors in image-based, high-throughput phenotyping |
title_full_unstemmed | Identification and utilization of genetic determinants of trait measurement errors in image-based, high-throughput phenotyping |
title_short | Identification and utilization of genetic determinants of trait measurement errors in image-based, high-throughput phenotyping |
title_sort | identification and utilization of genetic determinants of trait measurement errors in image-based, high-throughput phenotyping |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8408462/ https://www.ncbi.nlm.nih.gov/pubmed/34015121 http://dx.doi.org/10.1093/plcell/koab134 |
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