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TRiP: Tracking Rhythms in Plants, an automated leaf movement analysis program for circadian period estimation

BACKGROUND: A well characterized output of the circadian clock in plants is the daily rhythmic movement of leaves. This process has been used extensively in Arabidopsis to estimate circadian period in natural accessions as well as mutants with known defects in circadian clock function. Current metho...

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Autores principales: Greenham, Kathleen, Lou, Ping, Remsen, Sara E, Farid, Hany, McClung, C Robertson
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4445800/
https://www.ncbi.nlm.nih.gov/pubmed/26019715
http://dx.doi.org/10.1186/s13007-015-0075-5
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author Greenham, Kathleen
Lou, Ping
Remsen, Sara E
Farid, Hany
McClung, C Robertson
author_facet Greenham, Kathleen
Lou, Ping
Remsen, Sara E
Farid, Hany
McClung, C Robertson
author_sort Greenham, Kathleen
collection PubMed
description BACKGROUND: A well characterized output of the circadian clock in plants is the daily rhythmic movement of leaves. This process has been used extensively in Arabidopsis to estimate circadian period in natural accessions as well as mutants with known defects in circadian clock function. Current methods for estimating circadian period by leaf movement involve manual steps throughout the analysis and are often limited to analyzing one leaf or cotyledon at a time. RESULTS: In this study, we describe the development of TRiP (Tracking Rhythms in Plants), a new method for estimating circadian period using a motion estimation algorithm that can be applied to whole plant images. To validate this new method, we apply TRiP to a Recombinant Inbred Line (RIL) population in Arabidopsis using our high-throughput imaging platform. We begin imaging at the cotyledon stage and image through the emergence of true leaves. TRiP successfully tracks the movement of cotyledons and leaves without the need to select individual leaves to be analyzed. CONCLUSIONS: TRiP is a program for analyzing leaf movement by motion estimation that enables high-throughput analysis of large populations of plants. TRiP is also able to analyze plant species with diverse leaf morphologies. We have used TRiP to estimate period for 150 Arabidopsis RILs as well as 5 diverse plant species, highlighting the broad applicability of this new method. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13007-015-0075-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-44458002015-05-28 TRiP: Tracking Rhythms in Plants, an automated leaf movement analysis program for circadian period estimation Greenham, Kathleen Lou, Ping Remsen, Sara E Farid, Hany McClung, C Robertson Plant Methods Methodology BACKGROUND: A well characterized output of the circadian clock in plants is the daily rhythmic movement of leaves. This process has been used extensively in Arabidopsis to estimate circadian period in natural accessions as well as mutants with known defects in circadian clock function. Current methods for estimating circadian period by leaf movement involve manual steps throughout the analysis and are often limited to analyzing one leaf or cotyledon at a time. RESULTS: In this study, we describe the development of TRiP (Tracking Rhythms in Plants), a new method for estimating circadian period using a motion estimation algorithm that can be applied to whole plant images. To validate this new method, we apply TRiP to a Recombinant Inbred Line (RIL) population in Arabidopsis using our high-throughput imaging platform. We begin imaging at the cotyledon stage and image through the emergence of true leaves. TRiP successfully tracks the movement of cotyledons and leaves without the need to select individual leaves to be analyzed. CONCLUSIONS: TRiP is a program for analyzing leaf movement by motion estimation that enables high-throughput analysis of large populations of plants. TRiP is also able to analyze plant species with diverse leaf morphologies. We have used TRiP to estimate period for 150 Arabidopsis RILs as well as 5 diverse plant species, highlighting the broad applicability of this new method. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13007-015-0075-5) contains supplementary material, which is available to authorized users. BioMed Central 2015-05-03 /pmc/articles/PMC4445800/ /pubmed/26019715 http://dx.doi.org/10.1186/s13007-015-0075-5 Text en © Greenham et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology
Greenham, Kathleen
Lou, Ping
Remsen, Sara E
Farid, Hany
McClung, C Robertson
TRiP: Tracking Rhythms in Plants, an automated leaf movement analysis program for circadian period estimation
title TRiP: Tracking Rhythms in Plants, an automated leaf movement analysis program for circadian period estimation
title_full TRiP: Tracking Rhythms in Plants, an automated leaf movement analysis program for circadian period estimation
title_fullStr TRiP: Tracking Rhythms in Plants, an automated leaf movement analysis program for circadian period estimation
title_full_unstemmed TRiP: Tracking Rhythms in Plants, an automated leaf movement analysis program for circadian period estimation
title_short TRiP: Tracking Rhythms in Plants, an automated leaf movement analysis program for circadian period estimation
title_sort trip: tracking rhythms in plants, an automated leaf movement analysis program for circadian period estimation
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4445800/
https://www.ncbi.nlm.nih.gov/pubmed/26019715
http://dx.doi.org/10.1186/s13007-015-0075-5
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