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.
Bibliographical noteFunding Information:
We would like to thank Qiguang Xie for providing prr5-1prr7-3prr9-1 mutant seed. This work was supported by the National Science Foundation (NSF) National Plant Genome Initiative Postdoctoral Fellowship (IOS-1202779) to K.G., and by grants from the NSF (IOS-0923752 and IOS-1025965) to C.R.M and (CNS-0708209) to H.F.
© 2015 Greenham et al.; licensee BioMed Central.
- Circadian period
- Leaf movement
- Motion estimation