Evidence map›Paper›PMID 31139241›Full record

ArticlePlant methods2019

A high-throughput delayed fluorescence method reveals underlying differences in the control of circadian rhythms in

Hannah Rees, Susan Duncan, Peter Gould, Rachel Wells, Mark Greenwood, Thomas Brabbs, Anthony Hall

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In one paragraph

Article in Plant methods, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Hannah Rees1Earlham Institute, Norwich Research Park, Norwich, NR4 7UG UK.
Susan Duncan1Earlham Institute, Norwich Research Park, Norwich, NR4 7UG UK.
Peter Gould2Institute of Integrative Biology, University of Liverpool, Crown Street, Liverpool, L69 7ZB UK.
Rachel Wells3John Innes Centre, Norwich Research Park, Norwich, NR4 7UH UK.
Mark Greenwood4Sainsbury Laboratory, University of Cambridge, Cambridge, CB2 1LR UK.
Thomas Brabbs1Earlham Institute, Norwich Research Park, Norwich, NR4 7UG UK.
Anthony Hall1Earlham Institute, Norwich Research Park, Norwich, NR4 7UG UK.ORCID 0000-0002-1806-020X

Funding

Biotechnology and Biological Sciences Research Council BBS/E/J/000PR9788
6 · The paper itself

Abstract

backgroundA robust circadian clock has been implicated in plant resilience, resource-use efficiency, competitive growth and yield. A huge number of physiological processes are under circadian control in plants including: responses to biotic and abiotic stresses; flowering time; plant metabolism; and mineral uptake. Understanding how the clock functions in crops such as

resultsIn this study, we describe the plant-specific optimisation of DF imaging to obtain reliable circadian phenotypes with the robustness and reproducibility to detect diverging periods between cultivars of the same species. We find that the age of plant material, light regime and temperature conditions all significantly effect DF rhythms and describe the optimal conditions for measuring robust rhythms in each species. We also show that sections of leaf can be used to obtain period estimates with improved throughput for larger sample size experiments.

conclusionsWe present an optimized protocol for high-throughput phenotyping of circadian period specific to two economically valuable crop plants. Application of this method revealed significant differences between the periods of several widely grown elite cultivars. This method also identified intriguing differential responses of circadian rhythms in

Indexed as

AgingCircadian periodD:DDelayed fluorescenceFree-running conditionsHexaploid wheatL:LOilseed rapeRhythm robustnessTemperature

Identifiers

PMID31139241
PMCPMC6530173

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.