Evidence map›Paper›PMID 29155762›Full record

ArticleJournal of visualized experiments : JoVE2017

High-throughput Analysis of Locomotor Behavior in the Drosophila Island Assay.

Ilse Eidhof, Michaela Fenckova, Dei M Elurbe, Bart van de Warrenburg, Anna Castells Nobau, Annette Schenck

Abstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Ataxia-associated DNA repair genes protect theFrontiers in neural circuits · 2023
    Article
  2. Article
  3. Behavior Individuality: A Focus onFrontiers in physiology · 2021
    Review
  4. The Journal of biological chemistry · 2020
    Article
  5. Article
  6. Article
  7. Feeding difficulties, a key feature of theDisease models & mechanisms · 2018
    Article
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

6 authors.

Ilse EidhofDepartment of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center.
Michaela FenckovaDepartment of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center.
Dei M ElurbeCentre for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center.
Bart van de WarrenburgDepartment of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center.
Anna Castells NobauDepartment of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center; Annacnobau@hotmail.com.
Annette SchenckDepartment of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center; Annette.Schenck@radboudumc.nl.

Funding

Resource Component: Acquisition, maintenance and distribution of Drosophila stocksP40OD018537 · OD · TRUSTEES OF INDIANA UNIVERSITY · PI Annette L. Parks · 2014 to 2026
$13.5M
NIH HHS P40 OD018537
6 · The paper itself

Abstract

Advances in next-generation sequencing technologies contribute to the identification of (candidate) disease genes for movement disorders and other neurological diseases at an increasing speed. However, little is known about the molecular mechanisms that underlie these disorders. The genetic, molecular, and behavioral toolbox of Drosophila melanogaster makes this model organism particularly useful to characterize new disease genes and mechanisms in a high-throughput manner. Nevertheless, high-throughput screens require efficient and reliable assays that, ideally, are cost-effective and allow for the automatized quantification of traits relevant to these disorders. The island assay is a cost-effective and easily set-up method to evaluate Drosophila locomotor behavior. In this assay, flies are thrown onto a platform from a fixed height. This induces an innate motor response that enables the flies to escape from the platform within seconds. At present, quantitative analyses of filmed island assays are done manually, which is a laborious undertaking, particularly when performing large screens. This manuscript describes the "Drosophila Island Assay" and "Island Assay Analysis" algorithms for high-throughput, automated data processing and quantification of island assay data. In the setup, a simple webcam connected to a laptop collects an image series of the platform while the assay is performed. The "Drosophila Island Assay" algorithm developed for the open-source software Fiji processes these image series and quantifies, for each experimental condition, the number of flies on the platform over time. The "Island Assay Analysis" script, compatible with the free software R, was developed to automatically process the obtained data and to calculate whether treatments/genotypes are statistically different. This greatly improves the efficiency of the island assay and makes it a powerful readout for basic locomotion and flight behavior. It can thus be applied to large screens investigating fly locomotor ability, Drosophila models of movement disorders, and drug efficacy.

Indexed as

AnimalsBehavior, AnimalDrosophilaHigh-Throughput Screening AssaysLocomotion

Identifiers

PMID29155762
PMCPMC5755321

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.