Automated analysis of long-term grooming behavior in Drosophila using a k-nearest neighbors classifier

Bing Qiao, Chiyuan Li, Victoria W. Allen, Mimi Shirasu-Hiza, Sheyum Syed

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Despite being pervasive, the control of programmed grooming is poorly understood. We addressed this gap by developing a high-throughput platform that allows long-term detection of grooming in Drosophila melanogaster. In our method, a k-nearest neighbors algorithm automatically classifies fly behavior and finds grooming events with over 90% accuracy in diverse genotypes. Our data show that flies spend ~13% of their waking time grooming, driven largely by two major internal programs. One of these programs regulates the timing of grooming and involves the core circadian clock components cycle, clock, and period. The second program regulates the duration of grooming and, while dependent on cycle and clock, appears to be independent of period. This emerging dual control model in which one program controls timing and another controls duration, resembles the two-process regulatory model of sleep. Together, our quantitative approach presents the opportunity for further dissection of mechanisms controlling long-term grooming in Drosophila.

Original languageEnglish (US)
JournaleLife
Volume7
DOIs
StatePublished - Feb 27 2018

Fingerprint

Grooming
Drosophila
Classifiers
Clocks
Dissection
Diptera
Throughput
Circadian Clocks
Drosophila melanogaster
Sleep
Genotype

Keywords

  • circadian rhythm
  • computational biology
  • D. melanogaster
  • Drosophila
  • ethogram
  • grooming
  • neuroscience
  • period
  • systems biology
  • two-process

ASJC Scopus subject areas

  • Neuroscience(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)

Cite this

Automated analysis of long-term grooming behavior in Drosophila using a k-nearest neighbors classifier. / Qiao, Bing; Li, Chiyuan; Allen, Victoria W.; Shirasu-Hiza, Mimi; Syed, Sheyum.

In: eLife, Vol. 7, 27.02.2018.

Research output: Contribution to journalArticle

Qiao, Bing ; Li, Chiyuan ; Allen, Victoria W. ; Shirasu-Hiza, Mimi ; Syed, Sheyum. / Automated analysis of long-term grooming behavior in Drosophila using a k-nearest neighbors classifier. In: eLife. 2018 ; Vol. 7.
@article{9d5d12ed37b44e8cae8134b5e1728e8e,
title = "Automated analysis of long-term grooming behavior in Drosophila using a k-nearest neighbors classifier",
abstract = "Despite being pervasive, the control of programmed grooming is poorly understood. We addressed this gap by developing a high-throughput platform that allows long-term detection of grooming in Drosophila melanogaster. In our method, a k-nearest neighbors algorithm automatically classifies fly behavior and finds grooming events with over 90{\%} accuracy in diverse genotypes. Our data show that flies spend ~13{\%} of their waking time grooming, driven largely by two major internal programs. One of these programs regulates the timing of grooming and involves the core circadian clock components cycle, clock, and period. The second program regulates the duration of grooming and, while dependent on cycle and clock, appears to be independent of period. This emerging dual control model in which one program controls timing and another controls duration, resembles the two-process regulatory model of sleep. Together, our quantitative approach presents the opportunity for further dissection of mechanisms controlling long-term grooming in Drosophila.",
keywords = "circadian rhythm, computational biology, D. melanogaster, Drosophila, ethogram, grooming, neuroscience, period, systems biology, two-process",
author = "Bing Qiao and Chiyuan Li and Allen, {Victoria W.} and Mimi Shirasu-Hiza and Sheyum Syed",
year = "2018",
month = "2",
day = "27",
doi = "10.7554/eLife.34497",
language = "English (US)",
volume = "7",
journal = "eLife",
issn = "2050-084X",
publisher = "eLife Sciences Publications",

}

TY - JOUR

T1 - Automated analysis of long-term grooming behavior in Drosophila using a k-nearest neighbors classifier

AU - Qiao, Bing

AU - Li, Chiyuan

AU - Allen, Victoria W.

AU - Shirasu-Hiza, Mimi

AU - Syed, Sheyum

PY - 2018/2/27

Y1 - 2018/2/27

N2 - Despite being pervasive, the control of programmed grooming is poorly understood. We addressed this gap by developing a high-throughput platform that allows long-term detection of grooming in Drosophila melanogaster. In our method, a k-nearest neighbors algorithm automatically classifies fly behavior and finds grooming events with over 90% accuracy in diverse genotypes. Our data show that flies spend ~13% of their waking time grooming, driven largely by two major internal programs. One of these programs regulates the timing of grooming and involves the core circadian clock components cycle, clock, and period. The second program regulates the duration of grooming and, while dependent on cycle and clock, appears to be independent of period. This emerging dual control model in which one program controls timing and another controls duration, resembles the two-process regulatory model of sleep. Together, our quantitative approach presents the opportunity for further dissection of mechanisms controlling long-term grooming in Drosophila.

AB - Despite being pervasive, the control of programmed grooming is poorly understood. We addressed this gap by developing a high-throughput platform that allows long-term detection of grooming in Drosophila melanogaster. In our method, a k-nearest neighbors algorithm automatically classifies fly behavior and finds grooming events with over 90% accuracy in diverse genotypes. Our data show that flies spend ~13% of their waking time grooming, driven largely by two major internal programs. One of these programs regulates the timing of grooming and involves the core circadian clock components cycle, clock, and period. The second program regulates the duration of grooming and, while dependent on cycle and clock, appears to be independent of period. This emerging dual control model in which one program controls timing and another controls duration, resembles the two-process regulatory model of sleep. Together, our quantitative approach presents the opportunity for further dissection of mechanisms controlling long-term grooming in Drosophila.

KW - circadian rhythm

KW - computational biology

KW - D. melanogaster

KW - Drosophila

KW - ethogram

KW - grooming

KW - neuroscience

KW - period

KW - systems biology

KW - two-process

UR - http://www.scopus.com/inward/record.url?scp=85058936902&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85058936902&partnerID=8YFLogxK

U2 - 10.7554/eLife.34497

DO - 10.7554/eLife.34497

M3 - Article

C2 - 29485401

AN - SCOPUS:85058936902

VL - 7

JO - eLife

JF - eLife

SN - 2050-084X

ER -