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Autor(en) / Beteiligte
Titel
0009 AUTOMATED TRACKING AND QUANTITATIVE GENETIC ANALYSIS OF REST AND ACTIVITY BEHAVIOR IN DROSOPHILA LARVAE
Ist Teil von
  • Sleep (New York, N.Y.), 2017-04, Vol.40 (suppl_1), p.A3-A4
Ort / Verlag
US: Oxford University Press
Erscheinungsjahr
2017
Link zum Volltext
Quelle
Oxford Journals 2020 Medicine
Beschreibungen/Notizen
  • Abstract Introduction: Drosophila melanogaster is an ideal model system for the study of sleep as it exhibits the characteristics of mammalian sleep and is amenable to systems genetics approaches. Although many studies have identified novel genetic and pharmacological features of sleep in adults, little is known about rest and activity during the early developmental stages of the fly. Specifically, it is not known whether larval rest and activity behaviors are correlated with sleep in the adult stage. Methods: We used video monitoring and automated machine vision tracking to continuously measure kinematic parameters in third instar larvae during the first four hours of the dark cycle. Our system tracked and quantified movement in 12 larvae at a time. From the tracking data, we constructed behavioral ethograms of individual larvae and calculated total rest time, numbers of rest bouts, average rest bout length, average velocity, and distance traveled. We applied this tracking method to larvae from the Drosophila Genetic Reference Panel (DGRP) in order associate polymorphic variants with underlying larval rest and activity traits. Results: Preliminary results revealed significant genetic variation in the DGRP for all activity and rest measurements. Larvae were very active during the first four hours of the night and had very short pauses in activity. Some larvae were far more active than others, and explored their chamber to a greater extent during the monitoring period. Larvae had high numbers of rest and activity bouts which differed profoundly from the consolidated periods of rest shown in adult flies; yet some behaviors were partially correlated. Conclusion: Support (If Any):
Sprache
Englisch
Identifikatoren
ISSN: 0161-8105
eISSN: 1550-9109
DOI: 10.1093/sleepj/zsx050.008
Titel-ID: cdi_proquest_journals_2503443744

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