Literature DB >> 26688204

Computational classification of different wild-type zebrafish strains based on their variation in light-induced locomotor response.

Yuan Gao1, Gaonan Zhang2, Beth Jelfs1, Robert Carmer3, Prahatha Venkatraman2, Mohammad Ghadami1, Skye A Brown2, Chi Pui Pang4, Yuk Fai Leung5, Rosa H M Chan6, Mingzhi Zhang7.   

Abstract

Zebrafish larvae display a rapid and characteristic swimming behaviour after abrupt light onset or offset. This light-induced locomotor response (LLR) has been widely used for behavioural research and drug screening. However, the locomotor responses have long been shown to be different between different wild-type (WT) strains. Thus, it is critical to define the differences in the WT LLR to facilitate accurate interpretation of behavioural data. In this investigation, we used support vector machine (SVM) models to classify LLR data collected from three WT strains: AB, TL and TLAB (a hybrid of AB and TL), during early embryogenesis, from 3 to 9 days post-fertilisation (dpf). We analysed both the complete dataset and a subset of the data during the first 30after light change. This initial period of activity is substantially driven by vision, and is also known as the visual motor response (VMR). The analyses have resulted in three major conclusions: First, the LLR is different between the three WT strains, and at different developmental stages. Second, the distinguishable information in the VMR is comparable to, if not better than, the full dataset for classification purposes. Third, the distinguishable information of WT strains in the light-onset response differs from that in the light-offset response. While the classification accuracies were higher for the light-offset than light-onset response when using the complete LLR dataset, a reverse trend was observed when using a shorter VMR dataset. Together, our results indicate that one should use caution when extrapolating interpretations of LLR/VMR obtained from one WT strain to another.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Computational classification; Light-induced locomotor response; Support vector machines; Visual motor response; Zebrafish

Mesh:

Year:  2015        PMID: 26688204     DOI: 10.1016/j.compbiomed.2015.11.012

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  11 in total

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4.  Statistical Analysis of Zebrafish Locomotor Behaviour by Generalized Linear Mixed Models.

Authors:  Yiwen Liu; Ping Ma; Paige A Cassidy; Robert Carmer; Gaonan Zhang; Prahatha Venkatraman; Skye A Brown; Chi Pui Pang; Wenxuan Zhong; Mingzhi Zhang; Yuk Fai Leung
Journal:  Sci Rep       Date:  2017-06-07       Impact factor: 4.379

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Journal:  PLoS One       Date:  2017-04-18       Impact factor: 3.240

6.  C2orf71a/pcare1 is important for photoreceptor outer segment morphogenesis and visual function in zebrafish.

Authors:  Julio C Corral-Serrano; Muriël Messchaert; Margo Dona; Theo A Peters; Leonie M Kamminga; Erwin van Wijk; Rob W J Collin
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7.  Normalization of large-scale behavioural data collected from zebrafish.

Authors:  Rui Xie; Mengrui Zhang; Prahatha Venkatraman; Xinlian Zhang; Gaonan Zhang; Robert Carmer; Skylar A Kantola; Chi Pui Pang; Ping Ma; Mingzhi Zhang; Wenxuan Zhong; Yuk Fai Leung
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8.  Drug screening with zebrafish visual behavior identifies carvedilol as a potential treatment for an autosomal dominant form of retinitis pigmentosa.

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Journal:  Sci Rep       Date:  2021-06-01       Impact factor: 4.379

9.  Light regimes differentially affect baseline transcript abundance of stress-axis and (neuro)development-related genes in zebrafish (Danio rerio, Hamilton 1822) AB and TL larvae.

Authors:  Ruud van den Bos; Jan Zethof; Gert Flik; Marnix Gorissen
Journal:  Biol Open       Date:  2017-11-15       Impact factor: 2.422

10.  Emergence of consistent intra-individual locomotor patterns during zebrafish development.

Authors:  Jennifer A Fitzgerald; Krishna Tulasi Kirla; Carl P Zinner; Colette M Vom Berg
Journal:  Sci Rep       Date:  2019-09-20       Impact factor: 4.379

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