Sheltering Behavior and Locomotor Activity in 11 Genetically Diverse Common Inbred Mouse Strains Using Home-Cage Monitoring

Functional genetic analyses in mice rely on efficient and in-depth characterization of the behavioral spectrum. Automated home-cage observation can provide a systematic and efficient screening method to detect unexplored, novel behavioral phenotypes. Here, we analyzed high-throughput automated home-cage data using existing and novel concepts, to detect a plethora of genetic differences in spontaneous behavior in a panel of commonly used inbred strains (129S1/SvImJ, A/J, C3H/HeJ, C57BL/6J, BALB/cJ, DBA/2J, NOD/LtJ, FVB/NJ, WSB/EiJ, PWK/PhJ and CAST/EiJ). Continuous video-tracking observations of sheltering behavior and locomotor activity were segmented into distinguishable behavioral elements, and studied at different time scales, yielding a set of 115 behavioral parameters of which 105 showed highly significant strain differences. This set of 115 parameters was highly dimensional; principal component analysis identified 26 orthogonal components with eigenvalues above one. Especially novel parameters of sheltering behavior and parameters describing aspects of motion of the mouse in the home-cage showed high genetic effect sizes. Multi-day habituation curves and patterns of behavior surrounding dark/light phase transitions showed striking strain differences, albeit with lower genetic effect sizes. This spontaneous home-cage behavior study demonstrates high dimensionality, with a strong genetic contribution to specific sets of behavioral measures. Importantly, spontaneous home-cage behavior analysis detects genetic effects that cannot be studied in conventional behavioral tests, showing that the inclusion of a few days of undisturbed, labor extensive home-cage assessment may greatly aid gene function analyses and drug target discovery.

小鼠的功能遗传学研究，有赖于对其行为谱进行高效且深入的表征。自动化笼养行为观测可提供一套系统且高效的筛选手段，用于发现尚未被探索过的新型行为表型。本研究借助既有与全新的分析框架，对高通量自动化笼养行为数据开展分析，以在一组常用近交品系（129S1/SvImJ、A/J、C3H/HeJ、C57BL/6J、BALB/cJ、DBA/2J、NOD/LtJ、FVB/NJ、WSB/EiJ、PWK/PhJ及CAST/EiJ）中，检测自发行为层面的大量遗传差异。研究将对小鼠躲蔽行为与运动活性的连续视频追踪观测结果分割为可区分的行为单元，并在不同时间尺度下展开分析，最终得到115项行为参数，其中105项均呈现出极显著的品系差异。该115项参数构成的数据集具有极高维度；通过主成分分析（Principal Component Analysis），可识别出26个特征值大于1的正交分量。尤为值得注意的是，躲蔽行为的新型参数与描述小鼠笼内运动特征的参数，均展现出较高的遗传效应量。多日习惯化曲线以及围绕明暗周期转换的行为模式，同样呈现出显著的品系差异，不过其遗传效应量相对较低。本项自发笼养行为研究表明，该数据集具有高度维度特征，且特定行为指标体系受到显著的遗传调控。值得注意的是，自发笼养行为分析可检测到传统行为实验无法观测到的遗传效应，这表明纳入数天无干扰且需耗费大量人力的笼养评估环节，可极大助力基因功能研究与药物靶点发现。