Sheltering behavior and locomotor activity in 11 genetically diverse common inbred mouse strains using home-cage monitoring

Abstract

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.

Figure 1. Segmentation of move, arrest and sheltering behavior.

a) The distance moved by the center of gravity of a mouse during four 20 s segments is plotted, exemplifying arrest (red) and move (blue) segments. b) The length (log₂ transformed) of all move segments during 3 days was calculated for each individual mouse, and strain averages were plotted as a histogram. The inset shows how, for a representative C57BL/6J mouse, 2 different classes of moving segments could be dissociated by the intersection of 2 Gaussians that were fitted to the distance distribution of moving segments. c) The duration (log₂ transformed) of all arrest segments durations during 3 days was calculated for each individual mouse, and strain averages were plotted as a histogram. The inset shows how, for a representative C57BL/6J mouse, brief and long arrest segments were defined by an arbitrary threshold at the 90^th percentile of arrest durations. d) Visualizing a segmented track shows that short movements and long arrest occur in feeding and drinking zones. Brief arrests occur in between two long move segments, as well as in between short movements. Significant strain differences were observed in move and arrest measures, such as the e) long movement threshold f) long movement maximum velocity g) long arrest threshold and h) mean long arrest duration during the third dark phase. i) The duration (log₂ transformed) of each shelter visit during 3 days was recorded for each individual mouse and strain averages were plotted as a histogram. The inset shows how, for a representative C57BL/6J mouse, the shelter visit distribution can be approximated by fitting 3 Gaussian curves. The intercept between the 2^nd and 3^rd Gaussian was taken as individually determined threshold to recognize long shelter visits. To separate brief shelter visits from other shelter visit classes a cut off duration was defined at the 90^th percentile of the first fitted Gaussian. Strain differences were detected in sheltering measures, such as the j) long (left axis) and short (right axis) shelter visit threshold, k) cumulative long shelter visit duration per 24-hour (grey part of bars represents dark phase) and l) the mean long visit duration.

Figure 2. Activity bouts.

Strain differences were observed in activity bout characteristics, such as a) the mean duration of an activity bout during the dark phase and b) the number of activity bouts during the dark phase and c) the number of jumps onto the shelter.

Figure 3. Strain-specific patterns of home-cage activity.

During the three days in the home-cage environment, the strains showed different patterns with respect to multiday habituation (different line colors representing different days), differences between the proportions of activity during the dark (grey background) versus light (white background) phase, changes in activity during the hours surrounding the dark/light phase transitions.

Figure 4. Habituation during the first three days and the effect of Light/Dark phase.

a–b) The habituation effect across three days, in terms of the fold change from day 1 towards day 3 is plotted for dark (a) and light (b) phase. c) All strains have an activity duration DarkLight index above 0.5, i.e. representing more activity during the dark phase, however, substantial strain differences in this index were found.

Figure 5. Anticipation of – and response to – phase transitions.

Activity patterns were analyzed in terms of the change (slope) in the proportion of time active (activity proportion) in the few hours preceding and following the shift in light phase, and defined as the a) anticipation of the light phase, b) response to the start of the light phase, c) anticipation of the dark phase, d) response to the start of the dark phase. Each of these four slopes (i.e. change in activity proportion) showed significant strain differences (e–h).

Figure 6. Genetic influences on spontaneous home-cage behavior.

a) A histogram of the number of pairwise correlations among 115 parameters, with a particular shared genetic variance. b) The genetic effect size for each of the 115 parameter (bullets, with 20 key parameters grey filled) was calculated, and grouped per behavioral domain. The vertical mark represents the average genetic effect size of a category.