Unknown

Dataset Information

0

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.

SUBMITTER: Loos M 

PROVIDER: S-EPMC4180925 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC4692246 | biostudies-literature
2020-08-13 | E-MTAB-7730 | biostudies-arrayexpress
| S-EPMC6709912 | biostudies-literature
| S-EPMC8570043 | biostudies-literature
| S-EPMC5688739 | biostudies-other
| S-EPMC3929556 | biostudies-literature
| S-EPMC7253061 | biostudies-literature
| S-EPMC2974199 | biostudies-literature
| S-EPMC4142977 | biostudies-literature