The rapid growth of systems biology approaches in preclinical research, such as whole-genome sequencing and genome editing, has contributed to the need for high-throughput and reproducible phenotypic screening of genetically engineered animals. The relationship between genotype and phenotype is complex: targeted genes of interest interact with background genes and unknown mutations, as well as epigenetic and environmental factors, to exert specific or collective effects on health and behavior.

The availability of different strains and a wealth of genetic and phenotyping resources make the laboratory mouse an excellent genetic model. However, despite collective awareness and improvements in phenotyping pipelines and procedures, reproducibility and translatability remain constant challenges in rodent phenotypic screening. Due to time, labor, and cost constraints, mutant alleles are typically studied in a single inbred strain and sex or during limited time points. Furthermore, trained technicians perform traditional behavioral assays outside of the home cage, where inadvertent human impact or environmental factors can provide additional sources of variability. In this study, we investigate how continuous monitoring of animals in their home cage using automated biomarkers can reveal different longitudinal patterns of behavior among four commonly used inbred mouse strains.