Extensive characterization of a Williams Syndrome murine model showsGtf2ird1-mediated rescue of select sensorimotor tasks, but no effect on enhanced social behavior

Abstract

Williams Syndrome is a rare neurodevelopmental disorder exhibiting cognitive and behavioral abnormalities, including increased social motivation, risk of anxiety and specific phobias along with perturbed motor function. Williams Syndrome is caused by a microdeletion of 26-28 genes on chromosome 7, including GTF2IRD1, which encodes a transcription factor suggested to play a role in the behavioral profile of Williams Syndrome. Duplications of the full region also lead to frequent autism diagnosis, social phobias, and language delay. Thus, genes in the region appear to regulate social motivation in a dose-sensitive manner. A "Complete Deletion" mouse, heterozygously eliminating the syntenic Williams Syndrome region, has been deeply characterized for cardiac phenotypes, but direct measures of social motivation have not been assessed. Furthermore, the role of Gtf2ird1 in these behaviors has not been addressed in a relevant genetic context. Here, we have generated a mouse overexpressing Gtf2ird1, which can be used both to model duplication of this gene alone and to rescue Gtf2ird1 expression in the Complete Deletion mice. Using a comprehensive behavioral pipeline and direct measures of social motivation, we provide evidence that the Williams Syndrome Critical Region regulates social motivation along with motor and anxiety phenotypes, but that Gtf2ird1 complementation is not sufficient to rescue most of these traits, and duplication does not decrease social motivation. However, Gtf2ird1 complementation does rescue light-aversive behavior and performance on select sensorimotor tasks, perhaps indicating a role for this gene in sensory processing or integration.

Characterization of early markers of disease progression in the mouse model of Mucopolysaccharidosis IIIB

“…To process the videos, we used pose estimation software (DeepLabCut, version 2.2.1) to track body parts in space and time [37,38], building upon a previously built model [39]. Speci cally, we labeled 50 frames taken from 60 videos plus an additional 1700 frames of closely interacting animals, and 95% were used for training.…”

“…Training videos were annotated for attack behavior using the SimBA eventlogger using 180 annotated behavior les, downloaded from https://osf.io/tmu6y/ in addition to four inhouse annotated videos. All training les were annotated according to de nitions found in the simBA preprint [39,40]. Random forest classi ers were trained using default hyperparameters, and classi er performances were evaluated.…”