Early development in mice: V. Sensorimotor development of four coisogenic mutant strains

Behavioral Phenotyping for Down Syndrome in Mice

Down syndrome (DS) is the most frequent genetic cause of intellectual disability, characterized by alterations in different behavioral symptom domains: neurodevelopment, motor behavior, and cognition. As mouse models have the potential to generate data regarding the neurological basis for the specific behavioral profile of DS, and may indicate pharmacological treatments with the potential to affect their behavioral phenotype, it is important to be able to assess disease-relevant behavioral traits in animal models in order to provide biological plausibility to the potential findings. The field is at a juncture that requires assessments that may effectively translate the findings acquired in mouse models to humans with DS. In this article, behavioral tests are described that are relevant to the domains affected in DS. A neurodevelopmental behavioral screen, the balance beam test, and the Multivariate Concentric Square Field test to assess multiple behavioral phenotypes and locomotion are described, discussing the ways to merge these findings to more fully understand cognitive strengths and weaknesses in this population. New directions for approaches to cognitive assessment in mice and humans are discussed. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Preweaning neurodevelopmental battery Basic Protocol 2: Balance beam Basic Protocol 3: Multivariate concentric square field test (MCSF).

Measuring Preweaning Sensorial and Motor Development in the Mouse

The immaturity at birth and the slowness of ontogenic processes in mice provide the opportunity to measure rates of development. We describe here 18 measures covering the sensorial and motor onset from birth to weaning. The measures are non-invasive, making a follow-up strategy possible. The first basic protocol indicates how to produce mice with known conceptional or chronological age, as the control of the age is a prerequisite to compare rates of development in groups of mice. The second basic protocol describes a set of methods for identifying the pups during a follow-up study. A third basic protocol describes testing newborn mice for the appearance of sensorial and motor abilities in a follow-up design. Taken together, the three protocols make possible the validation of potential murine models of interest for understanding human developmental disorders. © 2018 by John Wiley & Sons, Inc.

Sensory and motor development in mice: genes, environment and their interactions

Sensory and motor developmental tests were designed to characterize spontaneous mutations in rodents. These tests are currently used to investigate developmental abnormalities associated with gene overexpression or gene targeting in mice. Here, we present an overview of our studies focused on 15 tests designed to measure sensory and motor development from birth to weaning in mice. Psychometric characteristics and factorial structure of these measures are considered first. The genetic correlates of these measures obtained with neurological mutants and gene mapping are compared. As a general rule, the contribution of genotype to the phenotypic variance of sensory and motor measures of development is low, inviting exploration of other sources of variation. Results from ovary transplantation, embryo transfer and fostering methods indicate that different components of maternal environment (cytoplasmic, uterine or postnatal) contribute to the behavioral phenotype. Although more difficult to detect, interactions between genotype and environment are involved.

Preweanling sensorial and motor development in laboratory mice: quantitative trait loci mapping

Chromosomal mapping of genes linked with 19 measures of sensorial, motor, and body weight development were investigated. Chromosomal mapping is the first step towards gene identification. When a genomic region is shown to be linked to a trait, it is possible to select a reduced number of candidate genes that have been previously mapped on this region. The involvement of every gene can be individually tested either by molecular (transgenesis, homologous recombination) or traditional methods (congenicity). Mapping was performed using 389 males and females from two inbred strains of laboratory mice C57BL/6By and NZB/BlNJ, their reciprocal F1s and F2s. Thirty-six Quantitative Trait Loci (QTL) were mapped, 12 reached the 3.13 lod score, being thus considered as confirmed. These QTL were tentatively labeled: Cliff Drop Aversion (Cliff Qtl), Geotaxia (Geot Qtl), Vertical Clinging (VertCling Qtl), Bar Holding with the 4 paws (BH4P Qtl), Age at Eyelid Opening (Aeyo Qtl), Visual Placing (Vispl Qtl), Startle Response (Start Qtl1, Start Qtl2), Body Weight at Day 10 in Males pooled with Females (Bwefmd10 Qtl), and Body Weight at Day 30 in males (Bwemd30 Qtl). For the majority of the developmental measures, the QTL that were mapped contributed little to the phenotypic variance, even when mitochondrial DNA contribution was included: Righting Response (12.7%), Cliff Drop Aversion (10%), Crossed Extensor Response (18.1%), Geotaxia (16.2%), Bar Holding Response for 10 s (12.1%), Bar Holding Response with 4 paws (8.1%), Vertical Clinging (9.3%), Vertical Climbing (5%), Startle Response (21.2%), Eyelid Opening (14.6%), Visual Placing (22%), Body Weight at Day 10 (27%), Body Weight at Day 15 in Females (52.5%), Body Weight at Day 15 in Males (17%), Body Weight at Day 30 in Females (42%), and Body Weight at Day 30 in Males (48%). A factorial analysis of the correlations between the measures of development did not provide evidence of a general factor. A general genetic factor of development was also rejected because few common genetic correlates were discovered for the 19 measures of development (Body Weight at Days 15 and 30 in Females on Chromosome 2, Eyelid Opening and Body Weight at Day 10 on Chromosome 5 and mitochondrial genome for five measures). Co-identification of genes, the function of which were previously known thanks to newly discovered QTL, should help to explain the function of QTL. Present data help to highlight candidate regions including several genes that could be candidates for the QTL function. Large confidence intervals were obtained as usual from the F2 intercrossed population. More stringent methods are suggested for more efficient co-identification.