Generation and analysis of new mouse models to determine novel therapeutic targets for Down syndrome-associated cognitive deficits

Roswell Park Cancer Institute Corp, Buffalo NY

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Abstract

In the United States, Down syndrome occurs in approximately one in every 691 newborns and presents with a constellation of clinical manifestations. It results from human trisomy 21, the most common chromosomal abnormality associated with intellectual disabilities. Currently, there are no effective treatments for the intellectual disabilities linked to Down syndrome, underscoring the urgent need for innovative strategies to develop therapeutic interventions. The mouse remains the premier model organism for studying Down syndrome due to the presence of highly conserved orthologous regions between human chromosome 21 and three mouse genomic segments located on chromosomes 10, 16, and 17. A prevailing hypothesis in Down syndrome research posits that its phenotypes may be causally linked to dosage increases of genes located on human chromosome 21. In line with this hypothesis, extensive efforts have focused on generating and analyzing mouse models that carry an extra copy of these orthologous regions—typically achieved by duplicating the corresponding segments in the mouse genome. These duplication models are often combined with mice carrying targeted deletions of smaller genomic intervals within the duplicated regions to help identify critical dosage-sensitive loci. Progress in this field has been greatly accelerated by advances in Cre/loxP-mediated chromosome engineering technology. To generate long-range chromosomal duplications and deletions in mice via Cre/loxP-mediated recombination, two independent gene targeting events must be performed in mouse embryonic stem cells, followed by Cre-mediated recombination. To support this process, several genetic cassettes are employed, including those encoding antibiotic resistance. In this supplement project, we aim to re-examine an underexplored area of knowledge related to chromosome engineering technology. The success of our efforts will have significant implications for Down syndrome research and broader applications in genetic modeling and analysis.