Genetic dissection of Down syndrome-associated congenital heart defects using a new mouse mapping panel
- The Francis Crick Institute, United Kingdom
- UCL Institute of Neurology, United Kingdom
Abstract
Down syndrome (DS), caused by trisomy of human chromosome 21 (Hsa21), is the most common cause of congenital heart defects (CHD), yet the genetic and mechanistic causes of these defects remain unknown. To identify dosage-sensitive genes that cause DS phenotypes, including CHD, we used chromosome engineering to generate a mapping panel of 7 mouse strains with partial trisomies of regions of mouse chromosome 16 orthologous to Hsa21. Using high-resolution episcopic microscopy and three-dimensional modeling we show that these strains accurately model DS CHD. Systematic analysis of the 7 strains identified a minimal critical region sufficient to cause CHD when present in 3 copies, and showed that it contained at least two dosage-sensitive loci. Furthermore, these new strains model a specific subtype of atrio-ventricular septal defects with exclusive ventricular shunting and demonstrate that, contrary to current hypotheses, these CHD are not due to failure in formation of the dorsal mesenchymal protrusion.
Article and author information
Author details
Reviewing Editor
- Margaret Buckingham, Institut Pasteur, France
Ethics
Animal experimentation: All animal work was carried out under a Project Licence granted by the UK Home Office.
Version history
- Received: September 16, 2015
- Accepted: January 4, 2016
- Accepted Manuscript published: January 14, 2016 (version 1)
- Version of Record published: February 12, 2016 (version 2)
- Version of Record updated: July 21, 2020 (version 3)
Copyright
© 2016, Lana-Elola et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Genetic dissection of Down syndrome-associated congenital heart defects using a new mouse mapping panel
eLife 5:e11614.
https://doi.org/10.7554/eLife.11614
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