Approximately 20-30 million Americans are affected by Mendelian genetic disorders with broad clinical consequences including congenital heart disease, congenital bone diseases, inherited skin diseases, hereditary neurological disorders, hereditary cancers, and others. Over the last several years, high-throughput, whole-exome sequencing has been used for molecular diagnosis and as a research tool for discovery of new disease-causative gene(s). Since the first successful application of this technology six years ago, the fundamental genetic bases for over 100 Mendelian diseases have been identified. Despite these advances, the clinical yield for human Mendelian disease by whole-exome sequencing is less than 40%. In contrast to these clinical cases, the discovery of Mendelian disease genes in mice is powered by genetically defined inbred strain backgrounds, large consanguineous pedigrees for segregation analysis, and disease modeling through the use of exciting new CRISPR/Cas9 approaches and more traditional genetic engineering techniques. With these allied technologies, the application of whole-exome sequencing in recent years has increased the rate of mutation discovery in mouse by nearly ten-fold. Yet, the success rate for Mendelian disease gene discovery in the mouse is only slightly higher than 50 percent. Possible limitations of whole-exome sequencing for disease gene discovery in mouse include shortcomings of variant calling tools, insufficient data resources describing `normal' genome variation, and the likely existence of structural variants that escape detection by exome- sequencing. With the promise of exploring and surmounting these limitations, our long-term goal is to create genomic resources that will facilitate functionalization of naturally occurring variation by employing forward genetic discovery and reverse genetic validation. More specifically, the objectives of this project are to continue to tackle the problem of robust discovery and functional validation of variants that cause Mendelian disease phenotypes in mice with an emphasis on those variants that escape detection by exome sequencing. We will harness newly affordable, third-generation, long-read sequencing technologies for the discovery of structural variants (SVs); and further develop pipelines that integrate these new datatypes into a data-driven framework formouse variant interpretation and candidate gene prioritization that is available to the research community. Finally, we will take advantage of new high throughput in vivo, CRISPR-based engineering and phenotyping to prove disease-causation from among a subset of our most interesting and relevant candidate genes.

Public Health Relevance

High-throughput understanding cases mutation that applied illness DNA sequence analysis and mutation etection technologies are key processes for genetic illnesses and diagnosing them in the clinic. However, in a significant percentage of sequencing attempts fail to deliver a plausible disease gene. This research study is designed to refine detection approaches in mice where mutation discovery efforts are supported by allied approaches cannot reasonably be used for human studies. Once refined, the improved approaches can once again be clinically, translating into improved public health by providing a better understanding of human genetic and more efficient and accurate diagnosis for patients and families. d

National Institute of Health (NIH)
Office of The Director, National Institutes of Health (OD)
Resource-Related Research Projects (R24)
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Special Emphasis Panel (ZRG1)
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Mirochnitchenko, Oleg
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Jackson Laboratory
Bar Harbor
United States
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Peng, Yanyan; Shinde, Deepali N; Valencia, C Alexander et al. (2017) Biallelic mutations in the ferredoxin reductase gene cause novel mitochondriopathy with optic atrophy. Hum Mol Genet 26:4937-4950