The proposed project, Rapid, cost-effective whole genome screening tools for cryptic inversions and translocations, will advance a genomic approach to precision medicine, enabling the discovery of disease- causing genomic structural variations and reducing the risks associated with clinical gene editing. Structural variations cause a wide range of diseases from rare diseases to cancers, and can be precise and definitive biomarkers. Also, because variations arise from the miss-repair of DNA strand breaks, off-target structural variations are a high-risk byproduct whenever a genome is edited, as in CRISPR-Cas9 approaches to curing human diseases. For these reasons, comprehensive detection of structural variations is a necessary step toward understanding, diagnosing and ultimately precisely treating genetic diseases. However, our collaborations with well-respected sequencing centers, and the experience of our partners and customers, confirms that structural variations such as inversions and translocations can be difficult to discover or even detect with NGS, genomic arrays, or any technique that relies on pooled DNA and a bioinformatic interpretation of data. In particular, detection of structural rearrangements that vary from cell to cell, occur in a minority of the cell population, or are confounded by other mutations and aberrations in the same cell, will benefit from an approach that directly reads the genome structure in many individual cells instead of algorithmically calculating a structure from pooled DNA or even the DNA of a single cell. Directional Genomic Hybridization is our hybrid cytogenetic/genomic platform for directly reading the structure of a genome in individual cells by analyzing chromatid paint data. dGH is capable of resolving very small inversions and translocations and easily identifies variable, rare, low occurrence and multiple structural rearrangements in individual cells. In a cytogenetic format, dGH is a commercial technique which we and our customers have applied across a range of applications from dosimetry to rare diseases to oncology. Reaching the full potential of dGH to discover and detect structural rearrangements, however, requires applications to larger libraries and larger numbers of cells than can be supported by a traditional cytogenetic approach. The goal of this FastTrack SBIR is to provide high-resolution structural rearrangement data to researchers who need to screen larger libraries of samples (oncology), investigate a very diverse patient population (rare diseases) or assay very large numbers of cells for complex rearrangements (gene editing). To accomplish this, KromaTiD proposes development of an automated, full genome dGH screening method comprised of high-density chromatid paints and image processing software. This novel method will detect inversions and translocations smaller than 10 kb and will be applicable to screening both very large numbers of samples and large numbers of cells in individual samples, making the discovery and detection of even the most complex structural variations routine, robust and economical.
Public Health Relevance Statement: PROJECT NARRATIVE Modern genomics demands higher throughput, higher integrity, and improved resolution of structural variations for precision medicine applications including discovery of disease drivers and control of off-target effects in gene editing systems such as CRISPR-Cas9. However, even with recent advances, structural variations such as translocations and inversions still cannot be definitively discovered or detected in complex cases involving random variations, variable breakpoints or multiple variations per cell. By making the cell-by-cell discovery and detection of structural variations routine and reliable in the most complex cases, this project--Rapid, Cost- Effective Whole Genome Screening Tools for Cryptic Inversions and Translocations--will enable a deeper understanding of the roots of human diseases, provide for the precision diagnosis of genetic diseases, and allow for the control of off-target effects in clinical gene editing systems.
NIH Spending Category: Bioengineering; Biotechnology; Clinical Research; Genetics; Human Genome; Precision Medicine; Prevention
Project Terms: Algorithms; base; Bioinformatics; Biological Assay; Biological Markers; Biomedical Research; Cell Count; Cell Line; Cells; Chromatids; Chromosomal Rearrangement; Clinical; clinically relevant; Collaborations; commercial application; Complex; Computer software; cost effective; CRISPR/Cas technology; Cytogenetics; Data; Data Analyses; density; design; Detection; Development; Diagnosis; Disease; disease diagnosis; disorder risk; DNA; DNA Repair; DNA strand break; dog genome; dosimetry; experience; Funding; Gene Targeting; Genes; Genetic Diseases; genetic disorder diagnosis; Genome; genome wide screen; Genomic approach; Genomic Hybridizations; genomic platform; Genomics; Goals; Government; high risk; Human; human disease; Human Genome; Hybrids; Image; Image Analysis; image processing; improved; Individual; Investigation; Knowledge; Libraries; Location; Longitudinal Studies; Low Prevalence; Malignant neoplasm of lung; Malignant Neoplasms; Medical; Methods; Minority; Modernization; Molecular; Monitor; mouse genome; Mutation; next generation; next generation sequencing; novel; Oncogenic; oncology; Output; Paint; patient population; Patients; Pharmacologic Substance; Phase; Plant Roots; Population; precision medicine; programs; Rare Diseases; Reading; research and development; Research Personnel; Resolution; Risk; Sampling; screening; Screening procedure; Sequence Homologs; Signal Transduction; Small Business Innovation Research Grant; structural genomics; Structure; System; Techniques; technological innovation; Technology; Therapeutic; tool; Variant; whole genome; Work
