The sequencing of individual human genomes may soon be routine in certain clinical contexts - for example, to diagnose suspected Mendelian disorders in pediatric patients, or to guide therapeutic decisions in cancer treatment. However, even as its cost plummets to $1,000 or less, the value of a personal genome will remain highly constrained by the poor interpretability of individual genetic variants. For example, although BRCA1 and BRCA2 are clinically actionable when loss-of-function mutations are present, and although both genes have been sequenced in >50,000 patients over the past decade, the result returned to patients is often still variant of uncertain significance. This challenge will profoudly deepen as clinical sequencing accelerates and as the list of clinically actionable genes grows. To address this, we propose to develop a novel approach for experimentally measuring the functional consequences of such variants of uncertain significance at an unprecedented scale, as well as innovative computational approaches for estimating the relative pathogenicity of any possible variant in the entire human genome. For clinically relevant genes, we will exploit massively parallel technologies for nucleic acid synthesis and sequencing towards a new paradigm for dissecting function at saturating resolution. The application of this paradigm will yield experimentally grounded predictions for the functional consequences of all possible single residue variants, thereby informing the interpretation of variants newly observed in patients. For the remainder of the human genome, we will develop a framework for integrating a proliferating diversity of coding and non-coding annotations to a single metric. We will then calculate this metric of relative pathogenicity for all possible single nucleotide variants in the human genome. We anticipate that these methods and the resulting pre-computations of pathogenicity will broadly enable the interpretation of human genome sequences in diverse clinical and research settings.
As we enter an era of ?personalized medicine?, the sequencing of individual human genomes will be increasingly important to public health, contributing towards the unraveling of the genetic basis of human disease and serving a growing role in patient care. However, the interpretation of genetic ?variants of uncertain significance? represents a fundamental obstacle for the field. This project will develop several innovative approaches for estimating the consequences of all possible genetic variants of clinically relevant genes. The resulting ?pre-computations? of pathogenicity will broadly enable the interpretation of human genome sequences in diverse clinical and research settings.
| Cao, Junyue; Cusanovich, Darren A; Ramani, Vijay et al. (2018) Joint profiling of chromatin accessibility and gene expression in thousands of single cells. Science 361:1380-1385 |
| Hill, Andrew J; McFaline-Figueroa, José L; Starita, Lea M et al. (2018) On the design of CRISPR-based single-cell molecular screens. Nat Methods 15:271-274 |
| Matreyek, Kenneth A; Starita, Lea M; Stephany, Jason J et al. (2018) Multiplex assessment of protein variant abundance by massively parallel sequencing. Nat Genet 50:874-882 |
| Cusanovich, Darren A; Reddington, James P; Garfield, David A et al. (2018) The cis-regulatory dynamics of embryonic development at single-cell resolution. Nature 555:538-542 |
| Starita, Lea M; Islam, Muhtadi M; Banerjee, Tapahsama et al. (2018) A Multiplex Homology-Directed DNA Repair Assay Reveals the Impact of More Than 1,000 BRCA1 Missense Substitution Variants on Protein Function. Am J Hum Genet 103:498-508 |
| Findlay, Gregory M; Daza, Riza M; Martin, Beth et al. (2018) Accurate classification of BRCA1 variants with saturation genome editing. Nature 562:217-222 |
| Raj, Bushra; Wagner, Daniel E; McKenna, Aaron et al. (2018) Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain. Nat Biotechnol 36:442-450 |
| Cusanovich, Darren A; Hill, Andrew J; Aghamirzaie, Delasa et al. (2018) A Single-Cell Atlas of In Vivo Mammalian Chromatin Accessibility. Cell 174:1309-1324.e18 |
| Gray, Vanessa E; Hause, Ronald J; Luebeck, Jens et al. (2018) Quantitative Missense Variant Effect Prediction Using Large-Scale Mutagenesis Data. Cell Syst 6:116-124.e3 |
| McKenna, Aaron; Shendure, Jay (2018) FlashFry: a fast and flexible tool for large-scale CRISPR target design. BMC Biol 16:74 |
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