A Functional Genomics Platform for the de novo Identification of Disease-relevant Alleles - PROJECT SUMMARY Deciphering the functional consequences of naturally occurring human genetic variation is critical to our understanding of human disease as well as to the advancement of precision medicine. The identification of loci that influence disease progression in human populations is not only important for identifying druggable targets, but also enables risk stratification approaches for the clinical management of disease. Unfortunately, practical and biological limitations to cohort-based association studies have restricted our ability to identify and mechanistically interrogate disease-relevant alleles, especially those that impact infectious diseases. As an example, despite repeated efforts over several decades, only a handful of human genetic variants have been linked to differences in Human Immunodeficiency Virus (HIV) pathogenesis, and these are only able to explain a small fraction of the observed clinical variation. One of these variants, a truncation in the HIV co-receptor CCR5, has been shown to provide resistance to HIV infection and is the basis for the only four cases of HIV cure achieved to date. Here, we propose to develop a new functional genomics platform for the engineering and functional phenotyping of naturally occurring genetic variants to enable de novo identification of disease-relevant alleles. Leveraging advances in gene editing technology, we seek to effectively recapitulate all known human genetic variation at a given locus in a single test tube of cells for rapid and cost-effective functional screening. As proof-of-principle, we aim to engineer and functionally classify the impact of all >1600 known naturally occurring CCR5 variants on: 1) CCR5 cell surface expression, 2) HIV-1 susceptibility, and 3) efficacy of the CCR5-targeting antiretroviral drug, Maraviroc. Using batched, tiled arrays of synthetic oligonucleotides, each variant will be cloned into a homology-directed repair template and pooled into an allelic variant library. This library will be delivered to a CCR5-haploid Jurkat cell line alongside CRISPR-Cas9 ribonucleoprotein complexes targeting CCR5 to generate knock-in, polyclonal pools of cells harboring distinct naturally occurring variants. These populations will be immunostained for CCR5, sorted, and subject to deep sequencing to identify variants impacting cell surface expression. Subsequently, cells will be subject to multiple rounds of HIV-1 infection and sorting to identify alleles with a protective phenotype. This same experiment will be done in the presence of the Maraviroc, selecting for variants that escape antiretroviral activity of the drug. Genotype-phenotype relationships will be additionally monitored at the single cell level by droplet-assisted RNA-targeting single-cell sequencing (DART-seq) for added rigor. The most significantly impactful variants will be validated by targeted insertion into primary human T cells to determine their impact on HIV infection ex vivo. Altogether, this proposal seeks to provide an innovative, actionable approach for the identification and mapping of host factor determinants at single nucleotide resolution with broad implications not only for the development of new HIV treatment modalities, but for continued research on the role of host genetic variation in human disease.
