A benchmarked, high-efficiency prime editing platform for multiplexed dropout screening.

Prime editing installs precise edits into the genome with minimal unwanted byproducts, but low and variable editing efficiencies have complicated application of the approach to high-throughput functional genomics. Leveraging several recent advances, we assembled a prime editing platform capable of high-efficiency substitution editing across a set of engineered prime editing guide RNAs (epegRNAs) and corresponding target sequences (80% median intended editing). Then, using a custom library of 240,000 epegRNAs targeting >17,000 codons with 175 different substitution types, we benchmarked our platform for functional interrogation of small substitution variants (1-3 nucleotides) targeted to essential genes. Resulting data identified negative growth phenotypes for nonsense mutations targeted to ~8,000 codons, and comparing those phenotypes to results from controls demonstrated high specificity. We also observed phenotypes for synonymous mutations that disrupted splice site motifs at 3' exon boundaries. Altogether, we establish and benchmark a high-throughput prime editing approach for functional characterization of genetic variants with simple readouts from multiplexed experiments.

Mapping the genetic landscape of DNA double-strand break repair.

Cells repair DNA double-strand breaks (DSBs) through a complex set of pathways critical for maintaining genomic integrity. To systematically map these pathways, we developed a high-throughput screening approach called Repair-seq that measures the effects of thousands of genetic perturbations on mutations introduced at targeted DNA lesions. Using Repair-seq, we profiled DSB repair products induced by two programmable nucleases (Cas9 and Cas12a) in the presence or absence of oligonucleotides for homology-directed repair (HDR) after knockdown of 476 genes involved in DSB repair or associated processes. The resulting data enabled principled, data-driven inference of DSB end joining and HDR pathways. Systematic interrogation of this data uncovered unexpected relationships among DSB repair genes and demonstrated that repair outcomes with superficially similar sequence architectures can have markedly different genetic dependencies. This work provides a foundation for mapping DNA repair pathways and for optimizing genome editing across diverse modalities.

Prime Editing: Precision Genome Editing by Reverse Transcription.

Genome editing is a method for making targeted sequence changes to the genomes of living cells. Prime editing, recently reported by Anzalone et al. (2019), is a new technology that uses reverse transcription to "write" programmed sequence changes into genomic DNA and thus promises significant technical advances.

Conservation of cell-intrinsic immune responses in diverse nonhuman primate species.

Differences in immune responses across species can contribute to the varying permissivity of species to the same viral pathogen. Understanding how our closest evolutionary relatives, nonhuman primates (NHPs), confront pathogens and how these responses have evolved over time could shed light on host range barriers, especially for zoonotic infections. Here, we analyzed cell-intrinsic immunity of primary cells from the broadest panel of NHP species interrogated to date, including humans, great apes, and Old and New World monkeys. Our analysis of their transcriptomes after poly(I:C) transfection revealed conservation in the functional consequences of their response. In mapping reads to either the human or the species-specific genomes, we observed that with the current state of NHP annotations, the percent of reads assigned to a genetic feature was largely similar regardless of the method. Together, these data provide a baseline for the cell-intrinsic responses elicited by a potent immune stimulus across multiple NHP donors, including endangered species, and serve as a resource for refining and furthering the existing annotations of NHP genomes.

Pathway networks generated from human disease phenome.

BACKGROUND: Understanding the effect of human genetic variations on disease can provide insight into phenotype-genotype relationships, and has great potential for improving the effectiveness of personalized medicine. While some genetic markers linked to disease susceptibility have been identified, a large number are still unknown. In this paper, we propose a pathway-based approach to extend disease-variant associations and find new molecular connections between genetic mutations and diseases. METHODS: We used a compilation of over 80,000 human genetic variants with known disease associations from databases including the Online Mendelian Inheritance in Man (OMIM), Clinical Variance database (ClinVar), Universal Protein Resource (UniProt), and Human Gene Mutation Database (HGMD). Furthermore, we used the Unified Medical Language System (UMLS) to normalize variant phenotype terminologies, mapping 87% of unique genetic variants to phenotypic disorder concepts. Lastly, variants were grouped by UMLS Medical Subject Heading (MeSH) identifiers to determine pathway enrichment in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. RESULTS: By linking KEGG pathways through underlying variant associations, we elucidated connections between the human genetic variant-based disease phenome and metabolic pathways, finding novel disease connections not otherwise detected through gene-level analysis. When looking at broader disease categories, our network analysis showed that large complex diseases, such as cancers, are highly linked by their common pathways. In addition, we found Cardiovascular Diseases and Skin and Connective Tissue Diseases to have the highest number of common pathways, among 35 significant main disease category (MeSH) pairings. CONCLUSIONS: This study constitutes an important contribution to extending disease-variant connections and new molecular links between diseases. Novel disease connections were made by disease-pathway associations not otherwise detected through single-gene analysis. For instance, we found that mutations in different genes associated to Noonan Syndrome and Essential Hypertension share a common pathway. This analysis also provides the foundation to build novel disease-drug networks through their underlying common metabolic pathways, thus enabling new diagnostic and therapeutic interventions.