Jeffrey A. Hussmann

While prime editing enables precise sequence changes in DNA, cellular determinants of prime editing remain poorly understood. Using pooled CRISPRi screens, we discovered that DNA mismatch repair (MMR) impedes prime editing and promotes undesired indel byproducts. We developed PE4 and PE5 prime editing systems in which transient expression of an engineered MMR-inhibiting protein enhances the efficiency of substitution, small insertion, and small deletion prime edits by an average 7.7-fold and 2.0-fold compared to PE2 and PE3 systems, respectively, while improving edit/indel ratios by 3.4-fold in MMR-proficient cell types. Strategic installation of silent mutations near the intended edit can enhance prime editing outcomes by evading MMR. Prime editor protein optimization resulted in a PEmax architecture that enhances editing efficacy by 2.8-fold on average in HeLa cells. These findings enrich our understanding of prime editing and establish prime editing systems that show substantial improvement across 191 edits in seven mammalian cell types.

A central goal of genetics is to define the relationships between genotypes and phenotypes. High-content phenotypic screens such as Perturb-seq (CRISPR-based screens with single-cell RNA-sequencing readouts) enable massively parallel functional genomic mapping but, to date, have been used at limited scales. Here, we perform genome-scale Perturb-seq targeting all expressed genes with CRISPR interference (CRISPRi) across >2.5 million human cells. We use transcriptional phenotypes to predict the function of poorly characterized genes, uncovering new regulators of ribosome biogenesis (including CCDC86, ZNF236, and SPATA5L1), transcription (C7orf26), and mitochondrial respiration (TMEM242). In addition to assigning gene function, single-cell transcriptional phenotypes allow for in-depth dissection of complex cellular phenomena-from RNA processing to differentiation. We leverage this ability to systematically identify genetic drivers and consequences of aneuploidy and to discover an unanticipated layer of stress-specific regulation of the mitochondrial genome. Our information-rich genotype-phenotype map reveals a multidimensional portrait of gene and cellular function.

Ribosome-footprint profiling provides genome-wide snapshots of translation, but technical challenges can confound its analysis. Here, we use improved methods to obtain ribosome-footprint profiles and mRNA abundances that more faithfully reflect gene expression in Saccharomyces cerevisiae. Our results support proposals that both the beginning of coding regions and codons matching rare tRNAs are more slowly translated. They also indicate that emergent polypeptides with as few as three basic residues within a ten-residue window tend to slow translation. With the improved mRNA measurements, the variation attributable to translational control in exponentially growing yeast was less than previously reported, and most of this variation could be predicted with a simple model that considered mRNA abundance, upstream open reading frames, cap-proximal structure and nucleotide composition, and lengths of the coding and 5' UTRs. Collectively, our results provide a framework for executing and interpreting ribosome-profiling studies and reveal key features of translational control in yeast.

A major limitation of high-throughput DNA sequencing is the high rate of erroneous base calls produced. For instance, Illumina sequencing machines produce errors at a rate of ~0.1-1 × 10(-2) per base sequenced. These technologies typically produce billions of base calls per experiment, translating to millions of errors. We have developed a unique library preparation strategy, "circle sequencing," which allows for robust downstream computational correction of these errors. In this strategy, DNA templates are circularized, copied multiple times in tandem with a rolling circle polymerase, and then sequenced on any high-throughput sequencing machine. Each read produced is computationally processed to obtain a consensus sequence of all linked copies of the original molecule. Physically linking the copies ensures that each copy is independently derived from the original molecule and allows for efficient formation of consensus sequences. The circle-sequencing protocol precedes standard library preparations and is therefore suitable for a broad range of sequencing applications. We tested our method using the Illumina MiSeq platform and obtained errors in our processed sequencing reads at a rate as low as 7.6 × 10(-6) per base sequenced, dramatically improving the error rate of Illumina sequencing and putting error on par with low-throughput, but highly accurate, Sanger sequencing. Circle sequencing also had substantially higher efficiency and lower cost than existing barcode-based schemes for correcting sequencing errors.