Base editing rescue of spinal muscular atrophy in cells and in mice.

Spinal muscular atrophy (SMA), the leading genetic cause of infant mortality, arises from survival motor neuron (SMN) protein insufficiency resulting from SMN1 loss. Approved therapies circumvent endogenous SMN regulation and require repeated dosing or may wane. We describe genome editing of SMN2, an insufficient copy of SMN1 harboring a C6>T mutation, to permanently restore SMN protein levels and rescue SMA phenotypes. We used nucleases or base editors to modify five SMN2 regulatory regions. Base editing converted SMN2 T6>C, restoring SMN protein levels to wild type. Adeno-associated virus serotype 9-mediated base editor delivery in Δ7SMA mice yielded 87% average T6>C conversion, improved motor function, and extended average life span, which was enhanced by one-time base editor and nusinersen coadministration (111 versus 17 days untreated). These findings demonstrate the potential of a one-time base editing treatment for SMA.

Peptide fusion improves prime editing efficiency.

Prime editing enables search-and-replace genome editing but is limited by low editing efficiency. We present a high-throughput approach, the Peptide Self-Editing sequencing assay (PepSEq), to measure how fusion of 12,000 85-amino acid peptides influences prime editing efficiency. We show that peptide fusion can enhance prime editing, prime-enhancing peptides combine productively, and a top dual peptide-prime editor increases prime editing significantly in multiple cell lines across dozens of target sites. Top prime-enhancing peptides function by increasing translation efficiency and serve as broadly useful tools to improve prime editing efficiency.

Vibration-controlled Transient Elastography for Assessment of Liver Fibrosis at a USA Academic Medical Center.

Background and Aims: Vibration-controlled transient elastography (VCTE) is a noninvasive tool that uses liver stiffness measurement (LSM) to assess fibrosis. Since real-life data during everyday clinical practice in the USA are lacking, we describe the patterns of use and diagnostic performance of VCTE in patients at an academic medical center in New York City. Methods: Patients who received VCTE scans were included if liver biopsy was performed within 1 year. Diagnostic performance of VCTE in differentiating dichotomized fibrosis stages was assessed via area under the receiver operating characteristics (AUROC). Fibrosis stage determined from VCTE LSM was compared to liver biopsy. Results: Of 109 patients, 49 had nonalcoholic fatty liver disease, 16 chronic hepatitis C, 15 congestive hepatopathy, and 22 at least two etiologies. AUROC was 0.90 for differentiating cirrhosis (stage 4) with a positive predictive value (PPV) range of 0.28 to 0.45 and negative predictive value range of 0.96 to 0.98. For 31 (32%) patients, VCTE fibrosis stage was at least two stages higher than liver biopsy fibrosis stage. Thirteen of thirty-five patients considered to have cirrhosis by VCTE had stage 0 to 2 and 12 stage 3 fibrosis on liver biopsy. Conclusions: VCTE has reasonable diagnostic accuracy and is reliable at ruling out cirrhosis. However, because of its low PPV, caution must be exercised when used to diagnose cirrhosis, as misdiagnosis can lead to unnecessary health care interventions. In routine practice, VTCE is also sometimes performed for disease etiologies for which it has not been robustly validated.

Reconstruction of evolving gene variants and fitness from short sequencing reads.

Directed evolution can generate proteins with tailor-made activities. However, full-length genotypes, their frequencies and fitnesses are difficult to measure for evolving gene-length biomolecules using most high-throughput DNA sequencing methods, as short read lengths can lose mutation linkages in haplotypes. Here we present Evoracle, a machine learning method that accurately reconstructs full-length genotypes (R2 = 0.94) and fitness using short-read data from directed evolution experiments, with substantial improvements over related methods. We validate Evoracle on phage-assisted continuous evolution (PACE) and phage-assisted non-continuous evolution (PANCE) of adenine base editors and OrthoRep evolution of drug-resistant enzymes. Evoracle retains strong performance (R2 = 0.86) on data with complete linkage loss between neighboring nucleotides and large measurement noise, such as pooled Sanger sequencing data (~US$10 per timepoint), and broadens the accessibility of training machine learning models on gene variant fitnesses. Evoracle can also identify high-fitness variants, including low-frequency 'rising stars', well before they are identifiable from consensus mutations.

PrimeDesign software for rapid and simplified design of prime editing guide RNAs.

Prime editing (PE) is a versatile genome editing technology, but design of the required guide RNAs is more complex than for standard CRISPR-based nucleases or base editors. Here we describe PrimeDesign, a user-friendly, end-to-end web application and command-line tool for the design of PE experiments. PrimeDesign can be used for single and combination editing applications, as well as genome-wide and saturation mutagenesis screens. Using PrimeDesign, we construct PrimeVar, a comprehensive and searchable database that includes candidate prime editing guide RNA (pegRNA) and nicking sgRNA (ngRNA) combinations for installing or correcting >68,500 pathogenic human genetic variants from the ClinVar database. Finally, we use PrimeDesign to design pegRNAs/ngRNAs to install a variety of human pathogenic variants in human cells.

Comprehensive Mapping of Key Regulatory Networks that Drive Oncogene Expression.

Gene expression is controlled by the collective binding of transcription factors to cis-regulatory regions. Deciphering gene-centered regulatory networks is vital to understanding and controlling gene misexpression in human disease; however, systematic approaches to uncovering regulatory networks have been lacking. Here we present high-throughput interrogation of gene-centered activation networks (HIGAN), a pipeline that employs a suite of multifaceted genomic approaches to connect upstream signaling inputs, trans-acting TFs, and cis-regulatory elements. We apply HIGAN to understand the aberrant activation of the cytidine deaminase APOBEC3B, an intrinsic source of cancer hypermutation. We reveal that nuclear factor κB (NF-κB) and AP-1 pathways are the most salient trans-acting inputs, with minor roles for other inflammatory pathways. We identify a cis-regulatory architecture dominated by a major intronic enhancer that requires coordinated NF-κB and AP-1 activity with secondary inputs from distal regulatory regions. Our data demonstrate how integration of cis and trans genomic screening platforms provides a paradigm for building gene-centered regulatory networks.