Scanning mutagenesis of the voltage-gated sodium channel NaV1.2 using base editing

Joint genotypic and phenotypic outcome modeling improves base editing variant effect quantification

CRISPR base editing screens enable analysis of disease-associated variants at scale; however, variable efficiency and precision confounds the assessment of variant-induced phenotypes. Here, we provide an integrated experimental and computational pipeline that improves estimation of variant effects in base editing screens. We use a reporter construct to measure guide RNA (gRNA) editing outcomes alongside their phenotypic consequences and introduce base editor screen analysis with activity normalization (BEAN), a Bayesian network that uses per-guide editing outcomes provided by the reporter and target site chromatin accessibility to estimate variant impacts. BEAN outperforms existing tools in variant effect quantification. We use BEAN to pinpoint common regulatory variants that alter low-density lipoprotein (LDL) uptake, implicating previously unreported genes. Additionally, through saturation base editing of LDLR, we accurately quantify missense variant pathogenicity that is consistent with measurements in UK Biobank patients and identify underlying structural mechanisms. This work provides a widely applicable approach to improve the power of base editing screens for disease-associated variant characterization.

Development of automated patch clamp assays to overcome the burden of variants of uncertain significance in inheritable arrhythmia syndromes

Advances in next-generation sequencing have been exceptionally valuable for identifying variants in medically actionable genes. However, for most missense variants there is insufficient evidence to permit definitive classification of variants as benign or pathogenic. To overcome the deluge of Variants of Uncertain Significance, there is an urgent need for high throughput functional assays to assist with the classification of variants. Advances in parallel planar patch clamp technologies has enabled the development of automated high throughput platforms capable of increasing throughput 10- to 100-fold compared to manual patch clamp methods. Automated patch clamp electrophysiology is poised to revolutionize the field of functional genomics for inheritable cardiac ion channelopathies. In this review, we outline i) the evolution of patch clamping, ii) the development of high-throughput automated patch clamp assays to assess cardiac ion channel variants, iii) clinical application of these assays and iv) where the field is heading.

Joint genotypic and phenotypic outcome modeling improves base editing variant effect quantification

CRISPR base editing screens are powerful tools for studying disease-associated variants at scale. However, the efficiency and precision of base editing perturbations vary, confounding the assessment of variant-induced phenotypic effects. Here, we provide an integrated pipeline that improves the estimation of variant impact in base editing screens. We perform high-throughput ABE8e-SpRY base editing screens with an integrated reporter construct to measure the editing efficiency and outcomes of each gRNA alongside their phenotypic consequences. We introduce BEAN, a Bayesian network that accounts for per-guide editing outcomes and target site chromatin accessibility to estimate variant impacts. We show this pipeline attains superior performance compared to existing tools in variant classification and effect size quantification. We use BEAN to pinpoint common variants that alter LDL uptake, implicating novel genes. Additionally, through saturation base editing of LDLR, we enable accurate quantitative prediction of the effects of missense variants on LDL-C levels, which aligns with measurements in UK Biobank individuals, and identify structural mechanisms underlying variant pathogenicity. This work provides a widely applicable approach to improve the power of base editor screens for disease-associated variant characterization.