Biology subjects

Fowler, D. M.

Publications and source records attributed to Fowler, D. M..

At least 19 recordsLinked to original sources

bioRxiv2026

Massively scaled variant effect mapping across the MAPK pathway reveals the importance of molecular and cellular context

Variation alters inherent protein properties like thermodynamic stability and catalytic activity, and these intrinsic effects are shaped by the complex cellular environment. Signaling cascades typify this complexity, with tens or hundreds of proteins acting in concert through regulated states and interactions to transduce signals. Here, we measure the effect of 186,676 variants across 17 proteins in the RAS-MAPK pathway on protein abundance and pathway activity in human cells under diverse conditions, for a total of 503,099 variant effect measurements. We discovered 14,412 dominant negative variants across 12 proteins, nearly all previously unknown, that disrupt specific domains or interaction interfaces while leaving other functions intact and that are depleted from the human population. Measuring the abundance of 106,642 variants across 10 proteins under HSP90 inhibition showed that HSP90 shapes the effect of 67% of missense variants across the pathway, buffering destabilizing variants in both strong and weak clients. Our variant effect data, collected in the context of an intact proteome, enabled us to assess the functional importance of 395 experimentally and computationally modeled MAPK protein interactions. Using additional mutational scans, we resolved how the promiscuous switch II helix binding surface of KRAS accommodates overlapping interactions with LZTR1 and SOS1, revealing distinct allosteric networks that support each interaction. Thus, we establish a framework for measuring variant effects at unprecedented scale in human cells, illuminating fundamental MAPK pathway signaling mechanisms and demonstrating that cellular context profoundly shapes the effect of most variants.

genomics↗

bioRxiv2026

CountESS: a flexible, graphical pipeline tool for deep mutational scanning analysis

Deep Mutational Scanning (DMS) experiments generate large volumes of sequencing data that must be processed through multi-step computational pipelines to yield interpretable variant scores. At least twelve dedicated tools have been published for this purpose, yet the diversity of experimental designs, scoring strategies, and software implementations has produced a fragmented landscape in which no single tool accommodates the full range of workflows encountered in practice. Here we present CountESS (Count-based Experiment Scoring and Statistics), an open-source pipeline tool that provides a modular, graphical interface for constructing flexible DMS analysis workflows. CountESS supports a wide range of input formats, barcode translation, HGVS variant calling, and user-defined scoring functions, enabling it to accommodate diverse experimental designs including selection assays, time-series experiments, and bin-based assays such as VAMP-seq. Implemented in Python with DuckDB as a computational backend, the software provides high-performance, memory-efficient processing suitable for large datasets. CountESS is freely available at https://github.com/CountESS-Project/CountESS under the 3-Clause BSD Licence. Supplementary data, including demonstration pipelines and example datasets, are available at https://github.com/CountESS-Project/countess-demo.

bioinformatics↗

bioRxiv2026

Gene- and domain-aware calibration increases the clinical utility of variant effect predictors

The utility of clinical genetic testing is limited because around 90% of missense variants in ClinVar remain of uncertain clinical significance. Variant effect predictors (VEPs) can score any missense variant, potentially empowering variant classification. Realizing this potential requires calibration to translate predictor scores into evidence. However, genome-wide calibration ignores predictor heterogeneity across genes, causing evidence misassignment. We developed an automated, data-adaptive framework that optimizes two complementary approaches: gene-specific calibration for genes with enough variants for calibration, and domain-aggregate calibration for other disease-associated genes, which groups variants from protein domains with similar predictor score distributions for calibration. Applied to three predictors across 2,769 genes, this framework assigned evidence to 10.6% more variants on average while generally improving evidence accuracy compared to genome-wide calibration. These calibrations and the resulting calibrated computational evidence are available through the PredictMD portal. Our framework substantially increases the clinical utility of VEPs for variant classification.

genetics↗

bioRxiv2026

An integrated, scaled approach to resolve TSC2 variants of uncertain significance

Obtaining a precise genetic tuberous sclerosis diagnosis is a challenge as many missense TSC2 variants are variants of uncertain significance (VUS). VUS in TSC2 have been resolved by one-at-a-time functional assays, but these assays cannot scale to the 3,634 TSC2 missense VUS observed so far. To address this challenge, we used massively parallel sequencing to measure the steady-state abundance of almost 9,000 TSC2 missense variants and developed an mTOR pathway activity assay using genome editing and cell sorting to generate activity scores for 391 missense variants. 1,288 of 8,891 (14.49%) missense variants assayed had altered TSC2 abundance, and 69 of 391 (17.65%) missense variants assayed had altered mTOR pathway activity. Calibration and integration of these data into classification of variants identified in a clinical cohort putatively reclassified 212 of 276 (76.8%) TSC2 missense VUS. These datasets will lead to improved genetic diagnosis of tuberous sclerosis with potential positive impacts on the clinical management of patients and their families.

genetics↗

bioRxiv2025

STARCall integrates image stitching, alignment, and read calling to enable scalable analysis of in situ sequencing data

Fluorescent in situ sequencing involves imaging-based sequencing by synthesis in intact cells or tissues to reveal target nucleotide sequences inside each cell. Often, the target sequences are barcodes that indicate a perturbation (e.g. CRISPR guide or genetic variant) delivered to the cell. However, processing in situ sequencing data presents a considerable challenge, requiring stitching and aligning tens of thousands of images with millions of cells, detecting small amplicon colonies across sequencing cycles, and calling reads. To address these challenges, we introduce STARCall: STitching, Alignment and Read Calling for in situ sequencing, a software package that analyzes raw in situ sequencing images to produce a genotype-to-phenotype mapping for each cell. STAR-Call improves upon previous solutions by combining stitching and alignment of images into a single step that minimizes both inter-cycle and intra-cycle alignment error. STARCall also improves detection and extraction of sequencing reads, incorporating filters and normalization to combat background fluorophore signal. We compare STARCall to other methods using a diverse set of images that include commonly encountered imaging problems such as variable intensity across channels and cycles and high levels of background. Specifically, this comprises [~]250,000 images from a pooled screen of [~]3,500 barcoded LMNA variants expressed in U2OS cells and [~]1,200 bar-coded PTEN variants in induced pluripotent stem cells (iPSC) and iPSC-derived neurons. Overall, STARCall aligned more than 50% of tiles with <1 pixel error on all nine image sets while alternative packages had higher error on four. STARCall also yielded an 8-40% increase in genotyped cells due to improved filtering and normalization methods that address background fluorescence. STARCall can call tools like CellPose to segment cells and CellProfiler to compute cell features from the phenotyping images. STARcall is open-source and freely available, providing a robust solution for the analysis of in situ sequencing data. Author summaryShort regions of RNA or DNA can be sequenced inside intact cells or tissues (i.e. in situ) by combining a microscope and sequencing by DNA synthesis. Multiple cycles of sequencing are performed, in which incorporation of a single fluorescently labeled nucleotide is imaged, and the corresponding base detected. Recently, in situ sequencing has proved useful in optical pooled screens, where a library of perturbations such as CRISPR-mediated gene knockouts or genetic variants is introduced into cells, and in situ sequencing is used to reveal the specific perturbation in each cell. However, processing in situ sequencing data presents a considerable challenge, requiring stitching and aligning tens of thousands of images, detecting small amplicon colonies across sequencing cycles, and calling reads. To address these challenges, we introduce STARCall: STitching, Alignment and Read Calling for in situ sequencing. STARCall uses a novel stitching algorithm that minimizes both inter-cycle and intra-cycle alignment error, and improved filters and normalization for base calling. When applied to a set of 9 in situ sequencing image sets, STARCall yielded an 8-40% increase in genotyped cells. STARCall is open-source and applicable to a variety of experiments, providing a robust pipeline for in situ sequencing data.

bioinformatics↗

bioRxiv2025

Multiplex design and discovery of proximity handles for programmable proteome editing

Although we now have a rich toolset for genome editing, an equivalent framework for manipulating the proteome with a comparable flexibility and specificity remains elusive. A promising strategy for "proteome editing" is to use bifunctional molecules (e.g. PROteolysis-Targeting Chimeras or PROTACs1) that bring a target protein into proximity with a degradation or stabilization effector, but their broader application is constrained by a limited repertoire of well-characterized target or effector "handles". We asked whether coupling de novo protein design to a multiplex screening framework could address this gap by accelerating the discovery of effector handles for intracellular protein degradation, stabilization, or relocalization. Using LABEL-seq2, a sequencing-based assay that enables multiplex, quantitative measurement of protein abundance, we screened 9,715 de novo designed candidate effector handles for their ability to recruit a target protein to components of the ubiquitin-proteasome system3 (UPS) (FBXL12, TRAF2, UCHL1, USP38) or the autophagy pathway4 (GABARAP, GABARAPL2, MAP1LC3A). In a single experiment, we discovered hundreds of de novo designed effector handles that reproducibly drove either intracellular degradation (n = 277) or stabilization (n = 204) of a reporter protein. Validation of a subset of these hits in an orthogonal assay confirmed that sequencing-based measurements from the primary screen reliably reflected changes in intracellular abundance of the target protein. Successful effector handles were discovered for both the UPS (n = 194) and autophagy (n = 287) pathways, which provide complementary routes for programmable proteome editing. Autophagy-recruiting effector handles generalized to endogenous targets, as substituting the reporter-specific target handle with a high-affinity MCL1 binder5 reduced endogenous levels of this intracellular oncoprotein6. Moreover, directing autophagy-recruiting effector handles to the outer mitochondrial membrane dramatically perturbed mitochondrial networks in a manner consistent with synthetic tethering and sequestration7,8. Beyond generating a diverse repertoire of protein abundance or localization effector handles, our results establish a scalable, low-cost platform that links deep learning-guided protein design to functional cellular readouts, and chart a course toward a general framework for programmable proteome editing.

synthetic biology↗

bioRxiv2025

Functional evidence for G6PD variant classification from mutational scanning

G6PD deficiency is one of the most common enzyme deficiencies worldwide, and increases the likelihood of adverse reactions to certain drugs and foods. Identifying people at risk is challenging, since most are asymptomatic until they encounter a trigger. This is further complicated since over 60% of 1,559 known genetic variants in G6PD are variants of uncertain significance and thus cannot guide drug prescribing and dosing. To resolve which variants are clinically meaningful and avoid harm from adverse drug reactions, we conducted two high-throughput functional assays: one for G6PD activity, and one for abundance. We measured the function of 9,527 missense, nonsense, and synonymous G6PD variants. The patterns of variant effect on activity and abundance confirmed the importance of structural NADP+ for G6PD activity and abundance, and G6PD dimerization for G6PD activity. Based on the ability of our functional assay scores to accurately classify G6PD variants of known clinical effect, we generated evidence that 4,870 missense variants contribute to G6PD deficiency and 2,245 are unlikely to contribute to G6PD deficiency. Our data can be used to deepen our understanding of G6PD as a protein, and to close the gap in classification for variants of uncertain significance to improve implementation of genetic medicine for G6PD deficiency.

genetics↗

bioRxiv2025

Image-based, pooled phenotyping reveals multidimensional, disease-specific variant effects

Genetic variants often produce complex phenotypic effects that confound current assays and predictive models. We developed Variant in situ sequencing (VIS-seq), a pooled, image-based method that measures variant effects on molecular and cellular phenotypes in diverse cell types. Applying VIS-seq to [~]3,000 LMNA and PTEN variants yielded high-dimensional morphological profiles that captured variant-driven changes in protein abundance, localization, activity and cell architecture. We identified gain-of-function LMNA variants that reshape the nucleus and autism-associated PTEN variants that mislocalize. Morphological profiles predicted variant pathogenicity with near-perfect accuracy and distinguished autism-linked from tumor syndrome-linked PTEN variants. Most variants impacted a multidimensional continuum of phenotypes not recapitulated by any single functional readout. By linking protein variation to cell images at scale, we illuminate how variant effects cascade from molecular to subcellular to cell morphological phenotypes, providing a framework for resolving the complexity of variant function.

genomics↗

bioRxiv2025

A complete map of human cytosolic degrons and their relevance for disease

Degrons are short protein segments that target proteins for degradation via the ubiquitin-proteasome system and thus ensure timely removal of signaling proteins and clearance of misfolded proteins from the intracellular space. Here, we describe a systematic screen for degrons in the human cytosol. We determine degron potency of >200,000 different 30-residue tiles from more than 5,000 cytosolic human proteins with 99.7% coverage. In total, 19.1% of the tiles function as strong degrons, 30.4% as intermediate degrons, while 50.5% did not display degron properties. The vast majority of the degrons are dependent on the E1 ubiquitin-activating enzyme and the proteasome but independent of autophagy. The results reveal both known and novel degron motifs, both internal as well as at the C-terminus. Mapping the degrons onto protein structures, predicted by AlphaFold2, revealed that most of the degrons are located in buried regions, indicating that they only become active upon unfolding or misfolding. Training of a machine learning model allowed us to probe the degron properties further and predict the cellular abundance of missense variants that operate by forming degrons in exposed and disordered protein regions, thus providing a mechanism of pathogenicity for germline coding variants at such positions.

biochemistry↗

bioRxiv2025

Gene-based calibration of high-throughput functional assays for clinical variant classification

High-throughput assays measure a broad range of variant effects on gene function and hold promise for supporting genomic medicine. Current clinical guidelines for rare Mendelian diseases rely on establishing gene-specific score thresholds for each assay that separate pathogenic from benign variants. This introduces inconsistencies and subjectivity, ultimately lacking the rigor of calibration; i.e., mapping a variant score to a probability of pathogenicity. To address this problem, we introduce a semi-supervised framework for calibrating experimental assay data and propose Experimental score CALIBRator (ExCALIBR), a method that jointly models pathogenic, benign, synonymous, and population variants using skew normal mixtures to produce variant-specific probabilities of pathogenicity. Evaluated across 80 datasets from 39 genes, all meeting fit quality criteria, ExCALIBR substantially outperformed existing field standards and was further validated on the All of Us biobank data. Our results demonstrate that calibrated experimental assays generate indispensable evidence that will dramatically reduce variants of uncertain significance.

bioinformatics↗

bioRxiv2024

Multiplex, multimodal mapping of variant effects in secreted proteins

Despite widespread advances in DNA sequencing, the functional consequences of most genetic variants remain poorly understood. Multiplexed Assays of Variant Effect (MAVEs) can measure the function of variants at scale, and are beginning to address this problem. However, MAVEs cannot readily be applied to the [~]10% of human genes encoding secreted proteins. We developed a flexible, scalable human cell surface display method, Multiplexed Surface Tethering of Extracellular Proteins (MultiSTEP), to measure secreted protein variant effects. We used MultiSTEP to study the consequences of missense variation in coagulation factor IX (FIX), a serine protease where genetic variation can cause hemophilia B. We combined MultiSTEP with a panel of antibodies to detect FIX secretion and post-translational modification, measuring a total of 44,816 effects for 436 synonymous variants and 8,528 of the 8,759 possible missense variants. 49.6% of possible F9 missense variants impacted secretion, post-translational modification, or both. We also identified functional constraints on secretion within the signal peptide and for nearly all variants that caused gain or loss of cysteine. Secretion scores correlated strongly with FIX levels in hemophilia B and revealed that loss of secretion variants are particularly likely to cause severe disease. Integration of the secretion and post-translational modification scores enabled reclassification of 63.1% of F9 variants of uncertain significance in the My Life, Our Future hemophilia genotyping project. Lastly, we showed that MultiSTEP can be applied to a wide variety of secreted proteins. Thus, MultiSTEP is a multiplexed, multimodal, and generalizable method for systematically assessing variant effects in secreted proteins at scale.

genomics↗

bioRxiv2023

Deep mutational scanning of CYP2C19 reveals a substrate specificity-abundance tradeoff

Cytochrome P450s (CYPs) are a family of enzymes responsible for metabolizing nearly 80% of small molecule drugs. Variants in CYPs can substantially alter drug metabolism, which may result in improper dosing and severe adverse drug reactions. CYPs have low sequence conservation, making it difficult to anticipate whether variant effects measured in one CYP may extend to others based on sequence alone. Even closely related CYPs, like CYP2C9 and its closest homolog CYP2C19, have distinct phenotypic properties despite sharing 92% amino acid sequence identity. Thus, we used Variant Abundance by Massively Parallel sequencing (VAMP-seq) to measure the steady-state protein abundance, a proxy for protein stability, of 7,660 missense variants in CYP2C19 expressed in cultured human cells. Our results confirmed positions and structural features critical for CYP function and revealed how variants at positions conserved across all eukaryotic CYPs influence abundance. We jointly analyzed 4,670 variants whose abundance was measured in both CYP2C19 and CYP2C9, finding that the homologs have different variant abundances in substrate recognition sites within the hydrophobic core, and that substitutions in some regions reduced abundance in CYP2C19 but not CYP2C9. We also measured the abundance of all single and some multiple WT amino acid exchanges between CYP2C19 and CYP2C9. While most exchanges had no effect, substitutions in substrate recognition site 4 (SRS4) reduced abundance in CYP2C19. When nearby amino acids were exchanged in double and triple mutants, we found distinct interactions between the sites in CYP2C19 and CYP2C9, revealing a region that is partially responsible for the difference in thermodynamic stability between the two homologs. Since these positions are also important for determining substrate specificity, there may be an evolutionary tradeoff between stability and altered enzymatic function. Finally, we used our data to analyze 368 previously unannotated human variants, finding that 43% had decreased abundance. Thus, by comparing variant effects between two closely related and important human genes, we have uncovered regions underlying their functional differences and paved the way for a more complete understanding of one of the most versatile families of enzymes.

genetics↗

bioRxiv2023

Deep mutational scanning reveals a tight correlation between protein degradation and toxicity of thousands of non-native aspartoacylase protein variants

When the structural stability of a protein is compromised, the protein may form non-native interactions with other cell proteins and thus becomes a hazard to the cell. To mitigate this danger, destabilized proteins are targeted by the cellular protein quality control (PQC) network, which either corrects the folding defect or targets the protein for degradation. However, the details of how the protein folding and degradation systems collaborate to combat potentially toxic non-native proteins are unknown. To address this issue, we performed systematic studies on destabilized variants of the cytosolic aspartoacylase, ASPA, where loss-of-function variants are linked to Canavans disease, an autosomal recessive and lethal neurological disorder, characterized by the spongy degeneration of the white matter in the brain. Using Variant Abundance by Massively Parallel sequencing (VAMP-seq), we determined the abundance of 6152 out of the 6260 ([~]98%) possible single-site missense and nonsense ASPA variants in cultured human cells. The majority of the low abundance ASPA variants are degraded through the ubiquitin-proteasome system (UPS) and become toxic upon prolonged expression. Variant cellular abundance data correlates with predicted thermodynamic stability, evolutionary conservation, and separates most known disease-linked variants from benign variants. Systematic mapping of degradation signals (degrons) shows that inherent primary degrons in ASPA are located in buried regions, and reveals that the wild-type ASPA C-terminal region functions as a degron. Collectively, our data can be used to interpret Canavans disease variants and also offer mechanistic insight into how ASPA missense variants are targeted by the PQC system. These are essential steps towards future implementation of precision medicine for Canavans disease.

molecular biology↗

bioRxiv2023

Multiplexed functional assessments of MYH7 variants in human cardiomyocytes at scale

BackgroundSingle, autosomal-dominant missense mutations in MYH7, which encodes a sarcomeric protein (MHC-{beta}) in cardiac and skeletal myocytes, are a leading cause of hypertrophic cardiomyopathy and are clinically-actionable. However, [~]75% of MYH7 variants are of unknown significance (VUS), causing diagnostic challenges for clinicians and emotional distress for patients. Deep mutational scans (DMS) can determine variant effect at scale, but have only been utilized in easily-editable cell lines. While human induced pluripotent stem cells (hiPSCs) can be differentiated to numerous cell types that enable the interrogation of variant effect in a disease-relevant context, DMS have not been executed using diploid hiPSC derivates. However, CRaTER enrichment has recently enabled the pooled generation of a saturated five position MYH7 variant hiPSC library suitable for DMS for the first time. ResultsAs a proof-of-concept, we differentiated this MYH7 variant hiPSC library to cardiomyocytes (hiPSC-CMs) for multiplexed assessment of MHC-{beta} variant abundance by massively parallel sequencing (VAMP-seq) and hiPSC-CM survival. We confirm MHC-{beta} protein loss occurs in a failing human heart with a pathogenic MYH7 mutation. We find the multiplexed assessment of MHC-{beta} abundance and hiPSC-CM survival both accurately segregate all pathogenic variants from synonymous controls. Overall, functional scores of 68 amino acid substitutions across these independent assays are [~]50% consistent. ConclusionsThis study leverages hiPSC differentiation into disease-relevant cardiomyocytes to enable multiplexed assessments of MYH7 missense variants at scale for the first time. This proof-of-concept demonstrates the ability to DMS previously restricted, clinically-actionable genes to reduce the burden of VUS on patients and clinicians.

genetics↗

bioRxiv2023

A mutational atlas for Parkin proteostasis

The delicate balance of protein homeostasis can be disturbed by mutations that affect folding and stability of the encoded protein. More than half of disease-causing missense variants are thought to lead to protein degradation, but determining which and the molecular mechanisms involved remain enigmatic. To examine these issues, we selected the ubiquitin-protein ligase Parkin, where known missense variants result in an autosomal recessive, early onset Parkinsonism. We used the variant abundance by massively parallel sequencing (VAMP-seq) approach to quantify the abundance of Parkin missense variants in cultured human cells. The resulting mutational map, covering 9219 out of the 9300 possible single-site amino acid substitutions and nonsense Parkin variants, show that most low abundance variants are located within the structured domains of the protein, while the flexible linker regions are more tolerant. The vast majority of low abundance Parkin variants are degraded through the ubiquitin-proteasome system and are stabilized at a lowered temperature. The cellular abundance data correlate with thermodynamic stability, evolutionary conservation, and show that half of the known disease-linked variants are found at low abundance. Systematic mapping of degradation signals (degrons) shows that inherent primary degrons in Parkin largely overlap with regions that are buried, and highly sensitive to mutations. An exposed degron region proximal to the so-called "activation element" is enhanced by substitutions to hydrophobic residues and destroyed by introduction of hydrophilic residues. The data provide examples of how missense variants may cause degradation either via destabilization of the native protein, or by introducing local signals for degradation. Combined with the computational methods based on Parkin structure and conservation, our abundance map sheds light on the mechanisms that cause loss of function, and points to variants where function potentially can be restored.

biochemistry↗

bioRxiv2023

Machine vision reveals micronucleus rupture as a potential driver of the transcriptomic response to aneuploidy

Recent advances in isolating cells based on visual phenotypes have transformed our ability to identify the mechanisms and consequences of complex traits. Micronucleus (MN) formation is a frequent outcome of genome instability, triggers extensive changes in genome structure and signaling coincident with MN rupture, and is almost exclusively defined by visual analysis. Automated MN detection in microscopy images has proved challenging, limiting discovery of the mechanisms and consequences of MN. In this study we describe two new MN segmentation modules: a rapid model for classifying micronucleated cells and their rupture status (VCS MN), and a robust model for accurate MN segmentation (MNFinder) from a broad range of cell lines. As proof-of-concept, we define the transcriptome of non-transformed human cells with intact or ruptured MN after chromosome missegregation by combining VCS MN with photoactivation-based cell isolation and RNASeq. Surprisingly, we find that neither MN formation nor rupture triggers a strong unique transcriptional response. Instead, transcriptional changes appear correlated with small increases in aneuploidy in these cell classes. Our MN segmentation modules overcome a significant challenge with reproducible MN quantification, and, joined with visual cell sorting, enable the application of powerful functional genomics assays to a wide-range of questions in MN biology.

cell biology↗

bioRxiv2023

High-throughput functional mapping of variants in an arrhythmia gene, KCNE1, reveals novel biology

BackgroundKCNE1 encodes a 129-residue cardiac potassium channel (IKs) subunit. KCNE1 variants are associated with long QT syndrome and atrial fibrillation. However, most variants have insufficient evidence of clinical consequences and thus limited clinical utility. ResultsHere, we demonstrate the power of variant effect mapping, which couples saturation mutagenesis with high-throughput sequencing, to ascertain the function of thousands of protein coding KCNE1 variants. We comprehensively assayed KCNE1 variant cell surface expression (2,554/2,709 possible single amino acid variants) and function (2,539 variants). We identified 470 loss-of-surface expression and 588 loss-of-function variants. Out of the 588 loss-of-function variants, only 155 had low cell surface expression. The latter half of the protein is dispensable for protein trafficking but essential for channel function. 22 of the 30 KCNE1 residues (73%) highly intolerant of variation were in predicted close contact with binding partners KCNQ1 or calmodulin. Our data were highly concordant with gold standard electrophysiological data ({rho} = -0.65), population and patient cohorts (32/38 concordant variants), and computational metrics ({rho} = -0.55). Our data provide moderate-strength evidence for the ACMG/AMP functional criteria for benign and pathogenic variants. ConclusionsComprehensive variant effect maps of KCNE1 can both provide insight into IKs channel biology and help reclassify variants of uncertain significance.

genomics↗

bioRxiv2023

CRaTER enrichment for on-target gene-editing enables generation of variant libraries in hiPSCs

Standard transgenic cell line generation requires screening 100-1000s of colonies to isolate correctly edited cells. We describe CRISPRa On-Target Editing Retrieval (CRaTER) which enriches for cells with on-target knock-in of a cDNA-fluorescent reporter transgene by transient activation of the targeted locus followed by flow sorting to recover edited cells. We show CRaTER recovers rare cells with heterozygous, biallelic-editing of the transcriptionally-inactive MYH7 locus in human induced pluripotent stem cells (hiPSCs), enriching on average 25-fold compared to standard antibiotic selection. We leveraged CRaTER to enrich for heterozygous knock-in of a library of single nucleotide variants (SNVs) in MYH7, a gene in which missense mutations cause cardiomyopathies, and recovered hiPSCs with 113 different MYH7 SNVs. We differentiated these hiPSCs to cardiomyocytes and show MYH7 fusion proteins can localize as expected. Thus, CRaTER substantially reduces screening required for isolation of gene-edited cells, enabling generation of transgenic cell lines at unprecedented scale.

genetics↗