Biology subjects

Pendyala, S.

Publications and source records attributed to Pendyala, S..

13 recordsLinked to original sources

bioRxiv2026

The role of urothelial PIEZO ion channels in urinary function

The urothelium is increasingly recognized as a dynamic sensory interface that contributes to the regulation of urinary tract function. Mechanosensitive PIEZO ion channels expressed by urothelial cells have been proposed to play important roles in bladder fullness sensation and urinary reflexes. However, the functional contribution of urothelial PIEZO channels to these processes remains unclear. Here, we investigated the consequences of urothelial Piezo1 and Piezo2 deletion using the commonly used Upk2-cre transgenic line. Surprisingly, combined deletion of urothelial PIEZO channels did not alter urinary behavior, and mice lacking urothelial PIEZO1/2 exhibited normal bladder pressure-volume relationships, indicating preserved bladder filling and voiding function. Notably, Upk2-cre; Piezo1fl/fl mice displayed enhanced external urethral sphincter reflex activity during voiding, suggesting that loss of PIEZO1 from cells targeted by Upk2-cre may influence sensory signaling outside of the bladder urothelium. Consistent with this possibility, we identified substantial off-target Cre expression in dorsal root ganglia. These findings demonstrate that the Upk2-cre line is not restricted to the urothelium and therefore raises important considerations for interpreting associated phenotypes attributed specifically to urothelial gene deletion. Biologically, this raises the possibility that PIEZO1 does not influence bladder pressure-volume handling but might contribute to urinary reflexes.

neuroscience↗

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

Embryo-scale Visual Cell Sorting reveals a conserved transcriptomic signature of nucleolar size linked to proteostasis

Nucleoli, nuclear speckles and other compartments regulate transcription, RNA processing, and chromatin organization within the nucleus, yet the relationship of their morphology to developmental gene expression programs in vivo is poorly understood. Here, we develop a high-throughput Visual Cell Sorting (VCS) workflow for fixed cells and nuclei that combines antibody-based photoconversion; GPU-accelerated, real-time image analysis; and three-level single-cell combinatorial indexing RNA-seq (sci-RNA-seq3) to link nuclear compartment morphology to single-nucleus transcriptomes at embryo scale. We use VCS to analyze and sort over 1 million mouse embryo-derived nuclei by nucleolar, nuclear speckle, or nuclear size and construct a transcriptional atlas annotated with nuclear compartment phenotypes. Nuclear compartment size varies both between and within lineages and is shaped by proliferation and differentiation. In extracellular matrix protein-producing cell types such as fibroblasts, chondrocytes, and osteoblasts, nucleolar enlargement is uncoupled from cell cycle, and in erythroid cells exhibit a sharp nucleolar contraction preceding cell-cycle exit. We identify a 41-gene transcriptional signature whose expression tracks nucleolar size, enriched for ribosome biogenesis, mitochondrial metabolism, unfolded protein response, stress granule, and ubiquitin-proteasome pathway components. We used this nucleolar transcriptional signature to annotate mouse, zebrafish and human developmental atlases with nucleolar size information, revealing a conserved coupling between nucleolar activity and proteostasis programs. Our work establishes Visual Cell Sorting as a scalable platform for mapping image-based phenotypes to molecular programs; details the relationship between nuclear compartment phenotypes and development; and provides a transcriptional signature to estimate nucleolar size from existing single-cell datasets.

genomics↗

bioRxiv2026

PIEZO1-mediated mechanosensation links aging to bladder dysfunction

Aging is accompanied by profound changes in bladder function, leading to increased urinary frequency and incontinence that impair quality of life in humans and are recapitulated in mouse models. Bladder filling and emptying rely on precise mechanosensory feedback, yet how aging alters this sensory control remains unclear. PIEZO ion channels convert mechanical forces into cellular signals essential for bladder fullness sensation. Using inducible smooth-muscle specific Piezo1 deletion, we find that loss of Piezo1 attenuates aging-related bladder dysfunction. Dietary enrichment with margaric acid, a membrane-active fatty acid previously shown to inhibit PIEZO channels, reduced urinary dysfunction in aged mice. In humans, genotype-phenotype analyses reveal an association between a PIEZO1 gain-of-function variant and early-onset neuromuscular bladder dysfunction. Together, these findings define a smooth-muscle, PIEZO1-mediated mechanosensory basis for aging-related bladder dysfunction and introduce a non-invasive strategy for targeting PIEZO channels in vivo.

physiology↗

bioRxiv2026

A scalable approach to resolving variants of uncertain significance

Over 90% of missense variants across [~]4,000 disease-associated genes are variants of uncertain significance (VUS). Experimental variant effect measurements provide critical evidence about pathogenicity and inform disease biology, but most variants lack data and clinical translation has been limited. The Impact of Genomic Variation on Function Consortium generated experimental data for 62,215 variants across ten genes using multiplexed assays and 1,407 variants across 163 genes using arrayed assays, curated 193,139 additional community-generated variant effect measurements across 30 additional genes, and developed automated calibration methods for translating experimental data and variant effect predictions into clinical evidence. To reduce current VUS, we developed a scalable workflow using only experimental and predictive evidence, enabling reclassification of 75% of the 16,115 VUS in these genes as pathogenic or benign with <1% error. To minimize future VUS, we analyzed >90,000 unobserved variants; 62% had enough evidence to be "preclassified" as pathogenic or benign. We validated our data, evidence and classifications using All of Us and created interactive resources to enable clinical use of the calibrated data. Thus, for 40 genes, representing 1% of the clinical genome, we resolve most existing VUS and future variants, illustrating how systematic use of scalable evidence can empower genomic medicine.

genomics↗

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

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↗

bioRxiv2023

Pseudotime analysis for time-series single-cell sequencing and imaging data

Many single-cell RNA-sequencing studies have collected time-series data to investigate transcriptional changes concerning various notions of biological time, such as cell differentiation, embryonic development, and response to stimulus. Accordingly, several unsupervised and supervised computational methods have been developed to construct single-cell pseudotime embeddings for extracting the temporal order of transcriptional cell states from these time-series scRNA-seq datasets. However, existing methods, such as psupertime, suffer from low predictive accuracy, and this problem becomes even worse when we try to generalize to other data types such as scATAC-seq or microscopy images. To address this problem, we propose Sceptic, a support vector machine model for supervised pseudotime analysis. Whereas psupertime employs a single joint regression model, Sceptic simultaneously trains multiple classifiers with separate score functions for each time point and also allows for non-linear kernel functions. Sceptic first generates a probability vector for each cell and then aims to predict chronological age via conditional expectation. We demonstrate that Sceptic achieves significantly improved prediction power (accuracy improved by 1.4 - 38.9%) for six publicly available scRNA-seq data sets over state-of-the-art methods, and that Sceptic also works well for single-nucleus image data. Moreover, we observe that the pseudotimes assigned by Sceptic show stronger correlations with nuclear morphology than the observed times, suggesting that these pseudotimes accurately capture the heterogeneity of nuclei derived from a single time point and thus provide more informative time labels than the observed times. Finally, we show that Sceptic accurately captures sex-specific differentiation timing from both scATAC-seq and scRNA-seq data.

genomics↗

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

Antigen perception in T cells by long-term Erk and NFAT signaling dynamics.

Immune system threat detection hinges on T cells ability to perceive varying peptide major-histocompatibility complex (pMHC) antigens. As the Erk and NFAT pathways link T cell receptor engagement to gene regulation, their signaling dynamics may convey information about pMHC inputs. To test this idea, we developed a dual reporter mouse strain and a quantitative imaging assay that, together, enable simultaneous monitoring of Erk and NFAT dynamics in live T cells over day-long timescales as they respond to varying pMHC inputs. Both pathways initially activate uniformly across various pMHC inputs, but diverge only over longer (9+ hrs) timescales, enabling independent encoding of pMHC affinity and dose. These late signaling dynamics are decoded via multiple temporal and combinatorial mechanisms to generate pMHC-specific transcriptional responses. Our findings underscore the importance of long timescale signaling dynamics in antigen perception, and establish a framework for understanding T cell responses under diverse contexts. SIGNIFICANCE STATEMENTTo counter diverse pathogens, T cells mount distinct responses to varying peptide-major histocompatibility complex ligands (pMHCs). They perceive the affinity of pMHCs for the T cell receptor (TCR), which reflects its foreignness, as well as pMHC abundance. By tracking signaling responses in single living cells to different pMHCs, we find that T cells can independently perceive pMHC affinity vs dose, and encode this information through the dynamics of Erk and NFAT signaling pathways downstream of the TCR. These dynamics are jointly decoded by gene regulatory mechanisms to produce pMHC-specific activation responses. Our work reveals how T cells can elicit tailored functional responses to diverse threats and how dysregulation of these responses may lead to immune pathologies.

immunology↗

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

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↗