Sriram Pendyala
@treependyala.bsky.social
340 followers 2K following 10 posts
MD/PhD Student in Doug Fowler's Lab, UW Genome Sciences
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treependyala.bsky.social
🔮 Multidimensional variant information may help empower or constrain next generation predictors! Current variant effect predictors perform poorly on molecular and cellular phenotypes, and struggle to parse complex variant-disease relationships.

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treependyala.bsky.social
🌎 LMNA variant ➡️ structure ➡️ abundance and localization ➡️ function! VIS-seq maps LMNA variant effects across scales of cellular organization and discovered a new subset of gain-of-function LMNA variants.

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UMAP of LMNA variant profiles (left) colored by Louvain-derived clusters. Colors legend at bottom.
Graphical representation (right) of lamin A processing, localization, aggregation, and degradation, annotated with their relationship to dimerization, multimerization and variant clusters.
treependyala.bsky.social
📊 PTEN variants ≠ one axis of “function”. VIS-seq’s multidimensional representations discriminate between PTEN autism- and tumor syndrome-associated variants.

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UMAP of iPS cell PTEN variant profiles (left). Triangles indicate association with clinical phenotypes. gnomAD v4.1 (light blue) variants are also plotted. Circles represent other variants, colored green (synonymous) or grey (non-synonymous).
Receiver operating characteristic (ROC) curves (right) produced by macro-averaging sensitivity and specificity over classes for models trained on iPS and neuron VIS-seq landmark features (dotted lines) as well as scores from (C) classifying gnomAD controls from PHTS-associated variants from ASD/DD-associated variants. AUC is shown on the right for each model.
treependyala.bsky.social
🌐 Generalizability and scale: ~3000 LMNA or PTEN variants • 11.4 million cells • 1000+ image-derived features per cell • Fluorescent proteins, antibodies, and RNA FISH readouts • Cancer cell lines, iPS and derived cells.

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Images of libraries of mEGFP-tagged lamin A in U2OS cells (left), mEGFP-tagged PTEN in human WTC11 PTEN-KO inducible-NGN2 iPS cells or mEGFP-tagged H1.4 and RPS19 in human WTC11 iPS cells (right), or mEGFP-tagged PTEN library in derived neurons, seven days after induction of NGN2 (far right). Some cells express variants with localization defects (lamin A=nuclear aggregates, PTEN=nucleocytoplasmic, HIST1H1E=chromatin binding, RPS19=nucleolar-cytoplasmic).  Scale bar indicates 20 μm.
treependyala.bsky.social
🎯 Barcoded circular RNAs are co-expressed in each cell along with a tagged variant ➡️ pooled imaging ➡️ in situ sequencing decodes the barcode ➡️ CellProfiler extracts thousands of molecular & cellular features per cell!

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VIS-seq uses fluorescent in situ sequencing of abundant circular RNA barcodes to genotype cells expressing protein variants. (1) A variant library in the VIS-seq expression cassette is integrated into cells via piggyBac-ase. (2) Cells are fixed; barcodes are reverse transcribed, captured with a padlock probe and amplified; (3) cells are stained and imaged; (4) barcode is sequenced in situ; (5) single cell phenotype-genotype pairs are determined using STARCall; and (6) features for each cell are extracted using CellProfiler.
treependyala.bsky.social
🤿 Dive-in yourself at visseq.gs.washington.edu! A website showing profiles, features, and cell images of LMNA and PTEN variants built by lab member and recent UW Computer Science graduate Nick Bradley.

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VISSEQ Data Exporer
visseq.gs.washington.edu
treependyala.bsky.social
⚡ I developed VIS-seq with the help of dougfowler.bsky.social and others at UW Genome Sciences. Check out my preprint:
www.biorxiv.org/content/10.1...

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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. ### Competing Interest Statement FPR is an advisor and shareholder in Constantiam Biosciences. National Human Genome Research Institute, https://ror.org/00baak391, RM1HG010461, R01HG013025 National Institute of General Medical Sciences, R35GM152106 National Heart Lung and Blood Institute, https://ror.org/012pb6c26, K99HL177347, R01HL171174, R01HL164675 Chan Zuckerberg Initiative (United States), CZIF2024-010284, CP-2-1-Fowler Brotman Baty Institute, https://ror.org/03jxvbk42, CC28 United States Department of Veterans Affairs, I01BX006428, IK2BX004642 Novo Nordisk Foundation, https://ror.org/04txyc737, Alex's Lemonade Stand for Childhood Cancer RUNX1 Foundation
www.biorxiv.org
treependyala.bsky.social
🚨 Most variant screens measure growth or abundance. What do they miss? That variants impact a spectrum of protein and cellular phenotypes. Variant in situ sequencing (VIS-seq) finds what’s missing: image cells 🔬 first, decode later, revealing multi-scale phenotypes for thousands of variants.👇

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