Cell-Type-Resolved Isoform Atlas of Human Tissues Reveals Age and Alzheimer's Disease-Associated Splicing Changes

Abstract

Alternative splicing is a key mechanism for transcriptomic diversity, but how isoforms map to specific cell types in bulk tissues remains unclear. We present Sciege, a multimodal method that integrates bulk short-read RNA-seq with single-cell and long-read data to estimate cell type-specific isoform distributions. Through simulations, we demonstrate that Sciege accurately estimates isoform abundances and identifies differentially abundant transcripts through statistical tests. Applied to seven tissues in GTEx and brain tissue in ROSMAP datasets, Sciege generates a first-to-date multi-tissue isoform atlas and reveals isoform changes linked to cell types, aging, and Alzheimers disease. Validation with external cohorts and experimental data confirms our findings. Notably, we identify upregulation of the MAPT-010 isoform in AD inhibitory neurons, consistent with known methylation signatures. Our approach demonstrates the value of integrating RNA-seq data to study cell type-specific splicing and provides a foundation for further genetic and functional studies of alternative splicing across biological contexts.