UCLA

Induced pluripotent stem cell (iPSC)-derived neural cultures from amyotrophic lateral sclerosis (ALS) patients can model disease phenotypes. However, heterogeneity arising from genetic and experimental variability limits their utility, impacting reproducibility and the ability to track cellular origins of pathogenesis. Here, we present methodologies using single-cell RNA sequencing (scRNA-seq) analysis to address these limitations. By repeatedly differentiating and applying scRNA-seq to motor neurons (MNs) from healthy, familial ALS, sporadic ALS, and genome-edited iPSC lines across multiple patients, batches, and platforms, we account for genetic and experimental variability toward identifying unified and reproducible ALS signatures. Combining HOX and developmental gene expression with global clustering, we anatomically classified cells into rostrocaudal, progenitor, and postmitotic identities. By relaxing statistical thresholds, we discovered genes in iPSC-MNs that were concordantly dysregulated in postmortem MNs and yielded predictive ALS markers in other human and mouse models. Our approach thus revealed early, convergent, and MN-resolved signatures of ALS.