| Literature DB >> 33382996 |
Ritchie Ho1, Michael J Workman2, Pranav Mathkar3, Kathryn Wu2, Kevin J Kim2, Jacqueline G O'Rourke3, Mariko Kellogg4, Valerie Montel4, Maria G Banuelos2, Olubankole Aladesuyi Arogundade5, Sandra Diaz-Garcia5, Daniel Oheb2, Steven Huang2, Irina Khrebtukova4, Lisa Watson4, John Ravits5, Kevin Taylor4, Robert H Baloh6, Clive N Svendsen7.
Abstract
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.Entities:
Keywords: ALS; ELAVL3; iPSC; single-cell RNA-seq
Mesh:
Year: 2020 PMID: 33382996 PMCID: PMC7897311 DOI: 10.1016/j.cels.2020.10.010
Source DB: PubMed Journal: Cell Syst ISSN: 2405-4712 Impact factor: 10.304