Transcriptome-Wide Analysis Reveals a Role for Extracellular Matrix and Integrin Receptor Genes in Otic Neurosensory Differentiation from Human iPSCs.
Lejo Johnson ChackoHanae LahlouClaudia SteinacherSaid AssouYassine MessatJozsef DudasAlbert EdgeBerta CrespoMoira CrosierConsolato Maria SergiAnneliese Schrott-FischerAzel ZinePublished in: International journal of molecular sciences (2021)
We analyzed transcriptomic data from otic sensory cells differentiated from human induced pluripotent stem cells (hiPSCs) by a previously described method to gain new insights into the early human otic neurosensory lineage. We identified genes and biological networks not previously described to occur in the human otic sensory developmental cell lineage. These analyses identified and ranked genes known to be part of the otic sensory lineage program (SIX1, EYA1, GATA3, etc.), in addition to a number of novel genes encoding extracellular matrix (ECM) (COL3A1, COL5A2, DCN, etc.) and integrin (ITG) receptors (ITGAV, ITGA4, ITGA) for ECM molecules. The results were confirmed by quantitative PCR analysis of a comprehensive panel of genes differentially expressed during the time course of hiPSC differentiation in vitro. Immunocytochemistry validated results for select otic and ECM/ITG gene markers in the in vivo human fetal inner ear. Our screen shows ECM and ITG gene expression changes coincident with hiPSC differentiation towards human otic neurosensory cells. Our findings suggest a critical role of ECM-ITG interactions with otic neurosensory lineage genes in early neurosensory development and cell fate determination in the human fetal inner ear.
Keyphrases
- induced pluripotent stem cells
- extracellular matrix
- endothelial cells
- gene expression
- genome wide
- single cell
- pluripotent stem cells
- genome wide identification
- stem cells
- dna methylation
- induced apoptosis
- mesenchymal stem cells
- bone marrow
- machine learning
- artificial intelligence
- cell therapy
- simultaneous determination
- signaling pathway
- bioinformatics analysis
- deep learning
- cell migration