Project description:It has been notoriously challenging for researchers in the fields of stem cell biology and regenerative medicine to robustly generate uniform populations of differentiated cells from human induced pluripotent stem cells (hiPSCs). In particular, the process of iPSC chondrogenesis has been difficult to reproduce among different laboratories. While several differentiation protocols are being developed, few, if any, yield homogenous hiPSC-derived chondrocytes without any off-target contaminating cells. To improve homogeneity of hiPSC chondrogenesis, we have developed the first application of single-cell RNA sequencing to systemically deconstruct each differentiation step and delineate molecular mechanisms underlying lineage commitment of hiPSCs toward chondrocytes. We identified that MITF as well as several specific canonical and non-canonical WNTs are hub genes of gene regulatory networks governing the off-target differentiation into neural cells and melanocytes during hiPSC chondrogenesis. By inhibiting these off-target molecules, we significantly enhanced chondrogenic lineage commitment of hiPSCs without cell sorting. Using sequencing data of day 28 (pellet time point) as an example, the percentage of chondrocytes within the pellet was improved from 59.63% (standard protocol) to 87.92% (optimized protocol; note: the other 12.07% belong to mesenchymal cells). Importantly, none of the off-target neural cells and melanocytes were detected, suggesting 100% removal of off-target differentiation by the optimized method. Our optimized protocol was validated by 3 unique hiPSC lines and 3 unique hMSC lines, indicating the protocol can be broadly applied to multiple cell lines. Moreover, therapeutic efficacy of hiPSC-derived chondrocytes was further validated in vivo by subcutaneous implantation and osteochondral defect repair in immunodeficient mice. In addition to the 11 consecutive time points from mesodermal to chondrogenic differentiation stages that were sequenced by bulk RNA-seq, we also sequenced 14 chondrogenic time points at single cell resolution. We believe that our bioinformatic analyses including gene regulatory networks, multicellular signaling models, as well as the large amount of data reported here will provide invaluable resources to investigate cell fate decision during human cartilage development.

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Characterisation of epigenomic changes during chondrogenesis

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