Single-cell analyses reveal distinct expression patterns and roles of long non-coding RNAs during hESC differentiation into pancreatic progenitors

• Published in: Stem cell research & therapy 2023-03, Vol.14 (1), p.38-38, Article 38
• Main Authors: Luo, Hai-Tao, He, Qian, Yang, Wei, He, Fei, Dong, Jun, Hu, Chao-Feng, Yang, Xiao-Fei, Li, Ning, Li, Fu-Rong
• Format: Article
• Language: English
• Subjects: Algorithms; Analysis; Base Sequence; Cell culture; Cell Differentiation; Chromosomes; Diabetes; Embryo cells; Embryonic stem cells; Exocytosis; Functional annotation; Genomics; Health aspects; hESC differentiation; HOX gene; Human Embryonic Stem Cells - metabolism; Humans; Karyotypes; LncRNA; Metacell; Non-coding RNA; Pancreas; Pancreatic progenitors; RNA; RNA sequencing; RNA, Long Noncoding - genetics; scRNA-seq; Signal transduction; Single-Cell Analysis; Software; Stem cells
• ISSN: 1757-6512; 1757-6512
• DOI: 10.1186/s13287-023-03259-x

Deep understanding the differentiation process of human embryonic stem cells (hESCs) is essential for developing cell-based therapeutic strategy. Substantial efforts have been made to investigate protein-coding genes, yet it remains lacking comprehensive characterization of long non-coding RNAs (lncRNAs) during this process. hESCs were passaged every 5-6 days and had maintained stable karyotype even until the 50th generation. Pancreatic progenitor specification of in vitro differentiation from hESCs was performed and modified. The nuclei were stained with 4,6-Diamidino-2-phenylindole (DAPI). Droplet-based platform (10X Genomics) was applied to generate the single-cell RNA sequencing (scRNA-seq) data. The quality of the filtered read pairs was evaluated by using FastQC. Batch effects were removed using the size factor method. Dimension reduction and unsupervised clustering analyses were performed using Seurat R package. The Monocle 2 and MetaCell algorithms were used to order single cells on a pseudotime course and partition the scRNA-seq data into metacells, respectively. Co-expression network was constructed using WGCNA. Module- and hub-based methods were adopted to predict the functions of lncRNAs. A total of 77,382 cells during the differentiation process of hESCs toward pancreatic progenitors were sequenced. According to the single-cell map, the cells from different time points were authenticated to constitute a relatively homogeneous population, in which a total of 7382 lncRNAs could be detected. Through further analyzing the time course data, conserved and specific expression features of lncRNAs during hESC differentiation were revealed. Based upon pseudotime analysis, 52 pseudotime-associated lncRNAs that grouped into three distinct expression patterns were identified. We also implemented MetaCell algorithm and network-based methods to explore the functional mechanisms of these lncRNAs. Totally, 464 lncRNAs, including 49 pseudotime-associated lncRNAs were functionally annotated by either module-based or hub-based methods. Most importantly, we demonstrated that the lncRNA HOTAIRM1, which co-localized and co-expressed with several HOX genes, may play crucial role in the generation of pancreatic progenitors through regulation of exocytosis and retinoic acid receptor signaling pathway. Our single-cell analyses provide valuable data resources for biological researchers and novel insights into hESC differentiation processes, which will guide future endeav