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《Developmental cell》2022,57(17):2127-2139.e6
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Deep learning is making major breakthrough in several areas of bioinformatics. Anticipating that this will occur soon for the single-cell RNA-seq data analysis, we review newly published deep learning methods that help tackle computational challenges. Autoencoders are found to be the dominant approach. However, methods based on deep generative models such as generative adversarial networks (GANs) are also emerging in this area. 相似文献
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Zhejun Chen Ting Zhang Kaiqiong Mao Xinghua Shao Yao Xu Minyan Zhu Hang Zhou Qin Wang Zhenyuan Li YuanYuan Xie Xiaodong Yuan Liang Ying Ming Zhang Jiajia Hu Shan Mou 《Journal of cellular and molecular medicine》2021,25(10):4684-4695
Glomerulonephritis is the one of the major causes of the end-stage kidney disease, whereas the pathological process of glomerulonephritis is still not completely understood. Single-cell RNA sequencing (scRNA-seq) emerges to be a powerful tool to evaluate the full heterogeneity of kidney diseases. To reveal cellular gene expression profiles of glomerulonephritis, we performed scRNA-seq of 2 human kidney transplantation donor samples, 4 human glomerulonephritis samples, 1 human malignant hypertension (MH) sample and 1 human chronic interstitial nephritis (CIN) sample, all tissues were taken from the biopsy. After filtering the cells with < 200 genes and > 10% mitochondria (MT) genes, the resulting 14 932 cells can be divided into 20 cell clusters, consistently with the previous report, in disease samples dramatic immune cells infiltration was found, among which a proximal tubule (PT) subset characterized by wnt-β catenin activation and a natural killer T (NKT) subset high expressing LTB were found. Furthermore, in the cluster of the podocyte, three glomerulonephritis related genes named FXYD5, CD74 and B2M were found. Compared with the mesangial of donor, the gene CLIC1 and RPS26 were up-regulated in mesangial of IgA nephropathy(IgAN), whereas the gene JUNB was up-regulated in podocyte of IgAN in comparison with that of donor. Meanwhile, some membranous nephropathy (MN) high expressed genes such as HLA-DRB5, HLA-DQA2, IFNG, CCL2 and NR4A2, which involve in highest enrichment pathway, display the cellular-specific expression style, whereas monocyte marker of lupus nephritis (LN) named TNFSF13B was also found and interferon alpha/beta signalling pathway was enriched in B and NKT of LN comparing with donor. By scRNA-seq, we first defined the podocyte markers of glomerulonephritis and specific markers in IgA, MN and LN were found at cellular level. Furthermore, the critical role of interferon alpha/beta signalling pathway was enriched in B and NKT of LN was declared. 相似文献
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Jesse K. Niehaus Bonnie Taylor-Blake Lipin Loo Jeremy M. Simon Mark J. Zylka 《Neuron》2021,109(8):1274-1282.e6
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Makoto Kashima Rei Komura Yuki Sato Chikara Hashimoto Hiromi Hirata 《Development, growth & differentiation》2024,66(1):43-55
The freshwater planarian Dugesia japonica maintains an abundant heterogeneous cell population called neoblasts, which include adult pluripotent stem cells. Thus, it is an excellent model organism for stem cell and regeneration research. Recently, many single-cell RNA sequencing (scRNA-seq) databases of several model organisms, including other planarian species, have become publicly available; these are powerful and useful resources to search for gene expression in various tissues and cells. However, the only scRNA-seq dataset for D. japonica has been limited by the number of genes detected. Herein, we collected D. japonica cells, and conducted an scRNA-seq analysis. A novel, automatic, iterative cell clustering strategy produced a dataset of 3,404 cells, which could be classified into 63 cell types based on gene expression profiles. We introduced two examples for utilizing the scRNA-seq dataset in this study using D. japonica. First, the dataset provided results consistent with previous studies as well as novel functionally relevant insights, that is, the expression of DjMTA and DjP2X-A genes in neoblasts that give rise to differentiated cells. Second, we conducted an integrative analysis of the scRNA-seq dataset and time-course bulk RNA-seq of irradiated animals, demonstrating that the dataset can help interpret differentially expressed genes captured via bulk RNA-seq. Using the R package “Seurat” and GSE223927, researchers can easily access and utilize this dataset. 相似文献