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      Genomic characteristics of adipose-derived stromal cells induced into neurons based on single-cell RNA sequencing

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          Abstract

          Adipose-derived stromal cells (ADSCs) can be induced to differentiate into neurons, representing the most promising avenue for cell therapy. However, the molecular mechanism and genomic characteristics of the differentiation of ADSCs into neurons remain poorly understood. In this study, cells from the adult ADSCs group, induction 1h, 3h, 5h, 6h, and 8h groups were selected for single-cell RNA sequencing (scRNA-Seq). Samples from these seven-time points were sequenced and analyzed. The expression of neuron marker genes, including NES, MAP2, TMEM59L, PTK2B, CHN1, DNM1, NRSN2, FBLN2, SCAMP1, SLC1A1, DLG4, CDK5, and ENO2, was found to be low in the ADSCs group, but highly expressed in differentiated cell clusters. The expression of stem cell marker genes, including CCND1, IL1B, MMP1, MMP3, MYO10, and BMP2, was the highest in the ADSCs cluster. This expression decreased significantly with the extension of induction time. Gene ontology (GO) enrichment analysis of upregulated genes in the induced samples showed that the biological processes related to neuronal differentiation and development, such as neuronal differentiation, projection, and apoptosis, were significantly upregulated with a longer induction time during cell cluster differentiation. The results of the cell communication analysis demonstrated the gradual formation of complex neural network connections between ADSC-derived neurons through receptor and ligand pairs at 5h after the induction of differentiation.

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            fastp: an ultra-fast all-in-one FASTQ preprocessor

            Abstract Motivation Quality control and preprocessing of FASTQ files are essential to providing clean data for downstream analysis. Traditionally, a different tool is used for each operation, such as quality control, adapter trimming and quality filtering. These tools are often insufficiently fast as most are developed using high-level programming languages (e.g. Python and Java) and provide limited multi-threading support. Reading and loading data multiple times also renders preprocessing slow and I/O inefficient. Results We developed fastp as an ultra-fast FASTQ preprocessor with useful quality control and data-filtering features. It can perform quality control, adapter trimming, quality filtering, per-read quality pruning and many other operations with a single scan of the FASTQ data. This tool is developed in C++ and has multi-threading support. Based on our evaluation, fastp is 2–5 times faster than other FASTQ preprocessing tools such as Trimmomatic or Cutadapt despite performing far more operations than similar tools. Availability and implementation The open-source code and corresponding instructions are available at https://github.com/OpenGene/fastp.
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              SCENIC: Single-cell regulatory network inference and clustering

              Although single-cell RNA-seq is revolutionizing biology, data interpretation remains a challenge. We present SCENIC for the simultaneous reconstruction of gene regulatory networks and identification of cell states. We apply SCENIC to a compendium of single-cell data from tumors and brain, and demonstrate that the genomic regulatory code can be exploited to guide the identification of transcription factors and cell states. SCENIC provides critical biological insights into the mechanisms driving cellular heterogeneity.
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                Author and article information

                Contributors
                Journal
                Heliyon
                Heliyon
                Heliyon
                Elsevier
                2405-8440
                14 June 2024
                30 June 2024
                14 June 2024
                : 10
                : 12
                : e33079
                Affiliations
                [a ]Department of Neurology of Kailuan General Hospital Affiliated North China University of Science and Technology, China
                [b ]Hebei Provincial Key Laboratory of Neurobiological Function, China
                Author notes
                [* ]Corresponding author. Department of Neurology, Kailuan General Hospital affiliated North China University of Science and Technology; addresses: 57 Xinhua East Road, Lubei District, Tangshan City, Hebei Province, 063000, China. yxd69@ 123456sohu.com
                [** ]Corresponding author. Pingshu Zhang. Department of Neurology, Kailuan General Hospital affiliated North China University of Science and Technology; addresses: 57 Xinhua East Road, Lubei District, Tangshan City, Hebei Province, 063000, China. 1977nana@ 123456sina.com
                [1]

                Xiaodong Yuan and Wen Li are Joint first authors.

                Article
                S2405-8440(24)09110-2 e33079
                10.1016/j.heliyon.2024.e33079
                11231542
                38984299
                9156a1af-37f9-4047-8e7c-cc64f975d42b
                © 2024 The Authors

                This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

                History
                : 27 June 2023
                : 13 June 2024
                : 13 June 2024
                Categories
                Research Article

                adipose-derived stromal cells,induced differentiation response,neurons,single-cell rna sequencing,gene,transcription factor

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