Simultaneous single-nucleus RNA sequencing and single-nucleus ATAC sequencing of neuroblastoma cell lines.

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2024-11-07 DOI:10.1038/s41597-024-04061-x
Richard A Guyer, Jessica L Mueller, Nicole Picard, Allan M Goldstein
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Abstract

Neuroblastoma is the most common extracranial solid tumor in children, and a leading cause of childhood cancer deaths. All neuroblastomas arise from neural crest-derived sympathetic neuronal progenitors, but numerous mutations, the most common of which is MYCN amplification, give rise to these lesions. Epigenetic aberrations also play a role in oncogenesis and tumor progression. To better understand biologic diversity of neuroblastomas, we performed joint single-nucleus ATAC sequencing and single-nucleus RNA sequencing on six neuroblastoma cell lines, three of which are MYCN amplified. After standard filtering for high-quality nuclei, we obtained chromatin accessibility and transcript abundance data from 41,733 neuroblastoma tumor cells. Preliminary analysis reveals significant diversity in chromatin landscape and gene expression across neuroblastoma cell lines. This dataset is a valuable resource for studying the transcriptional and epigenetic mechanisms of this deadly childhood disease.

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同时对神经母细胞瘤细胞系进行单核 RNA 测序和单核 ATAC 测序。
神经母细胞瘤是儿童最常见的颅外实体瘤,也是儿童癌症死亡的主要原因。所有神经母细胞瘤都源于神经嵴交感神经元祖细胞,但有许多突变,其中最常见的是 MYCN 扩增,导致了这些病变。表观遗传畸变也在肿瘤发生和发展过程中发挥着作用。为了更好地了解神经母细胞瘤的生物多样性,我们对六种神经母细胞瘤细胞系进行了单核 ATAC 测序和单核 RNA 测序。在对高质量细胞核进行标准过滤后,我们获得了来自 41,733 个神经母细胞瘤肿瘤细胞的染色质可及性和转录本丰度数据。初步分析显示,不同神经母细胞瘤细胞系的染色质景观和基因表达存在显著差异。这个数据集是研究这种致命儿童疾病的转录和表观遗传机制的宝贵资源。
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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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