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使用TempO-LINC进行的高通量基因表达分析能够在单细胞分辨率下灵敏地解析复杂的脑、肺和肾组织异质性。

High-throughput gene expression analysis with TempO-LINC sensitively resolves complex brain, lung and kidney heterogeneity at single-cell resolution.

作者信息

Eastburn Dennis J, White Kevin S, Jayne Nathan D, Camiolo Salvatore, Montis Gioele, Ha Seungeun, Watson Kendall G, Yeakley Joanne M, McComb Joel, Seligmann Bruce

机构信息

BioSpyder Technologies, Inc., Carlsbad, CA.

出版信息

bioRxiv. 2024 Aug 6:2024.08.03.606484. doi: 10.1101/2024.08.03.606484.

DOI:10.1101/2024.08.03.606484
PMID:39149288
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11326174/
Abstract

We report the development and performance of a novel genomics platform, TempO-LINC, for conducting high-throughput transcriptomic analysis on single cells and nuclei. TempO-LINC works by adding cell-identifying molecular barcodes onto highly selective and high-sensitivity gene expression probes within fixed cells, without having to first generate cDNA. Using an instrument-free combinatorial-indexing approach, all probes within the same fixed cell receive an identical barcode, enabling the reconstruction of single-cell gene expression profiles across as few as several hundred cells and up to 100,000+ cells per run. The TempO-LINC approach is easily scalable based on the number of barcodes and rounds of barcoding performed; however, for the experiments reported in this study, the assay utilized over 5.3 million unique barcodes. TempO-LINC has a robust protocol for fixing and banking cells and displays high-sensitivity gene detection from multiple diverse sample types. We show that TempO-LINC has an observed multiplet rate of less than 1.1% and a cell capture rate of ~50%. Although the assay can accurately profile the whole transcriptome (19,683 human or 21,400 mouse genes), it can be targeted to measure only actionable/informative genes and molecular pathways of interest - thereby reducing sequencing requirements. In this study, we applied TempO-LINC to profile the transcriptomes of 89,722 cells across multiple sample types, including nuclei from mouse lung, kidney and brain tissues. The data demonstrated the ability to identify and annotate at least 50 unique cell populations and positively correlate expression of cell type-specific molecular markers within them. TempO-LINC is a robust new single-cell technology that is ideal for large-scale applications/studies across thousands of samples with high data quality.

摘要

我们报告了一种新型基因组学平台TempO-LINC的开发和性能,该平台用于对单细胞和单细胞核进行高通量转录组分析。TempO-LINC的工作原理是在固定细胞内的高选择性和高灵敏度基因表达探针上添加细胞识别分子条形码,而无需先生成cDNA。使用无仪器的组合索引方法,同一固定细胞内的所有探针都接收相同的条形码,从而能够重建每次运行低至数百个细胞、高达100,000多个细胞的单细胞基因表达谱。TempO-LINC方法可根据所执行的条形码数量和条形码轮数轻松扩展;然而,对于本研究中报告的实验,该检测使用了超过530万个独特的条形码。TempO-LINC具有用于固定和保存细胞的稳健方案,并能从多种不同样本类型中进行高灵敏度基因检测。我们表明,TempO-LINC的观察到的多重率低于1.1%,细胞捕获率约为50%。尽管该检测可以准确描绘整个转录组(19,683个人类基因或21,400个小鼠基因),但它也可以针对性地仅测量感兴趣的可操作/信息性基因和分子途径,从而降低测序要求。在本研究中,我们应用TempO-LINC对多种样本类型的89,722个细胞的转录组进行分析,包括来自小鼠肺、肾和脑组织的细胞核。数据表明,该方法能够识别和注释至少50个独特的细胞群,并使其中细胞类型特异性分子标记的表达呈正相关。TempO-LINC是一种强大的新型单细胞技术,非常适合对数千个样本进行大规模应用/研究,并具有高质量的数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4723/11326174/f561b8f52214/nihpp-2024.08.03.606484v1-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4723/11326174/d1d5cf9000ce/nihpp-2024.08.03.606484v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4723/11326174/b395be4c9541/nihpp-2024.08.03.606484v1-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4723/11326174/6b7e2584ebda/nihpp-2024.08.03.606484v1-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4723/11326174/639dae61b5fe/nihpp-2024.08.03.606484v1-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4723/11326174/f561b8f52214/nihpp-2024.08.03.606484v1-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4723/11326174/d1d5cf9000ce/nihpp-2024.08.03.606484v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4723/11326174/b395be4c9541/nihpp-2024.08.03.606484v1-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4723/11326174/6b7e2584ebda/nihpp-2024.08.03.606484v1-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4723/11326174/639dae61b5fe/nihpp-2024.08.03.606484v1-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4723/11326174/f561b8f52214/nihpp-2024.08.03.606484v1-f0005.jpg

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