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科学家利用scRNA-Seq绘制人类炎症性皮肤病转录图谱
作者:小柯机器人 发布时间:2020/10/14 16:26:16

美国麻省理工学院和哈佛大学广泛研究所Alex K. Shalek和J. Christopher Love团队合作近日取得一项新成果。他们进行基于第二链合成的大规模平行单细胞RNA测序(scRNA-seq),揭示了人类炎症性皮肤病的细胞状态和分子特征。这一研究成果发表在2020年10月13日出版的国际学术期刊《免疫》上。

要精确研究细胞关键表型特征的表达,需要高保真度和高通量的scRNA-seq平台。为了满足此需求,他们创建了Seq-Well S3(“第二链合成”),这是一种大规模并行的scRNA-seq方案,使用随机引发的第二链合成来回复互补DNA(cDNA)分子,这些分子成功地被逆转录,但由于模板转换效率低,未进行第二个寡核苷酸处理(随后的整个转录组扩增必需)。

与以前的迭代相比,Seq-Well S3的转录本捕获和基因检测效率分别提高了10倍和5倍。他们使用Seq-Well S3绘制了五种人类炎症性皮肤病的转录图谱,从而为进一步研究人类皮肤炎症提供了资源。

据悉,通量scRNA-seq方法可通过增加可同时分析的细胞数量来表征复杂的生物样品。然而,与低通量策略相比,这些方法在每个细胞得到的信息更少。

附:英文原文

Title: Second-Strand Synthesis-Based Massively Parallel scRNA-Seq Reveals Cellular States and Molecular Features of Human Inflammatory Skin Pathologies

Author: Travis K. Hughes, Marc H. Wadsworth, Todd M. Gierahn, Tran Do, David Weiss, Priscila R. Andrade, Feiyang Ma, Bruno J. de Andrade Silva, Shuai Shao, Lam C. Tsoi, Jose Ordovas-Montanes, Johann E. Gudjonsson, Robert L. Modlin, J. Christopher Love, Alex K. Shalek

Issue&Volume: 2020/10/13

Abstract: High-throughput single-cell RNA-sequencing (scRNA-seq) methodologies enable characterization of complex biological samples by increasing the number of cells that can be profiled contemporaneously. Nevertheless, these approaches recover less information per cell than low-throughput strategies. To accurately report the expression of key phenotypic features of cells, scRNA-seq platforms are needed that are both high fidelity and high throughput. To address this need, we created Seq-Well S3 (“Second-Strand Synthesis”), a massively parallel scRNA-seq protocol that uses a randomly primed second-strand synthesis to recover complementary DNA (cDNA) molecules that were successfully reverse transcribed but to which a second oligonucleotide handle, necessary for subsequent whole transcriptome amplification, was not appended due to inefficient template switching. Seq-Well S3 increased the efficiency of transcript capture and gene detection compared with that of previous iterations by up to 10- and 5-fold, respectively. We used Seq-Well S3 to chart the transcriptional landscape of five human inflammatory skin diseases, thus providing a resource for the further study of human skin inflammation.

DOI: 10.1016/j.immuni.2020.09.015

Source: https://www.cell.com/immunity/fulltext/S1074-7613(20)30409-X

期刊信息

Immunity:《免疫》,创刊于1994年。隶属于细胞出版社,最新if:21.522
官方网址:https://www.cell.com/immunity/home
投稿链接:https://www.editorialmanager.com/immunity/default.aspx