期刊
IMMUNITY
卷 53, 期 4, 页码 878-+出版社
CELL PRESS
DOI: 10.1016/j.immuni.2020.09.015
关键词
-
类别
资金
- NIH [P30CA14051, 5P01AI039671, 1DP2GM1194192, U19AI0899922, R01HL0957911, U54CA2173772, P01AI 0396715, U24AI1186722, RM1HG0061931]
- Koch Institute for Integrative Cancer Research at MIT
- DanaFarber/Harvard Cancer Center
- Food Allergy Science Initiative at the Broad Institute
- Searle Scholars Program
- Beckman Young Investigator Program
- Pew-Stewart Scholars Program for Cancer Research
- Sloan Fellowship in Chemistry
- Bill and Melinda Gates Foundation [OPP1139972, OPP1202327, OPP1137006]
- Taubman Medical Research Institute
- Damon Runyon Cancer Research Foundation [DRG-2274-16]
- Richard and Susan Smith Family Foundation
- [R33CA2028201]
- [R01AI1385461]
- [R01HL1265541]
- [R01DA0462771]
- [U2CCA23319501]
- [5U19AI089992]
- [R01A R060802]
- [R01AI30025]
- [P30AR075043]
- [R01AI022553]
- [R01AR040312]
- [F30AI143160]
- [R01AR074302]
- Bill and Melinda Gates Foundation [OPP1137006, OPP1139972, OPP1202327] Funding Source: Bill and Melinda Gates Foundation
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. Neverthe-less, 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 S-3 (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 S-3 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 S-3 to chart the transcriptional landscape of five human inflammatory skin diseases, thus providing a resource for the further study of human skin inflammation.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据