Optimized single-nucleus transcriptional profiling by combinatorial indexing.
Optimized single-nucleus transcriptional profiling by combinatorial indexing.
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DOI：
10.1038/s41596-022-00752-0
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发表时间：
2023-01
期刊：
影响因子：
14.8
通讯作者：
Shendure, Jay
中科院分区：
文献类型：
--
作者：
Martin, Beth K.;Qiu, Chengxiang;Nichols, Eva;Phung, Melissa;Green-Gladden, Rula;Srivatsan, Sanjay;Blecher-Gonen, Ronnie;Beliveau, Brian J.;Trapnell, Cole;Cao, Junyue;Shendure, Jay
单细胞组合索引RNA测序（sci-RNA-seq）是一种从指数级扩展的单个细胞或细胞核中恢复基因表达数据的强大方法。然而，sci-RNA-seq是一种复杂的方案，历史上在不同组织上表现出不同的性能，而且灵敏度低于其他方法。在这里，我们报告了一个简化的、优化的三级sci-RNA-seq方案，它比原来的sci-RNA-seq3方案更快、产量更高、更健壮、更敏感，每个细胞的试剂成本在1美分左右或更低。从核分离到最终的文库准备，总动手时间需要2到3天，具体取决于共享实验的样品数量。这些改进还允许从富含RNA酶的组织中提取RNA谱，比如老年小鼠胚胎或成年组织，这些组织在最初的方法中是有问题的。我们通过E16.5小鼠胚胎的全生物体分析展示了优化的方案，单次实验分析了约38万个细胞核。最后，我们为输入材料非常有限的实验引入了“Tiny-Sci”协议。
Single cell combinatorial indexing RNA sequencing (sci-RNA-seq) is a powerful method for recovering gene expression data from an exponentially scalable number of individual cells or nuclei. However, sci-RNA-seq is a complex protocol that has historically exhibited variable performance on different tissues, as well as lower sensitivity than alternative methods. Here we report a simplified, optimized version of the three-level sci-RNA-seq protocol that is faster, higher yield, more robust, and more sensitive, than the original sci-RNA-seq3 protocol, with reagent costs on the order of 1 cent per cell or less. The total hands-on time from nuclei isolation to final library preparation takes 2 to 3 days, depending on the number of samples sharing the experiment. The improvements also allow RNA profiling from tissues rich in RNases like older mouse embryos or adult tissues that were problematic for the original method. We showcase the optimized protocol via whole organism analysis of an E16.5 mouse embryo, profiling ~380,000 nuclei in a single experiment. Finally, we introduce a “Tiny-Sci” protocol for experiments where input material is very limited.
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影响因子：
64.8
作者：
Cao, Junyue;Spielmann, Malte;Shendure, Jay
通讯作者：
Shendure, Jay
影响因子：
48
作者：
Vitak SA;Torkenczy KA;Rosenkrantz JL;Fields AJ;Christiansen L;Wong MH;Carbone L;Steemers FJ;Adey A
通讯作者：
Adey A
用于高通量单细胞表观基因组分析的 CoBATCH
影响因子：
16
作者：
Wang, Qianhao;Xiong, Haiqing;He, Aibin
通讯作者：
He, Aibin
影响因子：
48
作者：
Ramani V;Deng X;Qiu R;Gunderson KL;Steemers FJ;Disteche CM;Noble WS;Duan Z;Shendure J
通讯作者：
Shendure J
影响因子：
48
作者：
Hwang B;Lee DS;Tamaki W;Sun Y;Ogorodnikov A;Hartoularos GC;Winters A;Yeung BZ;Nazor KL;Song YS;Chow ED;Spitzer MH;Ye CJ
通讯作者：
Ye CJ