计算生物学
单细胞测序
合成生物学
可扩展性
巨量平行
生物
清脆的
DNA测序
表型
计算机科学
遗传学
外显子组测序
基因
并行计算
数据库
作者
David Feldman,Luke Funk,Anna Le,Rebecca J. Carlson,Michael D. Leiken,FuNien Tsai,Brian Y. Soong,Avtar Singh,Paul C. Blainey
出处
期刊:Nature Protocols
[Springer Nature]
日期:2022-01-12
卷期号:17 (2): 476-512
被引量:33
标识
DOI:10.1038/s41596-021-00653-8
摘要
Discovery of the genetic components underpinning fundamental and disease-related processes is being rapidly accelerated by combining efficient, programmable genetic engineering with phenotypic readouts of high spatial, temporal and/or molecular resolution. Microscopy is a fundamental tool for studying cell biology, but its lack of high-throughput sequence readouts hinders integration in large-scale genetic screens. Optical pooled screens using in situ sequencing provide massively scalable integration of barcoded lentiviral libraries (e.g., CRISPR perturbation libraries) with high-content imaging assays, including dynamic processes in live cells. The protocol uses standard lentiviral vectors and molecular biology, providing single-cell resolution of phenotype and engineered genotype, scalability to millions of cells and accurate sequence reads sufficient to distinguish >106 perturbations. In situ amplification takes ~2 d, while sequencing can be performed in ~1.5 h per cycle. The image analysis pipeline provided enables fully parallel automated sequencing analysis using a cloud or cluster computing environment. In this protocol, CRISPR perturbations are introduced in cells using lentiviral libraries and read out using in situ sequencing, coupling high-throughput pooled screening with phenotypic image readouts in live or fixed cells.
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