工作流程
吞吐量
计算机科学
计算生物学
RNA序列
多路复用
分析
转录组
数据挖掘
生物
基因
基因表达
遗传学
电信
无线
数据库
作者
Xiang Li,David Yoannidis,Susanne Ramm,Jennii Luu,Gisela Mir Arnau,Timothy Semple,Kaylene J. Simpson
出处
期刊:Methods in molecular biology
日期:2023-01-01
卷期号:: 279-325
被引量:1
标识
DOI:10.1007/978-1-0716-3331-1_22
摘要
Transcriptomic profiling has fundamentally influenced our understanding of cancer pathophysiology and response to therapeutic intervention and has become a relatively routine approach. However, standard protocols are usually low-throughput, single-plex assays and costs are still quite prohibitive. With the evolving complexity of in vitro cell model systems, there is a need for resource-efficient high-throughput approaches that can support detailed time-course analytics, accommodate limited sample availability, and provide the capacity to correlate phenotype to genotype at scale. MAC-seq (multiplexed analysis of cells) is a low-cost, ultrahigh-throughput RNA-seq workflow in plate format to measure cell perturbations and is compatible with high-throughput imaging. Here we describe the steps to perform MAC-seq in 384-well format and apply it to 2D and 3D cell cultures. On average, our experimental conditions identified over ten thousand expressed genes per well when sequenced to a depth of one million reads. We discuss technical aspects, make suggestions on experimental design, and document critical operational procedures. Our protocol highlights the potential to couple MAC-seq with high-throughput screening applications including cell phenotyping using high-content cell imaging.
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