MAC-Seq: Coupling Low-Cost, High-Throughput RNA-Seq with Image-Based Phenotypic Screening in 2D and 3D Cell Models
- Author(s)
- Li, XM; Yoannidis, D; Ramm, S; Luu, J; Arnau, GM; Semple, T; Simpson, KJ;
- Journal Title
- In: Jenkins, B.J. (ed) Inflammation and Cancer. Methods in Molecular Biology, vol 2691.
- Publication Type
- Book section
- Abstract
- 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.
- Publisher
- Humana, New York, NY
- Keywords
- RNA-Seq/methods; *High-Throughput Nucleotide Sequencing/methods; *Gene Expression Profiling/methods; Phenotype; High-Throughput Screening Assays/methods; Sequence Analysis, RNA/methods; 3D cell models; High-content imaging; High-throughput screening; Multiplexing; RNA-seq
- Department(s)
- Laboratory Research
- PubMed ID
- 37355554
- Publisher's Version
- https://doi.org/10.1007/978-1-0716-3331-1_22
- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2023-10-04 03:42:06
Last Modified: 2024-07-09 05:49:48