Literature DB >> 31028639

Single-Cell Dosing and mRNA Sequencing of Suspension and Adherent Cells Using the PolarisTM System.

Chad D Sanada1, Aik T Ooi2.   

Abstract

Single-cell functional analysis provides a natural next step in the now widely adopted single-cell mRNA sequencing studies. Functional studies can be designed to study cellular context by using single-cell culture, perturbation, manipulation, or treatment. Here we present a method for a functional study of 48 single cells by single-cell isolation, dosing, and mRNA sequencing with an integrated fluidic circuit (IFC) on the Fluidigm® Polaris™ system. The major procedures required to execute this protocol are (1) cell preparation and staining; (2) priming, single-cell selection, cell dosing, cell staining, and cDNA generation on the Polaris IFC; and (3) preparation and sequencing of single-cell mRNA-seq libraries. The cell preparation and staining steps employ the use of a universal tracking dye to trace all cells that enter the IFC, while additional fluorescence dyes chosen by the user can be used to differentiate cell types in the overall mix. The steps on the Polaris IFC follow standard protocols, which are also described in the Fluidigm user documentation. The library preparation step adds Illumina® Nextera® XT indexes to the cDNA generated on the Polaris IFC. The resulting sequencing libraries can be sequenced on any Illumina sequencing platform.

Keywords:  Adherent culture; Differentiation; Dose response; Extracellular matrix (ECM); Microfluidics; Phenotype–genotype correlation; Single-cell functional study; Single-cell perturbation; Time course; Time-lapse imaging

Mesh:

Substances:

Year:  2019        PMID: 31028639     DOI: 10.1007/978-1-4939-9240-9_12

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  2 in total

Review 1.  Single-Cell RNA Sequencing and Its Combination with Protein and DNA Analyses.

Authors:  Jane Ru Choi; Kar Wey Yong; Jean Yu Choi; Alistair C Cowie
Journal:  Cells       Date:  2020-05-04       Impact factor: 6.600

2.  Modeling expression ranks for noise-tolerant differential expression analysis of scRNA-seq data.

Authors:  Krishan Gupta; Manan Lalit; Aditya Biswas; Chad D Sanada; Cassandra Greene; Kyle Hukari; Ujjwal Maulik; Sanghamitra Bandyopadhyay; Naveen Ramalingam; Gaurav Ahuja; Abhik Ghosh; Debarka Sengupta
Journal:  Genome Res       Date:  2021-03-05       Impact factor: 9.043

  2 in total

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