Transcriptomic profiling by RNA sequencing (RNA-Seq) represents the preferred approach to measure genome-wide gene expression for understanding cellular function, tissue development, disease pathogenesis, as well as to identify potential biomarkers and therapeutic targets. For samples with small cell numbers, multiple methods have been described to increase the efficiency of library preparation and to reduce hands-on time and costs. This chapter reviews our approach, which combines flow cytometry and the most recent high-resolution techniques to perform RNA-Seq for samples with low cell numbers as well as for single-cell samples. Our approach reduces technical variability while increasing sensitivity and efficiency. Thus, it is well-suited for large-scale gene expression profiling studies with limited samples for basic and clinical studies.
Keywords: Low-input RNA; RNA-Seq; Single-cell RNA-Seq; Smart-Seq2; Transcriptomics.