RNA-Seq (short for RNA sequencing) is a next-generation sequencing (NGS) technique used to quantify and identify RNA molecules in a biological sample, providing a snapshot of the transcriptome at a specific time. It enables transcriptome-wide analysis by sequencing cDNA derived from RNA. Modern workflows often incorporate pseudoalignment tools (such as Kallisto and Salmon) and cloud-based processing pipelines, improving speed, scalability, and reproducibility.

RNA-Seq facilitates the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression over time, or differences in gene expression in different groups or treatments. In addition to mRNA transcripts, RNA-Seq can look at different populations of RNA to include total RNA, small RNA, such as miRNA, tRNA, and ribosomal profiling. RNA-Seq can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries. Recent advances in RNA-Seq include single cell sequencing, bulk RNA sequencing, 3' mRNA-sequencing, in situ sequencing of fixed tissue, and native RNA molecule sequencing with single-molecule real-time sequencing. Other examples of emerging RNA-Seq applications due to the advancement of bioinformatics algorithms are copy number alteration, microbial contamination, transposable elements, cell type (deconvolution) and the presence of neoantigens.

Prior to RNA-Seq, gene expression studies were done with hybridization-based microarrays. Issues with microarrays include cross-hybridization artifacts, poor quantification of lowly and highly expressed genes, and needing to know the sequence a priori. Because of these technical issues, transcriptomics transitioned to sequencing-based methods. These progressed from Sanger sequencing of Expressed sequence tag libraries, to chemical tag-based methods (e.g., serial analysis of gene expression), and finally to the current technology, next-gen sequencing of complementary DNA (cDNA), notably RNA-Seq in mid 2000s.

The first manuscripts that used RNA-Seq even without using the term includes those of prostate cancer cell lines (dated 2006), Medicago truncatula (2006), maize (2007), while the term "RNA-Seq" itself was first mentioned in 2008 . The number of manuscripts referring to RNA-Seq in the title or abstract (Figure, blue line) is continuously increasing with 6754 manuscripts published in 2018. The intersection of RNA-Seq and medicine (Figure, gold line) has similar celerity.

The general steps to prepare a complementary DNA (cDNA) library for sequencing are described below, but often vary between platforms.

The cDNA library derived from RNA biotypes is then sequenced into a computer-readable format. There are many high-throughput sequencing technologies for cDNA sequencing including platforms developed by Illumina, Thermo Fisher, BGI/MGI, PacBio, and Oxford Nanopore Technologies. For Illumina short-read sequencing, a common technology for cDNA sequencing, adapters are ligated to the cDNA, DNA is attached to a flow cell, clusters are generated through cycles of bridge amplification and denaturing, and sequence-by-synthesis is performed in cycles of complementary strand synthesis and laser excitation of bases with reversible terminators. Sequencing platform choice and parameters are guided by experimental design and cost. Common experimental design considerations include deciding on the sequencing length, sequencing depth, use of single versus paired-end sequencing, number of replicates, multiplexing, randomization, and spike-ins.

When sequencing RNA other than mRNA, the library preparation is modified. The cellular RNA is selected based on the desired size range. For small RNA targets, such as miRNA, the RNA is isolated through size selection. This can be performed with a size exclusion gel, through size selection magnetic beads, or with a commercially developed kit. Once isolated, linkers are added to the 3' and 5' end then purified. The final step is cDNA generation through reverse transcription.

Because converting RNA into cDNA, ligation, amplification, and other sample manipulations have been shown to introduce biases and artifacts that may interfere with both the proper characterization and quantification of transcripts, single molecule direct RNA sequencing has been explored by companies including Helicos (bankrupt), Oxford Nanopore Technologies, and others. This technology sequences RNA molecules directly in a massively-parallel manner.