page_title: RNA-Seq
section_title: Library preparation
hierarchical_section_title: RNA-Seq / Methods / Library preparation
caption_attribution_description: English: "RNA-seq data generation. A typical RNA-seq experimental workflow involves the isolation of RNA from samples of interest, generation of sequencing libraries, use of a high-throughput sequencer to produce hundreds of millions of short paired-end reads, alignment of reads against a reference genome or transcriptome, and downstream analysis for expression estimation, differential expression, transcript isoform discovery, and other applications. Refer to S1 Table, S3 Table, and S7 Table for more details on the concepts depicted in this figure." Image taken from Figure 2 in Griffith, Malachi; Walker, Jason R.; Spies, Nicholas C.; Ainscough, Benjamin J.; Griffith, Obi L. (2015). "Informatics for RNA Sequencing: A Web Resource for Analysis on the Cloud". PLOS Computational Biology. 11 (8): e1004393. doi:10.1371/journal.pcbi.1004393. ISSN 1553-7358.
context_page_description: RNA-Seq is a particular technology-based sequencing technique which uses next-generation sequencing to reveal the presence and quantity of RNA in a biological sample at a given moment, analyzing the continuously changing cellular transcriptome.
  Specifically, 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 and in situ sequencing of fixed tissue.
  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.
context_section_description: The general steps to prepare a complementary DNA (cDNA) library for sequencing are described below, but often vary between platforms.
  RNA Isolation: RNA is isolated from tissue and mixed with deoxyribonuclease (DNase). DNase reduces the amount of genomic DNA. The amount of RNA degradation is checked with gel and capillary electrophoresis and is used to assign an RNA integrity number to the sample. This RNA quality and the total amount of starting RNA are taken into consideration during the subsequent library preparation, sequencing, and analysis steps.
  RNA selection/depletion: To analyze signals of interest, the isolated RNA can either be kept as is, depleted of ribosomal RNA (rRNA), filtered for RNA with 3' polyadenylated (poly(A)) tails to include only mRNA,  and/or filtered for RNA that binds specific sequences (RNA selection and depletion methods table, below). In eukaryotes, the RNA with 3' poly(A) tails are mature, processed, coding sequences. Poly(A) selection is performed by mixing the eukaryotic RNA with poly(T) oligomers covalently attached to a substrate, typically magnetic beads. Poly(A) selection ignores noncoding RNA and introduces 3' bias, which is avoided with the ribosomal depletion strategy. The rRNA is removed because it represents over 90% of the RNA in a cell, which if kept would drown out other data in the transcriptome.
  cDNA synthesis: RNA is reverse transcribed to cDNA because DNA is more stable and to allow for amplification (which uses DNA polymerases) and leverage more mature DNA sequencing technology. Amplification subsequent to reverse transcription results in loss of strandedness, which can be avoided with chemical labeling or single molecule sequencing. Fragmentation and size selection are performed to purify sequences that are the appropriate length for the sequencing machine. The RNA, cDNA, or both are fragmented with enzymes, sonication, or nebulizers. Fragmentation of the RNA reduces 5' bias of randomly primed-reverse transcription and the influence of primer binding sites, with the downside that the 5' and 3' ends are converted to DNA less efficiently. Fragmentation is followed by size selection, where either small sequences are removed or a tight range of sequence lengths are selected. Because small RNAs like miRNAs are lost, these are analyzed independently. The cDNA for each experiment can be indexed with a hexamer or octamer barcode, so that these experiments can be pooled into a single lane for multiplexed sequencing.
caption: Overview of a typical RNA-Seq experimental workflow.[8]
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