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Transcriptome analysis: RNA-seq

Overview:

RNA-seq is an high throughput technology used to identify the presence and the quantity of RNA in a biological sample in a given moment. It provides far more precise measurement of levels of transcripts and their isoforms than other methods, allowing researchers to better analyze the transcriptome: the the complete set of transcripts in a cell, and their quantity, for a specific developmental stage or physiological/pathological condition. The key aims of transcriptomics are: 

• to catalogue all species of transcript, including mRNAs, non-coding RNAs and small RNAs; 
• to determine the transcriptional structure of genes, in terms of their start sites, 5′ and 3′ ends, splicing patterns and other post-transcriptional modifications; 
• to quantify the changing expression levels of each transcript during development and under different conditions

In general, a population of RNA is converted into a cDNA library with adaptors attached at one or both ends. Then, each molecule is sequenced to obtain informations from one end (single-end sequencing) or both ends (pair-end sequencing). The sequenced reads (generally 30-400 bp long, depending on the used machinery) are then aligned on a reference genome or transcriptome or de novo assembled to produce a genome-scale transcription map (also expression levels of different genes might be reported).

Respect to other technologies used to investigate transcriptome, RNA-seq has different advantages:

• It is not limited to detecting transcripts derived from an existing genomic sequence;
  
• It can reveal the precise location of transcription boundaries, to a single-base resolution;
• 30-bp short reads give information about how two exons are connected, whereas longer reads or pair-end short reads should reveal connectivity between multiple exons;
  
• It can be used to identify variations (as SNPs) in the transcribed region.
• It has very low background signal because DNA sequences can been unambiguously mapped to unique regions of the genome;
• It does not have an upper limit for quantification, which correlates with the number of sequences obtained;
• It  is highly accurate for quantifying expression levels;
  
• Finally, because there are no cloning steps, and with the Helicos technology there is no amplification step, it requires less RNA sample.
  

(Danilo Lombardi)