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Time-resolved RNA sequencing methods are applications of RNA-seq that allow for observations of RNA abundances over time in a biological sample or samples. Second-Generation DNA sequencing has enabled cost effective, high throughput and unbiased analysis of the transcriptome . [ 1 ]
As a result of the development of novel sequencing technologies, the years between 2008 and 2012 saw a large drop in the cost of sequencing. Per megabase and genome, the cost dropped to 1/100,000th and 1/10,000th of the price, respectively. [1]
RNA-Seq (named as an abbreviation of RNA sequencing) is a technique that uses next-generation sequencing to reveal the presence and quantity of RNA molecules in a biological sample, providing a snapshot of gene expression in the sample, also known as transcriptome.
Following sorting, single-cell RNA sequencing generates the transcriptome of the visualized cells. [25] This method can process thousands of cells within a defined niche at the cost of losing spatial data between cells in the niche. [25]
The word "transcriptome" was first used in the 1990s. [19] [20] In 1995, one of the earliest sequencing-based transcriptomic methods was developed, serial analysis of gene expression (SAGE), which worked by Sanger sequencing of concatenated random transcript fragments. [21] Transcripts were quantified by matching the fragments to known genes.
These fragments are sequenced by high-throughput next generation sequencing techniques and the reads are mapped back to the reference genome, providing a count of the number of reads associated with each gene. [13] Normalisation of RNA-seq data accounts for cell to cell variation in the efficiencies of the cDNA library formation and sequencing.
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