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Whole transcriptome shotgun sequencing (WTSS), also called RNA-Seq (RNA sequencing), uses next-generation sequencing (NGS) to Show the quantity and presence of RNA at a given moment in a biological sample. RNA-Seq is developed recently to approach transcriptome profiling which uses deep-sequencing technologies. Studies using this method have already altered our perspective of the complexity and extent of eukaryotic transcriptomes. It also provides a far more precise measurement of levels of isoforms and their transcripts than any other methods.
The complete set of transcripts in a cell and their quantity, for a specific developmental stage or physiological condition is called transcriptome. For interpreting the functional elements of the genome and revealing the molecular constituents of cells and tissues, and also for understanding development and disease, it is essential to understand the transcriptome. The main goals of transcriptomics are: to record all species of transcript, including mRNAs, non-coding RNAs and small RNAs; to define the transcriptional structure of genes, in terms of their start sites, 5? and 3? ends, splicing patterns and other post-transcriptional modifications; and to calculate the changing expression levels of each transcript during growth and under different conditions.
A number of technologies have been developed to deduce and calculate the transcriptome, including hybridization-or sequence-based approaches. Hybridization-based methods typically involve incubating fluorescently labelled cDNA with custom-made microarrays or commercial high-density oligo microarrays. Particular microarrays have also been designed; for example, arrays with probes spanning exon junctions can be used to identify and quantify distinctive spliced isoforms. Genomic tiling microarrays that symbolize the genome at high density have been created and allow the mapping of transcribed regions to a very high resolution, from several base pairs to ~100 bp. Hybridization-based methods are high throughput and relatively cheap, except for high-resolution tiling arrays that interrogate large genomes. However, these methods have several limits, which include: reliance upon existing knowledge about genome sequence; high background levels owing to cross-hybridization; and a narrow dynamic range of detection owing to both background and saturation of signals. Moreover, comparing expression levels across different experiments is often problematic and can require complex normalization methods.
In contrast to microarray approaches, sequence-based methods directly determine the cDNA sequence. Primarily, Sanger sequencing of cDNA or EST libraries was used, but this method is relatively low throughput, costly and generally not measureable. Tag-based methods were developed to overcome these limits, containing serial analysis of gene expression (SAGE), cap analysis of gene expression (CAGE) and massively parallel signature sequencing (MPSS). These tag-based sequencing methods are high throughput and can provide accurate, ‘digital’ gene expression levels. However, most are based on expensive Sanger sequencing technology, and a major portion of the short tags cannot be uniquely mapped to the reference genome. Moreover, only a portion of the transcript is analyzed and isoforms are mostly indistinguishable from each other. These disadvantages limit the use of traditional sequencing technology in interpreting the structure of transcriptomes. is my name and how are you.we have pleased and its h akd dsnf dsjnf shd djf dfff fdd