Student Wiki on methodology

This Wiki is intended to collectively make the point on methodologies employed in research papers we analyze during the course. "Writers" are students who wish to contribute to a specific subject. Before contributing, please add your name in the "Writers group choice". When initiating a contribution, please indicate your name in brackets.


PLEASE:  DO NOT change the INDEX page !!!
This page contains the links to the seven official subjects, which are the same in the Choice.

To contribute, go to the right page by clicking on the description here in the index, then click EDIT and contribute. At the end, please save.

 



Transcriptome analysis: special techniques, RNA-seq, GRO-seq, CAGE, etc.

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Modified: 18 March 2018, 12:40 PM   User: Danilo Lombardi  → 

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Transcriptome analysis: RNA-seq


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).


(Danilo Lombardi)