Open AccessRASL‐seq for Massively Parallel and Quantitative Analysis of Gene Expression
Author(s) -
Li Hairi,
Qiu Jinsong,
Fu XiangDong
Publication year - 2012
Publication title -
current protocols in molecular biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.533
H-Index - 42
eISSN - 1934-3647
pISSN - 1934-3639
DOI - 10.1002/0471142727.mb0413s98
Subject(s) - massively parallel , massive parallel sequencing , gene expression , computational biology , rna seq , gene , expression (computer science) , biology , genetics , computer science , transcriptome , genome , parallel computing , programming language
Large‐scale, quantitative analysis of gene expression can be accomplished by microarray or RNA‐seq analysis. While these methods are applicable to genome‐wide analysis, it is often desirable to quantify expression of a more limited set of genes in hundreds, thousands, or even tens of thousands of biological samples. For example, some studies may require monitoring a sizable panel of key genes under many different experimental conditions, during development, or following treatment with a large library of small molecules, for which current genome‐wide methods are either inefficient or cost‐prohibitive. This unit presents a method that permits quantitative profiling of several hundred selected genes in a large number of samples by coupling R NA‐mediated oligonucleotide A nnealing, S election, and L igation with Next‐Gen seq uencing (RASL‐seq). The method even allows direct analysis of RNA levels in cell lysates and is also adaptable to full automation, making it ideal for large‐scale analysis of multiple biological pathways or regulatory gene networks in the context of systematic genetic or chemical genetic perturbations. Curr. Protoc. Mol. Biol . 98:4.13.1‐4.13.9. © 2012 by John Wiley & Sons, Inc.