Complete Transcriptome RNA-Seq.
Cancer Gene Networks
Methods in molecular biology, January 2017
David F. B. Miller, Pearlly Yan, Fang Fang, Aaron Buechlein, Karl Kroll, David Frankhouser, Cameron Stump, Paige Stump, James B. Ford, Haixu Tang, Scott Michaels, Daniela Matei, Tim H. Huang, Jeremy Chien, Yunlong Liu, Douglas B. Rusch, Kenneth P. Nephew
Usha Kasid, Robert Clarke
RNA-Seq is the leading technology for analyzing gene expression on a global scale across a broad spectrum of sample types. However, due to chemical modifications by fixation or degradation due to collection methods, samples often contain an abundance of RNA that is no longer intact, and the capability of current RNA-Seq protocols to accurately quantify such samples is often limited. We have developed an RNA-Seq protocol to address these key issues as well as quantify gene expression from the whole transcriptome. Furthermore, for compatibility with improved sequencing platforms, we use restructured adapter sequences to generate libraries for Illumina HiSeq, MiSeq, and NextSeq platforms. Our protocol utilizes duplex-specific nuclease (DSN) to remove abundant ribosomal RNA sequences while retaining other types of RNA for superior transcriptome profiling from low quantity input. We employ the Illumina sequencing platform, but this method is described in sufficient detail to adapt to other platforms.
|Readers by professional status||Count||As %|
|Student > Ph. D. Student||6||24%|
|Student > Master||3||12%|
|Student > Doctoral Student||2||8%|
|Student > Postgraduate||2||8%|
|Readers by discipline||Count||As %|
|Biochemistry, Genetics and Molecular Biology||10||40%|
|Agricultural and Biological Sciences||7||28%|
|Medicine and Dentistry||2||8%|
|Immunology and Microbiology||2||8%|