| Chapter title |
Exploring Ribosome Positioning on Translating Transcripts with Ribosome Profiling.
|
|---|---|
| Chapter number | 5 |
| Book title |
Post-Transcriptional Gene Regulation
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3067-8_5 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3066-1, 978-1-4939-3067-8
|
| Authors |
Spealman, Pieter, Wang, Hao, May, Gemma, Kingsford, Carl, McManus, C Joel, Pieter Spealman, Hao Wang, Gemma May, Carl Kingsford, C. Joel McManus, McManus, C. Joel |
| Editors |
Erik Dassi |
| Abstract |
Recent technological advances (e.g., microarrays and massively parallel sequencing) have facilitated genome-wide measurement of many aspects of gene regulation. Ribosome profiling is a high-throughput sequencing method used to measure gene expression at the level of translation. This is accomplished by quantifying both the number of translating ribosomes and their locations on mRNA transcripts [1]. The inventors of this approach have published several methods papers detailing its implementation and addressing the basics of ribosome profiling data analysis [2-4]. Here we describe our lab's procedure, which differs in some respects from those published previously. In addition, we describe a data analysis pipeline, Ribomap, for ribosome profiling data. Ribomap allocates sequence reads to alternative mRNA isoforms, normalizes sequencing bias along transcripts using RNA-seq data, and outputs count vectors of per-codon ribosome occupancy for each transcript. |
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