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. The inventors of this approach have published several methods papers detailing its implementation and addressing the basics of ribosome profiling data analysis. 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.

• PMID: 26463378
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Journal Article | Research Support, N.I.H., Extramural | Research Support, U.S. Gov't, Non-P.H.S.

Authors

Spealman P, Wang H, May G, Kingsford C, McManus CJ

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