The use of duplex-specific nuclease in ribosome profiling and a user-friendly software package for Ribo-seq data analysis
- Betty Y. Chung1,3,
- Thomas J. Hardcastle1,3,
- Joshua D. Jones2,3,
- Nerea Irigoyen2,3,
- Andrew E. Firth2,
- David C. Baulcombe1 and
- Ian Brierley2
- 1Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom
- 2Division of Virology, Department of Pathology, University of Cambridge, Cambridge CB2 1QP, United Kingdom
- Corresponding authors: bcy23{at}cam.ac.uk, ib103{at}cam.ac.uk
Abstract
Ribosome profiling is a technique that permits genome-wide, quantitative analysis of translation and has found broad application in recent years. Here we describe a modified profiling protocol and software package designed to benefit more broadly the translation community in terms of simplicity and utility. The protocol, applicable to diverse organisms, including organelles, is based largely on previously published profiling methodologies, but uses duplex-specific nuclease (DSN) as a convenient, species-independent way to reduce rRNA contamination. We show that DSN-based depletion compares favorably with other commonly used rRNA depletion strategies and introduces little bias. The profiling protocol typically produces high levels of triplet periodicity, facilitating the detection of coding sequences, including upstream, downstream, and overlapping open reading frames (ORFs) and an alternative ribosome conformation evident during termination of protein synthesis. In addition, we provide a software package that presents a set of methods for parsing ribosomal profiling data from multiple samples, aligning reads to coding sequences, inferring alternative ORFs, and plotting average and transcript-specific aspects of the data. Methods are also provided for extracting the data in a form suitable for differential analysis of translation and translational efficiency.
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Footnotes
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↵3 Joint first authors.
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Article published online ahead of print. Article and publication date are at http://www.rnajournal.org/cgi/doi/10.1261/rna.052548.115.
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Freely available online through the RNA Open Access option.
- Received May 15, 2015.
- Accepted June 23, 2015.
This article, published in RNA, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.