4.4 Article

The use of duplex-specific nuclease in ribosome profiling and a user-friendly software package for Ribo-seq data analysis

期刊

RNA
卷 21, 期 10, 页码 1731-1745

出版社

COLD SPRING HARBOR LAB PRESS, PUBLICATIONS DEPT
DOI: 10.1261/rna.052548.115

关键词

ribosome profiling; duplex-specific nuclease; Chlamydomonas; mouse; translation

资金

  1. EMBL long-term postdoctoral fellowship
  2. Sir Henry Wellcome Fellowships
  3. Wellcome Trust [088789]
  4. UK Biotechnology and Biological Sciences Research Council grants [BB/L000334/1, BB/J007072/1]
  5. Gatsby Charitable Foundation
  6. European Research Council Advanced Investigator grant TRIBE
  7. BBSRC [BB/L000334/1, BB/J007072/1] Funding Source: UKRI
  8. MRC [MR/M011747/1] Funding Source: UKRI
  9. Biotechnology and Biological Sciences Research Council [BB/L000334/1, BB/J007072/1] Funding Source: researchfish
  10. Medical Research Council [MR/M011747/1] Funding Source: researchfish

向作者/读者索取更多资源

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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