Helmholtz Gemeinschaft

Search
Browse
Statistics
Feeds

deltaTE: detection of translationally regulated genes by integrative analysis of Ribo-seq and RNA-seq data

[img]
Preview
PDF (Original Article) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
3MB

Item Type:Article
Title:deltaTE: detection of translationally regulated genes by integrative analysis of Ribo-seq and RNA-seq data
Creators Name:Chothani, S. and Adami, E. and Ouyang, J.F. and Viswanathan, S. and Hubner, N. and Cook, S.A. and Schafer, S. and Rackham, O.J.L.
Abstract:Ribosome profiling quantifies the genome-wide ribosome occupancy of transcripts. With the integration of matched RNA sequencing data, the translation efficiency (TE) of genes can be calculated to reveal translational regulation. This layer of gene-expression regulation is otherwise difficult to assess on a global scale and generally not well understood in the context of human disease. Current statistical methods to calculate differences in TE have low accuracy, cannot accommodate complex experimental designs or confounding factors, and do not categorize genes into buffered, intensified, or exclusively translationally regulated genes. This article outlines a method [referred to as deltaTE (ΔTE), standing for change in TE] to identify translationally regulated genes, which addresses the shortcomings of previous methods. In an extensive benchmarking analysis, ΔTE outperforms all methods tested. Furthermore, applying ΔTE on data from human primary cells allows detection of substantially more translationally regulated genes, providing a clearer understanding of translational regulation in pathogenic processes. In this article, we describe protocols for data preparation, normalization, analysis, and visualization, starting from raw sequencing files.
Keywords:deltaTE, Ribo-seq, RNA-seq, Translation Efficiency, Translational Regulation
Source:Current Protocols in Molecular Biology
ISSN:1934-3639
Publisher:Wiley
Volume:129
Number:1
Page Range:e108
Date:December 2019
Official Publication:https://doi.org/10.1002/cpmb.108
PubMed:View item in PubMed
Related to:
URLURL Type
https://edoc.mdc-berlin.de/17565/Preprint version

Repository Staff Only: item control page

Downloads

Downloads per month over past year

Open Access
MDC Library