Small-scale sequencing enables quality assessment of Ribo-Seq data: an example from Arabidopsis cell culture

Amir Mahboubi,Nicolas Delhomme,Sara Häggström,Johannes Hanson

doi:10.1186/s13007-021-00791-w

Amir Mahboubi, Nicolas Delhomme + Show 2 more

Open Access

https://doi.org/10.1186/s13007-021-00791-w

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Abstract

BackgroundTranslation is a tightly regulated process, controlling the rate of protein synthesis in cells. Ribosome sequencing (Ribo-Seq) is a recently developed tool for studying actively translated mRNA and can thus directly address translational regulation. Ribo-Seq libraries need to be sequenced to a great depth due to high contamination by rRNA and other contaminating nucleic acid fragments. Deep sequencing is expensive, and it generates large volumes of data, making data analysis complicated and time consuming.Methods and resultsHere we developed a platform for Ribo-Seq library construction and data analysis to enable rapid quality assessment of Ribo-Seq libraries with the help of a small-scale sequencer. Our data show that several qualitative features of a Ribo-Seq library, such as read length distribution, P-site distribution, reading frame and triplet periodicity, can be effectively evaluated using only the data generated by a benchtop sequencer with a very limited number of reads.ConclusionOur pipeline enables rapid evaluation of Ribo-Seq libraries, opening up possibilities for optimization of Ribo-Seq library construction from difficult samples, and leading to better decision making prior to more costly deep sequencing.

Highlights

Translation is a tightly regulated process, controlling the rate of protein synthesis in cells
Mapping against a transcriptome reference is better suited to studies of translational efficiency and differential translation, whereas mapping against a genome reference is a standard procedure for discovering novel open reading frames (ORFs) and association of ribosomes with non-protein-coding RNA
High levels of contamination with rRNA, tRNA and other ribosome-protected RNA fragments remain the main challenge in reducing the cost of sequencing RiboSeq libraries while still being able to generate a sufficient number of ribosome protected fragments (RPFs) for statistically sound analyses

Summary

Introduction

Translation is a tightly regulated process, controlling the rate of protein synthesis in cells. Ribosome sequencing (Ribo-Seq) is a recently developed tool for studying actively translated mRNA and can directly address translational regulation. Translational regulation plays a prominent role in the expression of protein-coding genes, investigating gene expression based solely on transcriptome data may be insufficient [1,2,3]. With all the advances in sequencing technologies over the last decade, several experimental approaches have been developed to capture a global view of translation within a new branch of omics termed translatomics [4, 5]. A Ribo-Seq procedure consists of experimental and computational phases. Mapping against a transcriptome reference is better suited to studies of translational efficiency and differential translation, whereas mapping against a genome reference is a standard procedure for discovering novel ORFs and association of ribosomes with non-protein-coding RNA. The binary alignment map (BAM) files resulting from mapping Ribo-Seq reads to the reference of interest can be used for downstream P-site and triplet periodicity analyses, mainly using available R packages such as riboSeqR [14], riboWaltz [15] and RiboTaper [16]

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