bioRxivPlant Biology
Translational landscape in tomato revealed by transcriptome assembly and ribosome profiling
Abstract
mRNA translation is a critical step in gene expression, but our understanding of the landscape and control of translation in diverse crops remains lacking. Here, we combined de novo transcriptome assembly and ribosome profiling to study global mRNA translation in tomato roots. Taking advantage of the 3-nucleotide periodicity displayed by translating ribosomes, we identified 354 novel small ORFs (sORFs) translated from previously unannotated transcripts, as well as 1329 upstream ORFs (uORFs) translated within the 5 UTRs of annotated protein-coding genes. Proteomic analysis confirmed that some of these novel uORFs and sORFs generate stable proteins in planta. Compared with the annotated ORFs, the uORFs use more flexible Kozak sequences around translation start sites. Interestingly, uORF-containing genes are enriched for protein phosphorylation/dephosphorylation and signaling transduction pathways, suggesting a regulatory role for uORFs in these processes. We also demonstrated that ribosome profiling is useful to facilitate the annotation of translated ORFs and noncanonical translation initiation sites. In addition to defining the translatome, our results revealed the global control of mRNA translation by uORFs and microRNAs in tomato. In summary, our approach provides a high-throughput method to discover unannotated ORFs, elucidates evolutionarily conserved translational features, and identifies new regulatory mechanisms hidden in a crop genome. SignificanceSeveral studies have shown that altering mRNA translation is a powerful way of improving crop performance. However, due to limited genomic resources and methods, translational regulation remains poorly understood in crops. By leveraging de novo transcriptome assembly and ribosome profiling, we mapped and quantified translating ribosomes across the entire transcriptome in tomato roots. This is the first experiment-based survey to systematically identify actively translated ORFs in a crop. Our results reveal numerous unannotated translation events and uncover new regulatory mechanisms of gene expression in tomato. Our approach not only facilitates our understanding of the tomato translational landscape but also provides a practical strategy to study the translatomes of other species. O_LIThe raw RNA-seq and Ribo-seq data have been deposited in the Gene Expression Omnibus (GEO) database under accession no. GSE124962. C_LIO_LIProteomics raw data files and MaxQuant Search results have been deposited at the MassIVE repository with dataset identifier: MSV000083363. C_LI
- organism: plant (other)
- assay: bulk RNA-seq
- assay: proteomics
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: deep learning
- approach: statistical model
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