five

The landscape of mRNA translation in tomato roots

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NIAID Data Ecosystem2026-04-25 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP178496
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We used Ribo-seq (Ribosome profiling) combining with RNA-seq to explore the translational landscape of tomato roots. We generated three biological replicates of RNA-seq and Ribo-seq data for tomato roots. We next used the RNA-seq result for de novo transcriptome assembly and Ribo-seq to identify novel translated open reading frames (ORFs). Our data revealed more than three hundreds of novel translated ORFs on previously unannotated transcripts. Most of the newly identified ORFs are small and difficult to detect with in silico methods. We also identified over thirteen hundreds of upstream ORFs on annotated genes. This data could facilitate gene annotation. Besides, this data also demonstrated that uORFs, miRNAs and antisense RNAs are regulating the expression of associated genes. This study uncovered mechanisms of translational regulation and gene annotation in tomato. Overall design: 3 biological replicates of 4-day old tomato roots (about 2~3 cm from root tips) collected and processed for Ribo-seq and RNA-seq sample preparation. The Ribo-seq library was sequenced with illumina single-end 50 sequencing and the RNA-seq library was sequenced with illumina paired-end 100 sequencing.
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2019-09-24
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