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Small ORFs (sORFs) may encode signaling peptides or microproteins that regulate diverse developmental and environmental responses. Additionally, their translation may play a crucial role in the biogenesis of noncoding RNAs. Despite their importance, sORFs are typically absent from genome annotations, and their prediction remains a significant challenge. Here, we present a bioinformatics pipeline for the identification and visualization of novel translated sORFs using Ribo-seq data in Arabidopsis. This pipeline integrates: (1) Ribo-seq/RNA-seq preprocessing and mapping, (2) (optional) transcriptome assembly to detect unannotated transcripts, (3) ORF discovery using RiboTaper, and (4) the gene viewer ggRibo for high-resolution visualization of individual sORF expression. By combining these modules, our approach provides a powerful framework for analyzing Ribo-seq data, facilitating the discovery, visualization, and future functional characterization of hidden sORFs. This pipeline can be applied to different organisms for systematic identification and visualization of novel sORFs.

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Identifying and Visualizing Novel Small Open Reading Frames (sORFs) Via Ribo-Seq, Transcriptome Assembly, and ggRibo

  • 实验方案

  • 发表日期：

    2026年

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  • Hsin-Yen Larry Wu,
  • Isaiah D. Kaufman,
  • Polly Yingshan Hsu

摘要

Small ORFs (sORFs) may encode signaling peptides or microproteins that regulate diverse developmental and environmental responses. Additionally, their translation may play a crucial role in the biogenesis of noncoding RNAs. Despite their importance, sORFs are typically absent from genome annotations, and their prediction remains a significant challenge. Here, we present a bioinformatics pipeline for the identification and visualization of novel translated sORFs using Ribo-seq data in Arabidopsis. This pipeline integrates: (1) Ribo-seq/RNA-seq preprocessing and mapping, (2) (optional) transcriptome assembly to detect unannotated transcripts, (3) ORF discovery using RiboTaper, and (4) the gene viewer ggRibo for high-resolution visualization of individual sORF expression. By combining these modules, our approach provides a powerful framework for analyzing Ribo-seq data, facilitating the discovery, visualization, and future functional characterization of hidden sORFs. This pipeline can be applied to different organisms for systematic identification and visualization of novel sORFs.