# ORFannotate: reproducible coding sequence annotation of transcriptome assemblies

**Authors:** Sonia García-Ruiz, Hannah Macpherson, Laura Caton, Mina Ryten, Emil K Gustavsson

PMC · DOI: 10.1093/bioinformatics/btag082 · 2026-02-17

## TL;DR

ORFannotate is a tool that improves transcriptome annotations by adding precise coding sequence and translational features directly into GTF/GFF files.

## Contribution

ORFannotate introduces a GTF-native tool that reintegrates ORF and CDS annotations into transcript models, enhancing long-read sequencing workflows.

## Key findings

- ORFannotate accurately predicts and inserts CDS and UTR features into GTF/GFF files.
- The tool annotates Kozak sequences, uORFs, and NMD susceptibility for biological context.
- ORFannotate is fast, scalable, and integrates well with visualization and analysis tools.

## Abstract

Accurate annotation of coding sequences and translational features within transcript models is essential for interpreting assembled transcriptomes and their functional potential. Existing open reading frame (ORF) prediction tools typically operate on transcript FASTA files and do not reintegrate coding sequence (CDS) information back into transcript models, limiting their utility in long-read sequencing workflows where GTF/GFF annotations are the primary output. We present ORFannotate, a lightweight, GTF-native Python command-line tool that predicts ORFs from transcript annotations and reinserts precise, exon-aware CDS and UTR features into the original GTF/GFF file. In addition, ORFannotate provides biologically informative translational context by annotating Kozak sequence strength, detecting non-overlapping upstream ORFs (uORFs) with coding probabilities, characterising 5′ and 3′ untranslated regions (UTRs), and predicting nonsense-mediated decay (NMD) susceptibility. All annotations are consolidated in a transcript-level summary to support downstream analysis. By generating GTF files with accurate CDS annotations, ORFannotate facilitates reproducible analysis of both long- and short-read transcriptomes and integrates seamlessly with visualization tools, genome browsers, and comparative transcript analysis workflows. ORFannotate is fast, scalable and provides a practical solution for transcriptome annotation beyond coding potential prediction alone.

ORFannotate is implemented in Python and freely available under the GNU General Public License v3 (GPL-3.0) at: https://github.com/egustavsson/ORFannotate (DOI: https://doi.org/10.5281/zenodo.16812866)

## Full-text entities

- **Species:** Mus musculus (house mouse, species) [taxon 10090], Drosophila melanogaster (fruit fly, species) [taxon 7227], Danio rerio (leopard danio, species) [taxon 7955], Homo sapiens (human, species) [taxon 9606]
- **Mutations:** A2021009F

## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC12960903/full.md

---
Source: https://tomesphere.com/paper/PMC12960903