Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 27 min ago
Peer-reviewedCC BY-NC-ND 4.0Plant Methods

CDScompare: a frame-sensitive GFF comparison tool for improved detection of coding sequence discrepancies, with applications to wheat and rice annotations

Abstract

Background: The rapid expansion of high-quality plant genome assemblies, driven by advances in sequencing technologies and cost reductions, has led to a proliferation of genome assemblies. Moreover, for a single genome, multiple annotation sources often coexist: full-genome predictions from dedicated pipelines (sometimes split into high- and low-confidence sets), manually curated annotations focused on particular gene families, and independent annotations from public repositories such as NCBI. Accurately comparing these alternative annotations is essential to identify and resolve discrepancies, either by selecting the best gene model or, at minimum, by flagging conflicting gene structures at the same locus. Existing comparison tools can detect differences such as gene overlap, fusion or splitting, and some can also detect differences in coding/non-coding boundaries. However, when it comes to coding sequences, none of these tools take the reading frame into account despite its crucial role in interpreting protein-coding regions. This limits their ability to detect functionally relevant annotation conflicts, since the same nucleotide segment, when read in a different frame, yields a completely different protein. Results: We present CDScompare, a Python-based tool that performs frame-aware comparison of GFF annotation files with a focus on CDS regions. This is valuable not only for researchers involved in genome annotation, but also for the many scientists working with gene families of interest, who often face conflicting annotations across multiple sources. As case studies, we applied CDScompare to compare (i) two public annotations of the hexaploid bread wheat (Triticum aestivum), and (ii) two annotations of rice (Oryza sativa) cv. Azucena. CDScompare revealed many CDS conflicts overlooked by existing tools, including cases where overlapping or identical CDS boundaries result in completely different protein sequences due to reading frame differences. Despite the size of the wheat GFF input files (> 1 GB in total), CDScompare processed the comparison in under one minute on a standard laptop, thanks to several algorithmic optimizations. Conclusions: CDScompare introduces a necessary layer of precision in structural annotation comparison by incorporating reading-frame awareness. It enables more informed decisions for annotation pipeline comparison and supports downstream analyses where functional annotation integrity is critical. CDScompare is open source and freely available.

Related

  1. Comparison of Sonidegib and Vismodegib Efficiency in Drug-Sensitive and Resistant Ovarian Cancer Cell Lines—2D and 3D Model Study
    Piotr Stasiak, Justyna Sopel, Artur Płóciennik +3
    International Journal of Molecular SciencesPeer-reviewedCC BY 4.0General biochemistryCrossref
  2. Expanding the Human Ancestry Ontology to include under-represented populations and ethnicities for broader utility in annotations
    Anita Caron, Melek Chaouch, Zoë May Pendlington +2
    arXivPreprintCC BY 4.0Full textMolecular biology & gene regulationarXiv
  3. DR-GEM enables self-supervised machine learning for single-cell embeddings and annotations
    Christine Yiwen Yeh, Min Woo Sun, Dixian Zhu +1
    Nature CommunicationsPeer-reviewedCC BY 4.0Full textMolecular biology & gene regulationPMCEurope PMC
  4. DBCLS BioHackathon 2026 report: RDF publication of Marchantia polymorpha gene annotations, and agent-assisted preparation of DDBJ submissions
    Yasuhiro Tanizawa, Takatomo Fujisawa
    BioHackrXivPreprintCC BY 4.0Full textMolecular biology & gene regulationOSF
  5. An Annotation Consistency Checker for Evidence-Based Evaluation of Untargeted LC-MS/MS Metabolite Annotations
    Wilhan D. G. Nunes, Edward J. Mathias, Charles Terra +4
    ChemRxivPreprintCC BY-NCFull textMolecular biology & gene regulationChemRxiv
BibTeX
@article{ranwez2026cdscompare,
  title = {{CDScompare: a frame-sensitive GFF comparison tool for improved detection of coding sequence discrepancies, with applications to wheat and rice annotations}},
  author = {Vincent Ranwez and Johanna Girodolle and Vetea Jacot and Nathalie Chantret},
  journal = {Plant Methods},
  year = {2026},
  month = jul,
  doi = {10.1186/s13007-026-01576-9},
  url = {https://hal.inrae.fr/hal-05762060v1},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - CDScompare: a frame-sensitive GFF comparison tool for improved detection of coding sequence discrepancies, with applications to wheat and rice annotations
AU  - Vincent Ranwez
AU  - Johanna Girodolle
AU  - Vetea Jacot
AU  - Nathalie Chantret
PY  - 2026
DA  - 2026/07/31
JO  - Plant Methods
DO  - 10.1186/s13007-026-01576-9
UR  - https://hal.inrae.fr/hal-05762060v1
AB  - Background: The rapid expansion of high-quality plant genome assemblies, driven by advances in sequencing technologies and cost reductions, has led to a proliferation of genome assemblies. Moreover, for a single genome, multiple annotation sources often coexist: full-genome predictions from dedicated pipelines (sometimes split into high- and low-confidence sets), manually curated annotations focused on particular gene families, and independent annotations from public repositories such as NCBI. Accurately comparing these alternative annotations is essential to identify and resolve discrepancies, either by selecting the best gene model or, at minimum, by flagging conflicting gene structures at the same locus. Existing comparison tools can detect differences such as gene overlap, fusion or splitting, and some can also detect differences in coding/non-coding boundaries. However, when it comes to coding sequences, none of these tools take the reading frame into account despite its crucial role in interpreting protein-coding regions. This limits their ability to detect functionally relevant annotation conflicts, since the same nucleotide segment, when read in a different frame, yields a completely different protein. Results: We present CDScompare, a Python-based tool that performs frame-aware comparison of GFF annotation files with a focus on CDS regions. This is valuable not only for researchers involved in genome annotation, but also for the many scientists working with gene families of interest, who often face conflicting annotations across multiple sources. As case studies, we applied CDScompare to compare (i) two public annotations of the hexaploid bread wheat (Triticum aestivum), and (ii) two annotations of rice (Oryza sativa) cv. Azucena. CDScompare revealed many CDS conflicts overlooked by existing tools, including cases where overlapping or identical CDS boundaries result in completely different protein sequences due to reading frame differences. Despite the size of the wheat GFF input files (> 1 GB in total), CDScompare processed the comparison in under one minute on a standard laptop, thanks to several algorithmic optimizations. Conclusions: CDScompare introduces a necessary layer of precision in structural annotation comparison by incorporating reading-frame awareness. It enables more informed decisions for annotation pipeline comparison and supports downstream analyses where functional annotation integrity is critical. CDScompare is open source and freely available.
SN  - 1746-4811
ER  -