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Quantifying annotation-driven bias in alternative splicing from EGAP metadata.

Rebeca de la Fuente1, Wladimiro Díaz-Villanueva1,2,3, Vicente Arnau1,2,3

  • 1Foundation for the Promotion of Sanitary and Biomedical Research of the Valencian Community (FISABIO), 46020 Valencia, Spain.

NAR Genomics and Bioinformatics
|November 14, 2025
PubMed
Summary
This summary is machine-generated.

Annotation quality significantly impacts alternative splicing estimates in eukaryotes. We developed a normalization method to correct for this bias, improving comparative genomics analyses.

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Area of Science:

  • Genomics and Bioinformatics
  • Molecular Biology

Background:

  • Annotated coding sequences (CDSs) are crucial for estimating alternative splicing genome-wide.
  • Annotation quality and evidence support can introduce systematic biases in splicing event estimations across species.

Purpose of the Study:

  • To evaluate the impact of annotation variables from the NCBI Eukaryotic Genome Annotation Pipeline on inferred splicing levels.
  • To develop a method for correcting annotation-driven biases in alternative splicing estimates for comparative genomics.

Main Methods:

  • Analysis of 670 multicellular eukaryotic genomes.
  • Evaluation of annotation-related variables, including percentage of CDSs with experimental evidence, assembly quality, and raw transcriptomic input.
  • Development of a normalization procedure using polynomial regression.

Main Results:

  • The percentage of CDSs supported by experimental evidence was the primary predictor of variation in splicing estimates.
  • Assembly quality and raw transcriptomic input had a minor role in splicing estimate variations.
  • A novel, adjusted metric for alternative splicing was generated, mitigating annotation artifacts.

Conclusions:

  • Annotation quality, particularly experimental evidence support, is a critical factor influencing alternative splicing estimations.
  • The developed normalization procedure provides a more accurate metric for comparative splicing analysis across species.
  • This work has significant implications for improving the reliability of comparative genomics studies.