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Correction: Filippou et al. Transcriptomic Analysis Reveals Molecular Mechanisms Underpinning Mycovirus-Mediated Hypervirulence in <i>Beauveria bassiana</i> Infecting <i>Tenebrio molitor</i>. <i>J. Fungi</i> 2025, <i>11</i>, 63.

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BINge: Multispecies Ortholog Clustering for Differential Gene Expression Analyses.

Zachary Stewart1,2, Dimitri Perrin3,4, Alexie Papanicolaou5

  • 1School of Biology and Environmental Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.

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|April 27, 2026
PubMed
Summary

This study introduces BINge, a novel software for multispecies differential gene expression (DGE) analysis. BINge accurately models orthology to create essential references, minimizing bias in cross-species gene expression studies.

Keywords:
DGEcross‐speciesgenomicssequence clusteringtranscriptomics

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Area of Science:

  • Genomics
  • Bioinformatics
  • Evolutionary Biology

Background:

  • Differential gene expression (DGE) analysis links gene expression to phenotypic traits.
  • Accurate gene expression quantification is crucial for DGE studies within and across species.
  • Comparing gene expression across species reveals genetic underpinnings of phenotypic differences.

Purpose of the Study:

  • To address the challenge of creating accurate references for multispecies DGE analysis.
  • To minimize reference bias in cross-species gene expression quantification.
  • To introduce BINge, a software tool for improved multispecies DGE reference generation.

Main Methods:

  • Developed a novel approach for modeling orthology to create multispecies transcript clusters.
  • Ensured transcript clusters accurately reflect locus orthology.
  • Evaluated BINge's effectiveness against existing clustering methods.

Main Results:

  • BINge produces multispecies transcript clusters that accurately represent locus orthology.
  • The novel orthology modeling approach effectively minimizes bias in multispecies DGE.
  • Evaluation demonstrated BINge's superiority over existing methods not designed for multispecies DGE.

Conclusions:

  • BINge offers an effective solution for generating accurate references for multispecies DGE analysis.
  • The software mitigates reference bias, enabling more reliable cross-species gene expression comparisons.
  • BINge facilitates the study of genetic mechanisms underlying interspecies phenotypic variation.