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<p>Proteogenomics is a transformative approach for deciphering novel coding regions through integration of genomic, transcriptomic, and proteomic data. Here, we present pAnno, an end-to-end workflow designed to uncover hidden protein-coding elements with high precision and efficiency. pAnno generates customized protein databases by integrating multi-omic data, employs a multi-stage iterative open search strategy, and incorporates an efficient peptide-to-coding sequence mapping algorithm. Despite a 50-fold increase in database size, pAnno maintains high sensitivity and accuracy in peptide identification and achieves genomic localization of novel events with only <InlineEquation ID="IEq1"><EquationSource Format="TEX">\(\sim\)</EquationSource><EquationSource Format="MATHML"><math><mo>∼</mo></math></EquationSource></InlineEquation>3% additional processing time, delivering unprecedented resolution and speed in proteogenomic analysis. By detecting splicing, mutations, and novel protein isoforms, pAnno supports various downstream applications and reveals overlooked events, identifying 1.73<InlineEquation ID="IEq2"><EquationSource Format="TEX">\(\times\)</EquationSource><EquationSource Format="MATHML"><math><mo>×</mo></math></EquationSource></InlineEquation> more novel proteins in Pyrus and 34<InlineEquation ID="IEq3"><EquationSource Format="TEX">\(\times\)</EquationSource><EquationSource Format="MATHML"><math><mo>×</mo></math></EquationSource></InlineEquation> more non-canonical HLA peptides in lung cancer. These capabilities position pAnno as a gold-standard proteogenomic workflow, excelling in non-canonical coding discovery and large-scale database processing.</p>

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pAnno: a comprehensive, precise, and fast proteogenomic workflow for the discovery of novel coding regions

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月2日

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  • Kaifei Wang,
  • Zhuohong Wei,
  • Changrong Li,
  • Yaping Peng,
  • Jiale Zhao,
  • Pengzhi Mao,
  • Ching Tarn,
  • Jinyang Li,
  • Ranfei Chen,
  • Jiaxiang Ding,
  • Feng Ge,
  • Mingkun Yang,
  • Hao Chi

摘要

Proteogenomics is a transformative approach for deciphering novel coding regions through integration of genomic, transcriptomic, and proteomic data. Here, we present pAnno, an end-to-end workflow designed to uncover hidden protein-coding elements with high precision and efficiency. pAnno generates customized protein databases by integrating multi-omic data, employs a multi-stage iterative open search strategy, and incorporates an efficient peptide-to-coding sequence mapping algorithm. Despite a 50-fold increase in database size, pAnno maintains high sensitivity and accuracy in peptide identification and achieves genomic localization of novel events with only \(\sim\)∼3% additional processing time, delivering unprecedented resolution and speed in proteogenomic analysis. By detecting splicing, mutations, and novel protein isoforms, pAnno supports various downstream applications and reveals overlooked events, identifying 1.73\(\times\)× more novel proteins in Pyrus and 34\(\times\)× more non-canonical HLA peptides in lung cancer. These capabilities position pAnno as a gold-standard proteogenomic workflow, excelling in non-canonical coding discovery and large-scale database processing.