LRP2: A proteogenomics pipeline for long-read informed protein isoform analysis and discovery
- 1New York Genome Center
Abstract
Most human genes produce multiple RNA isoforms, yet it remains unclear which isoforms are translated into stable, functional proteins. Long-read RNA sequencing resolves full-length transcript structures and, when paired with mass spectrometry, can provide empirical evidence of isoform translation. Despite this opportunity, comprehensive workflows integrating isoform discovery, open reading frame prediction, peptide identification, and protein inference remain limited, leaving users to handle these steps piecemeal. Here, we present LRP2, a modular, end-to-end long-read proteogenomics pipeline built in Nextflow. LRP2 scales transcript discovery to hundreds of samples via PacBio's latest Isocall tool, removes technical artifacts with SQANTI QC, generates and classifies predicted proteomes via CPAT and SQANTI Protein, performs multi-group differential expression and usage analysis via edgeR, DRIMSeq, and a long-read adaptation of LeafCutter, and integrates protein-level evidence from DDA and DIA MS data through FragPipe. For cross-dataset comparison of novel isoforms, LRP2 employs deterministic splice-junction, coordinate-based isoform identifiers. Used as an integrated pipeline, LRP2 enables the detection of novel peptides and improves the protein isoform inference to confirm protein isoform translation.
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BibTeX
@misc{schertzer2026lrp2,
title = {{LRP2: A proteogenomics pipeline for long-read informed protein isoform analysis and discovery}},
author = {M. D. Schertzer and J. T. Lewandowski and E. F. Watts and W. Rosenow and M. M. Mehlferber and E. D. Jeffery and S. I. Adamson and J. Bruand and E. Tseng and Y. Neelamraju and F. E. Garrett-Bakelman and E. Dolzhenko and D. A. Knowles and G. Sheynkman},
howpublished = {bioRxiv},
year = {2026},
month = may,
doi = {10.64898/2026.05.27.728216},
url = {https://www.biorxiv.org/content/10.64898/2026.05.27.728216v2},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - LRP2: A proteogenomics pipeline for long-read informed protein isoform analysis and discovery
AU - M. D. Schertzer
AU - J. T. Lewandowski
AU - E. F. Watts
AU - W. Rosenow
AU - M. M. Mehlferber
AU - E. D. Jeffery
AU - S. I. Adamson
AU - J. Bruand
AU - E. Tseng
AU - Y. Neelamraju
AU - F. E. Garrett-Bakelman
AU - E. Dolzhenko
AU - D. A. Knowles
AU - G. Sheynkman
PY - 2026
DA - 2026/05/27
PB - bioRxiv
DO - 10.64898/2026.05.27.728216
UR - https://www.biorxiv.org/content/10.64898/2026.05.27.728216v2
AB - Most human genes produce multiple RNA isoforms, yet it remains unclear which isoforms are translated into stable, functional proteins. Long-read RNA sequencing resolves full-length transcript structures and, when paired with mass spectrometry, can provide empirical evidence of isoform translation. Despite this opportunity, comprehensive workflows integrating isoform discovery, open reading frame prediction, peptide identification, and protein inference remain limited, leaving users to handle these steps piecemeal. Here, we present LRP2, a modular, end-to-end long-read proteogenomics pipeline built in Nextflow. LRP2 scales transcript discovery to hundreds of samples via PacBio's latest Isocall tool, removes technical artifacts with SQANTI QC, generates and classifies predicted proteomes via CPAT and SQANTI Protein, performs multi-group differential expression and usage analysis via edgeR, DRIMSeq, and a long-read adaptation of LeafCutter, and integrates protein-level evidence from DDA and DIA MS data through FragPipe. For cross-dataset comparison of novel isoforms, LRP2 employs deterministic splice-junction, coordinate-based isoform identifiers. Used as an integrated pipeline, LRP2 enables the detection of novel peptides and improves the protein isoform inference to confirm protein isoform translation.
ER -