A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes
May 22nd, 2018
Here we present the proteogenomic tool PoGo and protocols for fast, quantitative, post-translational modification and variant enabled mapping of peptides identified through mass spectrometry onto reference genomes. This tool is of use to integrate and visualize proteogenomic and personal proteomic studies interfacing with orthogonal genomics data.
Overview
This article presents PoGo, a proteogenomic tool designed for the fast and quantitative mapping of peptides identified through mass spectrometry onto reference genomes. It facilitates the integration and visualization of proteogenomic data alongside orthogonal genomics data.
Key Study Components
Area of Science
- Proteogenomics
- Mass Spectrometry
- Genomic Data Integration
Background
- PoGo enables the mapping of peptides with post-translational modifications.
- It supports integration with RNA sequencing data.
- The tool is designed for ease of use and speed.
- It accommodates additional information such as quantitation and amino acid variance.
Purpose of Study
- To demonstrate the use of PoGo for peptide mapping.
- To facilitate the integration of proteomic and genomic data.
- To provide a user-friendly interface for researchers.
Methods Used
- Installation and setup of the PoGo software.
- Mapping of peptides to reference genomes using GUI and command line.
- Visualization of peptide data in the integrative genomics viewer.
- Comparison of PoGo with other proteogenomic tools.
Main Results
- PoGo outperforms other tools in speed and memory usage.
- It effectively maps post-translational modifications and quantitative data.
- The tool provides visual aids for peptide mapping uniqueness.
- Different color codes indicate various mapping characteristics.
Conclusions
- PoGo is a valuable tool for proteogenomic studies.
- It enhances the integration of mass spectrometry data with genomic information.
- The software's efficiency and user-friendly design make it accessible for researchers.
Frequently Asked Questions
Executive Industry Relevance
Integrating quantitative proteomics with genomic annotation is critical for advancing target validation and mechanistic de-risking in biopharma R&D. PoGo enables rapid, scalable mapping of peptides—including post-translational modifications and sequence variants—onto reference genomes, supporting high-confidence data integration across discovery and translational workflows. This capability enhances predictive confidence and portfolio decision-making by bridging proteomic and genomic insights at scale.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables mapping of peptide-level evidence to genomic loci for functional target validation.
- Supports identification of post-translational modifications relevant to pathway interrogation.
- Facilitates mechanistic de-risking by integrating proteomic and transcriptomic data.
- Improves predictive confidence in target selection through variant-enabled mapping.
Screening & Assay Development
- Prepares validated peptide datasets for downstream quantitative and modification-specific assays.
- Standardizes mapping outputs for reproducibility and cross-study comparability.
- Enables scalable processing of large proteomics datasets for screening readiness.
- Supports robust assay development by capturing quantitative and variant information.
Translational & Preclinical Research
- Aligns proteomic findings with genomic coordinates for disease-relevant system studies.
- Enables continuity from discovery through preclinical validation by integrating omics data.
- Supports translational biomarker identification through quantitative mapping outputs.
- Facilitates risk-adjusted advancement decisions by providing comprehensive molecular context.
Pipeline & Workflow Integration
PoGo positions peptide mapping as a bridge between mass spectrometry-based proteomics and genome annotation, supporting workflows from early discovery through translational research.
- Discovery Biology: Integrates peptide-level data with genomic annotation for hypothesis testing and pathway clarification.
- Screening: Delivers standardized, quantitative outputs for assay development and compound evaluation.
- Analytics: Provides quantitative and modification-specific readouts for comparative analysis across conditions.
- Translational Research: Enables mapping of proteomic data to disease-relevant genomic regions for biomarker alignment.
- Enterprise Reuse: Offers scalable, reusable mapping infrastructure for large-scale and multi-study applications.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence and reduces mechanistic ambiguity in target validation.
- Operational Value: Delivers rapid, standardized, and reproducible mapping of millions of peptides.
- Strategic Value: Supports informed go/no-go decisions and capital efficiency by integrating multi-omics data.
- Portfolio Impact: Enables risk-adjusted prioritization and advancement of discovery programs.
Implementation Considerations
- Requires expertise in proteomics, genomics, and data integration workflows.
- Needs access to mass spectrometry data, reference genome annotations, and compatible computational infrastructure.
- Demands cross-team standardization of input formats and mapping parameters.
- Supports adaptation across multiple species and model systems via Ensembl annotation compatibility.
- Dependent on accurate annotation and input data quality for optimal mapping fidelity.
Biopharma FAQs
Chapters in this video
0:05
Title
0:51
Mapping of Peptides using PoGoGUI
2:36
Visualizing in the Integrative Genomics Viewer
3:57
Mapping Peptides Identified Through a Custom Variant Database to a Reference Genome
4:44
Mapping Peptides from Multiple Files Using PoGoGUI
5:48
Generating a Track Hub from Mapped Peptides and Visualizing a Track Hub in the UCSC Genome Browser
6:50
Results: Post-translational Modification and Varient Enabled Mapping of Peptides to Genomes
8:21
Conclusion
