An Automated Proteogenomic Method Uses Mass Spectrometry to Reveal Novel Genes in Zea mays

Abstract

New technologies in genomics and proteomics have influenced the emergence of proteogenomics, a field at the confluence of genomics, transcriptomics, and proteomics. First generation proteogenomic toolkits employ peptide mass spectrometry to identify novel protein coding regions. We extend first generation proteogenomic tools to achieve greater accuracy and enable the analysis of large, complex genomes. We apply our pipeline to Zea mays, which has a genome comparable in size to human. Our pipeline begins with the comparison of mass spectra to a putative translation of the genome. We select novel peptides, those that match a region of the genome that was not previously known to be protein coding, for grouping into refinement events. We present a novel, probabilistic framework for evaluating the accuracy of each event. Our calculated event probability, or eventProb, considers the number of supporting peptides and spectra, and the quality of each supporting peptide-spectrum match. Our pipeline predicts 165 novel protein-coding genes and proposes updated models for 741 additional genes. Molecular & Cellular Proteomics 13: 10.1074/ mcp.M113.031260, 157-167, 2014.Accurate genome annotation, wherein the location and structure of all protein coding genes are identified, is critically important and yet it remains elusive for even the most extensively studied organisms. The wide availability of inexpensive next-generation sequencing technologies ensures that model organisms from all branches of the tree of life will continue to be sequenced at an ever increasing pace. However, the annotation pipelines are not able to keep up.Much recent focus on computational gene finding is on incorporating transcript evidence. As with genomic sequencing, availability of high-throughput technologies for transcript sequencing such as RNA-Seq (1) has dramatically changed the genome annotation landscape. Although RNA-Seq provides valuable evidence for genome annotation (2-5) it does not provide a comprehensive solution either. Increasing evidence suggests that a discrepancy exists between protein isoforms that are transcribed versus translated (6). Indeed in our own observation, we find evidence for genes in sampling proteins that are not visible at the transcript level. Moreover, the transcript evidence is confounded by prespliced messages, nontargeted expression noise, ncRNA, and lack of strand and frame information. All of these pose challenges for gene finding.Tandem mass spectrometry is a key technology for assaying the expressed proteome. In typical bottom-up workflows, enzymatically digested peptides are isolated via chromatography and then fragmented in the mass spectrometer. The collection of masses of peptide fragments (tandem mass spectrum) is used as a fingerprint for identification of expressed peptides.Historically, the genomics community has provided the annotations (aa sequences) and the proteomics community has focused on identifying peptides and proteins from this annotated list to assay for expression of proteins in specif...

An Analysis of the Sensitivity of Proteogenomic Mapping of Somatic Mutations and Novel Splicing Events in Cancer

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Integrated Transcriptomic-Proteomic Analysis Using a Proteogenomic Workflow Refines Rat Genome Annotation

“…Various approaches have been proposed to create a compact yet comprehensive search database for peptide and protein detection from MS data (22,45,46). The most promising of these utilizes RNA-seq to create a sample or tissue-specific search database.…”

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