ArticleBMC genomics2019
Peptimapper: proteogenomics workflow for the expert annotation of eukaryotic genomes.
Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 14 citations in OpenAlex.
- An overview of technologies for MS-based proteomics-centric multi-omics.Expert review of proteomics · 2022Article
- Personalized Proteome: Comparing Proteogenomics and Open Variant Search Approaches for Single Amino Acid Variant Detection.Journal of proteome research · 2021Article
- Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey.IEEE access : practical innovations, open solutions · 2021Article
- Identification of Non-Canonical Translation Products inFrontiers in genetics · 2021Article
- Multi-omics Visualization Platform: An extensible Galaxy plug-in for multi-omics data visualization and exploration.GigaScience · 2020Article
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundAccurate structural annotation of genomes is still a challenge, despite the progress made over the past decade. The prediction of gene structure remains difficult, especially for eukaryotic species, and is often erroneous and incomplete. We used a proteogenomics strategy, taking advantage of the combination of proteomics datasets and bioinformatics tools, to identify novel protein coding-genes and splice isoforms, assign correct start sites, and validate predicted exons and genes.
resultsOur proteogenomics workflow, Peptimapper, was applied to the genome annotation of Ectocarpus sp., a key reference genome for both the brown algal lineage and stramenopiles. We generated proteomics data from various life cycle stages of Ectocarpus sp. strains and sub-cellular fractions using a shotgun approach. First, we directly generated peptide sequence tags (PSTs) from the proteomics data. Second, we mapped PSTs onto the translated genomic sequence. Closely located hits (i.e., PSTs locations on the genome) were then clustered to detect potential coding regions based on parameters optimized for the organism. Third, we evaluated each cluster and compared it to gene predictions from existing conventional genome annotation approaches. Finally, we integrated cluster locations into GFF files to use a genome viewer. We identified two potential novel genes, a ribosomal protein L22 and an aryl sulfotransferase and corrected the gene structure of a dihydrolipoamide acetyltransferase. We experimentally validated the results by RT-PCR and using transcriptomics data.
conclusionsPeptimapper is a complementary tool for the expert annotation of genomes. It is suitable for any organism and is distributed through a Docker image available on two public bioinformatics docker repositories: Docker Hub and BioShaDock. This workflow is also accessible through the Galaxy framework and for use by non-computer scientists at https://galaxy.protim.eu . Data are available via ProteomeXchange under identifier PXD010618.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.