Peptimapper: proteogenomics workflow for the expert annotation of eukaryotic genomes

Laetitia Guillot; Ludovic Delage; Alain Viari; Yves Vandenbrouck; Emmanuelle Com; Andrés Ritter; Régis Lavigne; Dominique Marie; Pierre Peterlongo; Philippe Potin; Charles Pineau

doi:10.1186/s12864-019-5431-9

Peptimapper: proteogenomics workflow for the expert annotation of eukaryotic genomes

Laetitia Guillot ^{1, 2, 3} Ludovic Delage ⁴ Alain Viari ^{5, 6} Yves Vandenbrouck ⁷ Emmanuelle Com ^{1, 3, 2} Andrés Ritter ⁸ Régis Lavigne ^{1, 3, 2} Dominique Marie ⁸ Pierre Peterlongo ⁹ Philippe Potin ⁸ Charles Pineau ^{1, 2, 3}

1 EHESP - École des Hautes Études en Santé Publique [EHESP]

2 Irset - Institut de recherche, santé, environnement et travail

3 Protim - Proteomics Core Facility

4 SBR - Station biologique de Roscoff [Roscoff]

5 ERABLE - Equipe de recherche européenne en algorithmique et biologie formelle et expérimentale

Inria Grenoble - Rhône-Alpes

6 Baobab

PEGASE - Département PEGASE [LBBE]

7 EDyP - Etude de la dynamique des protéomes

BGE - UMR S1038 - Laboratoire de Biologie à Grande Échelle

8 LBI2M - Laboratoire de Biologie Intégrative des Modèles Marins

9 GenScale - Scalable, Optimized and Parallel Algorithms for Genomics

Inria Rennes – Bretagne Atlantique , IRISA_D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE

Abstract : Background: Accurate 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. Results: Our 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.

Document type :

Journal articles

Domain :

Computer Science [cs] / Bioinformatics [q-bio.QM]

Computer Science [cs] / Data Structures and Algorithms [cs.DS]

Liste complète des métadonnées

https://hal.inria.fr/hal-01987197
Contributor : Pierre Peterlongo <>
Submitted on : Sunday, January 20, 2019 - 10:08:28 PM
Last modification on : Thursday, April 18, 2019 - 3:28:54 PM

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