A. Pandey and P. A. Pevzner, Proteogenomics. Proteomics, vol.14, pp.2631-2633, 2014.

K. Krug, S. Nahnsen, and B. Macek, Mass spectrometry at the interface of proteomics and genomics, Mol BioSyst, vol.7, issue.2, pp.284-91, 2011.

J. D. Jaffe, H. C. Berg, and G. M. Church, Proteogenomic mapping as a complementary method to perform genome annotation, Proteomics, vol.4, issue.1, pp.59-77, 2004.

J. Armengaud, Reannotation of genomes by means of proteomics data, Methods Enzymol, vol.585, pp.201-217, 2017.

K. K. Datta, A. K. Madugundu, and H. Gowda, Proteogenomic methods to improve genome annotation, Methods Mol Biol, vol.1410, pp.77-89, 2016.

B. Kuster, P. Mortensen, J. S. Andersen, and M. Mann, Mass spectrometry allows direct identification of proteins in large genomes, Proteomics, vol.1, issue.5, pp.641-50, 2001.

A. I. Nesvizhskii, Proteogenomics: concepts, applications and computational strategies, Nat Methods, vol.11, issue.11, pp.1114-1139, 2014.

G. Menschaert and D. Fenyo, Proteogenomics from a bioinformatics angle: a growing field, Mass Spectrom Rev, vol.36, issue.5, pp.584-99, 2017.

K. V. Ruggles, K. Krug, X. Wang, K. R. Clauser, J. Wang et al., Methods, tools and current perspectives in proteogenomics, Mol Cell Proteomics, vol.16, issue.6, pp.959-81, 2017.

M. Mann and M. Wilm, Error-tolerant identification of peptides in sequence databases by peptide sequence tags, Anal Chem, vol.66, issue.24, pp.4390-4399, 1994.

. Yates, J. K. Eng, and A. L. Mccormack, Mining genomes: correlating tandem mass spectra of modified and unmodified peptides to sequences in nucleotide databases, Anal Chem, vol.67, issue.18, pp.3202-3212, 1995.

B. Nanduri, N. Wang, M. L. Lawrence, S. M. Bridges, and S. C. Burgess, Gene model detection using mass spectrometry, Methods Mol Biol, vol.604, pp.137-181, 2010.

D. E. Kalume, S. Peri, R. Reddy, J. Zhong, M. Okulate et al., Genome annotation of Anopheles gambiae using mass spectrometryderived data, BMC Genomics, vol.6, p.128, 2005.

D. Kumar, A. K. Yadav, X. Jia, J. Mulvenna, and D. Dash, Integrated transcriptomicproteomic analysis using a proteogenomic workflow refines rat genome annotation, Mol Cell Proteomics, vol.15, issue.1, pp.329-368, 2016.

S. Chocu, B. Evrard, R. Lavigne, A. D. Rolland, F. Aubry et al., Forty-four novel protein-coding loci discovered using a proteomics informed by transcriptomics (PIT) approach in rat male germ cells, Biol Reprod, vol.91, issue.5, p.123, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01121802

J. C. Wright, J. Mudge, H. Weisser, M. P. Barzine, J. M. Gonzalez et al., Improving GENCODE reference gene annotation using a high-stringency proteogenomics workflow, Nat Commun, vol.7, p.11778, 2016.

B. Chapman, N. Castellana, A. Apffel, R. Ghan, G. R. Cramer et al., Plant proteogenomics: from protein extraction to improved gene predictions, Methods Mol Biol, vol.1002, pp.267-94, 2013.

M. Ferro, M. Tardif, E. Reguer, R. Cahuzac, C. Bruley et al., PepLine: a software pipeline for high-throughput direct mapping of tandem mass spectrometry data on genomic sequences, J Proteome Res, vol.7, issue.5, pp.1873-83, 2008.
URL : https://hal.archives-ouvertes.fr/hal-02072530

N. E. Castellana, S. H. Payne, Z. Shen, M. Stanke, V. Bafna et al., Discovery and revision of Arabidopsis genes by proteogenomics, Proc Natl Acad Sci U S A, vol.105, issue.52, pp.21034-21042, 2008.

M. G. Potgieter, K. C. Nakedi, J. M. Ambler, A. J. Nel, S. Garnett et al., Proteogenomic analysis of mycobacterium smegmatis using high resolution mass spectrometry, Front Microbiol, vol.7, p.427, 2016.

J. Armengaud, E. M. Hartmann, and C. Bland, Proteogenomics for environmental microbiology, Proteomics, vol.13, pp.2731-2773, 2013.

A. De-groot, R. Dulermo, P. Ortet, L. Blanchard, P. Guerin et al., Alliance of proteomics and genomics to unravel the specificities of Sahara bacterium Deinococcus deserti, PLoS Genet, vol.5, issue.3, p.1000434, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00379051

S. A. Muller, S. Findeiss, S. R. Pernitzsch, D. K. Wissenbach, P. F. Stadler et al., Identification of new protein coding sequences and signal peptidase cleavage sites of helicobacter pylori strain 26695 by proteogenomics, J Proteome, vol.86, pp.27-42, 2013.

E. Venter, R. D. Smith, and S. H. Payne, Proteogenomic analysis of bacteria and archaea: a 46 organism case study, PLoS One, vol.6, issue.11, p.27587, 2011.

J. Armengaud, J. Trapp, O. Pible, O. Geffard, A. Chaumot et al., Nonmodel organisms, a species endangered by proteogenomics, J Proteome, vol.105, pp.5-18, 2014.

A. Frank and P. Pevzner, PepNovo: de novo peptide sequencing via probabilistic network modeling, Anal Chem, vol.77, issue.4, pp.964-73, 2005.

T. Carver, S. R. Harris, M. Berriman, J. Parkhill, and J. A. Mcquillan, Artemis: an integrated platform for visualization and analysis of high-throughput sequence-based experimental data, Bioinformatics, vol.28, issue.4, pp.464-473, 2012.

. Guillot, BMC Genomics, vol.20, p.56, 2019.

E. Com, A. Clavreul, M. Lagarrigue, S. Michalak, P. Menei et al., Quantitative proteomic isotope-coded protein label (ICPL) analysis reveals alteration of several functional processes in the glioblastoma, J Proteome, vol.75, issue.13, pp.3898-913, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00877756

R. Lavigne, E. Becker, Y. Liu, B. Evrard, A. Lardenois et al., Direct iterative protein profiling (DIPP)-an innovative method for large-scale protein detection applied to budding yeast mitosis, Mol Cell Proteomics, vol.11, issue.2, pp.111-012682, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00682837

J. A. Vizcaino, A. Csordas, N. Del-toro, J. A. Dianes, J. Griss et al., 2016 update of the PRIDE database and its related tools, Nucleic Acids Res, vol.44, issue.D1, pp.447-56, 2016.

M. Bern, Y. Cai, and D. Goldberg, Lookup peaks: a hybrid of de novo sequencing and database search for protein identification by tandem mass spectrometry, Anal Chem, vol.79, issue.4, pp.1393-400, 2007.

J. M. Cock, L. Sterck, P. Rouze, D. Scornet, A. E. Allen et al., The Ectocarpus genome and the independent evolution of multicellularity in brown algae, Nature, vol.465, issue.7298, pp.617-638, 2010.
URL : https://hal.archives-ouvertes.fr/cea-00906990

A. P. Lipinska, D. 'hondt, S. Van-damme, E. J. , D. Clerck et al., Uncovering the genetic basis for early isogamete differentiation: a case study of Ectocarpus siliculosus, BMC Genomics, vol.14, p.909, 2013.

S. M. Dittami, A. Gravot, S. Goulitquer, S. Rousvoal, A. F. Peters et al., Towards deciphering dynamic changes and evolutionary mechanisms involved in the adaptation to low salinities in Ectocarpus (brown algae), Plant J, vol.71, issue.3, pp.366-77, 2012.
URL : https://hal.archives-ouvertes.fr/hal-01208656

A. F. Peters, D. Marie, D. Scornet, B. Kloareg, and J. M. Cock, Proposal of Ectocarpus siliculosus (Ectocarpales, Phaeophyceae) as a model organism for brown algal genetics and genomics, J Phycol, vol.40, pp.1079-88, 2004.

J. M. Cock, S. M. Coelho, C. Brownlee, and A. R. Taylor, The Ectocarpus genome sequence: insights into brown algal biology and the evolutionary diversity of the eukaryotes, New Phytol, vol.188, issue.1, pp.1-4, 2010.

K. Avia, S. M. Coelho, G. J. Montecinos, A. Cormier, F. Lerck et al., High-density genetic map and identification of QTLs for responses to temperature and salinity stresses in the model brown alga, Ectocarpus. Sci Rep, vol.7, p.43241, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01510346

S. Heesch, G. Y. Cho, A. F. Peters, L. Corguille, G. Falentin et al., A sequence-tagged genetic map for the brown alga Ectocarpus siliculosus provides large-scale assembly of the genome sequence, New Phytol, vol.188, issue.1, pp.42-51, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01806415

S. M. Coelho, O. Godfroy, A. Arun, L. Corguille, G. Peters et al., OUROBOROS is a master regulator of the gametophyte to sporophyte life cycle transition in the brown alga Ectocarpus, Proc Natl Acad Sci, vol.108, issue.28, pp.11518-11541, 2011.
URL : https://hal.archives-ouvertes.fr/hal-01806390

S. M. Dittami, D. Scornet, J. L. Petit, B. Segurens, D. Silva et al., Global expression analysis of the brown alga Ectocarpus siliculosus (Phaeophyceae) reveals large-scale reprogramming of the transcriptome in response to abiotic stress, Genome Biol, vol.10, issue.6, p.66, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01806423

S. Ahmed, J. M. Cock, E. Pessia, R. Luthringer, A. Cormier et al., A haploid system of sex determination in the brown alga Ectocarpus sp, Curr Biol, vol.24, issue.17, pp.1945-57, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01132642

A. P. Lipinska, S. Ahmed, A. F. Peters, S. Faugeron, J. M. Cock et al., Development of PCR-based markers to determine the sex of kelps, PLoS One, vol.10, issue.10, p.140535, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01226462

L. Contreras, A. Ritter, G. Dennett, F. Boehmwald, N. Guitton et al., Two-dimensional gel electrophoresis analysis of brown algal protein extracts(1), J Phycol, vol.44, issue.5, pp.1315-1336, 2008.

A. Ritter, M. Ubertini, S. Romac, F. Gaillard, L. Delage et al., Copper stress proteomics highlights local adaptation of two strains of the model brown alga Ectocarpus siliculosus, Proteomics, vol.10, issue.11, pp.2074-88, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01925564

B. Gschloessl, Y. Guermeur, and J. M. Cock, HECTAR: a method to predict subcellular targeting in heterokonts, BMC Bioinformatics, vol.9, p.393, 2008.
DOI : 10.1186/1471-2105-9-393

URL : https://hal.archives-ouvertes.fr/hal-00359779

S. Prigent, G. Collet, S. M. Dittami, L. Delage, E. De-corny et al., The genome-scale metabolic network of Ectocarpus siliculosus (EctoGEM): a resource to study brown algal physiology and beyond, Plant J, vol.80, issue.2, pp.367-81, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01057153

A. Shevchenko, S. Sunyaev, A. Loboda, A. Shevchenko, P. Bork et al., Charting the proteomes of organisms with unsequenced genomes by MALDI-quadrupole time-of-flight mass spectrometry and BLAST homology searching, Anal Chem, vol.73, issue.9, pp.1917-1943, 2001.

F. Moreews, O. Sallou, H. Menager, L. Bras, Y. Monjeaud et al., BioShaDock: a community driven bioinformatics shared Docker-based tools registry, vol.4, p.1443, 2015.
DOI : 10.12688/f1000research.7536.1

URL : https://hal.archives-ouvertes.fr/hal-01243520

J. Goecks, A. Nekrutenko, J. Taylor, and T. Galaxy, Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences, Genome Biol, vol.11, issue.8, p.86, 2010.

E. Afgan, D. Baker, B. Batut, M. Van-den-beek, D. Bouvier et al., The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update, Nucleic Acids Res, vol.46, issue.W1, pp.537-581, 2018.
DOI : 10.1093/nar/gky379

URL : https://academic.oup.com/nar/article-pdf/46/W1/W537/25110642/gky379.pdf

W. S. Sanders, N. Wang, S. M. Bridges, B. M. Malone, Y. S. Dandass et al., The proteogenomic mapping tool, BMC Bioinformatics, vol.12, p.115, 2011.
DOI : 10.1186/1471-2105-12-115

URL : https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/1471-2105-12-115

F. Ghali, R. Krishna, S. Perkins, A. Collins, D. Xia et al., ProteoAnnotator-open source proteogenomics annotation software supporting PSI standards, Proteomics, vol.14, pp.2731-2772, 2014.
DOI : 10.1002/pmic.201400265

URL : http://eprints.keele.ac.uk/3464/1/J%20Wastling%20-%20ProteoAnnotator%20-%20Open%20Source%20proteogenomics%20annotation%20software%20supporting%20PSI%20standards.pdf

C. Has, S. A. Lashin, A. V. Kochetov, and J. Allmer, PGMiner reloaded, fully automated proteogenomic annotation tool linking genomes to proteomes, J Integr Bioinform, vol.13, issue.4, p.293, 2016.
DOI : 10.1515/jib-2016-293

URL : http://www.degruyter.com/downloadpdf/j/jib.2016.13.issue-4/jib-2016-293/jib-2016-293.xml

G. Menschaert, T. T. Vandekerckhove, G. Baggerman, B. Landuyt, J. V. Sweedler et al., A hybrid, de novo based, genomewide database search approach applied to the sea urchin neuropeptidome, J Proteome Res, vol.9, issue.2, pp.990-996, 2010.

P. D. Jagtap, J. E. Johnson, G. Onsongo, F. W. Sadler, K. Murray et al., Flexible and accessible workflows for improved proteogenomic analysis using the Galaxy framework, J Proteome Res, vol.13, issue.12, pp.5898-908, 2014.

G. M. Sheynkman, J. E. Johnson, P. D. Jagtap, M. R. Shortreed, G. Onsongo et al., Using Galaxy-P to leverage RNA-Seq for the discovery of novel protein variations, BMC Genomics, vol.15, p.703, 2014.

J. Fan, S. Saha, G. Barker, K. J. Heesom, F. Ghali et al., Galaxy integrated omics: web-based standards-compliant workflows for proteomics informed by transcriptomics, Mol Cell Proteomics, vol.14, issue.11, pp.3087-93, 2015.
DOI : 10.1074/mcp.o115.048777

URL : http://europepmc.org/articles/pmc4638048?pdf=render

R. Sajulga, S. Mehta, P. Kumar, J. E. Johnson, C. R. Guerrero et al., Bridging the chromosome-centric and biology/diseasedriven human proteome projects: accessible and automated tools for interpreting the biological and pathological impact of protein sequence variants detected via proteogenomics, J Proteome Res, 2018.

M. C. Chambers, P. D. Jagtap, J. E. Johnson, T. Mcgowan, P. Kumar et al., An accessible proteogenomics informatics resource for cancer researchers, Cancer Res, vol.77, issue.21, pp.43-49, 2017.
DOI : 10.1158/0008-5472.can-17-0331

URL : http://cancerres.aacrjournals.org/content/canres/77/21/e43.full.pdf

A. Cormier, K. Avia, L. Sterck, T. Derrien, V. Wucher et al., Re-annotation, improved large-scale assembly and establishment of a catalogue of noncoding loci for the genome of the model brown alga Ectocarpus, New Phytol, vol.214, issue.1, pp.219-251, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01402123

Y. Zhu, L. M. Orre, H. J. Johansson, M. Huss, J. Boekel et al., Discovery of coding regions in the human genome by integrated proteogenomics analysis workflow, Nat Commun, vol.9, issue.1, p.903, 2018.

Y. Li, X. Wang, J. H. Cho, T. I. Shaw, Z. Wu et al., JUMPg: an integrative proteogenomics pipeline identifying unannotated proteins in human brain and Cancer cells, J Proteome Res, vol.15, issue.7, pp.2309-2329, 2016.

C. Has, S. A. Lashin, A. Kochetov, and J. Allmer, PGMiner reloaded, fully automated proteogenomic annotation tool linking genomes to proteomes, J Integr Bioinform, vol.13, issue.4, pp.16-23, 2016.

J. Crappe, E. Ndah, A. Koch, S. Steyaert, D. Gawron et al., PROTEOFORMER: deep proteome coverage through ribosome profiling and MS integration, Nucleic Acids Res, vol.43, issue.5, p.29, 2015.

S. H. Nagaraj, N. Waddell, A. K. Madugundu, S. Wood, A. Jones et al., PGTools: a software suite for proteogenomic data analysis and visualization, J Proteome Res, vol.14, issue.5, pp.2255-66, 2015.

H. Kim, H. Park, and E. Paek, NextSearch: a search engine for mass spectrometry data against a compact nucleotide exon graph, J Proteome Res, vol.14, issue.7, pp.2784-91, 2015.

B. A. Risk, W. J. Spitzer, and M. C. Giddings, Peppy: proteogenomic search software, J Proteome Res, vol.12, issue.6, pp.3019-3044, 2013.