Integrated proteogenomics database

Bacteria iconS. meliloti 2011

Sinorhizobium meliloti strain 2011 (Genbank #NC_020528) is the reference strain [1].

An iPtgxDB was created by hierarchically integrating protein coding sequences from three these annotation resources (1-3) and three predictions:

Hierarchy Resource Link
1 NCBI RefSeq GCF_000346065.1_ASM34606v1; from 19/05/2017
2 NCBI Genbank GCA_000346065.1_ASM34606v1; from 31/01/2014
3 Genoscope [2] v2.7.3, accessed 14/11/2018
4 Prodigal [3] Ab initio gene predictions from Prodigal (v2.6)
5 ChemGenome [4] Ab initio gene predictions from ChemGenome (v2.0,; with parameters: method, Swissprot space; length threshold, 70 nt; initiation codons, ATG, CTG, TTG, GTG)
6 in silico ORFs The in silico ORF annotations were generated as described by Omasits and Varadarajan et al., 2017

Only ORFs above a selectable length threshold (here 18 aa) were considered. The iPtgxDB was created using the hierarchy RefSeq > Genbank > Genoscope > ChemGenome > Prodigal > in silico. Files were parsed to extract the identifier, coordinates and sequences of bona fide protein-coding sequences (CDS) and pseudogene entries. For more detail on how we generate iPtgxDBs and how the identifiers can be interpreted, please see reference [5].


  1. Carrere, S., Capela, D., Gouzy, J., Sallet, E., Sauviac, L., Roux, B., Jardinaud, F., Faraut, T., de Carvalho-Niebel, F., Gamas, P., Bruand, C. and Schiex, T. 2013. Next-generation annotation of prokaryotic genomes with EuGene-P: application to Sinorhizobium meliloti 2013. DNA Res. 20 (4): 339-354.
  2. Vallenet, D., Belda, E., Calteau, A., Cruveiller, S., Engelen, S., Lajus, A., Le Fevre, F., Longin, C., Mornico, D., Roche, D. et al. 2013. MicroScope--an integrated microbial resource for the curation and comparative analysis of genomic and metabolic data. Nucleic Acids Res 41: D636-647.
  3. Hyatt, D., Chen, G.L., Locascio, P.F., Land, M.L., Larimer, F.W., and Hauser, L.J. 2010. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 11: 119.
  4. Singhal, P., Jayaram, B., Dixit, S.B., and Beveridge, D.L. 2008. Prokaryotic gene finding based on physicochemical characteristics of codons calculated from molecular dynamics simulations. Biophys J 94: 4173-4183.
  5. Omasits, U., Varadarajan, A. R., Schmid, M., Goetze, S., Melidis, D., Bourqui, M., Nikolayeva, O., Quebatte, M., Patrignani, A., Dehio, C., Frey, J. E., Robinson, M. D., Wollscheid, B., and Ahrens., C. H. 2017. An integrative strategy to identify the entire protein coding potential of prokaryotic genomes by proteogenomics. Genome Research. 27: 2083-2095.
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