Integrated proteogenomics database

Bacteria iconS. meliloti 2011_tryptic

Sinorhizobium meliloti strain 2011 (Genbank #NC_020528 is the reference strain [1] which includes two plasmids #NC_020527 and #NC_020560.

An iPtgxDB was created by hierarchically integrating protein coding sequences from three 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, 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 [5]

Only ORFs above a selectable length threshold (here 18 aa) were considered. The iPtgxDB was created using the hierarchy RefSeq > Genbank > Genoscope > Prodigal > ChemGenome > in silico. Files were parsed to extract the identifier, coordinates and sequences of bona fide protein-coding sequences (CDS) and pseudogene entries. For extensions or reductions to already annotated CDSs, sequences were only included up to the first tryptic cleavage site, allowing to identify such proteins using the proteomics data obtained by using this protease. For more detail on how we generate iPtgxDBs and how the identifiers can be interpreted, please see reference [5].

References

  1. Sallet, E., Roux, B., Sauviac, L., Jardinaud, M. F., Carrere, S., Faraut, T., de Carvalho-Niebel, F., Gouzy, J., Gamas, P., Capela, D., Bruand, C. and Schiex, T. 2013. Next-generation annotation of prokaryotic genomes with EuGene-P: application to Sinorhizobium meliloti 2011. 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.
iPtgxDB Release Info
Versions
Version
1
Versions
Date
19.09.2019

Downloads icon Downloads

Compression icon

TAR.GZ

File icon
Size
11.9 MB
Data icon
MD5
704ebf8a48bc749c5dde9f72c40b76a4
Data icon
SHA1
8db3f1f1c2466fb0d4f66d9f51236f41d6cebafa
Compression icon

ZIP

File icon
Size
12.2 MB
Data icon
MD5
ebffb2ff1e0e8344da28e2fb2acf1ae0
Data icon
SHA1
ab2884f8ad5241f4efc3d2aae242c57817c937b1