UNLABELLED: Nowadays the most used pipeline for protein identification consists in the comparison of the MS/MS spectra to reference databases. Search algorithms compare obtained spectra to an in silico digestion of a sequence database to find exact matches. In this context, the database has a paramount importance and will determine in a great deal the number of identifications and its quality, being this especially relevant for non-model plant species. Using a single Viridiplantae database (NCBI, UniProt) and TAIR is not the best choice for non-model species since they are underrepresented in databases resulting in poor identification rates. We demonstrate how it is possible to improve the rate and quality of identifications in two orphan species, Quercus ilex and Pinus radiata, by using SEQUEST and a combination of public (Viridiplantae NCBI, UniProt) and a custom-built specific database which contained 593,294 and 455,096 peptide sequences (Quercus and Pinus, respectively). These databases were built after gathering and processing (trimming, contiging, 6-frame translation) publicly available RNA sequences, mostly ESTs and NGS reads. A total of 149 and 1533 proteins were identified from Quercus seeds and Pinus needles, representing a 3.1- or 1.5-fold increase in the number of protein identifications and scores compared to the use of a single database. Since this approach greatly improves the identification rate, and is not significantly more complicated or time consuming than other approaches, we recommend its routine use when working with non-model species. BIOLOGICAL SIGNIFICANCE: In this work we demonstrate how the construction of a custom database (DB) gathering all available RNA sequences and its use in combination with Viridiplantae public DBs (NCBI, UniProt) significantly improve protein identification when working with non-model species. Protein identification rate and quality is higher to those obtained in routine procedures based on using only one database (commonly Viridiplantae from NCBI), as we demonstrated analyzing Quercus seeds and Pine needles. The proposed approach based on the building of a custom database is not difficult or time consuming, so we recommend its routine use when working with non-model species. This article is part of a Special Issue entitled: Proteomics of non-model organisms.

Agricultural and Plant Biochemistry and Proteomics Research Group Dept of Biochemistry and Molecular Biology University of Córdoba Spain

Dept of Biology and Centre for Environmental and Marine Studies University of Aveiro Aveiro Portugal; GCRC Adaption Biotechnologies Academy of Sciences of the Czech Republic Brno Czech Republic

Plant Physiology Faculty of Biology Dept of Organisms and Systems Biology University of Oviedo Spain

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