A proteomic workfl ow using high-throughput de novo sequencing towards complementation of genome information for improved comparative crop science

Abstract

The proteomic study of non-model organisms, such as many crop plants, is challenging due to the lack of comprehensive genome information. Changing environmental conditions require the study and selection of adapted cultivars. Mutations, inherent to cultivars, hamper protein identifi cation and thus considerably complicate the qualitative and quantitative comparison in large-scale systems biology approaches. With this workfl ow, cultivar-specifi c mutations are detected from high-throughput comparative MS analyses, by extracting sequence polymorphisms with de novo sequencing. Stringent criteria are suggested to filter for confi dential mutations. Subsequently, these polymorphisms complement the initially used database, which is ready to use with any preferred database search algorithm. In our example, we thereby identified 26 specifi c mutations in two cultivars of Pisum sativum and achieved an increased number (17 %) of peptide spectrum matches.