Most noncoding RNAs are considered by their expression at low levels and as having a limited phylogenetic distribution in the cytoplasm, indicating that they may be only involved in specific biological processes. However, recent studies showed the protein-coding potential of ncRNAs, indicating that they might be a source of some special proteins. Although there are increasing noncoding RNAs identified to be able to code proteins, it is challenging to distinguish coding RNAs from previously annotated ncRNAs, and to detect the proteins from their translation. In this article, we designed a pipeline to identify these noncoding RNAs in Arabidopsis thaliana from three NCBI GEO data sets with coding potential and predict their translation products. 31 311 noncoding RNAs were predicted to be translated into peptides, and they showed lower conservation rate than common proteins. In addition, we built an interaction network between these peptides and annotated Arabidopsis proteins using BIPS, which included 69 peptides from noncoding RNAs. Peptides in the interaction network showed different characteristics from other noncoding RNA-derived peptides, and they participated in several crucial biological processes, such as photorespiration and stress-responses. All the information of putative ncPEPs and their interaction with proteins predicted above are finally integrated in a database, PncPEPDB ( http://bis.zju.edu.cn/PncPEPDB ). These results showed that peptides derived from noncoding RNAs may play important roles in noncoding RNA regulation, which provided another hypothesis that noncoding RNA may regulate the metabolism via their translation products.
Keywords: database and visualization; ncRNA-encoded peptides; peptide−protein interaction network; ribosome profiling.