RESUMEN
As a crucial molecular mechanism, post-translational modifications (PTMs) play critical roles in a wide range of biological processes in plants. Recent advances in mass spectrometry-based proteomic technologies have greatly accelerated the profiling and quantification of plant PTM events. Although several databases have been constructed to store plant PTM data, a resource including more plant species and more PTM types with quantitative dynamics still remains to be developed. In this paper, we present an integrative database of quantitative PTMs in plants named qPTMplants (http://qptmplants.omicsbio.info), which hosts 1 242 365 experimentally identified PTM events for 429 821 nonredundant sites on 123 551 proteins under 583 conditions for 23 PTM types in 43 plant species from 293 published studies, with 620 509 quantification events for 136 700 PTM sites on 55 361 proteins under 354 conditions. Moreover, the experimental details, such as conditions, samples, instruments and methods, were manually curated, while a variety of annotations, including the sequence and structural characteristics, were integrated into qPTMplants. Then, various search and browse functions were implemented to access the qPTMplants data in a user-friendly manner. Overall, we anticipate that the qPTMplants database will be a valuable resource for further research on PTMs in plants.
Asunto(s)
Bases de Datos de Proteínas , Plantas/genética , Procesamiento Proteico-Postraduccional/genética , Proteínas/genética , Plantas/clasificación , Proteínas/clasificación , Proteómica/normasRESUMEN
Since Epstein-Barr virus (EBV) was discovered in 1964, it has been reported to be associated with various malignancies as well as benign diseases, and the pathogenicity of EBV has been widely studied. Several databases have been established to provide comprehensive information on the virus and its relation to diseases and introduce convenient analysis tools. Although they have greatly facilitated the analysis of EBV at the genome, gene, protein, or epitope level, they did not provide enough insight into the genomic variants of EBV, which have been suggested as relevant to diseases by multiple studies. Here, we introduce dbEBV, a comprehensive database of EBV genomic variation landscape, which contains 942 EBV genomes with 109,893 variants from different tissues or cell lines in 24 countries. The database enables the visualization of information with varying global frequencies and their relationship with the human health of each variant. It also supports phylogenetic analysis at the genome or gene level in subgroups of different characteristics. Information of interest can easily be reached with functions such as searching, browsing, and filtering. In conclusion, dbEBV is a convenient resource for exploring EBV genomic variants, freely available at http://dbebv.omicsbio.info.