MOTIVATION: Protein structural research in plants lags behind that in animal and bacterial species. This lag concerns both the structural analysis of individual proteins and the proteome-wide characterization of structure-related properties. Until now, no systematic study concerning the relationships between protein disorder and multiple post-translational modifications (PTMs) in plants has been presented. RESULTS: In this work, we calculated the global degree of intrinsic disorder in the complete proteomes of eight typical monocotyledonous and dicotyledonous plant species. We further predicted multiple sites for phosphorylation, glycosylation, acetylation and methylation and examined the correlations of protein disorder with the presence of the predicted PTM sites. It was found that phosphorylation, acetylation and O-glycosylation displayed a clear preference for occurrence in disordered regions of plant proteins. In contrast, methylation tended to avoid disordered sequence, whereas N-glycosylation did not show a universal structural preference in monocotyledonous and dicotyledonous plants. In addition, the analysis performed revealed significant differences between the integral characteristics of monocot and dicot proteomes. They included elevated disorder degree, increased rate of O-glycosylation and R-methylation, decreased rate of N-glycosylation, K-acetylation and K-methylation in monocotyledonous plant species, as compared with dicotyledonous species. Altogether, our study provides the most compelling evidence so far for the connection between protein disorder and multiple PTMs in plants. CONTACT: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

MOTIVATION: A reconstruction of full-length transcripts observed by next-generation sequencer or tiling arrays is an essential technique to know all phenomena of transcriptomes. Several techniques of the reconstruction have been developed. However, problems of high-level noises and biases still remain and interrupt the reconstruction. A method is required that is robust against noise and bias and correctly reconstructs transcripts regardless of equipment used. RESULTS: We propose a completely new statistical method that reconstructs full-length transcripts and can be applied on both next-generation sequencers and tiling arrays. The method called ARTADE2 analyzes 'positional correlation', meaning correlations of expression values for every combination on genomic positions of multiple transcriptional data. ARTADE2 then reconstructs full-length transcripts using a logistic model based on the positional correlation and the Markov model. ARTADE2 elucidated 17 591 full-length transcripts from 55 transcriptome datasets and showed notable performance compared with other recent prediction methods. Moreover, 1489 novel transcripts were discovered. We experimentally tested 16 novel transcripts, among which 14 were confirmed by reverse transcription-polymerase chain reaction and sequence mapping. The method also showed notable performance for reconstructing of mRNA observed by a next-generation sequencer. Moreover, the positional correlation and factor analysis embedded in ARTADE2 successfully detected regions at which alternative isoforms may exist, and thus are expected to be applied for discovering transcript biomarkers for a wide range of disciplines including preemptive medicine. AVAILABILITY: http://matome.base.riken.jp CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUMMARY: sORF finder is a program package for identifying small open reading frames (sORFs) with high-coding potential. This application allows the identification of coding sORFs according to the nucleotide composition bias among coding sequences and the potential functional constraint at the amino acid level through evaluation of synonymous and non-synonymous substitution rates. AVAILABILITY: Online tools and source codes are freely available at http://evolver.psc.riken.jp/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: We have established a database named LegumeTFDB to provide access to transcription factor (TF) repertoires of three major legume species: soybean (Glycine max), Lotus japonicus and Medicago truncatula. LegumeTFDB integrates unique information for each TF gene and family, including sequence features, gene promoters, domain alignments, gene ontology (GO) assignment and sequence comparison data derived from comparative analysis with TFs found within legumes, in Arabidopsis, rice and poplar as well as with proteins in NCBI nr and UniProt. We also analyzed the promoter regions for all of the TFs to identify all types of cis-motifs provided by the PLACE database. Additionally, we supply hyperlinks to make available expression data of 2411 soybean TF genes. LegumeTFDB provides an important user-friendly public resource for comparative genomics and understanding of transcriptional regulation in agriculturally important legumes. AVAILABILITY: http://legumetfdb.psc.riken.jp/. SUPPLEMENTARY INFORMATION: Supplementary data available at Bioinformatics online.