Editorial:Plant and Cell Physiology’s 2016 Online Database Issue

We are pleased to present the sixth Database Issue of Plant and Cell Physiology (available at http://pcp.oxfordjournals.org/content/57/1.toc ). In line with past issues ( Matsuoka 2011 , Matsuoka and Yano 2012, Obayashi and Yano 2013 , Obayashi and Yano 2014 , Ohyanagi et al. 2015 ), the 2016 issue provides a valuable online resource and forum for the discussion of novel bioinformatics approaches and online tools that will facilitate the handling and analysis of large, multifaceted biological data sets available for plant research. Genome and transcriptome (including non-coding transcript) databases allow management of the flood of next-generation sequencing (NGS) data typically associated with this big data era, and have been rapidly extended to cover a wide range of non-model plant species. Concomitantly, proteome and phenome databases have also been developed and, in some instances, the creation of more sophisticated, visionary databases for multi-omics integration has also been achieved. Here we briefly introduce the 12 databases that are featured in this special online issue according to the multiple layers of ‘omics’ information they provide. OryzaGenome ( http://viewer.shigen.info/oryzagenome/ ) is a database for genomic variants of wild rice species from the Oryza genus ( Ohyanagi et al. 2016 ). The goal of this database is to establish a pan- Oryza genomic repository that covers both reference genome sequences and genomic variant information. The current version of OryzaGenome includes genotype information for 446 O. rufipogon accessions derived by imputation and of 17 accessions from multiple Oryza species by imputation-free deep sequencing. It is particularly aimed at a streamlined integration with phenotypic/habitat information by the authors’ previous and future activities stored in the related database, Oryzabase ( http://www.shigen.nig.ac.jp/rice/oryzabase/ ) ( Kurata and Yamazaki 2006 ). With information on the azuki bean genome becoming available, this issue features the Vigna Genome Server database, Vig GS ( http://viggs.dna.affrc.go.jp ), which stores comprehensive omics information about the genome and transcriptome of the genus Vigna together with functional annotations ( Sakai et al. 2016 ). Information on sequence polymorphisms between azuki bean and its wild relatives is available from Vig GS, which can also assist with comparative functional analyses. Vig GS should therefore serve as a useful platform on which to base new advances in the use of unique and valuable genetic resources of legume crops and their wild relatives. ALCOdb (Algae Gene Coexpression Database; http://alcodb.jp ) provides gene coexpression information for the green alga Chlamydomonas reinhardtii and the red alga Cyanidioschyzon merolae with functionalities for gene coexpression analyses (e.g. coexpressed gene list, gene information, coexpressed gene network) as well as for expression analyses [expression profiler, differentially expressed gene (DEG) finder] ( Aoki et al. 2016a ). In this paper, the authors provide evaluation results of the gene coexpression data in ALCOdb and an example of how coexpression data could be used for estimating gene function after mutant screening. AthaMap ( http://www.athamap.de ) provides a genomic map of predicted transcription factor (TF)-binding sites and small RNA target sites in Arabidopsis ( Hehl et al. 2016 ). This updated version of AthaMap incorporates 113 positional weight matrices based on a study of protein-binding microarrays. The total current number of the TF-binding sites has reached 4.9 × 10 7 for 126 TFs in 29 TF families. ATTED-II ( http://atted.jp ) is a coexpression database for plant species with parallel views of multiple coexpression data sets and network analysis tools ( Aoki et al. 2016b ). Version 8.0 of ATTED-II includes eight microarray- and six RNAseq-based coexpression data sets for 11 plant species, achieving higher reliability supported by reproducibility of the data. The authors provide an example of the use of reliable coexpression data in their paper, where they demonstrate monocot- and dicot-specific coexpression of cell wall genes by comparing eight coexpression data sets among four species. The Pleurochrysome database ( http://bioinf.mind.meiji.ac.jp/phapt/ ) is the first database providing comprehensive information of biological functions and orthologs of expressed genes in the algal genus Pleurochrysis ( Yamamoto et al. 2016 ). Pleurochrysis is a haptophyte alga that produces unique calcified scales called coccoliths. The Pleurochrysome database should facilitate research on the elucidation of the molecular mechanisms behind the characteristic features of Pleurochrysis , such as coccolith formation, and uncovering the evolutionary relationships among algal species. TENOR (Transcriptome ENcyclopedia Of Rice, http://tenor.dna.affrc.go.jp ) is a transcriptome database for abiotic stress responses in rice ( Kawahara et al. 2016 ). The authors performed detailed transcriptome experiments with >200 samples of leaves and roots typically at five time points under 12 stress-related conditions, the results of which are summarized in terms of sample similarity, gene function and regulation. TENOR provides gene expression profiles, DEG lists and coexpressed genes, as well as multilayered views via a genomic browser. A database named CANTATAdb ( http://cantata.amu.edu.pl , http://yeti.amu.edu.pl/CANTATA/ ) comprises a collection of long non-coding RNAs (lncRNAs) in 10 model plant species, aimed at a better understanding of their potential regulatory functions ( Szczesśniak et al. 2016 ). The lncRNAs were computationally identified with publicly available RNA-Seq samples and carefully evaluated and curated in terms of expression levels, coding potentials and sequence alignments. Other types of data provide annotations for the identified lncRNAs. A proteome database named the compendium of crop Proteins with Annotated Locations or cropPAL ( http://crop-PAL.org ) compiles information on plant protein subcellular localizations in four crop species ( Hordeum vulgare , Triticum aestivum , Oryza sativa and Zea mays ). The ultimate aim of this database is to depict plant cells as compartmentalized protein networks that can be investigated for crop yield and quality improvement in solving the imminent food security issue ( Hooper et al. 2016 ). It includes manually curated entries from 556 published studies as well as computationally predicted protein localization information by eight arrays of prediction tools. eHALOPH ( http://www.sussex.ac.uk/affiliates/halophytes/ ) is a database housing information on salt-tolerant plants ( Santos et al. 2016 ). The contents of this database include not only data on salt tolerance, but also information about plant type, life form, ecotypes, habitat, references, and so on. The advanced search function tool [e.g. for family, salinity (dS/m) or habitat] allows the user efficiently to retrieve information about the genetic resources available. The full list of salt-tolerant plants is also downloadable. The information gleaned from eHALOPH will be a vital resource in helping to promote bioremediation and breeding for salt tolerance in crop plants. TOMATOMA ( http://tomatoma.nbrp.jp/ ) is a relational database that provides phenotypic information and available mutant resources of the tomato dwarf cultivar Micro-Tom ( Saito et al. 2011 ). In this updated release, the authors newly generated 4,952 mutagenized lines by a second round of ethylmethane sulfonate (EMS) treatment of EMS-mutagenized M 3 seeds, isolating 618 individual mutants assigned to 1,194 phenotypic categories ( Shikata et al. 2016 ). In addition, TOMATOMA now contains metabolite information for mutant fruits, including sugar and carotenoid contents. Both phenotypic and metabolite data in the wild type and mutants are accessible to researchers together with the corresponding mutants through TOMATOMA. The visionary database named HRGRN ( http://plantgrn.noble.org/hgrn/ ) is an integrated database for the biological network of signal transduction, metabolism and gene regulation in Arabidopsis ( Dai et al. 2016 ). It employs Neo4j, a highly scalable Cypher Query Language-based database management system and hosts large-scale biological interactions among genes, proteins, compounds and small RNAs that were either validated experimentally or predicted computationally. It is envisaged that through HRGRN, novel relationships among genes, compounds, RNAs and even pathways from heterogeneous biological interaction data could be discovered, which would otherwise be missed by traditional Structured Query Language (SQL) database search methods. We trust you will find many of the above-featured databases of great relevance to your field of study and/or to the wider research community, and that you can find ways to exploit their stored information and implemented functions as part of your ongoing and future research activities. With its unique collection of published database articles ( http://www.oxfordjournals.org/our_journals/pcp/2012_pcp_database.html ), Plant and Cell Physiology aims to provide an invaluable portal site housing the latest information on newly released or updated plant-related omics and tool banks freely available to the plant research community. We are always eagerly scouting for more plant database articles suitable for inclusion in the annual Database Issues, for which we stipulate that databases should be completely open to the public domain and have user-friendly interfaces and online manuals. In principle, the data in each database should be as comprehensive as possible in its given domain. The originality in raw data sets will provide a certain advantage, but is not essential. In order to understand the biological significance of raw data contents, pure data warehouses are not acceptable for publication, but the inclusion of sophisticated features of database functions (e.g. intuitive user interface, advanced search functions, the latest graphical representation and batch data download function for advanced users) is encouraged. From the viewpoint of data reusability and detailed data accessibility, proper hyperlinks or more advanced linkages to web entities, within the database or to third party databases are favorable. Each database should be IT secured and guaranteed its long-term availability and sustainability. With this in mind, we strongly encourage the submission of more excellent papers describing novel databases, their features or any relevant updates of existing databases in time for next year’s Database Issue, which will be published in early 2017. The next pre-submission inquiry round will be announced later this spring.