BackgroundThe increase in human populations around the world has put pressure on resources, and as a consequence food security has become an important challenge for the 21st century. Wheat (Triticum aestivum) is one of the most important crops in human and livestock diets, and the development of wheat varieties that produce higher yields, combined with increased resistance to pests and resilience to changes in climate, has meant that wheat breeding has become an important focus of scientific research. In an attempt to facilitate these improvements in wheat, plant breeders have employed molecular tools to help them identify genes for important agronomic traits that can be bred into new varieties. Modern molecular techniques have ensured that the rapid and inexpensive characterisation of SNP markers and their validation with modern genotyping methods has produced a valuable resource that can be used in marker assisted selection. CerealsDB was created as a means of quickly disseminating this information to breeders and researchers around the globe.DescriptionCerealsDB version 3.0 is an online resource that contains a wide range of genomic datasets for wheat that will assist plant breeders and scientists to select the most appropriate markers for use in marker assisted selection. CerealsDB includes a database which currently contains in excess of a million putative varietal SNPs, of which several hundreds of thousands have been experimentally validated. In addition, CerealsDB also contains new data on functional SNPs predicted to have a major effect on protein function and we have constructed a web service to encourage data integration and high-throughput programmatic access.ConclusionCerealsDB is an open access website that hosts information on SNPs that are considered useful for both plant breeders and research scientists. The recent inclusion of web services designed to federate genomic data resources allows the information on CerealsDB to be more fully integrated with the WheatIS network and other biological databases.

BackgroundLong non-coding RNAs (lncRNAs) may play critical roles in a wide range of developmental processes of higher organisms. Recently, lncRNAs have been widely identified across eukaryotes and many databases of lncRNAs have been developed for human, mouse, fruit fly, etc. However, there is rare information about them in the only completely domesticated insect, silkworm (Bombyx mori).DescriptionIn this study, we systematically scanned lncRNAs using the available silkworm RNA-seq data and public unigenes. Finally, we identified and collected 6281 lncRNAs in the silkworm. Besides, we also collected 1986 microRNAs (miRNAs) from previous studies. Then, we organized them into a comprehensive and web-based database, BmncRNAdb. This database offers a user-friendly interface for data browse and online analysis as well as the three online tools for users to predict the target genes of lncRNA or miRNA.ConclusionsWe have systematically identified and collected the silkworm lncRNAs and constructed a comprehensive database of the silkworm lncRNAs and miRNAs. This work gives a glimpse into lncRNAs of the silkworm and lays foundations for the ncRNAs study of the silkworm and other insects in the future. The BmncRNAdb is freely available at http://gene.cqu.edu.cn/BmncRNAdb/index.php.

BackgroundThe underlying molecular processes representing stress responses to low-dose ionising radiation (LDIR) in mammals are just beginning to be understood. In particular, LDIR effects on the brain and their possible association with neurodegenerative disease are currently being explored using omics technologies.ResultsWe describe a light-weight approach for the storage, analysis and distribution of relevant LDIR omics datasets. The data integration platform, called BRIDE, contains information from the literature as well as experimental information from transcriptomics and proteomics studies. It deploys a hybrid, distributed solution using both local storage and cloud technology.ConclusionsBRIDE can act as a knowledge broker for LDIR researchers, to facilitate molecular research on the systems biology of LDIR response in mammals. Its flexible design can capture a range of experimental information for genomics, epigenomics, transcriptomics, and proteomics. The data collection is available at: .

Increased emphasis on reproducibility of published research in the last few years has led to the large-scale archiving of sequencing data. While this data can, in theory, be used to reproduce results in papers, it is difficult to use in practice. We introduce a series of tools for processing and analyzing RNA-Seq data in the Sequence Read Archive, that together have allowed us to build an easily extendable resource for analysis of data underlying published papers. Our system makes the exploration of data easily accessible and usable without technical expertise. Our database and associated tools can be accessed at The Lair: http://pachterlab.github.io/lair.