A genotypic and phenotypic information source for marker-assisted selection of cereals: the CEREALAB database

The CEREALAB database aims to store genotypic and phenotypic data obtained by the CEREALAB project and to integrate them with already existing data sources in order to create a tool for plant breeders and geneticists. The database can help them in unravelling the genetics of economically important phenotypic traits; in identifying and choosing molecular markers associated to key traits; and in choosing the desired parentals for breeding programs. The database is divided into three sub-schemas corresponding to the species of interest: wheat, barley and rice; each sub-schema is then divided into two sub-ontologies, regarding genotypic and phenotypic data, respectively

Gramene

Grasses are one of the largest agricultural crops, providing food, industrial materials and renewable energy sources. Due to their large genome size and the number of the species in the taxa, many of the genomes are not targeted for complete sequencing. Gramene seeks to provide basic researchers, industry and educators with a resource that can be used as a tool for knowledge discovery across grass species. This chapter briefly outlines system requirements for end users and database hosting, outlines data types and basic navigation within Gramene and provides an example of how a maize researcher would use Gramene to leverage rice genome organization and phenotypic information to support targeted experimental research in maize

BarleyBase—an expression profiling database for plant genomics

BarleyBase (BB) (www.barleybase.org) is an online database for plant microarrays with integrated tools for data visualization and statistical analysis. BB houses raw and normalized expression data from the two publicly available Affymetrix genome arrays, Barley1 and Arabidopsis ATH1 with plans to include the new Affymetrix 61K wheat, maize, soybean and rice arrays, as they become available. BB contains a broad set of query and display options at all data levels, ranging from experiments to individual hybridizations to probe sets down to individual probes. Users can perform cross-experiment queries on probe sets based on observed expression profiles and/or based on known biological information. Probe set queries are integrated with visualization and analysis tools such as the R statistical toolbox, data filters and a large variety of plot types. Controlled vocabularies for gene and plant ontologies, as well as interconnecting links to physical or genetic map and other genomic data in PlantGDB, Gramene and GrainGenes, allow users to perform EST alignments and gene function prediction using Barley1 exemplar sequences, thus, enhancing cross-species comparison

Construction and application for QTL analysis of a Restriction Site Associated DNA (RAD) linkage map in barley

<p>Abstract</p> <p>Background</p> <p>Linkage maps are an integral resource for dissection of complex genetic traits in plant and animal species. Canonical map construction follows a well-established workflow: an initial discovery phase where genetic markers are mined from a small pool of individuals, followed by genotyping of selected mapping populations using sets of marker panels. A newly developed sequence-based marker technology, Restriction site Associated DNA (RAD), enables synchronous single nucleotide polymorphism (SNP) marker discovery and genotyping using massively parallel sequencing. The objective of this research was to assess the utility of RAD markers for linkage map construction, employing barley as a model system. Using the published high density EST-based SNP map in the Oregon Wolfe Barley (OWB) mapping population as a reference, we created a RAD map using a limited set of prior markers to establish linakge group identity, integrated the RAD and prior data, and used both maps for detection of quantitative trait loci (QTL).</p> <p>Results</p> <p>Using the RAD protocol in tandem with the Illumina sequence by synthesis platform, a total of 530 SNP markers were identified from initial scans of the OWB parental inbred lines - the "dominant" and "recessive" marker stocks - and scored in a 93 member doubled haploid (DH) mapping population. RAD sequence data from the structured population was converted into allele genotypes from which a genetic map was constructed. The assembled RAD-only map consists of 445 markers with an average interval length of 5 cM, while an integrated map includes 463 RAD loci and 2383 prior markers. Sequenced RAD markers are distributed across all seven chromosomes, with polymorphic loci emanating from both coding and noncoding regions in the <it>Hordeum </it>genome. Total map lengths are comparable and the order of common markers is identical in both maps. The same large-effect QTL for reproductive fitness traits were detected with both maps and the majority of these QTL were coincident with a dwarfing gene (<it>ZEO) </it>and the <it>VRS1 </it>gene, which determines the two-row and six-row germplasm groups of barley.</p> <p>Conclusions</p> <p>We demonstrate how sequenced RAD markers can be leveraged to produce high quality linkage maps for detection of single gene loci and QTLs. By combining SNP discovery and genotyping into parallel sequencing events, RAD markers should be a useful molecular breeding tool for a range of crop species. Expected improvements in cost and throughput of second and third-generation sequencing technologies will enable more powerful applications of the sequenced RAD marker system, including improvements in <it>de novo </it>genome assembly, development of ultra-high density genetic maps and association mapping.</p

A roadmap for gene functional characterisation in crops with large genomes: Lessons from polyploid wheat

Understanding the function of genes within staple crops will accelerate crop improvement by allowing targeted breeding approaches. Despite their importance, a lack of genomic information and resources has hindered the functional characterisation of major crop genes. The recent release of high-quality reference sequences for these crops underpins a suite of genetic and genomic resources that support basic research and breeding. For wheat, these include gene model annotations, expression atlases and gene networks that provide information about putative function. Sequenced mutant populations, improved transformation protocols and structured natural populations provide rapid methods to study gene function directly. We highlight a case study exemplifying how to integrate these resources. This review provides a helpful guide for plant scientists, especially those expanding into crop research, to capitalise on the discoveries made in Arabidopsis and other plants. This will accelerate the improvement of crops of vital importance for food and nutrition security

CerealsDB 3.0:Expansion of resources and data integration

BACKGROUND: The 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. DESCRIPTION: CerealsDB 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. CONCLUSION: CerealsDB 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1139-x) contains supplementary material, which is available to authorized users