Benchmarking database systems for Genomic Selection implementation.

MOTIVATION: With high-throughput genotyping systems now available, it has become feasible to fully integrate genotyping information into breeding programs. To make use of this information effectively requires DNA extraction facilities and marker production facilities that can efficiently deploy the desired set of markers across samples with a rapid turnaround time that allows for selection before crosses needed to be made. In reality, breeders often have a short window of time to make decisions by the time they are able to collect all their phenotyping data and receive corresponding genotyping data. This presents a challenge to organize information and utilize it in downstream analyses to support decisions made by breeders. In order to implement genomic selection routinely as part of breeding programs, one would need an efficient genotyping data storage system. We selected and benchmarked six popular open-source data storage systems, including relational database management and columnar storage systems. RESULTS: We found that data extract times are greatly influenced by the orientation in which genotype data is stored in a system. HDF5 consistently performed best, in part because it can more efficiently work with both orientations of the allele matrix. AVAILABILITY: http://gobiin1.bti.cornell.edu:6083/projects/GBM/repos/benchmarking/browse.

Genomic variation in 3,010 diverse accessions of Asian cultivated rice.

Here we analyse genetic variation, population structure and diversity among 3,010 diverse Asian cultivated rice (Oryza sativa L.) genomes from the 3,000 Rice Genomes Project. Our results are consistent with the five major groups previously recognized, but also suggest several unreported subpopulations that correlate with geographic location. We identified 29 million single nucleotide polymorphisms, 2.4 million small indels and over 90,000 structural variations that contribute to within- and between-population variation. Using pan-genome analyses, we identified more than 10,000 novel full-length protein-coding genes and a high number of presence-absence variations. The complex patterns of introgression observed in domestication genes are consistent with multiple independent rice domestication events. The public availability of data from the 3,000 Rice Genomes Project provides a resource for rice genomics research and breeding.

Allele mining and enhanced genetic recombination for rice breeding.

Traditional rice varieties harbour a large store of genetic diversity with potential to accelerate rice improvement. For a long time, this diversity maintained in the International Rice Genebank has not been fully used because of a lack of genome information. The publication of the first reference genome of Nipponbare by the International Rice Genome Sequencing Project (IRGSP) marked the beginning of a systematic exploration and use of rice diversity for genetic research and breeding. Since then, the Nipponbare genome has served as the reference for the assembly of many additional genomes. The recently completed 3000 Rice Genomes Project together with the public database (SNP-Seek) provides a new genomic and data resource that enables the identification of useful accessions for breeding. Using disease resistance traits as case studies, we demonstrated the power of allele mining in the 3,000 genomes for extracting accessions from the GeneBank for targeted phenotyping. Although potentially useful landraces can now be identified, their use in breeding is often hindered by unfavourable linkages. Efficient breeding designs are much needed to transfer the useful diversity to breeding. Multi-parent Advanced Generation InterCross (MAGIC) is a breeding design to produce highly recombined populations. The MAGIC approach can be used to generate pre-breeding populations with increased genotypic diversity and reduced linkage drag. Allele mining combined with a multi-parent breeding design can help convert useful diversity into breeding-ready genetic resources.

SNP-Seek database of SNPs derived from 3000 rice genomes.

We have identified about 20 million rice SNPs by aligning reads from the 3000 rice genomes project with the Nipponbare genome. The SNPs and allele information are organized into a SNP-Seek system (http://www.oryzasnp.org/iric-portal/), which consists of Oracle database having a total number of rows with SNP genotypes close to 60 billion (20 M SNPs × 3 K rice lines) and web interface for convenient querying. The database allows quick retrieving of SNP alleles for all varieties in a given genome region, finding different alleles from predefined varieties and querying basic passport and morphological phenotypic information about sequenced rice lines. SNPs can be visualized together with the gene structures in JBrowse genome browser. Evolutionary relationships between rice varieties can be explored using phylogenetic trees or multidimensional scaling plots.

Comparative sequence analyses of the major quantitative trait locus phosphorus uptake 1 (Pup1) reveal a complex genetic structure.

The phosphorus uptake 1 (Pup1) locus was identified as a major quantitative trait locus (QTL) for tolerance of phosphorus deficiency in rice. Near-isogenic lines with the Pup1 region from tolerant donor parent Kasalath typically show threefold higher phosphorus uptake and grain yield in phosphorus-deficient field trials than the intolerant parent Nipponbare. In this study, we report the fine mapping of the Pup1 locus to the long arm of chromosome 12 (15.31-15.47 Mb). Genes in the region were initially identified on the basis of the Nipponbare reference genome, but did not reveal any obvious candidate genes related to phosphorus uptake. Kasalath BAC clones were therefore sequenced and revealed a 278-kbp sequence significantly different from the syntenic regions in Nipponbare (145 kb) and in the indica reference genome of 93-11 (742 kbp). Size differences are caused by large insertions or deletions (INDELs), and an exceptionally large number of retrotransposon and transposon-related elements (TEs) present in all three sequences (45%-54%). About 46 kb of the Kasalath sequence did not align with the entire Nipponbare genome, and only three Nipponbare genes (fatty acid alpha-dioxygenase, dirigent protein and aspartic proteinase) are highly conserved in Kasalath. Two Nipponbare genes (expressed proteins) might have evolved by at least three TE integrations in an ancestor gene that is still present in Kasalath. Several predicted Kasalath genes are novel or unknown genes that are mainly located within INDEL regions. Our results highlight the importance of sequencing QTL regions in the respective donor parent, as important genes might not be present in the current reference genomes.

The generation challenge programme platform: semantic standards and workbench for crop science.

The Generation Challenge programme (GCP) is a global crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. A key consortium research activity is the development of a GCP crop bioinformatics platform to support GCP research. This platform includes the following: (i) shared, public platform-independent domain models, ontology, and data formats to enable interoperability of data and analysis flows within the platform; (ii) web service and registry technologies to identify, share, and integrate information across diverse, globally dispersed data sources, as well as to access high-performance computational (HPC) facilities for computationally intensive, high-throughput analyses of project data; (iii) platform-specific middleware reference implementations of the domain model integrating a suite of public (largely open-access/-source) databases and software tools into a workbench to facilitate biodiversity analysis, comparative analysis of crop genomic data, and plant breeding decision making.

The Generation Challenge Programme comparative plant stress-responsive gene catalogue.

The Generation Challenge Programme (GCP; www.generationcp.org) has developed an online resource documenting stress-responsive genes comparatively across plant species. This public resource is a compendium of protein families, phylogenetic trees, multiple sequence alignments (MSA) and associated experimental evidence. The central objective of this resource is to elucidate orthologous and paralogous relationships between plant genes that may be involved in response to environmental stress, mainly abiotic stresses such as water deficit ('drought'). The web-based graphical user interface (GUI) of the resource includes query and visualization tools that allow diverse searches and browsing of the underlying project database. The web interface can be accessed at http://dayhoff.generationcp.org.

Chemical- and irradiation-induced mutants of indica rice IR64 for forward and reverse genetics.

IR64, the most widely grown indica rice in South and Southeast Asia, possesses many positive agronomic characteristics (e.g., wide adaptability, high yield potential, tolerance to multiple diseases and pests, and good eating quality,) that make it an ideal genotype for identifying mutational changes in traits of agronomic importance. We have produced a large collection of chemical and irradiation-induced IR64 mutants with different genetic lesions that are amenable to both forward and reverse genetics. About 60,000 IR64 mutants have been generated by mutagenesis using chemicals (diepoxybutane and ethylmethanesulfonate) and irradiation (fast neutron and gamma ray). More than 38,000 independent lines have been advanced to M4 generation enabling evaluation of quantitative traits by replicated trials. Morphological variations at vegetative and reproductive stages, including plant architecture, growth habit, pigmentation and various physiological characters, are commonly observed in the four mutagenized populations. Conditional mutants such as gain or loss of resistance to blast, bacterial blight, and tungro disease have been identified at frequencies ranging from 0.01% to 0.1%. Results from pilot experiments indicate that the mutant collections are suitable for reverse genetics through PCR-detection of deletions and TILLING. Furthermore, deletions can be detected using oligomer chips suggesting a general technique to pinpoint deletions when genome-wide oligomer chips are broadly available. M4 mutant seeds are available for users for screening of altered response to multiple stresses. So far, more than 15,000 mutant lines have been distributed. To facilitate broad usage of the mutants, a mutant database has been constructed in the International Rice Information System (IRIS; http: //www.iris.irri.org) to document the phenotypes and gene function discovered by users.

Linking genotype to phenotype: the International Rice Information System (IRIS).

The International Rice Information System (IRIS, http://www.iris.irri.org) is the rice implementation of the International Crop Information System (ICIS, http://www.icis.cgiar.org), a database system for the management and integration of global information on genetic resources and germplasm improvement for any crop. Building upon the germplasm genealogy and field data components of ICIS, IRIS is being extended to handle diverse rice genomics data including: genetic mapping, genome annotation, genotype, mutant, transcripteome, proteome and metabolomic data. Users can access information in the database through stand-alone programs and WWW interfaces offering specialist views to researchers with different interests.