The 3,000 rice genomes project

Genome-wide indel markers shared by diverse Asian rice cultivars compared to Japanese rice cultivar 'Koshihikari'

Insertion-deletion (indel) polymorphisms, such as simple sequence repeats, have been widely used as DNA markers to identify QTLs and genes and to facilitate rice breeding. Recently, next-generation sequencing has produced deep sequences that allow genome-wide detection of indels. These polymorphisms can potentially be used to develop high-accuracy polymerase chain reaction (PCR)-based markers. Here, re-sequencing of 5 indica, 2 aus, and 3 tropical japonica cultivars and Japanese elite cultivar 'Koshihikari' was performed to extract regions containing large indels (10-51 bp) shared by diverse cultivars. To design indel markers for the discrimination of genomic regions between 'Koshihikari' and other diverse cultivars, we subtracted the indel regions detected in 'Koshihikari' from those shared in other cultivars. Two sets of indel markers, KNJ8-indel (shared in eight or more cultivars, including 'Khao Nam Jen' as a representative tropical japonica cultivar) and C5-indel (shared in five to eight cultivars), were established, with 915 and 9,899 indel regions, respectively. Validation of the two marker sets by using 23 diverse cultivars showed a high PCR success rate (≥95%) for 83.3% of the KNJ8-indel markers and 73.9% of the C5-indel markers. The marker sets will therefore be useful for the effective breeding of Japanese rice cultivars.

Whole genome sequencing of elite rice cultivars as a comprehensive information resource for marker assisted selection

Current advances in sequencing technologies and bioinformatics revealed the genomic background of rice, a staple food for the poor people, and provided the basis to develop large genomic variation databases for thousands of cultivars. Proper analysis of this massive resource is expected to give novel insights into the structure, function, and evolution of the rice genome, and to aid the development of rice varieties through marker assisted selection or genomic selection. In this work we present sequencing and bioinformatics analyses of 104 rice varieties belonging to the major subspecies of Oryza sativa. We identified repetitive elements and recurrent copy number variation covering about 200 Mbp of the rice genome. Genotyping of over 18 million polymorphic locations within O. sativa allowed us to reconstruct the individual haplotype patterns shaping the genomic background of elite varieties used by farmers throughout the Americas. Based on a reconstruction of the alleles for the gene GBSSI, we could identify novel genetic markers for selection of varieties with high amylose content. We expect that both the analysis methods and the genomic information described here would be of great use for the rice research community and for other groups carrying on similar sequencing efforts in other crops.

Designing climate-resilient rice with ideal grain quality suited for high-temperature stress

To ensure rice food security, the target outputs of future rice breeding programmes should focus on developing climate-resilient rice varieties with emphasis on increased head rice yield coupled with superior grain quality. This challenge is made greater by a world that is increasingly becoming warmer. Such environmental changes dramatically impact head rice and milling yield as well as increasing chalkiness because of impairment in starch accumulation and other storage biosynthetic pathways in the grain. This review highlights the knowledge gained through gene discovery via quantitative trait locus (QTL) cloning and structural-functional genomic strategies to reduce chalk, increase head rice yield, and develop stable lines with optimum grain quality in challenging environments. The newly discovered genes and the knowledge gained on the influence of specific alleles related to stability of grain quality attributes provide a robust platform for marker-assisted selection in breeding to design heat-tolerant rice varieties with superior grain quality. Using the chalkiness trait in rice as a case study, we demonstrate here that the emerging field of systems genetics can help fast-track the identification of novel alleles and gene targets that can be pyramided for the development of environmentally robust rice varieties that possess improved grain quality.

Genomic analysis of hybrid rice varieties reveals numerous superior alleles that contribute to heterosis

Exploitation of heterosis is one of the most important applications of genetics in agriculture. However, the genetic mechanisms of heterosis are only partly understood, and a global view of heterosis from a representative number of hybrid combinations is lacking. Here we develop an integrated genomic approach to construct a genome map for 1,495 elite hybrid rice varieties and their inbred parental lines. We investigate 38 agronomic traits and identify 130 associated loci. In-depth analyses of the effects of heterozygous genotypes reveal that there are only a few loci with strong overdominance effects in hybrids, but a strong correlation is observed between the yield and the number of superior alleles. While most parental inbred lines have only a small number of superior alleles, high-yielding hybrid varieties have several. We conclude that the accumulation of numerous rare superior alleles with positive dominance is an important contributor to the heterotic phenomena.

The Arabidopsis alkaline ceramidase TOD1 is a key turgor pressure regulator in plant cells

Turgor pressure plays pivotal roles in the growth and movement of walled cells that make up plants and fungi. However, the molecular mechanisms regulating turgor pressure and the coordination between turgor pressure and cell wall remodelling for cell growth remain poorly understood. Here, we report the characterization of Arabidopsis TurgOr regulation Defect 1 (TOD1), which is preferentially expressed in pollen tubes and silique guard cells. We demonstrate that TOD1 is a Golgi-localized alkaline ceramidase. tod1 mutant pollen tubes have higher turgor than wild type and show growth retardation both in pistils and in agarose medium. In addition, tod1 guard cells are insensitive to abscisic acid (ABA)-induced stomatal closure, whereas sphingosine-1-phosphate, a putative downstream component of ABA signalling and product of alkaline ceramidases, promotes closure in both wild type and tod1. Our data suggest that TOD1 acts in turgor pressure regulation in both guard cells and pollen tubes.

The roots of future rice harvests

Rice production faces the challenge to be enhanced by 50% by year 2030 to meet the growth of the population in rice-eating countries. Whereas yield of cereal crops tend to reach plateaus and a yield is likely to be deeply affected by climate instability and resource scarcity in the coming decades, building rice cultivars harboring root systems that can maintain performance by capturing water and nutrient resources unevenly distributed is a major breeding target. Taking advantage of gathering a community of rice root biologists in a Global Rice Science Partnership workshop held in Montpellier, France, we present here the recent progresses accomplished in this area and focal points where an international network of laboratories should direct their efforts.

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.

diArk--the database for eukaryotic genome and transcriptome assemblies in 2014

Eukaryotic genomes are the basis for understanding the complexity of life from populations to the molecular level. Recent technological innovations have revolutionized the speed of data generation enabling the sequencing of eukaryotic genomes and transcriptomes within days. The database diArk (http://www.diark.org) has been developed with the aim to provide access to all available assembled genomes and transcriptomes. In September 2014, diArk contains about 2600 eukaryotes with 6000 genome and transcriptome assemblies, of which 22% are not available via NCBI/ENA/DDBJ. Several indicators for the quality of the assemblies are provided to facilitate their comparison for selecting the most appropriate dataset for further studies. diArk has a user-friendly web interface with extensive options for filtering and browsing the sequenced eukaryotes. In this new version of the database we have also integrated species, for which transcriptome assemblies are available, and we provide more analyses of assemblies.

Natural variation of root traits: from development to nutrient uptake

The root system has a crucial role for plant growth and productivity. Due to the challenges of heterogeneous soil environments, diverse environmental signals are integrated into root developmental decisions. While root growth and growth responses are genetically determined, there is substantial natural variation for these traits. Studying the genetic basis of the natural variation of root growth traits can not only shed light on their evolution and ecological relevance but also can be used to map the genes and their alleles responsible for the regulation of these traits. Analysis of root phenotypes has revealed growth strategies and root growth responses to a variety of environmental stimuli, as well as the extent of natural variation of a variety of root traits including ion content, cellular properties, and root system architectures. Linkage and association mapping approaches have uncovered causal genes underlying the variation of these traits.

RiceVarMap: a comprehensive database of rice genomic variations

Rice Variation Map (RiceVarMap, http:/ricevarmap.ncpgr.cn) is a database of rice genomic variations. The database provides comprehensive information of 6 551 358 single nucleotide polymorphisms (SNPs) and 1 214 627 insertions/deletions (INDELs) identified from sequencing data of 1479 rice accessions. The SNP genotypes of all accessions were imputed and evaluated, resulting in an overall missing data rate of 0.42% and an estimated accuracy greater than 99%. The SNP/INDEL genotypes of all accessions are available for online query and download. Users can search SNPs/INDELs by identifiers of the SNPs/INDELs, genomic regions, gene identifiers and keywords of gene annotation. Allele frequencies within various subpopulations and the effects of the variation that may alter the protein sequence of a gene are also listed for each SNP/INDEL. The database also provides geographical details and phenotype images for various rice accessions. In particular, the database provides tools to construct haplotype networks and design PCR-primers by taking into account surrounding known genomic variations. These data and tools are highly useful for exploring genetic variations and evolution studies of rice and other species.

The 3,000 rice genomes project: new opportunities and challenges for future rice research

Rice is the world's most important staple grown by millions of small-holder farmers. Sustaining rice production relies on the intelligent use of rice diversity. The 3,000 Rice Genomes Project is a giga-dataset of publically available genome sequences (averaging 14× depth of coverage) derived from 3,000 accessions of rice with global representation of genetic and functional diversity. The seed of these accessions is available from the International Rice Genebank Collection. Together, they are an unprecedented resource for advancing rice science and breeding technology. Our immediate challenge now is to comprehensively and systematically mine this dataset to link genotypic variation to functional variation with the ultimate goal of creating new and sustainable rice varieties that can support a future world population that will approach 9.6 billion by 2050.