HapRice, an SNP haplotype database and a web tool for rice

Haplotype-based breeding: A new insight in crop improvement

Haplotype-based breeding (HBB) is one of the cutting-edge technologies in the realm of crop improvement due to the increasing availability of Single Nucleotide Polymorphisms identified by Next Generation Sequencing technologies. The complexity of the data can be decreased with fewer statistical tests and a lower probability of spurious associations by combining thousands of SNPs into a few hundred haplotype blocks. The presence of strong genomic regions in breeding lines of most crop species facilitates the use of haplotypes to improve the efficiency of genomic and marker-assisted selection. Haplotype-based breeding as a Genomic Assisted Breeding (GAB) approach harnesses the genome sequence data to pinpoint the allelic variation used to hasten the breeding cycle and circumvent the challenges associated with linkage drag. This review article demonstrates ways to identify candidate genes, superior haplotype identification, haplo-pheno analysis, and haplotype-based marker-assisted selection. The crop improvement strategies that utilize superior haplotypes will hasten the breeding progress to safeguard global food security.

Genomics and transcriptomics to protect rice (Oryza sativa. L.) from abiotic stressors: -pathways to achieving zero hunger

More over half of the world's population depends on rice as a major food crop. Rice (Oryza sativa L.) is vulnerable to abiotic challenges including drought, cold, and salinity since it grown in semi-aquatic, tropical, or subtropical settings. Abiotic stress resistance has bred into rice plants since the earliest rice cultivation techniques. Prior to the discovery of the genome, abiotic stress-related genes were identified using forward genetic methods, and abiotic stress-tolerant lines have developed using traditional breeding methods. Dynamic transcriptome expression represents the degree of gene expression in a specific cell, tissue, or organ of an individual organism at a specific point in its growth and development. Transcriptomics can reveal the expression at the entire genome level during stressful conditions from the entire transcriptional level, which can be helpful in understanding the intricate regulatory network relating to the stress tolerance and adaptability of plants. Rice (Oryza sativa L.) gene families found comparatively using the reference genome sequences of other plant species, allowing for genome-wide identification. Transcriptomics via gene expression profiling which have recently dominated by RNA-seq complements genomic techniques. The identification of numerous important qtl,s genes, promoter elements, transcription factors and miRNAs involved in rice response to abiotic stress was made possible by all of these genomic and transcriptomic techniques. The use of several genomes and transcriptome methodologies to comprehend rice (Oryza sativa, L.) ability to withstand abiotic stress have been discussed in this review.

Duplication of a manganese/cadmium transporter gene reduces cadmium accumulation in rice grain

Global contamination of soils with toxic cadmium (Cd) is a serious health threat. Here we found that a tandem duplication of a gene encoding a manganese/Cd transporter, OsNramp5, was responsible for low-Cd accumulation in Pokkali, an old rice cultivar. This duplication doubled the expression of OsNramp5 gene but did not alter its spatial expression pattern and cellular localization. Higher expression of OsNramp5 increased uptake of Cd and Mn into the root cells but decreased Cd release to the xylem. Introgression of this allele into Koshihikari, an elite rice cultivar, through backcrossing significantly reduced Cd accumulation in the grain when cultivated in soil heavily contaminated with Cd but did not affect both grain yield and eating quality. This study not only reveals the molecular mechanism underlying low-Cd accumulation but also provides a useful target for breeding rice cultivars with low-Cd accumulation.

CONSTANS Polymorphism Modulates Flowering Time and Maturity in Soybean

CONSTANS (CO) plays a critical role in the photoperiodic flowering pathway. However, the function of soybean CO orthologs and the molecular mechanisms in regulating flowering remain largely unknown. This study characterized the natural variations in CO family genes and their association with flowering time and maturity in soybeans. A total of 21 soybean CO family genes (GmCOLs) were cloned and sequenced in 128 varieties covering 14 known maturity groups (MG 0000-MG X from earliest to latest maturity). Regarding the whole genomic region involving these genes, GmCOL1, GmCOL3, GmCOL8, GmCOL9, GmCOL10, and GmCOL13 were conserved, and the remaining 15 genes showed genetic variation that was brought about by mutation, namely, all single-nucleotide polymorphisms (SNPs) and insertions-deletions (InDels). In addition, a few genes showed some strong linkage disequilibrium. Point mutations were found in 15 GmCOL genes, which can lead to changes in the potential protein structure. Early flowering and maturation were related to eight genes (GmCOL1/3/4/8/13/15/16/19). For flowering and maturation, 11 genes (GmCOL2/5/6/14/20/22/23/24/25/26/28) expressed divergent physiognomy. Haplotype analysis indicated that the haplotypes of GmCOL5-Hap2, GmCOL13-Hap2/3, and GmCOL28-Hap2 were associated with flowering dates and soybean maturity. This study helps address the role of GmCOL family genes in adapting to diverse environments, particularly when it is necessary to regulate soybean flowering dates and maturity.

A first-generation haplotype map (HapMap-1) of tea (Camellia sinensis L. O. Kuntz)

MOTIVATION

Tea is a cross-pollinated woody perennial plant, which is why, application of conventional breeding is limited for its genetic improvement. However, lack of the genome-wide high-density SNP markers and genome-wide haplotype information has greatly hampered the utilization of tea genetic resources toward fast-track tea breeding programs. To address this challenge, we have generated a first-generation haplotype map of tea (Tea HapMap-1). Out-crossing and highly heterozygous nature of tea plants, make them more complicated for DNA-level variant discovery.

RESULTS

In this study, whole genome re-sequencing data of 369 tea genotypes were used to generate 2,334,564 biallelic SNPs and 1,447,985 InDels. Around 2928.04 million paired-end reads were used with an average mapping depth of ∼0.31× per accession. Identified polymorphic sites in this study will be useful in mapping the genomic regions responsible for important traits of tea. These resources lay the foundation for future research to understand the genetic diversity within tea germplasm and utilize genes that determine tea quality. This will further facilitate the understanding of tea genome evolution and tea metabolite pathways thus, offers an effective germplasm utilization for breeding the tea varieties.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Toward Integrated Multi-Omics Intervention: Rice Trait Improvement and Stress Management

Rice (Oryza sativa) is an imperative staple crop for nearly half of the world's population. Challenging environmental conditions encompassing abiotic and biotic stresses negatively impact the quality and yield of rice. To assure food supply for the unprecedented ever-growing world population, the improvement of rice as a crop is of utmost importance. In this era, "omics" techniques have been comprehensively utilized to decipher the regulatory mechanisms and cellular intricacies in rice. Advancements in omics technologies have provided a strong platform for the reliable exploration of genetic resources involved in rice trait development. Omics disciplines like genomics, transcriptomics, proteomics, and metabolomics have significantly contributed toward the achievement of desired improvements in rice under optimal and stressful environments. The present review recapitulates the basic and applied multi-omics technologies in providing new orchestration toward the improvement of rice desirable traits. The article also provides a catalog of current scenario of omics applications in comprehending this imperative crop in relation to yield enhancement and various environmental stresses. Further, the appropriate databases in the field of data science to analyze big data, and retrieve relevant information vis-à-vis rice trait improvement and stress management are described.

BarleyVarDB: a database of barley genomic variation

Barley (Hordeum vulgare L.) is one of the first domesticated grain crops and represents the fourth most important cereal source for human and animal consumption. BarleyVarDB is a database of barley genomic variation. It can be publicly accessible through the website at http://146.118.64.11/BarleyVar. This database mainly provides three sets of information. First, there are 57 754 224 single nuclear polymorphisms (SNPs) and 3 600 663 insertions or deletions (InDels) included in BarleyVarDB, which were identified from high-coverage whole genome sequencing of 21 barley germplasm, including 8 wild barley accessions from 3 barley evolutionary original centers and 13 barley landraces from different continents. Second, it uses the latest barley genome reference and its annotation information publicly accessible, which has been achieved by the International Barley Genome Sequencing Consortium (IBSC). Third, 522 212 whole genome-wide microsatellites/simple sequence repeats (SSRs) were also included in this database, which were identified in the reference barley pseudo-molecular genome sequence. Additionally, several useful web-based applications are provided including JBrowse, BLAST and Primer3. Users can design PCR primers to asses polymorphic variants deposited in this database and use a user-friendly interface for accessing the barley reference genome. We envisage that the BarleyVarDB will benefit the barley genetic research community by providing access to all publicly available barley genomic variation information and barley reference genome as well as providing them with an ultra-high density of SNP and InDel markers for molecular breeding and identification of functional genes with important agronomic traits in barley. Database URL: http://146.118.64.11/BarleyVar.

Association mapping identifies quantitative trait loci (QTL) for digestibility in rice straw

BACKGROUND

The conversion of lignocellulosic biomass from agricultural waste into biofuels and chemicals is considered a promising way to provide sustainable low carbon products without compromising food security. However, the use of lignocellulosic biomass for biofuel and chemical production is limited by the cost-effectiveness of the production process due to its recalcitrance to enzymatic hydrolysis and fermentable sugar release (i.e., saccharification). Rice straw is a particularly attractive feedstock because millions of tons are currently burned in the field each year for disposal. The aim of this study was to explore the underlying natural genetic variation that impacts the recalcitrance of rice (Oryza sativa) straw to enzymatic saccharification. Ultimately, we wanted to investigate whether we could identify genetic markers that could be used in rice breeding to improve commercial cultivars for this trait. Here, we describe the development and characterization of a Vietnamese rice genome-wide association panel, high-throughput analysis of rice straw saccharification and lignin content, and the results from preliminary genome-wide association studies (GWAS) of the combined data sets. We identify both QTL and plausible candidate genes that may have an impact on the saccharification of rice straw.

RESULTS

We assembled a diversity panel comprising 151 rice genotypes (Indica and Japonica types) from commercial, historical elite cultivars, and traditional landraces grown in Vietnam. The diversity panel was genotyped using genotype by sequencing (GBS) methods yielding a total of 328,915 single nucleotide polymorphisms (SNPs). We collected phenotypic data from stems of these 151 genotypes for biomass saccharification and lignin content. Using GWAS on the indica genotypes over 2 years we identified ten significant QTL for saccharification (digestibility) and seven significant QTL for lignin. One QTL on chromosome 11 occurred in both GWAS for digestibility and for lignin. Seven QTL for digestibility, on CH2, CH6, CH7, CH8, and CH11, were observed in both years of the study. The QTL regions for saccharification include three potential candidate genes that have been previously reported to influence digestibility: OsAT10; OsIRX9; and OsMYB58/63-L.

CONCLUSIONS

Despite the difficulties associated with multi-phasic analysis of complex traits in novel germplasm, a moderate resolution GWAS successfully identified genetic associations encompassing both known and/or novel genes involved in determining the saccharification potential and lignin content of rice straw. Plausible candidates within QTL regions, in particular those with roles in cell wall biosynthesis, were identified but will require validation to confirm their value for application in rice breeding.

Rice Stress-Resistant SNP Database

BACKGROUND

Rice (Oryza sativa L.) yield is limited inherently by environmental stresses, including biotic and abiotic stresses. Thus, it is of great importance to perform in-depth explorations on the genes that are closely associated with the stress-resistant traits in rice. The existing rice SNP databases have made considerable contributions to rice genomic variation information but none of them have a particular focus on integrating stress-resistant variation and related phenotype data into one web resource.

RESULTS

Rice Stress-Resistant SNP database (http://bioinformatics.fafu.edu.cn/RSRS) mainly focuses on SNPs specific to biotic and abiotic stress-resistant ability in rice, and presents them in a unified web resource platform. The Rice Stress-Resistant SNP (RSRS) database contains over 9.5 million stress-resistant SNPs and 797 stress-resistant candidate genes in rice, which were detected from more than 400 stress-resistant rice varieties. We incorporated the SNPs function, genome annotation and phenotype information into this database. Besides, the database has a user-friendly web interface for users to query, browse and visualize a specific SNP efficiently. RSRS database allows users to query the SNP information and their relevant annotations for individual variety or more varieties. The search results can be visualized graphically in a genome browser or displayed in formatted tables. Users can also align SNPs between two or more rice accessions.

CONCLUSION

RSRS database shows great utility for scientists to further characterize the function of variants related to environmental stress-resistant ability in rice.

Infrastructures of systems biology that facilitate functional genomic study in rice

Rice (Oryza sativa L.) is both a major staple food for the worldwide population and a model crop plant for studying the mode of action of agronomically valuable traits, providing information that can be applied to other crop plants. Due to the development of high-throughput technologies such as next generation sequencing and mass spectrometry, a huge mass of multi-omics data in rice has been accumulated. Through the integration of those data, systems biology in rice is becoming more advanced.To facilitate such systemic approaches, we have summarized current resources, such as databases and tools, for systems biology in rice. In this review, we categorize the resources using six omics levels: genomics, transcriptomics, proteomics, metabolomics, integrated omics, and functional genomics. We provide the names, websites, references, working states, and number of citations for each individual database or tool and discuss future prospects for the integrated understanding of rice gene functions.

Rice Genomics: over the Past Two Decades and into the Future

Domestic rice (Oryza sativa L.) is one of the most important cereal crops, feeding a large number of worldwide populations. Along with various high-throughput genome sequencing projects, rice genomics has been making great headway toward direct field applications of basic research advances in understanding the molecular mechanisms of agronomical traits and utilizing diverse germplasm resources. Here, we briefly review its achievements over the past two decades and present the potential for its bright future.

Genomic adaptation of flowering-time genes during the expansion of rice cultivation area

The diversification of flowering time in response to natural environments is critical for the spread of crops to diverse geographic regions. In contrast with recent advances in understanding the molecular basis of photoperiodic flowering in rice (Oryza sativa), little is known about how flowering-time diversification is structured within rice subspecies. By analyzing genome sequencing data and a set of 429 chromosome segment substitution lines (CSSLs) originating from 10 diverse rice accessions with wide distributions, we revealed diverse effects of allelic variations for common flowering-time quantitative trait loci in the recipient's background. Although functional variations associated with a few loci corresponded to standing variations among subspecies, the identified functional nucleotide polymorphisms occurred recently after rice subgroup differentiation, indicating that the functional diversity of flowering-time gene sequences was not particularly associated with phylogenetic relationship between rice subspecies. Intensive analysis of the Hd1 genomic region identified the signature of an early introgression of the Hd1 with key mutation(s) in aus and temperate japonica accessions. Our data suggested that, after such key introgressions, new mutations were selected and accelerated the flowering-time diversity within subspecies during the expansion of rice cultivation area. This finding may imply that new genome-wide changes for flowering-time adaptation are one of the critical determinants for establishing genomic architecture of local rice subgroups. In-depth analyses of various rice genomes coupling with the genetically confirmed phenotypic changes in a large set of CSSLs enabled us to demonstrate how rice genome dynamics has coordinated with the adaptation of cultivated rice during the expansion of cultivation area.

Inheritance, fine-mapping, and candidate gene analyses of resistance to soybean mosaic virus strain SC5 in soybean

Soybean mosaic virus (SMV) is one of the most devastating pathogens for soybeans in China. Among the country-wide 22 strains, SC5 dominates in Huang-Huai and Changjiang valleys. For controlling its damage, the resistance gene was searched through Mendelian inheritance study, gene fine-mapping, and candidate gene analysis combined with qRT-PCR (quantitative real-time polymerase chain reaction) analysis. The parents F1, F2, and RILs (recombinant inbred lines) of the cross Kefeng-1 (Resistance, R) × NN1138-2 (Susceptible, S) were used to examine the inheritance of SC5-resistance. The F1 was resistant and the F2 and RILs segregated in a 3R:1S and 1R:1S ratio, respectively, indicating a single dominant gene conferring the Kefeng-1 resistance. Subsequently, the genomic region conferring the resistance was found in "Bin 352-Bin353 with 500 kb" on Chromosome 2 using the phenotyping data of the 427 RILs and a high-density genetic map with 4703 bin markers. In the 500 kb genomic region, 38 putative genes are contained. The association analysis between the SNPs in a putative gene and the resistance phenotype for the 427 RILs prioritized 11 candidate genes using Chi-square criterion. The expression levels of these genes were tested by qRT-PCR. On infection with SC5, 7 out of the 11 genes had differential expression in Kefeng-1 and NN1138-2. Furthermore, integrating SNP-phenotype association analysis with qRT-PCR expression profiling analysis, Glyma02g13495 was found the most possible candidate gene for SC5-resistance. This finding can facilitate the breeding for SC5-resistance through marker-assisted selection and provide a platform to gain a better understanding of SMV-resistance gene system in soybean.

In-depth genome characterization of a Brazilian common bean core collection using DArTseq high-density SNP genotyping

BACKGROUND

Common bean is a legume of social and nutritional importance as a food crop, cultivated worldwide especially in developing countries, accounting for an important source of income for small farmers. The availability of the complete sequences of the two common bean genomes has dramatically accelerated and has enabled new experimental strategies to be applied for genetic research. DArTseq has been widely used as a method of SNP genotyping allowing comprehensive genome coverage with genetic applications in common bean breeding programs.

RESULTS

Using this technology, 6286 SNPs (1 SNP/86.5 Kbp) were genotyped in genic (43.3%) and non-genic regions (56.7%). Genetic subdivision associated to the common bean gene pools (K = 2) and related to grain types (K = 3 and K = 5) were reported. A total of 83% and 91% of all SNPs were polymorphic within the Andean and Mesoamerican gene pools, respectively, and 26% were able to differentiate the gene pools. Genetic diversity analysis revealed an average H E of 0.442 for the whole collection, 0.102 for Andean and 0.168 for Mesoamerican gene pools (F ST  = 0.747 between gene pools), 0.440 for the group of cultivars and lines, and 0.448 for the group of landrace accessions (F ST  = 0.002 between cultivar/line and landrace groups). The SNP effects were predicted with predominance of impact on non-coding regions (77.8%). SNPs under selection were identified within gene pools comparing landrace and cultivar/line germplasm groups (Andean: 18; Mesoamerican: 69) and between the gene pools (59 SNPs), predominantly on chromosomes 1 and 9. The LD extension estimate corrected for population structure and relatedness (r2SV) was ~ 88 kbp, while for the Andean gene pool was ~ 395 kbp, and for the Mesoamerican was ~ 130 kbp.

CONCLUSIONS

For common bean, DArTseq provides an efficient and cost-effective strategy of generating SNPs for large-scale genome-wide studies. The DArTseq resulted in an operational panel of 560 polymorphic SNPs in linkage equilibrium, providing high genome coverage. This SNP set could be used in genotyping platforms with many applications, such as population genetics, phylogeny relation between common bean varieties and support to molecular breeding approaches.

Low-cesium rice: mutation in OsSOS2 reduces radiocesium in rice grains

In Japan, radiocesium contamination in foods has become of great concern and it is a primary issue to reduce grain radiocesium concentration in rice (Oryza sativa L.). Here, we report a low-cesium rice mutant 1 (lcs1) with the radiocesium concentration in grain about half that in the wild-type cultivar. Genetic analyses revealed that a mutation in OsSOS2, which encodes a serine/threonine-protein kinase required for the salt overly sensitive (SOS) pathway in plants, is responsible for the decreased cesium (Cs) concentrations in lcs1. Physiological analyses showed that Cs+ uptake by lcs1 roots was significantly decreased under low-potassium (K+) conditions in the presence of sodium (Na+) (low K+/Na+). The transcript levels of several K+ and Na+ transporter genes, such as OsHAK1, OsHAK5, OsAKT1, and OsHKT2;1 were significantly down-regulated in lcs1 grown at low K+/Na+. The decreased Cs+ uptake in lcs1 might be closely related to the lower expression of these genes due to the K+/Na+ imbalance in the lcs1 roots caused by the OsSOS2 mutation. Since the lcs1 plant had no significant negative effects on agronomic traits when grown in radiocesium-contaminated paddy fields, this mutant could be used directly in agriculture for reducing radiocesium in rice grains.

Single Marker and Haplotype-Based Association Analysis of Semolina and Pasta Colour in Elite Durum Wheat Breeding Lines Using a High-Density Consensus Map

Association mapping is usually performed by testing the correlation between a single marker and phenotypes. However, because patterns of variation within genomes are inherited as blocks, clustering markers into haplotypes for genome-wide scans could be a worthwhile approach to improve statistical power to detect associations. The availability of high-density molecular data allows the possibility to assess the potential of both approaches to identify marker-trait associations in durum wheat. In the present study, we used single marker- and haplotype-based approaches to identify loci associated with semolina and pasta colour in durum wheat, the main objective being to evaluate the potential benefits of haplotype-based analysis for identifying quantitative trait loci. One hundred sixty-nine durum lines were genotyped using the Illumina 90K Infinium iSelect assay, and 12,234 polymorphic single nucleotide polymorphism (SNP) markers were generated and used to assess the population structure and the linkage disequilibrium (LD) patterns. A total of 8,581 SNPs previously localized to a high-density consensus map were clustered into 406 haplotype blocks based on the average LD distance of 5.3 cM. Combining multiple SNPs into haplotype blocks increased the average polymorphism information content (PIC) from 0.27 per SNP to 0.50 per haplotype. The haplotype-based analysis identified 12 loci associated with grain pigment colour traits, including the five loci identified by the single marker-based analysis. Furthermore, the haplotype-based analysis resulted in an increase of the phenotypic variance explained (50.4% on average) and the allelic effect (33.7% on average) when compared to single marker analysis. The presence of multiple allelic combinations within each haplotype locus offers potential for screening the most favorable haplotype series and may facilitate marker-assisted selection of grain pigment colour in durum wheat. These results suggest a benefit of haplotype-based analysis over single marker analysis to detect loci associated with colour traits in durum wheat.

The Development of Quality Control Genotyping Approaches: A Case Study Using Elite Maize Lines

Quality control (QC) of germplasm identity and purity is a critical component of breeding and conservation activities. SNP genotyping technologies and increased availability of markers provide the opportunity to employ genotyping as a low-cost and robust component of this QC. In the public sector available low-cost SNP QC genotyping methods have been developed from a very limited panel of markers of 1,000 to 1,500 markers without broad selection of the most informative SNPs. Selection of optimal SNPs and definition of appropriate germplasm sampling in addition to platform section impact on logistical and resource-use considerations for breeding and conservation applications when mainstreaming QC. In order to address these issues, we evaluated the selection and use of SNPs for QC applications from large DArTSeq data sets generated from CIMMYT maize inbred lines (CMLs). Two QC genotyping strategies were developed, the first is a “rapid QC”, employing a small number of SNPs to identify potential mislabeling of seed packages or plots, the second is a “broad QC”, employing a larger number of SNP, used to identify each germplasm entry and to measure heterogeneity. The optimal marker selection strategies combined the selection of markers with high minor allele frequency, sampling of clustered SNP in proportion to marker cluster distance and selecting markers that maintain a uniform genomic distribution. The rapid and broad QC SNP panels selected using this approach were further validated using blind test assessments of related re-generation samples. The influence of sampling within each line was evaluated. Sampling 192 individuals would result in close to 100% possibility of detecting a 5% contamination in the entry, and approximately a 98% probability to detect a 2% contamination of the line. These results provide a framework for the establishment of QC genotyping. A comparison of financial and time costs for use of these approaches across different platforms is discussed providing a framework for institutions involved in maize conservation and breeding to assess the resource use effectiveness of QC genotyping. Application of these research findings, in combination with existing QC approaches, will ensure the regeneration, distribution and use in breeding of true to type inbred germplasm. These findings also provide an effective approach to optimize SNP selection for QC genotyping in other species.

The Vigna Genome Server, 'VigGS': A Genomic Knowledge Base of the Genus Vigna Based on High-Quality, Annotated Genome Sequence of the Azuki Bean, Vigna angularis (Willd.) Ohwi & Ohashi

The genus Vigna includes legume crops such as cowpea, mungbean and azuki bean, as well as >100 wild species. A number of the wild species are highly tolerant to severe environmental conditions including high-salinity, acid or alkaline soil; drought; flooding; and pests and diseases. These features of the genus Vigna make it a good target for investigation of genetic diversity in adaptation to stressful environments; however, a lack of genomic information has hindered such research in this genus. Here, we present a genome database of the genus Vigna, Vigna Genome Server ('VigGS', http://viggs.dna.affrc.go.jp), based on the recently sequenced azuki bean genome, which incorporates annotated exon-intron structures, along with evidence for transcripts and proteins, visualized in GBrowse. VigGS also facilitates user construction of multiple alignments between azuki bean genes and those of six related dicot species. In addition, the database displays sequence polymorphisms between azuki bean and its wild relatives and enables users to design primer sequences targeting any variant site. VigGS offers a simple keyword search in addition to sequence similarity searches using BLAST and BLAT. To incorporate up to date genomic information, VigGS automatically receives newly deposited mRNA sequences of pre-set species from the public database once a week. Users can refer to not only gene structures mapped on the azuki bean genome on GBrowse but also relevant literature of the genes. VigGS will contribute to genomic research into plant biotic and abiotic stresses and to the future development of new stress-tolerant crops.

QTLs underlying natural variation of root growth angle among rice cultivars with the same functional allele of DEEPER ROOTING 1

BACKGROUND

The functional allele of the rice gene DEEPER ROOTING 1 (DRO1) increases the root growth angle (RGA). However, wide natural variation in RGA is observed among rice cultivars with the functional DRO1 allele. To elucidate genetic factors related to such variation, we quantitatively measured RGA using the basket method and analyzed quantitative trait loci (QTLs) for RGA in three F2 mapping populations derived from crosses between the large RGA-type cultivar Kinandang Patong and each of three accessions with varying RGA: Momiroman has small RGA and was used to produce the MoK-F2 population; Yumeaoba has intermediate RGA (YuK-F2 population); Tachisugata has large RGA (TaK-F2 population). All four accessions belong to the same haplotype group of functional DRO1 allele.

RESULTS

We detected the following statistically significant QTLs: one QTL on chromosome 4 in MoK-F2, three QTLs on chromosomes 2, 4, and 6 in YuK-F2, and one QTL on chromosome 2 in TaK-F2. Among them, the two QTLs on chromosome 4 were located near DRO2, which has been previously reported as a major QTL for RGA, whereas the two major QTLs for RGA on chromosomes 2 (DRO4) and 6 (DRO5) were novel. With the LOD threshold reduced to 3.0, several minor QTLs for RGA were also detected in each population.

CONCLUSION

Natural variation in RGA in rice cultivars carrying functional DRO1 alleles may be controlled by a few major QTLs and by several additional minor QTLs.

A QTL for root growth angle on rice chromosome 7 is involved in the genetic pathway of DEEPER ROOTING 1

BACKGROUND

Root growth angle (RGA) is an important trait that influences the ability of rice to avoid drought stress. DEEPER ROOTING 1 (DRO1), which is a major quantitative trait locus (QTL) for RGA, is responsible for the difference in RGA between the shallow-rooting cultivar IR64 and the deep-rooting cultivar Kinandang Patong. However, the RGA differences between these cultivars cannot be fully explained by DRO1. The objective of this study was to identify new QTLs for RGA explaining the difference in RGA between these cultivars.

RESULTS

By crossing IR64 (which has a non-functional allele of DRO1) with Kinandang Patong (which has a functional allele of DRO1), we developed 26 chromosome segment substitution lines (CSSLs) that carried a particular chromosome segment from Kinandang Patong in the IR64 genetic background. Using these CSSLs, we found only one chromosomal region that was related to RGA: on chromosome 9, which includes DRO1. Using an F2 population derived from a cross between Kinandang Patong and the Dro1-NIL (near isogenic line), which had a functional DRO1 allele in the IR64 genetic background, we identified a new QTL for RGA (DRO3) on the long arm of chromosome 7.

CONCLUSIONS

DRO3 may only affect RGA in plants with a functional DRO1 allele, suggesting that DRO3 is involved in the DRO1 genetic pathway.

Triticeae resources in Ensembl Plants

Recent developments in DNA sequencing have enabled the large and complex genomes of many crop species to be determined for the first time, even those previously intractable due to their polyploid nature. Indeed, over the course of the last 2 years, the genome sequences of several commercially important cereals, notably barley and bread wheat, have become available, as well as those of related wild species. While still incomplete, comparison with other, more completely assembled species suggests that coverage of genic regions is likely to be high. Ensembl Plants (http://plants.ensembl.org) is an integrative resource organizing, analyzing and visualizing genome-scale information for important crop and model plants. Available data include reference genome sequence, variant loci, gene models and functional annotation. For variant loci, individual and population genotypes, linkage information and, where available, phenotypic information are shown. Comparative analyses are performed on DNA and protein sequence alignments. The resulting genome alignments and gene trees, representing the implied evolutionary history of the gene family, are made available for visualization and analysis. Driven by the case of bread wheat, specific extensions to the analysis pipelines and web interface have recently been developed to support polyploid genomes. Data in Ensembl Plants is accessible through a genome browser incorporating various specialist interfaces for different data types, and through a variety of additional methods for programmatic access and data mining. These interfaces are consistent with those offered through the Ensembl interface for the genomes of non-plant species, including those of plant pathogens, pests and pollinators, facilitating the study of the plant in its environment.

MorTAL Kombat: the story of defense against TAL effectors through loss-of-susceptibility

Many plant-pathogenic xanthomonads rely on Transcription Activator-Like (TAL) effectors to colonize their host. This particular family of type III effectors functions as specific plant transcription factors via a programmable DNA-binding domain. Upon binding to the promoters of plant disease susceptibility genes in a sequence-specific manner, the expression of these host genes is induced. However, plants have evolved specific strategies to counter the action of TAL effectors and confer resistance. One mechanism is to avoid the binding of TAL effectors by mutations of their DNA binding sites, resulting in resistance by loss-of-susceptibility. This article reviews our current knowledge of the susceptibility hubs targeted by Xanthomonas TAL effectors, possible evolutionary scenarios for plants to combat the pathogen with loss-of-function alleles, and how this knowledge can be used overall to develop new pathogen-informed breeding strategies and improve crop resistance.

MorTAL Kombat: the story of defense against TAL effectors through loss-of-susceptibility

Many plant-pathogenic xanthomonads rely on Transcription Activator-Like (TAL) effectors to colonize their host. This particular family of type III effectors functions as specific plant transcription factors via a programmable DNA-binding domain. Upon binding to the promoters of plant disease susceptibility genes in a sequence-specific manner, the expression of these host genes is induced. However, plants have evolved specific strategies to counter the action of TAL effectors and confer resistance. One mechanism is to avoid the binding of TAL effectors by mutations of their DNA binding sites, resulting in resistance by loss-of-susceptibility. This article reviews our current knowledge of the susceptibility hubs targeted by Xanthomonas TAL effectors, possible evolutionary scenarios for plants to combat the pathogen with loss-of-function alleles, and how this knowledge can be used overall to develop new pathogen-informed breeding strategies and improve crop resistance.

Hybrid breakdown caused by epistasis-based recessive incompatibility in a cross of rice (Oryza sativa L.)

Viability and fertility in organisms depend on epistatic interactions between loci maintained in lineages. Here, we describe reduced fitness of segregants (hybrid breakdown, HB) that emerged in an F2 population derived from a cross between 2 rice (Oryza sativa L.) cultivars, "Tachisugata" (TS) and "Hokuriku 193" (H193), despite both parents and F1s showing normal fitness. Quantitative trait locus (QTL) analyses detected 13 QTLs for 4 morphological traits associated with the HB and 6 associated with principal component scores calculated from values of the morphological traits in the F2 population. Two-way analysis of variance of the putative QTLs identified 4 QTL pairs showing significant epistasis; among them, a pair on chromosomes 1 and 12 made the greatest contribution to HB. The finding was supported by genetic experiments using F3 progeny. HB emerged only when a plant was homozygous for the TS allele at the QTL on chromosome 1 and homozygous for the H193 allele at the QTL on chromosome 12, indicating that each allele behaves as recessive to the other. Our results support the idea that epistasis is an essential part of hybrid fitness.

Arabidopsis thaliana phosphoinositide-specific phospholipase C isoform 3 (AtPLC3) and AtPLC9 have an additive effect on thermotolerance

The heat stress response is an important adaptation, enabling plants to survive challenging environmental conditions. Our previous work demonstrated that Arabidopsis thaliana Phosphoinositide-Specific Phospholipase C Isoform 9 (AtPLC9) plays an important role in thermotolerance. During prolonged heat treatment, mutants of AtPLC3 showed decreased heat resistance. We observed no obvious phenotypic differences between plc3 mutants and wild type (WT) seedlings under normal growth conditions, but after heat shock, the plc3 seedlings displayed a decline in thermotolerance compared with WT, and also showed a 40-50% decrease in survival rate and chlorophyll contents. Expression of AtPLC3 in plc3 mutants rescued the heat-sensitive phenotype; the AtPLC3-overexpressing lines also exhibited much higher heat resistance than WT and vector-only controls. The double mutants of plc3 and plc9 displayed increased sensitivity to heat stress, compared with either single mutant. In transgenic lines containing a AtPLC3:GUS promoter fusion, GUS staining showed that AtPLC3 expresses in all tissues, except anthers and young root tips. Using the Ca(2+)-sensitive fluorescent probe Fluo-3/AM and aequorin reconstitution, we showed that plc3 mutants show a reduction in the heat-induced Ca(2+) increase. The expression of HSP genes (HSP18.2, HSP25.3, HSP70-1 and HSP83) was down-regulated in plc3 mutants and up-regulated in AtPLC3-overexpressing lines after heat shock. These results indicated that AtPLC3 also plays a role in thermotolerance in Arabidopsis, and that AtPLC3 and AtPLC9 function additionally to each other.

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.