Quantitative trait loci for rice blast resistance detected in a local rice breeding population by genome-wide association mapping

GWAS analysis reveals the genetic basis of blast resistance associated with heading date in rice

Rice blast is a destructive fungal disease affecting rice plants at various growth stages, significantly threatening global yield stability. Development of resistant rice cultivars stands as a practical means of disease control. Generally, association mapping with a diversity panel powerfully identifies new alleles controlling trait of interest. On the other hand, utilization of a breeding panel has its advantage that can be directly applied in a breeding program. In this study, we conducted a genome-wide association study (GWAS) for blast resistance using 296 commercial rice cultivars with low population structure but large phenotypic diversity. We attempt to answer the genetic basis behind rice blast resistance among early maturing cultivars by subdividing the population based on its Heading date 1 (Hd1) functionality. Subpopulation-specific GWAS using the mixed linear model (MLM) based on blast nursery screening conducted in three years revealed a total of 26 significant signals, including three nucleotide-binding site leucine-rich repeat (NBS-LRR) genes (Os06g0286500, Os06g0286700, and Os06g0287500) located at Piz locus on chromosome 6, and one at the Pi-ta locus (Os12g0281300) on chromosome 12. Haplotype analysis revealed blast resistance associated with Piz locus was exclusively specific to Type 14 hd1 among japonica rice. Our findings provide valuable insights for breeding blast resistant rice and highlight the applicability of our elite cultivar panel to detect superior alleles associated with important agronomic traits.

Advancement in the Breeding, Biotechnological and Genomic Tools towards Development of Durable Genetic Resistance against the Rice Blast Disease

Rice production needs to be sustained in the coming decades, as the changeable climatic conditions are becoming more conducive to disease outbreaks. The majority of rice diseases cause enormous economic damage and yield instability. Among them, rice blast caused by Magnaportheoryzae is a serious fungal disease and is considered one of the major threats to world rice production. This pathogen can infect the above-ground tissues of rice plants at any growth stage and causes complete crop failure under favorable conditions. Therefore, management of blast disease is essentially required to sustain global food production. When looking at the drawback of chemical management strategy, the development of durable, resistant varieties is one of the most sustainable, economic, and environment-friendly approaches to counter the outbreaks of rice blasts. Interestingly, several blast-resistant rice cultivars have been developed with the help of breeding and biotechnological methods. In addition, 146 R genes have been identified, and 37 among them have been molecularly characterized to date. Further, more than 500 loci have been identified for blast resistance which enhances the resources for developing blast resistance through marker-assisted selection (MAS), marker-assisted backcross breeding (MABB), and genome editing tools. Apart from these, a better understanding of rice blast pathogens, the infection process of the pathogen, and the genetics of the immune response of the host plant are very important for the effective management of the blast disease. Further, high throughput phenotyping and disease screening protocols have played significant roles in easy comprehension of the mechanism of disease spread. The present review critically emphasizes the pathogenesis, pathogenomics, screening techniques, traditional and molecular breeding approaches, and transgenic and genome editing tools to develop a broad spectrum and durable resistance against blast disease in rice. The updated and comprehensive information presented in this review would be definitely helpful for the researchers, breeders, and students in the planning and execution of a resistance breeding program in rice against this pathogen.

Genome-wide association mapping for resistance to bacterial blight and bacterial leaf streak in rice

Using genome-wide SNP association mapping, a total of 77 and 7 loci were identified for rice bacterial blight and bacterial leaf streak resistance, respectively, which may facilitate rice resistance improvement. Bacterial blight (BB) and bacterial leaf streak (BLS) caused by Gram-negative bacteria Xanthomonas oryzae pv. oryzae (Xoo) and X. oryzae pv. oryzicola (Xoc), respectively, are two economically important diseases negatively affecting rice production. To mine new sources of resistance, a set of rice germplasm collection consisting of 895 re-sequenced accessions from the 3000 Rice Genomes Project (3 K RGP) were screened for BB and BLS resistance under field conditions. Higher levels of BB resistance were observed in aus/boro subgroup, whereas the japonica, temperate japonica and tropical japonica subgroups possessed comparatively high levels of resistance to BLS. A genome-wide association study (GWAS) mined 77 genomic loci significantly associated with BB and 7 with BLS resistance. The phenotypic variance (R²) explained by these loci ranged from 0.4 to 30.2%. Among the loci, 7 for BB resistance were co-localized with known BB resistance genes and one for BLS resistance overlapped with a previously reported BLS resistance QTL. A search for the candidates in other novel loci revealed several defense-related genes that may be involved in resistance to BB and BLS. High levels of phenotypic resistance to BB or BLS could be attributed to the accumulation of the resistance (R) alleles at the associated loci, indicating their potential value in rice resistance breeding via gene pyramiding. The GWAS analysis validated the known genes underlying BB and BLS resistance and identified novel loci that could enrich the current resistance gene pool. The resources with strong resistance and significant SNPs identified in this study are potentially useful in breeding for BB and BLS resistance.

Translation of continuous artificial selection on phenotype into genotype during rice breeding programs

Understanding genetic diversity among local populations is a primary goal of modern crop breeding programs. Here, we demonstrated the genetic relationships of rice varieties in Hokkaido, Japan, one of the northern limits of rice cultivation around the world. Furthermore, artificial selection during rice breeding programs has been characterized using genome sequences. We utilized 8,565 single nucleotide polymorphisms and insertion/deletion markers distributed across the genome in genotype-by-sequencing for genetic diversity analyses. Phylogenetics, genetic population structure, and principal component analysis showed that a total of 110 varieties were classified into four distinct clusters according to different populations geographically and historically. Furthermore, the genome sequences of 19 rice varieties along with historic representations in Hokkaido, nucleotide diversity and F_ST values in each cluster revealed that artificial selection of elite phenotypes focused on chromosomal regions. These results clearly demonstrated the history of the selections on agronomic traits as genome sequences among current rice varieties from Hokkaido.

Marker-assisted selection in rice breeding programs in Hokkaido

Rice breeding programs in Hokkaido over the past 100 years have dramatically increased productivity and improved the eating quality of rice. Commercial varieties with high yield and good eating quality, such as Kirara 397, Hoshinoyume, and Nanatsuboshi, have been continuously registered since 1990. Furthermore, varieties with better eating quality using Wx1-1, which reduces amylose content to improve the taste of sticky rice, such as Oborozuki and Yumepirika, were registered in 2006 and 2008, respectively. However, to the best of our knowledge the genomic changes associated with these improvements have not been determined. Better understanding of the relationships between DNA sequences and agricultural traits could facilitate rice breeding programs in Hokkaido. Marker-assisted selection (MAS), which can select the plants with chromosomal regions tagged with DNA markers for desirable traits, is an advanced technology to manage genetic improvements. Here, we summarize the current states of MAS in rice breeding programs in Hokkaido before huge data sets of genome sequences using next-generation sequencing technology come into practical use in rice breeding programs.

Introgression of the chromosomal region with the Pi-cd locus from Oryza meridionalis into O. sativa L. during rice domestication

The genotype of the Pi-cd locus found in blast-resistant rice variety Kitakurin, which is a cultivated rice from Japan belonging to Oryza sativa japonica, is identical to that of its wild relative O. meridionalis. Crop domestication from wild relatives to cultivated species has encompassed significant phenotypic changes. However, little is known about the genetic changes involved in domestication. Here, we surveyed the origin of the Pi-cd locus across Oryza species with AA genomes by comparison with the genome sequences of Hoshinoyume (HS), which does not carry the Pi-cd blast resistance gene, and Kitakurin (KK), which carries the Pi-cd blast resistance gene. We found that variety-specific transposons were enriched at the Pi-cd locus. The genotype of the Pi-cd locus characterized by transposons in HS and KK was specific to each Oryza species with the AA genome. The Kitaake (KT) genotype at the Pi-cd locus found in KK was identical only to that of O. meridionalis and distributed only in subgroups of japonica in the World Rice Collection and tropical japonica in the Japanese Rice Collection, whereas it was not present in O. rufipogon accessions. The distinct distributions of genotypes of the Pi-cd locus clearly demonstrated that the Pi-cd locus was introgressed from O. meridionalis into O. sativa, specific to tropical japonica.

Gigwa-Genotype investigator for genome-wide analyses

BACKGROUND

Exploring the structure of genomes and analyzing their evolution is essential to understanding the ecological adaptation of organisms. However, with the large amounts of data being produced by next-generation sequencing, computational challenges arise in terms of storage, search, sharing, analysis and visualization. This is particularly true with regards to studies of genomic variation, which are currently lacking scalable and user-friendly data exploration solutions.

DESCRIPTION

Here we present Gigwa, a web-based tool that provides an easy and intuitive way to explore large amounts of genotyping data by filtering it not only on the basis of variant features, including functional annotations, but also on genotype patterns. The data storage relies on MongoDB, which offers good scalability properties. Gigwa can handle multiple databases and may be deployed in either single- or multi-user mode. In addition, it provides a wide range of popular export formats.

CONCLUSIONS

The Gigwa application is suitable for managing large amounts of genomic variation data. Its user-friendly web interface makes such processing widely accessible. It can either be simply deployed on a workstation or be used to provide a shared data portal for a given community of researchers.