The development of efficient, robust, and high-throughput SNP genotyping platforms is pivotal for crop genetics and breeding. Recently, SNP genotyping platforms based on target capture sequencing, which is very flexible in terms of the number of SNP markers, have been developed for maize, cassava, and fava bean. We aimed to develop a target capture sequencing SNP genotyping platform for rice. A target capture sequencing panel containing 2565 SNPs, including 1225 SNPs informative for japonica and 1339 SNPs informative for indica, was developed. This platform was used in diversity analysis of 50 rice varieties. Of the 2565 SNP markers, 2341 (91.3%) produced useful polymorphic genotype data, enabling the production of a phylogenetic tree of the 50 varieties. The mean number of markers polymorphic between any two varieties was 854. The platform was used for QTL mapping of preharvest sprouting (PHS) resistance in an F₈ recombinant inbred line population derived from the cross Odae × Joun. A genetic map comprising 475 markers was constructed, and two QTLs for PHS resistance were identified on chromosomes 4 and 11. This system is a powerful tool for rice genetics and breeding and will facilitate QTL studies and gene mapping, germplasm diversity analysis, and marker-assisted selection.

Temperate japonica rice varieties exhibit wide variation in the phenotypes of several important agronomic traits, including disease resistance, pre-harvest sprouting resistance, plant architecture, and grain quality, indicating the presence of genes contributing to favorable agronomic traits. However, gene mapping and molecular breeding has been hampered as a result of the low genetic diversity among cultivars and scarcity of polymorphic DNA markers. Single nucleotide polymorphism (SNP)-based kompetitive allele-specific PCR (KASP) markers allow high-throughput genotyping for marker-assisted selection and quantitative trait loci (QTL) mapping within closely related populations. Previously, we identified 740,566 SNPs and developed 771 KASP markers for Korean temperate japonica rice varieties. However, additional markers were needed to provide sufficient genome coverage to support breeding programs. In this study, the 740,566 SNPs were categorized according to their predicted impacts on gene function. The high-impact, moderate-impact, modifier, and low-impact groups contained 703 (0.1%), 20,179 (2.7%), 699,866 (94.5%), and 19,818 (2.7%) SNPs, respectively. A subset of 357 SNPs from the high-impact group was selected for initial KASP marker development, resulting in 283 polymorphic KASP markers. After incorporation of the 283 markers with the 771 existing markers in a physical map, additional markers were developed to fill genomic regions with large gaps between markers, and 171 polymorphic KASP markers were successfully developed from 284 SNPs. Overall, a set of 1225 KASP markers was produced. The markers were evenly distributed across the rice genome, with average marker density of 3.3 KASP markers per Mbp. The 1225 KASP markers will facilitate QTL/gene mapping and marker-assisted selection in temperate japonica rice breeding programs.

Bakanae disease (BD), caused by the fungal pathogen Fusarium fujikuroi, is a serious threat to rice production worldwide. Breeding elite rice varieties resistant to BD requires the identification of resistance genes. Previously, we discovered a resistant quantitative trait locus (QTL), qFfR1, in a Korean japonica rice variety, Nampyeong. In this study, we fine-mapped qFfR1 with a Junam^*4/Nampyeong BC₃F₃ population and delimited its location to a 37.1 kb region on chromosome 1. Complementation experiments with seven candidate genes in this region revealed that OsI_02728 is the gene for qFfR1. This gene encodes a protein with a typical leucine-rich repeat (LRR) receptor-like protein structure. RNA-sequencing-based transcriptomic analysis revealed that FfR1 induces the transcription of defense genes, including lignin and terpenoid biosynthesis genes, pathogenesis-related genes, and thionin genes. These results may facilitate investigations into the molecular mechanisms underlying BD resistance, including molecular patterns of Fusarium fujikuroi interacting with FfR1 and players working in signal transduction pathways downstream of FfR1, and the breeding of new BD-resistant varieties by providing a BD resistance gene with its precise selection marker. This will contribute to efficient control of BD, which is becoming more prevalent according to temperature rises due to climate change.

Grain size is a key factor influencing the grain yield in rice. To identify the as-yet-unknown genes regulating grain size in Korean japonica rice, we developed a recombinant inbred line population (n = 162) from a cross between Odae (large-grain) and Joun (small-grain), and measured six traits including the thousand-grain weights of unhulled and hulled seeds, grain area, grain length, grain width and grain length-to-width ratio using high-throughput image analysis at the F₈ and F₉ generations. A genetic map was constructed using 248 kompetitive allele-specific PCR (KASP) markers that were polymorphic between the parental genotypes, and 29 QTLs affecting the six traits were identified, of which 15 were stable in both F₈ and F₉ generations. Notably, three QTL clusters affecting multiple traits were detected on chromosomes 6, 7 and 11. We analyzed whole-genome resequencing data of Odae and Joun, and selected candidate genes for the stable QTLs in the identified clusters that have high- or moderate-impact variations between Odae and Joun and encode proteins the families of which have been reported to be related to grain size regulation. These results will facilitate the identification of genes underlying the QTLs and promote molecular breeding of high-yielding Korean japonica rice varieties.

Acorn size is of great importance, both ecologically and economically. However, the long lifespan is an obstacle to improvement in breeding. Keumsura1ho is a recently bred cultivar of oak (Quercus acutissima Carruth) selected after eight years of selection due to its larger acorns and higher weight compared to the control. In the present study, we investigated the transcriptional mechanisms underlying the outstanding morphological characteristics of Keumsura1ho. For this purpose, one- and two-year-old acorns from the control and Keumsura1ho groups were used for comparative transcriptome analyses of their seeds. Among morphological characteristics, the Keumsura1ho seeds were 18.3% longer than those of the control. Seed width and depth were 33.9% greater than those of the control. In the transcriptome analysis, genes related to seed size were further enriched, with biennial Keumsura1ho showing higher enrichment in comparison to control genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the upregulated genes of the two-year-old Keumsura1ho seeds showed higher enrichment in phenylpropanoid metabolism compared to the control, with OMT1 and PRXs exhibiting high expression levels. This pathway has a significant impact on seed coat lignification and size in Keumsura1ho. The results of this study will benefit the development of breeding techniques by identifying marker genes for seed size.

Traditionally, selective breeding has been used to improve tree growth. However, traditional selection methods are time-consuming and limit annual genetic gain. Genomic selection (GS) offers an alternative to progeny testing by estimating the genotype-based breeding values of individuals based on genomic information using molecular markers. In the present study, we introduced GS to an open-pollinated breeding population of Korean red pine (Pinus densiflora), which is in high demand in South Korea, to shorten the breeding cycle. We compared the prediction accuracies of GS for growth characteristics (diameter at breast height [DBH], height, straightness, and volume) in Korean red pines under various conditions (marker set, model, and training set) and evaluated the selection efficiency of GS compared to traditional selection methods. Training the GS model to include individuals from various environments using genomic best linear unbiased prediction (GBLUP) and markers with a minor allele frequency larger than 0.05 was effective. The optimized model had an accuracy of 0.164–0.498 and a predictive ability of 0.018–0.441. The predictive ability of GBLUP against that of additive best linear unbiased prediction (ABLUP) was 0.86–5.10, and against the square root of heritability was 0.19–0.76, indicating that GS for Korean red pine was as efficient as in previous studies on forest trees. Moreover, the response to GS was higher than that to traditional selection regarding the annual genetic gain. Therefore, we conclude that the trained GS model is more effective than the traditional breeding methods for Korean red pines. We anticipate that the next generation of trees selected by GS will lay the foundation for the accelerated breeding of Korean red pine.