Early selection of grain quality traits in rice (Oryza sativa L.), is essential to improve the yield and quality of this staple crop. We analyzed four key traits—protein content, grain filling rate, height, and panicle length—in 85 Korean cultivars. Through whole- genome resequencing we identified 12,718,879 raw single nucleotide polymorphisms (SNPs); after PLINK-based quality control (bi-allelic selection, call rate≥0.90, MAF≥0.03), ~2.20 million high-quality SNPs remained for machine-learning (ML) pre-screening. To rank the features (without marker-level inference), we applied a liberal univariate PLINK case-control scan using the top and bottom 30% per trait. We also analyzed associations with a linear mixed model (GCTA v1.93.2, MLMA; fixed covariates: ecotype, PC1, PC2; random effect: GRM) to verify calibration under population structure; with n=85, no genome-wide significant hits were detected, and QQ-plots indicated adequate calibration (per-trait effective tests m≈1.54-1.57 million under stricter filters). The random forest feature importance prioritized 26, 51, 19, and 20 core SNPs for the four traits, respectively. Across the algorithms, the best models achieved mean accuracies of 81.8% (protein content), 81.0% (grain filling rate), 73.1% (height), and 94.0% (panicle length). All selected SNPs met the Fluidigm array design requirements, supporting its deployment as a compact, genotype-based panel for early selection and a practical step toward digital breeding in rice.

Improving nitrogen use efficiency (NUE) is essential for sustainable wheat production, given the global demand for high-yielding and environmentally resilient crop varieties. NUE is a complex trait governed by multiple genetic, physiological, and environmental factors. This review synthesizes recent advances in the genetic dissection of NUE in wheat, focusing on quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and transcriptome analyses. Furthermore, novel approaches such as protein turnover quantification, epigenetic regulation, NIR-based quality prediction, and genomic selection optimization are discussed as emerging strategies to enhance NUE. Key genes identified include nitrate transporters (NRT1, NRT2), nitrogen assimilation enzymes (GS, GOGAT), transcription factors (NLPs, WRKYs, NACs), and signal transduction components (SnRK, CIPK). Integrative studies combining genomics, transcriptomics, and machine learning offer new insights into the dynamic regulation of NUE. This review highlights the importance of multi-layered breeding approaches and provides valuable genetic resources and methodological frameworks for future wheat NUE improvement programs.

Salt stress is a major abiotic factor that limits wheat production worldwide. However, this threat is increasing significantly because soil salinity affects approximately 20% of the irrigated agricultural land globally, leading to significant yield losses by impairing plant growth and photosynthetic efficiency. This study aimed to identify single-nucleotide polymorphisms (SNPs) associated with salt tolerance in wheat core collections during the heading stage under saline stress conditions. Chlorophyll content, a physiological indicator of salt tolerance at heading, and soil electrical conductivity (EC) were measured in 609 accessions and a Salt Tolerance Index (STI) was subsequently constructed. Genome-wide association studies (GWAS) were performed using a 35 K SNP chip to identify significant marker-trait associations. Three models (MLM, FarmCPU, and BLINK) were employed for the GWAS, with FarmCPU and BLINK demonstrating superior power over the MLM in controlling false positives. GWAS results revealed four significant SNPs (AX-94929101, AX- 94615611, AX-94510535, and AX-94411611) located on chromosomes 3D, 5D, and 7D. AX-94510535 exhibited significant phenotypic differences based on SNP genotype, suggesting its potential as a marker for STI. Furthermore, the identified candidate genes, TraesCS3D02G218100, TraesCS5D02G059500, and TraesCS5D02G175000, were implicated in biological processes such as DNA replication, cell death, and photosynthesis.

Barley (Hordeum vulgare L.) is an important cereal crop valued for its nutritional benefits and adaptability to diverse climates. β-glucan, a soluble dietary fiber found in barley, is recognized for its health benefits, including lowering cholesterol, managing postprandial blood glucose levels, and providing antioxidative properties. However, high β-glucan content can complicate food processing due to increased viscosity and water absorption rates. This study used genotyping-by-sequencing (GBS) to examine genetic variation within barley populations and to identify genetic markers associated with β-glucan content. A Genome-Wide Association Study (GWAS) was conducted to identify candidate genes linked to β-glucan levels. Functional annotation revealed several genes potentially involved in cellulose synthase activity and cell wall biosynthesis, including the MYB-related protein Zm38, C2 domain-containing protein, ATP synthase subunit beta (chloroplastic), ATP-dependent Clp protease proteolytic subunit, soluble inorganic pyrophosphatase, and glyceraldehyde-3-phosphate dehydrogenase 1 (cytosolic). These findings provide insights into the genetic architecture of β-glucan content in barley. By leveraging GBS and GWAS, breeders can identify and select genetic markers associated with high β-glucan content, thereby facilitating the development of superior barley varieties with enhanced nutritional and processing qualities.

Root development at the seedling stage is an important trait for the early growth of rice. In this study, the root length and weight of 211 Korean landrace rice at the seedling stage were evaluated, and the average root length and weight were 6.94 cm and 48.18 mg, respectively. Principal component analysis (PCA) of 211 accessions based on 70,849 SNPs presented three subgroups. Two quantitative trait loci (QTLs) associated with root length were detected on chromosomes 3 and 6 using genome-wide association study (GWAS). Four haplotypes were identified using associated SNPs for the two root length QTLs. The average root length of Hap2 and Hap 3 was 7.32 cm and 6.56 cm, respectively, and were significantly different. Gene expression analysis in the candidate regions of QTLs for root length at the seedling stage showed that several genes were expressed in the root. QTLs associated with root length at the seedling stage identified in this study may be applied to improve the root length trait and detect candidate genes.

Magnesium is important not only for the growth of rice itself, but also as an essential micronutrient component of half of the world population who are supported by rice. Here, we performed genome-wide association study (GWAS) with high-resolution density SNPs to identify natural allelic variation in Mg²⁺ increase from rice set, which is derived from a total 24,368 rice germplasms. The range of the concentration and distribution of Mg²⁺ in 295 core accessions of brown rice grain were wide, from 18.17mg/L to 57.11mg/L, with mean 39.71mg/L. In particular, GWAS result shows that the high peak found on chromosomes 3 and 11. The new natural variants identified through haplotyping analysis would be useful to develop new rice varieties with improved storage ability of the valuable mineral through the future molecular breeding.