Kosuke Hamazaki

Metabolome genome-wide association study reveals hierarchical and epistatic genetic control of flavonoid metabolism in soybean

Knowledge-guided Bayesian optimization using pre-trained LLMs speeds up the identification of superior genotypes from germplasm collection

This paper uses pre-trained LLMs to enhance Bayesian optimization for selecting superior genotypes from germplasm collections, improving efficiency with passport data and genomic information.

Dissecting oligogenic and polygenic indirect genetic effects through the lens of neighboring plant genotypes

The paper develops a multi-kernel mixed model to analyze indirect genetic effects (IGEs) in plant genotypes, finding evidence of intergenotypic competition in aspen and apple trees.

Optimizing progeny allocation strategies in breeding schemes while updating genomic prediction models

The paper develops a framework that optimizes breeding strategies by updating genomic prediction models during breeding schemes, showing improved performance under moderate to low selection intensities.

Haplotype Bias Detection Using Pedigree-Based Transmission Simulation: Traces of Selection That Occurred in Apple Breeding

The paper develops a method to detect haplotype bias using pedigree-based gene drop simulations in apple cultivars, identifying SNPs associated with fruit traits and potential selection signals.

DiffBreed: Automatic differentiation enables efficient gradient-based optimization of breeding strategies

DiffBreed uses automatic differentiation to optimize breeding strategies, achieving higher genetic gains than equal allocation through gradient-based optimization.

Optimization of crossing strategy based on the usefulness criterion in inter-population crosses considering different genetic effects among populations

This study proposes a method to select optimal cross pairs in inter-population crosses by considering genetic effects across populations, showing increased genetic gains in multiple traits.

Cross Potential Selection: A Proposal for Optimizing Crossing Combinations in Recurrent Selection Based on the Ability of Future Inbred Lines

This paper introduces Cross Potential Selection (CPS), a strategy for selecting crossing pairs in plant breeding to accelerate novel variety production, showing higher genetic improvements in early cycles of simulated breeding programs.

AI-assisted selection of mating pairs through simulation-based optimized progeny allocation strategies in plant breeding

This paper develops an AI method using simulation and optimization to improve genetic gain in plant breeding by optimizing progeny allocation strategies for mating pairs.

Development of a novel GWAS method to detect QTL effects interacting with the discrete and continuous population structure

This paper develops two new GWAS models, SNPxGB and HBxGB, to detect QTLs interacting with discrete and continuous population structures without requiring prior population structure information.

High-throughput Phenotyping of Soybean Biomass: Conventional Trait Estimation and Novel Latent Feature Extraction Using UAV Remote Sensing and Deep Learning Models

This study uses UAV remote sensing and deep learning to estimate soybean biomass traits and extract latent features for breeding applications.

Assessing the potential for genome-assisted breeding in red perilla using quantitative trait locus analysis and genomic prediction

This study evaluates genomic selection and marker-assisted selection for improving medicinal compound production in red perilla using quantitative trait locus analysis and genomic prediction.

Evaluating drought tolerance stability in soybean by theresponse of irrigation change captured from time-seriesmultispectral data

This study evaluates drought tolerance stability in soybean using time-series multispectral data and genomic prediction models, finding higher accuracy with changing irrigation treatments.

Bayesian optimization of multivariate genomic prediction models based on secondary traits for improved accuracy gains and phenotyping costs

The paper proposes a Bayesian optimization method to optimize multivariate genomic prediction models using secondary traits, achieving better accuracy while reducing phenotyping costs.

Choosing the optimal population for a genome-wide association study: a simulation using whole-genome sequences from rice

This study shows that combining target populations with more diverse populations improves GWAS power for detecting QTNs, depending on genetic diversity metrics like FST and He.

Haplotype-based genome wide association study using a novel SNP-set method : RAINBOW

RAINBOW is a novel SNP-set GWAS method that improves detection of causal variants and controls false positives, especially for nearby variants with opposite effects.