Biology subjects

Ogawa, D.

Publications and source records attributed to Ogawa, D..

4 recordsLinked to original sources

bioRxiv2026

Pyramiding panicle-level heat avoidance and grain-level heat tolerance improves rice grain appearance under high-temperature grain filling

High temperature during grain filling increases rice grain chalkiness and deteriorates grain appearance under climate warming. Although several loci that reduce chalkiness have been identified, breeding strategies that integrate grain level heat tolerance with panicle level heat avoidance remain limited. Here we characterized SL2033, a chromosome segment substitution line carrying a long IR64 derived segment on chromosome 10, and evaluated the combination of the chromosome 10 segment with Appearance quality of brown rice 1 (Apq1), a quantitative trait locus associated with reduced heat induced chalkiness that acts at the grain level. Compared with its recurrent parent Koshihikari, SL2033 had longer flag leaves, altered vertical plant architecture, and lower panicle temperature. Total starch and protein contents were comparable between the two genotypes, whereas RNAseq analysis of the developing endosperm identified specific differences in heat, stress, and cell wall related transcripts. In a two year field trial, a pyramided line combining the SL2033 derived segment with Apq1 had the highest proportion of perfect grains and lowest frequencies of multiple chalky kernel types during the year with hotter grain filling conditions, with no detectable yield penalty. The pyramided line combined longer flag leaves, as in SL2033, with shorter panicle exsertion, as in an Apq1 near isogenic line, and had the lowest panicle temperature among the tested genotypes. Time series unmanned aerial vehicle imaging also detected genotype dependent differences in plant height during early grain filling, supporting distinct temporal patterns of plant development among the lines. These findings demonstrate that pyramiding genetic loci that confer panicle level and grain level heat tolerance is a promising strategy for improving rice grain appearance under high temperature field conditions, which are becoming increasingly prevalent.

plant biology↗

bioRxiv2026

Rice Cultivars Carrying the Semi Dwarfing Allele Enables High Yield without Lodging under Hairy Vetch based Green Manure

Green manure is a promising strategy for reducing dependence on chemical fertilizers in crop production. However, vigorous growth due to green manure often leads to high yield accompanied by lodging in rice, hindering its practical use in rice cultivation. Here, we show that rice cultivars carrying a semi-dwarfing sd1/ga20ox2 allele achieve high grain yield without lodging under hairy vetch-based green manure conditions. The leading Japanese cultivar Koshihikari exhibited enhanced vegetative growth, increased panicle number, and consequently higher grain yield and quality under green manure conditions in 2023 and 2024 compared with chemical fertilizer management, although this was accompanied by increased culm length and widespread lodging. Among the four GA20-oxidase genes, green manure significantly upregulated Sd1/GA20ox2 mRNA levels. A temperate japonica cultivar, Nijinokirameki, and an indica cultivar, Hokuriku-193, carrying a non-functional sd1/ga20ox2 allele exhibited no lodging under hairy vetch-based green manure management while achieving improved yield performance. Notably, yields obtained under our hairy vetch-based cultivation system were comparable to or exceeded a recently reported high-yield benchmark observed for Hokuriku-193 under chemical fertilizer management in the same region of Japan. These findings suggest that cultivars harboring non-functional sd1/ga20ox2 alleles enable the practical implementation of annual hairy-vetch-rice rotation for sustainable rice production.

plant biology↗

bioRxiv2025

Dissecting Agronomically Favorable Genotypes in Temperate Japonica Rice via Haplotype Analysis of a Japan-MAGIC Population

O_LICrop breeding assembles genomic variants into cultivars via crossing and selection. Phenotypic selection has improved yield and lodging tolerance but has limited genetic insights. We show how specific genomic variants and their combinations underpin advances in modern rice breeding in Japan. C_LIO_LIThrough genome-wide association study using a multi-parent advanced-generation intercross population derived from four temperate japonica cultivars, we identified 11 quantitative trait loci (QTLs) for key agronomic traits, including days to heading, shoot biomass, panicle length, and culm length under field conditions. GA20ox1, GA20ox2, and Hd1 were among the QTLs, and their natural variants were well conserved in temperate japonica cultivars bred in Japan, underscoring distinct selection pressures at these loci. C_LIO_LIBy integrating genotype data with 5-year yield-performance-evaluation trials of elite cultivars, we found that cultivars carrying multiple-copy GA20ox1 and functional Hd1, together with non-functional ga20ox2, tended to have shorter culms and higher grain yield than cultivars with multiple-copy GA20ox1, functional Hd1, and GA20ox2. This yield advantage was consistent across latitudes in Japan. C_LIO_LIThese results reveal favorable genotype combinations underlying modern japonica improvement and provide a genomic framework for breeding semi-dwarf, high-yielding cultivars adapted to temperate rice-growing regions in Asia. C_LI

genomics↗

bioRxiv2024

Unsupervised learning as a computational principle works in visual learning of natural scenes, but not of artificial stimuli

Unsupervised learning--learning through repeated exposure without instruction or reward--is central to both machine learning and human cognition, including language acquisition and statistical learning. However, its role in visual perceptual learning (VPL) remains debated, as previous studies have not shown VPL for task-irrelevant but visible features, particularly in artificial stimuli. Here, we show that task-irrelevant exposure to natural scene images induces robust VPL, while artificial images that lack complex structure characteristics of natural scene images, known as higher-order statistics, do not. Behavioral and fMRI results suggest that although unsupervised learning underlies VPL, it can be suppressed by top-down attention. Higher-order statistics may evade this suppression, possibly because their slower processing reaches visual areas beyond V1 outside the optimal temporal window for attentional suppression. These findings suggest that unsupervised learning underlies VPL, but its occurrence depends on both higher-order stimulus structure and the brains attentional gating mechanisms.

neuroscience↗