GS6.1 controls kernel size and plant architecture in rice.

MAIN CONCLUSION: A novel QTL GS6.1 increases yield per plant by controlling kernel size, plant architecture, and kernel filling in rice. Kernel size and plant architecture are critical agronomic traits that greatly influence kernel yield in rice. Using the single-segment substitution lines (SSSLs) with an indica cultivar Huajingxian74 as a recipient parent and American Jasmine as a donor parent, we identified a novel quantitative trait locus (QTL), named GS6.1. Near isogenic line-GS6.1 (NIL-GS6.1) produces long and narrow kernels by regulating cell length and width in the spikelet hulls, thus increasing the 1000-kernel weight. Compared with the control, the plant height, panicles per plant, panicle length, kernels per plant, secondary branches per panicle, and yield per plant of NIL-GS6.1 are increased. In addition, GS6.1 regulates the kernel filling rate. GS6.1 controls kernel size by modulating the transcription levels of part of EXPANSINs, kernel filling-related genes, and kernel size-related genes. These results indicate that GS6.1 might be beneficial for improving kernel yield and plant architecture in rice breeding by molecular design.

qGLF5 from Oryza rufipogon Griff. improves kernel shape, plant architecture, and yield in rice.

KEY MESSAGE: A novel QTL qGLF5 from Oryza rufipogon Griff. improves yield per plant and plant architecture in rice. Kernel size and plant architecture are critical agronomic traits that are key targets for improving crop yield. From the single-segment substitution lines of Oryza rufipogon Griff. in the indica cultivar Huajingxian74 (HJX74) background, we identified a novel quantitative trait locus (QTL), named qGLF5, which improves kernel shape, plant architecture, and yield per plant in rice. Compared with the control HJX74, the plant height, panicles per plant, panicle length, primary branches per panicle, secondary branches per panicle, and kernels per plant of the near-isogenic line-qGLF5 (NIL-qGLF5) are significantly increased. NIL-qGLF5 has long and narrow kernels by regulating cell number, cell length and width in the spikelet hulls. Yield per plant of NIL-qGLF5 is increased by 35.02% compared with that of HJX74. In addition, qGLF5 significantly improves yield per plant and plant architecture of NIL-gw5 and NIL-GW7. These results indicate that qGLF5 might be beneficial for improving plant architecture and kernel yield in rice breeding by molecular design.

qGL3.4 controls kernel size and plant architecture in rice.

Kernel size and plant architecture play important roles in kernel yield in rice. Cloning and functional study of genes related to kernel size and plant architecture are of great significance for breeding high-yield rice. Using the single-segment substitution lines which developed with Oryza barthii as a donor parent and an elite indica cultivar Huajingxian74 (HJX74) as a recipient parent, we identified a novel QTL (quantitative trait locus), named qGL3.4, which controls kernel size and plant architecture. Compared with HJX74, the kernel length, kernel width, 1000-kernel weight, panicle length, kernels per plant, primary branches, yield per plant, and plant height of near isogenic line-qGL3.4 (NIL-qGL3.4) are increased, whereas the panicles per plant and secondary branches per panicle of NIL-qGL3.4 are comparable to those of HJX74. qGL3.4 was narrowed to a 239.18 kb interval on chromosome 3. Cell analysis showed that NIL-qGL3.4 controlled kernel size by regulating cell growth. qGL3.4 controls kernel size at least in part through regulating the transcription levels of EXPANSINS, GS3, GL3.1, PGL1, GL7, OsSPL13 and GS5. These results indicate that qGL3.4 might be beneficial for improving kernel yield and plant architecture in rice breeding.

Plant synthetic genomics: Big lessons from the little yeast.

Yeast has been extensively studied and engineered due to its genetic amenability. Projects like Sc2.0 and Sc3.0 have demonstrated the feasibility of constructing synthetic yeast genomes, yielding promising results in both research and industrial applications. In contrast, plant synthetic genomics has faced challenges due to the complexity of plant genomes. However, recent advancements of the project SynMoss, utilizing the model moss plant Physcomitrium patens, offer opportunities for plant synthetic genomics. The shared characteristics between P. patens and yeast, such as high homologous recombination rates and dominant haploid life cycle, enable researchers to manipulate P. patens genomes similarly, opening promising avenues for research and application in plant synthetic biology. In conclusion, harnessing insights from yeast synthetic genomics and applying them to plants, with P. patens as a breakthrough, shows great potential for revolutionizing plant synthetic genomics.