China News Service, Sanya, October 7 (Zhang Yuehe) The reporter learned from the Yazhou Bay joint research results press conference on the first life map of Southern Silicon Valley held in Sanya on the 7th that 12 scientific research teams from Yazhou Bay National Laboratory, BGI Life Sciences Institute and other institutions worked together to construct for the first time a three-dimensional spatio-temporal cell map covering the entire process of rice from seed germination to flowering and fruiting. It integrated genome, cell development stages and spatial transcriptome information, providing an important foundation for understanding plant development at the individual scale.
The relevant results were published online in the international academic journal Cell on the evening of the 6th. Chen Fan, deputy director and chief scientist of Yazhou Bay National Laboratory, said that the growth and development of rice involves the synergistic effect of different types of cells. In the past, researchers could analyze the function of a certain gene or observe changes in a certain tissue or a certain developmental stage. However, the industry still lacks a systematic understanding of where and when tens of thousands of genes participate in regulating growth and development during the complete life cycle.
This study used the japonica rice variety Zhonghua 11 as the material and integrated the spatiotemporal omics technology Stereo-seq independently developed by the BGI Life Sciences Institute, the single-cell library construction platform DNBelab C4, the high-throughput gene sequencer T7 and artificial intelligence analysis to establish a map covering 10 types of organs or tissues and 61 developmental stages. The research team obtained data on more than 850,000 high-quality cell nuclei and more than 340,000 spatial data units, annotating 119 cell types and 133 cell subtypes.
"This map can be understood as a map of life information with time and spatial location." Chen Fan said that it not only presents the distribution of different cell types in tissues, but also reflects changes in functional gene expression with developmental stages, helping researchers connect molecular-level information with the macroscopic growth process of rice.
One of the study's key findings occurred inside the endosperm. The endosperm is an important tissue in the kernel that stores nutrients. The team found that there is a fine "spatial division of labor" in the developing endosperm: the dorsal peripheral endosperm region is more enriched in genes related to starch synthesis, while the ventral peripheral endosperm region is more enriched in genes related to storage protein synthesis.
Further research by the team showed that mutations in related genes can change the accumulation pattern of starch and protein in the dorsal and ventral regions.
This discovery further deepens the study of grain nutrient distribution and quality formation into different spatial regions of the endosperm, providing a scientific basis for exploring more refined quality control strategies.
In addition, the team found that the key regulatory factor OsARF1 can be transcribed and expressed in different spaces and at different developmental stages, thereby participating in different molecular regulatory networks such as endosperm nutrient distribution. This provides a new perspective to explain the phenomenon of "one gene affecting multiple traits". In breeding research, directly changing a regulatory factor that has a wide impact may affect multiple traits at the same time; identifying more specific downstream regulatory modules is expected to provide research directions for targeted improvements.
In order to transform this achievement into a sustainable public resource, the team established an interactive online map platform to support gene query, spatial expression display and comparative analysis, and developed the rice single-cell basic model RICE scGPT. This model is equivalent to creating a "big AI model" for understanding rice cells for the agricultural scientific research community. Using this research and public rice single cell data training, it can assist cell type annotation and the integration of data sets from different sources, improving the comparability and reusability of data.
Chen Fan said that the release of the spatiotemporal cell map of the entire rice life cycle and related databases and models provides a new way for researchers to independently mine gene functions. Researchers can check the expression of genes of interest in different tissues and developmental stages, and then conduct functional verification based on experiments. This not only provides valuable public resources for scholars around the world, but also opens up new paths for research on the entire life cycle of plants.
It is reported that the "Rice Single Cell Spatiotemporalomics Research" project relied on by the institute is one of the joint "unveiling and leading" projects between the Hainan Provincial Seed Industry Laboratory and the BGI Life Sciences Research Institute. The collaborative research model of "uncovering the list and taking charge" jointly by science and technology enterprises is an enterprise-led, market application-oriented seed industry development innovation mechanism launched by Hainan in 2022. It aims to cooperate with scientific research institutions and enterprises to carry out research on key technical problems that are "stuck" in the seed industry required by the market, and accelerate the rapid transformation of scientific research results.
