Un Atlas de Transcriptómica Espacial a Resolución de Una Sola Célula Decodifica el Desarrollo de la Espiga de Trigo y...

The molecular regulatory mechanisms underlying spike development critically influence grain yield of wheat (Triticum aestivum L.) but remain incompletely understood. Using spatial transcriptomic analysis with single-cell resolution, we comprehensively mapped the spatiotemporal transcriptome across five key stages of wheat spike development. Our approach enabled the identification and annotation of nine distinct cell types, revealing the spatiotemporal distribution of hormonal and metabolic signaling pathways across multiple cell populations. Notably, we observed variations in biosynthesis and response signaling patterns among key phytohormones, particularly cytokinin and auxin, and demonstrated that the rachis cell population serves a crucial role in nutrient and energy supply during spike morphogenesis. The analysis of pseudotime and RNA velocity revealed cell populations with distinct differentiation states, highlighting the potential influence of spikelet primordium base cells on lateral organ development and grain number determination. By integrating snRNA-seq data from the W3.5 stage, gene regulatory relationships and GWAS data from public databases, we constructed a co-expression regulatory network for wheat spike development and identified a key gene module that regulates multiple spike-related traits. Subsequent investigations characterized the heterogeneous subpopulations of spikelet primordium base cells, identifying a novel gene cluster substantially regulates grain number per spike. Based on spatial transcriptomics data, we have developed a publicly accessible online platform (http://www.wssed.com/) that allows users to interactively query and visualize spatiotemporal gene expression patterns during wheat spike development. Overall, this study provides a comprehensive molecular framework for early spike development in wheat, offering valuable genetic resources and public data for functional genomics research. This information may hold significant implications for breeding efforts aimed at optimizing spike architecture and enhancing grain yield potential in wheat.