Integrated single-nucleus and spatial transcriptomics captures transitional states in soybean nodule maturation

Abstract

Legumes form symbiosis with rhizobium leading to the development of nitrogen-xing nodules. By integrating single-nucleus and spatial transcriptomics, we established a cell atlas of soybean nodules and roots. In central infected zone of nodule, we found that uninfected cells specialize into functionally distinct sub-groups during nodule development and revealed a transitional subtype of infected cells with enriched nodulation-related genes. Overall, our results provide a single-cell perspective for understanding rhizobium-legume symbiosis.

High-Throughput f-LAESI-IMS-MS for Mapping Biological Nitrogen Fixation One Cell at a Time

“…In a recent study, by integrating single-nucleus and spatial transcriptomics the expression patterns of specifically expressed genes in infected cells of soybean root nodules have been investigated . The comparison of gene expression levels, e.g., of symbiotic nitrogen fixation genes, between mature nodules (21 dpi) and immature nodules (12 dpi), suggested the presence of two transcriptionally distinct subcell types within the infection zone.…”

A high‐resolution transcriptomic atlas depicting nitrogen fixation and nodule development in soybean

“…A recent report established a cell atlas of soybean nodules and roots using single‐nucleus and spatial transcriptomics (Liu et al, 2023). Their study provided valuable insights into the specialization of uninfected cells into functionally distinct subgroups and the identification of a transitional subtype of infected cells during nodule development.…”

Spatial transcriptomics drives a new era in plant research

“…From a spatial perspective, ST can be utilized to study the interaction mechanism between soybean and rhizobia. In a study on the interaction between soybean and rhizobia, snRNA‐seq and Stereo‐seq were combined to construct the ST map of soybean nodules and roots (Liu et al., 2023). Furthermore, functional genes playing essential roles in soybean‐rhizobia interactions were identified based on the spatial expression patterns of specifically expressed genes in infected cells and uninfected cells (Liu et al., 2023).…”

“…In a study on the interaction between soybean and rhizobia, snRNA‐seq and Stereo‐seq were combined to construct the ST map of soybean nodules and roots (Liu et al., 2023). Furthermore, functional genes playing essential roles in soybean‐rhizobia interactions were identified based on the spatial expression patterns of specifically expressed genes in infected cells and uninfected cells (Liu et al., 2023). In addition, Saarenpaa and coworkers developed a spatial metatranscriptomics technique called (“SmT”) to capture fungal, bacterial, and host signals while preserving their spatial structure.…”

“…In addition, integrating multi‐omics data will facilitate the characterization of gene regulation at multiple omics levels, providing new insight into how plant cells spontaneously differentiate and evolve during development and evolution (Depuydt et al., 2022). For example, integrating scRNA‐seq and ST data can increase gene capture and enable the identification of specific cell types and spatial locations within tissues at single‐cell resolution, leading to a better understanding of how specific cell types interact in specific spatial scenarios (Liu et al., 2023; Xia et al., 2022). Therefore, developing and optimizing algorithms for data integration to identify common anchors across different molecular layers is a pressing need for future research.…”