Cotton Genomics and Genetics 2025, Vol.16, No.6, 290-299 http://cropscipublisher.com/index.php/cgg 292 Take BR as an example. It regulates the synthesis of very long chain fatty acids (VLCFA) and the modification of cell walls through transcription factors such as GhBES1.4, thereby affecting fiber length (Yang et al., 2023). Gibberellin has a different pathway. It activates genes related to wall dilation by degrading DELLA proteins and releasing inhibited transcription factors (He et al., 2024). Furthermore, transcription factors such as MYB, WRKY, HD-ZIP and bHLH jointly weave a vast signaling network, integrating hormone and developmental stage information (Bai and Scheffler, 2024). Interestingly, this regulation also has a division of labor among different subgenomes. For instance, the GhWRKY28-GhTOL9 module can participate in regulation through the ESCRT pathway, further refining the elongation response. The complexity of fiber growth largely stems from this interwoven signal dialogue layer upon layer. 2.3 Role of cell wall modification enzymes and their spatial expression patterns If turgor pressure provides the driving force, the cell wall is the bottleneck that determines whether it can be stretched open. Modifying enzymes such as dilator proteins, XTHs, pectin lyase and β -galactosyltransferase play a role of "unbinding" in it. They make the nascent cell walls more elastic, thereby cooperating with the turgor pressure to achieve cell extension. However, these enzymes are not always active. They are expressed at the highest level in the early stage of rapid fiber elongation, but their activity significantly decreases once they enter the secondary wall synthesis stage (Lu et al., 2022). This indicates that the plasticity of the cell wall is a process precisely controlled by time and space. Studies have found that the transcription factor GhMYB201 can directly activate the expression of these enzymes, thereby linking hormone signaling with wall remodeling (Suo et al., 2024). In addition, the interaction between the REDOX state within cells and polysaccharide synthesis is also believed to regulate the ductility of the cell wall, which may explain why fibers can continue to grow without losing their stability. 3 Spatial Transcriptomics: Tools and Techniques 3.1 Overview of mainstream spatial transcriptomics technologies and workflows The emergence of spatial transcriptomics has enabled us to observe gene expression on the "geographical coordinates" of tissues, and there is more than one way to achieve this. Techniques such as microdissection, in situ sequencing (ISS), single-molecule fluorescence in situ hybridization (smFISH), spatial barcoding (such as Visium, Slide-seq), and selection for specific regions have each developed unique paths. Their differences often lie in how mRNA is captured and located. Some pursue high resolution, while others emphasize flux or coverage. Typically, research begins with tissue sections, followed by the capture or labeling of transcripts, then proceeds to the sequencing or imaging stage, and finally reconstructs the spatial expression map through computational means. With the advancement of analytical processes and algorithms, these methods are no longer confined to medium and low resolutions but are gradually moving towards the study of the entire transcriptome and even single-cell and subcellular levels (Asp et al., 2020; Robles-Remacho et al., 2023). The combination of different technologies also enables spatial information to be analyzed at a higher dimension. 3.2 Technical advantages in resolving spatial gene activity over conventional transcriptomics Compared with traditional RNA sequencing, the most distinctive feature of spatial transcriptomics is that it does not "disrupt" the positions of genes. In other words, it not only tells you what the gene is expressing, but also where it is expressed. This "where" often conceals the key to biology. Therefore, researchers were able to identify genes with significant spatial differences, map the distribution of tissue structure, and observe cell interactions and local microenvironments that would otherwise be concealed in homogeneous samples (Rao et al., 2021; Williams et al., 2022). This method can not only help to propose hypotheses but also be used to verify them. In the construction of large-scale tissue maps and the integration with multi-omics data, it offers a level of detail that is difficult for traditional sequencing to reach. It can be said that it is more like a "microscope with coordinates", placing the complex molecular activities back into their original spatial context.
RkJQdWJsaXNoZXIy MjQ4ODYzNA==