Single-cell Spatial transcriptomics (sc-StereoSeq), opening a new era in plants and crops biology.

Jan 10, 2024

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WEILIN LIU SENIOR FIELD APPLICATION SCIENTISTS MGI

Dr. Weilin Liu - Field Application Scientist at MGI

Single-cell Spatial transcriptomics (sc-StereoSeq), opening a new era in plants and crops biology.
Single-cell Spatial transcriptomics (sc-StereoSeq), opening a new era in plants and crops biology.
Single-cell Spatial transcriptomics (sc-StereoSeq), opening a new era in plants and crops biology.

Unveiling the New Era in Plant Biology: Single-Cell Spatial Transcriptomics (sc-StereoSeq) 

Single-cell Spatial transcriptomics (sc-StereoSeq) is opening a new era in plant and crop biology. 

Bridging Spatial Information and Gene Expression in Plant Tissue Cells, advances and challenges  

Associating spatial information with gene expression at high resolution in plant tissue cells is essential to further understanding of plant physiological processes, such as development, evolution, and interactions of plants with (a)biotic stresses. The obtained new knowledge could lead to substantial significance in benefiting crop production and resistance, eventually alleviating the food shortage issue for a better life and society. 

In the last years, the fast pace in spatial transcriptomic (ST) technologies has overcome previous technical constraints in throughput capacity, resolution, and lack of cellular heterogeneity content, fine-tuning the functions of specific cell groups with their spatial details.The power of ST has led to discoveries in multiple fields, including embryonic development, neuroscience, and cancer research (Chen et al., Cell, 2022; Wei et al., Science, 2022; Wu et al., Nature 2021). However, its application to plant studies has fallen behind when compared with human and animal research due to several remaining challenges inherent to the nature of plants.First, the presence of cell wall hinders the plant morphological staining, tissue section embedding, and subsequent permeabilization for RNA capture. Protoplast method may trigger artificial changes, resulting in global gene expression alteration, biased proportions of cell types, thus affecting the final transcriptome profiling. Second, the high-water content in plants could cause difficulty in preserving the original spatial positions due to a common diffusion phenomenon especially when using cryo-sections. Third, it is known that certain secondary metabolites in plant tissues suppress RNA capture efficiency, causing bias in RNA molecule diversity and yield. 

A Path-Breaking Study on Arabidopsis Leaves, unrevealing subtle but significant transcriptional differences between cell subtypes 

 In spite of these bottlenecks in plant spatial transcriptomics, a path-breaking study on Arabidopsis leaves published in Developmental Cells by a group of Chinese scientists (Xia, et al., 2022) presents comprehensive data and unprecedented sub-cellular resolutions in nm scale (500 nm) on gene expression coupled with specific cell-type and accurate spatial information, achieved by single-cell spatial transcriptomic sequencing (sc-StereoSeq) combined with MGI proprietary DNA nanoball technology (DNB). In this study, Xia et al. established and validated this bona fide sc-StereoSeq technique in cryo-sectioned Arabidopsis leaves, not only showing its consistency with previously known transcriptomic profiles and canonical marker genes but also enhancing the expressional and spatial resolution to unmask subtle yet significant transcriptional differences between cell subtypes. More than 10,000 cells from Arabidopsis cauline leaves with a total of 19,720 genes were detected with high quality and spatially resolved single-cell transcriptome profiles, showing superior performance when compared with the Bin20 method with lower resolution as the control in the study. Moreover, the distribution of molecular identifiers (MID) seeded on the chip demonstrated perfect alignment between leaf areas and transcript signals, showing no signal diffusion, which is commonly observed in other ST techniques. The epidermis in Arabidopsis leaves can be subdivided into upper and lower epidermal cells, and mesophyll cells can also be classified into spongy mesophyll cells and palisade mesophyll cells. Previously, scRNA-seq data alone were not able to distinguish those cell subtypes owing to their highly identical cell lineage and transcriptomic profiles. 

With the excellent sub-cellular morphological information preserved by sc-StereoSeq, those cell subtypes and their boundaries could be well recognized. More importantly, cell-type-specific clusters of genes, which were not well reviewed in those cell subtypes, were identified, showing the genes associated with photosynthesis, cuticle development, and fatty acid biosynthesis were significantly up-regulated in upper epidermal cells, while the genes involved in immune response, response to absence of light, and cell death regulation were enriched in lower epidermal cells (Figure 3E). In addition, WAX2, which plays metabolic roles in both cuticle membrane and wax synthesis, and DIN6 involved in nitrogen metabolism are differentially expressed by upper- and lower-epidermal cells. These new findings revealed the subtle transcriptional differences between those cell subtypes, inspiring their unique yet to be investigated roles in plant physiology and functions. By taking advantage of the spatial content provided in this study, the expression analysis along the medio-lateral axis of the Arabidopsis leaf was also conducted to investigate any enriched specific gene cluster in certain areas of leaves. These spatial gene expression patterns along the medio-lateral leaf axis revealed by sc-StereoSeq provide indications to further understand the complex physiological functions and zonation in plant leaves. Lastly, the sensitivity of detecting subtle changes in gene expression between different cell types is significantly reinforced by sc-StereoSeq with its superior spatial information when compared with other conventional molecular methods.

Future prospective of sc-StereoSeq in plant and crop research 

Following the light of this inspiring work, other similar studies applying or combining spatial transcriptomic assays have been done recently on portulaca leaf cells (Moreno-Villena et al., Sci Adv, 2022), peanut needle (Liu et al, Plant Biotechno J, 2022), orchid meristem (Liu et al, Nucleic Acids Res, 2022) and poplar vascular issue (Du et al., Mol plant, 2023). The next worth-trying study would be applying this established scStereo-seq methodology on Arabidopsis/plant root to gain more detailed, unbiased and higher-resolution on gene expression atlas to deepen the understanding and further extrapolate the key mechanisms involved in plant root development, of which process is as equally essential as the leaf development. Moreover, this molecular tool could further dissect how plant root responds to those environmental factors, such as nutrients, abiotic stresses, and microbial interactions, such as symbiosis processes and pathogen infections, and how the physiological adjustments are archived via the transcriptional regulations. Furthermore, collecting the tissues from the different developmental stages followed by scStereo-seq assay would significantly enrich the biological information at both spatial and temporal aspects, thus lifting the plant and crops research to a new horizon. Additionally, what could be possibly improved in this and similar studies in the future, especially when studying particular groups of cells, is to utilize the power of fluorescence reporter (GFP/mCherry) driven by cell type-specific promoters, such as pPIN2, pSCR, pSHR and pWOX5 in Arabidopsis root (Marquès-Bueno et al., Plant J, 2016), pGC1 and pCER5 in leaf (Yang, et al., Plant methods, 2008; Mustroph et al., PNAS, 2009), to enable more precise and efficient cell identity classification besides the conventional morphology-based method. Cell boundary definition by staining and high-throughput fluorescence imaging to label per cell type before RNA extraction would further empower the potency and accuracy of scStereo-seq. 

About MGI

MGI Tech Co., Ltd. (MGI) is at the forefront of global innovation, actively contributing to life science through intelligent innovation. With a presence in over 100 countries and a customer base of 2600+, MGI's cutting-edge technology has been instrumental in the development of 736+ user patents, facilitating the creation of over 150 petabytes of data. The company's extensive portfolio includes sequencing instruments, automation instruments, reagents, and related products that cater to various sectors such as life science research, agriculture, precision medicine, and healthcare.

MGI is dedicated to advancing life science tools for the healthcare of the future. As of December 2021, the company's global presence has expanded to more than 100 countries and regions, serving over 1,300 international clients. With a workforce of over 2,900 professionals worldwide, including 5 centers for research and development and production facilities in Europe, MGI is committed to fostering innovation. Approximately 35% of MGI's employees are engaged in R&D, underscoring the company's focus on pioneering advancements in the field.

The impact of MGI's work is further evidenced by the publication of over 6,800 papers in prestigious scientific journals, showcasing the significant contribution of MGI's technology to the scientific community and beyond.

For more information about MGI and its contributions to life science and healthcare, please visit the MGI website or connect with us on Twitter, LinkedIn, or YouTube.

A picture of the DNBSEQ-T7 Sequencer from MGI-Tech

DNBSEQ-T7

The Vanguard of High-Throughput Sequencing

Single-Cell Spatial Transcriptomics

SC-STERO-Seq Technology

Plant Genomic Research

Crop Genetic Mapping

Spatial Omics Applications

Spatial Omics Applications

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