Cell-type-specific response to silicon treatment in soybean leaves revealed by single nucleus RNA-sequencing and targeted gene-editing

doi:10.21203/rs.3.rs-4618673/v1

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Cell-type-specific response to silicon treatment in soybean leaves revealed by single nucleus RNA-sequencing and targeted gene-editing

https://doi.org/10.21203/rs.3.rs-4618673/v1

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In agriculture, mineral nutrient uptake and deposition profoundly influences plant development, stress resilience, and productivity. Despite its classification as a non-essential element, silicon (Si) uptake and deposition alters plant physiology and particularly improves defense response and stress mitigation. While genetic and molecular mechanisms of Si uptake and transport are well-studied in monocots, particularly rice, its role in dicot species, such as soybean, remains unclear at the cellular and molecular levels. Traditional bulk transcriptomics methods lack the resolution to uncover cellular heterogeneity. Here, we present a study utilizing single-nucleus RNA sequencing (snRNA-seq) to dissect cellular responses to Si accumulation in soybean leaves. Our analysis revealed distinct cellular populations, including a novel Si-induced cell cluster within vascular cells, suggesting a specific mechanism of Si distribution. Si treatment induced the expression of defense-related genes, particularly enriched in vascular cells, highlighting their specialized role in activating plant defense mechanisms. Moreover, Si modulated the expression of genes involved in RNA silencing, phytoalexin biosynthesis, and immune receptor signaling, suggesting transcriptional priming of genes involved in defense responses. We also investigated putative Si transporters, revealing differential expression patterns in response to Si treatment, suggesting presence of active and gradient-based transport mechanisms. Furthermore, by employing CRISPR/Cas9 genome editing we functionally validated the role of efflux Si transporters in composite soybean plants. Our findings shed light on the vital biotic stress regulatory networks governed by Si treatment in soybean leaves, paving potential strategies for enhancing stress tolerance and agronomic performance in crops.

Biological sciences/Plant sciences/Plant stress responses/Biotic

Biological sciences/Plant sciences/Plant molecular biology

Mineral nutrients are essential elements that plants obtain from the soil and use for various physiological processes that are vital for the growth, development, and overall functioning of plants. Silicon (Si) is a lesser-known mineral nutrient but it is highly beneficial to plant health, environmental resilience, and agricultural productivity¹. Si is not classified as an essential nutrient for plants but has been recognized as quasi-essential for its beneficial effects on plant growth and stress tolerance ^2,3. Although Si ranks as the second most abundant element in the earth’s crust, the role of Si in plant development, abiotic stress tolerance, and disease resistance was unstudied until the discovery of Si transporter genes in rice ⁴. Si is absorbed through the plant root system as silicic acid (Si (OH)₄) and transported to aerial tissues. The deposition of Si in developing tissues form a complex with organic compounds which is thought to create an apoplastic barrier for invading pathogens ². These stronger epidermal layers with Si shield plants from environmental stresses and increase resistance to pathogens. Recent evidence based on comparative genomics, physiological, and molecular studies showed that Si uptake improves resistance against several fungal diseases such as powdery mildew ⁵, rice-blast ⁶, stem rust ⁷, root-rot ⁸, frog-eye disease ⁹, and Phytophthora ¹⁰ in various economically important crops. It also plays a beneficial role in abiotic stresses, including salt and osmotic stress tolerance in crops like cucumber and sorghum and reducing heavy metal toxicity in rice, wheat, and maize¹¹.

Accumulation of Si in the leaf epidermal layer acts as a modulator influencing the timing and extent of plant defense response. For example, it obstructs pathogenesis-related events, interferes with signaling, and prevents penetration by pathogenic fungi hypha into the cells ². Similarly, Si generated apoplastic barrier restricts evapotranspiration, positively impacting water stress ¹². Remarkably, Si uptake, transport, and deposition in various plant species are dynamic and diverse processes. In planta, Si content varies from 0.1–10% on a dry weight basis¹³. Furthermore, in monocots, Si deposition occurs in specialized dumbbell shaped cells called silica cells. This mechanism has been extensively studied in rice and sorghum ^4,14, while in the case of dicots (e.g., soybean and cucumber), Si is deposits in patches on leaf surfaces in between the cuticle layer and epidermal cells ^15–17. Si transport mechanisms were very well studied in monocot species and in rice it is mediated by two types of Si transporters, influx (Lsi1)and, efflux (Lsi2, Lsi3) transporters, and shows different polarity in the exodermis and endodermis of root tissue ^1,4,18. However, the molecular mechanisms involved in Si uptake, transport, deposition, and its effect on molecular cascades in dicot species, including soybean, has not been well studied. Moreover, previous studies have primarily relied on bulk transcriptomics, which fails to report for the cellular heterogeneity and does not consider the specific cell types possessing the ability of nutrient uptake and deposition ¹⁹. The single nucleus RNA-sequencing (snRNA-seq) technique has enabled researchers to identify cell-specific gene expression in several organisms ^20–26.

In the present study, we employed an snRNA-seq approach to identify the genetic and cellular heterogeneity of the soybean leaf upon Si treatment. We identified GmHiSil2c as an active efflux Si transporter in soybean and discussed the transformative impact of SnRNA-seq on understanding cellular and molecular networks and biological processes, highlighting the role of Si on plant immunity, and uncovering comprehensive transcriptomes of 12 distinct cell types upon Si treatment. The analysis identified specific gene expression patterns related to defense response, immune receptors, RNAi silencing machinery, salicylic acid (SA) metabolism, and other processes induced. Additionally, our study discovers a new subset of cells present in higher fractions in Si-treated plants, revealing the dynamic response of plants to Si treatment and providing insights into the subcellular localization of specific Si transporters.

SnRNA-seq analysis of Si + and Si- treated soybean leaves

Soybean plants grown hydroponically and treated with Si (Si+) and without Si (Si-, control) were used to determine Si content in leaf tissues. Following Si + treatment, Si deposition in the leaves was quantified using scanning electron microscopy - energy-dispersive X-ray spectroscopy (SEM-EDS), and a portable X-ray fluorescence analyzer (pXRF). As expected, Si deposition was observed in Si + leaves with an average concentration of 5,200 PPM compared to undetectable accumulation in Si- tissues (Fig. 1a, and Supplementary Fig. 1). Notably, Si deposition in soybean leaf tissues was not limited to specific cells but rather deposited in patches between epidermal cells and the cuticle layer, as well as in and around trichomes (Fig. 1a and Supplementary Fig. 2). Following high-quality nuclei isolation from control (Si-) and Si-treated (Si+) soybean leaves, the nuclei suspension was processed to generate snRNA-seq libraries using Chromium technology (10X Genomics). Illumina sequencing platforms were used to sequence the snRNA-seq libraries. After cell calling and quality filtering, we obtained an average of 2,080 high-quality nuclei with a mean number of 1,547 unique molecular identifiers (UMIs) and 1,007 genes expressed per nucleus (Supplementary Fig. 3a). Employing the Uniform Manifold Approximation and Projection (UMAP) for dimension reduction, 12 distinct cell types were identified based on their marker transcriptomic profiles, broadly classified into three major cell types, namely epidermal, vascular, and mesophyll (Fig. 1b, and Supplementary Fig. 3). The percentage analysis of different cell types showed disproportionate distribution of cell types between control and Si + treatment, especially for clusters #5 and #10 (vascular cell types) and clusters #3 and #7 (mesophyll cells) (Fig. 1c). Upset plot analysis revealed each cell type's contribution to genetic diversity, with palisade mesophyll cells exhibiting the highest portion of uniquely expressed genes, followed by epidermis, spongy mesophyll, and phloem companion cells. Additionally, upset plot analysis exhibited a greater number of unique genes expressed in mesophyll cell cluster (palisade and spongy) followed by vascular (xylem, phloem, companion, vascular bundle), epidermal, Si-induced and guard cells cluster (Fig. 1d).

Identification of “Silicon-induced” cell cluster

To identify preliminary cell populations, Arabidopsis orthologs of cluster-specific genes ^22,27 in conjunction with Gene Ontology (GO) term enrichment analysis was applied (Fig. 2a, 2b, 2c, and Supplemental Table S1A). Of the 12 clusters identified (Fig. 1b, Supplementary Fig. 3b), nine over-arching cell types were identified. Epidermal cells were clustered into three sub-clusters (#1, 11, and 12 indicated in Fig. 2) which expressed known genes and pathways related to wax and cuticle-formation, some of which include GmABCG32, GmCER4, GmKCS10, and GmGPAT8. Cluster #12 represented guard cells and genes involved in stomatal function and differentiation were identified (Fig. 2b). Through the exclusive expression of genes found within clusters #2, #5, #8, #9, and #10, we identified these cells as "vascular cells". Specifically, within this group, clusters #8 and #9 were identified as companion and phloem parenchyma cells, respectively. Vascular cell marker genes involved in phloem loading (GmSUC2, GmHPT1), sap components (GmLOX1), and molecular transportation (GmACA10&12, GmHIPP3) processes were expressed in these clusters. Clusters #5 and #10 were annotated as xylem-specific cells. However, the number of cells was disproportionately observed in Si + treatment (Fig. 1b and 1c). Notably, cluster #5 was nearly absent in control (Si-) samples and is hereafter referred to as “Si-induced cells”. This designation is supported by the well-established phenomenon wherein Si is transported through the xylem before being unloaded into the leaves and transported to the epidermis²⁸. Furthermore, based on the genes involved in photosynthetic and light harvesting complexes (GmLHCA4, GmLHB1B1, GmLHCB5, and GmLHCB6) and photosystem I and II genes (GmPSAK, GmPSAE-2, GmPSAH2 and GmPSBY, GmPSBX, and GmPSBR), clusters #3, 4, 6, and 7 were annotated as mesophyll cells (Fig. 1b and 2c). These cell types were sub-characterized as palisade mesophyll cells (clusters 3 and 7) and spongy cells (clusters 4 and 6) using Arabidopsis leaf scRNA-seq data ²⁷.

Discerning the cellular responses to Si treatment

Previous studies have investigated the effects of Si treatment on the expression of genes involved in both abiotic and biotic stress tolerance ^29,30. However, the precise mechanism by which Si treatment regulates gene expression across various cell types has remained to be explored. We elucidated the specific changes in transcript abundance within individual cell-type clusters induced by Si treatment. Comparing snRNA-seq data from both untreated and Si-treated samples, 4,327 differentially expressed genes (DEGs) across all cell types in response to Si treatment were identified (Supplemental Table S1B). To discern the impact of Si + treatment on specific cell types, we conducted a comparative analysis of UMI (Fig. 3) and revealed a notable increase in UMI counts for Si-induced xylem cells, phloem parenchyma, and epidermal cells in Si + treated plants. In contrast, a decrease in UMI values was observed for companion, guard, and mesophyll cells (Fig. 3a). We identified DEGs between Si- and Si + treatments and performed GO term interaction analysis (Fig. 3b, Supplementary Fig. 4–6). The number of DEGs was significantly increased upon Si + treatment wherein vascular (Si induced cells) and epidermal cells were the most affected cell types (Fig. 3c), supports the fact that Si is transported from vascular tissues and deposited on the epidermal cell layers.

In response to Si treatment, vascular cells, specifically Si-induced cells in cluster #5, exhibited a significant transcriptional change in GO terms associated with immune response, including NBS-LRR (NLR) pathway genes and WRKY family transcription factors (TFs), as well as defense responses against oomycetes and viruses (Fig. 3b). Additionally, the GO term "RNAi mediated antiviral response" showed prominent enrichment in these cells (Supplementary Fig. 4). Two other vascular cell types (clusters #10 and #2) displayed enrichment of GO terms related to ‘response to biotic stimulus’, ‘salicylic acid signaling’, and ‘innate immune response’ upon Si + treatment (Supplementary Fig. 4). Notably, epidermal cells under Si + treatment exhibited enrichment of GO terms associated with phytoalexin biosynthesis and response to chitin, both known to trigger immune responses ^31–33 (Supplementary Fig. 5). Overall, GO term interaction analysis revealed potential co-enrichment among genes involved in these processes, suggesting a coordinated transcriptional priming response to Si treatment aimed at enhancing biotic stress tolerance in plants (Fig. 3b).

To gain further insights into cell-type-specific gene expression under Si treatment, heatmaps for three key cell types: epidermis (cluster 1), xylem parenchyma cells (cluster #10), and Si-induced cells (cluster #5) (Fig. 3c) were constructed. The heatmaps revealed differential upregulation of 97 genes in epidermal cells, 68 genes in Si-induced cells, and 100 genes in xylem cells following Si + treatment (Fig. 3c). A predominant portion of the upregulated genes in xylem parenchyma and epidermal cell clusters upon Si + treatment was associated with defense responses, immune responses, protein kinases, and NLR pathway genes. Remarkably, the Arabidopsis homolog encoding Cysteine-rich receptor-like kinase10 (CRK10; Glyma.09G151400), known for its involvement in Fusarium oxysporum resistance ³⁴, exhibited high expression levels in both epidermal (cluster 1) and Si-induced cells (cluster 5) (Fig. 3c and 3d). In Arabidopsis, this plasma membrane-associated protein is expressed in vascular tissues, suggesting its role in plant-pathogen interaction. Similarly, transcription factor (WRKY33) and CALRETICULIN-3a; (CRT3a) gene associated with phytoalexin biosynthesis were highly expressed in epidermal and vascular cells in Si + treatment (Fig. 3e; Supplementary Fig. 7). Phytoalexins are vital antimicrobial secondary metabolite compounds synthesized in plants in response to biotic stress ^31,35,36. Several functional studies have demonstrated the role of CRT3a and WRKY33a in mediating production of phytoalexins and eventually conferring resistance against fungal diseases ^37–41.

Deciphering Si deposition in soybean

Si uptake, transport, and deposition processes vary among plant species. Si is generally deposited in specialized cells of monocot species such as rice, sorghum, barley, and maize ^14,42. Conversely, in dicot species such as Cucurbitaceae (pumpkin, watermelon) ⁴³, sunflower ⁴⁴, soybean ¹⁰, tomato ⁴⁵, and broad-leaf trees ⁴⁶, Si is deposited in patches at the trichome base, subsequently spreading to epidermal cell layers. Si deposition in plant cells creating a structure of amorphous Si also known as phytoliths, and is used for archaeological tracing ⁴⁶. The reason behind Si deposition in dicots in patches rather than a uniform distribution remains unclear. However, several factors may contribute to this phenomenon, including parallel venation in monocots compared to net-like (reticulate) veins in dicots, which may affect Si unloading in leaves. Additionally, the transpiration rate, dynamics of xylem flow, or preferential unloading of Si in dicot leaves could influence Si deposition. The snRNA-seq analysis indicated a significantly higher number of cells in cluster #5 upon Si + treatment, suggesting that these cells were explicitly differentiated from vascular cells (xylem parenchyma cells) and developed into putative Si-induced cells before unloading Si in the epidermal cells (Fig. 4a, 4b and Supplementary Fig. 8). The UMAP plot of vascular cell types revealed a proximity between xylem cells (#10) and Si-induced cells (#5) (Fig. 4b). The snRNA-seq analysis revealed major differences in vascular cells, particularly xylem, between Si + and Si- treated plants. This prompted us to visualize leaf anatomy and xylem cells upon Si + treatment. The fluorescence and scanning electron microscopy observations indicated that Si + treatment resulted in the re-organization of xylem cells into continuous, compact strip patterns with reduced spacing between vessels (Fig. 4c). In contrast, xylem cells in the leaves of Si- treated plants were arranged in clusters with more distance between vessels (Fig. 4c, Supplementary Fig. 9a and 9b). Subsequent gene expression analysis in Si-induced cells revealed that eleven out of twenty GO terms were directly linked to the defense response against fungi, viruses, and bacteria (Fig. 4d, Supplementary Figs. 4 and 10). Additionally, an association plot was generated to identify the most exclusive genes expressed in Si-induced cells (Supplementary Fig. 11a). Several well characterized pathogenesis-related genes such as NLRs, RPS3/RMP1, Dicer-Like protein (GmDCL1, GmDCL4), Argonaut (GmAGO5), and mitogen-activated protein kinases (GmMPK4) among others that were highly expressed in Si-induced cells upon Si + treatment (Fig. 4e, Supplementary Fig. 11b). This compelling evidence suggests that Si + treatment transcriptionally primes plants to activate their defense mechanisms, enhancing the hosts ability to combat various pathogens.

Perturbations of defense-responsive genes upon Si treatment

Si treatment significantly affected immune receptor genes such as RLP (Receptor-Like Protein) and NLR (NBS-LRR; nucleotide-binding domain leucine-rich repeat). RLPs function as cell surface receptors responsible for detecting pathogen-associated molecular patterns (PAMPs), thereby initiating a fundamental defense mechanism termed PAMP-triggered immunity (PTI). These receptors play a crucial role in regulating plant defense responses against various pathogens, including fungi, oomycetes, and bacteria ⁴⁷. Six RLP genes that were highly expressed in vascular cells upon Si + treatment was identified (Fig. 5a, 5b and Supplemental Table S1c) wherein GmRLP9, GmRLP13 and GmRLP56 showed higher expression in xylem and Si-induced cells after Si + treatment (Fig. 5c). Similarly, NLRs are intracellular immune receptors that perceives cytoplasmic effectors secreted by pathogens and initiate effector-triggered immunity (ETI) ^48,49. NLRs are categorized into three different classes based on their different N-terminal domains, namely, toll/interleukin-1 receptor/resistance protein NLR (TIR-NLR/TNL), coiled-coil-NLR (CNL/CC-NLR) and RPW8-like helper NLR (RNL)⁵⁰. In the soybean genome, 319 genes were identified as potential NLR genes⁵¹ and we identified 46 NLR genes (27 TNLs, 15 CNLs and 4 RNLs), that were highly expressed in Si + treated plants and confined mainly to epidermal and vascular cell clusters (#1, 2, 5, 9, 10, and 11) (Fig. 5a, 5b and Supplemental Table S1c). In several plant species, including soybean and Arabidopsis, it has been shown that the NLRs genes such as Rpp1, RPS11, DSC1, RPM1, and NRG1.2 are involved in fungal, oomycetes, bacterial, and viral defense^52–56. Moreover, in soybean the TNL class gene GmTNL2 was identified as a candidate gene for resistance to Asian soybean rust (P. pachyrihizi)⁵⁷. In our snRNA-seq dataset, the TNL class genes, GmTNL1, GmTNL2 and GmDSC1.1 exhibited higher expression in epidermal, vascular and Si-induced cells upon Si + treatment (Fig. 5d), whereas in the case of CNL and RNL classes GmRPM1.1 and GmNRG1.2 exhibited higher expression specifically in xylem and phloem parenchyma cells (Fig. 5d). These results indicate that RLP and NLR immune receptor pathways were induced upon Si + treatment, mainly in leaf vascular cells.

Salicylic acid is a signaling molecule (plant hormone) involved in systemic acquired resistance (SAR) and functions by triggering the plant immune system and activating pathogenesis-related genes^58,59. Previously, researchers have used various formulations of Si and SA to improve abiotic stresses by inducing antioxidant enzymes ^60–62. However, whether Si treatment can induce SA biosynthesis or its upstream signaling genes in plants is unknown. In our dataset, we observed cell-specific expression of SA biosynthesis and signaling genes (Supplementary Fig. 12a). SA biosynthesis occurs through isochorismate (ICS) and the phenylalanine (PAL) pathway ^63–65. In soybeans, both PAL and ICS pathways contribute equally to SA biosynthesis ⁶⁶. However, we did not observe the induction of ICS and PAL pathway genes upon Si + treatment, while these genes were expressed only in control (Si-) treatment (Supplementary Fig. 12a and 12b). Similarly, the MES (methyl esterase) gene, involved in converting inactive Methyl-SA to Active SA⁶⁷, was expressed in mesophyll cells of both Si- and Si + treatment. But interestingly, GmSARD1, a regulator for ICS1 in SA synthesis, was highly expressed in vascular cells (#10). This observation suggests that although Si + treatment does not promote expression of the core SA pathway genes, the upstream master regulators of the SAR pathway, including GmSARD1, GmPAD4, and GmWRKY40, were highly induced in vascular and guard cells upon Si + treatment. Expression of these genes has been reported to increase pathogen resistance, stomatal closure, and SAR through SA biosynthesis in plants ^68,69. Furthermore, genes involved in SAR downstream to the SA biosynthesis pathways such as GmNPR3 (Non-expression of PR protein), GmTGAs (TGACG cis-element binding), and GmWRKY70 were expressed in vascular and epidermal cells, whereas GmPR1s (Pathogenesis related-1) were expressed in vascular and mesophyll cell types upon Si + treatment.

GmHiSil2c regulates Si unloading in epidermal cell layers

Si transporters have been well-characterized in monocots, mostly in rice. Lsi1 (influx transporter) facilitates the translocation of Si from the soil into root cells via a gradient mechanism, functioning as a passive transporter. Conversely, Lsi2 (efflux transporter) acts as an active transporter, facilitating the transport of Si from root cells to the vascular stream ^1,4,70–74. In a recent genome wide association study (GWAS)¹⁷, we identified that Si accumulation in soybean leaves is controlled by a major QTL on Chromosome (Chr) 16, which harbors three efflux Si transporter genes (GmHiSil-2a, -2b and − 2c). To understand cell-specific expression of these genes identified on Chr. 16 and other putative Si influx aquaporin family transporters⁷⁵, the snRNA-seq data was explored. Among the several putative Si transporters in soybean (Supplemental Table S1D), the two influx Lsi1 type Si transporters GmNIP2-1 and GmNIP2-2 were found to be expressed in our datasets (Fig. 6a). On the other hand, among the three Si efflux transporters identified in GWAS¹⁷, only GmHiSil2c (Lsi2) was highly expressed in our snRNA-seq dataset. The UMAP plots showed that the expression of GmNIP2-1 and GmNIP2-2 was notably higher in Si- (control) leaves, particularly in the epidermal cells, whereas their expression decreased following Si + treatment (Fig. 6a). Whereas GmHiSil2c (Chr. 16 QTL gene) was exclusively expressed in leaf epidermal cells upon Si + treatment. In an independent experiment we validated the expression of these genes using qRT-PCR analysis and their expression pattern was similar to the snRNA-seq data (Fig. 6b). These findings suggest that GmHiSil2c acts as a functional Si transporter specific to leaves, possibly playing a role in Si loading into the space between the epidermis and cuticle bilayer. Subsequently, to determine the subcellular localization of these Si transporters, the coding sequences (CDS) of GmNIP2-1, GmNIP2-2, and GmHiSil2c were fused with the green fluorescent protein (GFP) at the C-terminal end and expressed under the control of constitutive promoter (CmYLCV) followed by transfection in N. benthamiana protoplast. Confocal microscopy analysis revealed that these transporter-GFP fusions were localized to the cell membrane, whereas the control construct (CmYLCV::GFP) was expressed and localized to the cell membrane, nucleus, and cytoplasm (Fig. 6c). Next, to validate whether a loss-of-function of efflux Si transporters GmHiSil2c (expressed only in leaf epidermal cells) and its homolog GmHiSil2b (expressed in roots) identified in GWAS¹⁷ results in altered Si uptake, we used CRISPR/Cas9 dual guide RNA constructs for targeted knockout in transgenic hairy roots of soybean composite plants.

Next, to validate whether a loss-of-function of efflux Si transporters GmHiSil2c that was expressed only in leaf epidermal cells (Fig. 6a) and also identified in GWAS¹⁷, results in altered Si uptake, we used CRISPR/Cas9 dual guide RNA constructs for targeted knockout in transgenic hairy roots of soybean composite plants. Additionally, its homolog GmHiSil2b (expressed in roots) was used as a control for gene-knockout study. Dual guide RNAs (gRNA) were designed to target exon 1 to generate small and large deletions in Hikmok background (Fig. 6d). Composite hairy root plants were generated using CR-GmHiSil2b, CR-GmHiSil2c, and empty vector (EV) constructs and plants expressing GFP positive roots were selected for Si uptake assay followed by genotyping. After a week of Si treatment, Si concentration was detected using pXRF. Hikmok hairy roots transformed with CR-GmHiSil2b showed significant reduction in leaf Si content compared to EV control, whereas CR-GmHiSil2c composite plant leaves exhibited no significant change in Si concentration (Fig. 6e). As gene knockout was generated in roots, these results further indicate that GmHiSil2b acts as root specific Si transporter, while GmHiSil2c is not involved in Si transport in roots, but it is a leaf specific Si transporter involved in Si unloading in epidermal cells. Transgenic roots from a subset of composite plants for each construct were collected to confirm CRISPR/Cas9-induced edits using amplicon sequencing. We observed deletions ranging from 53 to 185 base pairs (bp) in GmHiSil2b and for GmHiSil2c, the deletions were 273 bp and 418 bp (Fig. 6d and Supplementary Fig. 13).

Understanding cellular heterogeneity upon Si accumulation in leaves

In plant biology, numerous reports substantiate the importance of mineral nutrients on plant development, disease resistance, abiotic stress tolerance, seed quality, and net productivity ¹⁷. The availability of mineral nutrients to plants is a dynamic and complex process affected by various factors. These factors encompass the inherent gene pool governing nutrient uptake and translocation, soil composition, physical and chemical properties, and other environmental variables. Among several major and minor nutrients, the role of Si in plants is often overlooked. Although, Si is not classified as an essential plant nutrient, it plays a beneficial role in plant development ⁷⁶, abiotic stress tolerance ^77–79, and biotic stress alleviation ^10,11,80,81. The molecular mechanisms governing Si intake and translocation have been extensively examined in rice ^1,4,70,71. However, its role in various dicot crop plants including soybean is not well elucidated. In recent studies, a major QTL for Si uptake in soybean leaves has been identified ¹⁷. However, there is a lack of a comprehensive molecular understanding of Si uptake and translocation in dicot species, including soybean. Also, previous studies primarily relied on bulk transcriptomics, a methodology inherently unable to discern cellular heterogeneity and prone to overlooking cell-specific gene expression ^81–85. Single-nuclei-based transcriptomics is a powerful technology for elucidating the dynamics of biological processes and understanding the diversity among distinct cell types. SnRNA-seq techniques have enabled researchers to analyze complex traits at a single-cell resolution, particularly emphasizing tissue-specific single-cell atlas, tissue developmental processes, plant-microbe interactions, and abiotic stresses ^{20–24,86,87}. To comprehensively elucidate Si deposition in soybean leaves and its consequential effects on genes specific to individual cells and their associated gene networks, we employed snRNA-seq technology. This approach allowed us to gain comprehensive insights into the intricacies of Si mediated biological process in plants. The first step in single-cell genomics is the classification of cell types. The identification of leaf-specific cell types in soybean has remained unexplored to date, and to address this critical gap, we undertook a comprehensive approach, leveraging publicly available datasets ^20,22,27, iterative tools such as the R package ClusterFoldSimilarity ⁸⁸, and cross-species comparisons to classify the diverse cell types within soybean leaves. Previous studies in rice, Arabidopsis, and Maize identified 10 to18 cell types based on different cell type markers ^89,90. In this study, we developed an snRNA-seq transcriptome of soybean leaf treated with and without Si and successfully unveiled three major tissue types (vascular, epidermal, and mesophyll) that were further subclustered into 12 distinct cell populations (Fig. 1). Specifically, Si-induced cells (cluster #5) were exclusively identified in Si + treated soybean plants and were closely associated with xylem cells (Fig. 4a and 4b), indicating a potential differentiation from the xylem. Moreover, Si + treatment exhibited altered patterning and arrangement of xylem cells, which was more compact, continuous and showed lesser distance between the xylem vessels (Fig. 4c and Supplementary Fig. 9a and 9b). Previous studies have shown that Si deposition changes cell size, shape, differentiation and overall arrangements in leaf and root tissue^28,91. For instance, both high Si-accumulating (rice and maize) and low Si-accumulating (onion) plants develop new casparian band cells in roots upon Si treatment ⁹⁸. Similarly, addition of Si lead to change in vascular area in Glycyrrhiza uralensis, improving water transport efficiency⁹², changes leaf anatomy (thickness of epidermis and mesophyll) in banana and increase in metaxylem and vascular bundle length in wheat ^93,94. In agreement with these reports, we hypothesized that in Si + treated soybean plants pre-existing vascular cells may undergo differentiation and/or distinct transcriptome regulation leading to xylem cell patterning and arrangement in leaf (Fig. 4a, b and c). Nevertheless, this hypothesis necessitates dedicated experimentation to validate and further explore the underlying mechanisms.

Si treatment unlocks key role transcriptional priming of vascular cells in plant defense

In-depth characterization of distinct cell types identified a complex, yet compelling gene expression pattern across the cell types (Fig. 1, 2, and 3). Importantly, a subset of genes and their GO terms associated with 'defense response', 'plant immunity,' and response to salicylic acid and phytoalexin were predominantly enriched (Fig. 3). There are several mechanisms through which Si ameliorates biotic stress in plants, such as serving as a physical barrier or apoplastic obstruction, enhancing defense-responsive metabolites, hormones, and antimicrobial compounds (Phytoalexins), and activating defense-responsive molecular cascades ^29,81. While previous studies using bulk RNA sequencing of root tissues have suggested that Si alone has no impact on plant’s transcriptome and metabolism in a controlled or unstressed condition^2,95, our study shows that Si treatment alone can change the leaf transcriptome and primes the plant to induce defense-responsive genes even in the absence of pathogenic stress. This finding aligns with prior studies, showing that Si supplementation can change plant transcriptomes with or without pathogen or abiotic stressors. For instance, it has been reported that Si treatment in wheat elicits the upregulation of abundant genes, particularly highlighting the differential expression of MYB transcription factors¹⁹. Additionally, in rice under normal conditions, Si treatment leads to a decrease in phosphorus (P) uptake by modulating transcriptome including downregulation of P transporter genes, independent of any biotic or abiotic stressors⁹⁷. Nevertheless, it cannot be ruled out that the transcriptional priming could be temporal, which was not captured in previous studies. Intriguingly, cell-specific expression of defense responsive genes, significantly confined to vascular cell types represents a significant advancement beyond prior knowledge, emphasizing the distinct and specialized role of Si treatment in coordinating molecular responses related to biotic stress and phytohormonal signaling (Figs. 3 and 4). Moreover, this Si-induced cluster exhibited a unique gene expression pattern significantly enriched in genes related to plant-pathogen interaction including RNAi silencing, phytoalexin, immune response and SA signaling. Of such RNAi silencing pathway is well studied and it gets activated against pathogen attack such as viral infections and degrade the viral RNA via small interfering RNAs (siRNA), preventing the spread of the infection ^99–101. This mechanism is largely conserved in plants and functions through RNA-induced silencing complexes (RISCs), DICER-LIKEs (DCLs), and Argonaute (AGO) proteins. We identified a significantly higher transcript abundance of RNA silencing machinery genes, such as GmDCL1, GmDCL4, GmAGO5 and GmMPK4, in Si-induced and other cell types (Fig. 4e). Among other prominent biological processes, genes involved in the phytoalexin biosynthesis process (GmWRKY33a, GmWRKY33b, GmWRKY33c) were also significantly enriched in epidermal (cluster #1, 11), vascular (cluster #2, 5, 8, 9 and 10) and guard cells (cluster #12) after Si + treatment (Supplementary Fig. 7). Phytoalexins have antimicrobial properties and are synthesized in response to the onset of stress cues in plants and are involved in pathogen defense response ^31,36. In soybean, glyceollin is a major phytoalexin and play a crucial role in providing defense against Phytophthora sp. ^36,102–104. However, cell-type specific expression phytoalexins biosynthesis upon Si treatment remain elusive. Here we identified cell-type specific expressions of these genes upon Si + treatment, laying the foundation for understanding their role and suggesting their potential involvement in the Si + primed resistance mechanism (Supplementary Fig. 7).

We also identified complementary pathways involving extra-cellular and intra-cellular receptors, RLPs and NLRs, marked by a notable upregulation in Si + treated plants (Fig. 5a and 5b). RLPs are cell surface receptors involved in the detection of extracellular pathogen molecular signatures, through which they promote pathogen defense response ¹⁰⁵. Specifically, higher expression of GmRLP56, GmRLP13, and GmRLP9 genes confined to xylem and Si-induced cells after Si + treatment was identified (Fig. 5c). Similarly, NLR genes, extensively studied in various plant species, play a pivotal role in recognizing and initiating defense mechanisms through hypersensitive response (HR) and SAR ¹⁰⁶. A recent study applied single-cell transcriptomics to reveal cell-type specific responses to fungal infection in Arabidopsis leaves⁸⁶. Consistent with our finding, they reported the enrichment of intracellular immune receptors (NLRs) in vascular cells ⁸⁶. In our study, snRNA-seq provided a nuanced perspective, enabling the detection of distinct expression patterns of NLR immune response genes based on their classes GmTNL1, GmTLN2, GmDSC1.1 (TNLs), GmRPM1.1 (CNL) and GmNRG1.1 (RNL) in cell-types specific manner upon Si + treatment (Fig. 5d).

Salicylic acid (SA), a central player in plant innate immunity, orchestrates various defense responses against biotic attacks. SA acts locally at the infection site and systemically throughout the plant, commencing resistance, hypersensitive responses, and cell death to cease pathogen spread ¹⁰⁷. While the influence of Si on SA has not been investigated in previous studies, our observations reveal a subtle alteration in the expression of SA ‘signaling’ genes post Si + treatment, without significant changes in the core SA ‘biosynthesis’ genes (Supplementary Fig. 12). The upregulation of SA signaling genes (GmPAD4, GmSARD1, and GmWRKY40) in vascular cells supports the notion of priming the SA pathway in soybean. However, Si + treatment does not induce the expression of core SA biosynthesis genes (GmICS and GmPAL), suggesting an unknown negative regulator of SA. This finding is consistent with previous studies, which reported that Si + treatment alone did not induce endogenous ‘SA biosynthesis’ genes in soybean roots or jasmonate (JA) genes (OsAOS and OsCOI1) in rice leaves^10,108. Furthermore, our findings support that pathogen infection might be necessary to induce the expression of core SA biosynthesis genes and their accumulation in plant cells. However, our data also concludes that Si + treatment alone can induce the expression of SA signaling and receptor genes, such as GmSARD1, GmPAD4, GmWRKY40, GmNPR, GmPR and GmTGAs (Supplementary Fig. 12). In summary, pathogens employ diverse strategies to infiltrate host plant tissues, establishing robust colonization across various cell types. Particularly, vascular tissues are the primary destination for a variety of pathogens (fungi, oomycetes, bacteria etc.) seeking nutrients. Our findings further substantiate the vital role of Si absorption and modulation of gene expression networks in vascular cells to actuate the defense response in plants.

Unveiling Si deposition in soybean leaves

Silicon uptake in plants occurs primarily through the root epidermal cells, facilitated by specific transporters. The influx transporter Lsi1, a member of the aquaporin family, mediates Si uptake from the soil, while the efflux transporter Lsi2, belonging to the anion transport protein superfamily, facilitates Si efflux from the root cells into the xylem vessels. These transporters have been extensively characterized in monocot species such as rice and maize⁷⁰. To understand the expression patterns of putative Si influx and efflux transporters in soybean^74,75, the snRNA-seq data generated in this study was explored and genes were characterized using sub-cellular localization and gene-editing approaches. All putative Si transporters identified in genome-wide study⁷⁵ and GWAS¹⁷ were investigated and among them two influx transporters, GmNIP2-1 and GmNIP2-2 (homologous to OsLsi1), and one efflux transporter, GmHiSil2c (homologous to OsSiet4), were expressed in soybean leaf snRNA-seq datasets (Fig. 6a). Furthermore, the expression of these three genes was validated using qRT-PCR study (Fig. 6b). Relatively higher expression of GmNIP2-1 and GmNIP2-2 was observed in epidermal and vascular cells of control (Si-) leaves compared to those subjected to Si + treatment (Fig. 6a, b). The reduced expression of Lsi1 influx transporters (GmNIP2-1 and GmNIP2-2) in Si + treatment suggests a potential gradient-based transport mechanism, similar to observations in rice seedlings tissues⁷¹. Additionally, it has been studied that following Si accumulation in the leaves, Si does not move to other tissues⁷¹, and therefore the active supply is ceased by down-regulation of both Lsi1 and Lsi2 genes in rice^71,109. In soybean, we observed that GmHiSil2c (Lsi2) was highly expressed only in leaf epidermal and vascular cells in Si + treated plant (Fig. 6a). This suggests that during tissue harvesting for nuclei isolation, GmHiSil2c was actively expressing and was functioning in Si unloading in the leaf epidermis. Furthermore, sub-cellular localization of these genes confirmed their role as transmembrane proteins (Fig. 6c).

Recently, the new leaf-specific Si efflux transporter (OsSiet4) has been identified to regulate Si distribution in rice¹. The knockout mutant of ossiet4 exhibited a severe wilting phenotype in the presence of Si + due to disturbed and abnormal Si accumulation in rice leaf mesophyll cells¹. Although, the mechanism of Si efflux transporters has not been studied before in dicots, here we identified that GmHiSil2c (homolog of rice OsSiet4) is exclusively expressed upon Si + treatment in soybean leaf epidermal cells (cluster #1, #11) and its protein localized to the cell membrane (Fig. 6c). To further confirm the tissue specificity of the GmHiSil2c, we performed CRISPR/Cas9 mediated gene knockout in composite hairy root plants (Fig. 6d and e). After one week of Si treatment, the composite hairy root mutants of GmHiSil2C showed no difference in Si accumulation in leaves compared to EV (Fig. 6e). Whereas its homologous gene GmHisil2b, identified as root specific transporter¹⁷, showed significant reduction in Si accumulation in leaf tissue. These findings suggest that GmHisil2c functions as a leaf-specific Si transporter and plays a vital role in the precise distribution of Si within the soybean leaf. Overall, these findings contribute to our understanding of Si transport mechanisms in soybean leaf and highlight the potential regulatory mechanisms governing Si uptake, translocation and transcriptional priming in dicot system. Further studies elucidating the regulatory networks controlling Si transporter expression will enhance our ability to manipulate Si uptake and utilization in crops for improved agronomic performance and stress tolerance.

This study illuminates the significant impact of Si uptake on soybean physiology, particularly transcriptional priming in enhancing defense responses. Utilizing snRNA-seq, we identified distinct cellular populations and novel Si-induced clusters within vascular cells, indicating a specialized mechanism for Si distribution in dicot species. Si treatment notably induced the expression of defense-related genes, with a pronounced effect in vascular cells, underscoring their crucial role in plant defense. Key biological processes involved in RNA silencing, phytoalexin biosynthesis, and immune receptor signaling, substantiated a transcriptional priming of defense pathways. The differential expression patterns of putative Si transporters highlight active and gradient-based Si transport mechanisms. Functional validation using targeted gene editing confirmed the leaf specific role of Si transporters. These findings provide a deeper understanding of the biotic stress regulatory networks modulated by Si in soybean, offering pragmatic solutions for enhancing crop stress tolerance and productivity through strategic Si utilization.

Plant material, growth conditions, hydroponic system, and Silicon treatment

Soybean cultivar (cv) Hikmok-sorip (PI 372415) was used in this study. Seeds were grown on germination paper for duration of 5 days; subsequently, seedlings were transplanted onto hydroponic trays containing a solution with half-strength Hogland media at a pH of ~ 5.7. The hydroponic system was continuously aerated using an air pump to prevent oxygen deficiency. The hydroponic setup was established in a growth chamber with a photoperiod of 16/8 light/dark, providing 350 PAR light, relative humidity of 65%, day/night temperature regime at 26/24°C. The nutrient solution in the hydroponic system was replenished once in five days. After 2 weeks of seedling growth, silicon treatment was performed by applying 1.7 mM of K₂SiO₄ (Silicon treatment; Si+) for 7 days, while 1.7 mM of KCl (control, Si-) was used as a potassium control ¹¹⁰.

Nuclei extraction, SnRNA-seq library preparation, and sequencing

Nuclei isolation was performed from Si + and Si- soybean leaf tissues as previously described ¹¹¹. Briefly, the tissue was ground in a nuclei isolation buffer and incubated briefly on a slow shaker. After incubation the nuclei suspension is passed through 100 µm, 70 µm, 30 µm, and 10 µm cell strainers. The suspension was spun at 1000g for 5 minutes. The nuclei pellet was resuspended in wash buffer and spun again at 1000g for 2 minutes. The nuclei were stained with propidium iodide and counted with the Luna-FL (Logos Biosystems). The nuclei were then loaded onto the 10x Genomics chip as per 10x genomics recommendations. Library construction for Illumina sequencing was performed with the Chromium™ Single Cell 3’ Library & Gel Bead Kit v3.1 protocol (10x Genomics). The single-indexed sequencing and paired-end libraries was carried out on an Illumina™ NovaSeq 6000 platform according to the 10x Genomics references.

SnRNA-seq data pre-processing, integration, and clustering

Sequencing data was processed through cellranger (v7.2.0) to obtain cell feature counts for analysis. The data was aligned to the Glycine max Wm82.a4. v1 genome. Count data was further analyzed within the R package Seurat v4 ¹¹². Nuclei were filtered according to the following criteria: RNA gene count > 200, UMI count > 400 and < 10000, mitochondrial reads > 5% per cell, and chloroplast reads < 30% per cell. Doublets were removed with scDblFinder (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9204188/). The data was then normalized by SCTransform and the samples were integrated using 3000 features to reduce batch effect and identify conserved cell types. Dimension reduction of the integrated data was performed by PCA with RunPCA and the UMAP plots were generated using PCs 1 to 40. Leiden clustering was applied (resolution 0.8) to identify the potential cell types. Ubiquitous/nondescript clusters were removed manually and the UMAP and clustering were re-run according to previous specifications. After filtering 2080 total cells were obtained (1104 from control sample and 976 from silicon treated sample) with an average UMI of 1546 and a number of genes of 1005.

Annotation of Cell types by utilizing ortholog gene markers and Gene Ontology (GO) analysis

Annotation of cell clusters was performed through orthologous expression of Arabidopsis genes and GO term analysis. Markers for each cluster were generated with “FindAllMarkers” at the following specifications: min.pct = 0.25, logfc.threshold = 0.25, min.diff.pct = 0.15. Arabidopsis orthologs were then compared to ²⁰ and Leaf SC atlas, VIB Ghent, Belgium ²² (https://www.psb.ugent.be/sc-leaf-yieldlab/) to identify cell types. ClusterProfiler ¹¹³ was used to perform GO term enrichment analysis with default parameter.

Differential gene expression and Gene Ontology analysis

Differentially expressed genes between control and silicon treatments were found with FindMarkers with the following parameters: min.pct = 0.25, logfc.threshold = 0.25, min.diff.pct = 0.15, group.by = sample, subset.ident = cluster #. Gene Ontology analysis for treatment induced differentially enriched GO terms was performed with clusterProfiler as previously described.

RNA extraction and gene expression analysis

Total RNA extraction and purification from soybean leaves and roots were carried out using Trizol reagent, followed by the utilization of the Pure Link RNA Mini Kit (Invitrogen). Subsequently, cDNA synthesis and qRT-PCR procedures were conducted following previously established protocols ^114,115. The PCRs were executed using the C1000 Touch PCR with the CFX96 C1000 touch Real-Time Optics Module thermal cycler qRT-PCR System (BIO-RAD, USA). The qRT-PCR primers were designed using Quant prime online tool. GmElf1b (Glyma.02g276600) served as the internal control for gene expression analysis ¹¹⁴. All the qRT-PCR primers are listed (Supplemental Table S1E). Expression data were normalized by subtracting the mean CT value of the reference gene from the mean CT value of the gene of interest (ΔCT). The determination of statistical significance was carried out using the student’s t-test.

Silicon estimation by SEM-EDS

Silicon content analysis in soybean leaves was conducted through Scanning Electron Microscopy-Energy Dispersive X-ray Spectroscopy (SEM-EDS) as described¹⁷. The analysis was conducted at an accelerating voltage of 20 kV and 140 Pa under the variable pressure mode using a Hitachi S-3400 microscope equipped with an Oxford EDS system.

Silicon estimation by XRF

The plant tissues were subjected to a week-long drying process at 45°C, after which they were finely pulverized using the Tissue Lyser II (Qiagen, Cat. No. / ID: 85300). Subsequently, ~ 300 mg pellets were prepared from the dried and finely ground samples using a 15T hydraulic press with a 13 mm diameter (Athena Technology, India). Portable X-ray fluorescence (pXRF) analyzer (Bantam Axon, Olympus) was used to quantify mineral element accumulation in each sample as previously described ¹¹⁶. Briefly, the pXRF was set on the analysis mode (Vegetation Analysis) specifically optimized for plant samples by the manufacturer (Bantam Axon, Olympus). The NIST (National Institute of Standards and Technology) samples, including Apple Leaves (NIST1515), Peach Leaves (NIST1547), and Pine Needles (NIST-1575) with known mineral concentrations, were used to generate user factors for each element and as standard control to check the reproducibility of the XRF analysis.

Leaf anatomy, staining and imaging

To capture effects of Si treatment on leaf vasculature especially xylem, soybean (cv. hikmok) plants were grown as described above in Si (+) and Si (-) media for a week. After one week leaf midribs were sectioned with a sharp razor blade using a dissection microscope. Sections were stained with 0.1% (w/v) berberine hemi-sulphate (Sigma, C.I. no. 75160) to stain lignin in xylem cell walls as previously described by Brundrett et al ¹¹⁷. Finally, leaf midrib sections were transferred to 50% (v/v) glycerol for microscopic observation. Midrib leaf sections were imaged under EVOS™ M5000 Imaging System at 488 nm excitation and 520 nm emission wavelengths.

Generation of Constructs and genotyping

The Gateway recombination compatible C terminal GFP fusion destination modular vector pMod_A218-pCmYLCV:R1-CCDB-R2-GFP:HspT was made in the laboratory. Briefly, the CmYLCV (Cestrum yellow leaf curling virus) promoter amplicon from pMod_B2103 vector, R1-CCDB-R2 amplicon from pEarleyGate 100 vector, and GFP-HSPTerminator amplicon from pMod_C3003 vector were amplified by PCR and assembled by using NEB HiFi assembly master mix (E2621S, NEB, USA). Later, by employing gateway cloning (www.lifetechnologies.com) GmNIP2-1, GmNIP2-2, GmHiSil2c (genes synthesized from Twist Bioscience, USA) genes were cloned into Pd221 entry vector by using BP-clonase enzyme. Next entry clones were moved to GFP fusion destination modular vector pMod_A218 by using LR-clonase enzyme.

For genome editing by CRISPR/Cas9, Golden Gate construct modules such as A0521 (AtCas9), B2103b (cloning multiple gRNAs), C3001 (GFP marker) and pTRANS230d (binary vector) were used ¹¹⁸. Arabidopsis codon optimized Cas9 is expressed under the control of strong constitutive promoter GmUbi. Multiple guide RNAs (gRNAs) are expressed under the control of CmYLCV promoter and each gRNA with gRNA scaffold will be separated by Csy4 processing mechanism. GFP is expressed under enhanced CaMV 35S promoter, respectively. To knock out GmHisil2b and GmHiSil2c, gRNAs were designed by CRISPR-P tool ¹¹⁹. High ranking gRNAs were chosen with no possible off targets ¹¹⁹. Two gRNAs were designed for each gene to induce larger deletions. For GmHiSil2b, the two gRNAs were spaced 156 base pairs (bp) apart, while for GmHiSil2c, they were separated by 398 bp. We used a multiplex gRNA cloning protocol and vector B2103b to assemble dual gRNAs for GmHiSil2b and GmHiSil2c, as previously described ¹¹⁸. All vector cassettes (A0521, B2103b and C3001) were assembled together in binary vector pTRANS230d by employing Golden Gate cloning method utilizing type II restriction enzyme AarI as previously described by Cermak et al ¹¹⁸. Amplicons of CRISPR/Cas9 genome editing target genes (GmHiSil2b and GmHiSil2c) were amplified and cloned into pJET1.2 vector by using CloneJET PCR Cloning Kit (ThermoFisher, USA) and different clones were sequenced. All the primers used for cloning and genotyping are listed (Supplemental table S1E). All the constructs were sequence confirmed by sequencing whole plasmids by Oxford Nanopore Technology from Plasmidsaurus, Eugene, USA.

Generation of composite hairy roots and Si treatment

Composite soybean plants with GmHiSil2b- and GmHiSil2c-edited roots were generated using Agrobacterium rhizogenes (strain, K599) mediated transformation according to the established method ¹²⁰. After K599 inoculation, the plants were sealed and placed in a growth chamber maintained at 26°C with a 16-hour light (300 µmol/m²/s¹) /8-hour dark photoperiod for generation of hairy roots. Once the roots developed, the plants were moved to the greenhouse. Under fluorescent light, composite plants with transformed hairy roots were selected, and any untransformed roots were removed. Finally, the plants with uniform roots were transplanted. After one week of seedling growth, silicon treatment was performed by applying 1.7 mM of K₂SiO₄ (Silicon treatment; Si+) for 5 days, while 1.7 mM of KCl (control, Si-) was used as a potassium control. Later Si content was measured in leaves by XRF.

Protoplast preparation and transformation

Tobacco protoplasts were isolated from the leaves of Nicotiana benthamiana and transiently transformed as described by ^121,122. We used 2*10⁵ protoplasts per transfection reaction, Equal concentration (15µg) of plasmids were used for the localization experiments.

Laser Scanning Confocal Microscopy

Protoplasts, expressing fluorescent constructs transiently, were observed using a laser scanning confocal microscope (Olympus IX83) within their culture medium after 12h of transformation. GFP fluorescence was detected utilizing a 488 nm argon ion laser line, with emission recorded using a 500–540 nm filter set. The chlorophyll autofluorescence was detected using the fluorophore set at 647 nm and emission recorded at 650–750 nm filter set. Confocal microscope images were processed in Fiji ImageJ software ¹²³.

Data availability statement

All the soybean gene IDs for gene names mentioned in this study are listed in Supplemental Table S1-F.

Author Contributions

VD: experimental design, formal Analysis, data prediction, methodology and writing original draft, CRISPR/Cas9 construct designing, genotyping, Phenotyping; LDA: snRNA-seq analysis and writing; AOK: protoplast isolation; LY: snRNA-seq library preparation; ABN, VPT, AS, JM and RMS: reviewing and editing manuscript; LHE: project administration, supervision and editing manuscript; RD: methodology, data analysis and editing manuscript; GBP: Conceptualization, formal analysis, funding acquisition, supervision and writing and editing manuscript.

Acknowledgements

GBP is grateful to the Southern Soybean Research Program (SSRP), the United Soybean Board (2414-209-0202) and the State of Texas' Governor's University Research (GURI) for the research funding.

Declaration of Interests

Authors declare no competing interest.

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There is NO Competing Interest.

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Supplementary Fig. 1:Silicon treatment to Soybean cv. Hikmok in hydroponic system. (a) Soybean plants were grown in aerated hydroponic system in half-strength hogland media, pH 5.7. (b) Si content detected by XRF in leaves of Si (-) and Si (+) treated soybean plants grown hydroponically.
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Supplementary Fig. 2: Detection of Silicon by SEM-SDS microscopy. (a) Scanning electron microscopy (SEM) combined with EDS spectroscopy imaging of soybean leaves with different elemental profiling in Si- and Si+ treated plants. (b) Electron micrograph of soybean leaf trichome and its base area. Bottom graphs exhibit level of different elements including Si in scanned soybean leaf area. Red boxes highlights the presence of Si element.
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Supplementary Fig. 3: SnRNA-seq analysis reveals distinct clusters in soybean leaves. (a) Image depicts number of nuclei, detected genes, mean UMI and mean number of genes in soybean SnRNA-seq dataset. (b) Color-coded visualization of soybean leaf nuclei by Uniform Manifold Approximation and Projection (UMAP) plot based on transcriptomic profiles.
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Supplementary Fig. 4: Dot plot of GO term enrichments in xylem, phloem and Si-induced cell types.
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Supplementary Fig. 5: Dot plot of GO term enrichment in epidermal and guard cell types.
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Supplementary Fig. 6: Dot plot of GO term enrichment in mesophyll cells.
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Supplementary Fig. 7: UMAP plot depicts expression of putative phytoalexin biosynthesis activator genes. (a) UMAP plot exhibits expression of GmWRKY33b and GmWRKY33c. (b) UMAP plot exhibits expression of GmCRT3b gene. The color depicts relative gene expression (dark purple = higher expression, Green = medium expression, Yellow = lower expression).
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Supplementary Fig. 8: A bar graph represents the similarity between Si-induced cells and remaining cell type clusters after Si (+) treatment.
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Supplementary Fig. 9: Soybean leaf midrib cross sections visualizing vasculature cell types. (a) Scanning electron microscopy (SEM) of soybean leaf vasculature of Si (+) and Si (-) treated soybean plants. One headed white arrow indicate xylem cells. Purple arrows indicate area between group of xylem cells, whereas orange oval shapes denote organization of xylem cells in clusters in Si (-) whereas strip like continuous patterns in (Si+). (b) Fluorescence microscopy images of soybean leaf vasculature of Si (+) and Si (-) treated soybean plants. Left side images are brightfield, while the fluorescence images on the right side are stained with berberine hemisulphate salt to highlight the xylem cells. One headed white colored arrow shows xylem cells. Whereas two headed white arrows indicate area between groups of xylem cells.
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Supplementary Fig. 10: Heatmap and GO enrichment interactions of DEGs in Si-induced cell cluster. Dot size denotes enrichment of GO terms.
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Supplementary Fig. 11: UMAP plot showing expression of most exclusively expressed genes in Si induced cell cluster after Si treatment. (a) Association plot illustrate most distinct genes expressed (genes with red dots and IDs) exclusively in Si-induced cell cluster upon Si treatment. Red color denotes most distinctly expressed genes in Si-indued cell cluster while blue color denotes less distinctly expressed genes. (b) UMAP plot exhibits close-up view of expression of most distinctly expressed genes in Si-induced cells. The color depicts relative gene expression (dark purple = higher expression, Green = medium expression, Yellow = lower expression).
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Supplementary Fig. 12: SnRNA-Seq reveals transcriptional regulation of salicylic acid (SA) biosynthesis and signaling pathway genes in different cell types upon Si treatment. (a) Dot plot analysis depicts expression of SA biosynthesis and signaling genes in soybean leaves after Si- (control) and Si+ treatment. The size of the dots depicts the percentage of cells in each clusters that express the gene. The colors exhibit the relative expression. The red dot represents Si (-) sample, while blue dot represents Si (+) treated sample. (b) Figure depicts the genes involved in SA biosynthesis and signal transduction pathway network with representation of their expression patterns in various cell types in soybean leaves. Different colored circles indicate expression of genes in respective tissue type clusters. Genes in blue boxes are differentially expressed in snRNA-seq dataset in soybean leaves upon Si treatment.
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Cell-type-specific response to silicon treatment in soybean leaves revealed by single nucleus RNA-sequencing and targeted gene-editing

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Abstract

Figures

Introduction

Result

SnRNA-seq analysis of Si + and Si- treated soybean leaves

Identification of “Silicon-induced” cell cluster

Discerning the cellular responses to Si treatment

Deciphering Si deposition in soybean

Perturbations of defense-responsive genes upon Si treatment

GmHiSil2c regulates Si unloading in epidermal cell layers

Discussion

Understanding cellular heterogeneity upon Si accumulation in leaves

Si treatment unlocks key role transcriptional priming of vascular cells in plant defense

Unveiling Si deposition in soybean leaves

Materials and Methods

Plant material, growth conditions, hydroponic system, and Silicon treatment

Nuclei extraction, SnRNA-seq library preparation, and sequencing

SnRNA-seq data pre-processing, integration, and clustering

Annotation of Cell types by utilizing ortholog gene markers and Gene Ontology (GO) analysis

Differential gene expression and Gene Ontology analysis

RNA extraction and gene expression analysis

Silicon estimation by SEM-EDS

Silicon estimation by XRF

Leaf anatomy, staining and imaging

Generation of Constructs and genotyping

Generation of composite hairy roots and Si treatment

Protoplast preparation and transformation

Laser Scanning Confocal Microscopy

Declarations

References

Additional Declarations

Supplementary Files

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