Analysis method for interaction between testicular sertoli cells and germ cells of plateau livestock based on mononuclear transcriptomics technology

Abstract

The invention provides a mononuclear transcriptomics technology-based analysis method for interaction of testicular sertoli cells and germ cells of plateau livestock, and belongs to the technical field of bioinformatics. The analysis method comprises the following steps: carrying out mononuclear transcriptome sequencing by taking testis tissues of plateau livestock at different development stages as materials, dividing a supporting cell subset and a germ cell subset according to marker genes, drawing a quasi-time differentiation track, screening differential expression genes and enriching functions, and constructing a supporting cell and germ cell interaction molecular network. According to the method, molecular characteristics, differentiation tracks and interaction networks of supporting cells and germ cells of the testis of the Tibetan sheep in different development stages are analyzed, and the problems that in the prior art, cell resolution is insufficient, development dynamics are deficient, variety specificity information is deficient and the like are solved; a brand new technical approach and theoretical basis are provided for clarification of cell molecular basis of low reproductive capacity of Tibetan sheep and mining of key regulatory factors.

Description

Technical Field

[0001] This application belongs to the field of bioinformatics technology, specifically relating to an analytical method for the interaction between testicular supporting cells and germ cells in plateau livestock based on single-cell nuclear transcriptomics technology. Background Technology

[0002] The testis is the core organ of the male reproductive system in mammals, and its spermatogenesis efficiency directly affects male fertility. The testicular parenchyma is mainly composed of seminiferous tubules and interstitium. The interaction between Sertoli cells and germ cells at various stages within the seminiferous tubules constitutes the cellular basis of spermatogenesis, and their dynamic interaction is crucial for maintaining normal spermatogenesis and male fertility. Currently, to elucidate the regulatory mechanisms of spermatogenesis in male livestock, research typically focuses on constructing protein interaction networks or gene co-expression networks based on whole-cell samples or isolated and enriched samples of a specific cell type (such as Sertoli cells or germ cells) to screen for key genes related to spermatogenesis and testicular development. However, these methods cannot reflect the true cellular heterogeneity and intercellular interactions within the testis. The testis contains various cell types, including Sertoli cells, germ cells, and interstitial cells. Sertoli cells themselves exhibit a continuous differentiation process from immature to mature, and germ cells also have multiple developmental stages. Traditional research methods struggle to analyze the interactions between these cell subpopulations at single-cell resolution, and cannot systematically characterize the dynamic regulatory networks during cell state transitions. In addition, for livestock raised on plateaus (such as Tibetan sheep and yaks), their testicular cells have long adapted to special environments such as low oxygen and low temperature, and their cell interaction networks may be more complex and have unique regulatory patterns and response characteristics that are different from those of livestock raised on plains.

[0003] However, existing methods have not yet established an effective analytical method for systematically analyzing the interaction between supporting cells and germ cells in the testes of highland livestock at the single-cell level, especially for cell heterogeneity, continuous evolution of cell state, and dynamic intercellular interactions. Summary of the Invention

[0004] The purpose of this invention is to provide an analytical method for the interaction between supporting cells and germ cells in the testes of highland livestock based on single-cell nuclear transcriptomics technology. By analyzing the single-cell transcriptome of the testes of highland livestock at different developmental stages, the subpopulation classification, differentiation trajectory and interaction network of supporting cells and germ cells can be clarified, providing technical support and theoretical basis for optimizing the reproductive performance and reproductive adaptability of highland livestock.

[0005] This invention provides a method for analyzing the interaction between Sertoli cells and germ cells in the testes of high-altitude livestock based on single-cell nuclear transcriptomics technology, comprising the following steps: Single-cell nuclear transcriptome sequencing was performed on testicular tissues from highland livestock at different developmental stages to obtain sequencing results; Gene annotation was performed on the sequencing results to obtain single-nuclear transcriptome expression matrices supporting cell subpopulations and germ cell subpopulations at various levels; Gene expression matrices of single-nuclear transcriptomes supporting cell subpopulations and germ cell subpopulations at various levels were aligned to a ligand-receptor database to construct an interaction network between supporting cells and germ cells, thereby identifying key intercellular interaction pathways and / or ligand-receptor pairs.

[0006] Preferably, the different developmental stages of the plateau livestock include the early life stage, pre-sexual maturity stage, post-sexual maturity stage, and adulthood stage.

[0007] Preferably, the types of livestock raised on the plateau include at least one of the following: Tibetan sheep, Tibetan goat, Tibetan yak, Tibetan cattle, Tibetan bulldog, Tibetan horse, and Tibetan pig.

[0008] Preferably, after the gene annotation, the method further includes trajectory inference based on the single-nuclear transcriptome expression matrix of the supporting cell subpopulation and the germ cell subpopulation to construct pseudo-time differentiation trajectories of supporting cells and germ cells, identifying dynamically differentially expressed genes that are significantly related to pseudo-time along the pseudo-time axis, and identifying key genes and pathways related to the differentiation process through enrichment analysis.

[0009] Preferably, the supporting cell subpopulation includes immature supporting cells, transitional supporting cells, and mature supporting cells; the marker genes of the supporting cell subpopulation include at least one of the following genes: GATA4, AMH, FSHR, ABAT, SOX9, FATE1, and AR; The germ cell subpopulations at each level include spermatogonia, spermatocytes, and spermatids; the marker genes for the germ cell subpopulations at each level include at least one of the following genes: NCL, HMGB2, SPATA17, FSIP2, CHD5, and TNP1.

[0010] Preferably, the algorithms for constructing the interaction network supporting cells and germ cells include the CellChat and CellPhoneDB algorithms.

[0011] Preferably, the method for constructing the pseudo-time differentiation trajectories of the supporting cells and germ cells involves using Monocle 2 software to infer the trajectory of the single-nuclear transcriptome gene expression matrix of the supporting cell subpopulation and germ cell subpopulations at all levels, importing the gene expression matrix obtained by Seurat processing into a Monocle object, performing cell sorting and calculating pseudo-time series, and obtaining the pseudo-time differentiation trajectories of the supporting cells and germ cells at all levels. The identification of dynamically differentially expressed genes that are significantly correlated with the pseudo-time axis is achieved by using the FindMarkers function of Seurat to screen for differentially expressed genes; the enrichment analysis is performed using the clusterProfiler package for GO / KEGG functional enrichment analysis. The method for analyzing the interaction network between supporting cells and germ cells involves integrating ligand-receptor pairs from the CellPhoneDB and CellChat databases, and using CellChat software to analyze intercellular interactions.

[0012] Preferably, after identifying key intercellular interaction pathways and / or ligand-receptor pairs, the process further preferably includes verifying the key intercellular interaction pathways and / or ligand-receptor pairs. The verification method includes immunofluorescence staining. The immunofluorescence staining method for verifying supporting cell markers includes SOX9; the immunofluorescence staining method for verifying germ cell markers at all stages includes LIN28B, UTF1, RPLP1, EPCAM, JAK1, PIWIL1, and TNP2; the ligand-receptor pair includes CDH2-CDH2.

[0013] Preferably, the key interaction pathway includes at least one of the following signaling pathways: COLLAGEN, LAMININ, CADM, PTN, and ACTIVIN; The key ligand-receptor pairs include at least one of the following: CADM1-NECTIN3, CADM1-CADM1, and CDH2-CDH2.

[0014] This invention provides the application of the analytical method for the interaction between testicular supporting cells and germ cells in plateau livestock based on single-cell nuclear transcriptomics technology in the improvement of reproductive performance in plateau livestock.

[0015] This invention provides a method for analyzing the interactions between supporting cells and germ cells in the testes of highland livestock based on single-cell nuclear transcriptomics technology. The method includes the following steps: performing single-cell nuclear transcriptome sequencing on testicular tissues from highland livestock at different developmental stages; annotating the sequencing results with genes; aligning the single-cell nuclear transcriptome gene expression matrices of the obtained supporting cell subpopulations and germ cell subpopulations at various levels to a ligand-receptor database; constructing an interaction network between supporting cells and germ cells; and identifying key intercellular interaction pathways and / or ligand-receptor pairs. This invention analyzes the molecular characteristics, differentiation trajectories, and interaction networks of supporting cells and germ cells in the testes of highland livestock at different developmental stages. This method addresses the problems of insufficient cell resolution, lack of developmental dynamics, and insufficient breed-specific information in existing technologies, providing a novel technical approach and theoretical basis for elucidating the cellular and molecular basis of low fertility in Tibetan sheep and identifying key regulatory factors. Attached Figure Description

[0016] Figure 1 The results are single-cell transcriptome atlases of testicular development in Tibetan sheep. A shows H&E staining results of testicular tissue at four developmental stages; B shows t-SNE visualization of cell clusters and developmental stage distribution; C shows a bubble chart of cell type-specific marker gene expression; and D shows the correspondence between cell clusters and germ cell types. Figure 2 The results show the dynamic gene expression patterns during spermatogenesis, where A represents the pseudo-time differentiation trajectory of germ cells; B represents the gene expression heatmap on the pseudo-time sequence; C represents the expression patterns of key marker genes in the pseudo-time sequence; and D represents the GO enrichment results of differentially expressed genes in different germ cell subpopulations. Figure 3 The results show the dynamic gene expression characteristics of spermatogonial cell subsets. A represents the immunofluorescence staining results of spermatogonial cell marker genes; B represents the bubble diagram of gene expression related to spermatogonial stem cells (SSCs) and progenitor cells in the undifferentiated spermatogonial cell subset; C represents the violin diagram of cell cycle-related gene expression; D represents the LIN28B immunofluorescence staining results; E represents the metabolic changes of spermatogonial cells from spermatogonial stem cells to the differentiated state; and F represents the heatmap of gene expression related to glycolysis and oxidative phosphorylation. Figure 4 The results show the trajectory analysis of spermatogonial stem cell self-renewal and differentiation; where A is the pseudo-time trajectory of spermatogonial cells (stained according to cell state and subset); B is the gene expression heatmap on the pseudo-time sequence; C is the expression results of self-renewal and differentiation-related genes in the pseudo-time sequence; and D is the immunofluorescence staining results of DJAK1 and EPCAM. Figure 5The results show the dynamics of gene expression during meiosis; A is PIWIL1 immunofluorescence staining; B is the t-SNE diagram of spermatocyte re-clustering; C is the expression results of meiotic marker genes on the t-SNE diagram; D is the pseudo-time trajectory of spermatocytes; E is the gene expression heatmap on the pseudo-time sequence; F and G are the expression patterns of key meiotic genes. Figure 6 The results show the dynamics of gene expression during spermatogenesis; A represents the simulated time trajectory of sperm cells; B represents the transcriptomic differences between two developmental stages of round sperm cells; C represents the expression results of the top 6 genes in the two stages of round sperm cells; D represents the gene expression heatmap on the simulated time sequence; E represents the expression of key genes in the simulated time sequence; and F represents the immunofluorescence staining results of the TNP2 marker gene. Figure 7 To support the dynamics of heterogeneous cell populations during cell development; A shows the results of SOX9 immunofluorescence staining; B shows the t-SNE plot of supporting cell re-clustering; C shows the expression results of supporting cell marker genes on the t-SNE plot; D shows the expression of key genes in supporting cells at different developmental stages; E shows the pseudo-time developmental trajectory of supporting cells; F shows the distribution of supporting cells by age and cell cycle; G shows the gene expression heatmap on the pseudo-time series; H shows the expression results of immune-related genes during supporting cell maturation. Figure 8 The results show the global interaction network among testicular cells. A is a ring diagram of the number (left) and intensity (right) of ligand-receptor pair interactions between cells; B is a hierarchical diagram of the intercellular communication network; C is the expression of ligands (red) and receptors (blue) of key signaling pathways on the t-SNE diagram; D is the key ligand-receptor pairs of the supporting cell-germ cell interaction; E is a bubble diagram of ligand-receptor interactions between supporting cells (source) and germ cells (target); F is the results of CDH2 immunofluorescence staining; and G is a schematic diagram of the localization of CDH2 at the supporting cell-germ cell junction. Detailed Implementation

[0017] This invention provides a method for analyzing the interaction between Sertoli cells and germ cells in the testes of high-altitude livestock based on single-cell nuclear transcriptomics technology, comprising the following steps: Single-cell nuclear transcriptome sequencing was performed on testicular tissues from highland livestock at different developmental stages to obtain sequencing results; Gene annotation was performed on the sequencing results to obtain single-nuclear transcriptome expression matrices supporting cell subpopulations and germ cell subpopulations at various levels; By aligning the gene expression matrix of a single-cell nuclear transcriptome to a ligand-receptor database, an interaction network supporting cells and germ cells was constructed, and key intercellular interaction pathways and / or ligand-receptor pairs were identified.

[0018] This invention uses testicular tissue from plateau livestock at different developmental stages as material for single-cell nuclear transcriptome sequencing to obtain sequencing results.

[0019] In this invention, the preferred species of plateau livestock include at least one of the following: Tibetan sheep, Tibetan goat, Tibetan yak, Tibetan cattle, Tibetan bulldog, Tibetan horse, and Tibetan pig. Tibetan sheep are a major economic livestock species living in the Qinghai-Tibet Plateau and surrounding high-altitude areas (approximately 3000m above sea level). Their reproductive performance directly affects the sustainable development of local pastoral economy and the maintenance of the ecological balance of alpine grasslands. Through long-term natural selection and artificial breeding, they have developed unique physiological mechanisms adapted to extremely cold and low-oxygen environments. However, their growth environment has led to the evolution of unique reproductive characteristics in Tibetan sheep, such as prolonged developmental cycles, delayed sexual maturity, and low fertility, which restricts the expansion efficiency of the Tibetan sheep industry. Therefore, analyzing the molecular regulatory mechanisms of Tibetan sheep reproductive development, especially the dynamic changes and interactions of key cell types in the testes, is beneficial for understanding the biological essence of reproductive adaptation in plateau animals, elucidating the cellular and molecular basis of low fertility in Tibetan sheep, and identifying key regulatory factors, laying the foundation for improving their reproductive performance through molecular means. In this embodiment of the invention, the analysis method of the interaction between testicular supporting cells and germ cells in plateau livestock is illustrated using Tibetan sheep as an example.

[0020] In this invention, the different developmental stages of the plateau livestock span from neonatal to adulthood, preferably including the initial stage, pre-sexual maturity stage, post-sexual maturity stage, and adulthood. Taking Tibetan sheep as an example, the initial stage is preferably 1-5 days old, but can be 2-4 days old, or even 3 days old. The pre-sexual maturity stage includes 2-4 months old, but can be 2.5-3.5 months old, or even 3 months old. The post-sexual maturity stage preferably includes 0.8-1.2 years old, but can be 0.9-1.1 years old. The adulthood preferably includes 2.5-3.5 years old, but can be 2.8-3.2 years old, or even 3 years old. The testes of plateau livestock at different developmental stages comprehensively cover the complete process of testicular development and spermatogenesis, providing a complete sample system for analyzing the temporal dynamic changes in the interaction between supporting cells and germ cells. This invention, through in-depth analysis of the molecular characteristics of supporting cells and germ cells in the testes of highland livestock at different developmental stages, helps to solve the problem of insufficient cell resolution and fills the gap in the existing technology regarding the dynamic content of testicular development in highland livestock.

[0021] In this invention, after collecting testicular tissue from high-altitude livestock at different developmental stages, the epididymis, connective tissue, and secretions are preferably removed to obtain pretreated testicular tissue from high-altitude livestock. This pretreated tissue is divided into two parts: one part is used for single-cell suspension preparation, and the other part is used for verification experiments. The pretreated testicular tissue from high-altitude livestock is prepared into a single-cell suspension, preferably by quick-freezing in liquid nitrogen, followed by lysis, and then centrifugation with iodixanol at a gradient density to collect the nuclear layer. The density of the single-cell suspension is preferably 700-1200 cells / μL, but can be 800-1100 cells / μL or 900-1000 cells / μL.

[0022] In this invention, the single-cell nuclear transcriptome sequencing preferably includes sequencing library construction and high-throughput sequencing. This invention does not impose any particular limitation on the method of constructing the sequencing library; any sequencing library well-known in the art can be used. In this embodiment of the invention, the sequencing library is preferably constructed using 10× Genomics Chromium Next GEM Single Cell 3ʹ ReagentKits v3.1. This invention does not impose any particular limitation on the method of high-throughput sequencing; any high-throughput method well-known in the art can be used.

[0023] After obtaining the sequencing results, the present invention performs gene annotation on the sequencing results to obtain single-cell nuclear transcriptome expression matrices supporting cell subpopulations and germ cell subpopulations at various levels.

[0024] In this invention, the sequencing results are preferably quality filtered before gene annotation. The sequencing results are preferably quality controlled using CellRanger v3.1.0 software to remove low-quality barcodes and UMI reads. Then, STAR software is used to align clean reads to the Tibetan sheep reference genome (CAU_O.aries_1.0), retaining only reads uniquely mapped to the transcriptome and covering ≥50% of exon regions for UMI counting, generating a feature-barcode matrix and gene expression profile. The quality filtering also includes cell filtering, batch correction, removal of multiple cells, and cell clustering and annotation, preferably analyzed using Seurat v3.1.1 software. The preferred criteria for collecting sequencing results after quality filtering are: 200-5900 genes, <10% mitochondrial gene proportion, and <26000 UMI count; batch correction is performed using the Harmony algorithm, cell clustering using the Louvain algorithm, and visualization using t-SNE. The Harmony algorithm (theta=2, lambda=1, max.iter.harmony=10) is preferably used to perform batch effect correction on the first 50 principal components to preserve biological heterogeneity. The cell type annotation method preferably uses known cell type-specific marker genes and gene expression patterns to annotate various levels of germ cell subpopulations and supporting cell subpopulations. These various levels of germ cell subpopulations preferably include spermatogonia (including undifferentiated and differentiated spermatogonia), spermatocytes, and spermatids.

[0025] In this embodiment of the invention, 21 cell clusters were identified from Tibetan sheep testicular tissue at different growth stages, including three main types of germ cells (spermatogonia, spermatocytes, and spermatids) and six types of somatic cells (Serpentine cells, interstitial cells, macrophages, lymphocytes, myoid cells, and endothelial cells). Specific marker genes for each germ cell subpopulation include: NCL and HMGB2 (for identifying spermatogonia); SPATA17 and FSIP2 (for identifying spermatocytes); and CHD5 and TNP1 (for identifying spermatids). The marker genes for the Sertoli cell subpopulation preferably include at least one of the following genes: GATA4, AMH, FSHR, ABAT, SOX9, FATE1, and AR.

[0026] In this invention, in order to further evaluate the accuracy of the single-nuclear transcriptome expression matrix of the supporting cell subpopulation and the germ cell subpopulation at each level, the invention also includes trajectory inference based on the single-nuclear transcriptome expression matrix of the supporting cell subpopulation and the germ cell subpopulation at each level to construct pseudo-time differentiation trajectories of supporting cells and germ cells, and to identify dynamically differentially expressed genes that are significantly related to pseudo-time along the pseudo-time axis. After enrichment analysis, key genes and pathways related to the differentiation process are obtained.

[0027] In this invention, the software used to construct the pseudo-time differentiation trajectories of germ cells and supporting cells is preferably Monocle 2.10.1. Specifically, cells are sorted according to developmental time sequence, gene populations are divided based on gene expression patterns, key regulatory genes in the differentiation process are identified, and the gene expression matrix obtained from Seurat processing is imported and constructed into a Monocle object. The key regulatory genes include β-defensin genes in the maturation process of supporting cells or genes such as JAK1, EPCAM, ZBTB16, and DMRT1 in germ cell differentiation.

[0028] In this invention, differentially expressed genes at different differentiation stages were screened using the Wilcoxon rank-sum test in the FindMarkers function of Seurat software. The screening criteria were log2FC ≥ 0.36 (upregulation) or log2FC < 0 (downregulation). P ≤0.01, meaning that ≥25% of cells in the target subpopulation express this gene. For differentially expressed genes at different differentiation stages, functional injection using the clusterProfiler package for GO / KEGG functional enrichment analysis is preferred, as it helps to understand the functional characteristics of different cell subpopulations.

[0029] After obtaining the gene expression matrix of the single-nuclear transcriptome of the supporting cell subpopulation and germ cell subpopulations at all levels, this invention compares the gene expression matrix of the single-nuclear transcriptome of the supporting cell subpopulation and germ cell subpopulations at all levels to the ligand-receptor database, constructs the interaction network of supporting cells and germ cells, and identifies key intercellular interaction pathways and / or ligand-receptor pairs.

[0030] In this invention, the algorithm for constructing the interaction network between supporting cells and germ cells preferably includes the CellChat and CellPhoneDB algorithms. The preferred method for analyzing the interaction network between supporting cells and germ cells is to integrate ligand-receptor pairs from the CellPhoneDB and CellChat databases, utilize the UMI counting matrix generated by Seurat, and use CellChat software to analyze the signal transduction network between supporting cells and germ cells, quantify the interaction strength and probability of ligand-receptor pairs, and identify key interaction pathways and core ligand-receptor pairs.

[0031] In this invention, after identifying key intercellular interaction pathways and / or ligand-receptor pairs, the process preferably further includes verifying these pathways and pairs. The verification method preferably includes immunofluorescence staining and / or H&E staining. The immunofluorescence staining method for verifying supporting cell markers preferably includes SOX9; the immunofluorescence staining method for verifying germ cell markers includes LIN28B, UTF1, RPLP1, EPCAM, JAK1, PIWIL1, and TNP2; the ligand-receptor pair preferably includes CDH2-CDH2. This invention does not impose any special limitations on the operational steps of the immunofluorescence staining method; experimental procedures well known in the art can be used. The H&E staining and immunofluorescence staining verification achieve cross-validation of transcriptome data with tissue morphology and protein expression levels, improving the reliability of the research results.

[0032] In this invention, the key interaction pathways preferably include at least one of the following signaling pathways: COLLAGEN, LAMININ, CADM, PTN, and ACTIVIN. The key ligand-receptor pairs preferably include at least one of the following: CADM1-NECTIN3, CADM1-CADM1, and CDH2-CDH2.

[0033] In this invention, the method employs single-cell nuclear transcriptomics (snRNA-seq) technology, combined with bioinformatics analysis and molecular biology verification, to achieve precise identification of Tibetan sheep testicular cell subpopulations, revealing three immature subtypes, one transitional subtype, and one mature subtype of supporting cells, as well as multi-level differentiation subpopulations of germ cells.

[0034] This invention provides the application of the analytical method for the interaction between testicular supporting cells and germ cells in plateau livestock based on single-cell nuclear transcriptomics technology in the improvement of reproductive performance in plateau livestock.

[0035] The following detailed description, in conjunction with embodiments, illustrates an analytical method for analyzing the interaction between testicular supporting cells and germ cells in plateau livestock based on single-cell nuclear transcriptomics technology, but these descriptions should not be construed as limiting the scope of protection of this invention.

[0036] Example 1 1. Preparation of experimental materials (1) Sixteen healthy Tibetan sheep were selected and divided into four groups (T0M, T3M, T1Y, T3Y), with four sheep in each group. They were raised at the Gannan Tibetan Sheep Breeding Base in Gansu Province and were fed and managed uniformly until the corresponding age before sampling. The patient fasted for 12 hours before sampling. After euthanasia via veno-jugular vein bloodletting, the left testis was rapidly dissected and separated. The surface blood and impurities were rinsed with pre-cooled PBS. The epididymis, spermatic cord, and connective tissue were removed. The testicular tissue was divided into two parts: one part was cut into 1mm sections. 3 Small pieces were flash-frozen in liquid nitrogen for cell nucleus extraction; another portion was fixed in 4% paraformaldehyde solution for 24 hours for paraffin section preparation.

[0037] 2. Single-cell suspension preparation and snRNA-seq sequencing (1) Take out the testicular tissue block frozen in liquid nitrogen, put it into a pre-cooled mortar, add a small amount of liquid nitrogen and grind it into powder, transfer it to a centrifuge tube containing pre-cooled lysis buffer (10mM Tris-HCl pH 7.4, 10mM NaCl, 3mM MgCl2, 0.1% NP-40, 1mM MTT, 1× protease inhibitor), and incubate on ice for 10 min; Filter the lysate through a 70 μm cell sieve, collect the filtrate into a centrifuge tube, centrifuge at 4 °C and 500 g for 5 min, and discard the supernatant; Add 1 mL of pre-cooled iodixanol gradient solution (15%~25%), gently pipette to resuspend the precipitate, centrifuge at 4℃ and 10000g for 20 min, and aspirate the middle nuclear layer into a new centrifuge tube. Add 2 mL of cell nuclear washing buffer (10 mM Tris-HCl pH 7.4, 10 mM NaCl, 3 mM MgCl2, 1% BSA), centrifuge at 500 g for 5 min at 4 °C, discard the supernatant, and repeat the washing twice. Resuspend the cell nuclei in nuclear washing buffer, count them using a cell counting chamber, adjust the cell nucleus concentration to 700-1200 nuclei / μL, take 10μL for trypan blue staining, and observe the cell nucleus integrity under a microscope (viability ≥85%). The qualified cell nuclear suspension was sent to Guangzhou Genomics Biotechnology Co., Ltd., and a library was constructed according to the instructions of 10x GenomicsChromium Next GEM Single Cell 3ʹ Reagent Kits v3.1. PE150 sequencing was performed using a sequencing platform.

[0038] 3. Single-cell transcriptome data analysis (1) 1. Raw data processing: Using CellRanger v3.1.0 software, set the parameters --chemistry=3ʹv3.1, --expect-cells=5000 to filter, align and count the UMI of the raw sequencing data and generate the gene expression matrix.

[0039] 2. Use Seurat v3.1.1 software to perform cell filtering and integration.

[0040] 3. Cell clustering and visualization.

[0041] 4. Cell annotation: Based on the marker genes in Table 1, the expression of marker genes in each cell cluster was verified using the FeaturePlot and DotPlot functions to determine the cell type.

[0042] Table 1 Cell marker genes

[0043] 5. Differentially Expressed Genes and Functional Enrichment: First, at the cell subpopulation level, Seurat's FindMarkers function was used to screen for differentially expressed genes to identify differentially expressed genes in specific clusters, and the clusterProfiler package was used for GO / KEGG enrichment analysis. In addition, at the differentiation trajectory level, pseudo-time trajectories constructed based on Monocle2 were used to screen for dynamically differentially expressed genes that were significantly correlated with pseudo-time, and GO / KEGG enrichment analysis was performed on them to characterize the cell subpopulation-specific molecular features and continuous transcriptional changes during differentiation.

[0044] 6. Cell Interaction Analysis: Integrating ligand-receptor pairs from the CellPhoneDB and CellChat databases, cell-cell interactions were analyzed using CellChat software.

[0045] See results Figure 1 Cell annotation identified a total of 21 cell clusters, including 3 major germ cell types and 6 somatic cell types. Figure 1 (C, D, E) Germ cell subpopulations: Spermatogonia were identified based on marker genes such as NCL and HMGB2; spermatocytes were identified based on marker genes such as SPATA17 and FSIP2; and sperm cells were identified based on marker genes such as CHD5 and TNP1.

[0046] Supporting cell subsets: Based on marker genes such as SOX9 and FATE1, supporting cells were further divided into immature supporting cells (State 1 / 2 / 3), transitional supporting cells (State 4), and mature supporting cells (State 5). Figure 7 (B, C)

[0047] (4) Differentiation trajectory analysis: Pseudotime differentiation trajectories of germ cells and Sertoli cells were constructed using Monocle 2.10.1 software. Differentiation trajectories for spermatogonia, spermatocytes, spermatids, and Sertoli cells were constructed using default parameters. Spermatogenesis trajectories were constructed using specific genes (spermatogonia vs. spermatid-specific differential genes). Cells were sorted according to developmental time sequence, and gene cohorts were identified based on gene expression patterns to identify key regulatory genes during differentiation. Results are shown in […]. Figure 2 China A Figure 4 China A Figure 5 D, Figure 6 China A and Figure 7 E in Chinese.

[0048] (5) Differentially expressed genes (DEG) analysis and functional enrichment: The Wilcoxon rank-sum test in Seurat software was used to screen differentially expressed genes in different cell subpopulations or developmental stages. The screening criteria were log2FC≥0.36 (upregulated) or log2FC<0 (downregulated). P ≤0.01, ≥25% of cells in the target subpopulation express this gene; perform GO (GeneOntology) and KEGG (Kyoto Encyclopaedia of Genes and Genomes) functional enrichment analysis on differentially expressed genes to reveal the functional characteristics of different cell subpopulations. Figure 2 (D).

[0049] (6) Cell interaction network analysis: Integrate ligand-receptor pairs from CellPhoneDB and CellChat databases, use the UMI counting matrix generated by Seurat, and use the CellChat algorithm to analyze the signal transduction network between supporting cells and germ cells, quantify the interaction strength and probability of ligand-receptor pairs, and identify key interaction pathways and core ligand-receptor pairs.

[0050] The results of the global signaling network for intercellular interactions in Tibetan sheep testes are shown in [reference needed]. Figure 8 The results show that this embodiment identified the core pathways (COLLAGEN, LAMININ, CADM, PTN, ACTIVIN, etc.) and key ligand-receptor pairs (CADM1-NECTIN3, CADM1-CADM1, CDH2-CDH2, etc.) involved in the interaction between supporting cells and germ cells. Figure 8 (Among them, A, B, and E), some of the ligand-receptor pairs are Tibetan sheep-specific interacting molecules.

[0051] 4. Verification Experiment (1) H&E staining Paraffin-embedded testicular tissue sections (5 μm) were stained with H&E. After dewaxing, hematoxylin staining for 5 min, eosin staining for 30 s, dehydration and clearing, and mounting with neutral resin, the histomorphological characteristics of testicular tissue at different developmental stages were observed using an orthogonal light microscope (Nikon Eclipse E100).

[0052] See results Figure 1 A. The results demonstrate the consistency between cell composition and developmental state.

[0053] (2) Immunofluorescence staining Immunofluorescence staining of testicular tissue sections was performed using an orthogonal fluorescence microscope (Nikon Eclipse C1) to verify the protein expression localization of key marker genes, including germ cell markers (LIN28B, UTF1, RPLP1, EPCAM, JAK1, PIWIL1, TNP2, etc.), supporting cell markers (SOX9), and interaction-related proteins (CDH2). The dewaxing process was performed as follows: paraffin sections were dewaxed with xylene (3 times, 5 min each time), followed by graded ethanol dehydration (100%, 95%, 80%, 70%, 3 min each time), and rinsed with distilled water for 5 min. Antigen retrieval was then performed by placing sections in citrate buffer (pH 6.0), heating to boiling in a microwave oven, and holding for 15 min, followed by natural cooling to room temperature. Blocking was done with 3% BSA solution at room temperature for 30 min. Primary antibody incubation was followed by adding diluted primary antibody and incubating overnight at 4°C. Secondary antibody incubation was performed by adding fluorescent secondary antibody after washing and incubating at room temperature in the dark for 1 h. DAPI staining was performed by incubating with DAPI staining solution at room temperature in the dark for 5 min. Finally, the slides were mounted with anti-fluorescence quenching mounting medium, observed under a fluorescence microscope, and photographed. See results Figure 3 A and D in the middle Figure 4 Chinese E, Figure 5 China A Figure 6 China F, Figure 7 China A Figure 8 The results showed that different cell types exhibited clear marker-specific distributions: UTF1 and LIN28B signals were mainly enriched in spermatogonial stem cell populations, while RPLP1 showed a stronger positive signal in differentiated spermatogonia. Figure 3 China A Figure 3 JAK1 and EPCAM are expressed in spermatogonial stem cells before differentiation begins, and their protein signaling is mainly enriched in differentiated spermatogonia during subsequent developmental stages. Figure 4 The presence of PIWIL1 in spermatogonia (E) suggests that both may be involved in the early stages of spermatogonial transition from stem to differentiated state. As germ cell differentiation progresses, PIWIL1 is primarily located in spermatocytes (E). Figure 5 TNP2 is specifically expressed in sperm cells (A), while TNP2 is expressed in sperm cells (A). Figure 6 In the somatic cell level, SOX9 showed a stable positive rate in Supporting cells. Figure 7 CDH2 is located at the cell junction between supporting cells and germ cells (A); CDH2 is located at the cell junction between supporting cells and germ cells (A). Figure 8 The presence of F indicates that it plays an important role in communication between supporting cells and germ cells.

[0054] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for analyzing the interaction between Sertoli cells and germ cells in the testes of plateau livestock based on single-cell nuclear transcriptomics technology, characterized in that, Includes the following steps: Single-cell nuclear transcriptome sequencing was performed on testicular tissues from highland livestock at different developmental stages to obtain sequencing results; Gene annotation was performed on the sequencing results to obtain single-nuclear transcriptome expression matrices supporting cell subpopulations and germ cell subpopulations at various levels; Gene expression matrices of single-nuclear transcriptomes supporting cell subpopulations and germ cell subpopulations at various levels were aligned to a ligand-receptor database to construct an interaction network between supporting cells and germ cells, thereby identifying key intercellular interaction pathways and / or ligand-receptor pairs.

2. The method for analyzing the interaction between testicular supporting cells and germ cells in plateau livestock based on single-cell nuclear transcriptomics technology according to claim 1, characterized in that, The different developmental stages of the plateau livestock include the early life stage, pre-sexual maturity stage, post-sexual maturity stage, and adulthood stage.

3. The method for analyzing the interaction between Sertoli cells and germ cells in the testes of plateau livestock based on single-cell nuclear transcriptomics technology according to claim 1, characterized in that, The types of livestock raised on the plateau include at least one of the following: Tibetan sheep, Tibetan goat, Tibetan yak, Tibetan cattle, Tibetan bulldog, Tibetan horse, and Tibetan pig.

4. The method for analyzing the interaction between Sertoli cells and germ cells in the testes of plateau livestock based on single-cell nuclear transcriptomics technology according to claim 1, characterized in that, The supporting cell subpopulation includes immature supporting cells, transitional supporting cells, and mature supporting cells, and the marker genes of the supporting cell subpopulation include at least one of the following genes: GATA4, AMH, FSHR, ABAT, SOX9, FATE1, and AR; The germ cell subpopulations at each level include spermatogonia, spermatocytes, and spermatids; the marker genes for the germ cell subpopulations at each level include at least one of the following genes: NCL, HMGB2, SPATA17, FSIP2, CHD5, and TNP1.

5. The method for analyzing the interaction between Sertoli cells and germ cells in the testes of plateau livestock based on single-cell nuclear transcriptomics technology according to claim 1, characterized in that, After the gene annotation, the process also includes trajectory inference based on the single-nuclear transcriptome expression matrices of the supporting cell subpopulation and germ cell subpopulation to construct pseudo-time differentiation trajectories of supporting cells and germ cells, identifying dynamically differentially expressed genes that are significantly related to pseudo-time along the pseudo-time axis, and identifying key genes and pathways related to the differentiation process through enrichment analysis.

6. The method for analyzing the interaction between Sertoli cells and germ cells in the testes of plateau livestock based on single-cell nuclear transcriptomics technology according to claim 1, characterized in that, The algorithms for constructing the interaction network supporting cells and germ cells include the CellChat and CellPhoneDB algorithms.

7. The method for analyzing the interaction between Sertoli cells and germ cells in the testes of plateau livestock based on single-cell nuclear transcriptomics technology according to claim 1, characterized in that, The method for constructing the pseudo-time differentiation trajectories of supporting cells and germ cells involves using Monocle 2 software to infer the trajectory of the gene expression matrix of single-cell nuclear transcriptome of supporting cell subpopulations and germ cell subpopulations at all levels. The gene expression matrix obtained by Seurat processing is imported and constructed as a Monocle object. Cell sorting and pseudo-time series are then performed to obtain the pseudo-time differentiation trajectories of supporting cells and germ cells at all levels. The identification of dynamically differentially expressed genes that are significantly correlated with the pseudo-time axis is achieved by using the FindMarkers function of Seurat to screen for differentially expressed genes; the enrichment analysis is performed using the clusterProfiler package for GO / KEGG functional enrichment analysis. The method for analyzing the interaction network between supporting cells and germ cells involves integrating ligand-receptor pairs from the CellPhoneDB and CellChat databases, and using CellChat software to analyze intercellular interactions.

8. The method for analyzing the interaction between Sertoli cells and germ cells in the testes of plateau livestock based on single-cell nuclear transcriptomics technology according to claim 1, characterized in that, After identifying key intercellular interaction pathways and / or ligand-receptor pairs, the process further includes verifying the key intercellular interaction pathways and / or ligand-receptor pairs. The verification method includes immunofluorescence staining. The immunofluorescence staining method was used to verify that the cell markers supporting the cells included SOX9; The immunofluorescence staining method used to verify the cell markers for each stage of germ cells includes LIN28B, UTF1, RPLP1, EPCAM, JAK1, PIWIL1, and TNP2; the ligand-receptor pair includes CDH2-CDH2.

9. The method for analyzing the interaction between Sertoli cells and germ cells in the testes of plateau livestock based on single-cell nuclear transcriptomics technology according to any one of claims 1 to 8, characterized in that, The key interaction pathways include at least one of the following signaling pathways: COLLAGEN, LAMININ, CADM, PTN, and ACTIVIN; The key ligand-receptor pairs include at least one of the following: CADM1-NECTIN3, CADM1-CADM1, and CDH2-CDH2.

10. The application of the analytical method for the interaction between testicular supporting cells and germ cells of plateau livestock based on single-cell nuclear transcriptomics technology as described in any one of claims 1 to 9 in the improvement of reproductive performance of plateau livestock.

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