Method for screening molecular markers of parenchymal hepatic cell subgroups in liver tissue of pearl grouper
Through single-cell RNA sequencing technology, specific molecular markers of the liver parenchymal cell subpopulations in the liver tissue of pearl gentian grouper were identified and screened, which solved the problem of lack of targeted pathway research basis in the existing technology, achieved accurate identification of the liver parenchymal cell subpopulations, and provided a theoretical basis for the targeted regulation of grouper nutritional metabolism.
Patent Information
- Application Number
- CN202411673595.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-21
- Publication Date
- 2025-04-15
AI Technical Summary
The existing technology lacks the basis for the targeted pathway research of the nutritional metabolism of pearl gentian groupers, especially the function of liver parenchyma cells of pearl gentian groupers.
Through single-cell RNA sequencing technology, liver tissue samples of pearl gentian grouper were extracted, single cells were isolated and cell suspension was prepared. High-throughput sequencing was performed using the 10×genomics sequencing platform, and combined with bioinformatics analysis, specific molecular markers of liver parenchymal cell subpopulations were identified and screened out.
The accurate identification of the liver parenchymal cell subpopulations in the liver tissue of pearl gentian grouper was achieved, and specific molecular markers were screened out, providing a theoretical basis for the targeted regulation of grouper nutritional metabolism, and providing promotion and application value for the research of other tissues and cell subpopulations.
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Figure CN119824096A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the technical field of biological analysis, and more specifically, relates to a method for screening molecular markers of hepatocyte subpopulations in liver tissue of pearl grouper. Background Art
[0002] According to research reports, the rapid development of the global aquaculture industry and long-term overfishing have led to a shortage of resources such as fish meal and fish oil, and prices have continued to rise, bringing huge cost pressure to aquaculture, which has brought huge challenges to the sustainable and rapid development of my country's aquaculture industry and restricted the healthy development of the aquaculture industry. In order to solve such problems, studies on the replacement of nutrients in feed (protein sources and fat sources, etc.) to varying degrees can effectively deal with the current situation. During the research process, there is evidence that the liver, as the main organ of the fish body, plays an important role in regulating many physiological processes such as nutrient metabolism, lipid and cholesterol balance, and protein amino acid metabolism. When replacing protein and fat sources in fish diets, negative results such as reduced weight gain rate, weakened protein and lipid utilization efficiency, and decreased liver tissue metabolic enzyme activity were also found. How to regulate nutrient metabolism and explore the specific pathways of its synthesis, transport and decomposition can effectively provide new solutions to the current research on healthy feeding problems.
[0003] Single-cell mRNA sequencing (scRNA-seq) technology provides a solution to the problem at the molecular level. It can annotate unclassified cells in tissues based on the mRNA expression pattern of each cell. The large amount of bioinformatics data obtained through scRNAseq enables us to divide cells into specific groups, analyze cell heterogeneity, predict the functions of single-cell populations based on gene expression profiles, and the changes in signal pathways at the molecular transcriptional level and potential molecular mechanisms of single-cell populations with different functions under different experimental conditions, providing a theoretical basis for the targeted regulation of nutritional metabolism of grouper.
[0004] The existing technology lacks a targeted pathway research basis for the nutritional metabolism of pearl grouper. The reason is that there is no single-cell sequencing method for pearl grouper, nor is there any functional research on the hepatic parenchymal cells of pearl grouper. Summary of the invention
[0005] Based on the current state of the art, this application intends to provide a method for identifying hepatocyte subpopulations in the liver tissue of pearl grouper, in particular, a method for screening specific molecular markers of hepatocyte subpopulations in liver tissue. This application can reveal the main cell types in the liver tissue of pearl grouper, as well as specific molecular markers of hepatocytes, and can explore the potential molecular mechanisms of hepatocytes in the liver tissue of pearl grouper as the main functional cells of nutritional metabolism, as well as signal pathways related to nutritional metabolism, from the molecular transcription level, to provide a theoretical basis for the targeted regulation of nutritional metabolism of grouper.
[0006] The invention also provides the screened molecular markers of hepatocyte subpopulations in the liver tissue of pearl grouper.
[0007] The present invention also provides application of the screened molecular markers of hepatocyte subpopulations in the liver tissue of pearl grouper.
[0008] The purpose of the present invention is achieved through the following technical solutions:
[0009] The present invention firstly provides a molecular marker of hepatocyte subpopulation in the liver tissue of pearl grouper, wherein the molecular marker is FGA and ITIH3.
[0010] The invention also provides application of the molecular marker in studying the nutritional metabolism of pearl grouper.
[0011] The present invention also provides a method for screening molecular markers of hepatocyte subpopulations in the liver tissue of pearl grouper, the method comprising: extracting tissue samples, isolating single cells and preparing cell suspensions, using single-cell RNA sequencing technology, obtaining sequencing data based on a 10×genomics sequencing platform, and performing bioinformatics analysis on the sequencing data; the steps of the bioinformatics analysis are:
[0012] ① After high-throughput sequencing of all mRNAs in a single cell, the software analyzes the expression patterns of all genes in the cell and reduces the expression matrix to important eigenvalues through a dimensionality reduction algorithm; the Cell Ranger software pipeline provided by Genomics is used to map the reads to the genome and transcriptome, and the R software package Seurat is used to process the unique molecular identifier UMI count matrix; after eliminating a certain proportion of low-quality cells, the filtered matrix is normalized in Seurat to obtain normalized counts, and finally the proportions of effective high-quality cells retained are 95.6%, 96.2%, and 96.6%, respectively;
[0013] ②Use principal component analysis (PCA) to reduce the dimension of the matrix to reduce variable genes; cluster cells according to the graphical clustering method and use tSNE for two-dimensional visualization; test the average expression and percentage of expressing cells to identify genes with significant differential expression between clusters;
[0014] ③Use the R software package SingleR to automatically identify unbiased cell types of scRNA-seq data and cluster them into cell subpopulations; use confirmed cell marker genes to make the first distinction between cell subpopulations; use the Seurat software package to identify differentially expressed genes DEGs, and further screen out specific highly expressed genes for each type of cell subpopulation as molecular markers of hepatic parenchymal cells.
[0015] Preferably, in the method for screening molecular markers of hepatocyte subpopulations in the liver tissue of pearl grouper, the single-cell sequencing comprises the following steps: ① adding the single-cell suspension to the loading hole of the single-cell sequencing instrument in the corresponding order of the sample quantity; ② each cell and microparticle in the single-cell suspension will be mixed with gel beads containing barcode information in the instrument, and then wrapped by surfactant droplets in the system; ③ the gel beads will dissolve and release the barcode sequence when they are left in the reservoir, reverse transcribe the cDNA fragments, and mark the samples; ④ the gel beads have primers required for amplification, and each primer and each oil droplet has The unique marker is used to perform PCR amplification using cDNA as a template, and all the products are mixed to construct a standard sequencing library; ⑤ The cDNA is cut into fragments of about 200 to 300 bp using enzyme digestion, and sequencing adapter P5 and sequencing primer R1 are added, and finally PCR amplification is performed to obtain a DNA library; ⑥ The constructed library is subjected to high-throughput sequencing using the double-end sequencing mode of the Illumina sequencing platform. At the Read1 end, 16 bp of barcode information and 10 bp of UMI information are included; at the Read2 end, a cDNA fragment is included for reference genome comparison to determine the gene corresponding to the mRNA.
[0016] As a specific implementation method, in the above method for screening molecular markers of hepatocyte subpopulations in the liver tissue of pearl grouper, the liver tissue sample in the pearl grouper is extracted; the cells are separated and the steps of preparing a single cell suspension are as follows: ① First, the body surface of the grouper is wiped with 75% alcohol for disinfection, and the abdominal cavity of the grouper is opened with sterilized scissors and tweezers, and the liver is removed. ② The liver tissue sample is placed in physiological saline, washed three times with PBS, and then the liver tissue sample is cut into small pieces, washed three times with PBS, and then the cells are lysed with a cell lysis solution, and collected to prepare a single cell suspension.
[0017] The present invention also provides application of the method for screening molecular markers of hepatocyte subpopulations in the liver tissue of pearl grouper to identifying hepatocyte subpopulations of pearl grouper.
[0018] The present invention also provides application of the method for screening molecular markers of hepatocyte subpopulations in liver tissue of pearl grouper to studying nutritional metabolism of hepatocyte subpopulations of pearl grouper.
[0019] The present invention also provides a method for verifying the molecular markers of hepatocyte subpopulations in the liver tissue of pearl grouper, which is based on the above screening method, and the cell subpopulations with specific high expression genes are verified by counting and counting the proportion of cells through two-dimensional visualized tSNE maps and violins distribution maps. The biological functions of the cell subpopulations with specific molecular markers are further clarified by verification means, and the results of cell subpopulation classification are verified again by the expression of highly differential genes, which can be linked to the relevant signal pathways of nutritional metabolism and discover potential molecular mechanisms of action.
[0020] Compared with the prior art, the present invention has the following beneficial effects:
[0021] The present invention provides a method for screening specific molecular markers of hepatocyte subpopulations in the liver tissue of pearl grouper. The method uses scRNA-seq technology to draw a map of overall cell types in the liver tissue of pearl grouper to determine the specific cell types characterized by the relevant cell subpopulations, and further reveals the specificity of molecular markers of hepatocytes in the liver tissue of pearl grouper by locating and predicting the functions of specific molecules, locating the labeled cells by tSNE maps of highly differential genes, and counting and statistically verifying the proportion of cells occupied by violins distribution maps, so as to achieve the purpose of identifying cell subpopulations, and explore the potential molecular mechanisms of hepatocytes in the liver tissue of pearl grouper as the main functional cells of nutritional metabolism and signal pathways related to nutritional metabolism from the molecular transcription level, so as to provide a theoretical basis for the targeted regulation of nutritional metabolism of grouper.
[0022] The advantages of the present invention are:
[0023] (1) The present invention can accurately identify different cell subpopulations in the liver tissue of pearl grouper and screen out specific molecular markers. Unlike traditional sequencing methods, single-cell sequencing can detect heterogeneity between cells and perform high-throughput sequencing analysis of the genome, transcriptome, and epigenome at the single cell level, providing a more comprehensive, objective, and accurate method for finding new targets for targeted regulation of nutritional metabolism.
[0024] (2) The method for screening and verifying molecular markers of hepatocyte subpopulations in liver tissue in the present invention can be applied to the research of other tissues and other cell subpopulations, and has good promotion and application value. BRIEF DESCRIPTION OF THE DRAWINGS
[0025] Figure 1 This is a tSNE diagram showing the cell types detected in the liver tissue of pearl grouper by single-cell sequencing;
[0026] Figure 2 These are the annotated 9 cell subsets in the liver tissue of pearl grouper;
[0027] Figure 3 The bubble chart shows the categories of 9 cell subpopulations in the liver tissue of pearl grouper;
[0028] Figure 4 The violins map shows the potential specific molecular marker genes of hepatocytes in liver tissue;
[0029] Figure 5 The tSNE diagram shows the scatter plot of potential specific molecular markers of hepatocytes in liver tissue;
[0030] Figure 6 It is the result of validating the identification of 9 cell subpopulations in liver tissue by potential specific molecular markers. DETAILED DESCRIPTION
[0031] In order to better illustrate the purpose, technical scheme and advantages of the present invention, the present invention will be further described below in conjunction with specific drawings and embodiments. In the embodiments, the experimental methods used are conventional methods unless otherwise specified, and the materials, reagents, etc. used are all commercially available unless otherwise specified.
[0032] Example 1
[0033] 1. Extraction of Pearl Grouper Liver Tissue
[0034] (1) Use 75% alcohol to wipe the body surface of the grouper for disinfection, and use sterile scissors to cut open the abdominal cavity from the anus. After opening the abdominal cavity of the grouper, use sterile forceps and scissors to remove the liver.
[0035] (2) Place the liver tissue sample in physiological saline, wash it three times with 1× PBS, and cut the liver tissue sample into small pieces (1-2 mm 3 ), washed again with 1× PBS three times, and then lysed with cell lysis buffer, blown gently with a pipette, and collected to make a liver tissue single cell suspension.
[0036] 2. Single-cell sequencing analysis
[0037] (1) The single-cell sequencing instrument performs 10×genomics library construction. The single-cell suspension obtained in step 1 is added to the loading well of the single-cell sequencing instrument in the corresponding order of sample quantity.
[0038] (2) Each cell and particle in the single-cell suspension will be mixed with the gel beads containing barcode information in the instrument and then coated by the surfactant droplets in the system.
[0039] (3) The gel beads remaining in the reservoir will dissolve and release the barcode sequence, reverse transcribe the cDNA fragments, and label the samples.
[0040] (4) The gel beads contain primers required for amplification (primers are obtained by the bioinformatics company through special instruments before sequencing each cell), and each primer and each oil droplet has a unique label, and PCR amplification is performed using cDNA as a template. All products are mixed to construct a standard sequencing library.
[0041] (5) The cDNA is cut into fragments of about 200 to 300 bp using an enzyme digestion method, and then the sequencing adapter P5 and sequencing primer R1 are added to the traditional second-generation sequencing library construction process, and finally PCR amplification is performed to obtain a DNA library.
[0042] (6) The constructed library was sequenced using the paired-end sequencing mode of the Illumina sequencing platform. The Read1 end contains 16 bp of barcode information and 10 bp of UMI information for determining the cell and expression quantity; the Read2 end contains cDNA fragments for reference genome comparison to determine the gene corresponding to the mRNA.
[0043] 3. Data Analysis
[0044] (1) After high-throughput sequencing of all mRNAs in a single cell, the 10xGenomics official analysis software CellRanger was used to perform data quality statistics on the raw data and compare it to the reference genome (gene transcriptome of coioidea grouper); the CellRanger software pipeline provided by genomics was used to map the reads to the genome and transcriptome, and the R software package Seurat was used to process the unique molecular identifier (UMI) count matrix; CellRanger then filtered and corrected barcodes and UMIs, removed duplicates of the UMI corresponding to each geneid of each barcode, and calculated the number of uniqueUMIs as the expression level of the gene in the cell; after eliminating a certain proportion of low-quality cells, the filtered matrix was normalized in Seurat to obtain normalized counts for further quality control, analysis and data exploration. Finally, the proportions of effective high-quality cells retained were 95.6%, 96.2% and 96.6%, respectively.
[0045] (2) After retaining high-quality cells, the expression levels are further normalized. By default, the log normalization method is used to normalize the expression levels. This method divides the number of UMIs of each gene in each cell by the total number of UMIs, multiplies it by the scale factor (10000), and then takes the log value of the value. This method is expressed as:
[0046]
[0047] (3) Harmony was used to merge data and correct batch effects. First, PCA dimensionality reduction was performed on the merged data. Harmony used the soft k-means clustering algorithm to cluster the reduced-dimensional data, probabilistically assigning cells to clusters to maximize the diversity of the data set within each cluster. Cells were corrected to cluster toward the center until the clustering effect became stable. Seurat clustered cells using PCA, and each principal component represented a gene set with similar expression patterns. The nonlinear dimensionality reduction method t-SNE (t-distributed Stochastic Neighbor Embedding) was used to map high-dimensional cell data into a two-dimensional space, clustering cells with similar expression patterns together and separating cells with different expression patterns further apart, so as to more intuitively display the differences between cells.
[0048] (4) Use the R software package SingleR to automatically identify unbiased cell types of scRNA-seq data and cluster them into cell subpopulations; refer to the specific marker genes of hepatic parenchymal cells mentioned in relevant literature to make the first distinction of cell subpopulations; use the Seurat software package to identify differentially expressed genes (DEGs), and further screen out the specific highly expressed genes of each type of cell subpopulation as specific molecular markers of cell subpopulations, and use the two-dimensional visualization tSNE map to locate the labeled cells and the violins distribution map to verify the proportion of cells in the labeled cell subpopulation. Further clarify the biological functions of cell subpopulations with specific molecular markers, and re-verify the results of cell subpopulation classification through the expression of highly differential genes, which can be linked to the relevant signaling pathways of nutrient metabolism and discover potential molecular mechanisms of action.
[0049] The results showed that the identification markers of hepatocyte subpopulations in the liver tissue of pearl grouper were enriched in a variety of signal pathways related to nutritional metabolism. In addition to FGA and ITIH3, the specific molecular marker genes of hepatocyte subpopulations also included these verified potential specific marker genes (Apob, Erbb4, lrfn1l, Slc38a3, XDH and PIPOX). The tSNE map of highly differential genes was used to locate the labeled cells and the violins distribution map was used to count the proportion of cells. In addition, the differential gene pathways of hepatocyte subpopulations were enriched in genes related to nutritional metabolism signal pathways, such as carbohydrate metabolism, lipid metabolism and energy metabolism. In this way, the potential molecular marker genes of the 9 cell subpopulations were verified by tSNE maps and violins statistics, and displayed by bubble plot. It can be seen that the above specific molecular markers can be used as reference genes for hepatocytes in the liver tissue of pearl grouper. At the same time, we also identified a subpopulation of hepatocytes as the main functional cells for nutrient metabolism in liver tissue, which can be linked to relevant signal pathways of nutrient metabolism and discover potential molecular mechanisms of action.
[0050] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the essence and scope of the technical solution of the present invention.
Claims
1. A molecular marker of hepatocyte subpopulations in the liver tissue of pearl grouper, characterized in that: The molecular markers are FGA and ITIH3.
2. Application of the molecular markers described in claim 1 in studying the nutritional metabolism of pearl grouper.
3. A method for screening molecular markers of hepatocyte subpopulations in the liver tissue of pearl grouper, characterized in that: The method comprises the following steps: extracting tissue samples, isolating single cells and preparing cell suspensions, using single-cell RNA sequencing technology, obtaining sequencing data based on a 10×genomics sequencing platform, and performing bioinformatics analysis on the sequencing data; the steps of the bioinformatics analysis are as follows: ① After high-throughput sequencing of all mRNAs in a single cell, the software analyzes the expression patterns of all genes in the cell and reduces the expression matrix to important eigenvalues through a dimensionality reduction algorithm; the Cell Ranger software pipeline provided by Genomics is used to map the reads to the genome and transcriptome, and the unique molecular identifier UMI count matrix is processed using the R software package Seurat; after eliminating a certain proportion of low-quality cells, the filtered matrix is normalized in Seurat to obtain normalized counts; ②Use principal component analysis (PCA) to reduce the dimension of the matrix to reduce variable genes; cluster cells according to the graphical clustering method and use tSNE for two-dimensional visualization; test the average expression and percentage of expressing cells to identify genes with significant differential expression between clusters; ③Use the R software package SingleR to automatically identify unbiased cell types of scRNA-seq data and cluster them into cell subpopulations; use confirmed cell marker genes to make the first distinction between cell subpopulations; use the Seurat software package to identify differentially expressed genes DEGs, and further screen out specific highly expressed genes for each type of cell subpopulation as molecular markers of hepatic parenchymal cells.
4. The method for screening molecular markers of hepatocyte subpopulations in liver tissue of pearl grouper according to claim 3, characterized in that: The single-cell sequencing comprises the following steps: ① adding the single-cell suspension to the loading hole of the single-cell sequencing instrument in the corresponding order of the sample quantity; ② each cell and microparticle in the single-cell suspension will be mixed with the gel beads containing barcode information in the instrument, and then wrapped by the surfactant droplets in the system; ③ the gel beads will dissolve and release the barcode sequence in the reservoir, reverse transcribe the cDNA fragment, and mark the sample; ④ the gel beads have primers required for amplification, and each primer and each oil droplet have a unique label, PCR amplification is performed with cDNA as a template, all products are mixed, and a standard sequencing library is constructed; ⑤ the cDNA is cut into fragments of about 200 to 300 bp by enzyme digestion, and sequencing adapter P5 and sequencing primer R1 are added, and finally PCR amplification is performed to obtain a DNA library; ⑥ the constructed library is sequenced in high-throughput mode using the double-end sequencing mode of the Illumina sequencing platform, and at the Read1 end, 16 bp of barcode information and 10 bp of UMI information are included; at the Read2 end, the cDNA fragment is included, which is used to compare with the reference genome to determine the gene corresponding to the mRNA.
5. Application of the method according to any one of claims 3 or 4 in identifying hepatocyte subpopulations of pearl grouper.
6. Application of the method according to any one of claims 3 or 4 in studying the nutritional metabolism of hepatocyte subpopulations of pearl grouper.
7. A method for verifying molecular markers of hepatocyte subpopulations in the liver tissue of pearl grouper is based on the screening method described in any one of claims 3 or 4, and the cell subpopulations with specific high expression genes are verified by counting and counting the proportion of cells through two-dimensional visualized tSNE maps and violins distribution maps.