A method and system for evaluating the pluripotency of pluripotent stem cells

Abstract

The present invention relates to the field of stem cell technology, and specifically to a method and system for evaluating the pluripotency of pluripotent stem cells. The gene marker combination provided by the present invention can more comprehensively, accurately and objectively reflect the pluripotency of pluripotent stem cells. Through principal component analysis, the PCA results of the gene marker combination between different pluripotent stem cell samples have good correlation, high repeatability, high resolution, significant biological significance, and a very concentrated principal component space distribution, and have a low background in undifferentiated pluripotent stem cells. The pluripotency evaluation method of pluripotent stem cells established based on the gene marker combination evaluates the differentiation potential of pluripotent stem cells in a quantitative scoring manner. The method has good universality and is easy to standardize, providing an effective basis for cloning screening, characterization and quality control of pluripotent stem cells.

Description

Technical Field

[0001] The present invention relates to the field of stem cell technology, and in particular to a method and system for evaluating the pluripotency of pluripotent stem cells. Background Art

[0002] Pluripotent stem cells (PSC) are mainly represented by embryonic stem cells (ESC) and induced pluripotent stem cells (iPSC). Because of their ability to differentiate and develop into various tissues and organs, they have important application value in the fields of regenerative medicine and cell therapy. In practical applications, the pluripotency of PSC is a key factor affecting the quality and use of pluripotent stem cells. Therefore, the pluripotency evaluation method of PSC is of great significance for controlling the quality of PSC and functional cell differentiation.

[0003] Currently, the commonly used methods for evaluating PSC pluripotency mainly include the following:

[0004] (1) Teratoma detection: A certain number of human pluripotent stem cells (hPSCs) are injected into immunocompromised mice (usually injected into the hind limb muscles, testicles, groin or subcutaneous sites). 4-12 weeks after injection, the pluripotent stem cells will generate detectable teratomas. Teratomas contain tissues representing the three germ layers, and can be qualitatively analyzed by histological examination to confirm the presence of cells of the differentiation lineages of each germ layer, thereby qualitatively evaluating the pluripotency of PSCs. However, this method has a long detection cycle (4-12 weeks) and is prone to missing the detection window period, which in turn affects the progress of research and development and production; in addition, this method also has problems such as high detection costs and a large impact of experimental mouse heterogeneity on the experiment; in addition, this method has high requirements for experimental conditions and technicians, and any technical errors may affect the accuracy of the test results. Since teratomas are multi-lineage tumors containing multiple types of cells and tissues, a single sample may not be able to fully reflect the full picture of the tumor, resulting in deviations in the test results. In addition, differences in experimental mice may also cause experimental bias.

[0005] (2) Three-germ layer differentiation detection: Human embryonic stem cells (ES) and induced pluripotent stem cells (iPSC) have the potential to differentiate into three germ layers (endoderm, mesoderm and ectoderm). The three germ layer differentiation is carried out independently and simultaneously. Since the differentiation into different germ layers is carried out independently in different culture wells, after the differentiation is completed, the genes and markers of the corresponding germ layers can be detected by immunocytochemistry or RT-qPCR to determine the differentiation ability of PSC into the three germ layers. However, the differentiation ability of PSC is affected by culture conditions and different induction factors. At present, there are many kinds of three germ layer induction culture medium formulas and three germ layer differentiation kits on the market. Samples from different sources have large differences in the differentiation ability of each germ layer under different induction culture conditions, which makes this method difficult to standardize.

[0006] (3) Embryoid body (EB or EBs) formation detection: EB is a spherical structure formed by embryonic stem cells (ES) or induced pluripotent stem cells (iPSC) under certain culture conditions in vitro. It has three germ layers: the inner, middle and outer germ layers. Morphologically, it is very similar to the early embryonic development stage of mammals. Immunofluorescence, RT-qPCR and other methods are used to measure the three germ layer specific markers of differentiated EBs to evaluate the pluripotency of iPSCs and their differentiation ability to the inner, middle and outer germ layers, and then the pluripotency and differentiation potential of iPSCs can be evaluated. However, the use of immunofluorescence staining and RT-qPCR to detect the expression of specific markers usually only uses a small number or a few genes and markers for qualitative or semi-quantitative evaluation of the pluripotency of PSCs. It is difficult to comprehensively and accurately reflect the PSCs from different sources and the differentiated cells of multiple germ layers and multiple lineages after differentiation, and the detection method has a low throughput.

[0007] The existing PSC pluripotency evaluation methods all require multiple methods to jointly evaluate and characterize pluripotency. Therefore, there is still a need in the field for a comprehensive, stable, and standardized pluripotency evaluation method for pluripotent stem cells. Summary of the invention

[0008] The present invention provides a method and system for evaluating the pluripotency of pluripotent stem cells.

[0009] In order to solve the problems existing in the current evaluation methods of pluripotency of pluripotent stem cells, the present invention first screens the gene markers used to characterize the pluripotency of pluripotent stem cells. The present invention uses the Bulk RNA-seq method to perform transcriptome sequencing on pluripotent stem cells from multiple sources and multiple replicates and their differentiated embryoid bodies. Based on the analysis of the transcriptome data, a large number of early transcription genes of the three germ layers, their different combinations and their correlation with the pluripotency of pluripotent stem cells are screened, and a group of gene markers are obtained, which can more comprehensively and accurately reflect the pluripotency of pluripotent stem cells; through principal component analysis (PCA) and correlation analysis verification (Correlation), the PCA results of the above gene marker combination between different pluripotent stem cell samples have good repeatability, high resolution, significant biological significance, and very concentrated principal component spatial distribution. Some genes were verified by RT-qPCR method (Taqman probe method), and the results showed that RT-qPCR was highly correlated with the transcriptome sequencing results. Therefore, this group of gene markers is suitable as a marker for evaluating the pluripotency of pluripotent stem cells. The method has the advantages of high throughput, easy operation, strong universality, and easy standardization, and can more comprehensively evaluate the pluripotency of pluripotent stem cells. Specifically, the present invention provides the following technical solutions.

[0010] In a first aspect, the present invention provides a gene marker combination, wherein the gene marker combination includes one or more selected from four gene markers, wherein the four gene markers are stemness gene markers, ectoderm differentiation gene markers, mesoderm differentiation gene markers, and endoderm differentiation gene markers;

[0011] Wherein, the stemness gene markers include CNMD, CXCL5, DNMT3B, DPPA5, ESRG, HESX1, IDO1, LCK, LIN28A, NANOG, POU5F1, SOX2, TDGF1, TERT, TRIM22, USP44 and ZFP42;

[0012] The ectoderm differentiation gene markers include CDH9, COL2A1, DLK1, DMBX1, DMRT3, DRD4, EN1, FABP7, FGF5, GAD1, HES5, LHX2, LMX1A, MAP2, MEIS1, MYO3B, NCAM1, NES, NEUROD1, NOS2, NR2F1, NR2F2, OLFM3, OTX1, OTX2, PAPLN, PAX3, PAX6, POU4F1, RAX, SOX1, STMN4, TFAP2A, TFPI, TUBB3, WNT1 and ZBTB16;

[0013] The mesoderm differentiation gene markers include ABCA4, ALOX15, APLNR, BMP10, CD36, CDH5, CDX2, COLEC10, TNNT2, ESM1, FOXF1, HAND1, HAND2, HEY1, HOPX, HOXB7, HOXC8, IL10, IL6ST, ISL1, KDR, LHX1, MEOX1, MESP1, MESP2, MIXL1, MSGN1, MYH6, NKX2-5, ODAM, OSR1, PDGFRA, PLVAP, PPARG, RGS4, SNAI2, TAGLN, TBX3, TBX6, TDO2, TM4SF1 and TWIST1;

[0014] The endoderm differentiation gene markers include AFP, ALB, CABP7, CDH1, CDH2, CDH20, CER1, CLDN1, CPLX2, CXCR4, EOMES, FOXA1, FOXA2, FOXP2, GATA4, GATA5, GATA6, GREM2, GSC, HHEX, NGS2, HNF1A, HNF1B, HNF4a, KLF5, LEFTY2, MUC2, NODAL, PARP6, POU3F3, PRDM1, RXRG, SERHL2, SMAD2, SMAD3, SNAI1, SOX17, SOX7, SOX9, SST, VIL1 and WNT3.

[0015] The genes involved in the above gene marker combinations are all shown with their conventional names, and their sequence and other information can be obtained by querying public databases.

[0016] In the present invention, the gene marker combination is classified according to four dimensions: stemness, ectodermal differentiation potential, mesodermal differentiation potential and endoderm differentiation potential. In each dimension, a gene combination whose transcription level is highly correlated with the pluripotency of pluripotent stem cells is provided. By using these gene combinations, the differentiation potential of stem cells in each dimension of stemness, ectodermal differentiation, mesodermal differentiation and endoderm differentiation can be characterized by a limited number of genes.

[0017] Based on the need to evaluate the pluripotency of pluripotent stem cells, any one, two, three or a combination of four of the stemness gene markers, ectoderm differentiation gene markers, mesoderm differentiation gene markers and endoderm differentiation gene markers can be selected to evaluate the pluripotency of pluripotent stem cells from one or several dimensions of stemness, ectoderm differentiation potential, mesoderm differentiation potential and endoderm differentiation potential.

[0018] In order to comprehensively evaluate the pluripotency of pluripotent stem cells, the gene marker combination includes stemness gene markers, ectoderm differentiation gene markers, mesoderm differentiation gene markers and endoderm differentiation gene markers.

[0019] In a second aspect, the present invention provides use of the above-mentioned gene marker combination or a reagent for detecting the expression level of the gene marker combination in evaluating the pluripotency of pluripotent stem cells.

[0020] Preferably, the expression level is a transcription level. In the above application, the reagents used to detect the transcription level of the gene marker combination include reagents such as primers for the gene marker combination.

[0021] The above application includes the step of detecting the transcription level of the genes in the gene marker combination.

[0022] The above application also includes the step of evaluating the pluripotency of pluripotent stem cells based on the transcription levels of the genes in the gene marker combination or the data after the transcription levels are processed.

[0023] In a third aspect, the present invention provides a method for evaluating the pluripotency of pluripotent stem cells, wherein the method is to evaluate the pluripotency of pluripotent stem cells using the gene marker combination as a marker.

[0024] Based on the above-mentioned gene marker combination, the present invention provides a method for evaluating the pluripotency of pluripotent stem cells, which detects the transcription level of each gene in the above-mentioned gene marker combination of the pluripotent stem cell sample to be evaluated and the EB sample obtained by differentiation thereof, centralizes and standardizes the transcription level data FPKM, and finally takes the arithmetic mean of the standardized data of the gene markers in each dimension based on the four dimensions of stemness, ectoderm differentiation potential, mesoderm differentiation potential and endoderm differentiation potential, so as to quantitatively reflect the stemness, ectoderm differentiation potential, mesoderm differentiation potential and endoderm differentiation potential of pluripotent stem cells. Compared with the existing pluripotency evaluation method, this method has the advantages of short cycle, low detection cost, simple and easy detection means, high throughput, good repeatability, strong universality, easy standardization, and more comprehensive and accurate evaluation results.

[0025] Specifically, the evaluation method includes the following steps.

[0026] The pluripotent stem cell samples to be evaluated were divided into two groups. One group was differentiated for 6 to 10 days to obtain embryoid bodies, which were used as differentiation samples, and the other group was not treated and was used as undifferentiated samples.

[0027] Obtaining the transcription level data FPKM of the gene marker combination of the differentiated sample and the undifferentiated sample;

[0028] All the differentiated samples and undifferentiated samples to be analyzed are grouped into a group according to each gene in the gene marker combination for transcription level data centralization; the centralization is to calculate the N value of each sample, and the calculation formula of the N value is as follows: N=log2(FPKM+1);

[0029] The N values ​​of all the differentiated samples and undifferentiated samples to be analyzed are respectively grouped according to each gene in the gene marker combination for Z-Score standardization; the calculation formula of the Z-Score is as follows: Z-Score=(N-μ) / S; wherein, μ: the arithmetic mean of the N values ​​of all the differentiated samples and undifferentiated samples to be analyzed according to each gene as a group, S: the standard deviation of the N values ​​of all the differentiated samples and undifferentiated samples to be analyzed according to each gene as a group;

[0030] For each differentiated sample and undifferentiated sample to be analyzed, the stemness gene markers, ectoderm differentiation gene markers, mesoderm differentiation gene markers and endoderm differentiation gene markers in the gene marker combination are each taken as a group, and the arithmetic mean of the Z-Score of the gene marker combination corresponding to each sample in each group is calculated to obtain the pluripotency score.

[0031] Preferably, the pluripotency of the pluripotent stem cells to be evaluated is determined based on the magnitude of the pluripotency scores of the stemness gene markers of all undifferentiated samples to be analyzed, and the magnitude of the pluripotency scores of the ectoderm differentiation gene markers, mesoderm differentiation gene markers and / or endoderm differentiation gene markers of all differentiated samples to be analyzed;

[0032] Among them, the higher the pluripotency score of the stemness gene marker of the undifferentiated sample, the higher the pluripotency score of the ectoderm differentiation gene marker, mesoderm differentiation gene marker, and endoderm differentiation gene marker of the differentiated sample, the stronger the pluripotency of the pluripotent stem cells to be evaluated, and the higher the differentiation potential.

[0033] In the above method, the pluripotency of the pluripotent stem cells to be evaluated is judged according to the size of the pluripotency scores of all differentiated samples and undifferentiated samples to be analyzed; wherein, the higher the score of the stemness gene marker of the undifferentiated sample, the stronger the stemness, and the score can be used to quantitatively compare the stemness of different PSC samples. The higher the score of the ectoderm differentiation gene marker of the differentiated sample, the stronger the ectoderm differentiation ability, and the score can be used to quantitatively compare the strength of the ectoderm differentiation ability between each sample. The higher the score of the mesoderm differentiation gene marker of the differentiated sample, the stronger the mesoderm differentiation ability; the higher the score of the endoderm differentiation gene marker of the differentiated sample, the stronger the endoderm differentiation ability. Similarly, by analyzing the mesoderm differentiation gene marker or endoderm differentiation gene marker of the differentiated sample, the differentiation potential of any germ layer can be independently compared and quantified.

[0034] Preferably, the pluripotency scoring result can be characterized and evaluated in the form of a box plot, a heat map, a scoring table, etc.

[0035] In the above method, the pluripotent stem cells to be evaluated are differentiated into embryoid bodies and can be induced to differentiate by conventional methods. The undifferentiated sample is the pluripotent stem cell sample to be evaluated. The transcription level data after the treatment of the gene marker combination of the pluripotent stem cells to be evaluated and the EBs obtained by differentiation thereof are compared, and the pluripotency and differentiation potential of the pluripotent stem cells to be evaluated are judged according to the size of the pluripotency scores of the differentiated samples and the undifferentiated samples. In a specific embodiment of the present invention, the simplest EB formation medium is used to induce PSC to differentiate itself to reduce the influence of the induction factor on the EB differentiation potential.

[0036] In the above method, during the Z-Score calculation process, μ and S are calculated based on the set of all differentiated samples and undifferentiated samples, that is, μ and S are the arithmetic mean and standard deviation of the sum of all differentiated samples and undifferentiated samples.

[0037] In order to evaluate the reliability of the method for evaluating the pluripotency of pluripotent stem cells, the present invention uses a normalized heat map of gene expression, a sample-sample correlation heat map, and a principal component analysis method to test the reliability of the method for evaluating the pluripotency of pluripotent stem cells.

[0038] Among them, the evaluation method of the normalized heat map of gene expression is as follows: use each group of genes in the candidate gene combination list, center and standardize the scores of each gene corresponding to each sample as data, and perform unsupervised hierarchical clustering at the gene level.

[0039] The sample-sample correlation heatmap was evaluated as follows: each group of genes in the candidate gene combination list was used to perform unsupervised hierarchical clustering at the sample level, where the distance was defined as (1-r^2), where r is the correlation coefficient of the log_2 (FPKM+1) of the genes in the corresponding group.

[0040] Principal Component Analysis (PCA) is the most widely used data dimensionality reduction algorithm. This method converts n-dimensional variable features that may be correlated into k-dimensional linearly uncorrelated variable features through orthogonal transformation. The converted k-dimensional new orthogonal features are called principal components. The main principle of PCA analysis is to project high-dimensional data into a lower-dimensional space, reduce the dimension of the data while retaining the differences in the data as much as possible, efficiently find the main parts of the data, and reduce the dimensionality of the original complex data.

[0041] For the pluripotent stem cells to be evaluated, the above-mentioned hierarchical clustering, correlation analysis, and principal component analysis can evaluate the consistency of repeated samples, the differences between different samples, and reveal the relationship between samples.

[0042] In the above method, the transcription level data FPKM is obtained by Bulk RNA-seq. Using Bulk RNA-seq to obtain the transcription level data of each gene in the gene marker combination has the advantages of high detection throughput and large gene quantity, and can simultaneously obtain the transcription level data of all genes in the gene marker combination, avoiding the problems of poor comprehensiveness, poor universality, low detection flux, and low repeatability caused by only a few representative genes in the characterization of pluripotency by detection methods such as qPCR.

[0043] Based on the transcriptome data obtained by Bulk RNA-seq, Bulk RNA-seq was used for transcriptome level detection, and the sequencing data was quality controlled and filtered, compared with the reference genome, and the data was normalized to obtain the transcription level data FPKM of each gene.

[0044] In a fourth aspect, the present invention provides a system for evaluating the pluripotency of pluripotent stem cells, the system comprising:

[0045] (1) a data acquisition module, used to obtain the transcription level data FPKM of the gene marker combination of the differentiated sample and the undifferentiated sample;

[0046] Wherein, the gene marker combination is as described in the first aspect above;

[0047] The differentiated samples and the undifferentiated samples are: the pluripotent stem cell samples to be evaluated are divided into two groups, one of which is differentiated for 6 to 10 days to obtain embryoid bodies, which are used as differentiated samples, and the other group is not treated and is used as undifferentiated samples;

[0048] (2) An evaluation module, used to convert the transcription level data FPKM of the gene marker combination of the differentiated samples and the undifferentiated samples obtained by the data acquisition module into a pluripotency score;

[0049] The obtaining of the pluripotency score comprises the following steps:

[0050] All the differentiated samples and undifferentiated samples to be analyzed are grouped into a group according to each gene in the gene marker combination for transcription level data centralization; the centralization is to calculate the N value of each sample, and the calculation formula of the N value is as follows: N=log2(FPKM+1);

[0051] The N values ​​of all the differentiated samples and undifferentiated samples to be analyzed are respectively grouped according to each gene in the gene marker combination for Z-Score standardization; the calculation formula of the Z-Score is as follows: Z-Score=(N-μ) / S; wherein, μ: the arithmetic mean of the N values ​​of all the differentiated samples and undifferentiated samples to be analyzed according to each gene as a group, S: the standard deviation of the N values ​​of all the differentiated samples and undifferentiated samples to be analyzed according to each gene as a group;

[0052] For each differentiated sample and undifferentiated sample to be analyzed, the stemness gene markers, ectoderm differentiation gene markers, mesoderm differentiation gene markers, and endoderm differentiation gene markers in the gene marker combination are each taken as a group, and the arithmetic mean of the Z-Score of the gene marker combination corresponding to each sample in each group is calculated by grouping, which is the pluripotency score;

[0053] (3) An evaluation result output module, used to obtain the pluripotency score obtained by the evaluation module and output the evaluation result.

[0054] In the above-mentioned system, the basis for the evaluation result output module to output the evaluation result is:

[0055] The pluripotency of the pluripotent stem cells to be evaluated is determined according to the magnitude of the pluripotency scores of the stemness gene markers of all undifferentiated samples to be analyzed, and the magnitude of the pluripotency scores of the ectoderm differentiation gene markers, mesoderm differentiation gene markers and / or endoderm differentiation gene markers of all differentiated samples to be analyzed;

[0056] Among them, the higher the pluripotency score of the stemness gene marker of the undifferentiated sample, the higher the pluripotency score of the ectoderm differentiation gene marker, mesoderm differentiation gene marker, and endoderm differentiation gene marker of the differentiated sample, the stronger the pluripotency of the pluripotent stem cells to be evaluated, and the higher the differentiation potential.

[0057] In a fifth aspect, the present invention provides a computer device, comprising a memory and a processor, wherein the memory is used to store a program, and the processor implements the above-mentioned method for evaluating the pluripotency of pluripotent stem cells when executing the program.

[0058] In a sixth aspect, the present invention provides a computer-readable storage medium having a program stored thereon, and when the program is executed, the above-mentioned method for evaluating the pluripotency of pluripotent stem cells is implemented.

[0059] In a seventh aspect, the present invention provides use of the above-mentioned system, the computer device, or the computer-readable storage medium in evaluating the pluripotency of pluripotent stem cells.

[0060] The beneficial effects of the present invention include at least: the gene marker combination provided by the present invention can more comprehensively, accurately and objectively reflect the pluripotency of pluripotent stem cells. It is verified by principal component analysis (PCA) that the PCA results of the gene marker combination between different pluripotent stem cell samples have good correlation, high repeatability, high resolution, significant biological significance, and a very concentrated spatial distribution of the principal components, and have a low background in undifferentiated pluripotent stem cells. Based on the gene marker combination, the present invention provides a method for evaluating the pluripotency of pluripotent stem cells. The method obtains pluripotency scores in different dimensions of stemness, ectoderm differentiation potential, mesoderm differentiation potential and endoderm differentiation potential by centralizing and standardizing the transcription level data of the gene marker combination, and uses a variety of stemness genes and early genes for three germ layer differentiation to evaluate pluripotency, avoiding the one-sidedness and subjective judgment of the evaluation caused by using a few genes as markers, and can objectively and accurately evaluate the differentiation potential of pluripotent stem cell samples, with wider applicability; and the evaluation results of the method evaluate pluripotency and differentiation potential in a quantitative scoring manner, and the evaluation method is more scientific and simple, which can provide an effective basis for the cloning screening, characterization and quality control of pluripotent stem cells. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0062] Figure 1 , Figure 2 , Figure 3 Group 1 is a list of all genes not screened in Example 2 of the present invention: normalized expression heat map of stemness genes, sample-sample correlation heat map and PCA result map; wherein, Figure 1 is the normalized heat map of stemness gene expression, Figure 2 is the sample-sample correlation heat map, Figure 3 This is the PCA result graph.

[0063] Figure 4 , Figure 5 , Figure 6 Group 2 is a list of all genes not screened in Example 2 of the present invention: normalized heat map of expression of genes related to early ectoderm differentiation, heat map of sample-sample correlation and PCA result map; wherein, Figure 4 is the normalized heat map of stemness gene expression, Figure 5 is the sample-sample correlation heat map, Figure 6 This is the PCA result graph.

[0064] Figure 7 , Figure 8 , Fig. 9 Group 3 is a list of all genes not screened in Example 2 of the present invention: normalized heat map of expression of genes related to early mesoderm differentiation, heat map of sample-sample correlation and PCA result map; wherein, Figure 7 is the normalized heat map of stemness gene expression, Figure 8 is the sample-sample correlation heat map, Fig. 9 This is the PCA result graph.

[0065] Fig.10 , Fig.11 , Fig.12 Group 4 is a list of all genes not screened in Example 2 of the present invention: normalized heat map of expression of genes related to early endoderm differentiation, heat map of sample-sample correlation and PCA result map; wherein, Fig.10 is the normalized heat map of stemness gene expression, Fig.11 is the sample-sample correlation heat map, Fig.12 This is the PCA result graph.

[0066] Fig.13 , Fig.14 , Fig.15 Group 1 is a list of all genes screened and determined in Example 2 of the present invention: normalized heat map of stemness gene expression, sample-sample correlation heat map and PCA result map; wherein, Fig.13 is the normalized heat map of stemness gene expression, Fig.14 is the sample-sample correlation heat map, Fig.15 This is the PCA result graph.

[0067] Fig.16 , Fig.17 , Fig.18 Group 2 is a list of all genes screened and determined in Example 2 of the present invention: normalized heat map of expression of genes related to early ectoderm differentiation, heat map of sample-sample correlation, and PCA result map; wherein, Fig.16 is the normalized heat map of stemness gene expression, Fig.17 is the sample-sample correlation heat map, Fig.18 This is the PCA result graph.

[0068] Fig.19 , Fig. 20 , Fig.21 Group 3 is a list of all genes screened and determined in Example 2 of the present invention: normalized expression heat map, sample-sample correlation heat map and PCA result map of genes related to early mesoderm differentiation; wherein, Fig.19 is the normalized heat map of stemness gene expression, Fig. 20 is the sample-sample correlation heat map, Fig.21This is the PCA result graph.

[0069] Fig. 22 , Fig.23 , Fig.24 Group 4 is a list of all genes screened and determined in Example 2 of the present invention: normalized heat map of expression of genes related to early endoderm differentiation, heat map of sample-sample correlation and PCA result map; wherein, Fig. 22 is the normalized heat map of stemness gene expression, Fig.23 is the sample-sample correlation heat map, Fig.24 This is the PCA result graph.

[0070] Fig.25 This is a pluripotency scoring table for pluripotent stem cell samples from various sources in Example 4 of the present invention.

[0071] Fig.26 This is a heat map of the three germ layer differentiation tendencies of pluripotent stem cell samples from various sources in Example 4 of the present invention.

[0072] Fig. 27 This is a box plot of the pluripotency scores of pluripotent stem cell samples from various sources in Example 4 of the present invention.

[0073] Fig.28 This is a box plot of the pluripotency scores of pluripotent stem cell samples from various sources in Example 5 of the present invention.

[0074] Fig.29 , Fig.30 This is the fitting verification of the RT-qPCR results of 2 hiPSC samples of different generations, 2 HYS0103-iPSC samples of the same generation, and 2 BC-BiPSC samples of the same generation in Example 7 of the present invention.

[0075] Figures 1 to 24 A in the middle is H1 P79 (P79 generation of H1 cells) undifferentiated cells; A1, A2, A3 are three replicates of EBs differentiated from H1 P79 for 7 days; B is hiPSC P15 (P15 generation of hiPSC cells) undifferentiated cells; B1, B2, B3 are three replicates of EBs differentiated from hiPSC P15 for 7 days; C is BC-BiPSC P25 undifferentiated cells; C1, C2, C3 are three replicates of EBs differentiated from BC-BiPSC P25 (P25 generation of BC-BiPSC) for 7 days; D is HYS0103-iPSC P28 (P28 generation of HYS0103-iPSC) undifferentiated cells; D1, D2, D3 are three replicates of EBs differentiated from HYS0103-iPSC P28 for 7 days. DETAILED DESCRIPTION

[0076] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0077] The sources of reagents and raw materials used in the following examples are described as follows:

[0078] hiPSC (human induced pluripotent stem cells) were prepared by the applicant using Sendai virus (SEV) to reprogram mononuclear peripheral blood mononuclear cells (PBMC). HYS0103-iPSC (human induced pluripotent stem cells) were purchased from ATCC. H1 (hESC human embryonic stem cells) were from Tsinghua University (gift), and the H1 cell line was disclosed in the following literature: Hu BY, Weick JP, YuJ, Ma LX, Zhang XQ, Thomson JA, Zhang SC. Neural differentiation of humaninduced pluripotent stem cells follows developmental principles but with variable potency. Proc Natl Acad Sci US A. 2010 Mar 2;107(9):4335-40. doi:10.1073 / pnas.0910012107. Epub 2010 Feb 16. PMID: 20160098; PMCID: PMC2840097. BC-BiPSC (human induced pluripotent stem cells) were purchased from Cellapy.

[0079] DMEM / F12 (with GlutaMAX), MEM (NEAA), 2-Mercaptoethanol, and KnockOut Serum Replacement were purchased from Gibco.

[0080] Y-27632 dihydrochloride was purchased from STEMCELL, TryPLE Select was purchased from Thermo Fisher, Elplasia culture plates were purchased from CORNING, iScript cDNA Synthesis Kit was purchased from BIO-RAD, and TaqMan™ FastAdvanced master mix was purchased from Thermo Fisher.

[0081] Example 1 EB differentiation and culture

[0082] Preparation of EB differentiation medium: Take 79μL of DMEM / F12 (containing GlutaMAX), add 20μL of KnockOut SerumReplacement, 1mL of MEM (NEAA), and 100μL of 2-Mercaptoethanol, and mix well to prepare EB differentiation medium.

[0083] The cells were expanded using conventional PSC culture techniques, digested into single cells using TryPLE Select digestion solution, centrifuged and resuspended in EB differentiation medium, and cultured at 1.5 × 10 6 cells / well were inoculated in Elplasia culture plates, the final volume of the culture medium was 3 mL, and Y-27632 dihydrochloride was added to a final concentration of 10 μM. The EB differentiation medium was changed every day, and Y-27632 dihydrochloride was no longer added from the second day. The EBs were harvested on the 7th day of culture to obtain EB differentiation samples.

[0084] Example 2 Screening and optimization of gene marker combinations

[0085] Bulk RNA-seq method was used to sequence transcriptomes of pluripotent stem cells from multiple sources and multiple replicates and their differentiated embryoid bodies. Based on the analysis of transcriptome data, a large number of early transcribed genes of the three germ layers, their different combinations and their correlation with the pluripotency of pluripotent stem cells were screened. All candidate genes that were not screened are shown in Table 1.

[0086] Table 1 List of all candidate genes without screening

[0087]

[0088] In the present invention, cluster analysis (gene expression normalization heat map, sample-sample correlation heat map) and PCA analysis (principal component analysis) are mainly used for candidate gene screening. The specific method is described as follows.

[0089] Normalized heat map of gene expression: Use each group of genes in the candidate gene list, center and standardize the scores of each gene corresponding to each sample as data, and perform unsupervised hierarchical clustering at the gene level.

[0090] Sample-sample correlation heatmap. Unsupervised hierarchical clustering was performed at the sample level using each group of genes in the candidate gene list, where the distance was defined as (1-r^2), where r is the correlation coefficient of the log2 (FPKM+1) of the genes in the corresponding group.

[0091] PCA is the most widely used data dimensionality reduction algorithm. This method converts n-dimensional variable features that may be correlated into k-dimensional linearly uncorrelated variable features through orthogonal transformation. The converted k-dimensional new orthogonal features are called principal components. The main principle of PCA analysis is to project high-dimensional data into a lower-dimensional space, reduce the dimension of the data while retaining the differences in the data as much as possible, efficiently find the main parts of the data, and reduce the dimensionality of the original complex data.

[0092] The present invention provides a large number of genes related to PSC maintenance of stemness and early three-germ layer differentiation, reduces the influence of a small number of genes on the gene expression bias of the differentiation process of different cell lines on the detection results, increases the repeatability of the experiment, improves the resolution of detection differences, and increases the compactness of sample principal component analysis.

[0093] In the present invention, by screening the genes related to the maintenance of stemness of pluripotent stem cells and the early differentiation of the three germ layers of EB after differentiation, some genes expressed in both PSC and EB are excluded, such as ectoderm SDC2, mesoderm early differentiation gene CD8A and endoderm LEFTY1, which are highly expressed in ESC and iPSC, and the background of the undifferentiated PSC three germ layers early differentiation gene map is reduced, and the specificity of the genes after differentiation and the sensitivity of the standardized score are improved. The preferred gene list can objectively evaluate PSC samples from different sources and PSC (hESC and iPSC) samples with different differentiation gene lineages.

[0094] Based on the above results, the present invention finally obtained a group of gene markers, which consisted of the genes shown in Table 2.

[0095] Table 2 List of PSC pluripotency scoring gene markers identified by screening

[0096]

[0097] The normalized expression heatmaps, correlations, and PCA results of each gene in Tables 1 and 2 are shown in Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 , Figure 6 , Figure 7 , Figure 8 , Fig. 9 , Fig.10 , Fig.11 , Fig.12 , Fig.13 , Fig.14 , Fig.15 , Fig.16 , Fig.17 , Fig.18 , Fig.19 , Fig. 20 , Fig.21 , Fig. 22 , Fig.23 , Fig.24 As shown. The results show that based on a large number of ectoderm, mesoderm, endoderm early differentiation-related genes and stemness gene combinations, the bulk RNA-seq data of PSCs from different sources and their corresponding differentiated EBs can be analyzed, which can cover PSCs from different sources, hESCs and iPSCs of different differentiation lineages, and has higher universality. By screening the candidate gene list and removing the background, the gene marker combination in Table 2 was verified by principal component analysis (PCA) and correlation analysis. The PCA results between different pluripotent stem cell samples have good repeatability, high resolution, compact clustering between the same repeated samples, and a certain sensitivity to distinguish between samples with small differences, which can more comprehensively and accurately reflect the pluripotency and differentiation potential of pluripotent stem cells.

[0098] Example 3 Method for Scoring the Pluripotency of Pluripotent Stem Cells

[0099] This embodiment provides a method for evaluating the pluripotency of pluripotent stem cells. The method uses the gene marker combination shown in Table 2 as a marker to evaluate the pluripotency, and specifically includes the following steps:

[0100] (1) The pluripotent stem cell samples to be evaluated were divided into two groups, one of which was PSCs that had not been differentiated as undifferentiated samples, and the other was embryoid bodies (EBs) obtained after 7 days of differentiation as differentiated samples.

[0101] (2) Total RNA extraction (Trizol method), quality inspection, bulk transcriptome library construction, and bulk RNA-seq sequencing were performed on the undifferentiated samples and their corresponding differentiated samples. The sequencing data were filtered for quality control, compared with the reference genome (hg38), and normalized to obtain the transcription level data FPKM of the gene marker combination shown in Table 2.

[0102] (3) The FPKM of all samples (differentiated samples and undifferentiated samples) are centrally analyzed at the transcriptional level for each gene in the gene marker combination; centralization is to calculate the N value of the FPKM of each gene in the gene combination for each sample. The calculation formula of the N value is as follows: N = log2(FPKM + 1).

[0103] (4) The N values ​​of all samples obtained in step (3) are Z-Score standardized according to each gene in the gene marker combination as a group; the calculation formula of Z-Score is as follows: Z-Score = (N-μ) / S; where μ is the arithmetic mean of the N values ​​of all samples (including differentiated and undifferentiated samples) according to each gene as a group, and S is the standard deviation of the N values ​​of all samples (including differentiated and undifferentiated samples) according to each gene as a group.

[0104] (5) Each sample was grouped into a group with the stemness gene marker, ectoderm differentiation gene marker, mesoderm differentiation gene marker, and endoderm differentiation gene marker in the gene marker combination. The arithmetic mean of the Z-score of all gene markers in each group was calculated to obtain the pluripotency score.

[0105] (6) The higher the pluripotency score obtained from the stemness gene markers of the undifferentiated PSC sample, the stronger the stemness. The score can be used to quantitatively compare the stemness of different PSC samples. The higher the pluripotency score obtained from the ectoderm early differentiation gene markers of the differentiated cell sample, the stronger the ectoderm differentiation ability. The score can be used to quantitatively compare the ectoderm differentiation ability of each sample. Similarly, by analyzing the pluripotency score of the mesoderm or endoderm early differentiation gene markers of each sample, the differentiation potential of any germ layer can be independently compared and quantified.

[0106] Example 4 Evaluation of pluripotency of PSCs from different sources

[0107] The pluripotency evaluation method of pluripotent stem cells provided in the above Example 3 was used to evaluate the pluripotency of different pluripotent stem cell samples, including: hiPSC (human induced pluripotent stem cells), HYS0103-iPSC (human induced pluripotent stem cells), H1 (hESC human embryonic stem cells), BC-BiPSC (human induced pluripotent stem cells).

[0108] The pluripotency scores of pluripotent stem cell samples from various sources were plotted into a scoring table using Excel. The results are shown in the figure below. Fig.25 As shown. The results show that the stemness of each undifferentiated PSC is compared by the pluripotency score of the stemness gene marker combination of each PSC sample from different sources. The stemness score of each EB differentiation sample decreases to varying degrees, which is consistent with the logic of pluripotent stem cell differentiation. The score of the undifferentiated PSC in the early stage of ectoderm differentiation, mesoderm differentiation, and endoderm differentiation is low, and the background of each gene marker combination score in undifferentiated PSC is low. The score of the gene marker combination related to the early differentiation of each germ layer represents the ability of different samples in the differentiation of each germ layer.

[0109] Graphpad prism8 software was used to plot the pluripotency scores of pluripotent stem cell samples from various sources as a heat map of the three germ layer differentiation tendency of pluripotent stem cells and a box plot of the pluripotency score. The results are shown in Fig.26 , Fig. 27 As shown, the pluripotency of each PSC and the differentiation potential of different germ layers can be more intuitively displayed and evaluated.

[0110] The results showed that H1 samples received a high score in terms of ectodermal differentiation lineages, indicating that H1 samples may be a good choice for ectodermal research or differentiation. The embryonic stem cell H1 cell line is also currently recognized as a cell line with high ectodermal differentiation potential. Hu et al. (Hu BY, Weick JP, Yu J, Ma LX, Zhang XQ, Thomson JA, Zhang SC. Neural differentiation of human induced pluripotent stem cells follows developmental principles but with variable potency. Proc Natl AcadSci US A. 2010 Mar 2;107(9):4335-40. doi: 10.1073 / pnas.0910012107. Epub 2010Feb 16. PMID: 20160098; PMCID: PMC2840097.) published multiple reports on the differentiation of PSC cell lines into ectodermal motor neurons, and H1 did perform well.

[0111] Example 5

[0112] The pluripotency evaluation method of pluripotent stem cells provided in Example 3 was used to evaluate the cell samples of HYS0103-iPSC (human induced pluripotent stem cells) and BC-BiPSC (human induced pluripotent stem cells) of the same passage in Example 4. The experimental process was repeated with the same samples and the same passage to evaluate the experimental results.

[0113] The hiPSC (human induced pluripotent stem cell) cell samples of different passages (P10, P15) in the above Example 4 were evaluated using the pluripotency evaluation method of pluripotent stem cells provided in the above Example 3.

[0114] Graphpad prism8 software was used to draw a pluripotency score box plot of pluripotency scores of pluripotent stem cell samples from various sources, as shown in Fig.28As shown, the results show that: 1) The cell samples of HYS0103-iPSC (human induced pluripotent stem cells) and BC-BiPSC (human induced pluripotent stem cells) of the same generation in the above Example 4 were evaluated, and the experimental process was repeated with the same samples and the same generation. The evaluation results were consistent and the repeatability was good. 2) The cell samples of hiPSC (human induced pluripotent stem cells) of different generations (P10, P15) in the above Example 4 were evaluated. The ectoderm differentiation score decreased with the increase of the generation, and the ectoderm differentiation ability decreased significantly, indicating that the evaluation method of the present invention has good sensitivity to variation.

[0115] Example 6

[0116] This example uses RT-qPCR to verify some genes of each gene marker combination for pluripotency evaluation in the present invention (stem genes, ectoderm differentiation genes, mesoderm differentiation genes, and endoderm differentiation genes as shown in Table 2). The specific method is as follows:

[0117] Two genes in each gene marker combination were selected to verify the bulk RNA-seq data: stemness genes: OCT4 (POU5F1), NANOG, ectoderm early differentiation-related genes: PAX6, NES, mesoderm early differentiation-related genes: MIXL1, NCAM, endoderm early differentiation-related genes: SOX17, FOXA2, and the housekeeping gene is GAPDH.

[0118] The Fam-MGB second-generation probe was used for each target gene, and the HEX-MGB second-generation probe was used to combine with GAPDH to conduct experiments in a dual probe system.

[0119] The total RNA extracted from the transcriptome sequencing of hiPSC samples of two different generations in Example 3 and Example 4 was reverse transcribed using the iScript cDNA Synthesis Kit.

[0120] Taqman Fast Advanced Master Mix (Thermo Fisher) reagent was used to amplify and quantify each gene, and the Ct value of each gene corresponding to each sample was obtained.

[0121] The quantitative results were calculated according to 2 -△Ct The specific method is as follows:

[0122] The average Ct value of the target gene to be calculated for each sample is subtracted from the average Ct value of the internal reference gene itself, and then substituted into 2 -△Ct Formula to operate.

[0123] The calculated 2 -△CtThe values ​​were fitted with Bulk RNA-seq FPKM, and the correlation coefficient R was calculated using the RSQ function of EXCEL 2 .

[0124] Calculate the FPKM value of bulk RNA-seq and the 2 of RT-qPCR at two different passages (P10 and P15) of hiPSC (human induced pluripotent stem cells) -△Ct The results showed that (Table 3) the correlations of the tested stemness and three germ layer differentiation-related genes, except NESTIN, were all >70% for PAX6, NCAM1, MIXL1, SOX17, FOXA2, OCT4, and NANOG, indicating that the bulk RNA-seq sequencing results were highly correlated with RT-qPCR.

[0125] Table 3

[0126]

[0127] Example 7

[0128] This example uses the RT-qPCR method in Example 6 to verify the scoring results of the pluripotency evaluation method of the present invention.

[0129] The RT-qPCR method in Example 6 was used to perform RT-qPCR amplification and quantification on two different passages (P10, P15) of hiPSC (human induced pluripotent stem cells) samples in Examples 3 and 4, two HYS0103-iPSC samples of the same passage, and two BC-BiPSC samples of the same passage.

[0130] The quantitative results were analyzed using the Livak method (2 -△△Ct ) for normalized analysis, the specific method is as follows:

[0131] Calculate the average Ct value of each gene in each sample minus the average Ct value of the internal reference gene, and then subtract the △Ct of the undifferentiated PSC from the △Ct of the differentiated EB sample corresponding to each sample to obtain the △△Ct, and then substitute it into 2 -△△Ct Formula to operate.

[0132] Two hiPSC samples of different generations, two HYS0103-iPSC samples of the same generation, and two BC-BiPSC samples of the same generation were subjected to RT-qPCR amplification and quantitative normalization results (as shown in Tables 4, 5, and 6). Each sample was used as a group of two experiments to fit the regression curve using EXCEL. The results are shown in Fig.29 , Fig.30The results show that: 1) The correlation coefficients of the RT-qPCR quantitative normalization results of two repeated experiments of HYS0103-iPSC samples of the same generation and two BC-BiPSC samples of the same generation are: HYS0103-iPSC sample correlation coefficient R 2 The correlation coefficient of BC-BiPSC samples was 0.8116. 2 The correlation coefficient is 0.9094, which is high, indicating that the test results of the two samples are consistent with the scoring results of the pluripotency evaluation method of the present invention. 2) The relative expression of PAX6 in the two RT-qPCR quantitative normalization results of hiPSC samples of different generations has obvious changes. The correlation coefficient R 2 The correlation is 0.2356, which is low. If the results of the two experiments after removing the PAX6 gene, the fitting curves have good correlation (R 2 The score of the pluripotency evaluation method of the present invention is consistent with the score of the stemness, mesoderm differentiation and endoderm differentiation.

[0133] Table 4

[0134]

[0135] Table 5

[0136]

[0137] Table 6

[0138]

[0139] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating the pluripotency of pluripotent stem cells, characterized in that: The method is to evaluate the pluripotency of pluripotent stem cells using a combination of gene markers as markers; The gene marker combination is one or more selected from three gene marker combinations, wherein the three gene marker combinations are a stemness gene marker combination, an ectoderm differentiation gene marker combination, and a mesoderm differentiation gene marker combination; Wherein, the stemness gene marker combination is CNMD, CXCL5, DNMT3B, DPPA5, ESRG, HESX1, IDO1, LCK, LIN28A, NANOG, POU5F1, SOX2, TDGF1, TERT, TRIM22, USP44 and ZFP42; The ectoderm differentiation gene marker combination is CDH9, COL2A1, DLK1, DMBX1, DMRT3, DRD4, EN1, FABP7, FGF5, GAD1, HES5, LHX2, LMX1A, MAP2, MEIS1, MYO3B, NCAM1, NES, NEUROD1, NOS2, NR2F1, NR2F2, OLFM3, OTX1, OTX2, PAPLN, PAX3, PAX6, POU4F1, RAX, SOX1, STMN4, TFAP2A, TFPI, TUBB3, WNT1 and ZBTB16; The mesoderm differentiation gene marker combination is ABCA4, ALOX15, APLNR, BMP10, CD36, CDH5, CDX2, COLEC10, TNNT2, ESM1, FOXF1, HAND1, HAND2, HEY1, HOPX, HOXB7, HOXC8, IL10, IL6ST, ISL1, KDR, LHX1, MEOX1, MESP1, MESP2, MIXL1, MSGN1, MYH6, NKX2-5, ODAM, OSR1, PDGFRA, PLVAP, PPARG, RGS4, SNAI2, TAGLN, TBX3, TBX6, TDO2, TM4SF1 and TWIST1; The method comprises: The pluripotent stem cell samples to be evaluated were divided into two groups. One group was differentiated for 6 to 10 days to obtain embryoid bodies, which were used as differentiation samples, and the other group was not treated and was used as undifferentiated samples. Obtaining the transcription level data FPKM of the gene marker combination of the differentiated sample and the undifferentiated sample; All the differentiated samples and undifferentiated samples to be analyzed are grouped into a group according to each gene in the gene marker combination for transcription level data centralization; the centralization is to calculate the N value of each sample, and the calculation formula of the N value is as follows: N=log2(FPKM+1); The N values ​​of all the differentiated samples and undifferentiated samples to be analyzed are respectively grouped according to each gene in the gene marker combination for Z-Score normalization; the calculation formula of the Z-Score is as follows: Z-Score=(N-μ) / S; wherein, μ: the arithmetic mean of the N values ​​of all the differentiated samples and undifferentiated samples to be analyzed according to each gene as a group, S: the standard deviation of the N values ​​of all the differentiated samples and undifferentiated samples to be analyzed according to each gene as a group; For each differentiated sample and undifferentiated sample to be analyzed, the stemness gene marker combination, ectoderm differentiation gene marker combination and mesoderm differentiation gene marker combination in the gene marker combination are each taken as a group, and the arithmetic mean of the Z-Score of the gene marker combination corresponding to each sample in each group is calculated to obtain the pluripotency score.

2. The method for evaluating the pluripotency of pluripotent stem cells according to claim 1, characterized in that: Judging the pluripotency of the pluripotent stem cells to be evaluated according to the magnitude of the pluripotency scores of the stemness gene marker combination of all undifferentiated samples to be analyzed, and the magnitude of the pluripotency scores of the ectoderm differentiation gene marker combination and / or the mesoderm differentiation gene marker combination of all differentiated samples to be analyzed; Among them, the higher the pluripotency score of the stemness gene marker combination of the undifferentiated sample, the higher the pluripotency score of the ectoderm differentiation gene marker combination and the mesoderm differentiation gene marker combination of the differentiated sample, the stronger the pluripotency of the pluripotent stem cells to be evaluated, and the higher the differentiation potential.

3. The method for evaluating the pluripotency of pluripotent stem cells according to claim 1 or 2, characterized in that: The transcription level data FPKM was obtained by Bulk RNA-seq.

4. A system for evaluating the pluripotency of pluripotent stem cells, characterized in that: The system comprises: (1) a data acquisition module, used to obtain the transcription level data FPKM of the gene marker combination of the differentiated sample and the undifferentiated sample; Wherein, the gene marker combination is as described in claim 1; The differentiated samples and the undifferentiated samples are: the pluripotent stem cell samples to be evaluated are divided into two groups, one of which is differentiated for 6 to 10 days to obtain embryoid bodies, which are used as differentiated samples, and the other group is not treated and is used as undifferentiated samples; (2) An evaluation module, used to convert the transcription level data FPKM of the gene marker combination of the differentiated samples and the undifferentiated samples obtained by the data acquisition module into a pluripotency score; The obtaining of the pluripotency score comprises the following steps: All the differentiated samples and undifferentiated samples to be analyzed are grouped into a group according to each gene in the gene marker combination for transcription level data centralization; the centralization is to calculate the N value of each sample, and the calculation formula of the N value is as follows: N=log2(FPKM+1); The N values ​​of all the differentiated samples and undifferentiated samples to be analyzed are respectively grouped according to each gene in the gene marker combination for Z-Score standardization; the calculation formula of the Z-Score is as follows: Z-Score=(N-μ) / S; wherein, μ: the arithmetic mean of the N values ​​of all the differentiated samples and undifferentiated samples to be analyzed according to each gene as a group, S: the standard deviation of the N values ​​of all the differentiated samples and undifferentiated samples to be analyzed according to each gene as a group; For each differentiated sample and undifferentiated sample to be analyzed, the stemness gene marker combination, ectoderm differentiation gene marker combination, and mesoderm differentiation gene marker combination in the gene marker combination are each taken as a group, and the arithmetic mean of the Z-Score of the gene marker combination corresponding to each sample in each group is calculated, which is the pluripotency score; (3) An evaluation result output module, used to obtain the pluripotency score obtained by the evaluation module and output the evaluation result.

5. The system for evaluating pluripotency of pluripotent stem cells according to claim 4, characterized in that: The evaluation result output module outputs the evaluation result based on: judging the pluripotency of the pluripotent stem cells to be evaluated according to the size of the pluripotency score of the stemness gene marker combination of all undifferentiated samples to be analyzed, and the size of the pluripotency score of the ectoderm differentiation gene marker combination and / or the mesoderm differentiation gene marker combination of all differentiated samples to be analyzed; Among them, the higher the pluripotency score of the stemness gene marker combination of the undifferentiated sample, the higher the pluripotency score of the ectoderm differentiation gene marker combination and the mesoderm differentiation gene marker combination of the differentiated sample, the stronger the pluripotency of the pluripotent stem cells to be evaluated, and the higher the differentiation potential.

6. A computer device, characterized in that: The computer device includes a memory and a processor, the memory is used to store a program, and the processor implements the method for evaluating the pluripotency of pluripotent stem cells according to any one of claims 1 to 3 when executing the program.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program, and when the program is executed, the method for evaluating the pluripotency of pluripotent stem cells according to any one of claims 1 to 3 is implemented.

8. Use of the system according to claim 4 or 5, the computer device according to claim 6, or the computer-readable storage medium according to claim 7 in evaluating the pluripotency of pluripotent stem cells.

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