CN-121983134-A - Cell fate determination factor identification method and related device

CN121983134ACN 121983134 ACN121983134 ACN 121983134ACN-121983134-A

Abstract

The invention relates to a cell fate decision factor identification method and a related device, belonging to the technical field of bioinformatics, wherein the cell fate decision factor identification method comprises the steps of determining the expression quantity of transcription factors and target genes in single cell transcriptome sequencing data in cells, constructing a cell lineage, constructing a gene regulation model based on the relation between the expression quantity of each transcription factor in each cell cluster in the cell lineage and the expression quantity of each target gene in the cells, constructing a target function based on the precision of the gene regulation model of each cell cluster, the sparsity of the gene regulation model of each cell cluster and the similarity of the gene regulation model among adjacent cell clusters, determining the regulation coefficient of each cell cluster for the target genes based on the target function, determining differential transcription factors among the adjacent cell clusters based on the regulation coefficients, and determining the cell fate decision factors based on the differential transcription factors. The invention can accurately identify cell fate determinants.

Inventors

SHI MING
GAN HAITAO
ZHOU RAN
YANG ZHI
WANG HONGQIANG
HUANG ZHONGWEI
LIU CHUNTING

Assignees

湖北工业大学

Dates

Publication Date: 20260505
Application Date: 20251231

Claims (10)

1. A method for identifying a cell fate determinant, comprising: Determining the expression level of transcription factors and target genes in cells in single-cell transcriptome sequencing data, and constructing cell lineages based on the single-cell transcriptome sequencing data; constructing a gene regulation model based on the relation between the expression amount of each transcription factor in each cell cluster in the cell lineage and the expression amount of each target gene in the cell; Constructing an objective function with the purposes that the precision of the gene regulation model of each cell cluster is within a preset precision range, the sparsity of the gene regulation model of each cell cluster is within a preset sparsity range and the similarity of the gene regulation model between adjacent cell clusters is within a preset similarity range, and determining the regulation and control coefficient of the transcription factor in each cell cluster on the objective gene based on the objective function; determining differential transcription factors between adjacent cell clusters based on the regulatory coefficients, and determining cell fate determinants based on the differential transcription factors.
2. The method for identifying a cell fate determinant according to claim 1, wherein determining the intracellular expression levels of transcription factors and target genes in single cell transcriptome sequencing data comprises: Acquiring initial single-cell transcriptome sequencing data, and filtering the genes according to the number of cells involved in expression of each gene in the initial single-cell transcriptome sequencing data to obtain transcription factors and target genes; Normalizing the expression amounts of the transcription factors and the target genes in different cells to obtain a gene expression matrix for expressing the expression amounts of the transcription factors and the target genes in the cells.
3. The method of cell fate determinant recognition of claim 2, wherein the constructing a cell lineage based on the single cell transcriptome sequencing data comprises: obtaining cell cluster information in the single cell transcriptome sequencing data; the directed tree relationship between the cell clusters is constructed based on the differentiation process of the cells, resulting in a cell lineage.
4. The method for recognizing a cell fate determinant according to claim 1, wherein the constructing a gene regulation model based on a relationship between the intracellular expression amount of each transcription factor in each cell cluster in the cell lineage and the intracellular expression amount of each target gene comprises: for each cell cluster, the expression quantity of the target gene in the cell is taken as a dependent variable, the expression quantity of the transcription factor in the cell is taken as an independent variable, the regulation and control coefficient of the transcription factor on the target gene is taken as a slope, and Gaussian random noise is taken as an error term, so that a linear gene regulation and control model is constructed.
5. The method of claim 4, wherein the objective function is: Wherein, the For the regulation and control coefficient of transcription factor to the target gene, A is the precision range of the gene regulation and control model of each cell cluster, B is the sparseness range of the gene regulation and control model of the cell cluster, C is the similarity range of the gene regulation and control model between adjacent cell clusters, And Is a preset super parameter.
6. The method for identifying a cell fate determinant according to claim 5, wherein the determining the control coefficient of the transcription factor on the target gene in each of the cell clusters based on the objective function comprises: Performing collaborative optimization on the objective function by adopting a preset convex optimization algorithm, and determining the regulation and control coefficient of transcription factors in each cell cluster on the objective gene; and determining a linear gene regulation model of each cell cluster based on the regulation coefficient of the transcription factor on the target gene.
7. The method of claim 6, wherein determining differential transcription factors between neighboring cell clusters based on the control coefficients, determining cell fate determinants based on the differential transcription factors, comprises: Determining differential transcription factors which are different in regulation and control of the target genes in each adjacent cell cluster based on a linear gene regulation and control model of each adjacent cell cluster; determining the cell fate determinant type of the differential transcription factor based on whether the differential transcription factor is present in an adjacent cell cluster.
8. A cell fate determinant recognition device, comprising: a cell lineage determination module for determining the expression amounts of transcription factors and target genes in cells in the single cell transcriptome sequencing data, and constructing a cell lineage based on the single cell transcriptome sequencing data; The model construction module is used for constructing a gene regulation model based on the relation between the expression quantity of each transcription factor in each cell cluster in the cell lineage and the expression quantity of each target gene in the cell; The regulation and control coefficient determining module is used for constructing an objective function with the purposes that the precision of the gene regulation and control model of each cell cluster is within a preset precision range, the sparsity of the gene regulation and control model of each cell cluster is within a preset sparsity range and the similarity of the gene regulation and control model between adjacent cell clusters is within a preset similarity range, and determining the regulation and control coefficient of the transcription factor in each cell cluster on the objective gene based on the objective function; And the fate decision factor determining module is used for determining differential transcription factors between adjacent cell clusters based on the regulation and control coefficients and determining cell fate decision factors based on the differential transcription factors.
9. An electronic device comprising a memory and a processor, wherein, The memory is used for storing programs; the processor, coupled to the memory, for executing the program stored in the memory to implement the steps in the cell fate determinant recognition method of any of the above claims 1 to 7.
10. A computer readable storage medium storing a computer readable program or instructions which when executed by a processor is capable of carrying out the steps of the cell fate determinant recognition method of any of the preceding claims 1 to 7.

Description

Cell fate determination factor identification method and related device Technical Field The invention relates to the technical field of bioinformatics, in particular to a cell fate determining factor identification method and a related device. Background Biological development covers the history of primitive stem cells from dividing, differentiating, to forming fully functional cells. In the biological development process, from one fertilized egg, each cell expresses different genes orderly through growth and differentiation. Although they share the same genetic code, eventually they still go to disparate cell fate. Identifying genes and related regulatory effects that play a critical role in cell fate at different stages in the development process, and thus determining cell fate determinants has been a fundamental and important issue in the life sciences field. Research shows that the fate decision of cells in the biological development process is regulated by some key transcription factors and related regulation and control actions, the prior art only constructs a gene regulation network of whole cell 'groups' from a macroscopic angle, ignores the specific characteristics of cell clusters regulated by gene expression, and finally leads to low identification precision of determinants. It is contemplated that different cells share the same genetic code during development. In a cell cluster, the structure of the gene expression regulatory network should vary continuously rather than intermittently between adjacent cell clusters. Therefore, how to fuse the topology of the cell lineage tree, infer the cell cluster specific gene regulatory network, and further identify cell fate determinants in different developmental stages in the cell lineage is a research difficulty in the bioinformatics field. Therefore, the sparseness of the gene regulation model of the cell clusters and the similarity of the gene regulation model among the cell clusters cannot be considered in the recognition of the cell fate determinants in the prior art, so that the recognition accuracy of the cell fate determinants is poor. Disclosure of Invention In view of the foregoing, it is necessary to provide a method and a related device for identifying cell fate determinants, which are used for solving the problem that the prior art cannot consider the sparseness of cell cluster gene regulation models and the similarity of gene regulation models among cell clusters in the identification of cell fate determinants, resulting in poor accuracy of cell fate determinant identification. In order to solve the above problems, in a first aspect, the present invention provides a cell fate determining factor recognition method comprising: Determining the expression level of transcription factors and target genes in cells in single-cell transcriptome sequencing data, and constructing cell lineages based on the single-cell transcriptome sequencing data; Constructing a gene regulation model based on the relation between the expression amount of each transcription factor in each cell cluster in a cell lineage and the expression amount of each target gene in the cell; Constructing an objective function by taking the purposes that the precision of the gene regulation model of each cell cluster is within a preset precision range, the sparsity of the gene regulation model of each cell cluster is within a preset sparsity range and the similarity of the gene regulation model between adjacent cell clusters is within a preset similarity range, and determining the regulation and control coefficient of transcription factors in each cell cluster on the objective gene based on the objective function; Differential transcription factors between adjacent cell clusters are determined based on the control coefficients, and cell fate determinants are determined based on the differential transcription factors. In one possible embodiment, determining the amount of transcription factors and genes of interest expressed in a cell in single cell transcriptome sequencing data comprises: Acquiring initial single-cell transcriptome sequencing data, and filtering genes according to the number of cells involved in expression of each gene in the initial single-cell transcriptome sequencing data to obtain transcription factors and target genes; normalizing the expression amounts of the transcription factors and the target genes in different cells to obtain a gene expression matrix for expressing the expression amounts of the transcription factors and the target genes in the cells. In one possible embodiment, constructing a cell lineage based on single cell transcriptome sequencing data includes: obtaining cell cluster information in single cell transcriptome sequencing data; The cell differentiation process is based on building a directed tree relationship between cell clusters to obtain cell lineages. In one possible embodiment, constructing a gene regulation model based on the relationsh