CN112382339A - Method and device for identifying zygote type gene activated ZGA gene - Google Patents
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Abstract
The application provides a method and a device for identifying a zygote type gene activated ZGA gene, wherein the method comprises the following steps: acquiring a gene expression matrix of cell genes in an embryonic development process, wherein the gene expression matrix comprises the expression quantities of the cell genes at different development time points; dividing different development time points to obtain different development stages of the embryo; dividing the gene expression matrix into N gene expression submatrixes based on the obtained different development stages, wherein each gene expression submatrix comprises the expression quantity of cell genes in the same development stage; obtaining an expression quantity characteristic value corresponding to each gene expression submatrix; ZGA genes are determined based on the respective gene expression submatrices and the obtained expression amount characteristic values. Thus, ZGA genes are determined by the expression quantity characteristic values obtained from the gene expression submatrix determined from the cell genes, so that the error is small, the reliability is high, and the accuracy of cell gene identification is improved.
Description
Technical Field
The application relates to the technical field of gene identification, in particular to a method and a device for identifying a zygote type gene activated ZGA gene.
Background
One of the key events in early embryonic development of mammals is Zygotic Gene Activation (ZGA), which is an important index for determining whether an embryo normally develops, and identification of genes in the embryo ZGA is of great significance for biological research.
In the prior art, based on analysis of transcriptome sequencing (RNA-seq) data, a gene whose ratio between the gene expression level at time ZGA and the gene expression level before ZGA occurred varied greatly was used as the ZGA gene. However, the existing sequencing technology has noise, and only a single time point is selected for calculation, so that the influence of the noise is large, and the error is large, so that the accuracy of gene identification is low.
Disclosure of Invention
In view of the above, the present application aims to provide a method and an apparatus for identifying a zygote-type gene-activated ZGA gene, wherein ZGA gene is determined by each gene expression submatrix determined from cellular genes and obtained expression characteristic values, and the method and the apparatus have the advantages of small error, high reliability and improved accuracy of cellular gene identification.
In a first aspect, embodiments of the present application provide a method of identifying a zygote-type gene activated ZGA gene, the method comprising:
acquiring a gene expression matrix of cell genes in an embryonic development process, wherein the gene expression matrix comprises the expression quantities of the cell genes at different development time points;
dividing the different development time points to obtain different development stages of the embryo;
dividing the gene expression matrix into N gene expression submatrices based on the obtained different development stages, wherein each gene expression submatrix comprises the expression quantity of cell genes in the same development stage;
obtaining an expression quantity characteristic value corresponding to each gene expression submatrix;
ZGA genes are determined based on the respective gene expression submatrices and the obtained expression amount characteristic values.
Preferably, the dividing the different development time points to obtain different development stages of the embryo includes:
obtaining the expression quantity of all cell genes at each development time point;
and clustering the development time points according to the obtained expression quantity to obtain different development stages of the embryo.
Preferably, the expression level characteristic value is a characteristic value obtained by statistically processing the expression levels of cellular genes included in the gene expression submatrix.
Preferably, the determining ZGA of the gene based on each gene expression submatrix and the obtained expression quantity characteristic value includes:
dividing the cellular genes into at least one set including partial cellular genes based on the respective gene expression submatrices and the obtained expression amount characteristic values;
ZGA genes are determined based on the partitioned set.
Preferably, the dividing of the cellular genes into at least one set including a part of the cellular genes based on the respective gene expression submatrices and the obtained expression amount feature values includes:
obtaining an expression amount limit value for dividing a cell gene;
determining the gene type of the cell gene at the development stage corresponding to each gene expression submatrix by comparing the expression quantity characteristic value corresponding to each gene expression submatrix with the expression quantity limiting value;
and dividing the cell genes into at least one set comprising partial cell genes based on the determined gene types of the cell genes and the corresponding development stages of the cell genes.
Preferably, the limit value of the expression amount comprises an upper limit value and a lower limit value of the expression amount, wherein the determining of the gene type of the cellular gene at the development stage corresponding to each gene expression submatrix comprises:
if the expression quantity characteristic value corresponding to the gene expression submatrix is greater than the expression quantity upper limit value, determining that the cell gene is a high-expression gene at the development stage corresponding to the gene expression submatrix;
and if the expression quantity characteristic value corresponding to the gene expression submatrix is smaller than the expression quantity lower limit value, determining that the cell gene does not express the gene at the development stage corresponding to the gene expression submatrix.
Preferably, the dividing the cellular genes into at least one set including partial cellular genes based on the determined gene types of the cellular genes and the corresponding developmental stages of the cellular genes includes:
the cell gene composition 2 is the cell gene composition screened from the N developmental stages corresponding to the N gene expression submatricesNA set of individuals;
filtering out the corresponding sets of cell genes with the same gene types at N development stages to obtain 2N-2 sets;
obtaining 2 from the cellular geneN-2 sets of cellular genes.
Preferably, said determining ZGA genes based on the partitioned set comprises:
arranging different development stages of the embryos in a descending order, and determining the development stage arranged at the first position as a first development stage and the development stage arranged at the second position as a second development stage;
for each of the at least one set including partial cellular genes, the cellular genes belonging to the set corresponding to the non-expressed gene at the first development stage and corresponding to the highly expressed gene at the second development stage are determined as ZGA genes.
Preferably, after the determining ZGA of the genes based on the respective gene expression submatrices and the obtained expression amount characteristic values, the method further comprises:
obtaining a reference gene expression map corresponding to a historical ZGA gene;
acquiring an actual gene expression map corresponding to ZGA genes determined based on each gene expression submatrix and the expression quantity characteristic value;
and if the deviation between the actual gene expression map and the reference gene expression map is within a preset range, determining that the obtained ZGA gene is reliable.
In a second aspect, embodiments of the present application provide an apparatus for identifying a zygote-type gene activated ZGA gene, the apparatus comprising:
the matrix acquisition module is used for acquiring a gene expression matrix of cell genes in the embryonic development process, wherein the gene expression matrix comprises the expression quantities of the cell genes at different development time points;
the time point dividing module is used for dividing the different development time points to obtain different development stages of the embryo;
the submatrix division module is used for dividing the gene expression matrix into N gene expression submatrixes based on the obtained different development stages, wherein each gene expression submatrix comprises the expression quantity of the cell genes in the same development stage;
the characteristic value acquisition module is used for acquiring the expression quantity characteristic value corresponding to each gene expression submatrix;
and a gene determination module for determining ZGA genes based on the respective gene expression submatrices and the obtained expression quantity characteristic values.
Preferably, when the time point dividing module is configured to divide the different development time points to obtain different development stages of the embryo, the time point dividing module is configured to:
obtaining the expression quantity of all cell genes at each development time point;
and clustering the development time points according to the obtained expression quantity to obtain different development stages of the embryo.
Preferably, the expression level characteristic value is a characteristic value obtained by statistically processing the expression levels of cellular genes included in the gene expression submatrix.
Preferably, the gene determination module, when being configured to determine ZGA a gene based on each gene expression submatrix and the obtained expression amount characteristic value, is configured to:
dividing the cellular genes into at least one set including partial cellular genes based on the respective gene expression submatrices and the obtained expression amount characteristic values;
ZGA genes are determined based on the partitioned set.
Preferably, the gene determination module, when configured to divide cellular genes into at least one set including partial cellular genes based on the respective gene expression submatrices and the obtained expression amount feature values, is configured to:
obtaining an expression amount limit value for dividing a cell gene;
determining the gene type of the cell gene at the development stage corresponding to each gene expression submatrix by comparing the expression quantity characteristic value corresponding to each gene expression submatrix with the expression quantity limiting value;
and dividing the cell genes into at least one set comprising partial cell genes based on the determined gene types of the cell genes and the corresponding development stages of the cell genes.
Preferably, the limit value of the expression amount comprises an upper limit value and a lower limit value of the expression amount, wherein when the gene determination module is used for determining the gene type of the cell gene at the development stage corresponding to each gene expression submatrix, the gene determination module is used for:
if the expression quantity characteristic value corresponding to the gene expression submatrix is greater than the expression quantity upper limit value, determining that the cell gene is a high-expression gene at the development stage corresponding to the gene expression submatrix;
and if the expression quantity characteristic value corresponding to the gene expression submatrix is smaller than the expression quantity lower limit value, determining that the cell gene does not express the gene at the development stage corresponding to the gene expression submatrix.
Preferably, when the gene determination module is configured to divide the cellular genes into at least one set including partial cellular genes based on the determined gene types of the cellular genes and the corresponding developmental stages of the cellular genes, the gene determination module is configured to:
the cell gene composition 2 is the cell gene composition screened from the N developmental stages corresponding to the N gene expression submatricesNA set of individuals;
filtering out the corresponding sets of cell genes with the same gene types at N development stages to obtain 2N-2 sets;
obtaining 2 from the cellular geneN-2 sets of cellular genes.
Preferably, the gene determination module, when configured to determine ZGA a gene based on the partitioned set, is configured to:
arranging different development stages of the embryos in a descending order, and determining the development stage arranged at the first position as a first development stage and the development stage arranged at the second position as a second development stage;
for each of the at least one set including partial cellular genes, the cellular genes belonging to the set corresponding to the non-expressed gene at the first development stage and corresponding to the highly expressed gene at the second development stage are determined as ZGA genes.
Preferably, the apparatus further comprises:
the reference map acquisition module is used for acquiring a reference gene expression map corresponding to the historical ZGA gene;
the actual map acquisition module is used for acquiring an actual gene expression map corresponding to the ZGA gene determined based on each gene expression submatrix and the expression quantity characteristic value;
and the gene reliability determining module is used for determining that the obtained ZGA gene is reliable if the deviation between the actual gene expression map and the reference gene expression map is within a preset range.
In a third aspect, an embodiment of the present application further provides an electronic device, including: a processor, a memory and a bus, the memory storing machine readable instructions executable by the processor, the processor and the memory communicating over the bus when the electronic device is operating, the machine readable instructions when executed by the processor performing the steps of the method of identifying a zygote type gene activation ZGA gene as described above.
In a fourth aspect, embodiments of the present application further provide a computer-readable storage medium, having a computer program stored thereon, where the computer program is executed by a processor to perform the steps of the method for identifying a zygote-type gene activation ZGA gene as described above.
The embodiment of the application provides a method and a device for identifying a zygote type gene activated ZGA gene, wherein the method comprises the following steps: acquiring a gene expression matrix of cell genes in the process of embryonic development, wherein the gene expression matrix comprises expression quantities of the cell genes at different development time points, dividing the different development time points to obtain different development stages of an embryo, dividing the gene expression matrix into N gene expression submatrices based on the obtained different development stages, wherein each gene expression submatrix comprises the expression quantity of the cell genes at the same development stage, acquiring an expression quantity characteristic value corresponding to each gene expression submatrix, and determining ZGA genes based on each gene expression submatrix and the obtained expression quantity characteristic value. Thus, ZGA genes are determined by the expression quantity characteristic values obtained from the gene expression submatrix determined from the cell genes, so that the error is small, the reliability is high, and the accuracy of cell gene identification is improved.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
FIG. 1 is a flow chart of a method for identifying zygote-type gene activated ZGA gene according to the examples of the present application;
FIG. 2 is a flow chart of another method for identifying zygote-type gene activated ZGA gene provided in the examples of the present application;
FIG. 3 is a schematic diagram of clustering of gene expression matrices provided in the examples of the present application;
FIG. 4 is a schematic illustration of the gene screening and classification process provided in the examples of the present application;
FIG. 5 is a schematic structural diagram of an apparatus for identifying zygote-type gene activated ZGA gene according to the present embodiment;
FIG. 6 is a second schematic structural diagram of an apparatus for identifying zygote-type gene activated ZGA gene according to the embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. Every other embodiment that can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present application falls within the protection scope of the present application.
Referring to FIG. 1, FIG. 1 is a flowchart of a method for identifying a zygote type gene activated ZGA gene according to the embodiment of the present application. As shown in fig. 1, a method provided in an embodiment of the present application includes:
s110, obtaining a gene expression matrix of cell genes in the embryonic development process, wherein the gene expression matrix comprises the expression quantity of the cell genes at different development time points.
Here, embryonic development refers to a process from a fertilized egg to the embryo's emergence from the ovine membrane, which involves a large number of cellular genes, wherein the process includes an early stage ZGA starting at the late stage of a 1-cell embryo, also called minor zygote-type gene activation (minorZGA), and a late stage ZGA starting after the formation of a 2-cell embryo, also called major zygote-type gene activation (majorZGA), and the main objective of the present embodiment is to identify ZGA genes from among a large number of cellular genes.
In the step, sequence information and expression information of almost all transcripts in embryonic cells in the embryonic development process are comprehensively and quickly obtained through a transcriptome sequencing technology (RNA-Seq) to obtain RNA-Seq data, and gene expression quantity calculation in the RNA-Seq is carried out through an FPKM algorithm to obtain a gene expression matrix of cell genes. Wherein, the row of the gene expression matrix represents the cell gene, the column represents the development time point, the value at each development time point represents the expression quantity of the cell gene at the development time point, and the gene expression matrix comprises the expression quantities of the cell gene at all different development time points in the embryo development process because the cell gene has a plurality of development time points in the embryo development process.
And S120, dividing the different development time points to obtain different development stages of the embryo.
In this step, since each development stage includes a plurality of development time points, several different development time points are clustered to form one development stage. The clustering is based on the similarity of the expression levels of the same cellular genes at these developmental time points, i.e., the same expression pattern at these developmental time points. And then, dividing different development time points by adopting a clustering mode to obtain different development stages of the embryo.
S130, dividing the gene expression matrix into N gene expression submatrixes based on the obtained different development stages, wherein each gene expression submatrix comprises the expression quantity of the cell genes in the same development stage.
In the step, a gene expression matrix is divided into N gene expression submatrixes, each gene expression submatrix includes all expression levels included by all cell genes corresponding to one development stage, wherein rows of the gene expression submatrix represent the cell genes, columns represent each development time point under the same development stage, and values represent the expression levels of the cell genes at the development time points under the development stage.
Specifically, each gene expression submatrix corresponds to a developmental stage of a cellular gene, and thus, the number of gene expression submatrixes corresponds to the number of developmental stages, i.e., N gene expression submatrixes correspond to N developmental stages. Wherein N is an integer of 1 or more.
And S140, obtaining expression quantity characteristic values corresponding to each gene expression submatrix.
In this step, expression quantity characteristic values corresponding to all cell genes on each gene expression submatrix are calculated through the expression quantity of each cell gene, and it should be noted that when there are N gene expression submatrixes, one gene corresponds to N expression quantity characteristic values.
Here, the expression level characteristic value is a characteristic value obtained by statistically processing the expression levels of cellular genes included in the gene expression submatrix. Specifically, the expression quantity characteristic value corresponding to each gene expression submatrix can be obtained by processing the expression quantity characteristic value corresponding to each gene expression submatrix by using a statistical method.
The expression level characteristic value may be, but is not limited to, an average expression level, a maximum expression level, an expected expression level, or a variance of expression levels.
S150, determining ZGA genes based on each gene expression submatrix and the obtained expression quantity characteristic value.
In this step, different sets of cellular genes are screened from the cellular genes based on each gene expression submatrix and the expression amount characteristic value corresponding to each gene expression submatrix, and then ZGA genes are found from the cellular genes of the different sets.
The ZGA gene is determined mainly by inputting the gene expression submatrix and expression quantity characteristic value corresponding to each cell gene into a filter for screening and filtering by adopting a gene screening and classifying mode to obtain a plurality of different sets of cell genes, wherein the sets comprise sets belonging to ZGA genes, and finally, ZGA genes are determined from the cell genes in the different sets according to the biological characteristics of ZGA genes, wherein the filtering rule is set in advance according to the biological standard.
The identification method provided by the embodiment of the application has cross-species universality, the ZGA occurrence time is automatically identified according to the transcription mode characteristics, and when insufficient species are researched, the method can be used for detecting the ZGA occurrence; the identification reliability is good, the sensitivity is high, the identification result covers a large number of known ZGA genes with important biological functions (such as housekeeping genes and oncogenes), and the identification result has the capability of finding a potentially key ZGA gene; by utilizing time sequence data of a plurality of development stages, the used information is more comprehensive and complete, and the obtained result is more comprehensive and accurate.
In addition, due to the method for identifying ZGA genes, ZGA occurrence time does not need to be manually given, and the method can be applied to unknown species in the ZGA occurrence period, has good cross-species universality and can be applied to a plurality of species with insufficient research data.
The method for identifying the zygote type gene activated ZGA gene provided by the embodiment of the application comprises the following steps: acquiring a gene expression matrix of cell genes in the process of embryonic development, wherein the gene expression matrix comprises expression quantities of the cell genes at different development time points, dividing the different development time points to obtain different development stages of an embryo, dividing the gene expression matrix into N gene expression submatrices based on the obtained different development stages, wherein each gene expression submatrix comprises the expression quantity of the cell genes at the same development stage, acquiring an expression quantity characteristic value corresponding to each gene expression submatrix, and determining ZGA genes based on each gene expression submatrix and the obtained expression quantity characteristic value. Thus, ZGA gene is determined by each gene expression submatrix determined from cell genes and the obtained expression quantity characteristic value, so that the error is small, the reliability is high, and the accuracy of gene identification is improved.
Referring to FIG. 2, FIG. 2 is a flow chart of another method for identifying zygote type gene activation ZGA according to the examples of the present application. As shown in fig. 2, a method provided in an embodiment of the present application includes:
s210, acquiring a gene expression matrix of cell genes in an embryonic development process, wherein the gene expression matrix comprises the expression quantities of the cell genes at different development time points;
s220, dividing the different development time points to obtain different development stages of the embryo;
s230, dividing the gene expression matrix into N gene expression submatrixes based on the obtained different development stages, wherein each gene expression submatrix comprises the expression quantity of cell genes in the same development stage;
s240, obtaining an expression quantity characteristic value corresponding to each gene expression submatrix;
s250, determining ZGA genes based on each gene expression submatrix and the obtained expression quantity characteristic values;
the descriptions of S210 to S250 may refer to the descriptions of S110 to S150, and the same technical effects can be achieved, which are not described in detail.
S260, obtaining a reference gene expression map corresponding to the historical ZGA gene;
in this step, a gene expression profile is determined from the original ZGA gene and used as a reference gene expression profile for the comparison ZGA gene.
S270, obtaining an actual gene expression map corresponding to the ZGA genes determined based on the gene expression submatrix and the expression quantity characteristic value.
In the step, an actual gene expression map is drawn according to the determined ZGA genes, and the actual gene expression map comprises the gene expression type and abundance information of the embryonic cells.
And S280, if the deviation between the actual gene expression map and the reference gene expression map is within a preset range, determining that the obtained ZGA gene is reliable.
In the step, if the actual gene expression map is consistent with the reference gene expression map in comparison, namely the deviation between the actual gene expression map and the reference gene expression map is within a preset range, and specifically, the similarity between the actual gene expression map and the reference gene expression map is more than 95%, the determined ZGA gene is reliable and has high accuracy. Meanwhile, the gene expression map is displayed in a form of a gene expression map, so that the method is more visual and vivid and is convenient for operators to observe, and therefore it is determined that the ZGA gene can be better found out by the recognition method provided by the embodiment of the application.
Furthermore, the ZGA gene determined by means of multiple verification is reliable, the expression pattern and the biological function of the cell gene are analyzed by methods such as gene expression pattern analysis and GO enrichment analysis on the identified cell genes in the same set, and the ZGA gene is verified to meet the characteristics of the existing ZGA process. By adopting the method provided by the embodiment of the application, gene expression profile data of different RNA sequencing technologies (such as Bulk RNA-seq and Single Cell RNA-seq) or different Cell samples (such as different periods or different tissues) are analyzed and compared in the same species, so that the expression modes of the identified ZGA genes in the same development stage are consistent, the identification result in the application is stable, and the robustness across data sets is realized.
In the embodiment of the present application, as a preferred embodiment, the step S220 includes: obtaining the expression quantity of all cell genes at each development time point; and clustering the development time points according to the obtained expression quantity to obtain different development stages of the embryo.
In the step, the development time points with the same gene expression pattern are clustered, and specifically, the development time points are clustered according to the obtained expression amount to obtain different development stages of the embryo. Thus, it is possible to ensure that the expression levels at each developmental time point are similar at each developmental stage, and it is easy to observe the expression pattern of the cellular gene at that developmental stage. In addition, because all cell genes of each development stage of the embryonic development are involved, each development stage corresponds to a plurality of development time points, information of more time points can completely cover ZGA process, and time sequence data is adopted, so that the method has the information of a plurality of time points, more information amount and stronger robustness. Further, a more complete ZGA gene can be identified in batches.
Exemplarily, as shown in fig. 3, fig. 3 is a schematic clustering diagram of a gene expression matrix provided in an embodiment of the present application. Using a Gene expression Matrix Gene Exp Matrix (rows are cell genes, columns are development time points, values are expression amounts of the cell genes at the development time points) as input, clustering the development time points by using a clustering analysis method, and identifying a Gene expression pattern P (P-1, P-2, P-3, P-4, P-5 … … P-n) of each development stage, wherein as shown in the figure, for the Gene expression pattern P-1, 6 support legs are provided in total, and each support leg corresponds to one development time point, so that the Gene expression pattern P-1 corresponds to 6 development time points, and similarly, the Gene expression pattern P-2 corresponds to 4 development time points, and the like. It can be seen that a developmental stage is composed of several developmental time points having the same expression pattern P, i.e. similar expression levels of the same cellular gene at these developmental time points. The input gene expression matrix is divided into gene expression submatrixes X (X1, X2, X3, X4 … … Xn) of each development stage, wherein the rows of the gene expression submatrix X are cell genes, the columns are development time points of the same development stage, and the value is the expression amount of the cell genes at the development time points of the same development stage.
Preferably, the expression level characteristic value is a characteristic value obtained by statistically processing the expression levels of cellular genes included in the gene expression submatrix. Here, the expression level characteristic value may be an average expression level, a maximum expression level, an expected expression level, or a variance of the expression level, but is not limited thereto.
Here, the expression level x ([ x1, x2, x3, x4 … … xn ]) of the cellular gene g at n developmental time points in each developmental stage is decomposed from the gene expressor matrix in the developmental stage. The expression quantity x of the cell gene, the expected value (avg) or variance value (var) of the expression quantity of the cell gene at the development stage determines the expression characteristic value y of the cell gene, wherein the expression quantity x is used for determining the expression mode of the cell gene at the current development stage.
In the embodiment of the present application, as a preferred embodiment, the step S250 includes: dividing the cellular genes into at least one set including partial cellular genes based on the respective gene expression submatrices and the obtained expression amount characteristic values; ZGA genes are determined based on the partitioned set.
Specifically, the dividing of the cellular genes into at least one set including a part of the cellular genes based on the respective gene expression submatrix and the obtained expression amount characteristic value includes: obtaining an expression amount limit value for dividing a cell gene; determining the gene type of the cell gene at the development stage corresponding to each gene expression submatrix by comparing the expression quantity characteristic value corresponding to each gene expression submatrix with the expression quantity limiting value; and dividing the cell genes into at least one set comprising partial cell genes based on the determined gene types of the cell genes and the corresponding development stages of the cell genes.
In the step, cell genes of different sets are screened by using the expression limit value, in the embodiment of the application, a filter or a screener can be selected, a filtering rule is formulated in the filter or the screener in advance, then each gene expression submatrix and the obtained expression characteristic value are used as the input of the filter, and the filter executes inside: comparing the expression quantity characteristic value corresponding to each gene expression submatrix with an expression quantity limiting value, determining the gene type of the cell gene at the development stage corresponding to each gene expression submatrix, screening the cell gene layer by layer according to the development stage corresponding to the cell gene until cell genes of different sets are obtained, and simultaneously determining the gene type corresponding to the cell gene of each development stage, wherein the gene type comprises a high-expression gene and a non-expression gene.
Preferably, the limit value of the expression amount comprises an upper limit value and a lower limit value of the expression amount, wherein the determining of the gene type of the cellular gene at the development stage corresponding to each gene expression submatrix comprises: if the expression quantity characteristic value corresponding to the gene expression submatrix is greater than the expression quantity upper limit value, determining that the cell gene is a high-expression gene at the development stage corresponding to the gene expression submatrix; and if the expression quantity characteristic value corresponding to the gene expression submatrix is smaller than the expression quantity lower limit value, determining that the cell gene does not express the gene at the development stage corresponding to the gene expression submatrix.
In this step, the upper limit value and the lower limit value (up/down) of the expression level at the current developmental stage can be determined based on biological experience. The expression amount x and the expression characteristic value y of the cellular gene are input to the filter. When the expression characteristic value y is higher than the upper expression limit value up, the cell gene corresponding to the development stage is considered as a high expression gene high-exp, and the expression quantity x (x1, x2, x3, x4 … … xn) of the cell gene at the development stage is reserved; when the expression characteristic value y is lower than the expression lower limit value down, the cell gene is considered not to be expressed in the development stage, and the cell gene is also called as a non-expressed gene no-exp; otherwise, if the cell gene does not satisfy the two conditions, the cell gene is considered to belong to neither the high-expression gene nor the non-expression gene at the current development stage, and the cell gene is discarded. Further, in the present examples, the cellular genes were screened by hierarchical filtration according to the developmental stage.
Exemplarily, as shown in fig. 4, fig. 4 is a schematic diagram of a process of Gene screening and classification provided in an embodiment of the present application, taking fig. 4 as an example, a filter is divided into 3 layers, each layer corresponds to a development stage, and the development stages are arranged in order from front to back, and each Gene expression submatrix corresponding to all Gene expression and corresponding expression characteristic values are input into the filter shown in the figure for screening and classification.
When each gene expression submatrix corresponding to all genes and corresponding expression characteristic values enter a first layer of a filter, determining an expression upper limit value and an expression lower limit value corresponding to the layer, determining a gene expression submatrix and an expression characteristic value of a development stage corresponding to the layer at the same time, and screening the expression characteristic value corresponding to the input gene expression submatrix according to a principle established in advance by the filter, so that the genes corresponding to the development stage are divided into two parts, namely a high-expression gene high-exp and an unexpressed gene no-exp, wherein the genes corresponding to the development stage, which do not belong to the high-expression gene or the unexpressed gene, are discarded.
Based on the same principle, the genes filtered by the first layer of the filter are continuously input into the second layer of the filter, wherein the upper limit value and the lower limit value of the expression quantity of the development stage corresponding to the second layer of the filter are the same as those of the first layer, the realized process is also similar, similarly, the genes filtered by the second layer of the filter are continuously input into the third layer of the filter, the process is continuously executed, and finally a plurality of sets of genes are obtained, wherein the genes in each set have similar gene characteristics.
It should be noted that, a gene includes multiple gene expression submatrixes, each gene expression submatrix corresponds to a development stage, each development stage corresponds to a level of a filter, when filtering is performed on each level of the filter, the filter only processes the gene expression submatrix and the expression quantity characteristic corresponding to the development stage, while the gene expression submatrix and the expression quantity characteristic corresponding to other development stages need to be processed by the filter corresponding to the development stage, and finally, a plurality of sets are obtained after the filter processing, where each set includes multiple complete genes.
Specifically, the determining ZGA genes based on the partitioned set includes: arranging different development stages of the embryos in a descending order, and determining the development stage arranged at the first position as a first development stage and the development stage arranged at the second position as a second development stage; for each of the at least one set including partial cellular genes, the cellular genes belonging to the set corresponding to the non-expressed gene at the first development stage and corresponding to the highly expressed gene at the second development stage are determined as ZGA genes.
In the step, a means for determining ZGA genes is determined, and the determination can be performed according to the gene types corresponding to the genes in the gene screening and classifying process, and the determination means is obtained through a large amount of test data and has certain authority.
Since ZGA includes an early stage ZGA starting from the late stage of a 1-cell embryo and a late stage ZGA starting after the formation of a 2-cell embryo, when determining whether a cellular gene is ZGA gene, it is only necessary to select genes in the process of dividing 1 cell into 2 cells, in this embodiment, all the developmental stages of the embryo are arranged in the order from small to large, the developmental stage arranged at the first position is determined as the first developmental stage, the developmental stage arranged at the second position is determined as the second developmental stage, and then all the genes in the set corresponding to the genes whose first developmental stage is not expressed and whose second developmental stage is highly expressed are determined as ZGA genes.
Preferably, the dividing the cellular genes into at least one set including partial cellular genes based on the determined gene types of the cellular genes and the corresponding developmental stages of the cellular genes includes: the cell gene is screened from N developmental stages corresponding to N gene expression submatrices to form 2NA set of individuals; filtering out the corresponding sets of the genes with the same gene types at the N development stages to obtain 2N-2 sets; obtaining 2 from the cellular geneN-2 sets of genes.
In this step, the genes selected from the cellular genes in N developmental stages can be combined into 2 according to the gene screening and classification process described in FIG. 4NA set of genes with the same type of gene at each developmental stage are discarded according to biological characteristics, thereby obtaining 2 from the cellular genesN-2 sets of genes.
Illustratively, as shown in fig. 4, 8 sets of genes are identified after layer-by-layer screening and classification by a level-3 filter, but genes corresponding to set 0 and set 7 are discarded, and finally 6 sets of genes are obtained, which are represented as set 1 to combined 6 genes, wherein part of the combined 6 genes belong to ZGA genes.
The method for identifying the zygote-type gene activation ZGA gene provided by the embodiment of the application obtains a gene expression matrix of a cell gene in an embryonic development process, wherein the gene expression matrix comprises the expression amounts of the cell gene at different development time points; dividing different development time points to obtain different development stages of the embryo; dividing the gene expression matrix into N gene expression submatrixes based on the obtained different development stages, wherein each gene expression submatrix comprises the expression quantity of cell genes in the same development stage; dividing the cellular genes into at least one set including partial cellular genes based on the respective gene expression submatrices and the obtained expression amount characteristic values; arranging different development stages of the embryos in a descending order, and determining the development stage arranged at the first position as a first development stage and the development stage arranged at the second position as a second development stage; genes belonging to a set of genes which are not expressed correspondingly in the first development stage and highly expressed correspondingly in the second development stage are determined as ZGA genes, so that the error is small, the reliability is high, and the accuracy of gene identification is improved.
Based on the same inventive concept, the embodiment of the present application further provides a device for identifying a zygote type gene activation ZGA gene corresponding to the method for identifying a zygote type gene activation ZGA gene, and since the principle of solving the problem of the device in the embodiment of the present application is similar to that of the method in the embodiment of the present application, the implementation of the device can refer to the implementation of the method, and repeated details are omitted.
Referring to fig. 5 and 6, fig. 5 is a schematic structural diagram of an apparatus for identifying a zygote type gene activation ZGA gene according to the embodiment of the present application, and fig. 6 is a second schematic structural diagram of an apparatus for identifying a zygote type gene activation ZGA gene according to the embodiment of the present application. As shown in fig. 5, the apparatus 500 includes:
a matrix obtaining module 510, configured to obtain a gene expression matrix of a cell gene in an embryonic development process, where the gene expression matrix includes expression amounts of the cell gene at different development time points;
a time point dividing module 520, configured to divide the different development time points to obtain different development stages of the embryo;
a submatrix dividing module 530, configured to divide the gene expression matrix into N gene expression submatrices based on the obtained different development stages, where each gene expression submatrix includes an expression amount of a cellular gene at the same development stage;
a eigenvalue obtaining module 540, configured to obtain an expression quantity eigenvalue corresponding to each gene expression submatrix;
and a gene determination module 550 for determining ZGA genes based on the respective gene expression submatrices and the obtained expression amount characteristic values.
In this embodiment, as a preferred embodiment, when the time point dividing module 520 is configured to divide the different development time points to obtain different development stages of the embryo, the time point dividing module 520 is configured to:
obtaining the expression quantity of all cell genes at each development time point;
and clustering the development time points according to the obtained expression quantity to obtain different development stages of the embryo.
In the present embodiment, as a preferred embodiment, the expression level characteristic value is a characteristic value obtained by statistically processing the expression levels of cellular genes included in the gene expression submatrix.
In the embodiment of the present application, as a preferred embodiment, when the gene determination module 550 is configured to determine ZGA a gene based on each gene expression submatrix and the obtained expression amount characteristic value, the gene determination module 550 is configured to:
dividing the cellular genes into at least one set including partial cellular genes based on the respective gene expression submatrices and the obtained expression amount characteristic values;
ZGA genes are determined based on the partitioned set.
In the embodiment of the present application, as a preferred embodiment, when the gene determination module 550 is configured to divide cellular genes into at least one set including partial cellular genes based on the respective gene expression submatrices and the obtained expression amount feature values, the gene determination module 550 is configured to:
obtaining an expression amount limit value for dividing a cell gene;
determining the gene type of the cell gene at the development stage corresponding to each gene expression submatrix by comparing the expression quantity characteristic value corresponding to each gene expression submatrix with the expression quantity limiting value;
and dividing the cell genes into at least one set comprising partial cell genes based on the determined gene types of the cell genes and the corresponding development stages of the cell genes.
In the embodiment of the present application, as a preferred embodiment, the limit value of the expression amount includes an upper limit value and a lower limit value of the expression amount, wherein when the gene determination module 550 is used to determine the gene type of the cellular gene at the development stage corresponding to each gene expression submatrix, the gene determination module 550 is used to:
if the expression quantity characteristic value corresponding to the gene expression submatrix is greater than the expression quantity upper limit value, determining that the cell gene is a high-expression gene at the development stage corresponding to the gene expression submatrix;
and if the expression quantity characteristic value corresponding to the gene expression submatrix is smaller than the expression quantity lower limit value, determining that the cell gene does not express the gene at the development stage corresponding to the gene expression submatrix.
In the embodiment of the present application, as a preferred embodiment, when the gene determining module 550 is configured to divide cellular genes into at least one set including partial cellular genes based on the determined gene types of the cellular genes and the corresponding developmental stages of the cellular genes, the gene determining module 550 is configured to:
screening the cell genes through N developmental stages corresponding to N gene expression submatricesCellular Gene composition 2NA set of individuals;
filtering out the corresponding sets of cell genes with the same gene types at N development stages to obtain 2N-2 sets;
obtaining 2 from the cellular geneN-2 sets of cellular genes.
In the embodiment of the present application, as a preferred embodiment, when the gene determination module 550 is configured to determine ZGA genes based on the divided sets, the gene determination module 550 is configured to:
arranging different development stages of the embryos in a descending order, and determining the development stage arranged at the first position as a first development stage and the development stage arranged at the second position as a second development stage;
for each of the at least one set including partial cellular genes, the cellular genes belonging to the set corresponding to the non-expressed gene at the first development stage and corresponding to the highly expressed gene at the second development stage are determined as ZGA genes.
Further, as shown in fig. 5, the apparatus 500 further includes:
a reference map acquisition module 560, configured to acquire a reference gene expression map corresponding to a historical ZGA gene;
an actual map obtaining module 570, configured to obtain an actual gene expression map corresponding to ZGA genes determined based on each gene expression submatrix and the expression quantity feature value;
and the gene reliability determining module 580 is configured to determine that the obtained ZGA gene is reliable if the deviation between the actual gene expression profile and the reference gene expression profile is within a preset range.
The embodiment of the application provides a device for identifying zygote type gene activation ZGA, which comprises a matrix acquisition module, a time point division module, a submatrix division module, a characteristic value acquisition module and a gene determination module, wherein the matrix acquisition module is used for acquiring a gene expression matrix of cell genes in an embryonic development process, and the gene expression matrix comprises expression quantities of the cell genes at different development time points; the time point dividing module is used for dividing different development time points to obtain different development stages of the embryo; the submatrix division module is used for dividing the gene expression matrix into N gene expression submatrixes based on the obtained different development stages, wherein each gene expression submatrix comprises the expression quantity of the cell genes at the same development stage; the characteristic value acquisition module is used for acquiring an expression quantity characteristic value corresponding to each gene expression submatrix; the gene determination module is used for determining ZGA genes based on each gene expression submatrix and the obtained expression quantity characteristic values. Thus, ZGA gene is determined by each gene expression submatrix determined from cell genes and the obtained expression quantity characteristic value, so that the error is small, the reliability is high, and the accuracy of gene identification is improved.
Referring to fig. 7, fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. As shown in fig. 7, the electronic device 700 includes a processor 710, a memory 720, and a bus 730.
The memory 720 stores machine-readable instructions executable by the processor 710, when the electronic device 700 runs, the processor 710 and the memory 720 communicate with each other through the bus 730, and when the machine-readable instructions are executed by the processor 710, the steps of the method for identifying a zygote-type gene activation ZGA gene in the method embodiments shown in fig. 1 and fig. 2 may be executed.
An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program may perform the steps of the method for identifying a zygote-type gene activation ZGA gene in the method embodiments shown in fig. 1 and fig. 2.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the exemplary embodiments of the present application, and are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method of identifying a zygote type gene activated ZGA gene, the method comprising:
acquiring a gene expression matrix of cell genes in an embryonic development process, wherein the gene expression matrix comprises the expression quantities of the cell genes at different development time points;
dividing the different development time points to obtain different development stages of the embryo;
dividing the gene expression matrix into N gene expression submatrices based on the obtained different development stages, wherein each gene expression submatrix comprises the expression quantity of cell genes in the same development stage;
obtaining an expression quantity characteristic value corresponding to each gene expression submatrix;
ZGA genes are determined based on the respective gene expression submatrices and the obtained expression amount characteristic values.
2. The method of claim 1, wherein said dividing the different developmental time points to obtain different developmental stages of the embryo comprises:
obtaining the expression quantity of all cell genes at each development time point;
and clustering the development time points according to the obtained expression quantity to obtain different development stages of the embryo.
3. The method according to claim 1, wherein the expression level characteristic value is a characteristic value obtained by statistically processing the expression levels of cellular genes included in the gene expression submatrix.
4. The method of claim 1, wherein determining ZGA a gene based on each gene expression submatrix and the obtained expression quantity characteristic values comprises:
dividing the cellular genes into at least one set including partial cellular genes based on the respective gene expression submatrices and the obtained expression amount characteristic values;
ZGA genes are determined based on the partitioned set.
5. The method according to claim 4, wherein the dividing of cellular genes into at least one set including partial cellular genes based on the respective gene expression submatrices and the obtained expression amount feature values comprises:
obtaining an expression amount limit value for dividing a cell gene;
determining the gene type of the cell gene at the development stage corresponding to each gene expression submatrix by comparing the expression quantity characteristic value corresponding to each gene expression submatrix with the expression quantity limiting value;
and dividing the cell genes into at least one set comprising partial cell genes based on the determined gene types of the cell genes and the corresponding development stages of the cell genes.
6. The method of claim 5, wherein the threshold expression level comprises an upper threshold expression level and a lower threshold expression level, and wherein determining the gene type of the cellular gene at the developmental stage corresponding to each gene expression submatrix comprises:
if the expression quantity characteristic value corresponding to the gene expression submatrix is greater than the expression quantity upper limit value, determining that the cell gene is a high-expression gene at the development stage corresponding to the gene expression submatrix;
and if the expression quantity characteristic value corresponding to the gene expression submatrix is smaller than the expression quantity lower limit value, determining that the cell gene does not express the gene at the development stage corresponding to the gene expression submatrix.
7. The method of claim 5, wherein the dividing cellular genes into at least one set including partial cellular genes based on the determined gene types of the cellular genes and the corresponding developmental stages of the cellular genes comprises:
the cell gene composition 2 is the cell gene composition screened from the N developmental stages corresponding to the N gene expression submatricesNA set of individuals;
filtering out the corresponding sets of cell genes with the same gene types at N development stages to obtain 2N-2 sets;
obtaining 2 from the cellular geneN-2 sets of cellular genes.
8. The method of claim 4, wherein determining ZGA genes based on the partitioned set comprises:
arranging different development stages of the embryos in a descending order, and determining the development stage arranged at the first position as a first development stage and the development stage arranged at the second position as a second development stage;
for each of the at least one set including partial cellular genes, the cellular genes belonging to the set corresponding to the non-expressed gene at the first development stage and corresponding to the highly expressed gene at the second development stage are determined as ZGA genes.
9. The method of claim 1, wherein after said determining ZGA genes based on the respective gene expression submatrices and the obtained expression quantity eigenvalues, the method further comprises:
obtaining a reference gene expression map corresponding to a historical ZGA gene;
acquiring an actual gene expression map corresponding to ZGA genes determined based on each gene expression submatrix and the expression quantity characteristic value;
and if the deviation between the actual gene expression map and the reference gene expression map is within a preset range, determining that the obtained ZGA gene is reliable.
10. An apparatus for identifying a zygote type gene activated ZGA gene, the apparatus comprising:
the matrix acquisition module is used for acquiring a gene expression matrix of cell genes in the embryonic development process, wherein the gene expression matrix comprises the expression quantities of the cell genes at different development time points;
the time point dividing module is used for dividing the different development time points to obtain different development stages of the embryo;
the submatrix division module is used for dividing the gene expression matrix into N gene expression submatrixes based on the obtained different development stages, wherein each gene expression submatrix comprises the expression quantity of the cell genes in the same development stage;
the characteristic value acquisition module is used for acquiring the expression quantity characteristic value corresponding to each gene expression submatrix;
and a gene determination module for determining ZGA genes based on the respective gene expression submatrices and the obtained expression quantity characteristic values.
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