A method for estimating the cycle of an organ based on gene expression levels in cell types surrounding the organ.

Abstract

To provide a novel technique for estimating the cycle of an organ.SOLUTION: Provided is a method for estimating the cycle of an organ based on a gene expression level in a cell type surrounding the organ, comprising: a plot information preparation step of preparing plot information in which sample identification information with respect to the sample identification of the cell type, gene expression information with respect to the gene expression level in the cell type, and arrangement information with respect to a relative positional relation between pieces of sample identification information determined based on the similarity of the gene expression information in the plurality of cell types are associated with one another; a time series determination step of determining a time series of the plot information based on the arrangement information; and a cycle estimation step of estimating the cycle of the organ based on a result of the time series determination step.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a method for estimating the cycle of an organ.

Background Art

[0002] Hair follicles are tissues that produce hairs such as hair. The periodic regeneration and shedding of hair are controlled by hair matrix cells, hair stem cells, etc. that make up the hair follicles. Such repeated regeneration and hair loss of hair are called the hair cycle, and are classified into a growth phase, a regression phase, and a resting phase. It is known that abnormalities in the hair cycle cause hair growth disorders. In recent years, research has been particularly advanced in hair in order to elucidate the mechanisms related to hair loss and thinning hair.

[0003] Patent Document 1 discloses a method for evaluating a candidate substance for a hair growth agent or a hair nourishing agent by focusing on the relationship between hair cycle abnormalities and hair loss and using a hair loss model that induces hair cycle abnormalities.

[0004] In addition, in order to accurately judge the symptoms of patients with alopecia and the like, accurately classifying the hair cycle is clinically important. Regarding human hair, in order to accurately determine the hair cycle as an index, observations focusing on histological structures have been widely carried out (Non-Patent Document 1).

[0005] Conventionally, single-cell RNA sequencing (single-cell RNA sequencing; scRNA-seq) is known as a means for analyzing gene expression at the individual cell level in cell tissues.

Prior Art Documents

Patent Documents

[0006]

Patent Document 1

Non-Patent Documents

[0007] [Non-Patent Document 1] Ji Won Oh et al., J Invest Dermatol. 2016 Jan; 136(1): 34-44. [Overview of the project] [Problems that the invention aims to solve]

[0008] Given the existence of the above-mentioned prior art, the object of the present invention is to provide a new technique for estimating the cycle of organs. [Means for solving the problem]

[0009] The present invention, which solves the above problems, A method for estimating the cycle of an organ based on the gene expression levels in cell types surrounding the organ, Sample identification information relating to the identification of the aforementioned cell type, Gene expression information regarding the amount of gene expression in the cell type, Arrangement information relating to the relative positional relationship between sample identification information, determined based on the similarity of gene expression information in multiple cell types, The process involves preparing plotting information to which the plotting information is linked, A time-series determination step, which determines the time-series of the plotting information based on the arrangement information, Based on the results of the time series determination process, a period estimation process is performed to estimate the period of the organ, This is a method for estimating the periodicity of an organ, which has the following characteristics.

[0010] By using this invention, it is possible to estimate the period of the organ being evaluated. More specifically, according to the present invention, the period of the subject to evaluation can be estimated by arranging multiple gene expression data points from different stages of a periodic biological phenomenon in a time series.

[0011] In a preferred embodiment of the present invention, the organ is a hair follicle. The aforementioned cycle is the hair cycle.

[0012] Furthermore, in a preferred embodiment of the present invention, the gene expression information is obtained by subjecting a cell tissue containing the cell type to single-cell RNA sequencing (scRNA-sec).

[0013] More specifically, the gene expression information is preferably obtained by creating a single-cell cDNA library from isolated cells and sequencing the created cDNA library.

[0014] In a preferred embodiment of the present invention, the time series determination step is: After performing a runner-up determination process to identify a second plotting information having the arrangement information closest to the first plotting information, based on the arrangement information contained in the first plotting information, This process determines the time series of plotting information by using the plotting information identified in the previous runner-up determination process as a reference, and then performing the same runner-up determination process as described above, but excluding the plotting information that was previously used as a reference, to identify the plotting information that has the most similar arrangement information.

[0015] Furthermore, the present invention relates to the organ cycle estimated by the method described above and the gene expression information, This method also estimates genes whose expression levels fluctuate in cell types surrounding organs in accordance with changes in the organ's cycle.

[0016] According to the present invention, it is possible to analyze changes in gene expression associated with the organ cycle.

[0017] Furthermore, the present invention relates to genes whose expression levels fluctuate in accordance with changes in the organ cycle estimated by the method described above, The gene expression information mentioned above, The aforementioned arrangement information, This method is also used to estimate the changes in gene expression levels associated with changes in the organ cycle.

[0018] Furthermore, the present invention is a method for estimating genes with variable expression levels in cell types around an organ as the cycle of the organ changes, comprising: sample identification information related to sample identification of the cell type, gene expression information related to the expression level of a gene in the cell type, arrangement information related to the relative positional relationship between sample identification information, determined based on the similarity of gene expression information in a plurality of the cell types, a plot information preparation step of preparing plot information associated with these; a time series determination step of determining the time series of the plot information based on the arrangement information; a cycle-linked gene estimation step of estimating genes with variable expression levels as the cycle of the organ changes; and is also a method for estimating genes with variable expression levels in cell types around an organ as the cycle of the organ changes, having these steps.

[0019] Furthermore, the present invention is an apparatus for estimating the cycle of an organ based on the gene expression level in cell types around the organ, comprising: sample identification information related to sample identification of the cell type, gene expression information related to the expression level of a gene in the cell type, arrangement information related to the relative positional relationship between sample identification information, determined based on the similarity of gene expression information in a plurality of the cell types, a plot information preparation means for preparing plot information associated with these; a time series determination means for determining the time series of the plot information based on the arrangement information; a cycle estimation means for estimating the cycle of the organ based on the result of the time series determination step; and is also an apparatus for estimating the cycle of an organ, comprising these means.

[0020] Furthermore, the present invention is a program for estimating the cycle of an organ based on the gene expression level in cell types around the organ, causing a computer to: use sample identification information related to sample identification of the cell type, Gene expression information regarding the amount of gene expression in the cell type, Arrangement information relating to the relative positional relationship between sample identification information, determined based on the similarity of gene expression information in multiple cell types, A means for preparing plotting information that is linked to the plotting information, A time-series determination means for determining the time-series of the plotting information based on the arrangement information, It is also an organ period estimation program that functions as a period estimation means for estimating the period of an organ based on the results of the aforementioned time series determination process. [Effects of the Invention]

[0021] According to the present invention, a new technique for estimating the cycle of organs can be provided. [Brief explanation of the drawing]

[0022] [Figure 1] <1> Methods for estimating the periodicity of organs, and <2> This is a flowchart for estimating the gene expression levels that fluctuate in accordance with changes in the organ cycle. [Figure 2] This figure shows the results of summarizing the gene expression information of all cells in a two-dimensional space (UMAP; Uniform Manifold Approximation and Projection), and specifically shows the gene expression information corresponding to hair follicle keratinocytes (corresponding to cell types KC0 and KC2). [Modes for carrying out the invention]

[0023] <1> Methods for estimating organ cycles This invention is characterized by estimating the cycle of an organ based on the gene expression levels in cell types surrounding the organ.

[0024] In this specification, "organ cycle" refers to the period in which a collection of cells and tissues that perform a certain function changes their form and other characteristics based on the passage of time or other factors.

[0025] In the present invention, the hair cycle in the hair follicle can be preferably cited as the target for estimation. Here, the hair cycle refers to the cyclical changes in hair and hair follicles, which consist of three stages: the resting phase, the growth phase, and the regression phase. The growth phase is further subdivided into the start of the growth phase, the early growth phase, and the late growth phase, while the regression phase is further subdivided into the early regression phase, the middle regression phase, and the late regression phase.

[0026] Furthermore, in this specification, "cell types surrounding the organ" refers to cell types localized in the organ whose period is being estimated, and which are characteristic of that organ.

[0027] Furthermore, "period estimation" in this invention includes both the estimation of the absolute period of the organ being estimated and the estimation of the time series (pseudoperiod) of the samples of each cell type used for estimation.

[0028] If the organ being considered is a hair follicle, examples of cell types surrounding the organ include hair follicle keratinocytes. In particular, the cell types surrounding the organ can be selected from sebaceous glands, outer root sheath (upper basal part, basal part), cortex / medulla, inner root sheath, and hair matrix cells, and preferably include one or more, more preferably two or more, more preferably three or more, more preferably four or more, more preferably five or more, more preferably six or more, even more preferably seven or more, and especially preferably all of them.

[0029] And the present invention is The plotting information preparation process S11 involves preparing plotting information, S12 is a time series determination process that determines the time series of information for plotting, Based on the results of the time series determination process, a period estimation process S13 is performed to estimate the period of the organ, It is characterized by having (see Figure 1).

[0030] The following provides a detailed explanation of each step.

[0031] (1) Process S11 for preparing information for plotting The plotting information preparation step S11 is a step in which plotting information is prepared for use in the steps described later. Here, the plotting information is at least, Sample identification information regarding the identification of cell types in a sample, Gene expression information regarding the amount of gene expression in the cell type, Arrangement information relating to the relative positional relationship between sample identification information, determined based on the similarity of gene expression information in multiple cell types, They are linked.

[0032] The plotting information to be prepared here is preferably 4 or more, more preferably 6 or more, more preferably 8 or more, more preferably 12 or more, and more preferably 15 or more. By providing plotting information above the lower limit, the organ cycle can be estimated with greater accuracy.

[0033] Furthermore, the plotting information to be prepared can preferably be set to 40 or less, more preferably 35 or less, more preferably 30 or less, more preferably 25 or less, and more preferably 20 or less.

[0034] Furthermore, in this invention, plotting information prepared in advance in a database can also be used (see Figure 1).

[0035] The following provides a more detailed explanation of each element of the plotting information.

[0036] (i) Sample identification information Sample identification information is information related to the identification of a sample by cell type. Specifically, this information concerns the sample number assigned to each cell type. Sample identification information can be prepared by assigning labels such as sample numbers to cell tissues obtained from subjects.

[0037] (ii) Gene expression information Gene expression information is information about the genes expressed in a cell type and / or cell.

[0038] In this context, it is preferable that the gene expression information includes data on the types of genes being expressed and data on the amount of gene expression. In particular, gene expression information is preferably in a form that contains data on gene expression for each individual cell within a cell type.

[0039] Here, gene expression information can be obtained by confirming gene expression in cell tissue acquired from a subject using methods commonly used by those skilled in the art.

[0040] One method for obtaining gene expression information is to create a single-cell cDNA library from isolated cells and then sequence the created cDNA library.

[0041] As a method for obtaining the gene expression information described above, single-cell RNA sequencing (scRNA-sec) is a preferred example.

[0042] Single-cell RNA sequencing allows for the qualitative and quantitative comprehensive acquisition of the entire mRNA spectrum held by individual cells within a given cell type.

[0043] Furthermore, it is preferable to extract information regarding gene expression levels in cell types surrounding the aforementioned organs from the results of gene expression level analysis.

[0044] Specifically, when estimating the hair cycle, it is preferable to extract information regarding gene expression levels in hair follicle keratinocytes. In particular, when estimating the hair cycle, it is preferable to extract information on gene expression levels in one or more, more preferably two or more, more preferably three or more, more preferably four or more, more preferably five or more, more preferably six or more, even more preferably seven or more, and especially preferably all of them, selected from the sebaceous gland, outer root sheath (upper basal part, basal part), cortex / medulla, inner root sheath, and hair matrix cells.

[0045] One method for identifying cell types around an organ is to identify the cell population around the organ based on gene expression information of marker genes for cell types around the organ.

[0046] In particular, a preferred method for identifying cell types around an organ is one in which the gene expression information of all cells is summarized into a two-dimensional space (2D conversion using a dimensionality reduction technique), and the cell population around the organ is identified based on the gene expression information of marker genes for cell types around the organ. Here, UMAP (Uniform Manifold Approximation and Projection) can be preferred as a dimensionality reduction method.

[0047] Furthermore, in this embodiment, it is preferable to select information regarding genes characteristic of cell types surrounding the organ.

[0048] More specifically, it is preferable that the gene expression information is obtained by calculating the average gene expression level across all samples and all cells (bulk information), scaling the results so that the average gene expression level is 0 and the variance is 1, and then excluding all samples with a Z-Score of less than 0 (those with gene expression levels below the average). By adopting the above configuration, it becomes possible to obtain information about characteristic genes in cell types surrounding organs.

[0049] Furthermore, in this invention, the gene expression information may be information about genes that have the highest gene expression levels across all samples and all cells. Here, as genes with high gene expression levels across all samples and all cells, we can select genes that are in the top 50%, more preferably the top 30%, more preferably the top 20%, more preferably the top 15%, and even more preferably the top 10%.

[0050] (iii) Placement information The placement information is information about the relative positional relationship between sample identification information, determined based on the similarity of gene expression information across multiple cell types.

[0051] Here, it is preferable that the placement information is determined so that the closer the sample identification information is to the gene expression information of the plotted data, the higher the similarity between the data.

[0052] Furthermore, it is preferable that the placement information includes information regarding the distance from the placement information of other adjacent plots.

[0053] Here, a preferred method for determining the relative placement of plotting information is one that visualizes the relative relationships between products by replacing the strength of their relevance or similarity with the distance between points on a map.

[0054] Furthermore, it is preferable that the information used for plotting be information that can be displayed in two dimensions (plane).

[0055] More specifically, methods for converting plotting information into information that can be displayed in two dimensions (a plane) include principal component analysis and multidimensional scaling.

[0056] Among these methods, multidimensional scaling is a preferred method for converting plotting information into information that can be displayed in two dimensions (a plane). Here, multidimensional scaling refers to a method that analyzes one or more variables that characterize an object (sample information in this embodiment), replaces the degree of similarity between the objects with distance, and plots them on a coordinate system.

[0057] However, in the present invention, the arrangement information can also be, for example, information that can be displayed in three-dimensional space.

[0058] (2) Time series determination process S12 The time series determination process S12 is a process in which the time series of the information for plotting is determined based on the arrangement information.

[0059] Here, the time series determination step S12 includes a runner-up determination process that uses the arrangement information of the first plotting information as a reference and identifies a second plotting information having arrangement information that is most similar to said arrangement information.

[0060] More specifically, the process involves using the plot position (placement information contained in the first plot information) of the first plot (sample identification information contained in the first plot information) as a reference, and identifying the second plot (second plot information) as the plot that has the plot position (placement information) most similar to the plot position (placement information contained in the first plot information) of the first plot. Next, using the plot position (arrangement information contained in the second plot information) of the second plot (sample identification information contained in the second plot information) as a reference, the same process as above is performed to identify the third plot, which is the plot with the most similar plot position (arrangement information) from the plot information excluding the first plot (the first plot information that was once used as a reference).

[0061] By sequentially applying the above processing to the plotting information, the time series of the plotting information can be determined based on the placement information.

[0062] Furthermore, in a preferred form of the time series determination step S12, of the points in the plotting information (arrangement information of each cell type), preferably 30% or more, more preferably 50% or more, more preferably 80% or more, more preferably 90% or more, and especially preferably all points are specified only once, and a process is performed to calculate the shortest path back to the point in the plotting information that was initially used as the reference. By adopting the above configuration, the period in that organ can be estimated with greater accuracy in the period estimation process described later.

[0063] Furthermore, it is preferable that the time series determination step S12 is a process similar to the above, in which plotting information having the most similar arrangement information is identified from plotting information after excluding the plotting information that has been used as a reference, based on the plotting information identified in the next-choice determination process.

[0064] Here, the 2-opt method can be exemplified as a method for identifying plotting information that has the most similar arrangement information.

[0065] (3) Period estimation step S13 The period estimation step S13 is a step in which the period of the organ is estimated based on the results of the time series determination step described above.

[0066] As shown in the examples described later, in the time series determination step S12 described above, the plotting information is determined based on the similarity of gene expression information. In cell types surrounding organs with periodicity, the similarity of gene expression information indicates the approximation of the periodic time series between the cell types. In other words, it is preferable that in the period estimation step S13, the change in the arrangement information as a result of the time series determination step S12 is determined to be the period of the organ.

[0067] In this process, the period estimation step can also be implemented in a way that identifies which period the cell type sample belongs to using a known method.

[0068] One method for determining which phase of the cycle a cell type sample belongs to is to utilize the results of functional analysis of period-linked genes. Here, as the results of functional analysis of period-linked genes, the period-linked genes identified by the method described later can be divided into several groups (periodic-linked gene groups) with different peak expression levels, and functional analysis (e.g., Gene Ontology enrichment analysis) can be performed for each group (periodic-linked gene group) to determine which of the resting, growth, or regression phases each group (periodic-linked gene group) belongs to.

[0069] Furthermore, when estimating the hair cycle, it is also possible to determine which of the three stages—resting phase, growth phase, or regression phase—the hair cycle of the sample used for estimation falls into, based on its gene expression information, etc. Furthermore, the identification of the cycle can also be done in a more subdivided form, such as the start of the growth phase, the early growth phase, the late growth phase, the early regression phase, the middle regression phase, and the late regression phase.

[0070] (4) Form of estimation device and estimation program Furthermore, the present invention relates to an estimation device that estimates the period of an organ based on the gene expression levels in cell types surrounding the organ. The estimation device of the present invention uses sample identification information relating to the identification of the cell type of sample, Gene expression information regarding the amount of gene expression in the cell type, Arrangement information relating to the relative positional relationship between sample identification information, determined based on the similarity of gene expression information in multiple cell types, A means for preparing plotting information that is linked to the plotting information, A time-series determination means for determining the time-series of the plotting information based on the arrangement information, A period estimation means for estimating the period of an organ based on the results of the time series determination process, It is equipped with.

[0071] Here, preferred embodiments of the estimation device of the present invention can be found by reference to the above description.

[0072] Furthermore, the present invention relates to an estimation program that estimates the cycle of an organ based on the gene expression levels in the cell types surrounding the organ. The estimation program of the present invention uses a computer to obtain sample identification information relating to the identification of the cell type, Gene expression information regarding the amount of gene expression in the cell type, Arrangement information relating to the relative positional relationship between sample identification information, determined based on the similarity of gene expression information in multiple cell types, A means for preparing plotting information that is linked to the plotting information, A time-series determination means for determining the time-series of the plotting information based on the arrangement information, It is preferable to have an embodiment in which the period estimation means functions as a means for estimating the period of an organ based on the results of the time series determination process described above.

[0073] Herein, preferred embodiments of the estimation program of the present invention can be found by reference to the above description.

[0074] <2> Methods for estimating the expression levels of genes whose expression levels fluctuate in accordance with changes in the organ cycle. Furthermore, this invention is also a method for estimating genes whose expression levels fluctuate in accordance with changes in the organ cycle.

[0075] Specifically, the present invention is a method for estimating genes whose expression levels fluctuate in cell types surrounding an organ in accordance with changes in the organ cycle, Sample identification information relating to the identification of the aforementioned cell type, Gene expression information regarding the amount of gene expression in the cell type, Arrangement information relating to the relative positional relationship between sample identification information, determined based on the similarity of gene expression information in multiple cell types, The process involves preparing plotting information to which the plotting information is linked, A time-series determination step, which determines the time-series of the plotting information based on the arrangement information, A periodic gene estimation process that estimates genes whose expression levels fluctuate in accordance with changes in the organ cycle, It is characterized by having the following features.

[0076] Here, regarding sample identification information, gene expression information, and placement information, <1> The explanation of methods for estimating organ cycles can be used as a basis. Furthermore, the time series determination process also, <1> The explanation of methods for estimating organ cycles can be used as a basis.

[0077] (1) Periodic gene estimation process S14 The following provides a detailed explanation of the periodic gene estimation process S14. The periodic gene estimation step S14 is a process for estimating genes whose expression levels fluctuate in accordance with changes in the organ cycle.

[0078] In the present invention, the periodic gene estimation step S14 is preferably configured to include a plotting process and a periodic gene determination process.

[0079] (i) Plotting The plotting process is the process of preparing plots for use in the periodic gene identification process described later. Specifically, the plotting process can take the following forms:

[0080] First, in the plotting process, each sample identification information is placed on the x-axis according to the time series derived from the placement information in the time series determination process. In this case, any sample identification information within the time series can be set as the starting point.

[0081] Furthermore, it is preferable that the intervals between the sample identification information placed on the x-axis be constant.

[0082] In addition, in this invention, the spacing between plotting information can be arranged to correspond to the distance information contained in the arrangement information.

[0083] Furthermore, in order to improve the accuracy of estimating genes whose expression levels fluctuate in accordance with changes in the organ cycle, the period of the sample identification information placed on the x-axis is preferably one and a half cycles or more, more preferably two cycles or more. By adopting the above configuration, continuity between the previous sample identification information and the next sample identification information can be ensured for all sample identification information.

[0084] Furthermore, in this invention, for example, the purpose is to create multiple graphs starting from different points, and the plotting process can be carried out on multiple media.

[0085] Next, in the plotting process, the y-axis will represent the expression level of a specific gene. Here, the specific gene expression levels can preferably be determined using information extracted from the aforementioned gene expression information.

[0086] Furthermore, for each plotting piece of information, the expression level of a specific gene (y-axis) corresponding to the time series (x-axis) derived from the placement information can be plotted.

[0087] (ii) Periodic gene determination process The process for estimating period-linked genes involves determining whether a particular gene is linked to a period based on the results of the plotting process described above.

[0088] As a method for estimating period-linked genes, a preferred embodiment involves pre-creating an "equation or model" relating to the correlation between changes in the time series (period) of a sample and changes in the expression level of a specific gene, and then comparing the results of the plotting process described above with this "equation or model" to estimate period-linked genes. By adopting this embodiment, the estimation accuracy can be improved.

[0089] Here, the degree of discrepancy between the plot and the "equation or model (corresponding to the curve in this embodiment)" is preferably evaluated by the p-value of the plot and the "equation or model (corresponding to the curve in this embodiment)". Here, the p-value is the probability that a more skewed test statistic is obtained (the probability that a statistic contrary to the hypothesis is observed), given that the null hypothesis is true.

[0090] In particular, it is preferable to have a configuration in which, when the p-value of the plot and the “equation or model (corresponding to the curve in this embodiment)” is below the significance level, it is determined that the expression level of the specific gene used for estimation is linked to the period.

[0091] In this invention, it is preferable that when the p-value is 0.1 or less, more preferably 0.05 or less, it is determined that the p-value of the plot and the "equation or model (corresponding to the curve in this embodiment)" is below the significance level.

[0092] Alternatively, it is preferable to use an image in which, for example, the line connecting the plots is superimposed with the "equation or model (corresponding to the curve in this embodiment)" and subjected to image processing. The higher the agreement rate, the more it is determined that the expression level of the specific gene used for estimation is correlated with the period.

[0093] Herein, the present invention relates to genes whose expression levels fluctuate in accordance with changes in the organ cycle, as estimated by the results of the above-described period-linked gene estimation step S14, Gene expression information and, Placement information and, Based on this, it is possible to estimate the changes in gene expression levels associated with changes in the organ cycle.

[0094] Furthermore, a preferred embodiment of the method for estimating the changes in gene expression levels associated with changes in the organ cycle can be described by referring to the above explanation.

[0095] (2) Estimation device and estimation program form Furthermore, the present invention can also be in the form of a period-linked gene estimation device that estimates genes whose expression levels fluctuate in accordance with changes in the organ cycle. The estimation device of the present invention uses sample identification information relating to the identification of the cell type of sample, Gene expression information regarding the amount of gene expression in the cell type, Arrangement information relating to the relative positional relationship between sample identification information, determined based on the similarity of gene expression information in multiple cell types, A means for preparing plotting information that is linked to the plotting information, A time-series determination means for determining the time-series of the plotting information based on the arrangement information, A method for estimating period-linked genes that have fluctuating expression levels in accordance with changes in the organ cycle, It is equipped with.

[0096] Here, preferred embodiments of the estimation device of the present invention can be found by reference to the above description.

[0097] Furthermore, the present invention relates to a period-linked gene estimation program that estimates genes whose expression levels fluctuate in accordance with changes in the organ cycle. The estimation program of the present invention uses a computer to obtain sample identification information relating to the identification of the cell type, Gene expression information regarding the amount of gene expression in the cell type, Arrangement information relating to the relative positional relationship between sample identification information, determined based on the similarity of gene expression information in multiple cell types, A means for preparing plotting information that is linked to the plotting information, A time-series determination means for determining the time-series of the plotting information based on the arrangement information, It is preferable to provide an embodiment that functions as a period-linked gene estimation means for estimating genes whose expression levels fluctuate in accordance with changes in the organ cycle.

[0098] Herein, preferred embodiments of the estimation program of the present invention can be found by reference to the above description. [Examples]

[0099] The following are various test results that support the fundamental findings of this invention.

[0100] <Example 1> Estimation of the hair cycle (1) Obtaining gene expression information in cell types surrounding hair follicles (1-1) Acquisition of test materials and measurement sites In this example, human skin as shown in Table 1 was used as the test material. First, in this embodiment, three-dimensional skin tissue containing a single hair (n=19) was selected as the measurement site (hereinafter, the acquired three-dimensional skin tissue will be referred to as SH (Single-hair sample)). In this embodiment, hairless three-dimensional skin tissue (n=3) was selected as the measurement site (hereinafter, the acquired three-dimensional skin tissue will be referred to as NH (Non-hair sample)). Then, three-dimensional skin tissue samples were obtained from the selected areas (see Table 1).

[0101] [Table 1]

[0102] After removing the epidermis from the acquired cell tissue, the extracellular matrix was removed.

[0103] (1-2) Acquisition of integrated gene expression information Subsequently, single-cell RNA sequencing (scRNA-sec) was performed on each cell tissue to obtain data on the gene expression levels of each cell in each cell tissue. Specifically, we created a single-cell cDNA library from cells isolated from cell tissue, and then sequenced the created cDNA library to obtain data on the gene expression levels of each cell. In Table 1, "No. of cells" indicates the number of cells in the sequenced data that are suitable for data analysis.

[0104] Next, we integrated data on the gene expression levels of each cell in each cell tissue to prepare integrated gene expression information.

[0105] Then, using UMAP (Uniform Manifold Approximation and Projection), gene expression information corresponding to hair follicle keratinocytes (cell types KC0 and KC2; corresponding to the cell types surrounding organs in this invention) was extracted from all cells in the integrated gene expression information (see Figure 2). In this example, the distribution of cell numbers in single-hair samples and non-hair samples is compared to identify the hair follicle keratinocytes (cell types KC0 and KC2) in the integrated gene expression information.

[0106] (2) Estimation of the hair cycle based on gene expression levels in cell types surrounding the hair follicle. Next, we estimated the hair cycle based on gene expression levels in cell types surrounding the hair follicle.

[0107] (2-1) Process of preparing information for plotting S11 First, regarding gene expression information corresponding to hair follicle keratinocytes (corresponding to cell types KC0 and KC2), the average gene expression levels across all samples and all cells were calculated (bulk information), and evaluated using the Z-Score. At this time, scaling was performed so that the mean of gene expression levels was 0 and the variance was 1. Then, by excluding all samples with a Z-Score value of less than 0 (those with gene expression levels below average), we selected the gene expression information (corresponding to gene expression information in this invention) to be used in this study.

[0108] Then, based on the similarity of gene expression information in each single hair sample, the correlation coefficient between each single hair sample was calculated. In this embodiment, information regarding the relative positional relationship between sample identification information (corresponding to the arrangement information in this invention) is prepared by subtracting the aforementioned correlation coefficient from 1. As a result of the above subtraction process, the higher the correlation coefficient between samples, the closer the relative positions of the sample identification information become.

[0109] (2-2) Time series determination process S12 Subsequently, a 2D plot was created for each single-hair sample using multidimensional scaling. Here, the higher the similarity of the gene expression information, the closer the plots will be positioned to each other.

[0110] Then, the shortest path that passes through each point of the 2D plot (corresponding to the sample identification information in this invention) exactly once and that passes through all points was calculated. In this example, the shortest path described above was calculated using the 2-opt method.

[0111] (2-3) Period estimation step S13 In the above process, the position of the plot is determined based on the similarity of gene expression information. Furthermore, in cell types surrounding periodic organs, the similarity of their gene expression information indicates the approximation of the periodic time series between the cell types. As a result of the above processing, the shortest path that passes through each point in the 2D plot (corresponding to the sample identification information in this invention) exactly once, and that passes through all points, represents the time series of each single hair sample. In other words, it was found that the hair cycle can be visualized in a pseudo-way using the method of this embodiment.

[0112] <Example 2> Next, we estimated the genes whose expression levels fluctuate during the hair cycle in hair follicle keratinocytes (corresponding to the cell types surrounding the hair follicle in this invention).

[0113] (1) Plotting (i) Setting the horizontal axis (time axis) Each point of the 2D plot prepared in Example 1 (corresponding to sample identification information in this invention) was placed on the x-axis according to the arrangement information between each sample (1 - correlation coefficient). At this time, the distance between each point of the 2D plot was set to 1 for all points. There are 19 possible starting points (the number of 2D plots).

[0114] (ii) Setting the vertical axis (gene expression level) The vertical axis represents the expression level of a specific gene. Here, the specific gene expression levels were determined using information extracted from the aforementioned gene expression data.

[0115] (2) Period-linked gene determination process Based on the results of the plotting process described above, we determined whether or not a particular gene is linked to the cycle.

[0116] In this example, a "formula or model" relating to the correlation between changes in the time series (period) of a pre-prepared sample and changes in the expression levels of specific genes was used to estimate period-linked genes by comparing the results of the plotting process described above with the said "formula or model".

[0117] In this embodiment, the degree of discrepancy between the plot and the curve was evaluated based on the p-values ​​of the plot and the curve. In this example, we examined the degree of discrepancy between the plots and curves at the 19 starting points mentioned above, and genes whose p-values ​​were below the terminating level (0.1) in all 19 calculations were estimated to be "genes whose expression levels fluctuate during the hair cycle in hair follicle keratinocytes."

[0118] The above process revealed that it is possible to determine whether or not the expression levels of the genes used for estimation are correlated with the period. [Industrial applicability]

[0119] This invention can be used to estimate the cycle of organs. Furthermore, this invention can also be used for functional analysis of various cell types associated with the hair cycle.

Claims

1. A method for estimating the cycle of an organ based on the gene expression levels in cell types surrounding the organ, Sample identification information relating to the identification of the aforementioned cell type, Gene expression information regarding the amount of gene expression in the cell type, Arrangement information relating to the relative positional relationship between sample identification information, determined based on the similarity of gene expression information in multiple cell types, The process involves preparing plotting information to which the plotting information is linked, A time-series determination step, which determines the time-series of the plotting information based on the arrangement information, Based on the results of the time series determination step, a period estimation step is performed to estimate the period of the organ, It has, The aforementioned organ is a hair follicle, The aforementioned cycle is the hair cycle, The gene expression information is obtained by subjecting a cell tissue containing the cell type to single-cell RNA sequencing, The aforementioned time series determination process, After performing a runner-up determination process to identify a second plotting information having the arrangement information closest to the first plotting information, based on the arrangement information contained in the first plotting information, This process determines the time series of plotting information by using the plotting information identified in the aforementioned second-place determination process as a reference, and then performing a similar second-place determination process to identify the plotting information with the most similar arrangement information from the plotting information after excluding the plotting information that served as the reference. Methods for estimating the periodicity of organs.

2. The organ cycle estimated according to the method of claim 1, Based on the aforementioned gene expression information, A method for estimating genes whose expression levels fluctuate in cell types surrounding an organ in accordance with changes in the organ's cycle.

3. Regarding the genes whose expression levels fluctuate in accordance with the changes in the organ cycle estimated by the method of claim 2, The gene expression information mentioned above, The aforementioned arrangement information, A method for estimating the changes in gene expression levels associated with changes in the organ cycle, based on [a specific factor].

4. A method for estimating genes whose expression levels fluctuate in cell types surrounding an organ in accordance with changes in the organ cycle, Sample identification information relating to the identification of the aforementioned cell type, Gene expression information regarding the expression level of genes in the cell type, Arrangement information relating to the relative positional relationship between sample identification information, determined based on the similarity of gene expression information in multiple cell types, The process involves preparing plotting information to which the plotting information is linked, A time-series determination step, which determines the time-series of the plotting information based on the arrangement information, A periodic gene estimation process that estimates genes whose expression levels fluctuate in accordance with changes in the organ cycle, It has, The aforementioned organ is a hair follicle, The aforementioned cycle is the hair cycle, The gene expression information is obtained by subjecting a cell tissue containing the cell type to single-cell RNA sequencing, The aforementioned time series determination process, After performing a runner-up determination process to identify a second plotting information having the arrangement information closest to the first plotting information, based on the arrangement information contained in the first plotting information, This process determines the time series of plotting information by using the plotting information identified in the aforementioned second-place determination process as a reference, and then performing the same second-place determination process as described above, but excluding the plotting information that served as the reference, to identify the plotting information that has the most similar arrangement information. A method for estimating genes whose expression levels fluctuate in the cell types surrounding the organ in accordance with changes in the organ's cycle.

5. A device for estimating the cycle of an organ based on gene expression levels in cell types surrounding the organ, Sample identification information relating to the identification of the aforementioned cell type, Gene expression information regarding the amount of gene expression in the cell type, Arrangement information relating to the relative positional relationship between sample identification information, determined based on the similarity of gene expression information in multiple cell types, A means for preparing plotting information that is linked to the plotting information, A time-series determination means for determining the time-series of the plotting information based on the arrangement information, Based on the results of the time series determination means, a period estimation means for estimating the period of an organ, Equipped with, The aforementioned organ is a hair follicle, The aforementioned cycle is the hair cycle, The gene expression information is obtained by subjecting a cell tissue containing the cell type to single-cell RNA sequencing, The aforementioned time series determination means After performing a runner-up determination process to identify a second plotting information having the arrangement information closest to the first plotting information, based on the arrangement information contained in the first plotting information, This is a means for determining the time series of plotting information by performing a second-place determination process similar to the above, based on the plotting information identified in the second-place determination process, and then identifying the plotting information with the most similar arrangement information from the plotting information after excluding the plotting information that was once used as a reference. A device for estimating the periodicity of organs.

6. A program for estimating the cycle of an organ based on gene expression levels in cell types surrounding the organ, Computers Sample identification information relating to the identification of the aforementioned cell type, Gene expression information regarding the amount of gene expression in the cell type, Arrangement information relating to the relative positional relationship between sample identification information, determined based on the similarity of gene expression information in multiple cell types, A means for preparing plotting information that is linked to the plotting information, A time-series determination means for determining the time-series of the plotting information based on the arrangement information, A period estimation program for organs, which functions as a period estimation means for estimating the period of an organ based on the results of the time series determination means, The aforementioned organ is a hair follicle, The aforementioned cycle is the hair cycle, The gene expression information is obtained by subjecting a cell tissue containing the cell type to single-cell RNA sequencing, The aforementioned time series determination means After performing a runner-up determination process to identify a second plotting information having the arrangement information closest to the first plotting information, based on the arrangement information contained in the first plotting information, This is a means for determining the time series of plotting information by performing a second-place determination process similar to the above, based on the plotting information identified in the second-place determination process, and then identifying the plotting information with the most similar arrangement information from the plotting information after excluding the plotting information that was once used as a reference. A program for estimating the cycle of organs.

Images