JP7355325B2 - Cell lineage generation method, program, and cell lineage generation device - Google Patents

Description

The present invention relates to a cell lineage generation method, a program, and a cell lineage generation device.

In recent years, next-generation sequencer technology has been permeating the medical field. For example, by quantifying the transcripts of genes encoding specific proteins using a next-generation sequencer, the expression level of a specific protein can be estimated, and the estimated expression level of the specific protein can be used to diagnose a patient's condition. Inspection methods and the like to be used have been proposed (for example, see Patent Document 1). Against this background, expectations are increasing for the realization of personalized medicine tailored to each patient's condition.

International Publication No. 2016/181979

By the way, in order to realize personalized medicine, it is necessary to output more detailed information indicating the detailed condition of each patient.

The present invention has been made in view of the above, and provides a cell lineage generation method etc. that can obtain more detailed information.

A cell lineage generation method according to one aspect of the present invention includes a first frequency indicating a frequency of a first mutation, and a second frequency indicating a frequency of a second mutation in a plurality of cells constituting a first tissue of an individual to be analyzed. frequency, and a third frequency indicating the frequency of the third mutation, and a fourth frequency indicating the frequency of the first mutation, and a frequency of the second mutation in a plurality of cells constituting the second tissue of the individual. and a sixth frequency representing the frequency of the third mutation, the sum of the second frequency and the third frequency corresponds to the first frequency, and the sum of the second frequency and the third frequency corresponds to the first frequency, and a determination step of determining whether the sum of the fifth frequency and the sixth frequency corresponds to the fourth frequency, and based on the determination result in the determination step, the first mutation, the second mutation, and the and an analysis step of analyzing a third mutational relationship to generate a cell lineage based on the mutations in the individual's cells.

Further, one embodiment of the present invention can be realized as a program for causing a computer to execute the above cell lineage generation method.

The cell lineage generation device according to one aspect of the present invention also provides a first frequency indicating a frequency of a first mutation and a frequency of a second mutation in a plurality of cells constituting a first tissue of an individual to be analyzed. a second frequency and a third frequency indicating the frequency of the third mutation; a fourth frequency indicating the frequency of the first mutation in a plurality of cells constituting the second tissue of the individual; and a fourth frequency indicating the frequency of the second mutation. an acquisition unit that acquires a fifth frequency indicating the frequency of the third mutation and a sixth frequency indicating the frequency of the third mutation, the sum of the second frequency and the third frequency corresponds to the first frequency, and , a determination unit that determines whether the sum of the fifth frequency and the sixth frequency corresponds to the fourth frequency; and based on the determination result of the determination unit, the first mutation, the second mutation, and an analysis unit that analyzes the relationship between the third mutations and generates a cell lineage based on the mutations made in the cells of the individual.

The cell lineage generation method according to one embodiment of the present invention can obtain more detailed information.

FIG. 1A is a diagram showing the developmental process when a mutation occurs in a gamete. FIG. 1B is a diagram showing the developmental process when a mutation occurs during the process of early development. FIG. 2 is a diagram illustrating mutations used to generate cell lineages. FIG. 3 is a diagram illustrating the distribution of allele frequencies. FIG. 4 is a block diagram showing the functional configuration of the cell lineage generation device according to the embodiment. FIG. 5 is a flowchart showing the operation of the cell lineage generation device according to the embodiment. FIG. 6 is a first diagram showing mutation allele frequencies in multiple tissues according to the example. FIG. 7 is a second diagram showing mutation allele frequencies in multiple tissues according to the example. FIG. 8 is a third diagram showing mutation allele frequencies in multiple tissues according to the example. FIG. 9 is a fourth diagram showing mutation allele frequencies in multiple tissues according to the example. FIG. 10 is a diagram 5 showing mutation allele frequencies in multiple tissues according to the example. FIG. 11 is a schematic diagram showing the concept of cell lineage generation according to the example. FIG. 12A is a first diagram illustrating an algorithm of the cell lineage generation device according to the example. FIG. 12B is a second diagram illustrating the algorithm of the cell lineage generation device according to the example. FIG. 12C is a third diagram illustrating the algorithm of the cell lineage generation device according to the example. FIG. 13 is a diagram illustrating a cell lineage according to an example. FIG. 14 is a diagram illustrating the composition ratio of cells on the cell lineage in each tissue. FIG. 15 is a diagram illustrating an application example of the cell lineage generation method according to the embodiment.

(How the invention came about)
If we can clarify the cell lineage origin of individual cells contained in living tissues, it will be possible to quantitatively understand the state of various diseases and the degree of aging progression. Methods for generating cell lineages are being considered. For example, in the case of women, research has focused on the inactivation of the X chromosome (using the phenomenon in which one X chromosome is randomly inactivated during early development), and has A method has been developed to distinguish whether the origin is derived from a single cell on the cell lineage or is composed of a mixed state derived from multiple cells on the cell lineage. However, this method is only applicable to women, and the resolution of the generated cell lineages is poor. Specifically, in this method, only one of the paternal allele of the X chromosome derived from the father and the maternal allele of the X chromosome derived from the mother can be distinguished. In other words, with this method, only two types of cells can be distinguished, so there are limited cases in which clinically significant information can be obtained. For these reasons, this method has not been widely used in clinical settings.

In recent years, methods have been implemented to generate more detailed cell lineages using next-generation sequencers, but it is necessary to separate cells from a sample into single cells and to separate each cell into a quantity suitable for sequencing. It is necessary to perform sequencing after propagation. When the tissue to be analyzed is a tissue that is difficult to separate into single cells and undergo proliferation operations, this method is difficult to apply and requires enormous effort, time, and cost. Become. For these reasons, this method is also not practical for widespread use in clinical settings.

While there is a need for methods that are more suitable for clinical practice, in experiments using mice, sequencing has been used to efficiently detect mutations that occur at low frequencies in body tissues. We have succeeded in developing a new method that enables the generation of highly accurate cell lineages by using high mutation frequencies (i.e., abundance frequencies). This method is an innovative method that uses mutations that occur during early development as indicators to generate highly accurate cell lineages in any tissue through analysis using a mathematical model.

In this method, mutation frequencies are calculated for mutations that occur at low frequencies in each of multiple body tissues, as obtained by genome sequencing. Through mathematical analysis, we will clarify the genealogy of mutations during early development based on the frequencies obtained in multiple tissues. Thereby, in this method, a cell lineage is generated based on the mutations that occur in the cells of the individual to be analyzed. That is, this method is a method of generating a cell lineage based on the frequency of mutations in a plurality of cells constituting each of two or more tissues of an individual to be analyzed.

This method makes it possible to provide new indicators necessary for diagnosis from a cell lineage-based perspective, as next-generation sequencer technology is increasingly pervasive in clinical practice.

According to this method, for example, the limitations of conventional methods such as methods using inactivation of the X chromosome as an indicator can be dramatically improved, and the status of cell lineage can be clarified in more detail. In this way, the detailed status of cell lineage revealed can be used as a marker to clearly understand cell dynamics in body tissues (such as disease-related tissues) as the frequency of individual mutations. can. For example, in anticancer drug treatment, after the anticancer drug is administered and a population of cancer cells is killed, it becomes possible to track the tissue recovery process due to cell proliferation. In such an example, it is thought that determining whether there is an abnormality in the recovery process can provide useful information for determining a treatment policy. Furthermore, for example, it becomes possible to accurately grasp the proliferation of a single cell in the cell lineage, which is considered to be a cause of aging.

As exemplified above, by clarifying the status of cell lineage in more detail, it is possible to determine whether the symptoms of the disease are appropriately recovering (e.g., to a healthy state) through the treatment method applied to the patient. Cell lineage can also be used as an index to determine whether or not the disease occurs.

Hereinafter, embodiments will be specifically described with reference to the drawings. Note that the embodiments described below are all inclusive or specific examples. The numerical values, shapes, materials, components, arrangement positions and connection forms of the components, steps, order of steps, etc. shown in the following embodiments are merely examples, and do not limit the present invention. Further, among the constituent elements in the following embodiments, constituent elements that are not described in the independent claims will be described as arbitrary constituent elements.

Note that each figure is a schematic diagram and is not necessarily strictly illustrated. Further, in each figure, substantially the same configurations are denoted by the same reference numerals, and overlapping explanations may be omitted or simplified.

(Embodiment)
[overview]
First, an overview of the present invention will be explained using FIGS. 1A to 3. FIG. 1A is a diagram showing the developmental process when a mutation occurs in a gamete. Further, FIG. 1B is a diagram showing the developmental process when a mutation occurs during the initial developmental process.

In this embodiment, a cell lineage is generated based on the frequency of mutations in a plurality of cells constituting each of two or more tissues including a first tissue and a second tissue of an individual to be analyzed. .

In the following description, the second organization is a different organization from the first organization, and two or more organizations including the first organization and the second organization are each different organizations, but the present invention is not limited to this. The first organization and the second organization may be the same organization. For example, from each of two or more tissues including a first tissue and a second tissue obtained by collecting the same tissue at two or more different time points, based on the frequency of mutations in cells constituting the tissue, Cell lineages may also be generated.

Furthermore, the present invention can generate a cell lineage even from cells constituting a single tissue, as long as the frequency of mutations is calculated with high accuracy. Therefore, the first organization and the second organization may be the same single organization. For example, if a new sequencing or mutation frequency calculation method that can calculate the mutation frequency of individual cells with high precision emerges due to advances in technology or other derivative technologies, it will naturally be possible to use that method to easily calculate the mutation frequency of individual cells. A mutation frequency may be calculated from a plurality of cells constituting one tissue, and a cell lineage may be generated using the frequency.

According to this, it is determined whether the sum of the second frequency and the third frequency corresponds to the first frequency and the sum of the fifth frequency and the sixth frequency corresponds to the fourth frequency. It can be determined only by whether the sum of and the third frequency corresponds to the first frequency. Therefore, the present invention can be implemented more easily. Further, since only one tissue needs to be collected from an individual to be analyzed, the present invention can be used in clinical settings as a less invasive testing method.

As shown in FIG. 1A, if a mutation occurs in any of the gametes, the fertilized egg that is formed will carry the mutation that occurred in the gamete. Specifically, in the case of a diploid organism, the chromosomes of a fertilized egg include pairs of homologous chromosomes derived from each gamete, depending on the species. Among these pairs of homologous chromosomes, a pair of homologous chromosomes including a chromosome without a mutation and a chromosome with a mutation derived from a gamete is included. The figure shows pairs of such homologous chromosomes. These pairs of homologous chromosomes are passed on to the next generation of cells during the division process, so the ratio of chromosomes without mutations to chromosomes with mutations is always 1:1 in all somatic cells. Yes, the mutation frequency is 50%. Therefore, as shown in the figure, the mutation-based phenotype is uniformly expressed in cells throughout the individual's body.

On the other hand, as shown in Figure 1B, if a mutation occurs in only one of the two cells generated by division from the fertilized egg in a cell that did not have a mutation until it formed a fertilized egg, the One cell contains a pair of homologous chromosomes, one without a mutation and one with a mutation. Furthermore, the other of the two cells contains a pair of homologous chromosomes, neither of which has a mutation. Therefore, for example, if subsequent cell cycles were uniform, the ratio of chromosomes without mutations to chromosomes with mutations in all somatic cells would always be 3:1, and the frequency of mutations would be is 25%. In a tissue that is derived from a cell containing a chromosome with a mutation and has divided, a phenotype based on the mutation is expressed in a mosaic pattern in a portion of the individual, as shown in the figure.

The present invention discloses a method of generating a cell lineage using the probability of existence (hereinafter also referred to as mutation frequency or allele frequency), which is the proportion of chromosomes having a mutation, which varies depending on the timing at which the mutation occurs. It is something to do. In addition, below, a mutation may be explained simply as a mutation.

FIG. 2 is a diagram illustrating mutations used to generate cell lineages. FIG. 2 shows part of the results of genome sequencing for a plurality of cells collected from a specific tissue and making up the tissue. In FIG. 2, a reference sequence and a plurality of partial sequences read as a result of genome sequencing are shown at corresponding locations on the reference sequence. The reference sequence is shown at the top of the figure as a string of four characters based on the base portion of DNA (DeoxyriboNucleic Acid): adenine (A), thymine (T), guanine (G), and cytosine (C). There is.

In addition, rectangles extending to the left and right below the reference sequence in the figure each indicate the sequence of the genome sequence result. Note that the read array is not written as a character string, and only indicates whether it can be read or not. Specifically, in the figure, the read area, which is the area where the sequence was read, is shown as a hatched rectangle, and the non-read area, which is the area where the sequence was not read, is shown with a dashed white outline. Shown as a rectangle. In the figure, 15 partial sequences have been read out, of which 12 partial sequences have been read out, including the sequence at the mutation location indicated by the arrow in the center of the figure. At the mutation site, C is shown in the reference sequence, whereas T is shown in some of the read partial sequences. That is, at this mutation site, the originally sequenced C is mutated and changed to T.

The frequency of such mutations is the number of mutations occurring relative to the number read out including the sequence at the mutation site. That is, in the example shown in the figure, when expressed as a percentage, it is 7 (number of T's) x 100/12 (number of T's + number of C's) = approximately 58%. In this embodiment, generation of a cell lineage using mutation frequency based on a single nucleotide change in DNA will be described.

In addition, in this embodiment, the mutation is not limited to a change in one nucleotide as described above, but may be a change in a plurality of nucleotides such as an oligonucleotide or a gene unit. Furthermore, the change due to mutation may be a nucleotide substitution as described above, or may be a deletion or insertion. Insertions may be specified, for example, as changes in nucleotide copy number. Therefore, the mutation frequency may be calculated using an appropriate formula depending on the form of the mutation.

FIG. 3 is a diagram illustrating the distribution of allele frequencies. FIG. 3 is a graph showing the number of mutations at each allele frequency when mutations are classified into allele frequencies of 5% for a specific individual. In FIG. 3, the horizontal axis shows the allele frequency as a percentage, and the vertical axis shows the number of mutations as a relative number when the highest value is 100%.

As shown in FIG. 3, the mutations in a particular individual include the most mutations with an allele frequency of 100%. This indicates a homozygous mutation in which the same mutation occurred in each gamete that formed the fertilized egg. On the other hand, a mutation that follows a binomial distribution with a peak allele frequency of 50% indicates a heterozygous mutation 102 in which the mutation has occurred in any of the gametes that form the fertilized egg. Note that the heterozygous mutation 102 also includes the example described using FIG. 1A. Additionally, there are relatively few mutations at locations with allele frequencies less than 50%. This relatively small number of mutations represents mosaic mutations 101, including the example described using FIG. 1B.

In this embodiment, a cell lineage is generated using the allele frequency of mosaic mutation 101. The mosaic mutation 101 may be one that shows an allele frequency of less than 50%, but as shown in Figure 3, since the number of mosaic mutations 101 is small compared to other mutations, it is a heterozygous mutation. From the standpoint of separability with 102, a more accurate cell lineage can be generated by using mosaic mutations that exhibit an allele frequency of less than 40%. The allele frequency threshold of the mosaic mutation 101 used to generate the cell lineage may be set as appropriate depending on the accuracy of the sequencer, cell conditions, and the like.

[Configuration of cell lineage generation device]
Hereinafter, the configuration of the cell lineage generation device in this embodiment will be explained using FIG. 4. FIG. 4 is a block diagram showing the functional configuration of the cell lineage generation device according to the embodiment. In FIG. 4, various peripheral devices are illustrated together with the cell lineage generation device 100.

The cell lineage generation device 100 in this embodiment generates a genealogy based on the frequency of mutations in a plurality of cells constituting each of two or more tissues including a first tissue and a second tissue of an individual to be analyzed. Generate cell lineages.

The cell lineage generation device 100 includes an acquisition unit 11, a determination unit 13, and an analysis unit 15. It may be realized as a computer including a stored memory and a circuit that executes the program.

The acquisition unit 11 is connected to a mutation frequency calculation device 203 that calculates the frequency of mutations occurring in a DNA sequence obtained from cells of an individual to be analyzed and read by a sequencer 201.

The sequencer 201 is a device that uses a nucleic acid sample extracted from a plurality of cells constituting the tissue of an individual to be analyzed to read out (sequence) the DNA sequence contained in the cells. The sequencer 201 may have any configuration as long as it can perform sequencing using a nucleic acid sample, and the measurement principle, device configuration, etc. are not particularly limited. The sequencer 201 transmits the DNA sequence read as a result of sequencing to the mutation frequency calculation device 203.

The mutation frequency calculation device 203 is a device that calculates the frequency of mutations contained in the sequence based on the read DNA sequence. The mutation frequency calculation device 203 is realized, for example, as a computer including a circuit and a memory in which a program related to mutation frequency calculation is stored. As described using FIG. 2, the mutation frequency calculation device 203 detects locations where the received DNA sequence corresponds to a reference sequence obtained in advance. The mutation frequency calculation device 203 further identifies a mutation location where a mutation has occurred in the received DNA sequence by comparing it with a reference sequence, and calculates the mutation frequency at the mutation location.

In the present embodiment, the mutation frequency calculation device 203 calculates the first mutation, which is a mutation, The frequencies of the second mutation and the third mutation are calculated. The mutation frequency calculated by the mutation frequency calculation device 203 is acquired by the acquisition unit 11 connected to the mutation frequency calculation device 203.

That is, the acquisition unit 11 obtains a first frequency indicating the frequency of the first mutation, a second frequency indicating the frequency of the second mutation, and a third frequency in the plurality of cells constituting the first tissue of the individual to be analyzed. A third frequency indicating the frequency of mutation is obtained. The acquisition unit 11 also acquires a fourth frequency indicating the frequency of the first mutation, a fifth frequency indicating the frequency of the second mutation, and a third frequency indicating the frequency of the third mutation in the plurality of cells constituting the second tissue. 6 Get the frequency. The acquisition unit 11 is a processing unit that acquires the mutation frequency calculated by the mutation frequency calculation device 203 in this manner. The acquisition unit 11 transmits the acquired mutation frequency to the determination unit 13.

The determination unit 13 is a processing unit that determines whether a predetermined condition is satisfied based on the mutation frequency acquired by the acquisition unit 11. Specifically, the determination unit 13 determines whether the sum of the second frequency and the third frequency corresponds to the first frequency, and the sum of the fifth frequency and the sixth frequency corresponds to the fourth frequency. Determine. The determination unit 13 transmits the determination results based on the first to sixth frequencies to the analysis unit.

The analysis unit 15 analyzes the relationship between the first mutation, the second mutation, and the third mutation based on the determination result by the determination unit 13, and generates a cell lineage based on the mutation in the cells of the individual to be analyzed. This is the processing section. For example, the sum of the frequency of the second mutation and the frequency of the third mutation and the frequency of the first mutation match in multiple tissues including the first tissue and the second tissue (however, allowing for measurement errors in sequencing) ), it can be assumed that the second mutation and the third mutation originate from the first mutation and are complementary to each other. In other words, the first cell having the first mutation, the second cell having the second mutation, and the third cell having the third mutation form a first branch that branches from the first cell to the second cell or the third cell. It is estimated that there is a point relationship.

Note that the first cell, second cell, and third cell are concepts that indicate the classification of cells that have different types of mutations. In other words, the cell lineage generated in this embodiment can also be read as a branching classification diagram of mutations, in which the branching classification is performed using change points at which mutation variations change as branching points.

The cell lineage generated as a result of the analysis by the analysis unit 15 is output to the output unit 205 and presented to the user of the cell lineage generation device 100.

The output unit 205 is, for example, a display device such as a display, and can allow the user to visually recognize the cell lineage by presenting the cell lineage generated in the analysis unit 15 as an image.

Note that the acquisition unit 11, the determination unit 13, and the analysis unit 15 may be realized individually or may be integrated. In other words, the acquisition unit 11, the determination unit 13, and the analysis unit 15 may be implemented in a single configuration, for example, as one program.

[Operation of cell lineage generation device]
The operation of the cell lineage generation device 100 will be described below using FIG. 5. FIG. 5 is a flowchart showing the operation of the cell lineage generation device according to the embodiment.

The acquisition unit 11 of the cell lineage generation device 100 in this embodiment first acquires a plurality of mutation frequencies including the first to sixth frequencies from the mutation frequency calculation device 203 (S101). Further, the acquisition unit 11 obtains a first unattributed frequency indicating the frequency of the fourth mutation in the plurality of cells constituting the first tissue, and a frequency of the fourth mutation in the plurality of cells constituting the second tissue. A second unattributed frequency indicating ? is obtained from the mutation frequency calculation device 203 (S102).

Here, the determining unit 13 determines whether the sum of the acquired second frequency and third frequency matches the first frequency (S103). If the determining unit 13 determines that the sum of the second frequency and the third frequency does not match the first frequency (No in S103), the cell lineage generation device 100 ends the process. On the other hand, if the determining unit 13 determines that the sum of the second frequency and the third frequency matches the first frequency (Yes in S103), the determining unit 13 further determines that the sum of the second frequency and the third frequency matches the first frequency (Yes in S103). It is determined whether the sum with the frequency matches the fourth frequency (S104). If the determining unit 13 determines that the sum of the fifth frequency and the sixth frequency does not match the fourth frequency (No in S104), the cell lineage generation device 100 ends the process.

On the other hand, if the determining unit 13 determines that the sum of the fifth frequency and the sixth frequency matches the fourth frequency (Yes in S104), the analyzing unit 15 selects the first cell having the first mutation from the first cell. The relationship between the first branching point that branches into the second cell having the second mutation and the third cell having the third mutation is determined (S105). In other words, if it is determined that the sum of the second frequency and the third frequency corresponds to the first frequency, and the sum of the fifth frequency and the sixth frequency corresponds to the fourth frequency (Yes in S103 and S104 (Yes), the first cell, the second cell, and the third cell are determined to have a first branch point relationship.

The analysis unit 15 generates a cell lineage so as to match the relationship of the first branch point determined in this way (S106). For example, if there are more than three cells with different mutation variations among cells obtained from an individual to be analyzed, the analysis unit 15 selects the first branch point from among the more than three cells. A cell lineage may be generated by specifying three cells having this relationship and defining the direction of branching. Furthermore, when a plurality of such first branching point relationships are identified, a cell lineage that matches all of the plurality of first branching point relationships may be generated. That is, more than three cell lineages may be generated from the relationship of the first branch point.

Next, the cell lineage generation device 100 further updates the cell lineage using the first unattributed frequency and the second unattributed frequency acquired by the acquisition unit 11, thereby generating a cell lineage including more branching information. do. Here, the relationship between the second branching point, where the cell at the end of the cell lineage branches to the cell having the fourth mutation, is determined based on the magnitude relationship of mutation frequencies.

The analysis unit 15 compares the frequency of mutations in the fifth cell, which is a plurality of branch end cells of the cell lineage generated in step S106, with the frequency of the fourth mutation. Specifically, the analysis unit 15 calculates, for the branch end mutation possessed by each of the plurality of fifth cells, a first terminal frequency indicating the frequency in the plurality of cells constituting the first tissue and a first unassigned frequency. It is determined whether the first difference frequency, which is the difference, is greater than zero. That is, the analysis unit 15 determines whether the first terminal frequency is greater than the first unattributed frequency. In addition, the analysis unit 15 calculates the difference between a second terminal frequency indicating the frequency in a plurality of cells constituting the second tissue and a second unattributed frequency for the branch end mutation possessed by each of the plurality of fifth cells. It is determined whether the second difference frequency is greater than zero. That is, the analysis unit 15 determines whether the second terminal frequency is greater than the second unattributed frequency.

In this way, the analysis unit 15 determines that the branch end mutation for which the first difference frequency is greater than 0 and the second difference frequency is greater than 0 is only one of the plurality of branch end mutations. It is determined whether or not it is determined (S107). If the first difference frequency is larger than 0 and the second difference frequency is larger than 0 among the plurality of branch end mutations is not determined to be only one branch end mutation (No in S107), the cell lineage generation device 100 ends the process. On the other hand, if only one branch-end mutation with a first difference frequency greater than 0 and a second difference frequency greater than 0 is determined among the plurality of branch-end mutations (Yes in S107), the analysis unit No. 15 determines that the fourth cell having the fourth mutation and the fifth cell have a relationship of a second branching point that branches from the fifth cell to the fourth cell. At this time, in the relationship of the second branch point described above, a cell having a mutation variation that is paired with the fourth cell is not specified. In order to generate a cell lineage with more branches and over multiple generations, a sixth cell to be paired with the fourth cell may be provisionally set. That is, it is determined that the fourth cell, the fifth cell, and the sixth cell have a relationship of a second branching point where the fifth cell branches into the fourth cell or the sixth cell (S108). The sixth cell has a pseudo frequency in which the frequency in the plurality of cells constituting the first tissue is the first differential frequency, and the frequency in the plurality of cells constituting the second tissue is the second differential frequency. .

Note that in such a comparison of magnitude relationships, measurement errors in sequencing may be allowed. In other words, even if the first differential frequency or the second differential frequency is 0 or less as a numerical value, when considering the error range, if the first differential frequency or the second differential frequency includes a range larger than 0, then The above determination conditions may be satisfied.

The analysis unit 15 updates the cell lineage generated to match the relationship of the first branch point so as to further match the relationship of the second branch point determined in this manner, and creates a new cell lineage. is generated (S109). For example, in the explanation of the relationship at the first branch point, among the first cell, second cell, and third cell, the second mutation and the third mutation that the second cell and the third cell have, respectively, are expressed as the second mutation and the third mutation in the cell at the branch end. The process from step S107 onwards is executed by regarding this as a branch end mutation that has a branch end mutation. Thereby, a cell lineage that also matches the relationship of the second branching point branching from either the second mutation or the third mutation to the fourth cell or the sixth cell may be generated. This may generate a cell lineage spanning two branches and three generations.

[Example]
Hereinafter, this embodiment will be described in more detail using Examples.

FIG. 6 is a first diagram showing mutation allele frequencies in multiple tissues according to the example. In this example, a mouse is used as an individual to be analyzed. As shown in Figure 6, multiple tissues include the cerebrum, cerebellum, shoulder skin, buttock skin, stomach, lungs, liver, intestines, pancreas, quadriceps, tongue, heart, spleen, kidney, and secretory glands. , testis, and tail were used. Tissue pieces were collected from each of these multiple tissues, and sequencing was performed using multiple cells constituting the tissue pieces. Within the obtained DNA sequence, 31 mosaic mutations 101 and 2 heterozygous mutations 102 were found. In the figure, for each mutation, allele frequencies in each of a plurality of tissues are connected and shown as a curve of allele frequency for each mutation.

In FIG. 6, a correction process is first applied to the mutation frequency calculated by the mutation frequency calculation device 203. Specifically, using the following equation (1), components such as additive errors that may be uniformly included in the calculated mutation frequency are subtracted, and the percentage is converted into a decimal representation.

Note that X _{m, n, raw} is raw data of the frequency of mutation m in tissue n, calculated by the mutation frequency calculation device 203. As described above, the raw data is a 100% numerical value that may include additive errors for each mutation m. Therefore, the component X _m,ctrl such as the additive error calculated using the control group according to the above equation (1) is subtracted. Furthermore, for mutations occurring on sex chromosomes, since there are no homologous chromosomes, the frequency is calculated to be twice that of the original. Therefore, for mutations occurring on these sex chromosomes, raw data that has been corrected in half is calculated in advance.

Here, if the corrected frequency is lower than a predetermined value, the mutation indicating the frequency is excluded from subsequent processing. Specifically, a predetermined value is set to exclude frequencies at a level that cannot be distinguished from measurement errors of the sequencer 201, etc., and mutations are excluded using the predetermined value. Therefore, the predetermined value may be set as appropriate depending on the performance of the sequencer 201 used in the measurement, the measurement conditions, and the like.

In addition, in the subsequent data processing, for convenience, a heterozygous mutation 102 (that is, a mutation whose mutation frequency in all tissues can be considered to be 0.5) is included. A cell having such a heterozygous mutation 102 is positioned as the "root" of the cell lineage above all cells having the mosaic mutation 101. Therefore, when a cell lineage is automatically generated, by including cells with a heterozygous mutation 102, theoretically, if there are no errors, the branching relationships of cell lineages with all mosaic mutations 101 can be calculated. can be identified and a single cell lineage generated.

Among the multiple mutations shown in FIG. 6, there are mutations that exhibit approximately the same allele frequency in all of the multiple tissues. These mutations are expected to occur at the same timing. Therefore, if these mutations are treated as mutations in different cells, inconsistencies in the cell lineage may occur, such as the existence of a branch point relationship where one cell branches into three or more cells. Therefore, in order to handle these mutations in an integrated manner, we perform a process of clustering mutations that exhibit approximately the same allele frequency in any of a plurality of tissues.

At this time, the following equation (2) is used to quantify the similarity of allele frequencies between sudden frequencies.

Note that N is the number of target tissues used in the cell lineage generation method, including the first tissue and the second tissue among the plurality of tissues of the individual. Also, X _{i, ave.} is the average frequency of mutation i in a plurality of cells constituting the target tissue. Also, X _{ii, ave.} is the average frequency of mutation ii in a plurality of cells constituting the target tissue. Moreover, X _i,n is the frequency of the i-th mutation in a plurality of cells constituting the n-th (n is a positive integer) tissue. Moreover, X _ii,n is the frequency of the ii mutation in a plurality of cells constituting the n th tissue.

The larger the value obtained in the above formula (2), the smaller the difference in allele frequency between mutation i and mutation ii in the target tissue. Therefore, by making a determination using a threshold value, it can be determined whether or not mutation i and mutation ii are classified into the same cluster. More specifically, two mutations are used as mutation i and mutation ii, and when the value obtained in the above formula (2) is equal to or greater than a threshold value, the two mutations are classified into the same cluster. On the other hand, when two mutations are used as mutation i and mutation ii, and the value obtained in the above equation (2) is smaller than the threshold value, the two mutations are classified into different clusters. In this way, clustering can be performed in a brute force manner using mathematical formulas, and all mutations can be automatically classified into clusters.

If the threshold used here is too large, mutations that should be classified into the same cluster will be classified into different clusters. Furthermore, if the threshold is too small, mutations that should be classified into different clusters will be classified into the same cluster. Therefore, the threshold used here needs to be set appropriately. However, an appropriate value cannot be uniquely determined depending on the performance of the sequencer 201 and the like. Therefore, after setting several threshold values and applying subsequent processing to each, an appropriate threshold value may be determined based on the results.

Note that multiple mutations classified into the same cluster are treated as one mutation in subsequent processing. In other words, a mutation may be a cluster, which is a collection of multiple mutations. Therefore, the mutation frequency handled in subsequent processing is replaced by the following equation (3).

Note that M _i,num is the number of mutations m classified into cluster M _i . Moreover, X _m,n is the frequency of each mutation m in the nth tissue. That is, in the n-th tissue, the frequency in the set of mutations indicated by cluster M _i is represented by the average frequency of mutations m classified into cluster M _i in the n-th tissue. Note that even if the mutation m is an independent mutation that does not constitute a cluster, the above equation (3) holds true. Therefore, the above equation (3) can be applied to all clusters by treating independent mutations as a cluster M _i in which the classified mutation m is one. Further, in view of processing speed, the above equation (3) may be applied only to clusters M _i in which mutation m is 2 or more.

As described above, in this example, it is assumed that multiple mutations forming a cluster occur at the same timing in the cell lineage, and the average frequency of these multiple mutations is calculated as follows: Use. In other words, in the description of the above embodiment, at least one of the first mutation, second mutation, third mutation, and fourth mutation is a cluster (mutation cluster) composed of a set of a plurality of mutations. It may be. In other words, the mutational variation described above may be a combination of multiple mutations. In this case, the frequency of the first mutation, second mutation, third mutation, or fourth mutation that is a mutation cluster may be the average value of the frequencies of each of the plurality of mutations in the set that constitutes the mutation cluster.

According to this, it is possible to generate a cell lineage in which mutations that occur at the same timing on the cell lineage are treated integrally. There is no need to use individual mutations for calculations, and the amount of processing required to generate cell lineages can be reduced. Further, errors that may occur in the external environment related to mutation frequency calculation, such as the sequencer 201 and the mutation frequency calculation device 203, can be reduced, and a cell lineage can be generated with higher accuracy.

FIG. 7 is a second diagram showing mutation allele frequencies in multiple tissues according to the example. FIG. 7 illustrates mutation 30, which is one of the heterozygous mutations 102, and mutations 31 and 33, which are two mosaic mutations, among the mutations shown in FIG. Illustration is omitted. Further, in FIG. 7, a virtual frequency 35 obtained by adding the allele frequencies of the mutations 31 and 33 is also illustrated with a thick line. As shown in FIG. 7, the virtual frequency 35 almost matches the mutation 30. That is, it can be seen that the sum of the frequency of mutation 31 and the frequency of mutation 33 matches the frequency of mutation 30 in each of the plurality of tissues. In other words, the three frequencies have a sum relationship shown in equation (4) below.

Note that X _1,n is the (1+3(n-1))th frequency indicating the frequency of the first mutation in a plurality of cells constituting the nth tissue. Further, X _2,n is the (2+3(n-1))th frequency indicating the frequency of the second mutation in a plurality of cells constituting the nth tissue. Further, X _3,n is the (3+3(n-1))th frequency indicating the frequency of the third mutation in a plurality of cells constituting the nth tissue.

Thereby, it can be determined that the relationship between the cell having mutation 30, the cell having mutation 31, and the cell having mutation 33 is the first branch point relationship described above.

FIG. 8 is a third diagram showing mutation allele frequencies in multiple tissues according to the example. In FIG. 8, among the mutations in FIG. 6, three mosaic mutations, mutation 33, mutation 37, and mutation 39, are illustrated, and illustration of the other mutations is omitted. Further, in FIG. 8, a virtual frequency 41 obtained by adding the allele frequencies of mutation 37 and mutation 39 is also illustrated with a thick line. As shown in FIG. 8, the virtual frequency 41 almost matches the mutation 33. That is, it can be seen that the sum of the frequency of mutation 37 and the frequency of mutation 39 matches the frequency of mutation 33 in each of the plurality of tissues. Thereby, it can be determined that the relationship between the cell having mutation 33, the cell having mutation 37, and the cell having mutation 39 is the relationship of the first branch point described above.

As explained using FIGS. 7 and 8, the relationship between cells having mutation 30, cells having mutation 31, cells having mutation 33, cells having mutation 37, and cells having mutation 39 is This can be explained using a cell lineage that matches the relationship of one branch point. That is, a cell having mutation 30 branches into a cell having one of mutation 31 and mutation 33, and a cell having mutation 33 branches into a cell having one of mutation 37 and mutation 39.

Hereinafter, a cell lineage having more detailed information is generated based on the second branch point relationship obtained using the magnitude relationship of mutation frequencies as described in the above embodiment. Specifically, when focusing on one mutation, among the combinations of that one mutation and other mutations, there is only one other mutation in the combination that has the relationship of formula (5) below. Identify combinations.

Note that X _4,n is a first unattributed frequency indicating the frequency of the fourth mutation in a plurality of cells constituting the n-th tissue. Moreover, X _5,n is the first terminal frequency indicating the frequency of branch-end mutations in a plurality of cells constituting the n-th tissue. For each of the plurality of tissues, if there is only one branch end mutation that satisfies the above formula (5) in the fourth mutation, the cell having the fourth mutation and the cell having the branch end mutation are in the second branch. It is determined that the points have a relationship. In other words, if any one of the multiple tissues has the relationship of formula (6) below, the cell with the fourth mutation and the cell with the branch-end mutation have the relationship of the second branch point. Decide not to.

Hereinafter, the search for the relationship of the second branch point will be explained in more detail.

First, among the cell lineage generated based on the above first branch point relationship, each of the branch end cells located at the plurality of ends branched from the "root" cell having the heterozygous mutation 102. Let the plurality of branch end mutations possessed by the leaf be a set of "leaves" (L). Therefore, the set of "leaves" includes a plurality of branch-end mutations (l) that each of the branch-end cells has. In addition, in the generated cell lineage, mutations that are not included in the lineage branched from the ``root'' and have no branching point relationship with higher-level cells are ``isolated''. (O). Therefore, the "orphan" set includes multiple mutations (o) including the fourth mutation. Here, o is selected from among O for which the value obtained by the following equation (7) is maximum.

Note that X _o,n is the frequency of o in a plurality of cells constituting the n-th tissue. In other words, o selected here is a mutation thought to be possessed by a cell located at the highest position in the cell lineage among O. In other words, although the relationship of the second branch point holds true, in order not to select a cell in which another cell can be inserted in between on the cell lineage, o is selected that can take the maximum value in the above equation (7).

The frequency of o selected here and the frequency of each of the plurality of l's are compared using the following equation (8).

Note that X _l,n is the frequency of l in a plurality of cells constituting the n-th tissue. Moreover, X _o,n is the frequency of o in a plurality of cells constituting the n-th tissue.

If the value obtained by the above equation (8) exceeds the threshold value for all n-th organizations, the corresponding l is added to the set of parent candidates of the selected o. Specifically, the value obtained by the above equation (8) is the difference frequency between the frequency of l and the frequency of o in each of the n-th tissues. For example, when o is the fourth mutation, the first differential frequency, which is the differential frequency between the first terminal frequency and the first unattributed frequency, in the first tissue, and the second A differential frequency is obtained for each of the n-th organizations, including a second differential frequency that is a differential frequency between the second terminal frequency and the second unattributed frequency in the organization.

Further, the above threshold value is a value for allowing measurement errors such as sequencing. Therefore, in an ideal system in which such an error can be ignored, 0 is set as the threshold value. For example, when o is the fourth mutation, the differential frequencies in each of the n-th tissues, including the first differential frequency and the second differential frequency, all have a value greater than zero. However, in reality, the difference frequency may take a negative value due to a measurement error in sequencing, etc., so a negative threshold value is set in consideration of the measurement error and the like. For example, in this embodiment, −0.01 is set as the threshold value.

After completing the comparison between the frequency of l and the frequency of o using the above formula (8) for all of the plural l's, count the number of elements in the set of parent candidates and determine if the number of the element is 1. In this case, it is determined that the cell having l included in the set of parent candidates and the selected cell having o have a second branching point relationship. The cell lineage is updated and recreated to match the determined second branch point relationship. In addition, at this time, using l included in the set of parent candidates and the selected o, a "pseudo" which indicates the differential frequency in each of the n-th organization calculated using the above formula (8) is calculated. ” mutation (p: pseudomutation) is added to the second branch point relationship between the cell having o and the cell having l. Specifically, the relationship is a second branch point where a cell having l branches to a cell having o or a cell having p.

After that, o selected from O is deleted, l included in the set of parent candidates is deleted from L, and o and p are newly added to L. Note that the number of elements in the set of parent candidates is counted, and if the number of elements is 0 or 2 or more, o selected from O is deleted. This is done in order to not update the cell lineage and move on to the process for the next o when l that has a second branching point relationship with the selected o cannot be identified. The above process is repeated until O becomes an empty set.

FIG. 9 is a fourth diagram showing mutation allele frequencies in multiple tissues according to the example. In FIG. 9, among the mutations in FIG. 6, four mosaic mutations, mutation 31, mutation 37, mutation 39, and mutation 43, are illustrated, and illustration of the other mutations is omitted. Mutation 31, mutation 37, and mutation 39 are branch-end mutations in the cell lineage, as described above. Among these, mutation 31 is the only mutation that shows an allele frequency higher than that of mutation 43 in any tissue (that is, the difference frequency is >0). Therefore, it can be determined that the relationship between the cell having mutation 31 and the cell having mutation 43 is the second branch point relationship described above.

Here, FIG. 10 is a fifth diagram showing mutation allele frequencies in a plurality of tissues according to the example. In FIG. 10, among the mutations shown in FIG. 6, pseudo-mutation 45 having a differential frequency that is the difference between the allele frequency of mutation 31 and the allele frequency of mutation 43 is shown in bold lines for each mutation shown in FIG. It shows. Although mutations with such a differential frequency were not observed experimentally, cells with pseudo mutations could be used in subsequent analyzes as paired cells with cells with mutation 43 at the second branch point. good.

FIG. 11 is a schematic diagram showing the concept of the content explained using FIGS. 6 to 10. The circles in FIG. 11 indicate cells having individual mutational variations, and the arrows indicate parent-child relationships in the cell lineage. In other words, it shows that the cell lineage generation progresses from the cell at the base of the arrow to the cell at the tip of the arrow. Note that the 31 mutations observed in Examples include mutations in which multiple mutations occur simultaneously (that is, the same allele frequency is shown in any tissue). Therefore, in FIG. 11, cells with fewer mutational variations are shown for 31 mutations.

As shown in FIG. 11(a), a cell lineage of five cells is first generated based on the relationship of the first branch point. Subsequently, as shown in FIG. 11(b), a cell lineage including the sixth cell is generated based on the relationship of the second branch point. Furthermore, as shown in FIG. 11(c), a cell may be generated that pairs with the cell at the branch destination in the relationship of the second branch point.

Furthermore, an algorithm for more accurately and efficiently generating a cell lineage will be described using FIGS. 12A, 12B, and 12C. FIG. 12A is a first diagram illustrating an algorithm of the cell lineage generation device according to the example. FIG. 12B is a second diagram illustrating the algorithm of the cell lineage generation device according to the example. FIG. 12C is a third diagram illustrating the algorithm of the cell lineage generation device according to the example. As exemplified in this example, in actual use of the cell lineage generation device, it is necessary to specify the relationship of the first branch point among cells having a large number of mutational variations. Therefore, if the method of examining the sum of mutation frequencies for each of the three cells as described above is automated, a cell lineage can be generated more efficiently.

Therefore, the relationship between the first branch points may be automatically specified using the following equation (9), and the cell lineage may be generated.

Note that N is the number of target tissues used in the cell lineage generation method, including the first tissue and the second tissue among the plurality of tissues of the individual. Also, X _{2, ave.} is the average frequency of the second mutation in a plurality of cells constituting the target tissue. Also, X _{3, ave.} is the average frequency of the third mutation in a plurality of cells constituting the target tissue. Further, X _1,n is the (1+3(n-1))th frequency indicating the frequency of the first mutation in a plurality of cells constituting the nth tissue. Further, X _2,n is the (2+3(n-1))th frequency indicating the frequency of the second mutation in a plurality of cells constituting the nth tissue. Further, X _3,n is the (3+3(n-1))th frequency indicating the frequency of the third mutation in a plurality of cells constituting the nth tissue.

Using the above formula, for three cells with three specific mutations, the value obtained by subtracting the sum of the frequencies of two of the three mutations from the frequency of the remaining one mutation is calculated as the average value for each tissue. It can be calculated using the residual sum of squares as a value. In other words, the smaller the value obtained by the above equation, the more it can be considered that the three specific cells have a first branching point relationship. That is, a predetermined threshold value may be set, and the relationship of the first branch point may be established by comparing the value obtained by the above equation with the predetermined threshold value.

Here, FIG. 12A shows a cell lineage 103a in an example where a contradiction in the cell lineage occurs because the predetermined threshold value is too large. Conflicts in cell lineages include, for example, the existence of a branch point relationship where one cell branches into three or more cells, or a confluence relationship where two or more cells merge into one cell. The existence of In FIG. 12A, it can be seen that the predetermined threshold value is inappropriate because such a contradiction occurs. On the other hand, FIG. 12C shows a cell lineage 103b in an example where the cell lineage was not appropriately generated because the predetermined threshold value was too small. If the predetermined threshold value is too small, for example, even measurement errors in sequencing are excluded, so that only a small portion of the relationship between the first branch points between cells can be determined.

Therefore, the predetermined threshold value is preferably the maximum value that does not cause the above-mentioned contradiction. That is, by tentatively setting a predetermined threshold value to a value that is sufficiently larger than the value that can be taken by the above formula, and gradually decreasing the predetermined threshold value, the value when the contradiction in the cell lineage disappears is determined by the predetermined value. It may be determined as a threshold value.

In this example, for example, a predetermined threshold value α was initialized to 0.01 (α=0.01), and the presence or absence of the above-mentioned contradiction was determined in the generated cell lineage 103a. After that, if it is determined that the above-mentioned contradiction exists in the cell lineage 103a, a value obtained by subtracting 0.00025 from the predetermined threshold value is set as a new predetermined threshold value (α=α−0.00025), and the value is set again. , the presence or absence of the above contradiction was determined. When it was determined that there was no contradiction as described above in the cell lineage 103, a predetermined threshold value was determined, and the process was terminated. The above values are just examples, and for example, when initializing the predetermined threshold, the predetermined threshold may be set so that at least one contradiction exists. Furthermore, it is also possible to combine known techniques for speeding up processing, such as counting the number of locations where there is a contradiction and changing the value to be subtracted from a predetermined threshold using feedback control after determining the presence or absence of a contradiction. .

As described above, by setting a predetermined threshold value based on contradictions in the cell lineage 103, an appropriate predetermined threshold value can be set graphically. In addition, since the predetermined threshold value depends on the performance of the sequencer 201 used for sequencing, by giving flexibility to the predetermined threshold value, the external environment of the sequencer 201 etc. to which the cell lineage generation device 100 can be applied You can expand your options.

In this way, as shown in FIG. 12B, a cell lineage 103 in which the relationship of the first branch point is appropriately determined is generated.

FIG. 13 is a diagram illustrating a cell lineage according to an example. In FIG. 13, the mutations described in the examples are shown as cells having the mutations, and a cell lineage 103 generated in accordance with the relationship of each branch point is shown. As shown in FIG. 13, a cell 30a having mutation 30 branches into a cell 31a having mutation 31 or a cell 33a having mutation 33. Cell 33a having mutation 33 further branches into cell 37a having mutation 37 or cell 39a having mutation 39. On the other hand, the cell 31a having the mutation 31 branches into a cell 43a having the mutation 43 or a cell 45a having the unobserved pseudo-mutation 45.

Cells with each mutation further branch into the next generation of cells through the relationship of branch points. Specifically, further analysis revealed that cell 45a branched into cell 61 and cell 63, and cell 43a branched into cell 65 and cell 67. Further, by proceeding with the analysis, one cell branched from cell 39a branches into cell 69 and cell 71, and another cell branched from cell 39 branches three times to form cell 73, cell 75, and cell 2. It was found that the cells branched into cell 77 by degree branching, and cell 79 by degree branching. In this manner, in this example, a cell lineage 103 was generated that branched into 11 types of branch ends for a maximum of six generations. In the generation of cell lineage over multiple generations as explained above, the lack of information found in conventional methods such as X chromosome inactivation and the complexity found in conventional methods using next-generation sequencers are dramatic. This has been improved to make it easier to provide more detailed information.

The validity of the above-described examples has been confirmed in reproductive mating experiments using mice and cell line experiments in which cells with nuclei derived from single mouse cells were grown. Specifically, in the reproductive mating experiment, we confirmed the mutation status in each of the first generation offspring of the mice used in the above experiment, and identified individuals carrying the mutation corresponding to each generation of the cell lineage. I confirmed that it exists. In addition, in cell line experiments, cells with nuclei derived from a single mouse somatic cell used in the above experiment were proliferated, and cell lines carrying mutations corresponding to each generation of the cell lineage existed. It was confirmed.

Hereinafter, an application example of the cell lineage 103 generated in this example will be described.

FIG. 14 is a diagram illustrating the composition ratio of cells on the cell lineage in each tissue. FIG. 14 shows the composition ratios of 11 types of cells (cells 61 to 71 and cell 37a) on the cell lineage calculated using the frequency of each mutation in each of the 17 tissues used in the above example. It shows.

As shown in FIG. 14, it can be seen that the cell composition ratio varies greatly depending on the tissue. As a notable example, cells 67 and 69 are predominant in the testis. On the other hand, in the secretory glands, kidney, heart, and pancreas, cells 67 and 69 are in relatively small proportions. In this way, the cell lineage 103 generated from the frequency of mutations in multiple tissues of an individual is used to determine the cell lineage 103 of multiple cells constituting the tissue (third tissue) that is the target of analysis for the individual. It may also be calculated as a cell composition ratio.

Specifically, in the analysis step, based on the generated cell lineage 103, it is further specified to which cell on the cell lineage each of the plurality of cells constituting the tissue desired to be analyzed corresponds. Thereafter, the composition ratio of cells on the cell lineage in the tissue desired to be analyzed may be calculated. This makes it possible to find out how each of the multiple cells constituting the tissue you want to analyze was formed by tracing the cell lineage 103, and also to find out what kind of cells these cells are. It is possible to show the percentage contained within an organization.

For example, if the tissue you want to analyze is a tissue related to a disease, you may want to include a large number of cells, a small number of cells, and a number of cells that have increased before and after the disease among the multiple cells that make up the tissue. It becomes possible to show the decreased number of cells, etc. as a numerical value. Therefore, more detailed clinical information about disease-related tissues can be obtained from a perspective that has not been seen before.

Note that the tissue to be analyzed may be the tissue used to generate the cell lineage 103, or may be any other tissue. In other words, the third organization may be the same as the first organization, the second organization, or other organizations.

FIG. 15 is a diagram illustrating an application example of the cell lineage generation method according to the embodiment. FIG. 15 shows how the cell composition 51a of a certain person 51 changes over time. According to the present invention, it is possible to easily visualize the cell composition 51a that indicates which cells of the cell lineage are included in what proportion in a certain tissue of the person 51. Therefore, as shown in FIG. 15, by tracking the cell composition 51a of the person 51 over time, it is possible to identify the presence or absence of some kind of exogenous stress before and after the cell composition 51a changes to the cell composition 51b in the person 51. becomes possible. Further, as shown in FIG. 15, based on the change in the cell composition 51a of the person 51 to a cell composition 51c in which specific cells have abnormally proliferated, the diagnosis of carcinogenesis in the person 51 can be made at an early stage based on the change in the cell composition 51a. becomes possible.

In addition, although the first mutation, second mutation, third mutation, and fourth mutation were explained above as specific mutations or combinations of mutations, these do not explain the relationship between mutations. This is a convenient mutation for explanation. For example, it has been explained that in the cell lineage 103 generated in the above example, the cell 30a, the cell 31a, and the cell 33a have a first branch point relationship. In this case, the mutation 30 that the cell 30a has is the first mutation, and the mutation 31 that the cell 31a has and the mutation 33 that the cell 33a has are the second mutation and the third mutation. Furthermore, it has been explained that in the generated cell lineage 103, the cell 33a, the cell 37a, and the cell 39a have a first branching point relationship. In this case, the mutation 31 that the cell 31a has is the first mutation, and the mutation 37 that the cell 37a has and the mutation 39 that the cell 39a has are the second mutation and the third mutation.

That is, the first mutation, second mutation, third mutation, and fourth mutation are concepts that indicate mutations that fluidly differ at each stage of analysis for generating the cell lineage 103.

[Effects etc.]
As explained above, the cell lineage generation method according to the present embodiment is based on mutations in a plurality of cells constituting each of two or more tissues including a first tissue and a second tissue of an individual to be analyzed. A cell lineage 103 is generated based on the frequency of .

According to this, the cell lineage 103 can be generated by simply collecting the first tissue and the second tissue from the individual to be analyzed and calculating the frequency of cell mutations. More detailed information can be obtained from the generated cell lineage 103 than in the past.

More specifically, the cell lineage generation method according to the present embodiment calculates a first frequency indicating the frequency of a first mutation and a frequency of a second mutation in a plurality of cells constituting a first tissue of an individual to be analyzed. A second frequency indicating the frequency of the third mutation and a third frequency indicating the frequency of the third mutation are acquired, and a fourth frequency indicating the frequency of the first mutation and a fourth frequency indicating the frequency of the second mutation in a plurality of cells constituting the second tissue of the individual are obtained. an acquisition step of acquiring a fifth frequency indicating the frequency and a sixth frequency indicating the frequency of the third mutation, and the sum of the second frequency and the third frequency corresponds to the first frequency and the fifth frequency Based on the determination step of determining whether the sum with the sixth frequency corresponds to the fourth frequency and the determination results in the determination step, the relationship between the first mutation, the second mutation, and the third mutation is analyzed, and the individual and an analysis step of generating a cell lineage 103 based on mutations in the cells.

According to this, in the cell lineage generation method, a plurality of tissue pieces are collected from an individual to be analyzed, and the frequency of mutations calculated from the DNA sequence obtained using a sequencer or the like is obtained. A cell lineage 103 of cells having the mutation can be generated by simply comparing the frequencies of the mutations obtained. Therefore, since the cell lineage 103 is easily generated based on the relationship between at least three mutations, more detailed information can be obtained than in the past.

For example, in the analysis step, if it is determined that the sum of the second frequency and the third frequency corresponds to the first frequency, and the sum of the fifth frequency and the sixth frequency corresponds to the fourth frequency, , the first cell having the first mutation, the second cell having the second mutation, and the third cell having the third mutation are at a first branching point where the first cell branches into the second cell or the third cell. The cell lineage 103 may be generated that matches the relationship of the determined first branch point.

According to this, the cell lineage 103 can be generated as a lineage of cells having the mutation based on the relationship of mutation frequencies. Therefore, a cell lineage 103 from which more detailed information can be obtained is generated.

For example, in the acquisition step, the first unattributed frequency indicating the frequency of the fourth mutation in the plurality of cells constituting the first tissue, and the frequency of the fourth mutation in the plurality of cells constituting the second tissue. In the analysis step, the second unattributed frequency indicating The first terminal frequency indicating the frequency corresponds to the sum of the first unattributed frequency and the first difference frequency larger than 0, and the second terminal frequency indicating the frequency in the plurality of cells constituting the second tissue is the second terminal frequency. 2 When there is one branch-end mutation corresponding to the sum of the unattributed frequency and the second differential frequency larger than 0, the fourth cell having the fourth mutation and the fifth cell having one branch-end mutation are , the cell lineage 103 may be determined to have a second branching point relationship branching from the fifth cell to the fourth cell, and a cell lineage 103 that further matches the determined second branching point relationship may be generated.

According to this, by further specifying the next cell in the cell lineage 103, the cell lineage 103 is generated based on at least four displacement relationships. Therefore, more detailed information can be obtained than in the past.

Furthermore, for example, at least one of the first mutation, second mutation, third mutation, and fourth mutation may be a mutation cluster composed of a set of a plurality of mutations. In this case, the frequency of the first mutation, second mutation, third mutation, or fourth mutation that is a mutation cluster may be the average value of the frequencies of each of the plurality of mutations in the set that constitutes the mutation cluster.

According to this, it is possible to generate a cell lineage 103 in which mutations occurring at the same timing on the cell lineage 103 are treated integrally. In other words, the mutational variations described above may be a combination of multiple mutations.

Also, for example, in the analysis step, it is determined that the fourth cell, the fifth cell, and the sixth cell have a relationship of a second branching point that branches from the fifth cell to the fourth cell or the sixth cell, The sixth cell has a pseudo mutation whose frequency in the plurality of cells constituting the first tissue is the first differential frequency and whose frequency in the plurality of cells constituting the second tissue is the second differential frequency. Good too.

According to this, in order to further connect the cell lineage 103 to the next generation, cells having unobserved (undetected) mutations can be temporarily set. Thereby, it is possible to generate a cell lineage 103 that spans even more generations. Therefore, more detailed information can be obtained.

For example, in the analysis step, based on the generated cell lineage 103, it is further specified which cell on the cell lineage 103 each of the plurality of cells constituting the third tissue of the individual corresponds to, and The composition ratio of cells on the cell lineage 103 in the three tissues may be calculated.

According to this, it is possible to indicate as a calculated compositional ratio which cells on the cell lineage and in what ratio are included in the plurality of cells constituting the third tissue. For example, among the multiple cells that make up the tertiary tissue, numerical values can be used to indicate large numbers of cells, small numbers of cells, increased cells, decreased cells, etc. in terms of composition ratio. More detailed clinical information regarding the three tissues can be obtained.

For example, in the determination step, if the sum of squared residuals represented by the above formula is less than or equal to a predetermined threshold, the sum of the second frequency and the third frequency corresponds to the first frequency, and the fifth frequency It may be determined that the sum of and the sixth frequency corresponds to the fourth frequency.

According to this, the relationship of mutations can be determined in a brute force manner using a mathematical formula. Therefore, the cell lineage 103 can be generated more easily.

In addition, for example, the predetermined threshold value is determined by the following conditions: (i) a contradiction in the existence of a branching point relationship where one cell branches into three or more cells in the created cell lineage 103; It may be a value that does not contradict the existence of a confluence relationship where two or more cells merge into one cell.

According to this, it is possible to generate a cell lineage 103 with the highest number of generations within a reasonable range that does not cause contradictions and within the frequency of mutations that can be obtained. Therefore, more detailed information can be obtained.

Furthermore, for example, the cell lineage 103 may be generated based on mutations in cancer cells of an individual.

According to this, the cell lineage 103 of cancer cells can be generated. Since the origin of cancer cells can be clarified, more detailed information can be provided for determining effective anticancer drugs, treatment methods, prognosis, etc.

Further, for example, the second organization may be a different organization from the first organization.

According to this, the cell lineage 103 can be generated using the first tissue and the second tissue different from the first tissue. Since the frequency of mutations used to generate the cell lineage 103 can be calculated in tissues with more various cell compositions, the influence of detection errors caused by cells with a low composition ratio can be reduced. Therefore, more accurate cell lineage 103 can be generated.

Further, the program in this embodiment causes a computer to execute any of the methods described above.

According to this, the cell lineage generation method described above can be performed using a computer.

Furthermore, the cell lineage generation device 100 according to the present embodiment also has a first frequency indicating the frequency of the first mutation, and a second frequency indicating the frequency of the second mutation in the plurality of cells constituting the first tissue of the individual to be analyzed. 2 frequency and a third frequency indicating the frequency of the third mutation, and a fourth frequency indicating the frequency of the first mutation and a frequency of the second mutation in a plurality of cells constituting the second tissue of the individual. an acquisition unit 11 that acquires a fifth frequency and a sixth frequency indicating the frequency of the third mutation; the sum of the second frequency and the third frequency corresponds to the first frequency; A determining unit 13 determines whether the sum with the frequency corresponds to the fourth frequency, and based on the determination result of the determining unit, analyzes the relationship between the first mutation, the second mutation, and the third mutation to determine the individual's and an analysis unit 15 that generates a cell lineage 103 based on mutations made in the cells.

According to this, the cell lineage generation device 100 collects a plurality of tissue pieces from an individual to be analyzed, and uses the acquisition unit 11 to acquire mutation frequencies calculated from the DNA sequence obtained using a sequencer or the like. do. By simply comparing the frequencies of the mutations acquired by the determination unit 13, the analysis unit 15 can generate the cell lineage 103 of cells having the mutations. Therefore, since the cell lineage 103 is easily generated based on the relationship between at least three mutations, more detailed information can be obtained than in the past.

(Other embodiments)
Although the embodiments have been described above, the present invention is not limited to the above embodiments.

For example, in the embodiments described above, the processing executed by a specific processing unit may be executed by another processing unit. Further, the order of the plurality of processes may be changed, or the plurality of processes may be executed in parallel.

Furthermore, in the above embodiments, each component such as the input/output section may be realized by executing a software program suitable for each component. Each component may be realized by a program execution unit such as a CPU or a processor reading and executing a software program recorded on a recording medium such as a hard disk or a semiconductor memory.

Further, each component such as the input/output unit may be realized by hardware. Each component may be a circuit (or integrated circuit). These circuits may constitute one circuit as a whole, or may be separate circuits. Further, each of these circuits may be a general-purpose circuit or a dedicated circuit.

Further, general or specific aspects of the present invention may be implemented in a system, apparatus, method, integrated circuit, computer program, or computer readable recording medium such as a CD-ROM. Further, the present invention may be realized by any combination of a system, an apparatus, a method, an integrated circuit, a computer program, and a recording medium.

For example, it may be equipped with an interpolation device that interpolates cell lineages using the results of additional genetic experiments other than those described above. Further, an input device for inputting the results of experiments for such interpolation may be provided.

Further, for example, the cell lineage generation device, the sequencer, the mutation frequency calculation device, and the output unit in the above embodiments may be realized as an integrated cell lineage generation system.

Further, the present invention may be realized as an information presentation method performed by a computer, or may be realized as a program for causing a computer to execute the information presentation method. Further, the present invention may be realized as a computer-readable non-transitory recording medium on which such a program is recorded.

Other embodiments may be obtained by making various modifications to each embodiment that those skilled in the art can think of, or by arbitrarily combining the components and functions of each embodiment without departing from the spirit of the present invention. The present invention also includes such forms.

INDUSTRIAL APPLICABILITY The present invention can be effectively used in all clinical situations, such as providing useful information in preliminary examinations for diagnosis of diseases such as cancer, and treatments such as medication.

11 Acquisition unit 13 Determination unit 15 Analysis unit 30, 31, 33, 37, 39, 43 Mutation 30a, 31a, 33a, 37a, 39a, 43a, 45a, 61, 63, 65, 67, 69, 71, 73, 75 , 77, 79 cells 35, 41 hypothetical frequency 45 pseudomutation 51 people 51a, 51b, 51c cell composition 100 cell lineage generation device 101 mosaic mutation 102 heterozygous mutation 103, 103a, 103b cell lineage 201 sequencer 203 mutation frequency calculation device 205 Output section

Claims (10)

A first frequency indicating the frequency of the first mutation, a second frequency indicating the frequency of the second mutation, and a third frequency indicating the frequency of the third mutation in a plurality of cells constituting the first tissue of the individual to be analyzed. a fourth frequency indicating the frequency of the first mutation, a fifth frequency indicating the frequency of the second mutation, and a fifth frequency indicating the frequency of the third mutation in a plurality of cells constituting the second tissue of the individual; an obtaining step of obtaining a sixth frequency indicating the frequency;
Whether the sum of the second frequency and the third frequency matches or almost matches the first frequency, and the sum of the fifth frequency and the sixth frequency matches or almost matches the fourth frequency. a determination step of determining whether or not the
an analysis step of analyzing the relationship between the first mutation, the second mutation, and the third mutation based on the determination result in the determination step, and generating a cell lineage based on the mutation in the cells of the individual. fruit,
In the analysis step,
It is determined that the sum of the second frequency and the third frequency matches or almost matches the first frequency, and the sum of the fifth frequency and the sixth frequency matches or almost matches the fourth frequency. In this case, the first cell having the first mutation, the second cell having the second mutation, and the third cell having the third mutation are separated from the first cell by the second cell or the third mutation. It is determined that the cell has a relationship of the first branching point branching into 3 cells,
generating the cell lineage that matches the determined first branching point relationship;
Cell lineage generation method. In the acquisition step, further, a first unattributed frequency indicating a frequency of a fourth mutation in a plurality of cells constituting the first tissue, and a frequency of the fourth mutation in a plurality of cells constituting the second tissue. Obtain a second unattributed frequency indicating
In the analysis step,
Furthermore, with respect to the plurality of branch-end mutations possessed by each of the plurality of branch-end cells of the cell lineage, a first terminal frequency indicating a frequency in the plurality of cells constituting the first tissue is the first unassigned frequency. and a first differential frequency greater than 0, and a second terminal frequency indicating a frequency in a plurality of cells constituting the second tissue is greater than the second unattributed frequency and a second differential frequency greater than 0. When the number of branch-end mutations corresponding to the sum of the differential frequency is one, the fourth cell having the fourth mutation and the fifth cell having the one branch-end mutation are determined to have a second branching point relationship branching into 4 cells,
The cell lineage generation method according to claim 1 , further comprising generating the cell lineage that further matches the relationship of the determined second branch point. In the analysis step, the fourth cell, the fifth cell, and the sixth cell have a relationship of the second branching point that branches from the fifth cell to the fourth cell or the sixth cell. decided,
The sixth cell is a pseudo cell in which a frequency in a plurality of cells constituting the first tissue is the first differential frequency, and a frequency in a plurality of cells constituting the second tissue is the second differential frequency. The cell lineage generation method according to claim 2 , wherein the cell lineage generation method has a mutation. In the analysis step, further, based on the generated cell lineage, it is specified which cell on the cell lineage each of a plurality of cells constituting the third tissue of the individual corresponds to, and The cell lineage generation method according to any one of claims 1 to 3, comprising calculating a composition ratio of cells on the cell lineage in a tissue. In the determination step,

If the sum of squared residuals represented by 6 frequencies is determined to match or almost match the fourth frequency,
N is the number of target tissues used in the cell lineage generation method, including the first tissue and the second tissue among the plurality of tissues of the individual,
X _{2, ave.} is the average frequency of the second mutation in a plurality of cells constituting the target tissue,
X _{3, ave.} is the average frequency of the third mutation in a plurality of cells constituting the target tissue,
X _1,n is the (1+3(n-1))th frequency indicating the frequency of the first mutation in a plurality of cells constituting the nth (n is a positive integer) tissue;
X _2,n is the (2+3(n-1))th frequency indicating the frequency of the second mutation in a plurality of cells constituting the nth tissue,
4. The method according to any one of claims 1 to 3, _wherein Cell lineage generation method. The predetermined threshold value is based on the fact that, in the cell lineage to be created, (i) there is a contradiction in that there is a branch point relationship where one cell branches into three or more cells, and (ii) there is a relationship between two or more cells. 6. The cell lineage generation method according to claim 5, wherein the value is consistent with the existence of a confluence relationship where cells merge into one cell. The cell lineage generation method according to any one of claims 1 to 6, wherein the cell lineage is generated based on mutations in cancer cells of the individual. The cell lineage generation method according to any one of claims 1 to 7, wherein the second tissue is a tissue different from the first tissue. A program for causing a computer to execute the cell lineage generation method according to any one of claims 1 to 8 . A first frequency indicating the frequency of the first mutation, a second frequency indicating the frequency of the second mutation, and a third frequency indicating the frequency of the third mutation in a plurality of cells constituting the first tissue of the individual to be analyzed. a fourth frequency indicating the frequency of the first mutation, a fifth frequency indicating the frequency of the second mutation, and a fifth frequency indicating the frequency of the third mutation in a plurality of cells constituting the second tissue of the individual; an acquisition unit that acquires a sixth frequency indicating the frequency;
Whether the sum of the second frequency and the third frequency matches or almost matches the first frequency, and the sum of the fifth frequency and the sixth frequency matches or almost matches the fourth frequency. a determination unit that determines whether or not the
an analysis unit that analyzes the relationship between the first mutation, the second mutation, and the third mutation based on the determination result of the determination unit and generates a cell lineage based on the mutation made in the cells of the individual. ,
The analysis department is
It is determined that the sum of the second frequency and the third frequency matches or almost matches the first frequency, and the sum of the fifth frequency and the sixth frequency matches or almost matches the fourth frequency. In this case, the first cell having the first mutation, the second cell having the second mutation, and the third cell having the third mutation are separated from the first cell by the second cell or the third mutation. It is determined that the cell has a relationship of the first branching point branching into 3 cells,
generating the cell lineage that matches the determined first branching point relationship;
Cell lineage generator.

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