JP2010113413A - Apparatus, method and program for analyzing gene control network - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an apparatus, network and program for analyzing a gene control network, which may improve reliability. <P>SOLUTION: The expression amount for each measurement time for a plurality of genes in a target cell is acquired. The type of expression suppressing mechanism for a gene in a complementary sequence is classified based on the behavioral pattern of the expression amount for each measurement time corresponding to the gene and on presence of overlapping of the same chromosome in a complementary sequence for each gene in complementary sequence in the target cell. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a gene regulatory network analysis apparatus, a gene regulatory network analysis method, and a gene regulatory network analysis program, and belongs to the field of gene analysis technology and the like.

Conventionally, there is a concept called NATs (Natural Antisense Transcripts) (see Non-Patent Document 1, for example). These NATs have a portion where the complementary sequence of the coding region of one single-stranded DNA and the coding region of the other single-stranded DNA overlap, and the expression of the coding region of one single-stranded DNA is It is suppressed by the expression of the coding region of the single-stranded DNA. In Non-Patent Document 1, it is defined as cases A to D.
Michal Lapidot & Yitzhak Pilpel (Weizmann Institute of Sience, Rehovot, Israel), Genome-wide natural antisense transcription: coupling itsregulation to its different regulatory mechanisms, EMBO reports, EUROPEANMOLECULAR BIOLOGY ORGANIZATION, Submitted 28 March 2006; accepted 18 October 2006, p.1216 -1222

  By the way, in the said nonpatent literature, case C is not proved but exists as a hypothesis. Moreover, although the expression level of the part which the complementary sequence of the coding region of one single stranded DNA and the coding region of the other single stranded DNA overlap is shown, this is only speculation.

  If a network related to the control of gene expression and suppression can be constructed from the gene expression level in the complementary sequence portion, it is considered that the reliability of the network is improved.

  The present invention has been made in consideration of the above points, and intends to propose a gene regulatory network analyzer, a gene regulatory network analysis method, and a gene regulatory network analysis program capable of improving reliability.

  In order to solve such a problem, the present invention is a gene regulatory network analyzer, an acquisition unit for acquiring the expression level for each of a plurality of genes in a target cell, and for each gene that is a complementary sequence in the target cell, A classification unit that classifies the species of the expression suppression mechanism for the gene serving as the complementary sequence according to the behavior pattern of the expression level for each measurement time corresponding to the gene and the presence or absence of overlap in the same chromosome in the complementary sequence. Have.

  The present invention also relates to a gene regulatory network analysis method, wherein an acquisition step of acquiring an expression level for each of a plurality of genes in a target cell is measured, and each gene that is a complementary sequence in the target cell corresponds to the gene. A classification step of classifying the species of the expression suppression mechanism for the gene serving as the complementary sequence according to the behavior pattern of the expression level for each measurement time and the presence or absence of overlap in the same chromosome in the complementary sequence.

  The present invention also relates to a gene regulatory network analysis program, wherein a computer obtains the expression level for a plurality of genes in a target cell at each measurement time, and each gene that becomes a complementary sequence in the target cell Classifying the species of the expression suppression mechanism for the gene serving as the complementary sequence according to the behavior pattern of the expression level for each measurement time corresponding to and the presence or absence of overlap in the same chromosome in the complementary sequence.

  In the present invention, a gene having a possibility of having an expression-inhibiting relationship at the structural level (a gene serving as a complementary sequence) is actually determined from the behavior pattern of the actual expression level in the gene and the presence or absence of overlap in the same chromosome. The mechanism of expression suppression mechanism can be classified at the mechanism level.

  As described above, the present invention can automatically and comprehensively analyze the interrelationship between expression and repression through the actual mechanism level, and thus can improve the reliability of gene regulatory network analysis.

  The NATs described in Cited Document 1 have been proved only in a specific part of a specific organism, but whether this proven mechanism exists in a wide variety of organisms, and in some cases, in which cell It will be very useful to be able to automatically and comprehensively analyze through the actual mechanism level in that it can be surely obtained as information whether it is in the part.

  Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings.

(1) Overall Configuration of Gene Regulatory Network Analysis System FIG. 1 shows the overall configuration of a gene regulatory network analysis system 1 according to this embodiment. The gene regulatory network analysis system 1 includes a genome server 2, a fluorescence intensity measuring device 3, and a gene regulatory network analyzing device 4.

  The genome server 2 holds a database relating to genomes of various organisms in eukaryotes or prokaryotes. The genome server 2 can provide genome information corresponding to a request of a device accessed through a computer network such as the Internet to the device.

  The fluorescence intensity measuring device 3 has a measurement stage, and a nucleic acid chip CP is set on the measurement stage. The nucleic acid chip CP is a base on which nucleic acid probes corresponding to all genes in the target organism are arranged.

  In this nucleic acid chip CP, for example, as shown in FIG. 2, a target nucleic acid (part indicated by a black circle) extracted from a cell of a target organism and added with a labeling substance (part indicated by a black circle) is added to a nucleic acid probe (part indicated by a long wavy line). (Part indicated by a short wave line) is given, and a complementary strand formation reaction (hereinafter also referred to as hybridization) is performed.

  A nucleic acid probe is a single-stranded nucleotide that functions as a probe (detector) for detecting a specific gene. In general, a nucleic acid probe is designed as a plurality of probe fragments (hereinafter also referred to as a probe set) including partial sequences that are specific to the gene rather than nucleotides that are complementary to the entire sequence of a specific gene. The Specifically, it is designed as a DNA (deoxyribonucleic acid) fragment, cDNA (complementary DNA) fragment or PNA (peptide nucleic acid) of about 18 to 60 [mer].

  On the other hand, the target nucleic acid is a single-stranded nucleotide to be hybridized with a nucleic acid probe. In general, mRNA (including pre-mRNA) or a fragment thereof is not used as the target nucleic acid, but a mRNA obtained by converting the mRNA or a fragment thereof with a reverse transcriptase is used.

  On the other hand, the labeling substance is generally a fluorescent dye such as biotin or FITC (fluorescein isothiocyanate), but is not limited thereto, and may be a radioisotope, for example.

  When a measurement command is given, the fluorescence intensity measurement device 3 (FIG. 1) irradiates the nucleic acid chip CP set on the measurement stage with excitation light of a labeling substance added to the target nucleic acid. As shown in FIG. 2, when the nucleic acid probe of the nucleic acid chip CP forms a complementary strand with the target nucleic acid, the labeling substance added to the target nucleic acid emits light by excitation light. The amount of luminescence correlates with the amount of complementary strand formed between the target nucleic acid and the nucleic acid probe, and the amount of luminescence increases as the amount of target nucleic acid that forms a complementary strand with the nucleic acid probe increases.

The fluorescence intensity measuring device 3 reads, from the nucleic acid chip CP irradiated with the excitation light, the amount of light emitted from the nucleic acid probes corresponding to all the genes arranged on the nucleic acid chip by the sensor CE. The fluorescence intensity measuring device 3, for example, as shown in FIG. 3, the light emission quantity of each gene was read _{EM i (i = 1,2, ......} , m) allocates a gene unique identifier g _i in, the combination Data to which additional information TM such as reading time and chip number is added (hereinafter referred to as measurement data) is output.

  The gene control network analysis device 4 acquires genome information from the genome server 2 and acquires complementary strand formation amount data from the fluorescence intensity measurement device 3. Then, the gene regulatory network analyzer 4 classifies the species of the expression suppression mechanism for the gene that becomes a complementary sequence in the target cell using these genome information and complementary strand formation amount data.

(2) Configuration of Gene Regulatory Network Analyzer Next, the configuration of the gene regulatory network analyzer 4 will be described. As shown in FIG. 4, the gene regulatory network analyzer 4 is configured by connecting various hardware to a CPU (Central Processing Unit) 10 that controls the entire gene regulatory network analyzer 4.

  Specifically, a ROM (Read Only Memory) 11, a RAM (Random Access Memory) 12 serving as a work memory of the CPU 10, an operation unit 13, a storage unit 14, an interface 15, and a display unit 16 are connected via a bus 17.

  The ROM 11 stores a program for executing gene control network analysis processing (hereinafter also referred to as gene control network analysis program), and the interface 15 is individually connected to the genome server 2 and the fluorescence intensity measuring device 3. Is provided.

  When the gene control network analysis program stored in the ROM 11 is expanded in the RAM 12, the CPU 10 appropriately controls the storage unit 14, the interface 15 and the display unit 16 based on the gene control network analysis program, and performs gene control network analysis processing. It is made to run.

(3) Processing contents of the CPU based on the gene regulatory network analysis program The CPU 10, which has expanded the gene regulatory network analysis program in the RAM 12, functionally obtains the gene expression level acquisition unit 21, genome information acquisition as shown in FIG. The processing unit can be classified into a unit 22, an expression level reading unit 23, a binarization unit 24, and a classification unit 25.

For example, as shown in FIG. 5, the gene expression level acquisition unit 21 uses a target nucleic acid extracted from a passaged target cell every predetermined period and a nucleic acid chip CP _j (j = 1, 2,..., N). Based on the amount of complementary strand formed with the nucleic acid probe, gene expression levels GE _{1 to} GE _m per measurement time t _{1 to} t _n are obtained for each gene expressed in cells in the target organism.

  Here, one specific example of the processing in the gene expression level acquisition unit 21 is given.

  The gene expression level acquisition unit 21 inputs the target cell species using the operation unit 13, and inputs the company name and product number of the nucleic acid chip corresponding to the input species on the inside or on the Internet. Search from the database.

  The gene expression level acquisition unit 21 presents the company name and product number of the searched nucleic acid chip on the display unit 16, and presents that mRNA in the target cell should be measured at certain time intervals and the measurement conditions.

  Specifically, the time interval at which the target nucleic acid should be extracted from the passaged target cells, and the temperature and humidity to be protected when the target nucleic acid extracted at each time zone is hybridized with the nucleic acid probe of the nucleic acid chip Present measurement conditions such as a range of environmental conditions. As described above, the gene expression level acquisition unit 21 can suppress measurement variations by specifically presenting measurement conditions, and can increase measurement accuracy.

  In addition, the gene expression level acquisition unit 21 starts waiting for measurement data output from the fluorescence intensity measuring device 3 from the time when the company name of the nucleic acid chip and its product number are presented. The gene expression level acquisition unit 21 receives the difference between the reading time TM (FIG. 3) indicated in the measurement data and the reading time TM indicated in the measurement data read immediately before the measurement data. Is calculated.

  When this calculation result is outside the allowable range between the upper threshold and the lower threshold set based on the time interval set as the measurement condition, the gene expression level acquisition unit 21 displays that the measurement should be performed again from the beginning. 16 is used for visual notification. Thereby, the gene expression level acquisition unit 21 can accurately acquire the transition of the target nucleic acid level in the target cell. It will be understood that the narrower the time interval, which is the measurement condition, is, the more detailed the transition of the gene expression level expressed in the cells of the target organism.

  On the other hand, when the calculation result falls within the allowable range, the gene expression level acquisition unit 21 stores the measurement data in the storage unit 14 after converting the luminescence level of each gene included in the measurement data into the gene expression level.

  The gene expression level is the amount of luminescence correlated with the amount of complementary strand formed between the target nucleic acid and the nucleic acid probe, and the background (local physical effect), etc., is excluded by a statistical method. It is highly reliable as an amount indicating the gene expressed in.

  For example, when data analysis software called MAS (Micro Array Suite) manufactured by Affymetrix is used, the gene expression level is calculated as a ratio of the luminescence level.

  Incidentally, this MAS version 5 will be briefly described by focusing on a nucleic acid probe corresponding to a certain gene. In MAS5, (1) the local physical influence (background) is excluded from the amount of light emitted from the probe set (a plurality of probe fragments including a base sequence specific to the gene). (2) The light emission amount of each probe fragment (referred to as a perfect match probe) is appropriately corrected according to the difference between the probe fragment and the corresponding fragment control (referred to as a mismatch probe). (3) The amount of luminescence of each probe fragment is calculated as a gene expression level by logarithmic conversion.

  I. S. Kohane / A. T.A. Kho / A. J. et al. Butte Yoshi Hoshida, Microarray Data Analysis for Integrated Genomics, Springer Japan Publishing, p. 58-74.

  As mentioned above, although the specific example of the process in the gene expression level acquisition part 21 was given, this process is not limited to this example.

  The genome information acquisition unit 22 updates the cis-NATS database and the trans-NATS database stored in the storage unit 14 every predetermined update period.

  This cis-NATS database contains genes in which the coding region of one single-stranded DNA and the coding region of the other single-stranded DNA are complementary sequences, and a part of the sequence overlaps. These are associated with each type. The trans-NATS database is a database in which genes that are complementary sequences in a coding region on one chromosome and a coding region on another chromosome are associated with each other in units of organisms and cells.

  Here, one specific example of processing in the genome information acquisition unit 22 will be given.

  When the update period has elapsed, the genome information acquisition unit 22 automatically accesses the genome server 2 using the interface 15 and performs mutual authentication with the genome server 2. When the mutual authentication with the genome server 2 is established, the genome information acquisition unit 22 confirms whether or not the cis-NATS database or the trans-NATS database is updated with respect to the genome server 2.

  Here, when it is confirmed that the genome information acquisition unit 22 has been updated, the genome information acquisition unit 22 updates one or both of the cis-NATS database and the trans-NATS database stored in the storage unit 14.

  Incidentally, at this time, when there is genome information designated by the operation unit 13, the genome information acquisition unit 22 stores the genome information in the storage unit 14. Examples of genomic information include the base sequences of all mature mRNAs and their precursor mRNAs (pre-mRNA) that can be expressed in the target organism, introns and exons.

  As mentioned above, although the specific example of the process in the genome information acquisition part 22 was given, this process is not limited to this example.

  The expression level reading unit 23 recognizes all the genes that are complementary sequences in the cis-NATS database and the trans-NATS database stored in the storage unit 14. Incidentally, the gene in the cis-NATS database is a complementary sequence in a state where the coding region of one single-stranded DNA overlaps with the coding region of the other single-stranded DNA, as described above. The gene in the trans-NATS database is a complementary sequence between a coding region on one chromosome and a coding region on another chromosome.

Then, the expression level reading unit 23 reads data indicating the gene expression level GE (FIG. 5) for each measurement time t _{1 to} t _n corresponding to the gene of each complementary sequence from the storage unit 14, and the data is converted into a binarization unit 24. To give.

It should be noted that the expression level reading section 23, when data indicating a gene expression amount GE of each measurement time t ₁ ~t _n for each complementary sequence (Fig. 5) is not stored in the storage unit 14, to that effect, The display unit 16 is used for visual notification.

The binarization unit 24 receives the data indicating the gene expression levels GE _{1 to} GE _m (FIG. 5) for each measurement time t _{1 to} t _n corresponding to each complementary sequence from the expression level reading unit 23. Using the data, the behavior of the gene expression level in each sequence of the complementary sequence is binarized.

That is, the binarizing unit 24 generates a binary string (hereinafter also referred to as an expression level binary string) by taking a positive or negative difference in the time lapse direction of the observation point t _n for each gene expression level GE. If gene expression levels GE at each observation point t _n is 5, the expression level binary string is as shown in FIG.

  Incidentally, the value of each gene expression level GE in FIG. 6 is shown for convenience and is not an actual numerical value. Note that the present inventors have already proposed binarization of gene expression levels, and refer to 2008-213112 for details.

  Here, as shown in FIG. 7 or FIG. 8, when the behavior of the gene expression level GEX of a certain sequence and the gene expression level GEY of a sequence complementary to the sequence are the same or substantially the same, it is shown in FIG. In this way, the positive and negative patterns in the expression level binary string are the same.

  On the other hand, as shown in FIG. 10 or FIG. 11, the behavior of the gene expression level GEX of a certain sequence and the gene expression level GEY of a sequence complementary to the sequence has a constant inverse correlation or an approximate inverse correlation. In this case, as shown in FIG. 12, the positive and negative patterns in the expression amount binary string are opposite.

  The classification unit 25 is a seed of an expression suppression mechanism for a gene serving as a complementary sequence according to an expression amount binary string corresponding to the gene serving as a complementary sequence in the target cell and the presence or absence of overlap in the same chromosome in the complementary sequence. Classify.

  That is, when the positive / negative pattern of the expression amount binary string corresponding to each sequence of the complementary sequence is the same or opposite, the classification unit 25 detects that there is an action correlation between expression and suppression between the genes of the complementary sequence. .

  Then, the classification unit 25 checks whether or not the genes of complementary sequences that have an action correlation overlap with each other on a part of the same chromosome based on the cisNATS database and the transNATS database.

  Here, when complementary sequences that are in an action correlation between expression and suppression are “overlapping on the same chromosome”, and the expression amount binary string in the complementary sequence is an “opposite” positive / negative pattern, this is It means that it corresponds to cisNATS of case A or case D in the literature. In this case, the classification unit 25 generates information indicating that the complementary sequence has a mechanism relationship of case A or case D, and registers this information in the database for gene regulatory network analysis.

  In addition, when complementary sequences that are in an action relationship between expression and suppression are “overlapping on the same chromosome” and the expression amount binary string in the complementary sequence is “identical”, this is the above-mentioned non-patent document. It corresponds to cisNATS of case C in FIG. In this case, the classification unit 25 generates information indicating that the complementary sequence is in the relationship of the mechanism of case C, and registers this information in the database for gene regulatory network analysis.

  Furthermore, when the complementary sequence in the action correlation between the expression and the suppression does not “overlap”, this means that even if the expression binary string in the complementary sequence is “same” or “opposite” Means equivalent to transNATs. In this case, the classification unit 25 generates information indicating that the complementary sequence has a transNATS mechanism relationship, and registers this in the database for gene regulatory network analysis.

  Specifically, this database for gene control network analysis includes, for example, the name of the target organism, information about each complementary sequence (chromosome number having the sequence, gene name in the sequence portion, expression level in the sequence A binary string or the like), a code (identifier) assigned to a gene control mechanism seed (case A, case C, transNATs), or the like. Incidentally, common names or abbreviations are included in the names.

  In this way, the classification unit 25 determines the seeds of the expression suppression mechanism for the gene serving as the complementary sequence, “presence / absence of overlap on the same chromosome” and “simple behavior pattern of gene expression level” in the complementary sequence. And can be classified according to.

  Therefore, in this gene regulatory network analysis apparatus 4, among the proven gene regulatory mechanisms (case NAT or cis NATs in case D) and hypothetical stage gene regulatory mechanisms (case C cisNATS or transNATs), Subsequent editing of the database can be simplified, such as deleting the gene regulatory mechanism from the database for gene regulatory network analysis.

  Further, when the interaction relationship between genes registered in the database is displayed on the display unit 16 using predetermined display software, for example, as shown in FIG. 13, the action correlation between the expression and the suppression is in the verification stage. It is possible to intuitively distinguish whether it is in the hypothesis stage by color coding or the like.

(4) Gene Regulatory Network Analysis Processing Procedure Next, the gene regulatory network analysis processing procedure will be described using the flowchart shown in FIG.

  The CPU 10 starts this gene regulatory network analysis process, for example, when the power is turned on, and proceeds to step SP1 to wait for a gene regulatory network analysis request. Here, when the analysis request of the gene regulatory network is received, the CPU 10 proceeds to step SP2 and confirms whether or not the gene expression level for each observation point in the target cell has already been acquired.

Here, when the gene expression level is not acquired, the CPU 10 proceeds to step SP3 to function as the gene expression level acquisition unit 21, and from the fluorescence intensity measurement device 3, each observation point t _{1 to} t in the target organism. After acquiring _n gene expression levels GE _{1 to} GE _m (FIG. 5), the process proceeds to the next step SP4. On the other hand, when the gene expression level is acquired, the CPU 10 proceeds to step SP4 without passing through step SP3.

  In step SP4, the CPU 10 checks whether or not the cis-NATS database and the trans-NATS database have already been acquired.

  If the genome information is not acquired, the CPU 10 proceeds to step SP5, functions as the genome information acquisition unit 22, acquires the cis-NATS database and the trans-NATS database from the genome server 2, and then Proceed to step SP6.

  On the other hand, when the cis-NATS database and the trans-NATS database have been acquired, the CPU 10 proceeds to step SP6 without passing through step SP5.

  In step SP6, the CPU 10 functions as the expression level reading unit 23 and searches for genes that are complementary sequences by referring to the cis-NATS database and the trans-NATS database stored in the storage unit 14.

  Here, when a gene serving as one or more complementary sequences is detected, this means that NATs function may exist in the target cell. In this case, the CPU 10 proceeds to step SP7 and generates the behavior of the gene expression level (expression level binary string (FIG. 6)) for each gene of the complementary sequence.

  Then, the CPU 10 proceeds to step SP8 to classify the species of the mechanism of expression and suppression for the complementary sequence according to the pattern of the expression level binary string and the presence or absence of overlap in the same chromosome in the complementary sequence having the action correlation. After (registered in the database for gene regulatory network analysis), this gene regulatory analysis process is terminated.

  On the other hand, if a gene that becomes one or more complementary sequences is not detected in step SP6, the CPU 10 proceeds to step SP9, and the target organism has no gene that has a correlation between expression and suppression (has no NATs function). After the visual notification, the gene regulatory network analysis process is terminated.

  In this way, the CPU 10 can execute the gene regulatory network analysis process and classify the species of the expression suppression mechanism for each gene to be a complementary sequence. Note that the order of the steps is not limited to that shown in FIG.

(5) Operation and Effect In the above configuration, the gene regulatory network analyzer 4 performs the behavior of the expression level GE for each measurement time t _{1 to} t _n corresponding to the gene for each gene that is a complementary sequence in the target cell. The NATs species are classified according to the pattern and the presence or absence of overlap in the same chromosome in the gene.

  Therefore, in this gene regulatory network analysis device 4, with respect to a gene having a possibility of having an expression suppression relationship at the structure level (a gene serving as a complementary sequence), the behavior pattern of the actual expression level in the gene and the overlap in the same chromosome Based on the presence / absence of phenotypes, the species of the expression suppression mechanism can be supported (proven) and classified at the actual mechanism level.

  As a result, the gene regulatory network analyzer 4 can automatically and comprehensively analyze the correlation between expression and repression through the actual mechanism level, so that the reliability of gene regulatory network analysis can be improved. it can.

  The NATs described in Cited Document 1 have been proved only in a specific part of a specific organism, but whether this proven mechanism exists in a wide variety of organisms, and in some cases, in which cell It will be very useful to be able to automatically and comprehensively analyze through the actual mechanism level in that it can be surely obtained as information whether it is in the part.

  Moreover, in this gene control network analysis apparatus 4, as a method for generating a behavior pattern of the expression level GE, a method for generating a binary string by taking a positive or negative difference in the gene expression level GE in the time passage direction of the observation time is used. Adopted (FIG. 6).

  Conventionally, although there has been a request for classifying genes, there is no general standard for when to classify the gene expression level in what category. However, in this gene regulatory network analyzer 4, a binary series (binary) that focuses only on the behavior that the amount of expression at each observation time is “up” or “down” along the time transition of the observation time. By converting into (column), a pattern (positive / negative pattern) that can be taken by the binary string can be inevitably obtained.

  In addition, since the gene regulatory network analyzer 4 can easily pattern each gene from the temporal behavior of its expression level, when comparing all possible combinations from tens of thousands of genes. Become more efficient.

  Further, in this gene regulatory network analysis device 4, the NATs species are subdivided into proven gene control mechanisms (case NAT or cis NATs) and hypothetical gene control mechanisms (case NAT cisNATS or transNATSs). To do.

  Therefore, in this gene regulatory network analysis apparatus 4, editing of network construction can be facilitated according to research trends such as subsequent verification of hypotheses.

  The gene regulatory network analyzer 4 does not simply acquire the expression level in the gene expressed in the cells of the target organism, but the measurement interval of the expression level is a range between a set upper threshold and a lower threshold. The expression level is obtained selectively.

  Therefore, since the gene regulatory network analyzer 4 obtains the transition amount as a criterion for supporting at the actual mechanism level under a certain standard, the correlation between expression and suppression of a wide variety of target organisms is obtained. It is possible to determine whether or not there is an action correlation between expression and suppression based on equivalent criteria.

  According to the above configuration, the gene regulatory network that can improve the reliability by enabling the automatic and comprehensive analysis of the correlation between expression and suppression in the target organism through the actual mechanism level. The analysis device 4 can be realized.

(6) Other Embodiments In the above-described embodiment, the expression level data indicating the gene expression level of the target nucleic acid in the cell is acquired using the fluorescence intensity measurement device 3. However, the acquisition mode is not limited to this embodiment. For example, an embodiment in which each mRNA expressed in the target cell is extracted and directly obtained by proliferating to a certain amount using real-time PCR (Polymerase Chain Reaction) is also applicable.

  Further, for example, it is also possible to apply a mode in which data is obtained from a data storage medium that stores data indicating the amount of mRNA obtained as a result of measurement using a fluorescence intensity measuring device or real-time PCR in a predetermined organization. When this aspect is applied, for example, data indicating the amount of mRNA can be stored as an average index value at a plurality of experimental locations that are far away.

  Examples of the data storage medium include package media such as a flexible disk, CD-ROM (Compact Disk-Read Only Memory), and DVD (Digital Versatile Disc), a semiconductor memory in which data is temporarily or permanently stored, There are magnetic disks. In addition, as a method for acquiring data from these data storage media, a wired or wireless communication medium such as a local area network, the Internet, or digital satellite broadcasting can be used.

  Further, as the reading amount, in the above-described embodiment, the light emission amount is optically read. However, the reading amount is not limited to this embodiment. For example, an electromagnetic quantity or an impedance quantity can be applied electromagnetically. In short, a reading amount read by a sensor that reads a predetermined physical quantity can be applied. In addition, as the nucleic acid chip CP, for example, a Stanford type manufactured by Affymetorix can be applied, and a chip other than these can also be applied.

  In addition, the reading place is the nucleic acid chip CP in the above-described embodiment. However, the reading place is not limited to this. For example, a tissue section can be applied and other locations can also be applied.

  Further, MAS is applied as a method for calculating the gene expression level in the above-described embodiment. However, the calculation method is not limited to this. For example, known data analysis software such as RMA or other new calculation methods can be applied. In short, it is sufficient if data indicating the amount of complementary strand formed read from the sensor is corrected using a statistical method.

Further, in the above-described embodiment, _{assuming that} the behavior pattern at each observation point (t _{1 to} t _n (see FIG. 6)) has an action correlation between expression and suppression, the gene expression level GE in the time course direction of the observation time It was set as the case where it became a pattern from which the code | symbol of the binary sequence (expression amount binary sequence) which took the positive or negative difference became completely the same or opposite. However, it does not necessarily have to be completely the same or opposite. That is, even if one or two of the codes are different, there can be a case where there is an action correlation between expression and suppression. The number of code differences can be set larger as the binary string is longer (the number of codes constituting the binary string is larger).

Further, instead of a binary string (expression binary string) pattern, another pattern may be adopted. For example, the correlation coefficient of the expression level at each observation point (t _{1 to} t _n (see FIG. 6)) to be compared is calculated, and this correlation coefficient should be the minimum that should have an action correlation between expression and suppression. It can be the case where it becomes more than a value.

As another example, the ratio of the time length of the transition portion having a certain proportional relationship to the expression level to be compared with the total measurement time length (t _n −t ₁ ) of the expression level is calculated, and this ratio is expressed and suppressed. It can be set as the case where it becomes more than the minimum value which should be there.

As another example, the transition amount (t _{1 to} t _n in FIG. 6) of the expression level is matched as a shape pattern and matched, and the overlap amount and angle when the degree of overlap of the shape pattern is the largest are expressed and It can be set as the case where it becomes more than the minimum value which should have an action correlation of suppression.

  In the above-described embodiment, cisNATSs of case A or case D, cisNATSs of case C, and transNATSs in the non-patent literature are used as classification elements. However, expression suppression mechanisms other than these may be used as classification elements.

  The present invention can be used in the bio-industry such as genetic experiments, creation of medicines, or patient follow-up.

It is a basic diagram which shows the whole structure of the gene regulatory network analysis system by this Embodiment. It is an approximate line figure used for explanation of hybridization. It is a basic diagram which shows the structural example of measurement data. It is a block diagram which shows the structure of a gene regulatory network analyzer. It is a basic diagram with which it uses for description of acquisition of the gene expression level per unit time in a target organism. It is an approximate line figure used for explanation of binarization of gene expression level. It is a graph which shows (1) when there exists a fixed proportional relationship in the increase / decrease transition of each gene expression level of the gene pair estimated to have the relationship between expression and suppression. It is a graph which shows (2) when there exists a fixed proportional relationship in the increase / decrease transition of each gene expression level of the gene pair estimated to have the relationship between expression and suppression. It is a basic diagram which shows an expression level binary string when the behavior of a gene expression level has the same or substantially the same relationship. It is a graph which shows (1) when there exists an approximate proportional relationship in the increase-and-decrease transition of each gene expression level of the gene pair estimated to have the relationship between expression and suppression. It is a graph which shows (2) when there exists an approximate proportional relationship in the increase-and-decrease transition of each gene expression level of the gene pair estimated to have the relationship between expression and suppression. It is a basic diagram which shows an expression level binary string when the behavior of a gene expression level is opposite or substantially opposite. It is a basic diagram which shows the example of a display of a gene regulatory network. It is a flowchart which shows a gene regulatory network analysis processing procedure.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Gene control network analysis system, 2 ... Genome server, 3 ... Fluorescence intensity measuring device, 4 ... Gene control network analysis device, 10 ... CPU, 11 ... ROM, 12 ... RAM, 13 ... Operation unit, 14 ... storage unit, 15 ... interface, 16 ... display unit, 21 ... gene expression level acquisition unit, 22 ... genome information acquisition unit, 23 ... expression level reading unit, 24 ... binarization Part, 25 ... classification part.

Claims (8)

An acquisition unit that acquires the expression level for each measurement time for a plurality of genes in the target cell;
For each gene that becomes a complementary sequence in the target cell, a complementary sequence depending on the behavior pattern of the expression level for each measurement time corresponding to the gene and the presence or absence of overlap in the same chromosome in the gene that becomes the complementary sequence A gene regulatory network analysis apparatus comprising: a classification unit that classifies species of an expression suppression mechanism for a gene to be expressed. For each gene that becomes a complementary sequence in the target cell, further comprising a generating unit that generates a binary string by taking a positive or negative difference in the expression level in the direction of passage of the observation time,
The classification part
The gene control according to claim 1, wherein the species of expression suppression mechanism for the gene serving as the complementary sequence is classified according to the pattern of the binary string and the presence or absence of overlap in the same chromosome in the gene serving as the complementary sequence. Network analysis device. The classification part
The gene regulatory network analysis apparatus according to claim 2, wherein the NATs are classified according to the binary string pattern and the presence or absence of overlap in the same chromosome in the gene serving as the complementary sequence. The classification part
4. The gene regulatory network analysis according to claim 3, which is classified into at least proven NATs and hypothetical NATs according to the binary string pattern and the presence or absence of overlap in the same chromosome in the gene serving as the complementary sequence. apparatus. The classification part
The gene regulatory network analyzer according to claim 3, wherein the gene is classified into at least cis-NATS and trans-NATS according to the binary string pattern and the presence or absence of overlap in the same chromosome in the gene serving as the complementary sequence. . The acquisition unit
The gene control network analysis apparatus according to claim 3, wherein the expression level is measured so that the expression level measurement interval in the gene expressed in the cells of the target organism falls within a range between a set upper threshold and a lower threshold. An acquisition step of acquiring an expression level for each measurement time for a plurality of genes in the target cell;
For each gene that becomes a complementary sequence in the target cell, a complementary sequence depending on the behavior pattern of the expression level for each measurement time corresponding to the gene and the presence or absence of overlap in the same chromosome in the gene that becomes the complementary sequence A gene regulatory network analysis method comprising: a classification step of classifying species of an expression suppression mechanism for a gene to be expressed. Against the computer,
Obtaining the expression level of each gene for a plurality of genes in a target cell;
For each gene that becomes a complementary sequence in the target cell, a complementary sequence depending on the behavior pattern of the expression level for each measurement time corresponding to the gene and the presence or absence of overlap in the same chromosome in the gene that becomes the complementary sequence A gene regulatory network analysis program that classifies the species of the expression suppression mechanism for the target gene.