JP4975334B2 - Storage area detection system considering evolutionary process - Google Patents

Description

  The present invention relates to genome analysis that examines the meaning of genomic sequences by comparing genomic sequences from a plurality of DNA (or amino acid) sequences, and in particular, an evolution process for finding and displaying a conserved region conserved in the process of evolution. The present invention relates to a storage area detection system that considers

In the prior art, genome analysis of humans and animals and plants has progressed by sequence analysis projects all over the world, and such information can be easily obtained through public databases. By comparing the genome sequences that are the targets of genome analysis among the DNA sequences in and between species in various organisms, a specific portion of each species in the genome sequence or common to all species It is possible to clarify the part, and it is possible to use the information about the specific part and the common part to help the process of evolution and the interpretation of biological meaning. For example, mammalian MHC (the Major
References on the Histocompatibility Complex area (Hughes
AL, Yeager M. Natural selection at major histocompatibility complex loci of
vertebrates.Annu Rev Genet.
1998; 32: 415-35 and McConnell TJ,
Talbot WS, McIndoe RA, Wakeland EK.The origin of MHC class II gene
polymorphism within the genus Mus. Nature.
1988 14; 332 (6165): 651-4. Or Lawlor DA, Ward
FE, Ennis PD, Jackson AP, Parham P. HLA-A and B polymorphisms predate the
divergence of humans and chimpanzees.Nature.
1988 15; 335 (6187): 268-71. Etc.), it has become clear by comparing the genomes that MHC has persisted and functioned in the genome sequence for several hundred years.

  Now, comparing genome sequences means capturing (ie, grasping) changes (mutations) that occur in the genome sequence during the evolution process. Specifically, changes in genome sequences (mutation) during evolution are specifically: Substitution / deletion / insertion / inversion. 1 to 4 are explanatory diagrams showing the state of these changes. FIG. 1 shows the change of the substitution, in which the base A in the genome sequence is replaced with C. FIG. 2 shows how the insertion changes. A base C is newly added and inserted between bases A and T in the genome sequence. FIG. 3 shows how the deletion changes, and the base T is deleted. FIG. 4 shows a state of change of inversion, in which ATT in the genome sequence is TTA and rearranged so that the order is reversed.

  Of these four types of changes, substitution occurs with a change of one base unit, but deletion, insertion, and inversion may occur at once in a whole block unit containing hundreds to tens of thousands of bases. When these changes occur during the evolution process, they accumulate in the genome sequence and change the entire genome sequence, resulting in the creation of different species of organisms.

  One of the important facts revealed by genome analysis by comparing genome sequences is that genome regions (genes, etc.) that are important for organisms are often not affected by changes in the genome sequence. It is. This can result in changes in such important genomic regions, as changes in such parts are often extinct in most cases. This is because it is believed that it is necessary for the living organisms that have not been received to exist to the present day without being extinct, and to remain untouched in important genomic regions. Comparing the DNA sequences of different species of organisms, depending on the species of organisms, they may have different DNA sequences from each other, but these have not changed when examined at the amino acid level There are many cases.

  Such a region that has not undergone a change in the genome sequence, such as an important genomic region, is called a conserved region. Researchers take advantage of the fact that this conserved region has not undergone changes in the genome sequence, and compare the genome sequences of different species of organisms with each other to find the conserved region. It is a clue to guess the meaning.

  Another important fact is that the genome sequence remains and shows the history of evolution. In general, closely related species (such as humans and chimpanzees) have more similar portions as genomic sequences than distantly related species (such as humans and yeast). This is because not so much time has passed between closely related species and long time has passed between distantly related species since the species have differentiated. It is also possible to grasp the evolutionary history by tracking the transition of the state of a gene containing a specific DNA sequence.

  FIG. 5 is an explanatory diagram showing the history of evolution due to the transition of the state of such a gene. In FIG. 5, a certain gene a including a DNA sequence is duplicated in the ancestors of species 1 and 2 to generate tandem genes a1 and a2 arranged in a line, and then the species is separated into different species of organisms. It shows a culture. Species 1 gene a1 and Species 2 gene a1 (or Species 1 gene a2 and Species 2 gene a2) share a common ancestor tandem gene a1 (or tandem gene a2). is called. On the other hand, the genes a1 and a2 in the species 1 or 2 are generated by duplication of the gene a, and this is called a paralog.

  In addition to those shown in FIG. 5, there is a type called xenolog (foreign) as an evolution due to the transition of the gene state. In this xenolog, a gene evolves without sharing its evolutionary origin with any other gene, which is derived from an unrelated species by symbiosis or viruses, ie horizontal propagation. It is said that it was caused by.

Furthermore, in addition to genes, SINEs (short
interspersed repetitive elements) and LINEs (long
There is a special arrangement called interspersed repetitive elements. These have the property of replicating themselves in the genome sequence and inserting this duplicated sequence at other positions, and since they have the property of not being deleted once inserted, these special sequences are also It is used as a clue to grasp the history of evolution. Past reports (Verneau O, Catzeflis F, Furano AV. Determination of the evolutionary
relationships in Rattus sensu lato (Rodentia: Muridae) using L1 (LINE-1)
amplification events. J Mol Evol.
1997 45 (4): 424-36. And Furano AV,
Hayward BE, Chevret P, Catzeflis F, Usdin K. Amplification of the ancient
murine Lx family of long interspersed repeated DNA occurred during the murine
radiation. J Mol Evol. 1994
38 (1): 18-27. And Murata S, Takasaki N,
Saitoh M, Okada N. Determination of the phylogenetic relationships among
Pacific salmonids by using short interspersed elements (SINEs) as temporal
landmarks of evolution.Proc Natl Acad
According to Sci US A. 1993 1; 90 (15): 6995-9, etc., these sequences can be used as markers for examining evolution within 50 million years after the occurrence of the species culture. Researchers have been inferring events in the history of evolution using information as markers using these special sequences.

  Actually, three methods are mainly used as a method for examining the conserved region in the genome sequence and the history of evolution. The first method is called dot matrix analysis, and is performed to find a conserved region that exists in common without being changed between two genome sequences. FIG. 6 is an explanatory diagram showing a state in which the storage areas existing in the ATGGCA array 1 and the CATTGGCT array 2 are analyzed by dot matrix analysis. In this dot matrix analysis, a matrix of 6 vertical elements × 8 horizontal elements corresponding to the lengths of the two arrays is created, and the arrays 1 and 2 are arranged along the vertical and horizontal axes of the matrix. Then, each element of the vertical axis and each element of the horizontal axis are compared, and if there are bases (or residues) that are the same elements on the vertical and horizontal axes, the vertical and horizontal axes of the same base Mark the dots corresponding to the coordinates of the axis.

  In FIG. 6, the corresponding dot is displayed as a dark color (emphasized) as a mark. When there is a storage area between the arrays 1 and 2, the marked dots are arranged in a diagonal direction so that the storage area can be grasped by visually confirming this. It has become. As shown by the portion surrounded by the dotted line in FIG. 6, the dark (highlighted) display dots are arranged in a diagonal direction, and the ATGGC of the array 1 and the ATTGGC of the array 2 are similar to form a storage area. Is clear. In addition, the conserved region between the reverse complement sequence and the sequence 2 is converted by converting the base of the sequence 1 into the base of the complementary strand, that is, converting A to T, T to A, G to C, and C to G. It is also possible to clarify. In this case, the marked dots are arranged in a diagonal direction opposite to that in the case of the array 1, and the storage area can be grasped by visually confirming this.

  The second method is a method called multiple alignment, and is a method for performing optimal rearrangement so that as many elements as possible are gathered in one column when a plurality of arrays are arranged. FIG. 7 is an explanatory diagram showing a technique based on multiple alignment. In FIG. 7, as a result of performing multiple alignment on the amino acid sequence as 15 genome sequences, a gap character (-) is inserted in the sequence so that the same amino acid (similar amino acid) is arranged in each column. Yes. Multiple alignment can be seen as a representation of the evolutionary history between the genomic sequences contained therein.

  If the number of amino acids differing from each other as a mismatch is small and a very good multiple alignment can be obtained, it is assumed that their amino acid sequences have been separated relatively recently from a common ancestor. On the other hand, there are more complex and distant evolutionary relationships between groups that have a large number of mismatches and cannot achieve good alignment. Some genome sequences are similar, with few mismatches, and if a genome sequence requires multiple alignments of a group of genome sequences that do not have many mismatches, find evolutionary relationships between those genome sequences. Is possible.

  Finally, the third method is a method called phylogenetic tree analysis. This is to analyze the family strains containing nucleotide sequences (or amino acid sequences) that are closely related to each other, and to determine the path from which the family was derived during the evolution process. FIG. 8 is an explanatory diagram showing a state in which a phylogenetic tree analysis is performed on genome sequences included in families obtained from eight species. The relationship between genome sequences is represented as a tree with a tree structure with each genome sequence placed at the end of the branch, and the branching relationship inside the tree is displayed reflecting the degree of affinity of different genome sequences. Yes. The length of the branch corresponds to the degree of the close / distant edge, and the shorter the length of the branch, the closer the relation is.

  In this phylogenetic tree analysis, it is possible not only to analyze the changes that have occurred in the evolution of individual organism species, but also to investigate the evolution of the family of genomic sequences by looking at the degree of affinity and relatedness / distantness. As a result, the genome sequence occupying adjacent branches on the phylogenetic tree can be determined to be the closest genome sequence. If a gene family is found as a genomic sequence in an organism or group of organisms, examining the phylogenetic relationship between the genes will help predict which genes have the same function. If these function predictions are obtained, the function can be confirmed by genetic experiments. Phylogenetic analysis is also used to track changes that occur in rapidly changing species such as viruses. Phylogenetic analysis of the type of change within a population reveals important information for applications such as epidemiology, such as whether a particular gene has undergone natural selection. Also, in conventional biochips, probes that specifically hybridize with partial sequences that exist in common in the base sequences of different targets corresponding to the nodes of the phylogenetic tree are spotted. Has been proposed (see, for example, Patent Document 1).

JP 2002-330768 A

  In the prior art, in order to compare genome sequences and read the biological meaning from them, find conserved regions conserved among multiple genome sequences as shown above, and It is necessary to investigate what species it is shared with, that is, what evolution it has made.

  However, it is difficult or very difficult to comprehensively understand the storage area and its evolutionary relationship, even if the above-mentioned conventional techniques or the above three methods are used. This is complicated. Dot matrix analysis reveals a conserved region between two genome sequences, but does not know from which evolutionary stage it is conserved. In multiple alignment analysis, even if it is stored in inversion, it cannot be detected. In addition, phylogenetic tree analysis shows the evolutionary process, but it is not clear what kind of genomic sequence is conserved in relation to each other, and at what level of evolution, inversion, insertion, or deletion occurred.

  For example, consider a case where a conventional method is used to determine what kind of conserved regions are common in a family of biological species that are evolutionarily close among the genome sequences to be compared. Researchers first perform a phylogenetic tree analysis to find families that are evolutionarily close. Then, multiple alignment is performed or dot matrix analysis is performed. However, when performing multiple alignment, it takes a lot of time as a practical problem to compare long sequences (several thousand bases or more). In addition, since multiple alignments are assumed to input genome sequences that are somewhat similar to each other, alignment is not successful when many intron sequences are included or when the input sequences are regions other than genes. Furthermore, as described above, this analysis cannot detect even if inversion occurs in the genome sequence. Therefore, there is a problem that the genome sequences to be compared are very limited.

  Moreover, even if the genome sequence is a sequence suitable for multiple alignment, it is necessary to visually confirm a conserved region that exists in common with the family sequence and does not exist in the non-family sequence. On the other hand, in dot matrix analysis, only two genome sequences can be compared at a time due to the nature of this analysis method. Therefore, when finding a conserved region common to the species of a family, repeat the dot matrix analysis between the sequences of the family to find the conserved region, and confirm that the region is not conserved with sequences that do not belong to the family. There must be. As the number of families and the total number of genome sequences to be compared increase, the amount of work to be compared by dot matrix analysis becomes enormous, and there is a problem that it becomes unmanageable.

  Therefore, the present invention has been made in view of the problems of the prior art, and the object of the present invention is to detect a conserved region from the genome sequence of a species to be subjected to genome analysis, and the relationship between each species. Another object of the present invention is to provide a storage area detection system that takes into account the evolution process that can clearly display the relationship between storage areas.

In order to solve the above-mentioned problems, the present invention is an evolution process for finding a conserved region that is evolutionarily conserved in a genomic sequence that is subject to genomic analysis among a plurality of DNA sequences. In the storage area detection system considering the
Sequence recognition means for referring to a phylogenetic tree obtained on the basis of a genomic sequence and recognizing a genomic sequence belonging to an intermediate node constituting the phylogenetic tree;
And a storage detection means for detecting a storage region in the genome sequence starting from the position of the same character string existing in the genome sequence belonging to the intermediate node.

  In such an invention, the sequence recognition means recognizes the genome sequence belonging to the intermediate node constituting the phylogenetic tree, and the storage detection means starts from the position of the same character string existing in the genome sequence belonging to the intermediate node. Since the conserved region in the genome sequence is detected by starting, it is possible to accurately detect the conserved region that has not undergone the sequence change from the genome sequence of the species to be analyzed.

In the storage area detection system considering the evolution process described above,
The storage detection means includes
Starting from the position of the same character string existing in the two genome sequences belonging to the intermediate node, the storage region in the genome sequence is detected, and the region until the number of mismatched characters reaches the predetermined number It may be detected as a storage area.

  In such an invention, the storage detection means detects the storage region in the genome sequence starting from the position of the same character string existing in the two genome sequences belonging to the intermediate node, and the mismatched character Since the area until the number reaches the predetermined number is detected as a storage area, an area that is substantially the same as a whole and has not undergone a sequence change and can be regarded as a storage area is appropriately detected as a storage area Can do.

In the storage area detection system considering the above evolution process,
The storage detection means includes
Starting from the position of the same character string existing in multiple genome sequences belonging to the intermediate node, the same conserved region that was detected is detected repeatedly while changing the intermediate node based on the conserved region detected in the genome sequence. Thus, a conserved region in the genome sequence belonging to all intermediate nodes may be detected.

  In such an invention, the storage detection means repeatedly detects the same storage region detected while changing the intermediate node, and detects the storage regions in the genome sequence belonging to all the intermediate nodes. It is possible to detect a conserved region in the genome sequence belonging to all the intermediate nodes constituting.

In the storage area detection system considering the above evolution process,
Each storage region in the genome sequence detected by the storage detection means is configured by a line having a different form for each, and branches forming the intermediate node on the phylogenetic tree are each stored region in the genome sequence belonging to the intermediate node. It is good also as providing the analysis result display means comprised by the line | wire of the form made to respond | correspond to, and displaying each said storage area | region and phylogenetic tree simultaneously.

  In such an invention, the analysis result display means configures each storage region with a line having a different form for each, and the branches forming the intermediate nodes on the phylogenetic tree are represented by the storage regions in the genome sequence belonging to the intermediate node. Since each storage area and phylogenetic tree are displayed at the same time, researchers can clearly distinguish and refer to each storage area, and each storage area and phylogenetic tree By referring to the correspondence with the intermediate node, it is possible to confirm the evolutionary preservation area and to guess the evolution process.

In the storage area detection system considering the above evolution process,
The analysis result display means includes
Each of the storage regions may be displayed simultaneously in combination with information on a known genome sequence.

  In such an invention, it is possible to estimate the evolution process with reference to information on known genomic sequences combined with each conserved region.

In the storage area detection system considering the above evolution process,
The analysis result display means includes
Each of the storage regions may be combined with a genome sequence including each storage region, and the same storage region included between the genome sequences may be displayed in association with each other.

  In such an invention, it is possible to check the evolutionary storage area by referring to the situation of the same storage area displayed in association with each other, and estimate the evolution process.

In the storage area detection system considering the above evolution process,
Sequence search means for searching for a genome sequence belonging to an intermediate node constituting the phylogenetic tree based on an arbitrary sequence;
Specific display means for displaying information on genome sequences belonging to the intermediate nodes constituting the phylogenetic tree with a specific display method with reference to information on the genome sequence obtained as a result of the search by the sequence search means Also good.

  In such an invention, it is possible to check the evolutionary process by referring to the information on the genome sequence displayed by a specific display method, and confirming the evolutionary preservation of an arbitrary sequence.

In the storage area detection system considering the above evolution process,
The specific display means is
The genome sequence obtained as a result of the search by the sequence search means may be displayed in association with the arbitrary sequence portion.

  In such an invention, it is possible to check the state of being stored by referring to the arbitrary sequence portion displayed in association with each other, and to estimate the evolution process.

  As described above, according to the present invention, it is possible to detect a conserved region from the genome sequence of a species subject to genome analysis and clearly display the relationship between each species and the relationship between each conserved region. is there.

Embodiments of the present invention will be described below with reference to the drawings.

  FIG. 14 is an explanatory diagram showing the overall configuration of the storage area detection system in consideration of the evolution process according to the present invention. The storage region detection system 100 includes a target sequence 1401 that is data of genome sequences to be compared in genome analysis, and configuration information that is information for configuring a phylogenetic tree using each of the target sequences 1401. 1413, a display device 1402 for displaying an analysis result of genome analysis as an image, etc., and a keyboard which is an input means for inputting information such as numerical values and document information in the storage area detection system 100 and for selecting operation 1403 and mouse 1404, a known genome sequence to be annotated as reference information to analysis result data of genome analysis, and a sequence DB 1405 storing information attached to the known genome sequence, a program memory 1407 to be described later, and an illustration Detect storage area and system by executing program stored in storage device A central processing unit 1406 (hereinafter referred to as CPU 1406) that performs various processes such as data construction and analysis result display, a program memory 1407 that stores a program required for each process performed by the central processing unit 1406, and a central processing A data memory 1411 that temporarily stores data such as calculation results necessary for processing in the device 1406 is provided.

  As shown in FIG. 14, the program memory 1407 includes a storage area calculation processing unit 1408 for performing processing for detecting storage areas stored between the target arrays 1401 from the input target arrays 1401, A phylogenetic tree calculation processing unit 1409 that performs processing for constructing a phylogenetic tree using the target array 1401 and an analysis result display processing program 1410 for performing processing for displaying these analysis / calculation results are provided. These programs can be stored in a recording medium such as a CD-ROM, DVD-ROM, MO, and floppy (registered trademark) disk, and provided by being read from the recording medium by the CPU 1406, or public such as the Internet. It can also be provided by being downloaded from a server via a network.

  The array DB 1405 may be stored in a storage device connected to the CPU 1406, or may be managed by a server computer installed at a remote location. From the database in the server computer, a public network such as the Internet may be managed. Alternatively, gene data included in the sequence DB 1405 may be acquired. The data memory 1411 includes input data 1412 that is used as input data in executing the program.

  FIG. 15 is an explanatory diagram showing an example of the target array 1401. Here, each genome sequence corresponding to the target sequence 1401 is displayed in the FASTA format, the name for identifying the genome sequence is displayed after “>”, and the genome sequence itself is displayed from the next line. ing. In addition, as a format representing the genome sequence, it may be displayed in the GenBank format or the EMBL format.

  FIG. 16 is an explanatory diagram illustrating an example of configuration information 1413 for configuring a phylogenetic tree using each target array 1401. In this configuration information 1413, leaf and branch lengths of the phylogenetic tree are associated with the names of the genome sequences of the target sequence 1401, and information on one intermediate node is formed by a set of parentheses and numerical values (the numerical values are It shows the length of the branch to the intermediate node at a position higher than that intermediate node). When the intermediate node further has an intermediate node lower than its own position (closer to the leaf in the tree), it is expressed in a nested structure. In other words, when displayed in BNF notation, it is as follows.

Node :: = (node, node): branch length from this intermediate node to its upper intermediate node | array name: branch length from this leaf to upper intermediate node

  In this configuration information 1413, two names or intermediate nodes surrounded by a pair of parentheses indicate the close relationship of genome sequences, and information on the relative relationship between intermediate nodes corresponding to the root of this phylogenetic tree Is configured. For example, “(Species 1:15, Species 2:10): 20” indicates an intermediate node of the portion 902 of the phylogenetic tree displayed in FIG. 9 to be described later. Species 1 (Leaf) to Species 1 and 2 The branch length to the branch point of 15 is 15, the branch length from seed 2 to the branch point of seed 1 and seed 2 is 10, and the branch length to this branch point and the intermediate node (node corresponding to 901) is 20 It shows that there is. In addition to this, as a format representing the relationship between the phylogenetic trees, it may be displayed in the Physlip format, CLUSTAL format, and Distance Matrix format.

FIG. 17 is a configuration diagram showing a data structure for creating index information related to all DNA (or amino acid) sequences corresponding to the target sequence 1401. The array KtupleArrayD included in the index information is an array of p ^k elements, and p indicates the number of types of elements constituting the array, that is, 4 for a DNA sequence and 20 for an amino acid sequence. . k indicates the length of the tuple (character string). Each tuple is assigned to each element of the array KtupleArrayD. For example, when the target sequence 1401 is a DNA sequence and k is 2, the array KtupleArrayD is composed of 16 elements, and each element includes AA, AT, AG, AC, TA, TT, TG, TC, GA, and GT.・ 16 tuples of GG, GC, CA, CT, CG, and CC are assigned.

  Each element of the array KtupleArrayD represents the position of the tuple where the tuple assigned to the element appears most rearward in the target array 1401. If the tuple assigned to the element is not in the array, it is represented by 0.

  The array IdxArrayD is an array having a length equal to that of the target array 1401 and is an array including elements assigned to each element of the target array 1401. Each element of the array IdxArrayD is assigned to each position on the target array 1401. If the same tuple as the tuple starting from the character assigned to each element appears in the array before that element, that element appears. Represents the position of the element that appears immediately before each of the elements. If the same tuple as each element does not appear before, it is represented by 0.

  FIG. 28 is an explanatory diagram showing the arrays KtupleArrayD and IdxArrayD created for the array GTCTCACGACACTC as the target array 1401. In this array, the tuple TC appears in the second, fourth, and thirteenth positions in the array, and the tuple TC appears last in the target array 1401 in the element (KtupleArrayD [8]) corresponding to the TC of the array KtupleArrayD. Position 13 is displayed. Also, in IdxArrayD [13], the same TC as the tuple TC appearing at position 13 is “4”, and the same TC as the tuple TC appearing at position 4 is present in IdxArrayD [4]. “2”, which is the position that appeared immediately before, is displayed. Therefore, as shown here, the location of a specific tuple can be searched at high speed by using the two arrays KtupleArrayD and IdxArrayD. The sequences KtupleArrayR and IdxArrayR are created for the reverse complement sequence of the DNA sequence (or amino acid sequence) as the target sequence 1401 in the same manner as the sequences KtupleArrayD and IdxArrayD.

  FIG. 18 is an explanatory diagram showing a data structure for recording the storage area of the target array 1401. The structure array ConservedReg indicated by this data structure is created for each target array 1401 if a storage area exists. The storage area has a position 1800 indicating a storage area, a storage area length 1801, and a storage area. It consists of each data of direction (whether forward direction or reverse direction) 1802.

  FIG. 19 is an explanatory diagram showing a data structure ListOfConservedReg for recording the relationship between the storage areas between the target arrays 1401. This data structure is created for each storage area at each intermediate node on the configuration information 1413. In order to indicate which array name 1900 for identifying the target array 1401 and which ConservedReg created in the target array 1401 corresponds, each structure array ConservedReg created for each array name 1900 is identified. Therefore, it is created from each data of index 1901.

  FIG. 20 is an explanatory diagram showing the data structure of an array AllOfConservedReg in which the array ListOfConservedReg representing the set of related storage areas described in FIG. 19 is collected. Each element of this array AllOfConservedReg displays a pointer linked to ListOfConservedReg, and one array AllOfConservedReg is created for each intermediate node on the configuration information 1413. Each of the different types of storage regions stored in the genome sequence belonging to the intermediate node corresponding to this array AllOfConservedReg is displayed by this array linked with each element and ListOfConservedReg. Note that the storage area detection system in consideration of the evolution process in this embodiment can also be realized by using a personal computer that is an information processing apparatus for performing various types of information processing that is generally used.

  Next, the operation of the storage area detection system considering the evolution process of the present embodiment having the above-described configuration will be described in detail with reference to the flowcharts shown in FIGS. In the flowcharts shown in FIG. 21 to FIG. 27, each of the phylogenetic trees 1413 necessary for displaying the image data shown in FIG. 9, FIG. 10, FIG. 11, FIG. A ConservedReg for the leaf, an array ListOfConservedReg that holds the association of the storage area, and an array AllOfConservedReg are obtained. In the operation described below, an algorithm for obtaining these three arrays for each intermediate node of the system tree 1413 from the target array 1401 and the system tree 1413 will be described.

  A schematic processing flow of the storage area detection system 100 in consideration of the evolution process in the present embodiment will be described with reference to a flowchart shown in FIG. First, the CPU 1406 of the storage area detection system 100 in consideration of the evolution process stores the target array 1401 and the phylogenetic tree configuration information 1413 input by the researcher using an external recording medium such as a floppy (registered trademark) disk or CD-ROM. Data is read, stored in the data memory 1411 and held as input data 1412 (step 2100). At this time, as for the configuration information 1413, even if the information of the phylogenetic tree itself is not read, only the parameter information necessary for configuring the phylogenetic tree is input, and the CPU 1406 creates the data of the configuration information 1413 based on the parameter information. It is also good to do.

  Next, the CPU 1406 performs processing for reading parameters k, w, and m for detecting a storage area and holding them as input data 1412 of the data memory 1411 (step 2101). Where k is the length of the tuple character string, w is the length of the window, m is the number of mismatches allowed in the window, that is, the maximum number of characters that are different from each other in the two genome sequences that detect the conserved region Shows the number. When detecting conserved areas, the number of mismatches that are different from each other in the two sequences is maximum m for consecutive w characters (bases or residues) in the area detected as the conserved area. Until now. For example, FIG. 29 shows the location of the conserved region between two genome sequences, sequence A and sequence B, where the window size w is 5 and the number of allowed mismatches m is 1. In this case, when the same character sequence is detected for every five consecutive character pairs and the storage area is detected, the number of mismatches is less than one for every five character pairs. The area 2601 is a storage area between the two sequences.

  Next, when the target sequence 1401 is a DNA sequence and it is desired to compare it as an amino acid sequence, the CPU 1406 performs processing for converting all the DNA sequences into amino acid sequences (step 2102).

  Next, the CPU 1406 performs processing for creating the index information shown in FIGS. 17 to 20, that is, KtupleArrayD [], IdxArrayD [], KtupleArrayR [], IdxArrayR [] for each target array 1401 as described above ( Step 2103). Details of this processing will be described later.

  Next, the CPU 1406 performs a process of determining whether or not all storage regions have been detected from the genome sequence belonging to the intermediate node for all intermediate nodes of the phylogenetic tree configured by the configuration information 1413 (step S1). 2104).

  Next, when all the storage areas are not detected (NO in step 2104), the CPU 1406, for all intermediate nodes of the phylogenetic tree configured by the configuration information 1413, genome sequences belonging to the intermediate node A process for selecting a storage area that has not yet been detected is performed (step 2105).

  Next, the CPU 1406 performs processing for detecting a storage area stored between the selected genome sequences (step 2106). The process for detecting this storage area will be described in detail later. When the process for detecting the storage area is completed, the process of step 2104 is executed.

  Next, when the CPU 1406 detects all the storage regions (YES in step 2104), the CPU 1406 searches the sequence DB 1405 based on the storage region, and stores information such as information on the genome sequences of species having the same storage region. If there is information related to the region, this related information is added to the results of the genome analysis described above. Then, a process for displaying the result of the genome analysis on the display device 1402 is performed (step 2107), and the entire process is terminated.

  Subsequently, the process of creating index information, that is, KtupleArrayD [], IdxArrayD [], KtupleArrayR [], IdxArrayR [] for each target array 1401 in step 2103 described above will be described in detail with reference to the flowchart shown in FIG. explain. First, the CPU 1406 performs a process of initializing all elements of KtupleArrayD [], IdxArrayD [], KtupleArrayR [], IdxArrayR [] corresponding to each target array 1401 with 0 (step 2200).

  Next, the CPU 1406 performs processing for setting the variable j = 1 (step 2201).

  Next, the CPU 1406 determines whether or not the variable j is a numerical value indicating the position of the element corresponding to the rearmost tuple on the array end side of the target array 1401, that is, j = array length−k (step). 2202). If j = array length−k (YES in step 2202), the process of step 2207 is executed.

Next, when j = array length−k is not satisfied (NO in step 2202), the CPU 1406 sets a tuple composed of k character strings starting from the j-th in the target array 1401 as K, and this K Processing to configure each element in the array KtupleArrayD [] by setting the element index of the array KtupleArrayD [] assigned to to (that is, the element number indicating the position of the element in the array KtupleArrayD []) to i (Step 2203). For example, the array KtupleArrayD [
], When tuple K is TC, i is “8” indicating the eighth element index.

  Next, the CPU 1406 substitutes the value of KtupleArrayD [i] for IndexArrayD [j], and inputs j to KtupleArrayD [i] (steps 2204 and 2205). Since KtupleArrayD [i] always displays the position of the tuple that appears at the rearmost side in the array of the target array 1401, these two steps (2204, 2205) increment the numerical value of the variable j ( Step 2206) Each time a new tuple corresponding to K appears in the array, the value of KtupleArrayD [i] is updated, and the value of KtupleArrayD [i] before the update is displayed in IdxArrayD [j]. It is a process of updating.

  Next, the above steps 2202 to 2206 are executed for all the variables j, thereby creating the index information of the arrays IndexArrayD [j] and KtupleArrayD [i] as shown in FIG.

  Next, the CPU 1406 executes the processing of the above steps 2202 to 2206 for all the variables j. If j = array length−k (YES in step 2202), the reverse of the target array 1401 is performed. Processing for setting the complement sequence as the target sequence is performed again (step 2207).

Next, the CPU 1406
Processing for creating index information arrays IndexArrayR [j] and KtupleArrayR [i] for the complement array is performed (steps 2208 to 2213). The CPU 1406 executes the same processing as the processing in steps 2202 to 2206 described above on the target array 1401 to create arrays IndexArrayR [j] and KtupleArrayR [i]. The processes in steps 2208 to 2213 described above are executed for all variables j. If j = array length−k (YES in step 2209), the process ends.

  Next, processing for detecting a storage region stored between each selected genome sequence in the above-described step 2106 will be described in detail with reference to flowcharts configured integrally in FIGS. First, the CPU 1406 performs processing for setting information seq1, seq2,..., SeqM for identifying the target sequence 1401 for each target sequence 1401 to be detected in the storage area selected in the above step 2105 ( Step 2300).

  Next, the CPU 1406 performs processing for setting the variable i = 1 (step 2301).

Then, CPU1406 determines number, i.e. whether a i> p ^k the variable i indicating the end position of the sequence KtupleArrayD (step 2302). If that is the i> p ^k (YES in Step 2302), the process ends.

  Next, the CPU 1406 performs processing for assigning the numerical value of the array KtupleArrayD [i] of the array of seq1 to the constant c1 (step 2303). The value of KtupleArrayD [i] created for the sequence of seq1 in 2103 is substituted for c1.

  Next, the CPU 1406 performs a process of determining whether or not c1 is 0 (step 2304). If c1 is 0 (YES in step 2304), the process of step 2328 is executed.

  Next, when c1 is not 0 (NO in step 2304), the CPU 1406 performs a process of substituting the numerical value of the array KtupleArrayD [i] of the array of seq2 into the constant c2 (step 2305). The value of KtupleArrayD [i] created for the sequence of seq2 in 2103 is substituted for c2.

  Next, the CPU 1406 performs a process of determining whether c2 is 0 (step 2306). If c2 is 0 (YES in step 2306), the process of step 2317 is executed.

  Next, when c2 is not 0 (NO in step 2306), the CPU 1406 indicates that the tuple assigned to KtupleArrayD [i] of the sequence seq1 exists in the sequences of seq1 and seq2, and these 2 A process of detecting a conserved region is performed starting from the same tuple existing at the c1 position of the two genome sequences seq1 and the c2 position of seq2 (step 2307). From these two genomic sequences seq1 and seq2, the conserved region is detected for every w consecutive strings (bases or residues) in the alignment from the start position of the process to be detected, and c1 and seq2 of seq1 The alignment is expanded from the c2 of the number of characters that match as the storage area. And the storage area is expanded within the range of the character string in which the number of mismatches that are different characters between genome sequences seq1 and seq2 is less than m, and the number of mismatches is more than m When there are many character strings, the position is set as the boundary position of the storage area. In this way, the storage area is detected, and if there is a storage area, a process of setting it as C is performed.

  Next, the CPU 1406 performs processing for determining whether or not a storage area exists in step 2307 (step 2308). If the storage area does not exist (NO in step 2308), the process of step 2316 is executed, and the CPU 1406 performs the process of substituting KtupleArrayD [c2] of seq2 into c2, and executes the processes after step 2306 (Step 2316).

  Next, when a storage region exists (YES in step 2308), the CPU 1406 detects the same storage region C in the remaining target sequences 1401, ie, seq3,..., SeqM genome sequences. Processing is performed (step 2309). A process of setting j = 3 for the variable j is performed.

  Next, the CPU 1406 determines whether or not the variable j is a numerical value indicating the last genome sequence of the target sequence 1401, that is, j> M (step 2310).

  Next, when j> M is not satisfied (NO in step 2310), the CPU 1406 performs processing for detecting the storage region C existing in the genome sequence seq j (step 2311). Processing for detecting the conserved region C in the sequence of seq j will be described in detail later.

  Next, the CPU 1406 performs processing for determining whether or not the storage area C exists in step 2311 (step 2312). When the storage area C does not exist (NO in step 2312), the process of step 2316 is executed, and the CPU 1406 performs a process of substituting KtupleArrayD [c2] of seq2 into c2, and performs the processes after step 2306. Execute (step 2316).

Next, when the storage area C exists (YES in Step 2312), the CPU 1406 increments the variable j by one, and executes the processing after Step 2310 again (Step 2313). If j> M in step 2310 (YES in step 2310), the processing of step 2314 is executed, and the CPU 1406 stores the storage areas C and C in each target array 1401 detected by the above processing. The information such as the position that appears in the sequence seq1, ..., seqM is stored in ConservedReg [
], ListOfConservedReg [], AllOfConservedReg [], and the processing of step 2316 is executed.

  Next, when c2 is 0 in step 2306 (YES in step 2306), the CPU 1406 performs a process of substituting KtupleArrayR [i] of seq2 into c2 (step 2317). The value of KtupleArrayR [i] created for the array of seq2 in 2103 is substituted for c2.

  Next, the CPU 1406 performs processing to determine whether c2 is 0 (step 2318). If c2 is 0 (YES in step 2318), the process of step 2315 is executed, and the CPU 1406 performs a process of substituting IdxArrayD [c1] of seq1 into c1, and executes the processes after step 2304 ( Step 2315).

  Next, when c2 is not 0 (NO in step 2318), the CPU 1406 indicates that the tuple assigned to KtupleArrayD [i] of the sequence seq1 exists in the sequence of seq1 and the reverse complement sequence of seq2. Thus, a process of detecting a conserved region is performed starting from the same tuple present at the c1 position in the c1 of the two genome sequences seq1 and the reverse complement sequence of seq2 (step 2319). This is the same as the processing in step 2307 described above, and a description thereof will be omitted.

  Next, the CPU 1406 performs processing to determine whether or not a storage area exists in step 2319 (step 2320). If the storage area does not exist (NO in step 2320), the process of step 2327 is executed, and the CPU 1406 performs the process of substituting IdxArrayR [c2] of seq2 into c2, and executes the processes after step 2318. (Step 2327).

  Next, when there is a storage region (YES in step 2320), the CPU 1406 detects the same storage region C in the remaining target sequences 1401, that is, the genome sequences of seq3,. Processing is performed (step 2321). A process of setting j = 3 for the variable j is performed.

  Next, the CPU 1406 determines whether or not the variable j is a numerical value indicating the last genome sequence of the target sequence 1401, that is, j> M (step 2322).

  Next, when j> M is not satisfied (NO in step 2322), the CPU 1406 performs processing for detecting a storage region C existing in the sequence of the genome sequence seq j (step 2323). Processing for detecting the conserved region C in the sequence of seq j will be described in detail later.

  Next, the CPU 1406 performs processing to determine whether or not the storage area C exists in step 2323 (step 2324). If the storage area C does not exist (NO in step 2324), the process of step 2327 is executed, and the CPU 1406 performs a process of substituting IdxArrayR [c2] of seq2 into c2, and performs the processes after step 2318. Execute (step 2327).

Next, when the storage area C exists (YES in Step 2324), the CPU 1406 increments the variable j by one and executes the processing after Step 2322 again (Step 2325). If j> M in step 2322 (YES in step 2322), the processing of step 2326 is executed, and the CPU 1406 stores the storage areas C and C in each target array 1401 detected by the above processing. The information such as the position that appears in the sequence seq1, ..., seqM is stored in ConservedReg [
], ListOfConservedReg [], AllOfConservedReg [] and execute the processing of step 2327.

  Next, when c1 is 0 in step 2304 (YES in step 2304), the CPU 1406 performs a process of substituting KtupleArrayR [i] of seq1 into c1 (step 2328). The value of KtupleArrayR [i] created for the sequence of seq1 in 2103 is substituted for c1.

  Next, the CPU 1406 performs processing for determining whether c1 is 0 (step 2329). If c1 is 0 (YES in step 2329), the process of step 2342 is executed, and the CPU 1406 increments the variable i by one and executes the processes after step 2302 (step 2342).

  Next, the CPU 1406 performs processing for substituting KtupleArrayD [i] of seq2 into c2 (step 2330). The value of KtupleArrayD [i] created for the sequence of seq2 in 2103 is substituted for c2.

  Next, the CPU 1406 performs processing to determine whether c2 is 0 (step 2331). If C2 is 0 (YES in step 2331), the processing after step 2343 is executed.

Next, when c2 is not 0 (NO in Step 2331), the CPU 1406 determines that the tuple assigned to KtupleArrayR [i] of the reverse complement sequence of seq1 is the reverse of seq1.
A conserved region starting from this same tuple that exists in the c1 and c2 positions in the reverse complement sequence of these two genomic sequences seq1. The process of detecting is performed (step 2332). This is the same as the processing in step 2307 described above, and a description thereof will be omitted.

  Next, the CPU 1406 performs processing to determine whether or not a storage area exists in step 2332 (step 2333). If the storage area does not exist (NO in step 2333), the process of step 2341 is executed, and the CPU 1406 performs the process of substituting IdxArrayD [c2] of seq2 into c2, and executes the processes after step 2331. (Step 2341).

  Next, when a storage region exists (YES in step 2333), the CPU 1406 detects the same storage region C in the remaining target sequences 1401, ie, seq3,. Processing is performed (step 2333). A process of setting j = 3 to the variable j is performed (step 2334).

  Next, the CPU 1406 determines whether or not the variable j is a numerical value indicating the last genome sequence of the target sequence 1401, that is, j> M (step 2335).

  Next, when j> M is not satisfied (NO in step 2335), the CPU 1406 performs a process of detecting the storage region C existing in the genome sequence seq j (step 2336). Processing for detecting the conserved region C in the sequence of seq j will be described in detail later.

  Next, the CPU 1406 performs processing for determining whether or not the storage area C exists in step 2336 (step 2337). If the storage area C does not exist (NO in step 2337), the processing after step 2341 is executed.

Next, when the storage area C exists (YES in step 2337), the CPU 1406 increments the variable j by one and executes the processing after step 2335 again (step 2338). If j> M in step 2335 (YES in step 2335), the processing of step 2339 is executed, and the CPU 1406 stores the storage areas C and C in each target array 1401 detected by the above processing. The information such as the position that appears in the sequence seq1, ..., seqM is stored in ConservedReg [
], ListOfConservedReg [], AllOfConservedReg [], and the processing of step 2341 is executed.

  Next, when c2 is 0 in Step 2331 (YES in Step 2331), the CPU 1406 performs a process of substituting KtupleArrayR [i] of seq2 into c2 (Step 2343). The value of KtupleArrayR [i] created for the array of seq2 in 2103 is substituted for c2.

  Next, the CPU 1406 performs processing to determine whether c2 is 0 (step 2344). If c2 is 0 (YES in step 2344), the process of step 2340 is executed, and the CPU 1406 performs a process of substituting IdxArrayR [c1] of seq1 into c1, and executes the processes after step 2329 ( Step 2340).

Next, when c2 is not 0 (NO in step 2344), the CPU 1406 determines that the tuple assigned to KtupleArrayR [i] of the reverse complement sequence of seq1 is the reverse of seq1.
It is supposed to be present in the complement sequence and in the reverse complement sequence of seq2, and the reverse of the c1 and seq2 in the reverse complement sequence of these two genomic sequences seq1
A process of detecting a conserved region is performed starting from the same tuple present at the c2 position in the complement sequence (step 2345). This is the same as the processing in step 2307 described above, and a description thereof will be omitted.

  Next, the CPU 1406 performs processing for determining whether or not a storage area exists in step 2345 (step 2346). If the storage area does not exist (NO in step 2346), the process of step 2353 is executed, and the CPU 1406 performs the process of substituting IdxArrayR [c2] of seq2 into c2, and executes the processes after step 2344. (Step 2353).

  Next, when the storage region exists (YES in step 2346), the CPU 1406 detects the same storage region C in the remaining target sequences 1401 to be detected, that is, the genome sequences of seq3,. Processing is performed (step 2347). A process of setting j = 3 for the variable j is performed.

  Next, the CPU 1406 determines whether or not the variable j is a numerical value indicating the last genome sequence of the target sequence 1401, that is, j> M (step 2348).

  Next, when j> M is not satisfied (NO in step 2348), the CPU 1406 performs processing for detecting a storage region C existing in the sequence of the genome sequence seq j (step 2349). Processing for detecting the conserved region C in the sequence of seq j will be described in detail later.

  Next, the CPU 1406 performs processing for determining whether or not the storage area C exists in step 2349 (step 2350). If the storage area C does not exist (NO in step 2350), the processing after step 2353 is executed.

Next, when the storage area C exists (YES in Step 2350), the CPU 1406 increments the variable j by one, and executes the processing after Step 2348 again (Step 2351). If j> M in step 2348 (YES in step 2348), the processing of step 2352 is executed, and the CPU 1406 stores the storage areas C and C in each target array 1401 detected by the above processing. The information such as the position that appears in the sequence seq1, ..., seqM is stored in ConservedReg [
], ListOfConservedReg [], AllOfConservedReg [], and the process of step 2353 is executed. As described above, processing for detecting a storage region stored between each selected genome sequence is performed.

  Next, detection of the conserved region C present in the sequence of the genome sequence seq j in the above steps 2311, 2323, 2336, and 2349 will be described in detail with reference to the flowchart shown in FIG. First, the CPU 1406 performs a process of setting the variable i to the index corresponding to the first tuple located in the foremost side in the storage area C (step 2400).

  Next, the CPU 1406 performs a process of setting the value of KtupleArrayD [i] of the genome sequence seq j as c1 (step 2401).

  Next, the CPU 1406 performs a process of determining whether or not c1 is 0 (step 2402). If c1 is 0 (YES in step 2402), the process of step 2406 is executed, and the CPU 1406 performs the process of substituting KtupleArrayR [i] of seqj into c1, and executes the processes after step 2407 ( Step 2406).

  Next, when c1 is not 0 (NO in step 2402), the CPU 1406 indicates that the top tuple of the storage area C exists in the sequence of seqj, and starts from the c1th of the genome sequence seqj. , The storage area is detected based on the data of the storage area C detected in steps 2307, 2319, 2332, and 2345 (steps 2403 and 2404). Character strings are compared from the start position of the processing to be detected in these genome sequences seqj and the start position in the storage region C, and the storage region is stored for every w character strings (bases or residues) that are continuously aligned. , And the number of character strings that match the storage area C is expanded by extending the alignment from c1 of seqj. Then, the storage region is expanded within the range of the character string in which the number of mismatches that are different characters between the genome sequence seqj and the storage region C is m or less, and the number of mismatches is m When there are more character strings, the position is set as the boundary position of the storage region in the genome sequence seqj. In this way, the storage area is detected, and when the storage area exists, processing for temporarily storing it in the data memory 1411 is performed. Even when the detected storage area is shorter than the storage area C, the detected storage area is newly set as the storage area C in the genome sequence seqj and stored in the data memory 1411.

  Next, the CPU 1406 performs a process of substituting IdxArrayD [c1] of seqj into c1, and executes the processes after step 2402 (step 2405).

  Next, when c1 is 0 in step 2402 (YES in step 2402), the CPU 1406 executes the process of step 2406, and the CPU 1406 performs a process of substituting KtupleArrayR [i] of seqj into c1 ( Step 2406).

  Next, the CPU 1406 performs a process of determining whether or not c1 is 0 (step 2407). If c1 is 0 (YES in step 2407), the process ends.

Next, when c1 is not 0 (NO in Step 2407), the CPU 1406 reverses the storage area C with the top tuple being seqj.
The conserved region is determined based on the data of conserved region C detected in steps 2307, 2319, 2332, and 2345, starting from c1 in the reverse complement sequence of genomic sequence seqj. The detection process is performed (steps 2408 and 2409). This is the same as the processing in steps 2403 and 2404 described above, and a description thereof will be omitted.

  Next, the CPU 1406 performs a process of substituting IdxArrayR [c1] of seqj into c1, and executes the processes after step 2407 (step 2410).

  When the CPU 1406 performs the operation of the storage area detection system 100 in consideration of the evolution process described above, the storage stored in the target array 1401 for each leaf belonging to the intermediate node belonging to the tree constituted by the configuration information 1413. An area is detected and a structure array ConservedReg, an array ListOfConservedReg holding the association of the storage areas, and an array AllOfConservedReg are obtained. The CPU 1406 performs processing for creating image data shown in FIGS. 9, 10, 11, 12, and 13 and displaying the image data on the display device 1402 as described below.

  FIG. 9 is an explanatory diagram showing a phylogenetic tree created using data of the structure array ConservedReg, the array ListOfConservedReg, and the array AllOfConservedReg. In this phylogenetic tree, the left half of the display screen has a phylogenetic tree configured using the names of the target sequences 1401 (for example, species 1 to 6), and the right half has storage regions on the genome sequence corresponding to each target sequence 1401. It is displayed. Each branch of the phylogenetic tree is displayed by a line having a different form such as a different color, a solid line, a dotted line, or a one-dot chain line for each target array 1401. Thus, the sequence family is identified, for example, the line 901 represents the family of species 1, species 2, species 3, and species 4, and the line 902 represents the family of species 1, species 2. In FIG. 9, the color and line form are changed in order to identify each branch. However, other representation methods may be used in practice, for example, an implementation method for displaying a tag, number, name, etc. near the line. May be used.

  Further, on the right side of the phylogenetic tree in FIG. 9, the position of the storage area and the level at which the storage area is stored in the phylogenetic tree are schematically displayed for each target array 1401. The level of the phylogenetic tree corresponds to the color and line form of the branches of the left half of the phylogenetic tree. For example, an area stored only in the species 1 and 2 is an intermediate node to which the species 1 and 2 belong. This is a portion 905 indicated by using a line of the same color and form as the line 902 forming the line. Similarly, the region conserved only in Species 1, Species 2, Species 3, and Species 4 is the portion indicated by 903 indicated by using the same color and shape line as the line 901, and all the target sequences 1401 The region stored in (Seed 1 to Seed 6) is the portion indicated by 904 using the same color and shape as the upper line of the line 901. What is preserved between distantly related species should be preserved between closely related species, and in the display result of FIG. 9, the conserved area represented by the line near the root in the phylogenetic tree is It is displayed that it exists in all the target arrays 1401 near the leaves.

  FIG. 10 is an explanatory diagram showing the conserved region of species 1 as the target sequence 1401 shown in FIG. 9 as an actual base sequence (or amino acid sequence). FIG. 10 allows the researcher to know the DNA (or amino acid) sequence of the conserved region of the target sequence 1401. In the figure of FIG. 10, the area of the arrow searches the database of the seed 1 sequence on a public network such as the Internet or a local network based on this DNA (or amino acid) sequence, and finds the result. It is displayed by mapping (the direction of the arrow is the direction of the search sequence). Researchers can also refer to this result to know the correspondence between the DNA (or amino acid) sequence of this conserved region and known information. In the figure, a situation where a known result is found in the storage area is shown, so that a researcher can know the biological meaning of the storage area.

  FIG. 11 is an explanatory diagram showing the relationship between the storage areas in each target array 1401 shown in FIG. The color and shape of the line correspond to the line displaying the storage area in the right half of FIG. In order to select the target array 1401 to be displayed (in the case of FIG. 11, seed 1, seed 2, seed 3, and seed 4), for example, a line on which a storage area such as 901 is displayed on the display screen of FIG. Can be selected with the mouse 1404 to display a menu as to whether or not to display such. Alternatively, an arbitrary array set may be selected and displayed from the input menu. In FIG. 11, the storage area 1101 on the left side of the screen has the same orientation for the seed 1, the seed 2, and the seed 3, but the orientation differs for the seed 4. By referring to this, researchers at some point in the evolution, inversion occurred only in Species 4 or changed direction, or the fact that Species 1, Species 2, and Species 3 all changed direction due to inversion, etc. It becomes possible to guess, and it can be a clue to know the process of evolution from now on.

  FIG. 12 is also an explanatory diagram showing the relationship between the storage areas in each target array 1401 shown in FIG. In FIG. 12, species 5 and species 6 in the phylogenetic tree of FIG. 9 are displayed as targets. By referring to the screen of FIG. 12, the researcher can infer the fact that there are two regions 1201 in species 5 and one in species 6 and that seed 5 overlaps region 1201 in the past. Similarly, in the area 1202, it is possible to guess the fact that the same area has overlapped with the seed 6 in the past.

  FIG. 13 is an explanatory diagram showing a situation in which the storage area corresponding to the species in the phylogenetic tree shown in FIG. 9 also exists in other species. FIG. 13 shows a situation in which the same sequence as that in the other species is searched for the 1301 region of the species 5 and it is found in the species 3 and 6. The found sequences are clearly displayed with the species name highlighted. Here, referring to the screen of FIG. 13, the researcher found that the evolutionary tree itself was wrong as one of the reasons that the region 1301 was found in Species 3, and the other was the SINE array, LINE array, etc. It can be estimated that a retrotransposon sequence has been inserted. On the contrary, by using this fact, it is possible to realize a usage mode in which whether or not the phylogenetic tree is correct is confirmed by repeatedly searching the found storage area.

  As described above, in the storage region detection system 100 in consideration of the evolution process in the present embodiment, the CPU 1406 performs KtupleArrayD [], IdxArrayD [], KtupleArrayR [] on the data of the target sequence 1401 to be subjected to genome analysis. , IdxArrayR [] processing for creating index information, and a storage area stored in the target array 1401 for each leaf belonging to the intermediate node belonging to the phylogenetic tree configured by the configuration information 1413 is detected and the structure array ConservedReg And processing for obtaining an array ListOfConservedReg that holds the association of the storage areas and an array AllOfConservedReg.

  Then, the CPU 1406 uses the data of the structure array ConservedReg, the array ListOfConservedReg, and the array AllOfConservedReg, the actual genome sequence of each target sequence 1401 constituting the phylogenetic tree and the phylogenetic tree, and each storage region in each target sequence 1401 Display data showing the relationship between them, and the storage region between the genome sequences is associated with the evolution process and displayed on the display screen 1402 together with the information of the phylogenetic tree. It is possible to estimate the evolution process of the conserved region of the species of the target sequence 1401 and use the evolution process as a clue. And it is expected to gain a more fundamental understanding of biology.

(Other embodiments)
In the process performed using the flowcharts shown in FIG. 21 and FIG. 22, the target sequence 1401 and the configuration information 1413 are used to select the genome sequence that is the detection target of the storage region. However, the present invention is not limited to this. This process can also be executed for a set of arbitrary genome sequences other than the target sequence 1401. In that case, the processing of step 2104 in FIG. 21 is skipped without being executed, and an “arbitrary sequence set” other than the target sequence 1401 is selected as the genome sequence to be detected in the storage area in the processing of step 2105. You can do it.

  Further, in order to obtain the analysis result as shown in FIG. 13, this is the same as the processing for detecting the storage region C existing in the sequence seq j described in the processing using the flowchart shown in FIG. Can be executed. If the storage region C is also detected in the genome sequence as another target sequence 1401 by this processing, the display result shown in FIG. 13 can be obtained by recording the position of the storage region C in the genome sequence.

  Concerning genome analysis that examines the meaning of genomic sequences by comparing genomic sequences from multiple DNA (or amino acid) sequences, especially conserved in consideration of evolutionary processes to find and display conserved conserved regions during evolutionary processes It can be used in an area detection system.

It is explanatory drawing explaining substitution among the changes of the genome sequence in evolution. It is explanatory drawing explaining insertion among the changes of the genome sequence in evolution. It is explanatory drawing explaining deletion among the changes of the genome sequence in evolution. It is explanatory drawing explaining inversion among the changes of the genome sequence in evolution. It is explanatory drawing explaining the ortholog and paralog which are the types of an ancestor arrangement | sequence. It is explanatory drawing which shows the example of a dot matrix analysis. It is explanatory drawing which shows the example of a multiple alignment analysis. It is explanatory drawing which shows the example of a phylogenetic tree analysis. It is explanatory drawing which shows the screen displayed combining the relationship of a phylogenetic tree and a preservation | save area | region. It is explanatory drawing which shows the screen displayed combining the preservation | save area | region and known information. It is explanatory drawing which shows the screen which matched and displayed the storage area | region by the some arrangement | sequence. It is explanatory drawing which shows the screen which matched and displayed the storage area | region by the some arrangement | sequence. This is one of the display examples of the present invention in which a storage area found in a certain sequence is searched for another sequence and the search result is displayed. It is a functional block diagram which shows roughly the system configuration | structure of the preservation | save area | region detection system 100 in consideration of the evolution process in this Embodiment. It is explanatory drawing which shows the data structure of the object arrangement | sequence 1401 of the preservation | save area | region detection system 100 in consideration of the evolution process in this Embodiment. It is explanatory drawing which shows the data structure of the structure information 1413 of the preservation | save area | region detection system 100 in consideration of the evolution process in this Embodiment. It is explanatory drawing which shows the data structure for displaying the index information of the object arrangement | sequence 1401 in the preservation | save area | region detection system 100 in consideration of the evolution process in this Embodiment. It is explanatory drawing which shows the data structure for recording the preservation | save area | region of the target arrangement | sequence 1401 in the preservation | save area | region detection system 100 in consideration of the evolution process in this Embodiment. FIG. 11 is an explanatory diagram showing a data structure for recording a correspondence relationship between storage areas between target arrays 1401 in the storage area detection system 100 in consideration of the evolution process in the present embodiment. It is explanatory drawing which shows the data structure for recording a storage area of a different kind in the storage area detection system 100 in consideration of the evolution process in this Embodiment. In the preservation | save area | region detection system 100 which considered the evolution process in this Embodiment, it is a flowchart which shows the flow of the whole process roughly. 5 is a flowchart showing in detail processing for creating index information for each target array 1401 in the storage area detection system 100 in consideration of the evolution process in the present embodiment. It is a flowchart which shows in detail the process which detects a preservation | save area | region in the preservation | save area | region detection system 100 in consideration of the evolution process in this Embodiment. It is a flowchart which shows in detail the process which detects a preservation | save area | region in the preservation | save area | region detection system 100 in consideration of the evolution process in this Embodiment. 6 is a flowchart showing in detail a process for calculating a storage area in the storage area detection system considering the evolution process of the present invention. It is a flowchart which shows in detail the process which detects a preservation | save area | region in the preservation | save area | region detection system 100 in consideration of the evolution process in this Embodiment. It is a flowchart which shows in detail the flow of the process which detects the preservation | save area | region in a genome sequence in the preservation | save area | region detection system 100 in consideration of the evolution process in this Embodiment. It is explanatory drawing which showed an example of arrangement | sequence data KtupleArrayD and IdxArrayD in the preservation | save area | region detection system 100 in consideration of the evolution process in this Embodiment. It is explanatory drawing which showed the state which detected the preservation | save area | region between two arrangement | sequences in the preservation | save area | region detection system 100 which considered the evolution process in this Embodiment.

Explanation of symbols

100 storage area detection system 1401 target array 1402 display device 1403 keyboard 1404 mouse 1405 array DB
1406 Central processing unit 1407 Program memory 1408 Storage area calculation processing section 1409 Phylogenetic tree calculation processing section 1410 Analysis result display processing section 1411 Data memory 1412 Input data 1413 Phylogenetic tree 2601 Storage area

Claims (7)

In a conserved region detection system that takes into account the evolution process of finding conserved regions that are evolutionarily conserved without undergoing sequence changes in the genomic sequence to be subjected to genomic analysis among a plurality of DNA sequences,
Sequence recognition means for referring to a phylogenetic tree obtained on the basis of a genomic sequence and recognizing a genomic sequence belonging to an intermediate node constituting the phylogenetic tree;
And a storage detecting means will detect the save area that is present in the genome sequence belonging to the intermediate node,
The storage detection means includes
Starting from the position of the same character string existing in the two genome sequences belonging to the intermediate node, the region within the genome sequence is detected for each fixed character string, and the number of mismatched characters is less than the predetermined number The storage area is detected by expanding the area where the character string exists as a storage area, and setting the position where the number of mismatched characters exceeds a predetermined number as the boundary position of the storage area. A storage area detection system that takes into account the evolutionary process that is characteristic. In the storage area detection system considering the evolution process according to claim 1 ,
The storage detection means includes
Starting from the position of the same character string existing in multiple genome sequences belonging to the intermediate node, the same conserved region that was detected is detected repeatedly while changing the intermediate node based on the conserved region detected in the genome sequence. A storage region detection system that takes into account the evolutionary process, characterized by detecting storage regions in the genome sequence belonging to all intermediate nodes. In the storage area detection system considering the evolution process according to claim 2 ,
Each storage region in the genome sequence detected by the storage detection means is configured by a line having a different form for each, and branches forming the intermediate node on the phylogenetic tree are each stored region in the genome sequence belonging to the intermediate node. A storage area detection system taking into account the evolution process, characterized by comprising analysis result display means configured to display each storage area and phylogenetic tree at the same time. In the storage area detection system considering the evolution process according to claim 3 ,
The analysis result display means includes
A storage region detection system considering an evolution process, wherein each storage region is simultaneously displayed in combination with information on a known genome sequence. In the preservation area detection system in consideration of the evolution process according to claim 4 ,
The analysis result display means includes
A storage area detection system considering an evolution process, wherein each storage area is combined with a genome sequence including each storage area and the same storage area included between the genome sequences is displayed in association with each other. In the storage area detection system considering the evolution process according to claim 5 ,
Sequence search means for searching for a genome sequence belonging to an intermediate node constituting the phylogenetic tree based on an arbitrary sequence;
Specific display means for displaying information on genome sequences belonging to the intermediate nodes constituting the phylogenetic tree with a specific display method with reference to information on the genome sequence obtained as a result of the search by the sequence search means A storage area detection system that takes into account the evolutionary process. In the preservation area detection system considering the evolution process according to claim 6 ,
The specific display means is
A storage region detection system in consideration of an evolution process, characterized in that a genome sequence obtained as a result of searching by the sequence search means is displayed in association with the arbitrary sequence portion.

Images