KR20030049499A - Method for scoring and selection for optimum probes in probes design - Google Patents

Abstract

PURPOSE: A method for scoring and selecting optimum probes in probes design is provided, thereby designing optimum oligonucleotide probes, and increasing the efficiency of designing and production of a DNA chip. CONSTITUTION: A method for scoring and selection for optimum probes in probes design comprises the steps of: (a) setting up at least one factor selected from the group consisting of hybridization melting point(TM), difference of hybridization melting point(ΔTM), self-alignment, mutation site, probe length, repetitive sequence content and GC content; (b) representing the response function of the selected factors of the step (a) as simple cosine, an exponential function and a hyperlolic function, and determining used factors; and (c) preparing the optimum function for selection of probes by combination of response functions for each of the factors of the step (b) and scoring each probe to select the optimum probes.

Description

Method for scoring and selection for optimum probes in probes design

The present invention relates to a method for scoring and selection of probes for optimal probe design, and more particularly to (a) hybridization melting point (T _M ), hybridization melting point difference (ΔT _M ), self-alignment, Setting one or more factors selected from the group consisting of mutation location, probe length, degree of repetition sequence and probe selection criteria factors of GC content; (b) expressing the behavior function of each factor selected in step (a) by a simplified cosine, exponent, and hyperbolic function, and defining the arguments used therein; And (c) a method for designing an optimized oligonucleic acid probe consisting of creating an optimization function of probe selection and scoring each probe to select an optimal probe by combining the behavioral functions of the factors in step (b). will be.

There are several types of mutations in the human genome, including single nucleotide polymorphisms (SNPs), microsatellite, insertions and deletions (Kleyn PW and Vesell ES, 1998). Several techniques in the search for sequencing and genotyping of high-productivity mutations include the use of gel electrophoresis-based genotyping, fluorescent dye-based genotyping, and molecular labeled sequencing. beacon genotyping, mass spectrometry genotyping, and DNA chip-based microarrays (Shi MM, 2001).

Currently, DNA chips have been developed as an indispensable tool for experimentation, diagnosis, and treatment in genomics, medicine, and biochemistry. Gene expression analysis by DNA chips is currently one of the most widely used tools in functional genomics. It is also possible to determine nucleic acid sequences using DNA chips or to determine mutations in SNPs and nucleic acid sequences (Yershov and Barsky et. Al., 1996).

DNA chips require the design of nucleic acid probes to detect mutations in disease-related genes for the purpose of diagnosing and treating specific diseases. The design of such a probe is important to detect the mutations present in the target nucleic acid specifically and with high reliability through hybridization with the target nucleic acid. When hybridizing with a probe between a mutant target oligonucleotide and a mutant normal target oligonucleotide, the detection power of the mutation can be increased, that is, the difference in each signal can be maximized. The probe needs to be designed so that it

It is possible to make an array of probes on the stationary phase that are exactly complementary to the reference sequence or have one or more variations, and this process is called probe design. Unlike planting one strand of cDNA as a probe on a stationary phase, such as a cDNA chip, the process of properly selecting an optimized probe from hundreds of probes based on hybridization bonds is important in oligonucleotide DNA chips. There are many factors to consider in the design of probes, especially in the case of oligonucleotide probes, the determination of the length and length of the probes is based on hybridization melting point (T _M ), hybridization melting point difference (ΔT _M ), and self-alignment ( Self-alignment (hairpin, self-alignment), mutation location, probe length, repeat sequence degree, GC content is determined by considering the factors.

When designing an oligonucleotide probe for reading a target nucleic acid mutation or SNP, it is most important to determine whether the target nucleic acid and nucleotide sequence are exactly complementary or different. U. S. Patent No. 6,228, 575 B1 presents experimental data on the position of mutations. That is, the intensity difference of the fluorescence signal when the target sample was applied after planting a probe consisting of eight oligonucleotides (change position of the mutation from the first nucleic acid to the eighth nucleic acid based on 5 ') was compared. . When the position of the mutation was in the middle of the probe (ie when the fourth and fifth nucleic acids changed), the difference in signal intensity was maximized. The DNA chip bound the 3 'portion of the probe onto the stationary phase and found that the variation in fluorescence intensity was greater when the mutation was located at the first nucleic acid relative to the 5' than when the mutation was located at the eighth nucleic acid. Therefore, when drawing the position of the mutation (relative to 5 ') on the horizontal axis and the intensity difference of the fluorescence signal on the vertical axis, a cosine shape with a tail on the right was drawn. From this figure, it can be seen that when the mutation position is medium (50%), the target nucleic acid mutation or SNP can be identified as the highest signal. The patent, however, did draw a picture of the mutation location and signal, but did not define a cosine function.

International patent WO 01/06013 A1 describes a method for evaluating one or more probes that can maximize the sensitivity and specificity for hybridization of a target nucleic acid. In addition, European Patent Publication No. 1,103,910 (EP # 1,103,910 A1) discloses a method for automatically selecting an oligonucleic acid probe for detecting DNA mutations. These patents specifically list the method of calculating hybridization melting points and obtaining various factors using a thermodynamic neighboring model to obtain the sensitivity and specificity of the probe. There is no mention of methods for scoring and selecting oligonucleic acid probes using optimization functions by simulation.

U. S. Patent No. 5,556, 749 relates to a computer system for designing optimized oligonucleotide probes and relates to calculations and designs relating to nucleic acid probes in DNA or mRNA hybridization processes. The probe designed in this invention takes into account the specificity or covalentness of GenBank DNA, mRNA sequence and candidate probe. U.S. Patent No. 6,228,593 B1 is a computer system that analyzes the sequence of nucleic acid by analyzing the fluorescence intensity by hybridization of nucleic acid probes in the biochip to calculate the probability for an unknown base.

US Pat. No. 5,837,832 discloses a method of making a DNA chip by making a probe array using a probe that is exactly complementary to a reference sequence and a probe that differs in one or more bases. The former method is called a tiled array method, and once the probe length is determined (usually 12-18), a five-row probe array is usually used (Figure 1). That is, the top row places probes that are completely complementary to normal DNA, and the four columns below place A, G, C, and T mutations, each of which can probe the mutation at the midpoint of each probe. In some cases, there may be a space in the lower row for measuring the background signal, or a probe that can be used to detect insertion or loss of bases. It is true that the design of such probes can detect highly reliable sequence variations, but it does not take into account the thermodynamic coupling force between the probe and the target sample, and it is not flexible to design the probe, but also to find one variation. The number of probes has become so large that many probes must be planted, such as increasing the density of DNA chips.

Accordingly, the present inventors have diligently researched to overcome the problems of the prior art, and as a result, hybridization melting point (T _M ), hybridization melting point difference (ΔT _M ), self-alignment (hairpin, self-alignment), and variation If information about factors such as location, probe length, repeat sequence degree and GC content are reflected in the probe design (Fig. 2), it is possible to easily select an optimized oligonucleotide probe to facilitate the fabrication of DNA chips. It confirmed and completed this invention.

Therefore, the main object of the present invention is to provide a method for designing an optimized oligonucleic acid probe for efficient and simple DNA chip fabrication.

1 is a view showing a tile array probe design method of the prior art.

Figure 2 is a diagram showing the oligonucleic acid probe design method of the present invention.

3 is a graph showing the behavior function φ ₁ of the hybridization melting point (T _M ) X ₁ as a cosine function.

4 is a graph showing the behavior function φ ₂ of the hybridization melting point difference ΔT _M X ₂ factor as an exponential function.

5 is a graph showing the behavior function φ ₃ of the self-alignment X ₃ factor as a hyperbolic function.

Fig. 6 is a graph showing the behavior function φ ₄ of the shift position X ₄ factor as a cosine function.

7 is a graph showing the behavior function φ ₅ of the probe length X ₅ factor as a cosine function.

Figure 8 is a graph showing the behavior of the function φ ₆ as a hyperbolic function repeat sequence level (repeated) X ₆ factor.

9 is a graph showing the behavior function φ ₇ of the GC content X ₇ factor as a cosine function.

In order to achieve the object of the present invention, the present invention provides a method of designing an optimized oligonucleic acid probe.

The method for designing an optimized oligonucleic acid probe of the present invention consists of the following steps:

(a) from a group consisting of hybridization melting point (T _M ), hybridization melting point difference (ΔT _M ), self-alignment, mutation location, probe length, repeat sequence degree and probe selection criteria factors Setting one or more factors to be selected;

(b) expressing the behavior function of each factor selected in step (a) by a simplified cosine, exponent, and hyperbolic function, and defining the arguments used therein; And

(c) creating an optimization function of probe selection by combining the behavioral functions of each of the factors in step (b) and scoring each probe to select the optimal probe.

There are many factors to consider in the design of probes, especially in the case of oligonucleotide probes, the determination of the length and length of the probes is based on hybridization melting point (T _M ), hybridization melting point difference (ΔT _M ), and self-alignment ( Self-alignment (hairpin, self-alignment), mutation location, probe length, repeat sequence degree, GC content is determined by considering the factors. When hybridizing the target target nucleic acid (mutant and normal target oligonucleotide) with the probe, the detection power of the mutation increases, that is, the difference between each signal is maximized and high Probes need to be designed to have reliability. The present invention is a method for selecting a plurality of oligonucleotides for the detection of mutations in SNPs and nucleic acid sequences as an optimal probe, and after obtaining the behavior function of each of these factors, combining them to set one optimization formula, and to each probe candidate group It is a method that enables the selection of simple and efficient probes through scoring.

In the present invention, preferably the behavior function φ ₁ of the hybridization melting point (T _M ) X ₁ factor can be represented by the following equation (1).

[Equation 1] φ ₁ = cos ((X ₁ -T0) * π / (T0 / 2) + A0 (X ₁ -A1) / (T0 / 2)

(Wherein, X ₁ value when T0 = φ ₁ is maximum);

A0 = constant to adjust the asymmetry, if A0> 0, T0 moves higher (φ ₁ is the left tail), if A0 <0, T0 moves lower (φ ₁ is the right tail), and if A0 = 0, T0 is unchanged. φ ₁ is symmetric, the asymmetry increases as the absolute value of A 0 increases;

A1 = 3/4 T0).

In the present invention, preferably, the behavior function φ ₂ of the hybridization melting point difference ΔT _M X ₂ factor can be expressed by the following equation (2).

[Equation 2] φ ₂ = exp (X ₂ -dT0) / A0

Wherein dT0 = {(X ₂ ) at 50% φ ₂ } − ln (A0 / 2);

_{{(X 2) at 50%} φ 2} X 2 having a φ of ₂ = 50%;

A0 = constant that controls the slope of the exponential function, the larger the slope).

In the present invention, preferably, the behavior function φ ₃ of the self-alignment X ₃ factor can be expressed by the following equation (3).

[Equation 3] φ ₃ = A0 / (X ₃ )

(Wherein, A 0 = constant to adjust the slope of the hyperbolic function, the larger the smoother).

In the present invention, preferably, the behavior function φ ₄ of the shift position X ₄ factor can be expressed by the following expression (4).

[Equation 4] φ ₄ = cos (X ₄ -p0) * π / (p0 * 2) + A0 * X ₄ / (p0 * 2)

₍₄ X value when the above formula, p0 = φ ₄ up;

A0 = constant to adjust the asymmetry, p0 moves high if A0> 0 (φ ₄ is left tail), p0 moves low if A0 <0 (φ ₄ is right tail), p0 is unchanged if A0 = 0 φ ₄ is symmetric, the asymmetry increases as the absolute value of A0 increases.

In the present invention, preferably, the behavior function φ ₅ of the probe length X ₅ factor can be expressed by the following expression (5).

[Equation 5] φ ₅ = cos (X ₅ -L0) * π / (L0 * 2) + A0 * X ₅ / (L0 * 2)

(Wherein, X ₅ value when L0 = φ ₅ is maximum;

A0 = constant to adjust the asymmetry, if A0> 0, L0 moves high (φ ₅ is left tail), if A0 <0, L0 moves low (φ ₅ is right tail), if A0 = 0, L0 is unchanged φ ₅ is symmetric, the asymmetry increases as the absolute value of A0 increases.

In the present invention, the factor function φ ₆ of the repeated sequence degree (X ₆ ) factor is preferably represented by the following formula (6).

[Equation 6] φ ₆ = A0 / (X ₆ )

(Wherein, A 0 = constant to adjust the slope of the hyperbolic function, the larger the smoother).

In the present invention, the printing function φ ₇ of the GC content X ₇ factor is preferably represented by the following equation (7).

₇ = cos (X ₇ -GC0) * π / (GC0 * 2) + A0 * X ₇ / (GC0 * 2)

(In the above formula, the value of X ₇ where GC0 = φ ₇ is the highest value.

A0 = constant to adjust the asymmetry, if GC0> 0, GC0 moves high (φ ₇ is left tail), if A0 <0, GC0 moves low (φ ₇ is right tail), and if A0 = 0, GC0 is invariant φ ₇ is symmetric, the asymmetry increases as the absolute value of A0 increases.

In the present invention, the optimization function preferably represents the degree of effect of each factor in correlation with each factor behavior function as an exponential power for two or more factors as shown in Equation 8 below. By scoring, the optimal probe is selected.

(8) ψ = φ ₁ (X ₁ ) ^a1 φ ₂ (X ₂ ) ^a2 φ ₃ (X ₃ ) ^a3 φ ₄ (X ₄ ) ^a4 φ ₅ (X ₅ ) ^a5 φ ₆ (X ₆ ) ^a6 φ ₇ (X ₇ ) ^a7

(In the above formula, the definitions of the factors X _i , i = 1, 2, ..., 7 and the behavior function φ _i , i = 1, 2, ..., 7 are the same as those of the formulas 1 to 7 above ( The non-selected factors can be omitted), and the exponents ai, i = 1,2, ..., 7 are the weighting factors of φ _i , i = 1,2, ..., 7, respectively. Defined).

Hereinafter, the present invention will be described in more detail with reference to Examples and accompanying drawings. Since these examples are only for illustrating the present invention, the scope of the present invention is not to be construed as being limited by these examples.

(Example)

1.Behavior function φ ₁ of the hybridization melting point (T _M ) X ₁ factor

The behavior function φ ₁ represents the difference in the signal of the hybridization reaction as the hybridization melting point (T _M ) X ₁ factor changes. Normalize to 0 when there is no signal difference and to 1 when the difference between signals is large. FIG. 3 is a cosine function to simulate the best signal difference when the hybridization melting point is 60 ^° C. When the function φ ₁ is 1, that is, the equation is as follows, and FIG. 3 is A0. = 0.

Where A0 is a constant to adjust the asymmetry and if A0> 0, T _M with the maximum value moves higher than 60 ^o C (φ ₁ is the left tail); if A0 <0, T _M with the maximum value is 60 ^o C Moving lower (φ ₁ is the right tail), if A0 = 0, T _M with the maximum value is 60 ^o C and φ ₁ is symmetric. As the absolute value of A 0 increases, asymmetry increases.

2. hybridization raised gradually (△ T _M) behavior function of factor X ₂ φ ₂

The behavior function φ ₂ represents the difference in the signal of the hybridization reaction as the hybridization melting point difference (ΔT _M ) X ₂ factor changes. Normalize to 0 when there is no signal difference and to 1 when the difference between signals is large. FIG. 4 is an exponential function that simulates the best signal difference when the behavior function φ ₂ is 1 when the hybridization melting point difference is 10 ^° C or more. In other words, it is as follows.

Where exp3 is a constant that adjusts the slope, and the larger the value, the steeper the slope. In addition, the constant 6 was used as a constant to adjust φ ₂ to 0.5 when the hybridization melting point difference was 6 ^° C. The equation was corrected to 1 when φ ₂ had a value greater than 1 in the exponential function. That is, all behavior functions φ ₁ to φ ₇ are defined as follows to have a value between 0 and 1.

φ _i = 0 if φ _i <0, i = 1, 2, ..., 7

φ _i = φ _i if 0 ≤ φ _i ≤ 1, i = 1, 2, ..., 7

φ _i = 1 if φ _i > 1, i = 1, 2, ..., 7

3. The behavior of the function of the self-alignment (self-alignment) X ₃ factor φ ₃

The behavior function φ ₃ represents the difference in the signal of the hybridization reaction as the self-alignment X ₃ factor changes. Self-alignment refers to the value at which the probe forms a hairpin or cross hybridization, and has zero when no self-alignment and is more preferred as a probe. 5 is a hyperbolic function, and the larger the self-alignment value, the more the φ ₃ approaches 0 and represents the difference in the bad signal. In other words, it is as follows.

Where 0.5 is a constant that controls the slope of the hyperbolic function, and as the value increases, the slope becomes smooth.

4. Behavior function φ ₄ of transition position X ₄ factor

The behavior function φ ₄ represents the difference in the signal of the hybridization reaction as the variation position X ₄ factor changes. Mutation position indicates the position of the mutation in the sequence from the 5 'position to a value of 0-1. FIG. 6 illustrates that the behavior function φ ₄ shows the best signal difference when the variation position is 50% as a cosine function. In other words, the equation is as follows, and FIG. 6 shows a case where A0 = 0.

Where A0 is a constant to adjust the asymmetry, and if A0> 0, the shift position with the maximum value moves higher than 50% (φ ₄ is the left tail); if A0 <0, the shift position with the maximum value is lower than 50% If the shift (φ ₄ is the right tail), A0 = 0, the maximum shift is 50% and φ ₄ is symmetric. As the absolute value of A 0 increases, asymmetry increases.

5. Behavior function φ ₅ of probe length X ₅ factor

The behavior function φ ₅ represents the difference in the signal of the hybridization reaction as the probe length X ₅ factor changes. Normalize to 0 when there is no signal difference and to 1 when the difference between signals is large. FIG. 7 simulates the best signal difference when the behavior function φ ₅ is 1 when the probe length is 20 bases as a cosine function. In other words, the equation is as follows, and FIG. 7 shows a case where A0 = 0.

Where A0 is a constant to adjust the asymmetry, and if A0> 0, the probe length with maximum value moves higher than 20 bases (φ ₅ is the left tail); if A0 <0, the probe length with maximum value is lower than 20 bases If the shift (φ ₅ is the right tail), A0 = 0, the maximum probe length is 20 bases, and φ ₅ is symmetric. As the absolute value of A 0 increases, asymmetry increases.

6. The behavior of the function repeat sequence approximately ₆ X ₆ factor φ

The behavior function φ ₆ represents the difference in the signal of the hybridization reaction with the change in the degree of repetition sequence X ₆ . The degree of repetition sequence indicates the number of bases with the highest repetition among the bases of the probe. 8 is a hyperbolic function, and as the degree of the repetition sequence increases, φ ₆ approaches 0, indicating that the difference between the signals is poor. In other words, it is as follows.

0.8 is a constant that controls the slope of the hyperbolic function. The larger the value is, the gradual the slope becomes.

7.Behavior Function φ ₇ of GC Content X ₇ Factor

The behavior function φ ₇ represents the difference in the signal of the hybridization reaction as the GC content X ₇ factor changes. Normalize to 0 when there is no signal difference and to 1 when the difference between signals is large. FIG. 9 simulates the best signal difference when the behavior function φ ₇ is 1 when the GC content is 50% as a cosine function. In other words, the equation is as follows, and FIG. 6 shows a case where A0 = 0.

Where A0 is a constant to adjust the asymmetry, where A0> 0 moves the GC content with the maximum value higher than 50% (φ ₇ is the left tail), and when A0 <0, the GC content with the maximum value is lower than 50% Movement (φ ₇ is the right tail), if A0 = 0, the GC content with the maximum value is 50% and φ ₇ is symmetric. As the absolute value of A 0 increases, asymmetry increases.

8. Scoring the Probe by the Optimization Function ψ

Using the factors of the above 1 to 7 using the optimization function ψ of the following probe was correlated and scored the degree of effect of each factor. The optimal probe was selected by correlating the scores of two or more factors as the exponential power of each factor function and correlating the degree of effect of each factor.

ψ = φ ₁ (X ₁ ) ^a1 φ ₂ (X ₂ ) ^a2 φ ₃ (X ₃ ) ^a3 φ ₄ (X ₄ ) ^a4 φ ₅ (X ₅ ) ^a5 φ ₆ (X ₆ ) ^a6 φ ₇ (X ₇ ) ^a7

Here, the exponents ai, i = 1,2, ..., 7 can be defined as the weighting factors of the factor functions φ _i , i = 1,2, ..., 7 respectively. Set all to 1.

Here, examples for the following three probes are shown.

Sequence Hybrid Melting Point (T _M ) Hybrid Melting Point Difference (△ T _M ) Self-alignment % Of variation Probe length Repetition Sequence GC content Optimum function, ψ ctgtgggAtgttgtg 53.6 7.3 0 53.3 15 3 53.3 0.03 gtgtggcgAagatgg 56.3 9.6 0 60 15 2 60 0.56 tggcgAagatggtca 55.1 12.0 0 40 15 2 53.3 0.30

Here, the uppercase base in the sequence indicates where the mutation of the desired base is located. Hybridization melting point, hybridization melting point difference, and self-alignment values were obtained using MeltCalc ^™ program (Schutz and von Ahsen, 1999), but may be obtained using similar software. If one of the above three probes is to be selected, the second sequence gtgtggcgAagatgg has the highest optimization function as ψ = 0.56 and can be selected. Therefore, according to the present invention, it is possible to increase the design and fabrication efficiency of DNA chips by allowing researchers or experimenters to design optimized oligonucleotide probes.

As described above, according to the present invention, a researcher or an experimenter can design an optimized oligonucleotide probe, thereby increasing the design and manufacturing efficiency of the DNA chip.

[References]

1.Burchard J, "Methods for determining the specificity and sensitivity of oligonucleotides for hybridization," WO 01/06013 A1 (2001).

2. Chee M, Cronin MT, et. al., “Arrays of nucleic acid probes and biological chips,” US Patent 5,837,832 (1998).

3. Gingeras TR, Mack D, et al., "Chip-based species identification and phenotypic characterization of microorganisms," US Patent 6,228,575 B1 (2001).

Kleyn PW, Vesell ES, "Genetic variation as a guide to drug development," Science 281: 1820-1821 (1998).

5. Lipshutz R, Walker MG, "Computer-aided probability base calling for arrays of nucleic acid probes on chips," US Patent 6,228,593 B1 (2001).

6. Mitsuhashi M, Cooper AJ, Waterman MS and Pevzner PA, "Oligoprobe designstation: A computerized method for designing optimal DNA probes," US Patent 5,556,749 (1996).

7. Schutz E, "Method of automatically selecting oligonucleotide hybridization probes," European Patent 1,103,910 A1 (2001).

8. Schutz E and Ahsen, "Spreadsheet software for thermodynamic melting point prediction of oligonucleotide hybridization with and without mismatches," Biotechniques 27: 1218-1224 (1999).

9. Shi MM, "Enabling large-scale pharmacogenetic studies by high-throughput mutation detection and genotyping technologies," Clinical Chemistry 47 (2): 164-172 (2001).

10. Yershov G, Barsky V, et al., "DNA analysis and diagnostics on oligonucleotide microchips (sequencing by hybridization / hybridization pattern)," Proc. Natl. Acad. Sci. USA, 93: 4913-4918 (1996).

Claims (9)

How to design an optimized oligonucleic acid probe consisting of the following steps: (a) from a group consisting of hybridization melting point (T _M ), hybridization melting point difference (ΔT _M ), self-alignment, mutation location, probe length, repeat sequence degree and probe selection criteria factors Setting one or more factors to be selected; (b) expressing the behavior function of each factor selected in step (a) by a simplified cosine, exponent, and hyperbolic function, and defining the arguments used therein; And (c) creating an optimization function of probe selection by combining the behavioral functions of each of the factors in step (b) and scoring each probe to select the optimal probe. The method of claim 1, wherein the behavior function φ ₁ of the hybridization melting point (T _M ) X ₁ factor is φ ₁ = cos ((X ₁ -T0) * π / (T0 / 2) + A0 (X ₁ -A1) / (T0 / 2) (Wherein, X ₁ value when T0 = φ ₁ is maximum); A0 = constant to adjust the asymmetry, if A0> 0, T0 moves higher (φ ₁ is the left tail), if A0 <0, T0 moves lower (φ ₁ is the right tail), and if A0 = 0, T0 is unchanged. φ ₁ is symmetric, the asymmetry increases as the absolute value of A 0 increases; A1 = 3/4 T0) Method characterized in that. The method of claim 1, wherein the behavior function φ ₂ of the hybridization melting point difference (ΔT _M ) X ₂ factor is φ ₂ = exp (X ₂ -dT0) / A0 Wherein dT0 = {(X ₂ ) at 50% φ ₂ } − ln (A0 / 2); _{{(X 2) at 50%} φ 2} X 2 having a φ of ₂ = 50%; A0 = constant to adjust the slope of the exponential function, the larger the slope is) Method characterized in that. The method of claim 1, wherein the behavior function φ ₃ of the self-alignment X ₃ factor is φ ₃ = A0 / (X ₃ ) (Wherein, A0 = a constant that adjusts the slope of the hyperbolic function, the larger the smoother) Method characterized in that. The method of claim 1, wherein the behavior function φ ₄ of the variation position X ₄ factor is φ ₄ = cos (X ₄ -p0) * π / (p0 * 2) + A0 * X ₄ / (p0 * 2) ₍₄ X value when the above formula, p0 = φ ₄ up; A0 = constant to adjust the asymmetry, p0 moves high if A0> 0 (φ ₄ is left tail), p0 moves low if A0 <0 (φ ₄ is right tail), p0 is unchanged if A0 = 0 φ ₄ is symmetric, and the asymmetry increases as the absolute value of A0 increases.) Method characterized in that. The method of claim 1, wherein the behavior function φ ₅ of the probe length X ₅ factor φ ₅ = cos (X ₅ -L0) * π / (L0 * 2) + A0 * X ₅ / (L0 * 2) (Wherein, X ₅ value when L0 = φ ₅ is maximum; A0 = constant to adjust the asymmetry, if A0> 0, L0 moves high (φ ₅ is left tail), if A0 <0, L0 moves low (φ ₅ is right tail), if A0 = 0, L0 is unchanged φ ₅ is symmetric, asymmetry increases as the absolute value of A0 increases) Method characterized in that. The method of claim 1, wherein the behavior function φ ₆ of the repeated sequence X ₆ factor is φ ₆ = A0 / (X ₆ ) (Wherein, A0 = a constant that adjusts the slope of the hyperbolic function, the larger the smoother) Method characterized by The method according to claim 1, wherein the behavior function φ ₇ of the GC content X ₇ factor is φ ₇ = cos (X ₇ -GC0) * π / (GC0 * 2) + A0 * X ₇ / (GC0 * 2) (In the above formula, the value of X ₇ where GC0 = φ ₇ is the highest value. A0 = constant to adjust the asymmetry, if GC0> 0, GC0 moves high (φ ₇ is left tail), if A0 <0, GC0 moves low (φ ₇ is right tail), and if A0 = 0, GC0 is invariant φ ₇ is symmetric, and as the absolute value of A0 increases, asymmetry increases) Method characterized by The method of claim 1, wherein the optimization function correlates the degree of effect of each factor with the power of each factor function with respect to two or more factors as shown in the following equation: ψ = φ ₁ (X ₁ ) ^a1 φ ₂ (X ₂ ) ^a2 φ ₃ (X ₃ ) ^a3 φ ₄ (X ₄ ) ^a4 φ ₅ (X ₅ ) ^a5 φ ₆ (X ₆ ) ^a6 φ ₇ (X ₇ ) ^a7 (Wherein, the definitions of the factors X _i , i = 1, 2, ..., 7 and the behavior functions φ _i , i = 1, 2, ..., 7 are the same as those of claims 2 to 8 The non-set factors can be omitted), and the exponents ai, i = 1,2, ..., 7 are the weighting factors of φ _i , i = 1,2, ..., 7 respectively. Defined).