JP5998674B2 - Comparative analysis method of small RNA expression level - Google Patents

Description

  The present invention relates to a method, apparatus, and program for comparative analysis of small RNAs among a plurality of specimens.

  Non-coding RNA (ncRNA) is a general term for RNA that does not encode proteins, and is broadly classified into housekeeping RNA and regulatory RNA. There are ncRNAs of various lengths, especially molecules with less than 200 bases are called small RNAs.

  Known housekeeping RNAs include ribosomal RNA (rRNA), transport RNA (tRNA), small nuclear RNA (snRNA) involved in splicing, and small nuclear RNA (snoRNA) involved in rRNA modification. ing.

  Regulatory RNA has attracted particular attention in recent years as a factor that plays an important role in elucidating biological functions, and plays an important role in regulating gene expression by regulating gene expression and intracellular distribution of RNA. Recently, it is becoming clear that it is responsible. The gene expression suppression mechanism that this regulatory RNA functions is called RNA interference (RNAi), and was clarified in an experiment using nematodes in 1988, and then the existence of a similar mechanism in Drosophila and mammalian cells It became. The ncRNA as a regulatory RNA has a chain length of approximately 20-25 bases, and its mechanism of action is the suppression of translation by microRNA (miRNA), cleavage of target mRNA by small interference RNA (siRNA), and target DNA It is broadly divided into gene silencing through heterochromatinization of regions.

  miRNA is transcribed from genomic DNA as RNA (precursor) with a hairpin-like structure. This precursor is cleaved by a dsRNA cleaving enzyme (Drosha, Dicer) having a specific enzyme RNase III cleaving activity, then changed into a double-stranded form, and then becomes a single strand. One of the antisense strands is incorporated into a protein complex called RISC and is considered to be involved in mRNA translational suppression. Thus, miRNA has different aspects at each stage after transcription, so usually when miRNA is targeted (detection target), such as a hairpin structure, a double-stranded structure, a single-stranded structure, etc. Various forms need to be considered. miRNA consists of RNA of 15 to 25 bases, and its existence has been confirmed in various organisms.

  On the other hand, siRNA is excised from long-chain dsRNA such as virus, transposon, transgene, endogenous dsRNA, etc. by dsRNA cleaving enzyme (Dicer) having RNase III cleavage activity. Thereafter, one antisense RNA of dsRNA is incorporated into a protein complex called RISC or RITS, and is involved in mRNA degradation or transcriptional repression as a complex. Therefore, siRNA can be in a double-stranded state as dsRNA, or in a single-stranded state forming a complex with RISC. Therefore, when siRNA is the target (detection target) It is necessary to consider various forms such as long dsRNA, siRNA after cleavage, or single strand.

  When gene expression analysis is performed using a DNA microarray, it is well known that errors occur in the data obtained depending on the specimen, the experimenter, and the experimental conditions. Therefore, a data correction method for correcting the error has been devised. For the correction, a method based on the premise that there is no difference in the expression level when any sample is expressed as a group of gene expression data for any sample is used. . Global normalization method, quantile method, lowess method, 75 percentile method and so on.

  In addition, focusing on a specific gene (beta actin, GAPDH, etc.) whose expression level is the same among samples, a method of correcting data for each sample is also performed so that the detected value of that gene is constant. .

  When analyzing small RNAs by DNA microarrays, correction methods such as the global normalization method, the quantile method, the lowess method, and the 75 percentile method used in gene expression analysis as described above are used. As a method to correct the expression level of a specific gene, housekeeping RNA (U1snoRNA, U2snoRNA, U3snoRNA, U4snoRNA, U5snoRNA, U6snoRNA, 5SrRNA, 5.8SrRNA) among small RNAs expressed in the sample is used. A method of correcting by using these has been proposed (Patent Document 1, Patent Document 2).

  In Patent Documents 1 and 2, when miRNA, which is a small RNA, is detected, the detection result of miRNA is corrected so that the detected value of 5SrRNA detected at the same time is constant in all samples.

JP 2007-75095 A JP 2007-97429 A

Since the expression level of small RNA varies greatly from sample to sample, a method based on the assumption that there is no difference in expression level between samples cannot be used. Even if it is applied, there is a concern that an incorrect correction is made. In addition, it has been pointed out that small RNAs contained in housekeeping RNAs such as U1snoRNA, U2snoRNA, U3snoRNA, U4snoRNA, U5snoRNA, U6snoRNA, 5S rRNA, and 5.8S rRNA have a constant expression level between samples. It is not effective.
As described above, in a small RNA analysis using a DNA microarray, there is no effective correction method for any sample.
Accordingly, an object of the present invention is to provide a means for appropriately correcting the expression level of a plurality of small RNAs measured by a microarray or the like so that comparative analysis of small RNA expression levels between samples can be performed more accurately than before. It is to provide.

  As a result of diligent research, the inventors of the present application measured the mRNA contained in the sample RNA simultaneously with the small RNA in the sample RNA extracted from the sample containing the mRNA and the small RNA, and then obtained the signal obtained from the mRNA capture probe. It was found that by correcting the signal value of the small RNA using the value, the signal correction of the small RNA can be performed more accurately than before, and the present invention has been completed.

That is, the present invention is a method for comparative analysis of the expression level of small RNA between a plurality of specimens,
A measurement step of measuring the expression levels of a plurality of mRNAs simultaneously with the measurement of the expression levels of a plurality of small RNAs for each of the plurality of specimens;
A representative value acquisition step of acquiring a representative value represented by a logarithmic value from the measured value of the mRNA expression level for each specimen;
The arbitrarily selected first sample is used as a reference sample, and the difference between the mRNA representative value of the reference sample and the mRNA representative values of the remaining second and subsequent samples is used as a correction coefficient for each of the second and subsequent samples. Acquiring a correction coefficient;
Correcting the small RNA expression level measured in the second and subsequent samples using the obtained correction coefficients for the second and subsequent samples, respectively; and a small RNA expression level in the reference sample and the second Including a comparison step that compares the corrected small RNA expression level in subsequent samples,
In the correction coefficient acquisition step, when a value obtained by subtracting the mRNA representative value of the second and subsequent samples from the mRNA representative value of the reference sample is acquired as a correction coefficient, the small RNA expression level in the second and subsequent samples is acquired in the correction step. The correction is performed by adding a correction coefficient to the logarithmic value of the measured value,
In the correction coefficient acquisition step, when a value obtained by subtracting the mRNA representative value of the reference sample from the mRNA representative value of the second and subsequent samples is acquired as a correction coefficient, the small RNA expression level in the second and subsequent samples is acquired in the correction step. The method provides the correction by subtracting a correction coefficient from the logarithmic value of the measured value.

The present invention is a small RNA expression analyzer for comparative analysis of the expression level of small RNA in a plurality of specimens,
For each of a plurality of specimens, storage means for storing a plurality of small RNA expression levels and a plurality of mRNA expression levels measured simultaneously,
For each sample, representative value acquisition means for acquiring a representative value represented by a logarithmic value from the measured value of the mRNA expression level,
The arbitrarily selected first sample is used as a reference sample, and the difference between the mRNA representative value of the reference sample and the mRNA representative values of the remaining second and subsequent samples is used as a correction coefficient for each of the second and subsequent samples. Correction coefficient acquisition means for acquiring,
Correction means for correcting the small RNA expression level measured in the second and subsequent samples, respectively, using the correction coefficients for the second and subsequent samples acquired by the correction coefficient acquiring means;
An output means for outputting a comparison result between the small RNA expression level of the reference sample and the corrected small RNA expression level in the second and subsequent samples,
When the correction coefficient acquisition unit acquires a value obtained by subtracting the mRNA representative value of the second and subsequent samples from the mRNA representative value of the reference sample as the correction coefficient, the correction unit obtains the small RNA expression level in the second and subsequent samples. The correction is performed by adding a correction coefficient to the logarithmic value of the measured value,
When the correction coefficient acquisition unit acquires a value obtained by subtracting the mRNA representative value of the reference specimen from the mRNA representative value of the second and subsequent specimens as a correction coefficient, the correction means obtains a small RNA expression level in the second and subsequent specimens. An apparatus is provided for performing the correction by subtracting a correction coefficient from a logarithmic value of a measured value.

Furthermore, the present invention provides a computer for comparative analysis of small RNA expression levels among a plurality of specimens.
A storage means for storing a plurality of small RNA expression levels and a plurality of mRNA expression levels measured simultaneously for each of a plurality of samples,
For each specimen, representative value acquisition means for acquiring a representative value represented by a logarithmic value from the measured value of the mRNA expression level,
An input means for inputting a first sample designated as a “reference sample” among a plurality of samples;
Correction coefficient acquisition means for acquiring the difference between the mRNA representative value of the reference specimen and the mRNA representative values of the remaining second and subsequent specimens as a correction coefficient for the second and subsequent specimens,
Correction means for correcting the small RNA expression level measured in the second and subsequent samples using the correction coefficients for the second and subsequent samples acquired by the correction coefficient acquisition means, and the small RNA of the reference sample A program for outputting the comparison result between the expression level and the corrected small RNA expression level in the second and subsequent samples, and functioning as an output means,
When the correction coefficient acquisition unit acquires a value obtained by subtracting the mRNA representative value of the second and subsequent samples from the mRNA representative value of the reference sample as the correction coefficient, the correction unit obtains the small RNA expression level in the second and subsequent samples. The correction is performed by adding a correction coefficient to the logarithmic value of the measured value,
When the correction coefficient acquisition unit acquires a value obtained by subtracting the mRNA representative value of the reference specimen from the mRNA representative value of the second and subsequent specimens as a correction coefficient, the correction means obtains a small RNA expression level in the second and subsequent specimens. The program is provided for performing the correction by subtracting a correction coefficient from the logarithmic value of the measured value.

Furthermore, the present invention provides a computer-readable recording medium on which the program of the present invention is recorded .

  According to the present invention, when measuring the expression level of a large number of small RNAs using a microarray or the like and comparing the small RNA expression levels between samples, the small RNA expression level can be corrected more accurately than before. . This makes it possible to more accurately perform comparative analysis of small RNAs between specimens.

It is a conceptual diagram of the method of this invention. It is a block diagram which shows the outline of a structure of the analyzer of this invention. It is an example of the flowchart of the correction process of the small RNA expression level by this invention. The histogram of the DNA microarray detection signal value measured in the Example is shown. The result of having compared an analysis result between Taqman PCR method about each of an Example and a comparative example is shown.

  First, the concept of the small RNA correction method performed in the present invention will be described with reference to FIG. In FIG. 1, the result of detection with a microarray in which sample RNA is labeled and a plurality of types of small RNA capture probes and mRNA capture probes are immobilized is schematically shown by a histogram of signal values.

  In FIG. 1A, the results of analyzing the sample RNA extracted from the sample A and the sample B using the DNA microarray are shown as histograms. The signal value obtained from the several small RNA capture probe mounted in the microarray and the histogram of the signal value obtained from the several mRNA capture probe are each shown. In the sample A and the sample B, the histograms of small RNAs are greatly shifted. From this, it can be interpreted that there is a large difference in the expression level of small RNA between samples. On the other hand, it can be interpreted that a difference is caused by an experimental error. It is not possible to judge which is correct.

  By the way, the premise used in the correction method of gene expression analysis is that there is no difference in the expression level when the expression data of a plurality of genes is taken as one lump and taken as a group of gene expression data, regardless of the specimen. It was that. In this case, the histogram of signal values should match between samples. The above assumption is established for the expression level of mRNA.

  The histogram of the signal values obtained from the mRNA capture probe shown in FIG. 1A shows almost the same distribution for specimen A and specimen B. That is, it can be determined that the sample A and the sample B are correctly subjected to the experiment and there is no experimental error. In this case, there is a large difference in the expression level of the small RNA between the samples AB, and it is not necessary to correct the signal value of the small RNA when comparing the samples.

  FIG. 1B schematically shows the results of analyzing Sample C and Sample D using a DNA microarray. The histogram of the signal value obtained from the small RNA capture probe and the signal value obtained from the mRNA capture probe is shown.

  In sample C and sample D, the histograms of small RNAs show similar distributions. On the other hand, the histogram of the signal value obtained from the mRNA capture probe is greatly shifted between the sample C and the sample D. From this, it can be seen that an experimental error has occurred in the detection results of the sample C and the sample D for some reason. In such a case, it is necessary to appropriately correct the signal value of the small RNA when comparing between specimen CDs.

  The histogram after correcting the signal value of the small RNA according to the present invention is shown in FIG. 1C. A specific method of correction is as described later. The data of sample C was corrected so that the histograms of the signal values obtained from the mRNA capture probes of sample C and sample D matched. As a result of this correction, the signal value histograms obtained from the mRNA capture probes are matched between the sample C and the sample D, and the signal value histograms of the small RNA capture probes corrected using the same correction coefficient are greatly shifted. Come. In other words, there is a large difference in the expression level of small RNA even between specimen CDs.

  Hereinafter, the comparative analysis method, apparatus, and program of the present invention will be described in detail.

  In the present invention, the expression level of small RNA is comparatively analyzed among a plurality of specimens. The number of specimens may be two, or three or more.

  “Small RNA” means RNA having a chain length of less than 200 bases produced in vivo. Examples thereof include ribosomal RNA (5S rRNA, 5.8S rRNA), transfer RNA (tRNA), small nuclear ribonucleoprotein particle RNA (snoRNA), small nuclear RNA (snRNA), and microRNA (miRNA). Examples of preferred small RNAs include, but are not limited to, miRNA.

  The specimen to which the present invention can be applied is a specimen separated from a living body, for example, body fluid such as blood, serum, plasma, urine, feces, spinal fluid, saliva, swab fluid, various tissue fluids, various tissues, paraffin embedded Examples include specimens (FFPE) and sections thereof, various foods and drinks, and dilutions thereof, but are not limited thereto. The plurality of specimens to be compared and analyzed may be a plurality of specimens derived from different tissues, or may be a plurality of specimens derived from the same tissue separated from different living bodies, and different sites (for example, tumors) in the same tissue A plurality of specimens derived from a lesioned part and a non-lesioned part).

  RNA is extracted from these samples without separating mRNA and small RNA, and the expression levels of small RNA and mRNA are measured using this RNA. Such RNA extraction methods are known (for example, the method of Favaloro et al. (Favaloro et.al., Methods Enzymol. 65: 718 (1980))), and various kits therefor are commercially available (for example, QIAGEN miRNeasy etc.).

<Measurement process>
In the comparative analysis method of the present invention, the expression levels of a plurality of types of mRNA are measured simultaneously with the measurement of the expression levels of a plurality of types of small RNAs. The mRNA expression level is used to calculate a correction coefficient for correcting the expression level of the small RNA, as will be described later. Simultaneous measurement of the expression levels of a plurality of RNAs can be performed by a hybridization assay using an array chip such as a microarray in which a probe that specifically binds to the target RNA is immobilized on a support. In the present invention, an array chip including a support on which a plurality of small RNA capture probes and a plurality of mRNA capture probes are immobilized may be used.

  “Capture probe” means a substance capable of binding directly or indirectly, preferably directly and selectively with RNA to be captured, and representative examples thereof include nucleic acids, proteins, saccharides, and the like. And an antigenic compound. In the present invention, a nucleic acid probe can be preferably used. In addition to DNA and RNA, nucleic acid derivatives such as PNA (peptide nucleic acid) and LNA (Locked Nucleic Acid) can be used as the nucleic acid. Here, in the case of nucleic acid, a derivative is a labeled derivative by a fluorophore, a modified nucleotide (for example, a nucleotide containing a group such as halogen, alkyl such as methyl, alkoxy such as methoxy, thio, carboxymethyl, etc.) Means a chemically modified derivative such as a derivative comprising a nucleotide, etc. that has undergone configuration, double bond saturation, deamination, substitution of oxygen molecules with sulfur molecules, and the like.

  The chain length of the nucleic acid probe is preferably 20 bases or more from the viewpoint of ensuring hybridization stability. Usually, when the chain length is about 20 to 100 bases, the probe can sufficiently exhibit selective binding to the target RNA. Such an oligonucleic acid probe having a short chain length can be easily prepared by a known chemical synthesis method or the like.

  The nucleic acid probe preferably has a nucleotide sequence that is completely complementary to the target RNA. However, even if there are some differences, the bases have high homology to the extent that they can hybridize with the target RNA under stringent conditions. Any array can be used as a capture probe.

  It is known that stringency during hybridization is a function of temperature, salt concentration, probe chain length, GC content of the probe nucleotide sequence, and concentration of chaotropic agent in the hybridization buffer. As the stringent conditions, for example, the conditions described in Sambrook, J. et al. (1998) Molecular Cloning: A Laboratory Manual (2nd ed.), Cold Spring Harbor Laboratory Press, New York can be used. . Stringent temperature conditions are about 30 ° C or higher. Other conditions include the hybridization time, the concentration of the detergent (eg, SDS), the presence or absence of carrier DNA, and various stringencies can be set by combining these conditions. Those skilled in the art can appropriately determine conditions for obtaining a function as a capture probe prepared for detection of a desired sample RNA.

  Small RNA sequence information can be obtained from databases such as GenBank (http://www.ncbi.nlm.nih.gov/genbank/). Moreover, the sequence information of miRNA can be obtained from, for example, the website of Trust Sanger Institute (http://www.sanger.ac.uk/Software/Rfam/mirna/index.shtml). Small RNA capture nucleic acid probes can be designed based on sequence information available from these sites.

  The number of small RNA capture probes immobilized on the support is not particularly limited. For example, the expression level of the small RNA may be measured by using a small number of small RNA capture probes covering all known miRNAs whose sequences have been identified immobilized on a support.

  As the mRNA capture nucleic acid probe, for example, the same mRNA capture probe used in a commercially available DNA microarray can be used. For example, in the Operon microarray, there is a one-to-one correspondence between mRNA and probe (ie, one type of capture probe is mounted on the array for one type of mRNA). Affymetrix microarrays have multiple capture probes for one type of mRNA. When the expression level is measured using an array chip in the measurement step of the present invention, the number of mRNA capture nucleic acid probes immobilized on the support is from several hundred to several tens of thousands of randomly selected mRNAs. Any number that targets. The more the number of mRNAs to be measured, the more the distribution data of the detected values when the expression data is regarded as a group of gene expression data groups, the accuracy of correction by the method of the present invention increases. As shown in the Examples below, the miRNA expression level can be corrected accurately even for about 1000 types of mRNA. Accordingly, the number of mRNAs targeted by the mRNA capture probe mounted on the array chip may be about several thousand or less, for example, about 300 to 3000 types, about 400 to 2000 types, or about 500 to 1500 types. It can be as species.

  As the support on which the capture probe is immobilized, the same support as that used in known microarrays and macroarrays can be used. For example, a slide glass, a membrane, a bead, or the like can be used. A support having a shape having a plurality of convex portions on the surface described in Japanese Patent No. 4244788 can also be used. The material of the support is not particularly limited, and examples thereof include inorganic materials such as glass, ceramic, and silicon; polymers such as polyethylene terephthalate, cellulose acetate, polycarbonate, polystyrene, polymethyl methacrylate, and silicone rubber.

  As a method for immobilizing a capture probe on a support, a method of synthesizing oligo DNA on the surface of the support and a method of dropping and immobilizing oligo DNA synthesized in advance on the surface of the support are known.

  Examples of the former method include the method of Ronald et al. (US Pat. No. 5,705,610), the method of Michel et al. (US Pat. No. 6,142,266), and the method of Francesco et al. (US Pat. No. 7037659). . In these methods, since an organic solvent is used during the DNA synthesis reaction, the support is preferably made of a material resistant to the organic solvent. In the method of Francesco et al., DNA synthesis is controlled by irradiating light from the back surface of the support, and therefore the support is preferably made of a light-transmitting material.

  Examples of the latter method include the method of Iwata et al. (Japanese Patent No. 3922454) and the method using a spotter. Examples of the spot method include a pin method based on mechanical contact of a pin tip with a solid phase, an ink jet method utilizing the principle of an ink jet printer, and a capillary method using a capillary tube. After spot treatment, post-treatment such as cross-linking by UV irradiation and surface blocking is performed as necessary. In order to immobilize the oligo DNA by covalent bonding to the surface of the surface-treated support, a functional group such as an amino group or an SH group is introduced at the end of the oligo DNA. The surface modification of the support is usually performed by treatment with a silane coupling agent having an amino group or the like.

  For hybridization with each probe immobilized on a support, a nucleic acid sample labeled with a labeling substance (a sample-derived nucleic acid sample) is prepared from RNA extracted from the sample, and this labeled nucleic acid sample is contacted with the probe. To implement. The “sample-derived nucleic acid sample” includes not only RNA extracted from the sample, but also cDNA and cRNA prepared from the RNA by a reverse transcription reaction. The labeled sample-derived nucleic acid sample may be a sample obtained by directly or indirectly labeling a sample RNA with a labeling substance, or a cDNA or cRNA prepared from the sample RNA may be directly or indirectly labeled with a labeling substance. It may be labeled.

  As a method for binding a labeling substance to a sample-derived nucleic acid sample, a method for binding a labeling substance to the 3 ′ end of the nucleic acid sample, a method for binding a labeling substance to the 5 ′ end, and a nucleotide bound to the labeling substance are incorporated into the nucleic acid. Can be mentioned. An enzyme reaction can be used in the method of binding a labeling substance to the 3 'end and the method of binding a labeling substance to the 5' end. For the enzyme reaction, T4 RNA Ligase, Terminal Deoxitidil Transferase, Poly A polymerase, etc. can be used. For any labeling method, the method described in “miRNA Experimental Protocol (Yodosha)” can be referred to. Various kits for binding a labeling substance directly or indirectly to the end of RNA are commercially available. For example, as a kit for binding a labeling substance directly or indirectly to the 3 ′ end, miRCURY miRNA HyPower labeling kit (Exicon), NCode miRNA Labeling system (Life Technologies), FlashTag Biotin RNA Labeling Kit (Genissphere) Etc. can be illustrated. Life Technologies 'NCode miRNA Labeling system adds a poly A tail to miRNA, then ligates the capture sequence to the 3' end using cross-linked oligo dT, hybridizes it to the array, and then converts it to the capture sequence. In this method, a labeling substance having a hybridizing sequence is added, and miRNA is labeled via a capture sequence, and the labeling substance is indirectly bound to miRNA. In these commercially available kits, a poly A tail is added to a small RNA, and a labeling substance is bound using this poly A tail, but the mRNA contained in the sample RNA originally has a poly A tail. Simultaneously with the labeling of mRNA, labeling of mRNA is also possible.

  In addition, as in the conventional method, cDNA or cRNA incorporating a labeled substance is prepared by synthesizing cDNA or cRNA from sample RNA in the presence of labeled deoxyribonucleotides or labeled ribonucleotides, and this is arrayed. A method of hybridizing with the above probe is also possible.

  In the present invention, a plurality of specimens are used, but the same labeling substance may be used for all of them.

  In the present invention, examples of labeling substances that can be used include various labeling substances that are also used in known microarray analysis. Specific examples include fluorescent dyes, phosphorescent dyes, enzymes, and radioisotopes, but are not limited thereto. Preferred are fluorescent dyes that can be easily measured and signals can be easily detected. Specifically, cyanine (cyanine 2), aminomethylcoumarin, fluorescein, indocarbocyanine (cyanine 3), cyanine 3.5, tetramethylrhodamine, rhodamine red, Texas red, indocarbocyanine (cyanine 5), cyanine 5.5, Although well-known fluorescent dyes, such as cyanine 7 and oyster, are mentioned, It is not limited to these.

  Further, as the labeling substance, semiconductor fine particles having a light emitting property may be used. Examples of such semiconductor fine particles include cadmium selenium (CdSe), cadmium tellurium (CdTe), indium gallium phosphide (InGaP), silver indium zinc sulfide (AgInZnS), and the like.

  The nucleic acid sample derived from the specimen labeled as described above is brought into contact with the probe on the support, and the nucleic acid sample and the probe are hybridized. This hybridization step can be performed in the same manner as in the past. The reaction temperature and time are appropriately selected according to the chain length of the nucleic acid to be hybridized. In the case of nucleic acid hybridization, the reaction temperature and time are usually about 30 ° C. to 70 ° C. for 1 minute to several tens of hours. Hybridization is performed, and after washing, the signal intensity from the labeling substance in each probe-immobilized region on the support is detected. The signal intensity is detected using an appropriate signal reader according to the type of labeling substance. When a fluorescent dye is used as a labeling substance, a fluorescence microscope or a fluorescence scanner may be used.

  The detected signal value is compared with ambient noise. Specifically, the signal value obtained from the probe-immobilized region is compared with the signal value obtained from other positions, and the case where the former numerical value exceeds is detected (effective determination positive) .

  When background noise is included in the detected signal value, the background noise may be subtracted. The ambient noise can be subtracted from the detected signal value as background noise. In addition, the method described in “Microarray Data Statistical Analysis Protocol (Yodosha)” may be used.

  According to said method, the measured value of the expression level of small RNA and mRNA is obtained as a measured value of signal intensity.

<Representative value acquisition process>
Next, in the analysis method of the present invention, for each specimen, a representative value represented by a logarithmic value is acquired from the measured value of the mRNA expression level (representative value acquisition step). The “logarithmic value” in the present invention means a value converted to a logarithm with a base of 2. Typical examples of the representative value include an average value and a median value. When the representative value is an average value, the “average value expressed in logarithmic value” is a measured value of the expression level of a plurality of mRNAs (for example, a measured value of signal intensity obtained using a microarray). Mean value obtained by logarithmic value converted to logarithm of. When the representative value is the median value, the “median value expressed as a logarithmic value” is a measured value of the expression level of a plurality of mRNAs (for example, a measured value of signal intensity obtained using a microarray). The logarithm of the logarithmic value converted into the logarithm of the above or the logarithmic value obtained by converting the median of the measured mRNA expression level into the logarithm of the base 2. In the case of the median value, the same value can be obtained whether the logarithmic conversion of the measured value is performed first or later.

  The average value and the median value may be obtained by using all measured values of a plurality of mRNAs to be measured, or by using a part of measured values extracted from the plurality of mRNAs. It may be what was requested. For example, it may be obtained using all mRNA measurement values obtained with the mRNA capture probe mounted on the microarray, or a part of the total mRNA capture probe (for example, the mRNA capture probe mounted on the microarray). If there are 1000 species, 500 of them may be extracted and obtained. For example, the mRNA representative value can be obtained by extracting only the mRNA capture probe immobilization region that is positive for the effective determination in common for all samples to be compared and analyzed.

  Alternatively, in the present invention, the logarithmic value of the measured mRNA expression level of a gene whose expression level is known to be constant among the plurality of specimens can be employed as the representative value.

<Correction coefficient acquisition process>
Next, using the mRNA representative value of each specimen obtained in the representative value acquiring step, a correction coefficient used for correcting the expression level of the small RNA is acquired (correction coefficient acquiring step). At this time, one sample (first sample) is arbitrarily selected from a plurality of samples, and this is set as a “reference sample”. The remaining second and subsequent samples are “corrected samples”.

  In the present specification, the term “second and subsequent samples” includes the second sample. For example, if there are two samples to be compared, only the second sample is corrected, and if there are three samples to be compared, the sample to be corrected is the second sample. And a third specimen.

  In the method of the present invention, the difference between the mRNA representative value of the reference sample and the mRNA representative values of the second and subsequent samples (samples to be corrected) is used as a correction coefficient for the second and subsequent samples. As many correction coefficients as the number of specimens to be corrected are acquired.

Specifically, the correction coefficient is
c = (representative mRNA value of reference sample) − (represented mRNA value of corrected sample) Equation 1
Or
c ′ = (mRNA representative value of the sample to be corrected) − (mRNA representative value of the reference sample) Equation 1 ′
Is required. If the correction factor for the second sample,
c2 = (mRNA representative value of reference sample) − (mRNA representative value of second sample)
Or
c2 ′ = (mRNA representative value of the second specimen) − (mRNA representative value of the reference specimen)
Is required.

  For example, when the expression level is measured using a microarray and an average value is used as the mRNA representative value, the correction coefficient for the second specimen can be obtained by any one of the following formulas.

（式中、
nは、支持体上のmRNA捕捉プローブ固定化領域の総数、
Xjは、基準検体における、j番目（1≦j≦n）のｍＲＮＡ捕捉プローブ固定化領域からのシグナル測定値、
Yjは、第２の検体における、j番目（1≦j≦n）のｍＲＮＡ捕捉プローブ固定化領域からのシグナル測定値
である。）

(Where
n is the total number of mRNA capture probe immobilization regions on the support,
Xj is the signal measurement value from the j-th (1 ≦ j ≦ n) mRNA capture probe immobilization region in the reference sample,
Yj is a signal measurement value from the j-th (1 ≦ j ≦ n) mRNA capture probe immobilization region in the second specimen. )

  If the probe has a one-to-one correspondence with mRNA, n is equal to the number of mRNAs targeted by the mRNA capture probe on the support.

  In the formula 1-1 and the formula 1-1 ′, the total number n ′ of mRNA capture probe immobilization regions that are positive in the validity determination in common for all the samples to be compared can be used instead of n.

  In addition, for example, when the logarithmic value of the measured mRNA expression level of a specific gene (here, referred to as gene G for convenience) whose expression level is known to be constant among a plurality of specimens is used as the representative mRNA value The correction coefficient for the second specimen can be obtained by any of the following formulas.

（式中、
Gaは基準検体における遺伝子Gの発現量測定値、
Gbは第２の検体における遺伝子Gの発現量測定値
である。）

(Where
Ga is the measured expression level of gene G in the reference sample,
Gb is a measured value of the expression level of gene G in the second specimen. )

<Correction process>
The correction of the small RNA expression level in the second and subsequent samples is performed using the correction coefficients for the second and subsequent samples, respectively. In other words, when correcting the small RNA expression level for the second sample, the correction coefficient (c2 or c2 ′) for the second sample is used, and the small RNA expression level is corrected for the third sample. Uses the correction factor (c3 or c3 ′) for the third specimen.

  When a value obtained by subtracting the mRNA representative value of the second and subsequent samples from the mRNA representative value of the reference sample is used as the correction coefficient, that is, in the case of the above formula 1, each small RNA expression level measurement value in the second and subsequent samples is used. By adding a correction coefficient to the logarithmic value, the small RNA expression level for each of the second and subsequent samples is corrected. When the correction in this case is expressed by an equation, the corrected expression level Ei of the i-th small RNA in a certain “corrected sample” can be obtained by the following equation 2.

（Ziは、i番目の小型RNA捕捉プローブ固定化領域からのシグナル測定値である。）

(Zi is a signal measurement value from the i-th small RNA capture probe immobilization region.)

  On the contrary, when a value obtained by subtracting the mRNA representative value of the reference sample from the mRNA representative value of the second and subsequent samples is used as the correction coefficient, that is, in the case of the above formula 1 ′, By subtracting the correction coefficient from the logarithmic value of each small RNA expression level measurement value, the small RNA expression level is corrected for each of the second and subsequent samples. When the correction in this case is expressed by an equation, the corrected expression level Ei of the i-th small RNA in a certain “corrected sample” can be obtained by the following equation 2 ′.

（Ziの定義は上記式２に同じ）

(Definition of Zi is the same as equation 2 above)

  If the small RNA expression level measured in the second sample is corrected, c2 may be added to the logarithmic value of each small RNA expression level measurement value in the second sample, or c2 ′ may be subtracted. . The same applies to the third and subsequent samples. The value of the corrected small RNA expression level Ei finally obtained is the same in the procedures of Formulas 1 and 2 and the procedures of Formulas 1 'and 2'.

<Contrast process>
The small RNA expression level in the reference sample is compared with the corrected small RNA expression level in the second and subsequent samples. The comparison process itself can be performed in the same manner as in the conventional method. For example, a scatter plot of expression level data called a scatter plot may be created. If there are three or more samples to be compared, a scatter plot that compares the reference sample and the second sample and a scatter plot that compares the reference sample and the third sample may be created. Accordingly, a scatter plot that compares the second specimen and the third specimen may be created. Comparison of four or more specimens can be performed in the same manner. It should be noted that a scatter plot can also be created three-dimensionally if the three samples are compared.

  The small RNA expression analyzer of the present invention is an apparatus for performing the comparative analysis method of the present invention. The apparatus includes storage means for storing a plurality of small RNA expression levels and a plurality of mRNA expression levels measured simultaneously for each of a plurality of specimens; and a mRNA expression level measurement value for each specimen. Representative value acquisition means for acquiring a representative value represented by a logarithmic value; an arbitrarily selected first sample as a reference sample, an mRNA representative value of the reference sample and the remaining mRNAs of the second and subsequent samples Correction coefficient acquisition means for acquiring a difference from the representative value as a correction coefficient for each of the second and subsequent specimens; and using correction coefficients for the second and subsequent specimens acquired by the correction coefficient acquisition means, respectively. Correction means for correcting the small RNA expression level measured in the second and subsequent samples; and a comparison result between the small RNA expression level of the reference sample and the corrected small RNA expression level in the second and subsequent samples. Output means for outputting.

  FIG. 2 is a block diagram showing an outline of the configuration of the analysis apparatus. The analysis apparatus 10 includes an input unit 110, a display unit 120, an output unit 130, a storage unit 140, a control unit 150, a conversion unit 160, and an analysis unit 170. FIG. 3 shows an example of a flowchart of a small RNA expression level correction process according to the present invention.

  The input unit 110 is a means for inputting information related to the operation of the analysis apparatus 10. Conventionally known input means such as a keyboard can be preferably used. The expression level data obtained by the hybridization assay using the microarray is read by reading means such as a scanner different from the apparatus of the present invention and converted into numerical data, and then the numerical data is input from the input unit 110. Input to the analyzer 10. Alternatively, reading means such as a scanner may be included in the analysis device 10 of the present invention (not shown).

  Expression level data input from the input unit 110 or expression level data read and digitized by a reading unit incorporated in the analysis apparatus 10 is stored in the storage unit 140. At this time, the storage unit 140 serves as a storage unit that stores, for each of the plurality of specimens, measured values of the expression levels of a plurality of small RNAs and the expression levels of a plurality of mRNAs that are simultaneously measured.

  The small RNA and mRNA expression level measurement value data of each specimen stored in the storage unit 140 is converted into a logarithm with a base of 2 by the conversion unit 160. Next, the analysis unit 170 acquires a representative value of the logarithmically transformed mRNA expression level measurement value for each specimen. As described in the explanation of the comparative analysis method, the representative value can be an average value, a median value, or an mRNA measurement value of a specific gene whose expression level is constant between samples.

  After the representative value is acquired, the analysis unit 170 calculates the difference between the mRNA representative value of the reference sample and the mRNA representative values of the second and subsequent samples, and obtains correction coefficients for the second and subsequent samples, respectively. Is done. Details of the correction coefficient acquisition are as described in <Correction coefficient acquisition step> of the comparative analysis method.

  In the device 10, the selection of the reference sample may be performed by a person operating the device 10 specifying one arbitrary sample from the input unit 110. Alternatively, the apparatus 10 may automatically select one sample as a reference sample. For example, a sample in which data is input from the input unit 110 and data is first stored in the storage unit 140 can be selected as a reference sample by the apparatus 10. The step of selecting or inputting the reference specimen is positioned after the representative value acquisition step (S-3) in FIG. 3 for convenience, but is not limited to this, and is an earlier step, for example, when storing data. May be executed.

  Next, the analysis unit 170 corrects the small RNA expression level data measured for the second and subsequent samples, using the correction coefficients for the second and subsequent samples, respectively. The details of the correction operation are as described in <Correction process> of the comparative analysis method.

  Next, the analysis unit 170 compares the small RNA expression level of the reference sample with the corrected small RNA expression levels of the second and subsequent samples. The comparison result is output to the display unit 120 by the output unit 130 and displayed. Furthermore, the comparison result can be output to an output device such as a printer or a recording medium. Furthermore, the output unit 130 can be configured to output the comparison analysis result to an external storage device such as a database existing outside the device via a network.

  The storage unit 140 stores the measurement values of the expression levels of a plurality of small RNAs and the expression levels of a plurality of mRNAs, and also appropriately stores intermediate analysis results generated in each of the above steps.

  The various operations described above of the apparatus 10 are controlled by the control unit 150. Specifically, as indicated by broken line arrows in FIG. 2, for each unit of the input unit 110, the display unit 120, the output unit 130, the storage unit 140, the control unit 150, the conversion unit 160, and the analysis unit 170, Control information is output from the control unit 150, and each unit operates in cooperation with the control information, and the entire apparatus 10 operates.

  Further, the present invention is a program that causes a computer to function as the above-described analysis device, and causes a computer to correct a small RNA expression level using mRNA expression level data measured simultaneously with the small RNA expression level by a microarray or the like, and A computer-readable recording medium on which a program is recorded is provided.

  The “recording medium” is an arbitrary “portable physical medium” such as a flexible disk, a magneto-optical disk, a ROM, an EPROM, an EEPROM, a CD-ROM, an MO, a DVD, or a network represented by a LAN, WAN, or the Internet. It includes a “communication medium” that holds a program in a short period of time, such as a communication line or a carrier wave in the case of transmitting a program via a network.

  The “program” is a data processing method described in an arbitrary language or description method, and may be in any format such as source code or binary code. Note that the “program” is not necessarily limited to a single configuration, but is configured to be distributed as a plurality of modules or libraries, or in cooperation with a separate program represented by an OS (Operating System). Including those that achieve the function. Note that a well-known configuration and procedure can be used for a specific configuration for reading a recording medium, a reading procedure, an installation procedure after reading, and the like in each device described in the embodiment.

  An array chip including a support on which a plurality of small RNA capture probes and a plurality of mRNA capture probes can be preferably used, which can be preferably used in the present invention, can be provided as a small RNA expression analysis chip. Preferred conditions for the chip are as described in the comparative analysis method of the present invention.

  Hereinafter, the present invention will be described more specifically based on examples using two types of RNA specimens. However, the present invention is not limited to the following examples.

  Many studies using commercially available RNA samples derived from human tissues have been conducted and published as papers. In a report by Sato et al. (Sato et.al., Plos One 4 (5): e5540 (2009)), using the human prostate-derived RNA specimen and the human liver-derived RNA specimen, the miRNA expression data contained in it is the golden standard. Comparison analysis with data obtained by the taqman PCR method. In this example, the correction method of the present invention was applied using an RNA sample derived from human prostate and an RNA sample derived from human liver.

(Capture probe design)
As a small RNA capture probe, a complementary strand of 939 human miRNA sequences obtained from miRBase release 12 was used (http://www.sanger.ac.uk/Software/Rfam/mirna/index.shtml).

  As the mRNA trapping probe, 1054 kinds of sequences randomly selected from probes published by Operon were used. Since the operon probe sequence was designed with the same plus strand as mRNA, the complementary strand of the operon probe sequence was used as the mRNA capture probe.

  As for the small RNA capture probe and the mRNA capture probe, a synthetic DNA having an amino group modification at the 3 ′ end was synthesized by Operon.

(Production of DNA microarray)
Using the amino group introduced at the 3 ′ end, the above small RNA capture probe and mRNA capture probe are immobilized on the convex portion of the 3D-Gene (registered trademark) substrate (3000 column substrate) manufactured by Toray Industries, Inc. A microarray was prepared. The following experiment was performed using this DNA microarray.

(Sample RNA preparation)
Human prostate RNA (Ambion) and human liver RNA (Ambion) were used as sample RNA. RNase III was added to 1 μg of sample RNA and reacted at 37 ° C. for 90 minutes to fragment the RNA. The fragmented sample RNA was purified using miRNeasy mini kit (Qiagen). The obtained sample RNA was labeled using miRCURY LNA HyPower labeling kit (Exicon). The labeled sample RNA was subjected to hybridization and washing according to the standard protocol of 3D-Gene (registered trademark) miRNA chip (Toray Industries, Inc.). The reacted DNA microarray detected a fluorescent signal using a microarray scanner (Toray Industries, Inc.). The scanner settings were 100% laser output and 70% photomultiplier voltage.

(Correction of small RNA signal value)
The signal value obtained from the DNA microarray is converted into a logarithm with a base of 2, and a histogram is shown in FIG. FIG. 4A shows a signal value of RNA hybridized to the small RNA capture probe, and FIG. 4B shows a histogram of signal value of RNA hybridized to the mRNA capture probe.

  The average value of each signal value and the difference between the average values are shown in Table 1. The prostate-derived RNA was defined as “reference sample RNA”, and the liver-derived RNA was defined as “sample RNA to be compared”. By subtracting the average signal of the liver-derived RNA (sample RNA to be compared) from the mRNA-supplemented probe from the average value of the signal from the prostate-derived RNA (reference sample RNA) mRNA-supplied probe, a value of 0.25 was obtained (in the present invention Correction factor used).

  Next, among the signal values obtained from the DNA microarray reacted with liver-derived RNA (sample RNA to be compared), the signal values obtained from the RNA hybridized to the small RNA capture probe are each logarithm with a base of 2. And a correction factor of 0.25 was added. The correction was implemented by the above operation.

(Data acquisition with Taqman PCR)
For comparison, miRNA expression data was obtained by Taqman PCR (Applied Biosystems). Data acquisition was performed according to the manufacturer's recommended protocol. 34 types of miRNAs selected arbitrarily were used as detection targets (Table 2). The data analysis method followed the report of Sato et al. (Sato et.al., Pros One 4 (5): e5540 (2009)).

(Data comparison)
Table 3 shows the signal values (logarithmic values) obtained by DNA microarray analysis of 34 miRNAs targeted by Taqman PCR. Since the signal value of the DNA microarray and the detection result of taqman PCR cannot be directly compared, they were converted into a fluctuation ratio and compared. The variation ratio is a logarithmic value of a value obtained by dividing a liver-derived RNA signal value in a small RNA by a prostate-derived RNA signal value.

  FIG. 5 shows the result of comparing the signal value of the corrected small RNA capture probe with the data of taqman PCR. FIG. 5A shows a scatter diagram in which the horizontal axis represents the fluctuation ratio obtained by taqman PCR and the vertical axis represents the fluctuation ratio obtained by the microarray. If the results are similar, the regression line should overlap the y = x line. When the regression line was calculated, the slope was 0.93 and the intercept was 0.073.

Comparative Example As a comparative example, correction was performed by a global normalization method, which is a correction method according to the prior art, which makes the distribution of signal values of small RNAs the same. The average signal value of the small RNA is 5.34 for prostate-derived RNA and 4.39 for liver-derived RNA (Table 1). The average difference 1.05 at this time was used as a correction coefficient.

  Of the signal values obtained from the DNA microarray reacted with liver-derived RNA, the signal value of the small RNA capture probe was converted to a logarithm with a base of 2, and a correction factor of 1.05 was added. The correction was implemented by the above operation. Similar to the example, it was compared with taqman PCR using the variation ratio (FIG. 5B). The regression line has a slope of 0.93 and an intercept of 0.823, which is far from the y = x line.

  As described above, by using the correction method of the present invention, it was possible to obtain a result that was in good agreement with taqman PCR, which is said to be the golden standard.

Claims (14)

A method for comparatively analyzing the expression level of small RNA between multiple samples,
A measurement step of measuring the expression levels of a plurality of mRNAs simultaneously with the measurement of the expression levels of a plurality of small RNAs for each of the plurality of specimens;
A representative value acquisition step of acquiring a representative value represented by a logarithmic value from the measured value of the mRNA expression level for each specimen;
The arbitrarily selected first sample is used as a reference sample, and the difference between the mRNA representative value of the reference sample and the mRNA representative values of the remaining second and subsequent samples is used as a correction coefficient for each of the second and subsequent samples. Acquiring a correction coefficient;
Correcting the small RNA expression level measured in the second and subsequent samples using the obtained correction coefficients for the second and subsequent samples, respectively; and a small RNA expression level in the reference sample and the second Including a comparison step that compares the corrected small RNA expression level in subsequent samples,
In the correction coefficient acquisition step, when a value obtained by subtracting the mRNA representative value of the second and subsequent samples from the mRNA representative value of the reference sample is acquired as a correction coefficient, the small RNA expression level in the second and subsequent samples is acquired in the correction step. The correction is performed by adding a correction coefficient to the logarithmic value of the measured value,
In the correction coefficient acquisition step, when a value obtained by subtracting the mRNA representative value of the reference sample from the mRNA representative value of the second and subsequent samples is acquired as a correction coefficient, the small RNA expression level in the second and subsequent samples is acquired in the correction step. The method, wherein the correction is performed by subtracting a correction coefficient from the logarithmic value of the measured value.   The method according to claim 1, wherein the expression level of the small RNA is comparatively analyzed between the two specimens.   In the measurement step, a plurality of small RNA capture probes and a plurality of mRNA capture probes immobilized on a support are brought into contact with a nucleic acid sample derived from a sample labeled with a labeling substance, and hybridization is performed. And measuring the expression level of each small RNA and each mRNA as a signal intensity measurement value by measuring a signal from a labeling substance in each probe-immobilized region on the support, respectively. The method described.   The method according to claim 3, wherein the probe is a nucleic acid probe and the labeling substance is a fluorescent dye.   The method according to any one of claims 1 to 4, wherein the representative value is an average value calculated by a logarithmic value of the mRNA expression level measurement value.   The method according to any one of claims 1 to 5, wherein the small RNA is miRNA. A small RNA expression analyzer for comparative analysis of the expression level of small RNA in multiple specimens,
For each of a plurality of specimens, storage means for storing a plurality of small RNA expression levels and a plurality of mRNA expression levels measured simultaneously,
For each sample, representative value acquisition means for acquiring a representative value represented by a logarithmic value from the measured value of the mRNA expression level,
The arbitrarily selected first sample is used as a reference sample, and the difference between the mRNA representative value of the reference sample and the mRNA representative values of the remaining second and subsequent samples is used as a correction coefficient for each of the second and subsequent samples. Correction coefficient acquisition means for acquiring,
Correction means for correcting the small RNA expression level measured in the second and subsequent samples, respectively, using the correction coefficients for the second and subsequent samples acquired by the correction coefficient acquiring means;
An output means for outputting a comparison result between the small RNA expression level of the reference sample and the corrected small RNA expression level in the second and subsequent samples,
When the correction coefficient acquisition unit acquires a value obtained by subtracting the mRNA representative value of the second and subsequent samples from the mRNA representative value of the reference sample as the correction coefficient, the correction unit obtains the small RNA expression level in the second and subsequent samples. The correction is performed by adding a correction coefficient to the logarithmic value of the measured value,
When the correction coefficient acquisition unit acquires a value obtained by subtracting the mRNA representative value of the reference specimen from the mRNA representative value of the second and subsequent specimens as a correction coefficient, the correction means obtains a small RNA expression level in the second and subsequent specimens. The apparatus performing the correction by subtracting a correction coefficient from the logarithmic value of the measured value.   The apparatus according to claim 7, wherein the expression level of small RNA is comparatively analyzed between two specimens.   The apparatus according to claim 7 or 8, wherein the representative value is an average value calculated as a logarithmic value of the mRNA expression level measurement value. To compare and analyze small RNA expression levels among multiple samples,
A storage means for storing a plurality of small RNA expression levels and a plurality of mRNA expression levels measured simultaneously for each of a plurality of samples,
For each specimen, representative value acquisition means for acquiring a representative value represented by a logarithmic value from the measured value of the mRNA expression level,
An input means for inputting a first sample designated as a “reference sample” among a plurality of samples;
Correction coefficient acquisition means for acquiring the difference between the mRNA representative value of the reference specimen and the mRNA representative values of the remaining second and subsequent specimens as a correction coefficient for the second and subsequent specimens,
Correction means for correcting the small RNA expression level measured in the second and subsequent samples using the correction coefficients for the second and subsequent samples acquired by the correction coefficient acquisition means, and the small RNA of the reference sample A program for outputting the comparison result between the expression level and the corrected small RNA expression level in the second and subsequent samples, and functioning as an output means,
When the correction coefficient acquisition unit acquires a value obtained by subtracting the mRNA representative value of the second and subsequent samples from the mRNA representative value of the reference sample as the correction coefficient, the correction unit obtains the small RNA expression level in the second and subsequent samples. The correction is performed by adding a correction coefficient to the logarithmic value of the measured value,
When the correction coefficient acquisition unit acquires a value obtained by subtracting the mRNA representative value of the reference specimen from the mRNA representative value of the second and subsequent specimens as a correction coefficient, the correction means obtains the small RNA expression level in the second and subsequent specimens The program for performing the correction by subtracting a correction coefficient from a logarithmic value of a measured value. To compare and analyze small RNA expression levels among multiple samples,
A storage means for storing a plurality of small RNA expression levels and a plurality of mRNA expression levels measured simultaneously for each of a plurality of samples,
For each specimen, representative value acquisition means for acquiring a representative value represented by a logarithmic value from the measured value of the mRNA expression level,
A reference sample selection means for selecting a first sample as a “reference sample” from a plurality of samples;
Correction coefficient acquisition means for acquiring the difference between the mRNA representative value of the reference specimen and the mRNA representative values of the remaining second and subsequent specimens as a correction coefficient for the second and subsequent specimens,
Correction means for correcting the small RNA expression level measured in the second and subsequent samples using the correction coefficients for the second and subsequent samples acquired by the correction coefficient acquisition means, and the small RNA of the reference sample A program for outputting the comparison result between the expression level and the corrected small RNA expression level in the second and subsequent samples, and functioning as an output means,
When the correction coefficient acquisition unit acquires a value obtained by subtracting the mRNA representative value of the second and subsequent samples from the mRNA representative value of the reference sample as the correction coefficient, the correction unit obtains the small RNA expression level in the second and subsequent samples. The correction is performed by adding a correction coefficient to the logarithmic value of the measured value,
When the correction coefficient acquisition unit acquires a value obtained by subtracting the mRNA representative value of the reference specimen from the mRNA representative value of the second and subsequent specimens as a correction coefficient, the correction means obtains a small RNA expression level in the second and subsequent specimens. Performing the correction by subtracting the correction coefficient from the logarithm of the measured value,
The program.   The program according to claim 10 or 11, wherein the expression level of small RNA is comparatively analyzed between two specimens.   The program according to any one of claims 10 to 12, wherein the representative value is an average value calculated as a logarithmic value of an mRNA expression level measurement value.   The computer-readable recording medium which recorded the program of any one of Claims 10 thru | or 13.

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