KR20180046592A - Method for selecting and utilizing tag-SNP for discriminating haplotype in gene unit - Google Patents

Abstract

The present invention relates to a tag-single nucleotide polymorphism (SNP) selection and utilization technology for distinguishing a haplotype from a gene unit, and more specifically, to a tag-SNP selection technology having higher information strength than an existing method for just arbitrarily selecting and using mutation generated by an SNP. Each tag-SNP selected through the technology of the present invention may represent one gene, may distinguish a haplotype of each gene, and includes position information in a chromosome of a corresponding gene and non-synonymous SNP information causing changes in amino acids. Therefore, the efficiency of detecting a gene related to a target trait of a sarcoma is significantly increased when the tag-SNP having higher information strength than an existing SNP selected and used in a random manner is used for QTL mapping and GWAS analysis.

Description

[0001] The present invention relates to a method for selecting a SNP for discriminating a single-phase type from a gene unit,

The present invention relates to a tag-SNP selection and utilization technique for distinguishing a single-phase type in a gene unit.

The demand for molecular markers for effective crop breeding is steadily increasing, and the development of molecular markers is accelerating with the development of next-generation sequencing equipment. Various structural variations present in the genome are developed as molecular markers and are very important information to distinguish cultivars or to find and utilize genes associated with major traits. Analytical techniques such as quantitative trait mapping (QTL mapping) and genome-wide association study (GWAS) are widely used to explore trait-related markers.

Molecular markers are classified into single nucleotide polymorphism (SNP), short insertion / deletion, and simple sequence repeat (SSR) molecular markers depending on the nature of the genetic variation. Depending on the detection method, it can be classified into a PCR-based detection method, a sequencing method, and a hybridization method. Depending on the position of the mutation information search, a selection method is used in the whole genome or a selection method in the expressed gene sequence fragment (EST) region.

In the past, if it was important to detect the genetic mutation as in the above type, since 2007, the next generation nucleotide sequencing technology (NGS) has enabled the production of large-scale sequence data, Quantitative molecular markers can be quickly and rapidly detected, resolving quantitative constraints in mutation detection.

Therefore, it is important to select candidates for high-quality molecular markers (SNPs) that can be directly used for QTL mapping and GWAS. High quality molecular markers refer to markers capable of detecting gene and molecular markers with a minimum number of traits. However, the concept of mutation information representing the gene itself, excavation techniques, and whether gene mutation has not been studied to date.

SNP is one of the most frequently occurring structural mutations in the genome and is the most widely used molecular marker because it is easy to obtain SNP mutation information at the target gene or chromosome position. However, in order to reduce the number of molecular markers that can be used as a molecular marker because the experimental cost required to identify all the excess SNPs can not be met, the concept of tag-SNP (tag-SNP) is introduced only in the field of human genome research And the research has not yet been conducted on the plants.

Methods for selecting tag-SNPs in genomes are divided into two categories: block-based methods and genome-wide approaches. The block-based approach relies on a predefined haplotype block structure. If the blocks are separated based on the frequency of crossing over, crossing occurs within a very small level, so that haplotypes in the block have very few variations.

Korean Patent Publication No. 2012-0121500 discloses a method for constructing a comparative analysis system for an expressed genome for the evolution and function study of cruciferous plant genes, Korean Patent Publication No. 2011-0064699 discloses a method for constructing a SNP ) ≪ / RTI > However, the tag-SNP selection and utilization technique for distinguishing single-phase type from the gene unit of the present invention has not been described.

DISCLOSURE OF THE INVENTION The present invention has been made in view of the above needs, and the present invention has been made in view of the above problems, and it is an object of the present invention to provide genome data of a large number of tomato lines which can be used as a breeding material or represent whole tomato species, A non-synonymous SNP (non-synonymous SNP) which has a high possibility of affecting the function of a gene (protein) due to the substitution of an amino acid was selected as a tag-SNP, and the selected tag-SNP was subjected to QTL mapping, GWAS analysis And the present inventors have completed the present invention by confirming that linkage disequilibrium (LD) analysis can be further performed to further reduce the number of SNPs and to be used for screening.

In order to solve the above-mentioned problems, the present invention provides a method for producing a genome comprising the steps of: aligning a reference genome of a target crop; Making SNPs of target crop lines corresponding to the location of the extracted SNPs in a matrix form; Selecting a SNP generated at a position where the SNP occurs; Selecting a set of SNPs capable of distinguishing a haplotype representing a gene; And selecting a non-synonymous SNP that causes amino acid substitution among the SNPs as a tag-SNP. The present invention also provides a tag-SNP selection method in which the efficiency of the method for detecting a transgene-related gene is enhanced.

The present invention also provides a recording medium on which a computer-readable program for performing the above method is recorded.

The present invention is a technology for selecting tag-SNP having a higher information power than the conventional method in which a mutation generated by a single nucleotide sequence substitution (SNP) generated at a wide level of a block unit is arbitrarily selected and used. Each tag-SNP selected by this technology can represent one gene, can distinguish haplotypes of each gene, and can be used to identify the position of a gene in a chromosome, SNP (non-synonymous SNP) information. Therefore, using QTL mapping and GWAS analysis using tag-SNP with high information power compared to SNP selected by existing random method, it will significantly increase the efficiency of detecting genes related to the target traits of breeding.

1 is a schematic diagram illustrating a gene haplotype and a tag-SNP (tag-SNP).
2 is a schematic diagram of a large-scale genome sequence-based tag-SNP selection assay.
Figure 3 shows the number according to SNP type of Solanum lycopersicum var cerasiforme strain.
Figure 4 shows the number according to the SNP type of the Solanum lycopersicum strain.
Figure 5 shows the number according to SNP type of Solanum pimpinellifolium system.
Figure 6 shows a simple SNP-based phylogenetic tree.
7 shows the number of tomato genes according to the number of SNP occurrences.
Figure 8 shows the intermediate results of the gene haplotype analysis.
Fig. 9 shows the results of analysis of gene haplotypes of the three tomato lines.
Fig. 10 shows the results of a tomato gene haplotype analysis.
Figure 11 shows a tag-SNP based tomato phylogenetic tree.
Figure 12 shows the LD block of Solanum licocercum.
13 shows the LD block of Solanum pimpinelipolyum.

In order to achieve the object of the present invention,

a) producing genome sequence data of the subject crop line that can represent the entire crop, or collecting it in a public database;

b) measuring the quality of the base sequence in step a), and filtering the base sequence with a sequence having a quality of at least a reference value;

c) aligning each of the selected base sequences of step b) with a reference genome sequence of the target crop, and then extracting a large amount of SNPs compared with the standard genome;

d) making SNPs of target crop lines corresponding to the location of the SNP extracted in step c) as a matrix;

e) classifying the SNPs of the target crop lineage sorted in the form of a matrix in the d) step by gene and classifying the SNPs representing each gene;

f) sorting the gene haplotype through SNPs representing each gene in step e); And

g) a single-stranded (single-stranded) gene having no non-synonymous SNP or non-synonymous SNP information causing the amino acid substitution among the SNPs representing the haplotype of the gene of step f) selecting SNPs (tag-SNPs) for homozygous SNPs in the case of haplotypes. The present invention also provides a tag-SNP selection method in which the efficiency of the detection of the transgene-related gene is enhanced.

In the method according to an embodiment of the present invention, the public database of step a) may be a short read archive (SRA) database, but it is preferable to provide a genome or a transcript base sequence of an object to which a tag- Database or NGS equipment.

In the method according to an embodiment of the present invention, the sequence quality of step b) may be measured using a sequence quality analysis program, for example FASTX-Toolkit, FastQC, SolexaQA package, But is not limited thereto. The range of the reference value of the sequence quality analyzed by the above sequence quality analysis program is 0 to 40 for the phred score and 0 to 100 bp for the base sequence length, preferably 20 to 40 for the Fred score, and 25 to 100 bp But is not limited thereto. The Fred Score is a numerical representation of the reliability of each base analyzed in the sequencing results. The Fred Score 20 means that the probability that each base sequence information analyzed differs from the actual base sequence is about 1/100, Fred score 20 can be set as a reference value. The length of the Fred score and the nucleotide sequence can be arbitrarily controlled within a range depending on the purpose of analysis.

In the method according to an embodiment of the present invention, the sorting program of step c) may be Burrows-Wheeler Aligner (BWA) or TopHat, but is not limited thereto. The sorting option of the BWA sorting program may be set to a default value, but is not limited thereto. As an option of the TopHat sorting program, a minimum intron-size 40, a maximum intron length max -intron-size) 23000 and mismatches 1, but it is not limited thereto and can be arbitrarily set according to the dielectric characteristics of the variety.

In the method according to an embodiment of the present invention, the program used for SNP extraction in step c) may be SAMtools, but is not limited thereto. In general, the SNP extraction option can be performed by setting the default value (default), and in order to extract the SNP with high accuracy, the option value can be arbitrarily adjusted according to the analysis purpose.

The SNP selection for representing the gene of the step e) is classified into a matrix form, and the SNPs classified by the genes are classified by utilizing the chromosome position information generated by the SNPs.

The gene haplotype classification in step f) is characterized in that each system can be distinguished by comparing a set of SNPs representing each gene on a systematic basis of a target crop.

The tag-SNP selection in the step g) is selected as a representative SNP capable of distinguishing a single-phase type representing a gene by prioritizing a non-synonymous SNP causing amino acid substitution SNP (homozygous SNP) in the case of a haplotype of a gene having no non-synonymous SNP information is selected as a tag-SNP.

The present invention also provides a recording medium on which a computer-readable program for performing the above method is recorded.

A computer-readable recording medium is any recording medium that can be directly read and accessed by a computer. Examples of the recording medium include magnetic recording media such as a floppy disk, a hard disk and a magnetic tape; optical recording media such as CD-ROM, CD-R, CD, RW, DVD-ROM, DVD- , And mixtures of these categories (for example, magnetic / optical recording media such as MO), but are not limited thereto.

The selection of a device for recording or inputting the recording medium or an apparatus or an apparatus for reading information in the recording medium is based on the type of recording medium and the access method. In addition, various data processor programs, software, comparators and formats may be used to record a program for carrying out the method of the present invention on the medium. The information may be represented, for example, in the form of a binary file, a text file, or an ASCII file formatted with commercially available software.

Hereinafter, the present invention will be described in detail with reference to examples. However, the following examples are illustrative of the present invention, and the present invention is not limited to the following examples.

Example  1. Open database ( NCBI SRA ) Of the 234 base sequences of tomatoes haplotype ) Through analysis tag - SNP  Selection

1. Analysis material

A) Securing and characterizing tomato genome information

Most of the cultivars currently on the market belong to Solanum lycopersicum and are being cultivated by introducing some genes and chromosomes to introduce useful traits such as disease resistance in various wildtype tomatoes. Tomato genome sequencing data was produced by researchers from various countries and accumulated about 800 SRA information in NCBI's Sequence Read Archive (SRA) database. The nucleotide sequence length (bp) collected for this study was 7.8Tb (See Table 1).

B) Selection of a line representing tomato crops

Based on the published literature (Tao Lin et al., 2014, Nature Genetics 46 (11)), nucleotide sequence data of 234 tomato lines were selected using sequence data available for research and analysis (see Tables 1 and 2 ). Details of the tomato SRA data used in this analysis are shown in Tables 2 to 6 below.

Solanum lycopersicum , the most commonly used cultivar in the collected tomato SRA, was mainly selected and Solanum lycopersicum var cerasiforme, which is most similar to the present cultivar, Some of the wild tomato varieties were used for the analysis based on Solanum pimpinellifolium , which is frequently used in the breeding process.

C) Collection of tomato standard genomic sequence data

Tomato standard genomes were Solanum lycopersicum Heinz 1706 (ITAG version 2.4) collected from SGN (ftp://ftp.solgenomics.net/). The standard genome consists of a total of 13 chromosome sequences, a total of 781,666,411 bp in length, consisting of one other group of scaffold sequences stranded on chromosomes of either 12 chromosomes or 12 chromosomes (Table 7).

2. Analysis method

A) filtering the quality of the collected base sequence data;

The SolexaQA package (v. 1.13; Cox et al., 2002) was used to measure the quality of the genome sequence data of 234 tomatoes collected and to filter only base sequences above the reference quality. 2010, BMC Bioinformatics, 11: 485). The reference value of the quality measurement was applied to a phred score of 20, and when a quality value of a base forming a base sequence is lower than 20, it is only necessary to obtain a base sequence having a remaining base sequence of 25 bp or more Respectively.

(B) alignment of the pre-treatment sequences with tomato-

Since the pre-processed tomato sequences are in the form of a genome, the tomato genome sequence is determined using the BWA (Burrows-Wheeler Aligner; v0.6.1-r104; Li and Dubin, 2009, Bioinformatics, 25: 1754-1760) Alignment was performed. Program options include defaults of up to 2 mismatches and seed length 27 settings.

C) Search for large genome-wide SNPs

The genomic sequence of the genomes of the tomatoes was determined using SAMtools (v0.1.16; Li et al., 2009, Bioinformatics. 25: 2078-2079) Markers (SNPs) were searched. The SAMtools program application option is applied by default and the alignment quality value is applied to the default value of 30 to 30 to select the SNP with high accuracy and at least 3 raw reads. Only a short fragment sequence constituting the nucleotide sequence) was selected.

D) Generation of SNP matrix between tomato lines

SNP mutation information was summarized in a matrix form by integrating SNP occurrence information of each of 234 tomato lines. The matrix consisted of the chromosome number and position information of the SNP, the nucleotide sequence of the standard genome, and SNP nucleotide sequence information of 234 tomato lines.

E. SNP Classification based on matrix-based gene level

SNPs in the genome were selected using information on the SNP position provided by the SNP matrix and the information on the physical position of the tomato standard genome, and SNPs were classified for each tomato gene predicted to be composed of 34,727 genes.

F) Analysis of haplotypes based on tomato genes

SNP purification was performed to define and analyze the gene haplotype composed of SNPs representing the genes. In the SNP screening process, the SNP occurrence rate of the same type among the tomato lines was 3% or more, the read depth was 5 or more, and the sequence lacking the nucleotide sequence was 30% or less SNPs satisfying the criteria were selected. The haplotypes that can distinguish genes from selected SNPs are summarized.

G) Selection of non-synonymous SNP

Changes in the nucleotide sequence codon due to the occurrence of SNPs in the gene and changes in the amino acid may affect the function of the gene. Thus, non-synonymous SNPs that cause amino acid substitution among SNPs representing haplotypes can be selected to increase the likelihood of screening for transgene-related genes.

SNPs (non-synonymous SNPs) were defined as tag-SNPs, which can be used as trait-related molecular markers to represent haplotypes.

A) Tomato lineage analysis (LD) analysis

Linkage disequilibrium (LD) analysis was performed on each chromosome using a tomato SNP matrix. For the LD analysis, the Haploview program developed by the Barrett Jeffrey team of Broad Institute was introduced and used.

The LD distribution patterns between the Solanium lycopersicum and Solanium pimpinelipolium groups were investigated at the chromosome level and one SNP was selected for a certain length and over 20% of MAF in the LD analysis. The Solanium lycopersicum group selected one SNP for only 1 kb of chromosome 11 and 12, while the Solanium pimpinellifolium group selected one SNP per 5 kb (only one chromosome per 7 kb).

3. Analysis Results

A) Selection of a line representing tomato crops

(Tao Lin et al., 2014), the sequence data of 234 tomato lines were selected from the sequence data available for research and analysis. Fig. 3 shows the relationship of the tomato root relationship used in this analysis.

B) filtering the quality of the collected nucleotide sequence data;

Raw data and trimmed data of the 234 genomic DNA sequences of the collected tomatoes are shown in Table 8 below. Table 8 shows the number of reads (No. of reads), the average length of the fragment sequence (total length), the total length, and the ratio of the length of the acquired base sequence (Trimmed / Raw (%)) Respectively.

The quality of genome sequence data of 234 tomatoes collected was measured and a base sequence of about 1.2 Tbp in length was obtained by filtering only the base sequences above the reference quality (Table 8).

(C) Alignment of the pretreatment base sequence to the tomato standard dielectric.

The results obtained by sorting the purified sequence data by the tomato line into the tomato standard genome ( S. lycopersicum , 2.4v) are shown in Table 9 below. 89.97% of the preprocessed fragments were aligned to the standard genome and the mutation information could be detected.

D) Search for large amounts of genome-wide SNP

A large number of genomic SNPs were searched for in all 234 tomato lines compared to the standard genome sequence (Tables 10 to 13).

E. Creation of SNP matrix between tomato lines

The SNP variation information was collected in a matrix form by integrating the SNP occurrence information of each of 234 tomato lines, resulting in a total of 29,504,960 SNPs.

As a result of investigating the trends according to SNP types among the top three cultivars of the 234 tomato lines, 68 strains belonging to Solanum lycopersicum cerasipore showed the number of SNPs per individual, ranging from as few as 100,000 to as many as 2.5 million The range was wide (Figure 3). The 126 strains belonging to Solanum lycopersicum were found to belong to the same species as the standard genome and were found to have 10,000 to 100,000 SNPs, except for one strain (SRR1572666) (Fig. 4). Thirty-three strains belonging to Solanium pimpinelipolium extracted more than 3 million SNPs compared to the standard genome (Fig. 5).

Based on the extracted SNP information, the results of analysis of the tree number of 234 tomatoes are shown in FIG. The top three lines, Solanium Lycopersicum, Solanum Lycopersicum Cercifion, Solanium Pimpinelipolyum, were distinguishable but there were indistinguishable individuals.

F) SNP classification based on SNP matrix-based gene level

Using the SNP location information provided by the SNP matrix and the information on the physical position in the tomato standard genome, SNPs generated in the genes were selected and classified into SNPs of tomato genes predicted to be composed of 34,727 genes.

As a result of the frequency of SNPs by gene, 2,160 genes showed no SNP, which is about 6.2% of total genes. Of the 10 SNPs per gene, the highest rate was found, and more than 50 SNPs were found in 2,189 genes (Fig. 7).

G) Tomato gene based haplotype analysis

In order to define and analyze the gene haplotype composed of SNPs representing the gene, the SNPs were purified and 175,287 SNPs were obtained (Table 14).

The results of primary analysis of the gene haplotype through selected SNPs are shown in Fig. From the left, the gene name (ID), the number of lines used for haplotype analysis in the gene, the type of the specific haplotype, and the number of lines with the corresponding haplotype are referred to as haplotype ).

Fig. 9 and Fig. 10 show the results obtained by dividing the haplotype types among the examined strains into the types in which the haplotype types occur most frequently and those in which the occurrence frequency decreases. Although there was no significant difference between the solanium lycopersicum and the solanium lycopersicum cerasipome, the solanium pimpinelipolium showed a large difference in the dielectric composition. The results showed that tomatoes consisted of about two haplotypes.

A) Non-synonymous SNP search and tag-SNP selection

SNPs with non-synonymous SNPs, which cause amino-acid substitutions in the gene region and cause protein structural changes and have a high possibility of affecting the function of genes (proteins), were selected. As a result, 13,845 SNPs were selected Tag-SNP. Tables 15 and 16 show some of the entire SNPs identified in the present invention.

When there is no non-synonymous SNP information, 13,694 homozygous SNPs were selected as tag-SNPs. A total of 27,539 tag-SNPs meeting these requirements were selected (Table 15, 16).

Based on the selected tag-SNP information, the analysis results of 234 tomato phylogeny classification are shown in FIG. It can be seen that the classification ability of the top three groups (Solanum lycopersicum, Solanum lycopersicum cerasipome, Solanum pimpinelipolium) is increased compared to the results classified as basic SNPs.

Application: Analysis of Linkage Disequilibrium (LD) between tomato lines

Analysis of the distribution of LD (linkage dragging) blocks of the Solanum lycopascikum and Solanium pimpinelipolium strains based on the tag-SNP revealed a significantly different pattern between the two groups (Table 17).

A large LD phenomenon was observed on chromosomes 1, 2, 4, 6, 10, 11 and 12 of the Solanium lycopersicum group (Fig. 12). However, it has been observed that the solanium pimpinelipolium group is spread evenly across the entire chromosome region, and the size of the LD is relatively small (FIG. 13).

It was confirmed that the distribution of LDs in the chromosomal euchromatic or heterochromatic regions was larger than that in the chromosomal or specific regions. This phenomenon has been artificially selected during the breeding process, In the case of the group, it can be inferred that the gene group containing the useful trait is continuously selected depending on the purpose of breeders.

Claims (10)

a) producing genome sequence data of the subject crop line that can represent the entire crop, or collecting it in a public database;
b) measuring the quality of the base sequence in step a), and filtering the base sequence with a sequence having a quality of at least a reference value;
c) aligning each of the selected base sequences of step b) with a reference genome sequence of the target crop, and then extracting a large amount of SNPs compared with the standard genome;
d) making SNPs of target crop lines corresponding to the location of the SNP extracted in step c) as a matrix;
e) classifying the SNPs of the target crop lineage sorted in the form of a matrix in the d) step by gene and classifying the SNPs representing each gene;
f) sorting the gene haplotype through SNPs representing each gene in step e); And
g) a single-stranded (single-stranded) gene without the non-synonymous SNP or non-synonymous SNP information causing the amino acid substitution among the SNPs representing the haplotype of the gene in step f) selecting SNPs (tag-SNPs) for a homozygous SNP in the case of the haplotype of the tag-SNP. The tag-SNP selection method according to claim 1, wherein the sequence quality of step b) is measured in a FASTX-Toolkit, FastQC or SolexaQA package. 3. The tag-SNP selection method according to claim 2, wherein the reference value of the sequence quality is a phred score of 20 or more and a base sequence length of 25 bp or more. The method according to claim 1, wherein the alignment in step c) is performed using Burrows-Wheeler Aligner (BWA) or TopHat. The method according to claim 1, wherein the SNP extraction in step c) is performed using a SAMtools program. [2] The method according to claim 1, wherein the SNP selection for representing the gene of step e) is classified into a matrix form, and the SNPs classified for each gene are classified by using the chromosome position information generated by the SNPs, Tag-SNP selection method with improved efficiency of trait-associated gene detection. 2. The method according to claim 1, wherein the haplotype classification of step (f) is performed by comparing the SNPs representing each gene with each strain of the target crop to distinguish each strain. Tag-SNP selection method with improved efficiency. 2. The method according to claim 1, wherein the tag-SNP selection in step g) is a single-phase type in which a non-synonymous SNP causing amino acid substitution is prioritized to represent a gene Wherein the selected SNPs are selected as representative SNPs. The method according to claim 1, wherein the tag-SNP selection in step g) comprises the step of selecting a homozygous SNP in the case of a haplotype having no non-synonymous SNP information, SNP selection method according to claim 1 or 2, wherein the tag-SNP is selected as a tag-SNP. A recording medium on which a computer-readable program for performing the method according to any one of claims 1 to 9 is recorded.

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