CN109326322B - Method and system for comparing QTL (quantitative trait loci) among different segregation groups of crops - Google Patents
Method and system for comparing QTL (quantitative trait loci) among different segregation groups of crops Download PDFInfo
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Abstract
The invention provides a method and a system for comparing QTL (quantitative trait loci) among different segregation groups of crops, belonging to the field of bioinformatics. The method comprises the following steps: establishing a genetic marker database, establishing a query target, matching molecular marker sequences, performing genome positioning on the matched molecular marker sequences, eliminating false positive results, determining a genome region corresponding to the target trait QTL, and finally realizing comparison of the target trait QTL among different groups. The system comprises: the system comprises a genetic marker database module, a query target module, a matching molecular marker sequence module, a genome positioning module and a genome region module corresponding to a QTL (quantitative trait locus) for determining a target trait. The invention constructs a genetic marker database, can quickly complete the acquisition of the position information of the genome and realize the automatic screening of the position of the marker in the genome.
Description
Technical Field
The invention belongs to the field of bioinformatics, and particularly relates to a QTL comparison method and system among different segregation populations.
Background
In rape genetic and breeding research, most agronomic traits are Quantitative Trait Loci (QTLs), which are controlled by a number of genes and are susceptible to environmental influences. The method of QTL mapping based on high density genetic linkage mapping is the most classical and reliable means to resolve quantitative trait control sites (genes) for gene map cloning and molecular assisted selection breeding (MAS). Over the past twenty years, researchers have used various molecular markers (mainly PCR-based SNP markers, which are single nucleotide polymorphisms in recent years, such as AFLP, SSR, and STS) to construct genetic linkage maps and to analyze QTL locations. Before rape 6K and 60K SNP chips are widely used, different researchers generally search an online database or verify the polymorphism of a group constructed by the researchers by using published markers when carrying out QTL positioning analysis by using different groups, and develop a part to construct a genetic linkage map, so that the markers of different groups are not uniform. In addition, the essential difference between the widely used SNP marker in recent years and the traditional PCR basic marker makes the detection of QTL in early years more difficult compared with the current research.
Generally speaking, the purpose gene of QTL is cloned by using a stable and reliable QTL as a guarantee. The discovery of the novel QTL provides new gene resources for variety improvement and has greater research value. Identifying QTL stability and novelty is the necessity of researchers to make comparisons between different populations. In addition, the QTL is linearized to the genome through the closely linked markers, so that the comparison is more accurate, and meanwhile, a candidate interval is provided for the identification of candidate genes.
The prior art scheme for QTL comparison among different groups is mainly to obtain marker names and attached marker sequence data of the marker names which are closely linked with the QTL from the literature, and to compare the marker names or sequence identities by means of Biomecater software by means of a rape molecular marker database (such as rape data center: http:// www.rapedata.com/rapedata/marker/index. htm).
The QTL based on SNP map detection and the previous detection based on PCR are usually carried out by researchers with certain bioinformatics basis, and the QTL is linearized on a genome for comparison by utilizing the collection and arrangement of primers and SNP probe sequences, Excel arrangement, local blast function provided by NCBI and E-PCR software based on a Linux platform.
The prior art has many difficulties in comparison between studies based on PCR-type markers and SNP markers.
(1) First, in early studies based primarily on PCR-based markers, comparisons of QTLs between different populations relied on marker names and primer sequences for the markers, and whether they were the same QTL was determined by whether there were identical, closely linked markers. Because the genetic markers are not strictly uniform in each study, further confirmation through primer sequences is required, then mapping between maps is carried out by software, and QTL is compared by means of closely linked markers.
(2) When searching for the PCR basic primer sequence, the method is complicated, because no comprehensive and perfect online marking sequence database is available, a plurality of databases are needed to search, but the method cannot be found. This makes the acquisition of PCR-type tagged primer sequences difficult, time consuming and cumbersome.
(3) After the rape 60K SNP chip is widely used, because the SNP markers are single nucleotide polymorphism markers, the QTL using SNP-based map detection has not been mapped and compared with the previous PCR-based marker studies. Generally we use e-PCR for PCR-based markers that tightly link QTLs, and after linearization of SNP markers to the genome using BLASTN, use their locations for comparison. Although this comparison method solves the problem of QTL comparison between different early PCR-based markers and current SNP marker studies, it still faces the problem of sequence search for PCR-based type markers, and e-PCR and BLASTN directly hinder the analysis for most researchers without bioinformatics basis. For researchers with a certain trust foundation, the primer sequence search, the SNP probe sequence calling, the data arrangement, the frequent system switching, the software switching and the identification of the marked correct genome position are carried out, and the complicated procedures cause the comparison efficiency to be low and the errors to be easy to occur.
Disclosure of Invention
The invention solves the problems that in the QTL comparison process among different segregation populations in the prior art, the marker primer sequence of the PCR type is difficult to obtain, consumes time and is complicated; the genetic markers are not strictly uniform in nomenclature, resulting in the need for further confirmation by primer sequences; and the technical problems of repeated operation, confusion and frequent switching of the operating system are manually solved, and the method and the system for comparing the QTL among different segregation populations of the crops are provided.
According to a first aspect of the present invention, there is provided a method for comparing QTLs between different segregating populations of a crop, comprising the steps of:
(1) constructing a genetic marker database: the database contains molecular marker names and sequence information of different crop separation groups based on DNA hybridization, primer names and sequence information of different crop separation groups based on PCR molecular markers, and names of SNP molecular markers of the different crop separation groups and probe sequence information of the SNP molecular markers;
(2) constructing a query target: the query target comprises QTL names of different segregation populations of crops and molecular marker names linked with the QTL, the target trait QTL contains at least one linked molecular marker, and the combination of the QTL name of the target trait and the molecular marker name linked with the QTL is used as a query target;
(3) matching molecular marker sequences: matching the query target in the step (2) with the genetic marker database in the step (1), and calling a molecular marker sequence corresponding to the query target in the step (2);
(4) genome mapping: if the molecular marker sequence in the step (3) is a molecular marker sequence based on DNA hybridization or an SNP molecular marker sequence, performing Blast comparison on the molecular marker sequence in the step (3) in a genome sequence database of the crop, and taking an obtained comparison hot spot as potential genome positioning of the marker; if the molecular marker sequence in the step (3) is based on a PCR molecular marker sequence, performing Blast comparison on the forward primer sequence and the reverse primer sequence of the molecular marker sequence in the step (3) in a genome sequence database of the crop respectively, and if the matching hot spots of the two primer sequences are located in the range of 300bp-500bp on the same chromosome and the matching hot spots of the forward primer and the reverse primer are respectively the positive strand and the reverse strand of a DNA sequence, taking the matching sites of the two primer sequences as potential genome positioning of the marker;
(5) eliminating false positive results: judging whether the potential genome mapping and the chromosome where the corresponding QTL is located are the same chromosome or not in the step (4); if the potential genome location in the step (4) is not the same chromosome as the chromosome where the corresponding QTL is located, determining that the potential genome location is a false positive, and rejecting a false positive result; secondly, performing secondary screening by using a box-type graph method, and screening out genome positioning deviating from an aggregation region in each molecular marker linked with the QTL;
(6) determining a genome region corresponding to the QTL of the target character: determining the region corresponding to the reaction site gathered in the gathering region on the same chromosome in the genome positioning obtained in the step (5) as the genome region corresponding to the QTL (quantitative trait locus); and judging whether the QTL of different segregation populations corresponds to the same genome region or not.
Preferably, the DNA hybridization-based molecular marker of step (1) is a DNA hybridization-based molecular marker of Brassica napus; the SNP molecular marker in the step (1) is a marker for typing a cabbage type rape 6K or 60K SNP chip; the PCR-based molecular marker in the step (1) is a PCR-based molecular marker for Brassica napus.
Preferably, the query target in step (2) further comprises information of the chromosome where the molecular marker linked to the QTL is located.
Preferably, the genetic marker database in step (1) further comprises position information of chromosomes in which PCR molecular marker primer sequences, SNP molecular marker probe sequences or molecular marker sequences based on DNA hybridization are located.
According to another aspect of the invention, there is provided a QTL comparison system for different segregating populations of a crop, comprising:
a genetic marker database module: the genetic marker database module is used for collecting genetic marker data; the database contains molecular marker names and sequence information of different crop separation groups based on DNA hybridization, primer names and sequence information of different crop separation groups based on PCR molecular markers, and names of SNP molecular markers of the different crop separation groups and probe sequence information of the SNP molecular markers;
and a query target module: the query target module is used for collecting target trait QTL linked molecular markers to be compared among different segregation populations; the query target comprises different segregation population target trait QTL names and molecular marker names linked with the QTL, the target trait QTL contains at least one linked molecular marker, and the combination of the target trait QTL name and the molecular marker name linked with the QTL is used as a query target;
matching molecular marker sequence modules: for matching the query target with a database of genetic markers; matching the query target with the genetic marker database, and calling a molecular marker sequence corresponding to the query target in the genetic marker database;
a genome mapping module: for identifying potential genomic locations; if the molecular marker sequence is a molecular marker sequence based on DNA hybridization or an SNP molecular marker sequence, performing Blast comparison on the molecular marker sequence in a genome sequence database of the crop to obtain a comparison hot spot as potential genome positioning of the marker; if the molecular marker sequence is based on a PCR molecular marker sequence, performing Blast comparison on a forward primer sequence and a reverse primer sequence of the molecular marker sequence in a genome sequence database of the crop respectively, and if the matching hot spots of the two primer sequences are located in the range of 300bp-500bp on the same chromosome and the matching hot spots of the forward primer and the reverse primer are respectively a positive strand and a reverse strand of a DNA sequence, taking the matching sites of the two primer sequences as potential genome positioning of the marker;
a false positive result eliminating module: the method is used for eliminating matching hot spots deviating from a QTL prediction region; judging whether the chromosome of the potential genome location and the chromosome of the corresponding QTL are the same chromosome; if the potential genome location and the chromosome where the corresponding QTL is located are not the same chromosome, the potential genome location is a false positive, and the false positive result is removed; secondly, screening out genome positioning deviating from an aggregation region in each molecular marker linked with the QTL by using a box-type diagram method;
determining a genome region module corresponding to the QTL of the target character: for determining the location interval of the QTL on the genome; determining the region corresponding to the reaction site gathered in the gathering region on the same chromosome in the genome positioning as the genome region corresponding to the target character QTL; and judging whether the QTL of different segregation populations corresponds to the same genome region or not.
Generally, compared with the prior art, the above technical solution conceived by the present invention mainly has the following technical advantages:
(1) the same genetic marker may have different nomenclature in different documents, and there may be some degree of difference between these different nomenclature. According to the invention, on the premise of confirming that the genetic marker sequences are the same, the characteristics (such as short transverse lines, underlines, case difference, last letter when the last digit is a number, and the like) which are common and do not influence the genetic marker identification in the genetic marker name are automatically removed, so that the integration of genetic marker data from different documents is realized, and a genetic marker library is built. When reference mapping is performed from a query target to a genetic marker, since the query target does not carry sequence information, a plurality of genetic marker results which are approximately matched but have consistent sequences may be queried. The method of the invention can reserve all the genetic marker mapping results of fuzzy matching so as to reserve the data of the correctness of manual backtracking check.
(2) The invention constructs a molecular marker local database which is easy to expand. The invention integrates the molecular marker and sequence based on DNA hybridization, the molecular marker and primer sequence based on PCR and the probe sequence of the cabbage type rape 60K SNP chip into a database, so that the marker sequence information with the closely linked QTL does not need to be found in the literature or searched in each online database when being searched, and only the name of the universal marker needs to be directly input, and the software automatically goes into a local database for extraction. In order to map the marker onto the genome, marker sequence information for close linkage of QTLs needs to be obtained from the literature. In the prior art, data formats provided by various documents are not uniform, data are scattered, and manual query needs to be executed in a plurality of databases respectively. The invention provides a reusable extensible genetic marker sequence database with a uniform format, new data can be added into the database by once arranging the data provided by each document according to a specific input format, and after that, only the marker name needs to be directly input, and the database can be queried once without respectively querying the data with different formats each time.
(3) The invention can complete the acquisition of the genome position information in one step. The method comprises the steps of obtaining marked genome position information, wherein in the prior art, an e-PCR method is used for marking based on a PCR type, and a BLASTN method is used for realizing SNP marking, in the process, the e-PCR and the BLASTN under Linux need to be operated independently, and the switching between systems is possibly needed, so that the method is very complicated. The method calls BLASTN in an automated way, based on the database of genetic markers and the target the user wants to query, and the BLASTN results can be used to assemble into potential PCR reaction sites. The invention aims to identify the location of the QTL in the genome, and can conveniently remove false positive reaction sites under the combined screening of a plurality of closely linked markers. After the marked name or fault-tolerant name txt file is prepared, software automatically goes to a library to extract a sequence, BLASTN analysis is carried out under a Windows system, and then the genome position corresponding to the mark is obtained.
(4) The invention simultaneously realizes the automatic screening of the position of the marker in the genome. Brassica napus is an allotetraploid species with a large number of repetitive sequences present in the genome. The tags are usually mapped to multiple positions by e-PCR and BLASTN. In order to determine the true position of the marker, it is usually only resolved by human beings. The invention can utilize the linkage relationship existing between the markers with the QTL close linkage to screen and confirm the real position of the markers.
(5) The system of the invention has a Windows operating environment, uses C + + language, only provides two data input interfaces (genetic marker library, query target) with limited formats and a data output interface (QTL prediction information), and has the advantages that most of the work originally needing manual processing in the system is finished in an automatic mode, and the processing process of data abnormity is greatly reduced after the deduplication and normalization are carried out in advance and the common and obviously wrong data screening (such as wrong characters) is carried out. And due to the characteristics that the C + + runs after being completely compiled and the type is limited, the possibility of structural errors of data transmission among the modules is greatly reduced. All data processing is performed in a Windows environment, and a user does not need to operate tools in the linux system. In the prior art, a plurality of systems need to be frequently switched, data exchange among the systems depends on manual format conversion and manual carrying, and therefore efficiency is reduced and errors are prone to occurring. The communication of each module in the system and the calling of the external program are all subjected to data integrity screening, the format conversion is stable, and the manual errors can be reduced or even avoided.
(6) The method can be used for comparing the QTL researches of the cabbage type rape and is also suitable for the QTL comparison researches of other crops, and only the local primer database and the genome database are required to be adjusted to corresponding species.
Drawings
FIG. 1 is a flow chart of QTL comparison of oil content between different segregating populations of Brassica napus.
FIG. 2 shows the location of the QTL of oil content in genome of different segregation populations of Brassica napus identified by the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
FIG. 1 is a flow chart of QTL comparison of oil content between different segregating populations of Brassica napus in accordance with the present invention. The method for comparing the oil content QTL among different separation groups comprises the following steps:
(1) construction of a database of genetic markers
Collecting reported molecular marker primers (such as RAPD, SRAP, AFLP, SSR, InDel and the like) based on DNA hybridization (such as RFLP) and PCR in the brassica napus and probe sequence information of 6K and 60K SNP chip of the brassica napus, and constructing a brassica napus molecular marker library. Wherein the combination of molecular tag name and sequence information serves as a unique identifier and a primary bond that is not reproducible. The PCR-based molecular marker, the sequence information of which is composed of forward and reverse primer sequences; DNA hybridization-based markers (including SNP markers) consist of a probe sequence.
(2) Constructing target data to be queried
And (3) collecting published results of positioning the oil content QTL by using different separated groups of the cabbage type rape, and constructing target data to be inquired. The target data to be inquired comprises the name of a molecular marker to be inquired and the QTL name of the oil content detected by different groups to which the molecular marker belongs, and the combination of the name of each molecular marker and the QTL name to which the molecular marker belongs is used as an inquiry target; the combination of molecular marker names with the oil content QTL marker names of different populations serves as a unique identifier and a primary bond that is not repeatable.
(3) Matching genetic markers to query targets
When carrying out the brassica napus QTL study, DNA hybridization and PCR based markers sometimes detect two or more polymorphisms, and researchers typically make appropriate modifications to the molecular markers to distinguish the different polymorphisms of the markers. For example, nia001 has two polymorphisms, which are designated nia001a and nia001b, respectively. Thus, the same marker is named differently for different polymorphisms, but the sequence information is identical. Fuzzy matching is required in performing genetic marker name matching. Each query target may be matched with multiple genetic markers, and each genetic marker may also be matched with multiple query targets, whose referenced genetic markers are recorded by the query targets.
(4) BLAST alignment of sequences referenced by a query target using the NCBI's local BLAST program
The query target will reference a large number of repeated or non-repeated DNA sequences, which will be de-duplicated and numbered and then output as FASTA files in the clear. The external tool used was local BLAST from NCBI and the genome database used was the "Darmor-dzh" reference genome (downloaded from http:// www.genoscope.cns.fr/blat-server/cgi-bin/colza/webBlat). After the screening is finished, the output result of the BLAST program adopts the Format 6 carried by the BLAST program, and the BLAST program is coded in a text Format. This format can be recognized by the program and referenced by the DNA sequence referenced by the query object.
(5) Direct or indirect conversion of BLAST results into their location in the genome
The cabbage rape is based on DNA hybridization, 6K and 60K SNP chip probe sequences are single sequences, and the position of the matched site of the BLAST on the genome is the potential genome positioning. The primer sequence of the cabbage type rape based on the PCR marker is 2 forward and reverse sequences, the matched sites of the BLAST on the genome must extend in opposite directions and have enough distance to become potential matched sites, and the nearest distance needs a researcher to set program parameters according to the length of PCR products marked by different types.
(6) Screening for false positive results
In the last step, there are partial false positive results for the potential matching sites. And (3) carrying out primary screening according to the chromosome information of the QTL (the QTL research of most of the segregation populations can provide the chromosome information of the QTL), and removing the false positive result. And (3) carrying out secondary screening by using a box diagram mode, and screening out irregular and unfocused genome positioning of each molecular marker linked with the QTL.
(7) QTL genome location determination
The results after false positive screening will show that the genomic location of the QTL-linked markers will define a small range, and the box plot for secondary screening provides a quartet locus range, which is used as the chromosomal interval corresponding to the QTL.
(8) After the oil content QTL detected from each population is subjected to the implementation steps, the genome location of all the QTL of the oil content reported at present is obtained, and then the genome location of all the QTL of the oil content detected by the KN population is compared with the genome location of the QTL of the oil content detected by the KN population to identify the stable and novel QTL, as shown in figure 2, the QTL of the cabbage type rape identified by the invention is located in the genome (taking A09 chromosome as an example), the vertical bar on the left in figure 2 is A09 chromosome, the dark vertical bar on the right is QTL, and the horizontal position of the QTL is located in the genome corresponding to the position of the left chromosome. The QTL is followed by the chromosome name, and the suffix is the QTL detected corresponding to the QTL, such as qOC-A9-1-TN is a QTL on A9 detected by the segregation population TN. Provides reference for future Molecular Assisted Selection (MAS) breeding and map-based cloning.
In the database in the step (1), the genetic marker name and the sequence information provided by the user are only the minimum data requirements, and additional auxiliary information such as user-defined tags, preset QTL names, preset chromosome positions and the like can be added in an expanded manner.
In the data in the step (2), the query target name and the QTL name provided by the user are only the minimum data requirements, and additional auxiliary information such as user-defined tags, preset chromosome positions and the like can be added in an expanded mode.
In the fuzzy matching method described in step (3), because the universal naming rules of the genetic markers have certain differences and the same commonalities, in the fuzzy matching method, the ignored naming features are: underlining and dash separators, letter case, last letter in the case of the penultimate digit being a number. The fuzzy matching scheme constructs a substitute name only containing lower case letters and numbers by a method of eliminating the ignored naming characteristics, and accurately matches the substitute name so as to realize fuzzy matching of the genetic marker naming.
The external software described in step (4) is a publicly available, open source, local BLAST program from NCBI. The module used is blastn.exe in its BLAST program suite.
And (4) outputting the FORMAT of the BLAST program carried by the BLAST program in the FORMAT of FORMAT NO.6, so as to facilitate subsequent processing. Other formats may be used.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (5)
1. A QTL comparison method among different segregation populations of crops is characterized by comprising the following steps:
(1) constructing a genetic marker database: the database contains molecular marker names and sequence information of different crop separation groups based on DNA hybridization, primer names and sequence information of different crop separation groups based on PCR molecular markers, and names of SNP molecular markers of the different crop separation groups and probe sequence information of the SNP molecular markers;
(2) constructing a query target: the query target comprises QTL names of different segregation populations of crops and molecular marker names linked with the QTL, the target trait QTL contains at least one linked molecular marker, and the combination of the QTL name of the target trait and the molecular marker name linked with the QTL is used as a query target;
(3) matching molecular marker sequences: matching the query target in the step (2) with the genetic marker database in the step (1), and calling a molecular marker sequence corresponding to the query target in the step (2);
(4) genome mapping: if the molecular marker sequence in the step (3) is a molecular marker sequence based on DNA hybridization or an SNP molecular marker sequence, performing Blast comparison on the molecular marker sequence in the step (3) in a genome sequence database of the crop to obtain an alignment site as potential genome positioning of the marker; if the molecular marker sequence in the step (3) is based on a PCR molecular marker sequence, performing Blast comparison on the forward primer sequence and the reverse primer sequence of the molecular marker sequence in the step (3) in a genome sequence database of the crop respectively, and if the matching sites of the two primer sequences are positioned on the same chromosome close enough to become potential matching sites, the closest distance needs to be taken as reference according to the lengths of PCR products of different types of markers, and the matching sites of the forward primer and the reverse primer are respectively a positive strand and a reverse strand of a genome DNA sequence, taking the matching sites of the two primer sequences as potential genome positioning of the marker;
(5) eliminating false positive results: judging whether the potential genome mapping and the chromosome where the corresponding QTL is located are the same chromosome or not in the step (4); if the potential genome location in the step (4) is not the same chromosome as the chromosome where the corresponding QTL is located, determining that the potential genome location is a false positive, and rejecting a false positive result; secondly, screening out genome positioning deviating from an aggregation region in each molecular marker linked with the QTL by using a box-type diagram method;
(6) determining a genome region corresponding to the QTL of the target character: determining the region corresponding to the reaction site gathered in the gathering region on the same chromosome in the genome positioning obtained in the step (5) as the genome region corresponding to the QTL (quantitative trait locus); and judging whether the QTL of different segregation populations corresponds to the same genome region or not.
2. The method for comparing QTLs between different segregating populations of a crop according to claim 1, wherein the DNA-hybridization based molecular marker of step (1) is a DNA-hybridization based molecular marker of brassica napus; the SNP molecular marker in the step (1) is a marker for typing a cabbage type rape 6K or 60K SNP chip; the PCR-based molecular marker in the step (1) is a PCR-based molecular marker for Brassica napus.
3. The method for comparing QTLs between different segregating populations of a crop according to claim 1, wherein the query in step (2) is further directed to information about the chromosome on which the molecular marker linked to the QTL is located.
4. The method for QTL comparison between different segregating populations of a crop according to claim 1, wherein the genetic marker database in step (1) further comprises information on the location of the chromosome on which the PCR molecular marker primer sequence, the SNP molecular marker probe sequence or the DNA hybridization-based molecular marker sequence is located.
5. A QTL comparison system for crop segregation population, comprising:
a genetic marker database module: the genetic marker database module is used for collecting genetic marker data; the database contains molecular marker names and sequence information of different crop separation groups based on DNA hybridization, primer names and sequence information of different crop separation groups based on PCR molecular markers, and names of SNP molecular markers of the different crop separation groups and probe sequence information of the SNP molecular markers;
and a query target module: the query target module is used for collecting target trait QTL linked molecular markers to be compared among different segregation populations; the query target comprises different segregation population target trait QTL names and molecular marker names linked with the QTL, the target trait QTL contains at least one linked molecular marker, and the combination of the target trait QTL name and the molecular marker name linked with the QTL is used as a query target;
matching molecular marker sequence modules: for matching the query target with a database of genetic markers; matching the query target with the genetic marker database, and calling a molecular marker sequence corresponding to the query target in the genetic marker database;
a genome mapping module: for identifying potential genomic locations; if the molecular marker sequence is a molecular marker sequence based on DNA hybridization or an SNP molecular marker sequence, performing Blast comparison on the molecular marker sequence in a genome sequence database of the crop to obtain a comparison site as potential genome positioning of the marker; if the molecular marker sequence is based on a PCR molecular marker sequence, performing Blast comparison on a forward primer sequence and a reverse primer sequence of the molecular marker sequence in a genome sequence database of the crop respectively, and if the matching sites of the two primer sequences are positioned on the same chromosome close enough to become potential matching sites, the closest distance needs to be taken as reference according to the lengths of PCR products of different types of markers, and the matching sites of the forward primer and the reverse primer are respectively a positive strand and a negative strand of a genome DNA sequence, taking the matching sites of the two primer sequences as potential genome positioning of the marker;
a false positive result eliminating module: the method is used for removing matching sites deviating from a QTL prediction region; judging whether the chromosome of the potential genome location and the chromosome of the corresponding QTL are the same chromosome; if the potential genome location and the chromosome where the corresponding QTL is located are not the same chromosome, the potential genome location is a false positive, and the false positive result is removed; secondly, screening out genome positioning deviating from an aggregation region in each molecular marker linked with the QTL by using a box-type diagram method;
determining a genome region module corresponding to the QTL of the target character: for determining the location interval of the QTL on the genome; determining the region corresponding to the reaction site gathered in the gathering region on the same chromosome in the genome positioning as the genome region corresponding to the target character QTL; and judging whether the QTL of different segregation populations corresponds to the same genome region or not.
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