Method and system for constructing database of wild rice introduction lines

Abstract

This invention relates to a method and system for constructing a database of wild rice introduction lines. The method includes: acquiring raw genotype data, sample metadata, and phenotypic data of individual samples from multiple wild rice introduction line populations, where the sample metadata includes a sample number; parsing and identifying the raw genotype data to determine the fragment location, fragment type, and fragment length of the wild rice introduction fragment, thus obtaining the corresponding genotype data; and, based on the sample number, associating and integrating the genotype data, sample metadata, and phenotypic data to generate a structured dataset. This structured dataset is then used to construct a database corresponding to multiple wild rice introduction line populations, improving the integration and correlation of wild rice introduction line data, promoting the collaborative utilization of genetic resources, facilitating the sharing of genetic resources among wild rice introduction line populations, and enhancing the interoperability and value of scientific research resources.

Description

Technical Field

[0001] This invention relates to the field of database processing technology, and in particular to a method and system for constructing a database of wild rice introduction lines. Background Technology

[0002] Wild rice, as a closely related wild species to cultivated rice, contains many excellent genes such as stress resistance, disease resistance, and high quality, making it a valuable resource for broadening the genetic base of cultivated rice and carrying out genetic improvement. To utilize these resources, breeders have constructed multiple sets of "wild rice introduction lines" with clear genetic backgrounds, carrying only specific wild rice chromosome segments, through hybridization and multiple backcrosses, combined with molecular marker selection. These populations are key experimental material systems for discovering beneficial genes in wild rice and elucidating the genetic mechanisms of complex traits.

[0003] With the widespread application of high-throughput genotyping technology, massive amounts of multi-dimensional data have been generated surrounding these imported line populations. This data mainly includes: 1) raw genotypic data obtained through gene chips or sequencing; 2) sample metadata describing the sample's origin, parents, generations, etc.; and 3) phenotypic data recording traits such as plant height and yield. However, in actual scientific research and breeding work, the effective utilization of these data resources faces significant challenges: First, data integration and association operations are cumbersome and rely heavily on manual intervention. Genotypic data, sample management information, and phenotypic data are usually scattered across different files, tables, or simple databases. Researchers need to manually match sample numbers to associate the phenotypic expression of a sample with a specific segment in its genome. This process is time-consuming, labor-intensive, and prone to errors, severely limiting the scale and efficiency of genotype-phenotype association analysis. Second, the extraction process of imported fragment information is non-standardized and difficult to automate and reuse. Accurately identifying, locating, and determining the wild rice imported fragment carried by each sample from massive, fine-grained raw genotypic data currently often requires researchers to write ad-hoc scripts for semi-manual analysis. This method lacks standardized rules, leading to inconsistent analytical results and making direct comparison and integration across different laboratories or different introductory line populations difficult. Thirdly, data resources exist in silos, hindering scientific collaboration and in-depth resource exploration. Due to the aforementioned obstacles in data management and analysis, the valuable introductory line materials and their corresponding multi-dimensional data constructed by various research teams are difficult to share effectively in a structured, machine-readable manner. This makes cross-team and cross-population collaborative analysis and comparative studies difficult to conduct, and the value of genetic resources is not maximized.

[0004] Therefore, the current research and breeding application of wild rice introduction lines urgently need a technical solution that can systematically and automatically transform multi-source raw data into a standardized and structured knowledge system to support efficient and accurate gene mining and breeding decisions. Summary of the Invention

[0005] In view of this, it is necessary to provide a method and system for constructing a database of wild rice introduction lines to solve the technical problems of existing wild rice introduction line data being scattered, lacking correlation, and difficult to share.

[0006] To address the aforementioned problems, in a first aspect, the present invention provides a method for constructing a database of introduced wild rice lines, comprising: The original genotype data, sample metadata, and phenotypic data of each individual sample in multiple wild rice introduction line populations were obtained. The sample metadata includes the sample number used to identify different individual samples. The original genotype data is analyzed and identified to determine the fragment location, fragment type, and fragment length of the wild rice introduced from the wild rice introduced line population in each individual sample, thereby obtaining the corresponding genotype data. Based on the sample number, the genotype data, sample metadata, and phenotypic data are linked and integrated to generate a structured dataset, and multiple databases corresponding to the wild rice import line populations are constructed based on the structured dataset.

[0007] In one possible implementation, the parsing and identification processing of the original genotype data includes: According to the preset genotype coding rules, the original genotype data is parsed to determine the genotype of each sample corresponding to the sample metadata at each probe site. The genotype coding rules are used to distinguish between the recipient parent homozygous type, the donor wild rice parent homozygous type, and the heterozygous type. Based on the genotype, continuous chromosomal intervals with genotypes that are homozygous or heterozygous for the donor wild rice parent are identified. Each chromosomal interval is determined to be a wild rice introduced fragment from the wild rice introduced line population in each sample, and the fragment location, fragment type, and fragment length of the wild rice introduced fragment are recorded.

[0008] In one possible implementation, after constructing multiple databases corresponding to the wild rice importation line populations based on the structured dataset, the method further includes: Deploy and configure a data retrieval interface in the database to perform retrieval operations on the structured dataset in response to retrieval criteria; The search criteria include at least one of the following: the sample number or donor-recipient combination corresponding to the sample metadata, the chromosome position corresponding to the imported fragment position, and the fragment type corresponding to the imported fragment type.

[0009] In one possible implementation, after constructing multiple databases corresponding to the wild rice importation line populations based on the structured dataset, the method further includes: Deploy data visualization services in the database; The genotype data in the structured dataset is read using the data visualization service. A chromosome fragment distribution map is generated based on the retrieved genotype data; The distribution map of the chromosome imported fragments is shown.

[0010] In one possible implementation, the fragment type includes homozygous import fragments and heterozygous import fragments; The step of displaying the chromosome fragment distribution map includes: In the chromosome fragment distribution map, different visual styles are used to distinguish between homozygous and heterozygous imported fragments.

[0011] In one possible implementation, the step of obtaining the phenotypic data includes: Standardize the agronomic trait phenotypic data.

[0012] In one possible implementation, the step of obtaining the original genotype data includes: The detection is based on rice gene chips, wherein the rice gene chip includes the rice green gene chip GSR40K.

[0013] In one possible implementation, the types of phenotypic data include at least plant height, spike neck length, spike length, number of effective spikes, total number of filled grains, yield per plant, thousand-grain weight, and number of grains per spike.

[0014] In one possible implementation, after constructing multiple databases corresponding to the wild rice importation line populations based on the structured dataset, the method further includes: Save the structured dataset as a JSON file.

[0015] Secondly, the present invention also provides a system for constructing a database of wild rice introduced lines, comprising: The acquisition unit is used to acquire the original genotype data, sample metadata and phenotypic data of each individual sample in multiple sets of wild rice introduction line populations. The sample metadata includes the sample number used to identify different individual samples. The analysis unit is used to parse and identify the original genotype data, determine the fragment location, fragment type and fragment length of the wild rice introduced fragment from the wild rice introduced line population in each individual sample, and obtain the corresponding genotype data. The construction unit is used to associate and integrate the genotype data, the sample metadata, and the phenotypic data based on the sample number to generate a structured dataset, and to construct multiple databases corresponding to the wild rice import line populations based on the structured dataset.

[0016] Thirdly, the present invention also provides a computer-readable storage medium for storing a computer-readable program or instruction, which, when executed by a processor, can implement the steps in the method for constructing the wild rice introduction line database described in any of the above implementations.

[0017] The beneficial effects of this invention are: The method for constructing a wild rice introduction line database provided by this invention acquires the original genotype data, sample metadata, and phenotypic data of individual samples from multiple wild rice introduction line populations. The sample metadata includes sample numbers used to identify different individual samples, avoiding data bias caused by selective collection and ensuring the subsequent construction of a database that comprehensively reflects the genetic structure of the population. The original genotype data is analyzed and identified to determine the fragment location, fragment type, and fragment length of the wild rice introduction fragment from the wild rice introduction line population in each individual sample, obtaining their corresponding genotype data. This improves the efficiency and accuracy of wild rice beneficial gene localization and breeding utilization, and enhances the comparability and integration efficiency of cross-study data. Based on the sample numbers, the genotype data, sample metadata, and phenotypic data are correlated and integrated to generate a structured dataset. Based on this structured dataset, a database corresponding to multiple wild rice introduction line populations is constructed, realizing the "parental background-genotype-phenotype" of the wild rice introduction line population. The integrated approach improves the integration and quality of structured datasets, enhances the integration and correlation of wild rice introduction line data, promotes the collaborative utilization of genetic resources, facilitates the sharing of genetic resources among wild rice introduction line populations, effectively realizes the efficient sharing and collaborative utilization of wild rice introduction line data, and enhances the interoperability and value of scientific research resources. Attached Figure Description

[0018] Figure 1 A schematic flowchart of an embodiment of the method for constructing a database of introduced wild rice lines provided by the present invention; Figure 2 Provided by the present invention Figure 1 A schematic diagram of an embodiment of S102; Figure 3 A schematic diagram of the database website login interface provided by this invention; Figure 4 This is a schematic diagram of the user management page operation provided by the present invention; Figure 5 This is a schematic diagram of the sample information interface operation provided by the present invention; Figure 6 A schematic diagram of the page for the phenotypic data provided by this invention; Figure 7 This is a visual page illustration provided by the present invention; Figure 8 This is a schematic diagram of the structure of the system for constructing the wild rice introduction line database provided by the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0020] In the description of the embodiments of the present invention, unless otherwise stated, "a plurality of" means two or more.

[0021] The terms "first," "second," etc., used in the embodiments of this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a technical feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature.

[0022] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0023] This invention provides a method and system for constructing a database of introduced wild rice lines, which will be described below.

[0024] The execution entity of the method for constructing the wild rice introduction line database in this application embodiment can be the wild rice introduction line database construction system provided in this application embodiment, or different types of electronic devices such as server equipment, physical host, or user equipment (UE) that integrate the wild rice introduction line database construction system. The wild rice introduction line database construction system can be implemented in hardware or software. The UE can be a terminal device such as a smartphone, tablet computer, laptop computer, handheld computer, desktop computer, or personal digital assistant (PDA).

[0025] Figure 1 This is a schematic flowchart of an embodiment of the method for constructing a database of introduced wild rice lines provided by the present invention, as shown below. Figure 1 As shown, the method for constructing the wild rice introduced line database includes: S101. Obtain the original genotype data, sample metadata, and phenotypic data of each individual sample in multiple sets of wild rice introduction line populations. The sample metadata includes the sample number used to identify different individual samples.

[0026] In this application, the wild rice introduction line population specifically refers to a series of lines obtained by hybridizing wild rice (donor) and cultivated rice (recipient), followed by multiple generations of backcrossing and marker-assisted selection. These lines have a genetic background highly restored to that of the recipient and carry different wild rice fragments on different chromosomes. This material is an ideal carrier for genetic mapping and gene localization. Specifically, the wild rice introduction line population can be constructed as follows: using wild rice as the donor and cultivated rice as the recipient, an introduction line population covering the entire genome is constructed through a process of "hybridization-backcrossing-gene chip detection-single plant screening".

[0027] In this embodiment, the multiple sets of wild rice introduction line populations can be three sets of wild rice introduction line populations, using Gaozhou wild rice, Conghua wild rice, and Zhanying wild rice as donors, and Teqing (TQ) and Guanghui 998 (R998) as recipients. Through hybridization, continuous backcrossing, and rice gene chip-assisted selection, three sets of introduction line populations are constructed: Conghua wild rice × Teqing (TQ), Zhanying wild rice × Teqing (TQ), and Gaozhou wild rice × Guanghui 998 (R998), with each set containing more than 100 introduction line strains.

[0028] The raw genotyping data consists of electronic files recording the genetic signals of tens of thousands of probe sites. These files reflect the raw genetic state of each individual sample at hundreds of thousands of specific locations across the entire genome, including structured information such as: probe / marker identifiers: a unique ID for each detection site; genomic coordinates: the chromosome number corresponding to the probe and its precise physical location on the reference genome (unit: base pairs, bp); and genotyping signals or preliminary results for each sample at each probe site: the genotype call for each sample-probe site combination, expressed as "AA", "BB", "AB", "--", etc., or directly providing signal intensity values ​​(e.g., fluorescence intensity on the X and Y axes) for genotyping.

[0029] Sample metadata refers to the identification and genetic background description of each wild rice introduction line individual sample, that is, the description information of the parental background, recording the unique sample number of the individual sample, the donor-recipient combination to which it belongs, the backcross generation, and other identity and origin information.

[0030] Phenotypic data refers to specific numerical or categorical information used to describe the heritable traits such as appearance, physiological characteristics, and yield composition of wild rice introduced lines. These include agronomic trait indicators, which serve as the direct basis for screening superior materials and locating functional genes in genetic breeding research.

[0031] Specifically, for each individual sample in the wild rice introduction line population, three types of data can be collected in parallel: the first type is raw genotype data, which can be obtained by scanning the whole genome of the sample through a high-throughput genotyping platform; the second type is sample metadata; and the third type is phenotypic data, obtained through field trials, covering a series of important agronomic traits. Understandably, in this embodiment, by acquiring these three types of data from each individual sample in multiple sets of wild rice introduction line populations, the data bias caused by selective collection is avoided, ensuring that a comprehensive database reflecting the population's genetic structure can be constructed subsequently.

[0032] S102. The original genotype data is analyzed and identified to determine the fragment location, fragment type, and fragment length of the wild rice introduced from the wild rice introduced line population in each individual sample, thereby obtaining the corresponding genotype data.

[0033] Among them, the wild rice introduced fragment refers to a continuous chromosomal segment in the genetic background of the recipient cultivated rice, whose genetic material originates from the wild rice donor.

[0034] Wild rice imported fragments include three key attributes: fragment location, fragment type, and fragment length. Fragment location refers to the physical location of the fragment on the reference genome, typically described by chromosome number and the start and end physical positions (unit: base pairs, bp), for example, "Chr6: 12,345,678-15,678,901 bp". Fragment type is derived from the genotype coding structure of the fragment at the time of identification. If all sites within the fragment are of type "B", it is identified as a "homozygous imported fragment"; if "H" sites are present, it is identified as a "heterozygous imported fragment". Fragment length is calculated based on the start and end physical positions, reflecting the physical distance across the genome traversed by the imported fragment.

[0035] The fragment type is either homozygous or heterozygous.

[0036] Specifically, based on the original genotype data, background genotyping analysis is performed on each sample of the wild rice introduction line. The chromosomal location and genotyping results of the probe sites are analyzed, and the genotypic differences between the progeny and the recipient parents are compared to determine the fragment location, fragment type, and fragment length of the wild rice introduction fragment. The original genotype data can be parsed based on sample metadata to determine the genotype of each sample at each probe site. Based on the genotype, the fragment location, fragment type, and fragment length of the wild rice introduction fragment from the wild rice introduction line population in each sample are identified and defined, i.e., the interval, start and end positions on the chromosome, and homozygous / heterozygous status. Then, the fragment location, fragment type, and fragment length of the wild rice introduction fragment are structured and stored as genotype data.

[0037] Understandably, this embodiment performs background genotyping analysis on each sample, enabling the extraction of genetically significant introductory fragments from massive amounts of raw genotyping data at the base-pair level. The fragment location and interval provide a directly usable coordinate system and classification standard for precise genotype-phenotype association studies. Researchers can quickly anchor observed phenotypic differences to specific chromosomal intervals based on fragment location. Simultaneously, fragment type provides crucial information for breeding selection. This improves the efficiency and accuracy of wild rice gene localization and breeding utilization, and enhances the comparability and integration efficiency of cross-study data.

[0038] S103. Based on the sample number, the genotype data, the sample metadata, and the phenotypic data are associated and integrated to generate a structured dataset, and multiple databases corresponding to the wild rice import line populations are constructed based on the structured dataset.

[0039] Specifically, the sample number can be used as a unique key to bind the genotype data containing fragment information corresponding to each individual sample to the sample number, and the phenotypic data corresponding to each individual sample to the sample number. This enables structured data recombination and aggregation of genotype data, sample metadata, and phenotypic data of each individual sample in the wild rice introduction line population, resulting in a structured dataset. This achieves integrated "parental background-genotype-phenotype" data of the wild rice introduction line population, improving the integration degree and quality of the structured dataset. Based on this highly integrated and high-quality structured dataset, a corresponding database of the wild rice introduction line population can be deployed and constructed. The associated and integrated data is stored in a unified database system and deployed on a web server, allowing authorized researchers to remotely access the complete, multi-dimensional, and associated structured dataset through a data retrieval interface without having to acquire and integrate the original scattered files. This improves the integration degree and correlation of the wild rice introduction line data, promotes the collaborative utilization of genetic resources, facilitates the sharing of genetic resources of the wild rice introduction line population, effectively realizes the efficient sharing and collaborative utilization of wild rice introduction line data, and enhances the interoperability and value of scientific research resources.

[0040] In one specific implementation, a series of data tables linked together by sample number foreign keys are constructed in the database. Physically, this can be converted to a structured data format such as JSON. In the structured dataset, each record under any valid sample number contains the individual sample's background identity (sample metadata), genetic makeup (genotype data), and phenotypic expression (phenotype data). This integrated "parental background-genotype-phenotype" data organization ensures that information from all relevant dimensions can be accessed synchronously and consistently in any subsequent query, analysis, or visualization operations.

[0041] In summary, the method for constructing a wild rice introduction line database provided in this embodiment of the invention obtains the original genotype data, sample metadata, and phenotypic data of each individual sample from multiple wild rice introduction line populations. The sample metadata includes sample numbers used to identify different individual samples, avoiding data bias caused by selective collection and ensuring that a database comprehensively reflecting the genetic structure of the population can be constructed subsequently. The method also analyzes and identifies the original genotype data to determine the fragment location, fragment type, and fragment length of the wild rice introduction fragment from the wild rice introduction line population in each individual sample, obtaining their corresponding genotype data. This improves the efficiency of wild rice beneficial gene localization and breeding utilization. This approach improves accuracy and enhances the comparability and integration efficiency of cross-study data. Based on sample numbers, genotype data, sample metadata, and phenotypic data are linked and integrated to generate structured datasets. Multiple databases corresponding to wild rice introduction lines are then constructed based on these structured datasets. This achieves integrated "parental background-genotype-phenotype" data for wild rice introduction lines, improving the integration and quality of structured datasets, enhancing the integration and correlation of wild rice introduction line data, promoting the collaborative utilization of genetic resources, facilitating the sharing of genetic resources among wild rice introduction line populations, effectively realizing the efficient sharing and collaborative utilization of wild rice introduction line data, and enhancing the interoperability and value of scientific research resources.

[0042] In some embodiments of the present invention, such as Figure 2 As shown, step S102 includes: S201. According to the preset genotype coding rules, the original genotype data is parsed to determine the genotype of each sample corresponding to the sample metadata at each probe site. The genotype coding rules are used to distinguish between the homozygous type of the recipient parent, the homozygous type of the wild rice donor parent, and the heterozygous type. S202. Based on the genotype, identify continuous chromosomal intervals with genotypes that are homozygous or heterozygous for the donor wild rice parent, determine each chromosomal interval as a wild rice introduced fragment from the wild rice introduced line population in each sample, and record the fragment location, fragment type, and fragment length of the wild rice introduced fragment.

[0043] Among them, the genotype coding rule definition can be: "A" to represent the homozygous genotype consistent with the recipient parent, "B" to represent the homozygous genotype consistent with the donor wild rice parent, "H" to represent the heterozygous genotype, and "NA" to represent missing data.

[0044] Based on genotype, consecutive chromosomal intervals with genotype "B" or "H" are identified, each interval is determined as a wild rice introductory fragment, and its fragment location, fragment type, and fragment length are recorded.

[0045] Specifically, basic probe information (chromosome number, physical location) and sample genotyping results are extracted from the raw genotype data, using a unified coding system: "A" represents a homozygous genotype consistent with the recipient parent, "B" represents a homozygous genotype of the wild rice donor parent, "H" represents a heterozygous genotype of the wild rice-recipient parent, and "NA" represents missing data. Using the recipient parent genotype as a reference, the genotyping results of the progeny lines are compared site by site. When the progeny exhibits "H" or "B" type, it is determined to be a wild rice introduction site. Combined with the physical locations of adjacent probes, continuous introduction fragments are spliced ​​together to determine the chromosomal interval, origin, end point, and heterozygous / homozygous status of the fragments. This achieves the analysis and standardization of genotype data.

[0046] Understandably, this embodiment automates and objectifies the genotype data analysis process by adopting standardized coding rules and a continuous fragment recognition method. This avoids the subjective differences and errors caused by traditional manual interpretation or temporary script processing, ensuring the consistency and comparability of analysis results between different samples, batches, and even different laboratories. At the same time, it parses and identifies massive amounts of fine-grained locus data into structured fragment records, compressing the data scale while ensuring the accuracy and integrity of genetic characteristics.

[0047] In some embodiments of the present invention, after step S103, the method further includes: deploying and configuring a data retrieval interface in the database to perform a retrieval operation on the structured dataset in response to retrieval conditions; wherein the retrieval conditions include at least one of the following: a sample number or donor-recipient combination corresponding to sample metadata, a chromosome position corresponding to the imported fragment position, and a fragment type corresponding to the imported fragment type.

[0048] The data retrieval interface is the programming interface through which a database system provides data query services. It allows users or applications to send requests containing search criteria using a specific query language or protocol. For example, the data retrieval interface can be designed based on the RESTful application programming interface architecture, receive Hypertext Transfer Protocol requests and return Extensible Markup Language or JSON format data, and search and filter the generated structured dataset by executing Structured Query Language (SQL) statements or calling preset query functions.

[0049] Search criteria are specific fields mapped to the structured dataset, including: sample number or donor-recipient combination corresponding to sample metadata, and chromosome location and fragment type corresponding to genotype data.

[0050] Specifically, to further improve data availability and access efficiency, a data retrieval interface is configured in the database to perform retrieval operations. For example, the retrieval interface can handle combinations of conditions such as "donor is wild rice with bark and recipient is TQ" and convert them into filtering of the sample metadata table; it can also handle conditions such as "chromosome location is between 1,200,000 and 1,500,000 base pairs on chromosome 6" and convert them into range queries for imported fragment location information. The interface supports the combined use of these conditions, thereby enabling complex queries accurate to specific populations, specific chromosome ranges, and specific fragment types. This allows researchers to efficiently and flexibly obtain target data through a standardized interface without directly manipulating the underlying database, supporting multi-condition combined retrieval and personalized data downloads to meet the diverse needs of researchers.

[0051] Understandably, this embodiment improves the efficiency and accuracy of locating and extracting specific information from complex structured datasets by abstracting and solidifying diverse search criteria into a standardized data retrieval interface. This allows for the efficient mining of the integrated value of data encompassing "parental background, genotype, and phenotype," enabling researchers to quickly verify scientific hypotheses such as "whether a specific wild rice fragment is related to a specific phenotype," thereby accelerating the process of gene localization and functional research. Furthermore, the standardized interface promotes data resource sharing and collaboration. Researchers from different teams can access and utilize resources in the database through a unified access method, avoiding collaboration barriers caused by inconsistent data formats or access methods.

[0052] In some embodiments of the present invention, after step S103, the method further includes: deploying a data visualization service in the database; reading genotype data from the structured dataset through the data visualization service; generating a chromosome import fragment distribution map based on the read genotype data; and displaying the chromosome import fragment distribution map.

[0053] Specifically, based on the genotype data in the structured dataset retrieved by the data visualization service, a chromosome import fragment distribution map is generated using a graphics rendering engine. In this view, the chromosome import fragment distribution map uses chromosome number and physical location as the horizontal axis and different import line samples as the vertical axis. Each import fragment is plotted according to its physical location and length at the intersection of the corresponding chromosome interval and sample row using graphic elements (such as rectangular bars). The chromosome import fragment distribution map can also be dynamically displayed through the front-end interface of the database system, allowing users to clearly understand the import status of wild rice fragments on different samples and chromosomes.

[0054] Understandably, in this embodiment, by deploying a dedicated data visualization service, complex genotype data, such as spatial distribution information of imported fragments, is transformed into an intuitive and interactive graphical representation. Through genotype background typing and visualization, the location of wild rice imported fragments and their corresponding genotype and phenotypic information can be quickly located. By referencing the advantages of molecular marker-assisted selection constructed from imported lines, gene cloning efficiency is further improved, and analysis efficiency is enhanced. At the same time, it supports the development of multi-dimensional visualization maps to intuitively display the distribution, genotype, and phenotypic information of imported fragments, thereby significantly reducing the data interpretation threshold for researchers.

[0055] In some embodiments of the present invention, the fragment type includes homozygous imported fragments and heterozygous imported fragments; displaying the chromosome imported fragment distribution map includes: using different visual styles to distinguish the homozygous imported fragments from the heterozygous imported fragments in the chromosome imported fragment distribution map.

[0056] Visual style refers to the combination of visual features used to represent different data categories in a graphical interface. This can be achieved, but is not limited to, using different colors (e.g., red for homozygous segments and blue for heterozygous segments), different fill patterns (such as diagonal fills and dotted fills), or different shape outlines for differentiation. By applying this differentiated visual mapping, users can simultaneously and clearly identify the physical location and precise genetic state (homozygous or heterozygous) of each imported segment on a single distribution map.

[0057] Specifically, to achieve an intuitive and information-rich display, the data visualization service in this embodiment uses differentiated visual styles to distinguish between homozygous and heterozygous imported fragments when generating a chromosome imported fragment distribution map. This facilitates intuitive comparative analysis between different samples or different imported line populations, thereby improving analysis efficiency.

[0058] In some embodiments of the present invention, the step of obtaining phenotypic data includes: standardizing the agronomic trait phenotypic data.

[0059] Specifically, the phenotypic data comes from a systematic field survey of each individual sample in multiple wild rice introduction lines, and the data is obtained after standardization. The standardization methods can include unifying the units of measurement, correcting obvious observation errors, and converting text descriptions into classification codes, thereby transforming the multi-source and heterogeneous original observation records into a structured data table with a unified format, standardized values, and precise correspondence with the sample numbers.

[0060] In some embodiments of the present invention, the step of obtaining the original genotype data includes: detection based on a rice gene chip, wherein the rice gene chip includes the rice green gene chip GSR40K.

[0061] Specifically, detection can be performed based on the rice green gene chip GSR40K. For example, whole-genome genotyping analysis can be performed on the rice green gene chip GSR40K to obtain the detection results. Then, the detection results can be screened. For example, lines with clear imported fragments and high background recovery rates can be screened out, and the original genotypic data of these lines can be used as the original genotypic data of individual samples.

[0062] In some embodiments of the present invention, the types of phenotypic data include at least plant height, spike neck length, spike length, number of effective spikes, total number of filled grains, yield per plant, thousand-grain weight, and number of grains per spike.

[0063] Specifically, the phenotypic data covers traits that mainly target key agronomic traits in rice breeding, such as, but not limited to: plant height and panicle neck elongation length, which characterize plant structure; panicle length, number of grains per panicle, seed setting rate and thousand-grain weight, which characterize panicle traits; and effective panicle number, total number of filled grains and yield per plant, which characterize final yield. This constitutes a multi-level phenotypic profile from morphology and components to final output, which can comprehensively evaluate the agronomic performance of the introduced line material.

[0064] In some embodiments of the present invention, after step S103, the method further includes: saving the structured dataset as a JSON format file.

[0065] Specifically, the structured dataset is saved as a JSON file for subsequent loading and use by the database website. This can be achieved using libraries in programming languages ​​such as Python and Java (e.g., Python's `json` module). The structured data objects in memory (e.g., dictionaries or lists containing sample lists, each with nested metadata, phenotypic value lists, and import fragment object lists) can be converted into JSON-compliant strings and written to a physical file with the ".json" extension. This JSON file serves as the static storage medium for the structured dataset. This provides a standardized, portable, and fast-loading medium for the wild rice import line database. Due to the universality of the JSON format, this file can be easily read and used by various front-end technology stacks or data analysis tools. For example, in the database website construction, the front-end visualization module (developed using JavaScript and the ECharts.js library) can directly load this JSON-formatted data file via HTTP requests and leverage JavaScript's native support for JSON parsing to quickly convert the data into objects in the browser's memory, thereby driving the dynamic rendering of the chromosome import fragment distribution map. This approach avoids the performance overhead of complex parsing of custom binary formats or frequent queries to the backend database on the front end, achieving efficient decoupling of data and presentation logic.

[0066] Meanwhile, using JSON format to store structured datasets improves the efficiency of data loading and parsing in web application environments compared to custom binary formats or direct storage in relational database tables for later querying.

[0067] It is worth noting that a database website accessible via a web browser can also be established and deployed; wherein, the database website is configured to provide users with the following functional pages based on the structured dataset: The user management page is used by administrators to create user accounts, assign permissions, and manage user accounts. The sample information display and retrieval page is used to display imported sample information in tabular form based on the sample metadata and to support filtering by sample number and basic background conditions. The phenotypic data query page is used to query and display agronomic trait phenotypic data associated with the sample based on the phenotypic data. A visualization page is used to dynamically render and display the distribution of wild rice imported fragments in the form of chromosome maps based on the genotype data.

[0068] In one specific implementation, a database website can be built by combining the completed database, specifically including: (1) Technical architecture: The main technologies used in the development of the wild rice import system database website include: the front-end browser page uses HTML5, CSS3, JavaScript and React technologies; the back-end interface is built using the Spring Boot framework; and the database uses MySQL.

[0069] (2) Core Page Construction: The core pages of the wild rice import line database website include: The user management page is used for account management under administrator privileges. Administrators can create new user accounts, assign user permissions, and edit user information on this page. In addition, users can search the user list by name, account, creation time, and other information.

[0070] The sample information page displays various information about wild rice introduced lines, including generation, system number, sample number, background, chromosome segment number, chromosome segment type, and seed information. Furthermore, this page can display filtered introduced lines based on user-input system number, sample number, background, chromosome segment type, and seed information. Additionally, links in the table's operation fields can navigate to the phenotypic information page or the visualization page.

[0071] The phenotypic information page displays phenotypic data in tables and allows users to filter phenotypic types to see the corresponding results. In the results table, users can search for samples by entering the system number, sample number, and the maximum and minimum values ​​for numerical phenotypic types.

[0072] The visualization page visually displays chromosome fragment diagrams of the imported line population. Utilizing ECharts.js dynamic rendering technology, the page uses chromosome location as the horizontal axis and different samples as the vertical axis, labeling homozygous imported fragments from wild rice donors (type B, marked in red), heterozygous imported fragments (type H, marked in blue), and homozygous fragments from recipient parents (type A, marked in gray) with different colors to generate a chromosome imported fragment distribution map. The results graph has the following functions: ① Mouse wheel zoom support; ② Filtering imported line fragments by entering chromosome number, start position, and end position in a form; ③ Clicking on the sample ID displays the sample name, genotyping results, and corresponding phenotypic values; ④ Graphs can be downloaded in PNG format; ⑤ A list of sample IDs displayed in the graph (CSV format table) can be downloaded.

[0073] In another specific implementation, a database website application example is provided, specifically including: 1. User login, such as Figure 3The image shows a schematic diagram of the database website login interface. Researchers access the database website by entering the URL in their browser, and then log in with their username and password to enter the wild rice introduction line database website.

[0074] 2. User management page operations, such as... Figure 4 The image shows a diagram illustrating the user management page operation. Entering "Test" in the name input box of the search bar will retrieve three accounts that match the criteria. Clicking "Edit" on the account "Test User 2" allows you to edit and modify the account's name, account name, role, and status information. Clicking "New" in the pop-up window allows you to enter the new account's name and account name, select the user's permissions, and then click "OK" to create a new user.

[0075] 3. Sample information page operation, such as... Figure 5 The diagram shows the sample information interface operation. By selecting "Zhanying Wild Rice (ZY) × Special Green (TQ)" from the "Select Donor × Recipient" dropdown menu in the upper left corner of the page, and then selecting "2024 Late Season" from the "Select Generation" dropdown menu, you can switch the import line population to which the table data belongs. Entering "6" in the "Chromosome Segment Number" input box in the table search bar and clicking "Search" will retrieve 9 matching individual plants. Clicking the "Visualization" link in the "Operation" field of the table will take you to the visualization page. Clicking the "Phenographic Information" link in the "Operation" field of the table will display the phenotypic data associated with the sample in a pop-up window.

[0076] 4. Table information page operations, such as... Figure 6 The image shows a schematic diagram of the phenotypic data page. After selecting "Plant Height" and "Neck Extension Length" from the drop-down menu in the upper left corner of the page and clicking "Submit," you can view the phenotypic values ​​of plant height and neck extension length for all samples on the platform in the table. By entering "120-140" in the "Plant Height" input box and 0 in the "Minimum Value of Neck Extension Length" input box in the table search bar, you can retrieve 5 single plants that meet the criteria. In addition, clicking on the "Plant Height" column name in the table allows you to sort the table.

[0077] 5. Visual page operation, such as Figure 7The image shown is a schematic diagram of the visualization page. By selecting "Zhanying Wild Rice (ZY) × Teqing (TQ) - 2024 Late Season" from the "Select Donor × Recipient" dropdown menu in the search bar, you can switch the wild rice introductory line population used in the visualization. Entering "6" in the "Chromosome Number" input box in the search bar will filter out visualizations of progeny plants containing introductory line fragments on chromosome 6. Further filtering of the images is possible using "Start Position" and "End Position". The visualization can be zoomed in and out using the mouse wheel, and hovering the mouse over a segment of the image will display its specific information, including sample name, probe name, chromosome name, and chromosome location. Clicking the button in the upper right corner of the image will download it as a PNG file or the sample number of the sample shown in the image as a CSV file.

[0078] To better implement the method for constructing the wild rice introduction line database in this embodiment of the invention, based on the method for constructing the wild rice introduction line database, correspondingly, as follows: Figure 8 As shown, this embodiment of the invention also provides a system for constructing a database of wild rice introduction lines. The system 800 for constructing a database of wild rice introduction lines includes: The acquisition unit 801 is used to acquire the original genotype data, sample metadata and phenotypic data of each individual sample in multiple sets of wild rice introduction line populations. The sample metadata includes the sample number used to identify different individual samples. Analysis unit 802 is used to parse and identify the original genotype data, determine the fragment location, fragment type and fragment length of the wild rice introduced fragment from the wild rice introduced line population in each individual sample, and obtain the corresponding genotype data. The construction unit 803 is used to associate and integrate the genotype data, the sample metadata, and the phenotypic data based on the sample number to generate a structured dataset, and to construct multiple databases corresponding to the wild rice import line populations based on the structured dataset.

[0079] The wild rice introduction line database construction system 800 provided in the above embodiments can realize the technical solutions described in the above embodiments of the wild rice introduction line database construction method. The specific implementation principles of each module or unit can be found in the corresponding content in the above embodiments of the wild rice introduction line database construction method, which will not be repeated here.

[0080] Accordingly, this application also provides a computer-readable storage medium for storing computer-readable programs or instructions. When the programs or instructions are executed by a processor, they can implement the steps or functions in the method for constructing the wild rice introduction line database provided in the above-described method embodiments.

[0081] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware (such as a processor, controller, etc.), and the computer program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0082] The above provides a detailed description of the construction method and system for the wild rice introduction line database provided by this invention. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A method for constructing a database of introduced wild rice lines, characterized in that, The method includes: The original genotype data, sample metadata, and phenotypic data of each individual sample in multiple wild rice introduction line populations were obtained. The sample metadata includes the sample number used to identify different individual samples. The original genotype data is analyzed and identified to determine the fragment location, fragment type, and fragment length of the wild rice introduced from the wild rice introduced line population in each individual sample, thereby obtaining the corresponding genotype data. Based on the sample number, the genotype data, sample metadata, and phenotypic data are linked and integrated to generate a structured dataset, and multiple databases corresponding to the wild rice import line populations are constructed based on the structured dataset.

2. The method according to claim 1, characterized in that, The process of parsing and identifying the original genotype data includes: According to the preset genotype coding rules, the original genotype data is parsed to determine the genotype of each sample corresponding to the sample metadata at each probe site. The genotype coding rules are used to distinguish between the recipient parent homozygous type, the donor wild rice parent homozygous type, and the heterozygous type. Based on the genotype, continuous chromosomal intervals with genotypes that are homozygous or heterozygous for the donor wild rice parent are identified. Each chromosomal interval is determined to be a wild rice introduced fragment from the wild rice introduced line population in each sample, and the fragment location, fragment type, and fragment length of the wild rice introduced fragment are recorded.

3. The method for constructing a database of wild rice introduction lines according to claim 1, characterized in that, After constructing multiple databases corresponding to the wild rice importation line populations based on the structured dataset, the method further includes: Deploy and configure a data retrieval interface in the database to perform retrieval operations on the structured dataset in response to retrieval criteria; The search criteria include at least one of the following: the sample number or donor-recipient combination corresponding to the sample metadata, the chromosome position corresponding to the imported fragment position, and the fragment type corresponding to the imported fragment type.

4. The method for constructing a database of wild rice introduction lines according to claim 1, characterized in that, After constructing multiple databases corresponding to the wild rice importation line populations based on the structured dataset, the method further includes: Deploy data visualization services in the database; The genotype data in the structured dataset is read using the data visualization service. A chromosome fragment distribution map is generated based on the retrieved genotype data; The distribution map of the chromosome imported fragments is shown.

5. The method for constructing a database of wild rice introduction lines according to claim 4, characterized in that, The fragment types include homozygous import fragments and heterozygous import fragments; The step of displaying the chromosome fragment distribution map includes: In the chromosome fragment distribution map, different visual styles are used to distinguish between homozygous and heterozygous imported fragments.

6. The method for constructing a database of wild rice introduction lines according to claim 1, characterized in that, The steps for obtaining the phenotypic data include: Standardize the agronomic trait phenotypic data.

7. The method for constructing a database of wild rice introduction lines according to claim 1, characterized in that, The steps for obtaining the original genotype data include: The detection is based on rice gene chips, wherein the rice gene chip includes the rice green gene chip GSR40K.

8. The method for constructing a database of wild rice introduction lines according to claim 1, characterized in that, The types of phenotypic data include at least plant height, spike neck length, spike length, number of effective spikes, total number of filled grains, yield per plant, thousand-grain weight, and number of grains per spike.

9. The method for constructing a database of wild rice introduction lines according to any one of claims 1-8, characterized in that, After constructing multiple databases corresponding to the wild rice importation line populations based on the structured dataset, the method further includes: Save the structured dataset as a JSON file.

10. A system for constructing a database of introduced wild rice lines, characterized in that, include: The acquisition unit is used to acquire the original genotype data, sample metadata and phenotypic data of each individual sample in multiple sets of wild rice introduction line populations. The sample metadata includes the sample number used to identify different individual samples. The analysis unit is used to parse and identify the original genotype data, determine the fragment location, fragment type and fragment length of the wild rice introduced fragment from the wild rice introduced line population in each individual sample, and obtain the corresponding genotype data. The construction unit is used to associate and integrate the genotype data, the sample metadata, and the phenotypic data based on the sample number to generate a structured dataset, and to construct multiple databases corresponding to the wild rice import line populations based on the structured dataset.

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