A method, device and program product for accurate evaluation of a genetic background of a backcross breeding block

Abstract

The application relates to the field of plant breeding, in particular to a backcross breeding block genetic background precise evaluation method, equipment and program product. By obtaining single plant and parent genotype data in a backcross population, a standardization chromosome fragment recovery state judgment and transformation process from the genotype to the haplotype is established; the ratio of the chromosome recovery fragment and the unrecovered fragment of the backcross single plant is calculated to form a genetic background precise evaluation parameter system. The first parameter is calculated by counting the maximum and minimum values of the unrecovered fragment number of all single plant chromosomes in the backcross population; the second parameter is calculated by counting the unrecovered fragment ratio of each chromosome of each single plant, and the average unrecovered fragment ratio of the chromosomes is obtained; and the unrecovered chromosome fragment distribution index is calculated by adding and calculating the first parameter and the second parameter after assigning weights to the first parameter and the second parameter. The application can improve the corn backcross breeding efficiency and screening precision, and has high popularization and application value.

Description

Technical Field

[0001] This application relates to the field of plant breeding, specifically to a method, platform equipment and program products, and computer-readable storage medium for accurate assessment of the genetic background of backcross breeding blocks. Background Technology

[0002] Backcross breeding is a key strategy for the targeted introduction of target traits in crop genetic improvement. Its traditional paradigm relies on multiple generations of continuous backcrossing and phenotypic selection to gradually restore the genetic background of recurrent parents, which inherently suffers from long breeding cycles, high costs, and low selection efficiency. The development of molecular marker-assisted selection (MAS) technology has provided crucial support for backcross breeding. Its technological evolution has mainly gone through the following stages:

[0003] 1. SSR-based marker-assisted selection. Early studies often used simple sequence repeat (SSR) markers for background assessment. However, this technology suffers from low genome coverage density, limited throughput, and allele interpretation easily affected by experimental conditions. For example, in the backcross breeding of the maize opaque2 gene, using five SSR markers required constructing a BC1F1 population of over 1400 plants to effectively remove flanking linkage cues <5cM, fully exposing its limitations in screening efficiency and making it difficult to meet the needs of precise genome-wide selection. 2. SNP-based marker-assisted selection. High-throughput molecular markers, represented by single nucleotide polymorphisms (SNPs), have achieved high-density genotyping across the entire genome through gene chips or sequencing technologies, significantly improving the throughput and accuracy of background selection, and have become the mainstream technology for current MAS (Magnetic Searching). In practice, SNP chips have successfully shortened the backcross generation of waxy maize to BC3F1. However, such techniques are essentially still within the scope of "dot-marker" analysis. Their core flaw lies in treating the genome as a collection of discrete sites, failing to effectively characterize and track continuous haplotype blocks on chromosomes. Consequently, it is difficult to accurately identify recombination breakpoints and assess the true recovery of chromosome segments. This forces breeders to rely solely on statistical background recovery rates (BRR) for selection, without understanding the underlying chromosomal structure, potentially leading to the misselection of suboptimal plants with high BRR values ​​but genomes fragmented by numerous scattered donor fragments. 3. Analysis methods based on haplotype blocks (HTP). To overcome the limitations of dot-markers, a trend towards haplotype analysis has emerged in existing technologies. The closest existing technology to this invention is the haplotype tag polymorphism (HTP) marker system developed by the Maize Research Institute of the Beijing Academy of Agricultural and Forestry Sciences. This system achieves a paradigm shift from "dot-markers" to "block-markers" by dividing the entire maize genome into 6163 seamlessly connected HTP blocks, and can display recombination events through visualization tools (such as BCplot).

[0004] Although this closest existing technology has upgraded the analysis unit, it still has the following technical problems that urgently need to be solved: 1. Lack of a standardized block determination process: There is a lack of an objective, robust, and unified set of criteria and thresholds for accurately determining the background recovery source of each HTP block (i.e., belonging to the recurrent parent, donor parent, or heterozygous state), which affects the accuracy and reproducibility of the background assessment analysis results. 2. Inability to quantitatively assess the quality of chromosome structure: Although this method can visualize the chromosome recovery map of backcross individuals, it cannot quantitatively assess the distribution of non-recovered chromosome segments (such as quantity, size, and continuity). Breeders therefore find it difficult to systematically screen out ideal individuals with "fewer non-recovered segments, larger segments, and a cleaner genetic background" from single plants with similar BRR, while such individuals are crucial for avoiding small segment residues and accelerating the homozygous process in higher generations. Summary of the Invention

[0005] To address the problem of the inability to quantitatively assess the distribution of non-recovery chromosome fragments, this invention provides a method for quantifying the non-recovery chromosome fragments in the genetic background of backcross breeding, quantifying the distribution of non-recovery chromosomes in backcross individual plants; and provides conditions for constructing a dual-track decision-making model based on the background recovery rate of recovered chromosome fragments and the distribution index of non-recovery fragments, specifically including:

[0006] Calculate the maximum and minimum number of non-reverted chromosome segments in all individual chromosomes of the backcross population;

[0007] The first parameter is calculated based on the number, maximum, and minimum values ​​of unrecovered segments of chromosomes from backcrossed single plants;

[0008] The proportion of non-returning chromosome segments in each chromosome of each individual plant is counted, and the average proportion of non-returning chromosome segments in N chromosomes is calculated to obtain the second parameter, where N is a natural number greater than 1.

[0009] The distribution index parameter of unrecovered chromosome fragments is obtained by weighting the first parameter and the second parameter and then summing them.

[0010] Optionally, the calculation process for the first parameter is as follows:

[0011] The first difference is calculated based on the number of unrecovered segments in the chromosomes of the backcrossed individual and the minimum number of unrecovered segments in all chromosomes of the individual; the second difference is calculated based on the maximum and minimum number of unrecovered segments in all chromosomes of the individual.

[0012] The first parameter is obtained based on the ratio of the first difference and the second difference.

[0013] The purpose of this invention is to provide a method for accurate assessment of the genetic background of backcross breeding blocks, comprising:

[0014] S1. Obtain chromosome recovery fragments from backcrossed plants and calculate recovery fragment evaluation parameters, including the genetic background recovery rate of backcrossed plants;

[0015] S2. Calculate the distribution index of unrecovered chromosome segments to quantify the distribution status of unrecovered chromosome segments, which, together with the parameters for assessing recovered segments, constitutes a precise scanning strategy for genetic background assessment.

[0016] The calculation of the genetic background reversion rate of the backcrossed single plant is based on the calculation of the recurrent parental background reversion rate of the polymorphic blocks of the two parents;

[0017] Optionally, the calculation of the genetic background recovery rate of the backcross plant includes: acquiring dotted marker genotype data; integrating the dotted marker genotype data into haplotype blocks (HTPs); determining the recovery status of the haplotype blocks (HTPs); counting the number of HTP blocks that are consistent with the haplotype of the recurrent parent and the total number of blocks after removing deletion HTPs containing non-polymorphic sites and / or deletion sites; and calculating the genetic background recovery rate of the backcross plant based on the ratio of the number of HTP blocks consistent with the haplotype of the recurrent parent to the total number of HTP blocks after removing deletion sites.

[0018] Optionally, the recovery fragment evaluation parameters further include calculating the whole-genome genetic background recovery rate, smoothing whole-genome HTP blocks, merging adjacent blocks with the same recovery status, filtering abnormal fragments, calculating the total length of the smoothed HTP blocks consistent with the recurrent parental haplotype and the total length of the whole-genome HTP blocks; and calculating the whole-genome background recovery rate based on the ratio of the total length of the HTP blocks consistent with the recurrent parental haplotype and the total length of the whole-genome HTP blocks.

[0019] Optionally, the whole genome background recovery rate also includes generating a chromosome recovery visualization map, which is obtained by visualizing the calculated whole genome background recovery rate;

[0020] Optionally, the smaller the value of the non-recovery chromosome segment distribution index, the fewer the number of non-recovery chromosome segments and the better the continuity;

[0021] Optionally, target individual plants are screened based on the evaluation results of the background recovery rate of recurrent parents, the whole genome background recovery rate, and the unrecovered chromosome segments in the parental polymorphic blocks.

[0022] Optionally, the state determination of the HTP block is an HTP block determined by the HTP block background recovery state determination method. The HTP block state includes HTP blocks that are consistent with the recurrent parent haplotype, deletion HTP blocks containing non-polymorphic sites and / or deletion sites, and HTP blocks with interparental polymorphic sites and composed of parental sites.

[0023] The purpose of this invention is to provide a method for determining the background response of HTP blocks, comprising:

[0024] Obtain genotypic data of backcross individuals and parents;

[0025] The genotypes of the backcrossed individuals are compared with the genotypes of the parents and digitally encoded to obtain three coding results: homozygous genotype, heterozygous genotype, and genotype with no difference between the parents or a deletion site.

[0026] The proportions of the three digital codes at the parent polymorphic sites within each HTP block were statistically analyzed.

[0027] The proportions of the three digital codes are compared with a preset threshold. When the proportion of a digital code is greater than the preset threshold, the HTP block is determined to be of the type corresponding to that digital code.

[0028] Optionally, the homozygous genotype at a polymorphic site between the parents that is consistent with the recurrent parent corresponds to the restored type, the heterozygous genotype at a polymorphic site between the parents that is a combination of the parental sites corresponds to the non-restored type, and the genotype at a non-differential site between the parents or the genotype at a deletion site corresponds to the deletion type.

[0029] Optionally, the method further includes calculating the whole genome background recovery rate, obtaining the recovered HTP blocks after smoothing correction, calculating the total length of all HTP blocks and the total length of the recovered HTP blocks, and calculating the whole genome background recovery rate by the ratio of the total length of the recovered HTP blocks to the total length of all HTP blocks;

[0030] Optionally, the whole-genome background recovery rate calculation further includes data preprocessing, merging adjacent HTP blocks with consistent recovery status to obtain corrected HTP blocks, calculating the total length of corrected recoverable HTP blocks, and calculating the whole-genome background recovery rate by the ratio of the total length of recoverable HTP blocks to the total length of all HTP blocks.

[0031] Optionally, the method further includes calculating the background reversion rate based on parental polymorphic HTP, obtaining parental polymorphic reverting HTP blocks, missing HTP blocks, and total parental polymorphic HTP blocks, calculating the difference between the total HTP blocks and the missing HTP blocks, and then calculating the ratio of the reverting HTP blocks to the difference to obtain the background reversion rate based on parental polymorphic HTP.

[0032] The purpose of this invention is to provide a plant breeding method that uses the above-mentioned method for precise assessment of genetic background in backcross breeding to evaluate the genetic background of the backcross improved population and selects individual plants with a genetic background that is less different from the recipient parent for pollination or protection.

[0033] The purpose of this invention is to provide a computer program product comprising a computer program or instructions, wherein the computer program or instructions are executed by a processor to implement the above-described method for quantifying the unrecovered chromosome segments of the genetic background in backcross breeding, or to implement the above-described method for accurate assessment of the genetic background of backcross breeding blocks, or to implement the above-described method for determining the background recovery of HTP blocks, or to implement the above-described plant breeding method.

[0034] The purpose of this invention is to provide a computer device comprising a memory, a processor, and a computer program or instructions stored in the memory. The computer program or instructions are executed by the processor to implement the above-described method for quantifying the unrecovered chromosome segments of the genetic background in backcross breeding, or to implement the above-described method for accurate assessment of the genetic background of backcross breeding blocks, or to implement the above-described method for determining the background recovery of HTP blocks, or to implement the above-described plant breeding method.

[0035] The purpose of this invention is to provide a computer-readable storage medium storing a computer program or instructions, wherein the computer program or instructions are executed by a processor to implement the above-described method for quantifying the unrecovered chromosome segments of the genetic background in backcross breeding, or to implement the above-described method for accurate assessment of the block-based genetic background in backcross breeding, or to implement the above-described method for determining the background recovery of HTP blocks, or to implement the above-described plant breeding method.

[0036] Advantages of this invention:

[0037] 1. This invention proposes the Non-Recovery Chromosome Segment Distribution Index (CFDI). The CFDI parameter is the first to achieve a quantitative assessment of the distribution characteristics of non-recovery segments, effectively identifying and avoiding the risk of scattered small fragments remaining. Secondly, it avoids the misjudgment of "false recovery": through chromosome-level structural analysis, it accurately distinguishes between truly genetically pure single plants and "trap" materials with only high BRR values.

[0038] 2. This invention proposes a dual-track decision model (BRR+CFDI) to ensure that the selected individual plants perform stably in subsequent generations, significantly improving the breeding success rate and enhancing the predictability of selection.

[0039] 3. This invention proposes a method for determining HTP background recovery. Through a standardized HTP analysis process, single plants with a background recovery rate >90% and excellent genetic structure can be stably screened out in the BC2 generation, achieving early and precise screening. The traditional backcross breeding process requires 6-8 generations, which is shortened to 3-4 generations. Combined with rapid breeding technology, homozygous improved lines can be obtained within 1-1.5 years, significantly shortening the breeding cycle. Through precise selection, the population size required for each generation is effectively reduced, saving field trial and management costs. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a schematic flowchart of a method for quantifying unrestored chromosome fragments in backcross breeding genetic background according to an embodiment of the present invention;

[0042] Figure 2 This is a schematic diagram of the background response determination method for HTP blocks provided in an embodiment of the present invention;

[0043] Figure 3 This is a schematic diagram of the HTP block background response determination system provided in an embodiment of the present invention;

[0044] Figure 4 A schematic diagram of a computer device provided in an embodiment of the present invention;

[0045] Figure 5 A flowchart of the G2H strategy provided in an embodiment of the present invention;

[0046] Figure 6 Genetic background assessment in the BC1 population using the G2H strategy provided in this embodiment of the invention;

[0047] Figure 7 Genetic background assessment of the G2H strategy provided in this embodiment of the invention in the BC2 population. Detailed Implementation

[0048] To enable those skilled in the art to better understand the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0049] In some of the processes described in the specification, claims, and accompanying drawings of this invention, multiple operations appearing in a specific order are included. However, it should be clearly understood that these operations may not be executed in the order they appear herein, or may be executed in parallel. The operation numbers, such as S101, S102, etc., are merely used to distinguish different operations and do not represent any execution order. Furthermore, these processes may include more or fewer operations, and these operations may be executed sequentially or in parallel. It should be noted that the descriptions such as "first," "second," etc., in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit "first" and "second" to different types.

[0050] Figure 1 A schematic diagram of the method for quantifying non-reverting chromosome segments in backcross breeding genetic background provided in this embodiment of the invention is shown, specifically including:

[0051] Obtain the chromosome recovery status of individual plants in the target backcross population;

[0052] In one embodiment, the individual plants in the target backcross population are either the first offspring obtained by crossing the recurrent parent with the F1 hybrid combination of the two parents, or the second offspring obtained by continuously crossing the recurrent parent with the first offspring.

[0053] S101: Calculate the maximum and minimum number of non-repairing segments in the chromosomes of all individual plants in the backcross population;

[0054] In one embodiment, the number of unreply fragments is obtained by the HTP block background response determination method, wherein the proportion of unreply fragments in the HTP block is determined by digital encoding to obtain the number of unreply fragments.

[0055] S102: The first parameter is calculated based on the number, maximum and minimum values ​​of unrecovered segments of chromosomes from backcrossed single plants;

[0056] In one embodiment, the calculation process of the first parameter is as follows:

[0057] The first difference is calculated based on the number of unrecovered segments in the chromosomes of the backcrossed individual and the minimum number of unrecovered segments in all chromosomes of the individual; the second difference is calculated based on the maximum and minimum number of unrecovered segments in all chromosomes of the individual.

[0058] The first parameter is obtained based on the ratio of the first difference and the second difference.

[0059] S103: Calculate the proportion of non-returning chromosome segments on each chromosome of each individual plant, and calculate the average proportion of non-returning chromosome segments on N chromosomes to obtain the second parameter, where N is a natural number greater than 1;

[0060] S104: After assigning weights to the first and second parameters, the distribution index parameter of unrecovered chromosome segments is calculated by summing them. This invention provides a method for accurately assessing the genetic background of backcross breeding blocks, including:

[0061] S1. Obtain chromosome recovery fragments from backcrossed plants and calculate recovery fragment evaluation parameters, including the genetic background recovery rate of backcrossed plants;

[0062] In one embodiment, the calculation of the genetic background reversion rate of the backcrossed single plant is based on the calculation of the background reversion rate of the recurrent parents in the polymorphic blocks of the two parents.

[0063] In one embodiment, the calculation of the genetic background recovery rate of the backcross plant includes: acquiring dotted marker genotype data, integrating the dotted marker genotype data into haplotype blocks (HTPs) to determine the recovery status of the haplotype blocks (HTPs), counting the number of HTP blocks that are consistent with the haplotype of the recurrent parent and the total number of blocks after removing deletion HTPs containing non-polymorphic sites and / or deletion sites; and calculating the genetic background recovery rate of the backcross plant based on the ratio of the number of HTP blocks consistent with the haplotype of the recurrent parent to the total number of HTP blocks after removing deletion sites.

[0064] S2. Calculate the distribution index of unrecovered chromosome segments to quantify the distribution status of unrecovered chromosome segments, which, together with the parameters for assessing recovered segments, constitutes a precise scanning strategy for genetic background assessment.

[0065] In one embodiment, the method includes calculating the background recovery rate of recurrent parental lines based on parental polymorphic blocks, obtaining dotted marker genotype data, determining the recovery status of haplotype blocks (HTPs) based on digital encoding, block transformation, threshold determination, and block integration, counting the number of HTP blocks consistent with the recurrent parental haplotype and the total number of blocks after removing deletion HTPs containing non-polymorphic sites and deletion sites; and calculating the genetic background recovery rate of backcrossed single plants by the ratio of the number of HTP blocks consistent with the recurrent parental haplotype to the total number of HTP blocks after removing deletion sites.

[0066] In one embodiment, the recovery fragment evaluation parameters further include calculating the whole-genome genetic background recovery rate, smoothing whole-genome HTP blocks, merging adjacent blocks with the same recovery status, filtering abnormal fragments, calculating the total length of the smoothed HTP blocks consistent with the recurrent parental haplotype and the total length of the whole-genome HTP blocks; and calculating the whole-genome background recovery rate by ratio of the total length of the HTP blocks consistent with the recurrent parental haplotype and the total length of the whole-genome HTP blocks.

[0067] Optionally, the whole genome background recovery rate also includes generating a chromosome recovery visualization map, which is obtained by visualizing the calculated whole genome background recovery rate.

[0068] In one embodiment, the smaller the value of the non-recovery chromosome segment distribution index, the fewer the number of non-recovery chromosome segments and the better the continuity.

[0069] In one embodiment, target single plants are screened based on the evaluation results of the recurrent parental background recovery rate, whole-genome background recovery rate, and unrecovered chromosome segments in the parental polymorphic blocks.

[0070] In one embodiment, dotted marker genotype data is acquired. The dotted marker genotype data is used to obtain haplotype blocks (HTPs) based on digital encoding, block transformation, threshold determination, and block integration. The recovery status of the haplotype blocks is determined, and the number of HTP blocks that are consistent with the haplotype of the recurrent parent and the total number of blocks after removing deletion HTPs containing non-polymorphic sites and deletion sites are counted. The genetic background recovery rate of the backcross plant is calculated by the ratio of the number of HTP blocks consistent with the haplotype of the recurrent parent and the total number of HTP blocks after removing deletion sites.

[0071] In one embodiment, the state determination of the HTP block is an HTP block determined by the HTP block background recovery state determination method. The HTP block state includes HTP blocks that are consistent with the recurrent parent haplotype, deletion HTP blocks containing non-polymorphic sites and / or deletion sites, and HTP blocks with interparental polymorphic sites and composed of parental sites.

[0072] In one embodiment, the HTP block is an HTP block that has been determined by the HTP block background recovery determination method, including:

[0073] Obtain genotypic data of backcross individuals and parents;

[0074] The genotypes of the backcrossed individuals are compared with the genotypes of the parents and digitally encoded to obtain three coding results: homozygous genotype, heterozygous genotype, and genotype with no difference between the parents or a deletion site.

[0075] The proportions of the three digital codes at the parent polymorphic sites within each HTP block were statistically analyzed.

[0076] The proportions of the three digital codes are compared with a preset threshold. When the proportion of a digital code is greater than the preset threshold, the HTP block is determined to be of the type corresponding to that digital code.

[0077] Homozygous genotypes correspond to restored genotypes, heterozygous genotypes correspond to non-restored genotypes, and genotypes with no difference between parents or at deletion sites correspond to deletion genotypes.

[0078] In one embodiment, genotype data of individual plants and their parents in the backcross population are obtained, and a standardized process for determining and transforming chromosome fragment recovery status from point markers to block markers and from genotypes to haplotypes in the backcross population and its parents is established; the ratio of recovered to unrecovered chromosome fragments in the backcross individual plants is calculated to form a precise genetic background assessment parameter system.

[0079] In one specific embodiment, the present invention introduces the Chromosome Fragment Distribution Index (CFDI), which enables the background assessment dimension to shift from "quantity" to "quality".

[0080] Technical principle: Background recovery rate (BRR) only reflects the "quantity" of recoveries, while CFDI is a quantitative indicator that comprehensively calculates the number and size of unrecovered chromosome fragments. The lower the value, the fewer the number of unrecovered chromosome fragments, the larger the fragments, and the more concentrated their distribution.

[0081] The reason for addressing the shortcomings: The CFDI parameter provides breeders with an unprecedented objective benchmark for measuring the "cleanliness" of genetic background. It directly addresses the breeding pain point of "difficulty in removing small fragments," making it possible to systematically screen for ideal individuals with superior genetic structure and easier subsequent purification among individuals with similar BRR. This overcomes the limitation of existing technologies (including the closest, HTP technology), which can only "interpret images" and cannot quantify structural quality.

[0082] In one specific embodiment, a comprehensive evaluation index system is established: the Unrecovered Chromosomal Segment Distribution Index (CFDI) parameter is established, and the calculation formula is as follows:

[0083] N*= (N- N min ) / (N max - N min );

[0084] N: The number of unrecovered fragments in a single sample;

[0085] N max : The maximum number of non-repairing fragments in all individual plants of the backcross population;

[0086] N min The minimum number of non-repairing segments in all individual plants of a backcross population;

[0087] Then, the proportion of non-repairing segments on each chromosome of each individual plant was calculated, and the mean P* of the 10 chromosomes was calculated. The weights for the number and size of non-repairing segments were both set to 0.5. The formula for calculating the comprehensive index is as follows:

[0088] CFDI = (0.5 × N*) + (0.5 × P*);

[0089] The CFDI value ranges from 0 to 1; a smaller value indicates fewer unrecovered chromosome segments and better continuity. A dual-track decision-making model combining WGBR and CFDI is constructed to achieve comprehensive evaluation of individual plants.

[0090] Figure 2 This invention provides a method for determining the background response of an HTP block, comprising:

[0091] Obtain genotypic data of backcross individuals and parents;

[0092] The genotypes of the backcrossed individuals are compared with the genotypes of the parents and digitally encoded to obtain three coding results: homozygous genotype, heterozygous genotype, and genotype with no difference between the parents or a deletion site.

[0093] The proportions of the three digital codes at the parent polymorphic sites within each HTP block were statistically analyzed.

[0094] The proportions of the three digital codes are compared with a preset threshold. When the proportion of a digital code is greater than the preset threshold, the HTP block is determined to be of the type corresponding to that digital code.

[0095] In one embodiment, the proportions of the three digital codes for parental polymorphic sites within each HTP block are statistically analyzed based on genotype data.

[0096] In one embodiment, the homozygous genotype corresponds to the restored type, the heterozygous genotype corresponds to the non-restored type, and the genotypes at indifferent loci in both parents or the genotypes at deletion loci correspond to the deletion type.

[0097] In one embodiment, the method further includes calculating the whole genome background recovery rate, obtaining smoothed corrected reverting HTP blocks and all HTP blocks in the whole genome, calculating the total length of all HTP blocks and the total length of the reverting HTP blocks, and calculating the whole genome background recovery rate by the ratio of the total length of the reverting HTP blocks to the total length of the whole genome HTP blocks.

[0098] In one embodiment, the calculation of the whole-genome background recovery rate further includes data preprocessing, merging adjacent HTP blocks with consistent recovery states to obtain corrected HTP blocks, calculating the total length of the corrected HTP blocks, and calculating the whole-genome background recovery rate by the ratio of the total length of the recoverable HTP blocks to the total length of the corrected HTP blocks.

[0099] In one embodiment, the method further includes calculating the reverting background recovery rate based on parent polymorphic blocks, obtaining parent polymorphic reverting HTP blocks, missing HTP blocks, and total parent polymorphic HTP blocks, calculating the difference between the total HTP blocks and the missing HTP blocks, and then calculating the ratio of the reverting HTP blocks to the difference to obtain the reverting background recovery rate.

[0100] In one specific embodiment, the core of this application lies in constructing a precise assessment and decision-making system for genetic background from "genotype" to "haplotype" (G2H strategy). This strategy systematically solves the deficiencies of existing technologies (especially the closest HTP technology) in standardized determination and chromosome structure quantification through the following three key improvements:

[0101] 1. A standardized "genotype-haplotype" transformation process was established, realizing a qualitative change in the genetic background analysis unit from "point" to "line";

[0102] 2. The Chromosome Fragment Distribution Index (CFDI) was introduced, enabling a shift in background assessment dimensions from "quantity" to "quality";

[0103] 3. A dual-track decision-making model of "BRR+CFDI" was constructed, realizing the upgrade of breeding selection from "experience-dependent" to "model-driven".

[0104] In one specific embodiment, while existing HTP technology divides data into blocks, it does not provide a unified and objective method for determining block background information. This application addresses this issue through a complete calculation process:

[0105] 1. Digital coding: First, the SNP genotypic differences between backcross individuals and their parents are converted into unified digital codes (such as 0 / 1 / 2).

[0106] 2. Block consolidation: Physically adjacent SNPs are merged based on the 6,163 HTP blocks identified in previous studies.

[0107] 3. Thresholding determination: By calculating the proportion of dominant digital codes within a block and setting a verified threshold, each HTP block is objectively determined as "recovery type", "non-recovery type" or "missing type".

[0108] The reason for addressing the shortcomings: This process integrates tens of thousands of discrete and noisy SNP "points" into hundreds of stable and clear haplotype "lines." This fundamentally overcomes the limitation of point markers in tracking continuous chromosome segments and provides a reproducible and standardized data foundation for the entire analysis, resolving the ambiguity in the determination process in closest-to-close techniques.

[0109] In one specific embodiment, this embodiment constructs a complete G2H technical route, the core process of which is as follows: Figure 5 As shown, it specifically includes the following four key steps:

[0110] 1. Data standardization processing;

[0111] Genotyping of test materials (including recurrent parents, donor parents, and backcross populations) was performed using the Maize 6H-60K chip. Quality control analysis was conducted using Axiom Analysis Suite software (DQC > 0.82, QC call rate > 95%). Genotypes of backcross individuals were compared with those of the parents and converted into standardized digital codes.

[0112] "1": A homozygous genotype with a polymorphic locus between the parents and consistent with the recurrent parent;

[0113] "2": A heterozygous genotype consisting of a polymorphic locus between the parents and a combination of loci from both parents;

[0114] "0": Genotype at the indifferent locus of both parents or genotype at the deletion locus;

[0115] 2. HTP block integration and determination;

[0116] In practical backcross breeding, when using MAS technology for background selection, the main focus is on tracking polymorphic sites between parents. Therefore, this strategy is based on the previously established framework of 6,163 seamlessly connected haplotype blocks. The proportion of digitally encoded parental polymorphic sites within each HTP block is statistically analyzed, and a threshold of 0.5 is used to determine the block recovery status.

[0117] If the proportion of numeric codes "1" within a block is greater than 0.5, it is determined to be "reply type" and recorded as 1;

[0118] If the proportion of the numeric code "2" in the block is ≥ 0.5: it is judged as "unresponsive" and recorded as 2;

[0119] Non-polymorphic sites and deletion sites: These are identified as deletions and recorded as 0.

[0120] The percentage of recovered HTP blocks is calculated, which is the recurrent parent background recovery rate (HTBR) based on parent polymorphism HTP, as shown in the following formula:

[0121] HTBR (%) = NS HTP / N HTP × 100%;

[0122] Among them, NS HTP N represents the number of HTP blocks that are identical to the haplotype of the recurrent parent; HTP This represents the total number of HTP blocks in the single plant after removing missing HTPs.

[0123] 3. Data optimization and visualization;

[0124] The CBS algorithm was applied to smooth 6,163 HTP blocks across the entire genome, merging adjacent blocks with consistent recovery states and filtering out abnormal fragments. The genome-wide background recovery rate (WGBR) was calculated based on the corrected HTP blocks, and a chromosome recovery visualization map was generated using the RIdeogram package. The formula is as follows:

[0125] WGBR (%) = LS HTP / L HTP × 100%;

[0126] Among them, LS HTP L represents the total length of the HTP block that is consistent with the recurrent parental haplotype after smoothing; HTP This indicates the total length of 6,163 HTP blocks.

[0127] The background recovery rate parameter HTBR is used for the initial screening of high background recovery plants in each backcross generation, while WGBR is used for the whole-genome genetic background assessment of target plants after initial screening.

[0128] This invention provides a plant breeding method that assesses the genetic background of a backcross improved population based on the aforementioned method for precise assessment of genetic background in backcross breeding blocks, and selects individual plants with a genetic background that is less different from the recipient parent for pollination or protection.

[0129] In one specific embodiment, a dual-track decision-making model of "BRR+CFDI" was constructed, realizing the upgrade of breeding selection from "experience-dependent" to "model-driven".

[0130] Technical principle: This application does not simply replace BRR with CFDI, but combines the two to form a collaborative decision-making model. The preferred selection criterion is: while ensuring a high BRR (e.g., ≥90%), priority is given to selecting individual plants with lower CFDI values.

[0131] The reason for addressing the shortcomings: This model upgrades the traditional single decision logic of "selecting the one with the highest recovery rate" to a comprehensive decision logic of "selecting one with high recovery rate and good chromosome structure." This directly guides breeders to avoid selecting "trap" single plants that have high BRR but severe genome fragmentation, thus paving the way for rapid background purification in subsequent generations in the early generations, fundamentally accelerating the entire backcross breeding process and achieving the goal of precision breeding.

[0132] In one embodiment, the execution process of the BRR+CFDI dual-track decision model is as follows:

[0133] Obtain genotypic data of backcross individuals and parents;

[0134] The genotypes of the backcrossed individuals are compared with the genotypes of the parents and digitally encoded to obtain three coding results: homozygous genotype, heterozygous genotype, and genotype with no difference between the parents or a deletion site.

[0135] The proportions of the three digital codes at the parent polymorphic sites within each HTP block were statistically analyzed.

[0136] The proportions of the three digital codes are compared with a preset threshold. When the proportion of a digital code is greater than the preset threshold, the HTP block is determined to be the type corresponding to that digital code.

[0137] CFDI and BRR (HTBR, WGBR) calculations were performed on HTP blocks whose types had been determined to obtain the assessment results of unrecovered chromosome segments and the genetic background recovery rate;

[0138] Target individuals were selected based on the evaluation results of unrecovered chromosome segments and the genetic background recovery rate.

[0139] Cultivation and planting are carried out using target individual plants.

[0140] In another embodiment, the calculation of CFDI and BRR can also be obtained by labeling using other techniques such as MAS.

[0141] In one specific embodiment, the genetic background assessment of the maize BC1 population:

[0142] This embodiment uses a systematic analysis of the Q1B1 population (BC1) (such as...) Figure 6 As shown in the figure, the advantages of the G2H strategy compared to traditional point marking methods are verified. The specific implementation and results are as follows:

[0143] 1. Consistency verification of evaluation results;

[0144] The background response rate range for the G2H strategy assessment was 52.5%-81.84% (HTBR) and 56.11%-83.21% (WGBR); the range for the traditional point-marking method was 57.39%-83.59%. The overall trends of both methods were highly consistent, with the largest difference being only 2.97% in the response rate of individual Q1B1-58.

[0145] 2. Comparability analysis of screening results;

[0146] The top three strains with the highest background response rates selected by both methods were completely consistent, confirming that the G2H strategy has comparable reliability to traditional methods in selecting individuals with high response rates.

[0147] 3. The advantages of chromosome structure analysis;

[0148] In-depth analysis of the top three single plants with the highest recovery rates revealed the following:

[0149] Single plant Q1B1-86 (highest BRR: 83.21%), CFDI=0.24;

[0150] Single plant Q1B1-72 (BRR: 82.45%), CFDI=0.12;

[0151] Single plant Q1B1-70 (BRR: 81.93%), CFDI=0.42;

[0152] 4. The decision-making value of CFDI parameters;

[0153] In comparisons of individual plants with similar recovery rates:

[0154] The CFDI value of Q1B1-72 (0.12) is better than that of Q1B1-86 (0.24), indicating that its unrepaired fragments are more concentrated, which is more conducive to efficient removal in subsequent generations. Based on the CFDI index, Q1B1-72 is preferred for the next generation backcross.

[0155] In a specific implementation, the G2H strategy was evaluated and validated for its breeding value in the BC2 population, and its breeding value was analyzed.

[0156] This embodiment verifies the practical application effect of the G2H strategy in high-generation backcross breeding by systematically analyzing the genetic background of the Q1B2 population (BC2). Figure 7 (As shown).

[0157] 1. Quantitative assessment of genetic background;

[0158] The genetic background reversion rate of the BC2 population ranged from 87.09% to 97.64%. 81.8% (27 / 33) of the individual plants had a reversion rate exceeding 90%, and the average population reversion rate increased by about 15 percentage points compared to the BC1 generation, demonstrating that early selection based on the G2H strategy effectively accelerated the background homozygosity process.

[0159] 2. Precise tracking of fragment removal effects;

[0160] By comparing the chromosome structure of the BC1 parent (Q1B1-86) and the BC2 offspring:

[0161] Large unrecovered segments on chromosomes 6 and 7 were successfully removed, while small unrecovered segments remained on chromosomes 2, 3, 4, and 9. The number and distribution of unrecovered segments varied significantly among different individuals, confirming that the G2H strategy can accurately track the recovery dynamics of specific chromosomes.

[0162] 3. Verification of multi-dimensional optimization mechanism;

[0163] Among top-performing plants with similar recovery rates, a comprehensive comparison of the total number of unrecovered fragments, average length, and distribution concentration revealed that while some plants had slightly lower overall recovery rates, their unrecovered fragment continuity was stronger. G2H mapping visually identified genetic structures more conducive to subsequent eradication, achieving a decision-making upgrade from "simple numerical comparison" to "structure-function analysis."

[0164] 4. Improved breeding efficiency;

[0165] Traditional methods require purity levels to be achieved in the BC4 generation, but this strategy can achieve this in the BC2 generation. Combined with the selection of single plants using the CFDI index, the breeding cycle is expected to be shortened by another 1-2 generations, providing a technical guarantee for completing the selection of homozygous inbred lines within 1-1.5 years.

[0166] In one specific embodiment, the G2H strategy and its supporting technical solutions proposed in this application have the following significant advantages compared with the prior art:

[0167] 1. Choose a breakthrough in efficiency;

[0168] ① Achieve accurate early screening: Through a standardized HTP analysis process, single plants with a background recovery rate of >90% and excellent genetic structure can be stably screened in the BC2 generation.

[0169] ②Significantly shortens the breeding cycle: Reduces the 6-8 generations required for traditional backcross breeding to 3-4 generations, and combined with rapid breeding technology, homozygous improved lines can be obtained within 1-1.5 years.

[0170] ③ Reduce breeding costs: Through precise selection, the population size required for each generation can be effectively reduced, saving on field trial and management costs.

[0171] 2. Fundamental improvement in assessment accuracy;

[0172] ① Solving the problem of small fragment residue: The CFDI parameter is the first to achieve a quantitative assessment of the distribution characteristics of unrecovered fragments, effectively identifying and avoiding the risk of scattered small fragment residue.

[0173] ② Avoid misjudgment of "false recovery": Through chromosome-level structural analysis, accurately distinguish between single plants with truly pure genetic backgrounds and "trap" materials with only high BRR values.

[0174] ③ Improve selection predictability: The dual-track decision model (BRR+CFDI) ensures that the selected individual plants perform stably in subsequent generations, significantly improving the breeding success rate.

[0175] 3. The systematic establishment of technical standards;

[0176] ① Achieve standardization of the analysis process: For the first time, a complete technical standard for genotype-to-haplotype transformation was established, including digital coding rules, etc.

[0177] ② Ensure reproducibility of results: Standardized operating procedures ensure that consistent analytical results can be obtained by different laboratories and different operators.

[0178] ③ Lower the technical barriers to use: Transform complex genomic analysis into a standardized process that can be processed in batches, making it easier to promote and apply on a large scale in breeding practices.

[0179] 4. Scientific innovation in decision-making basis;

[0180] ① From "experience-dependent" to "data-driven": Provide objective and quantitative selection indicators to reduce reliance on the personal experience of breeders.

[0181] ② Achieve multi-dimensional comprehensive evaluation: Simultaneously consider the recovery rate and chromosome structural quality to provide a comprehensive basis for parent selection.

[0182] 5. The potential for expansion of the technology system;

[0183] It has the potential for cross-crop applications: the technical principles are applicable to other crop species with reference genomes (such as rice, wheat, etc.).

[0184] This technical solution establishes a standardized "genotype-haplotype" background assessment system, innovatively introduces quantitative indicators of chromosome structure, and constructs a scientific multi-dimensional decision-making model. It solves the core problems of low efficiency, insufficient accuracy, and lack of standards in traditional backcross breeding, and provides key technical support for the transformation and upgrading of crop breeding from "experience-based screening" to "precision design".

[0185] The present invention also discloses a computer program product or system, including a computer program that, when executed by a processor, implements the above-described method steps.

[0186] This invention provides a system for quantifying unreverted chromosome segments in the genetic background of backcross breeding, comprising:

[0187] Acquisition module: Acquires the chromosome recovery status of individual plants in the target backcross population;

[0188] Statistics module: Calculates the maximum and minimum number of non-repairing segments on chromosomes of all individuals in the backcross population;

[0189] First calculation module: The first parameter is calculated based on the number, maximum and minimum values ​​of unrecovered segments of chromosomes from backcrossed single plants;

[0190] The second calculation module: Calculates the proportion of non-repair segments on each chromosome of each individual plant, and calculates the average proportion of non-repair segments on N chromosomes to obtain the second parameter, where N is a natural number greater than 1;

[0191] The index module calculates the distribution index of unrecovered chromosome fragments by assigning weights to the first and second parameters and then summing them.

[0192] This invention provides a precise assessment system for the genetic background of backcross breeding blocks, comprising:

[0193] Acquisition module: Acquires chromosome recovery fragments from backcrossed plants, calculates recovery fragment evaluation parameters, including the genetic background recovery rate of backcrossed plants;

[0194] Assessment module: Calculates the distribution index of unrecovered chromosome segments, quantifies the distribution status of unrecovered chromosome segments, and, together with the assessment parameters of recovered segments, constitutes a precise scanning strategy for genetic background assessment.

[0195] Figure 3 The schematic diagram of the HTP block background response determination system provided in this embodiment of the invention specifically includes:

[0196] Acquisition Unit: Acquire genotype data of backcross individuals and parents;

[0197] Encoding unit: The genotype of the backcross individual is compared with the genotype of the parents and digitally encoded to obtain three encoding results: homozygous genotype, heterozygous genotype, and genotype with no difference between the parents or a deletion site.

[0198] Calculation unit: Calculates the proportion of the three digital codes for parent polymorphic sites within each HTP block;

[0199] Judgment Unit: The ratio of the three digital codes is compared with a preset threshold. When the ratio of a digital code is greater than the preset threshold, the HTP block is determined to be the type corresponding to that digital code.

[0200] Figure 4 An embodiment of the present invention provides a schematic diagram of a computer device, specifically including:

[0201] The system includes a memory and a processor; the memory is used to store program instructions; the processor is used to invoke program instructions, which, when executed, are any of the above-described methods for quantifying unrecovered chromosome segments in backcross breeding genetic background, or methods for accurately assessing the genetic background of backcross breeding blocks, or methods for determining the background recovery of HTP blocks, or methods for implementing the above-described plant breeding methods.

[0202] The present invention also discloses a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it performs any of the above-described methods for quantifying unrecovered chromosome segments in backcross breeding genetic background, or performs the above-described method for accurate assessment of backcross breeding block genetic background, or performs the above-described method for determining the background recovery of HTP blocks, or performs the above-described plant breeding method.

[0203] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the systems, devices, and methods disclosed in the several embodiments provided in this application can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for example, the division of units is merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed between each other can be indirect coupling or communication connection through some interfaces, devices, or units, and can be electrical, mechanical, or other forms. The units described as separate components may or may not be physically separate; the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of this embodiment. Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units. Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. This program can be stored in a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0204] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0205] The computer device provided by the present invention has been described in detail above. For those skilled in the art, there will be changes in the specific implementation and application scope based on the ideas of the embodiments of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for precise assessment of the genetic background of backcross breeding blocks, characterized in that, include: S1. Obtain chromosome recovery fragments from backcrossed plants and calculate recovery fragment evaluation parameters, including the genetic background recovery rate of backcrossed plants; S2. Calculate the distribution index of unrecovered chromosome segments to quantify the distribution status of unrecovered chromosome segments, which, together with the recovery segment assessment parameters, constitutes a precise scanning strategy for genetic background assessment. The calculation process for the distribution index of unrecovered chromosome segments is as follows: Calculate the maximum and minimum number of non-reverting chromosome segments in all individual chromosomes of the backcross population; The first parameter is calculated based on the number, maximum, and minimum values ​​of unrecovered segments of chromosomes from backcrossed single plants; The proportion of non-returning chromosome segments in each chromosome of each individual plant is counted, and the average proportion of non-returning chromosome segments in N chromosomes is calculated to obtain the second parameter, where N is a natural number greater than 1. The first and second parameters are weighted and summed to calculate the distribution index parameter of unrecovered chromosome segments.

2. The method for precise assessment of genetic background in backcross breeding blocks according to claim 1, characterized in that, The calculation process for the first parameter is as follows: The first difference is calculated based on the number of unrecovered segments in the chromosomes of the backcrossed individual and the minimum number of unrecovered segments in all chromosomes of the individual; the second difference is calculated based on the maximum and minimum number of unrecovered segments in all chromosomes of the individual. The first parameter is obtained based on the ratio of the first difference and the second difference.

3. The method for precise assessment of genetic background in backcross breeding blocks according to claim 1, characterized in that, The calculation of the genetic background reversion rate of the backcrossed single plant is based on the recurrent parental background reversion rate of the polymorphic blocks of the two parents.

4. The method for precise assessment of genetic background in backcross breeding blocks according to claim 1, characterized in that, The calculation of the genetic background recovery rate of the backcross plant includes: acquiring dotted marker genotype data; integrating the dotted marker genotype data into haplotype blocks (HTPs); determining the recovery status of the haplotype blocks; counting the number of HTP blocks that are consistent with the haplotype of the recurrent parent and the total number of blocks after removing deletion HTPs containing non-polymorphic sites and / or deletion sites; and calculating the genetic background recovery rate of the backcross plant by the ratio of the number of HTP blocks consistent with the haplotype of the recurrent parent to the total number of HTP blocks after removing deletion sites.

5. The method for precise assessment of genetic background in backcross breeding blocks according to claim 1, characterized in that, The recovery fragment evaluation parameters also include the calculation of the whole genome genetic background recovery rate, smoothing the whole genome HTP blocks, merging adjacent blocks with the same recovery status, filtering abnormal fragments, calculating the total length of the smoothed HTP blocks consistent with the recurrent parent haplotype and the total length of the whole genome HTP blocks; the whole genome background recovery rate is obtained by calculating the ratio based on the total length of the HTP blocks consistent with the recurrent parent haplotype and the total length of the whole genome HTP blocks.

6. The method for precise assessment of genetic background in backcross breeding blocks according to claim 5, characterized in that, The whole genome background recovery rate also includes generating a chromosome recovery visualization map, which is obtained by visualizing the calculated whole genome background recovery rate.

7. The method for precise assessment of genetic background in backcross breeding blocks according to claim 1, characterized in that, The smaller the value of the distribution index of unrecovered chromosome segments, the fewer the number of unrecovered chromosome segments and the better the continuity.

8. The method for precise assessment of genetic background in backcross breeding blocks according to claim 4 or 5, characterized in that, The genetic background recovery rate of backcrossed plants is based on the evaluation results of the recurrent parental background recovery rate of the polymorphic blocks of the two parents, the whole genome background recovery rate, and the distribution index of unrecovered chromosome segments, and the target plants are selected comprehensively.

9. The method for precise assessment of genetic background in backcross breeding blocks according to claim 4 or 5, characterized in that, HTP blocks identified by the HTP block background recovery status determination method include HTP blocks that are consistent with the recurrent parent haplotype, deletion HTP blocks containing non-polymorphic sites and / or deletion sites, and HTP blocks containing interparental polymorphic sites and composed of parental sites.

10. The method for precise assessment of genetic background in backcross breeding blocks according to claim 9, characterized in that, The method for determining the background response status of the HTP block: Obtain genotypic data of backcross individuals and parents; The genotypes of the backcrossed individuals are compared with the genotypes of the parents and digitally encoded to obtain three coding results: homozygous genotype, heterozygous genotype, and genotype with no difference between the parents or a deletion site. The proportions of the three digital codes at the parent polymorphic sites within each HTP block were statistically analyzed. The proportions of the three digital codes are compared with a preset threshold. When the proportion of a digital code is greater than the preset threshold, the HTP block is determined to be of the type corresponding to that digital code.

11. The method for precise assessment of genetic background in backcross breeding blocks according to claim 10, characterized in that, Homozygous genotypes with polymorphic loci between parents and consistent with the recurrent parent correspond to the restored type; heterozygous genotypes with polymorphic loci between parents and combinations of loci from both parents correspond to the non-restored type; and genotypes with indifferent loci or deletion loci between parents correspond to the deletion type.

12. The method for precise assessment of genetic background in backcross breeding blocks according to claim 5, characterized in that, The method further includes calculating the whole genome background recovery rate, obtaining the recovered HTP blocks after smoothing correction, calculating the total length of all HTP blocks and the total length of the recovered HTP blocks, and calculating the whole genome background recovery rate by the ratio of the total length of the recovered HTP blocks to the total length of all HTP blocks.

13. The method for precise assessment of genetic background in backcross breeding blocks according to claim 12, characterized in that, The calculation of the whole-genome background recovery rate also includes data preprocessing, merging adjacent HTP blocks with the same recovery status to obtain corrected HTP blocks, calculating the total length of the corrected recoverable HTP blocks, and calculating the whole-genome background recovery rate by the ratio of the total length of the recoverable HTP blocks to the total length of all HTP blocks.

14. The method for precise assessment of genetic background in backcross breeding blocks according to claim 10, characterized in that, The method further includes calculating the background recovery rate based on parental polymorphic HTP, obtaining parental polymorphic recoverable HTP blocks, missing HTP blocks, and total parental polymorphic HTP blocks, calculating the difference between the total HTP blocks and the missing HTP blocks, and then calculating the ratio of the recoverable HTP blocks to the difference to obtain the background recovery rate based on parental polymorphic HTP.

15. A plant breeding method, characterized in that, The genetic background of the backcross breeding block genetic background is evaluated based on the precise evaluation method of backcross breeding block genetic background as described in any one of claims 1-14, and individual plants with small differences in genetic background from the recipient parent are selected for pollination or protection.

16. A computer program product comprising a computer program or instructions, characterized in that, The computer program or instructions are executed by the processor to implement the precise assessment method for backcross breeding block genetic background as described in any one of claims 1-14, or to implement the plant breeding method as described in claim 15.

17. A computer device comprising a memory, a processor, and a computer program or instructions stored in the memory, characterized in that, The computer program or instructions are executed by the processor to implement the precise assessment method for backcross breeding block genetic background as described in any one of claims 1-14, or to implement the plant breeding method as described in claim 15.

18. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, The computer program or instructions are executed by the processor to implement the precise assessment method for backcross breeding block genetic background as described in any one of claims 1-14, or to implement the plant breeding method as described in claim 15.

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