Method for selecting high-nutrition wheat under assistance of molecular marker

Abstract

The invention provides a molecular marker-assisted selection method for high-nutrition wheat, which comprises the following steps: obtaining grains in a development stage on a wheat plant, and introducing fluorescence resonance energy transfer sensing protein with specific response to a target nutrient into the grains; performing in-vivo imaging on the grains into which the fluorescence resonance energy transfer sensing protein is introduced so as to obtain space-time fluorescence signal data representing the dynamic accumulation process of the target nutrient in the grains; on the basis of the space-time fluorescence signal data, one or more space-time nutrition kinetic parameters of the dynamic accumulation process are calculated; and screening out wheat plants with excellent dynamic accumulation process characteristics by taking space-time nutrition kinetic parameters as a selection basis. By means of non-destructive living body dynamic monitoring, high-throughput and high-precision quantitative evaluation of the nutritional traits of the breeding materials is achieved, and a new technical approach is provided for accelerating breeding of high-nutrition crop varieties.

Description

Technical Field

[0001] This invention relates to the fields of biotechnology and crop genetic improvement, and in particular to a method for selecting high-nutrition wheat using molecular markers. Background Technology

[0002] Developing high-nutritional-value wheat varieties is a crucial way to address the global problem of "hidden hunger" and safeguard human health. Taking wheat as an example, the content of micronutrients such as zinc and iron in its grains directly affects human nutrient intake. Therefore, accurately and efficiently screening germplasm resources with excellent nutrient accumulation capabilities is one of the core objectives of modern crop breeding.

[0003] However, existing breeding screening techniques have inherent limitations in assessing plant nutritional traits. Traditional screening methods heavily rely on the chemical composition analysis of mature seeds, such as atomic absorption spectrometry or inductively coupled plasma mass spectrometry, to determine the final nutrient content. This method is essentially an endpoint detection; while it provides a static cumulative total result, it completely ignores the dynamic processes of nutrients throughout the entire plant growth and development cycle. Key kinetic information such as nutrient absorption, distribution among different tissues, and translocation efficiency under environmental stress is completely obscured. Due to its destructive nature, the tested seeds cannot be used for subsequent propagation, forcing breeders to make inferential selections based on the test results of other seeds from the same plant, which undoubtedly introduces potential errors and reduces the accuracy of selection.

[0004] With the development of molecular biology techniques, although the function of specific genes can be studied by constructing stable transgenic lines, this process is time-consuming and labor-intensive, making it difficult to apply to the rapid screening and functional verification of multiple candidate genes in large-scale breeding populations. Therefore, existing technologies generally lack a non-destructive, high-throughput, and high-precision method for quantifying the nutritional dynamics of living plants. This deficiency means that the breeding process remains a relatively black-box selection process relying on static endpoint data, severely limiting the efficiency and accuracy of breeding high-nutrient crop varieties. Summary of the Invention

[0005] In view of the above problems, the present invention is proposed to provide a method for selecting high-nutrition wheat using molecular markers to overcome or at least partially solve the above problems. This method addresses the issue that existing methods for selecting high-nutrition wheat using molecular markers mainly rely on static DNA markers, whose association with the target trait is easily affected by genetic background and environmental factors, leading to insufficient selection accuracy. Furthermore, this method can directly reflect the actual functional expression and efficiency of genes in a specific genetic background, avoiding the uncertainty of association between traditional static DNA markers and the final trait caused by environmental interactions.

[0006] Specifically, according to one aspect of the present invention, a method for selecting high-nutrition wheat using molecular markers includes the following steps: S1. Obtain wheat grains in the developmental stage from wheat plants, and introduce a fluorescent resonance energy transfer sensing protein that specifically responds to the target nutrient into the grains. S2. Perform in vivo imaging on the seeds in which the fluorescence resonance energy transfer sensing protein is introduced to obtain spatiotemporal fluorescence signal data characterizing the dynamic accumulation process of the target nutrient inside the seeds. S3. Based on the spatiotemporal fluorescence signal data, calculate one or more spatiotemporal nutrient kinetic parameters of the dynamic accumulation process; S4. Using the aforementioned spatiotemporal nutrient kinetic parameters as the selection criteria, wheat plants with excellent dynamic accumulation process characteristics are screened out.

[0007] Preferably, in step S2, performing in vivo imaging on the seeds infused with the fluorescence resonance energy transfer sensing protein to obtain spatiotemporal fluorescence signal data characterizing the dynamic accumulation process of the target nutrient within the seeds includes: S21. The seeds are placed on a microfluidic chip for perfusion culture; S22. Apply standardized environmental stress by altering the composition of the perfusion culture medium; S23. Obtain the spatiotemporal fluorescence signal data of the seeds under stress and after stress relief.

[0008] Preferred options also include: In step S1, a gene silencing element targeting a specific candidate gene is introduced simultaneously with the introduction of the fluorescence resonance energy transfer sensing protein. In step S2, in vivo imaging is performed on the grains in which the fluorescent resonance energy transfer sensing protein and gene silencing element have been introduced to obtain spatiotemporal fluorescence signal data characterizing the dynamic accumulation process of the target nutrient inside the grains. In step S3, based on the spatiotemporal fluorescence signal data of the grains obtained by importing the fluorescence resonance energy transfer sensing protein and the gene silencing element, one or more spatiotemporal nutrient kinetic parameters of the dynamic accumulation process are calculated. In step S4, wheat plants with excellent dynamic accumulation process characteristics are screened out based on the spatiotemporal nutrient kinetic parameters of the grains with and without the introduced gene silencing element.

[0009] Preferred options also include: S5. Genotyping is performed on the wheat plants screened in step S4, and genome-wide association analysis is conducted on the spatiotemporal nutrient kinetic parameters and genotype data to identify molecular markers associated with the dynamic accumulation process.

[0010] Preferably, in step S1, the fluorescence resonance energy transfer sensor protein is introduced into the grain via a viral vector-mediated or Agrobacterium-mediated transient expression method.

[0011] Preferably, the spatiotemporal nutrient dynamics parameters include at least one of the following: peak flux rate, stress resilience index, spatial allocation preference, and accumulation initiation time; The peak flux rate is used to characterize the maximum rate at which the target nutrient accumulates within the grain. The stress resilience index is used to characterize the stability and resilience of the target nutrient accumulation process of the grain when subjected to environmental stress. The spatial allocation preference is used to characterize the distribution ratio of the target nutrient among different tissues within the grain; The accumulation start time is used to characterize the time required for the target nutrient to begin to accumulate significantly within the grain.

[0012] Preferably, the spatiotemporal nutrient kinetic parameter is the peak flux rate; the value of the peak flux rate is determined by the maximum rate of change of the fluorescence signal ratio of the fluorescence resonance energy transfer sensing protein with respect to time. Peak flux rate ; In its formula, The peak or maximum value of a certain quantity represents the maximum response of the system. Operators that represent the maximum value Representation function The change, that is The derivative with respect to time t, Represents minute changes over time. yes The derivative with respect to t represents rate or slope of change over time Preferably, the spatiotemporal nutritional kinetic parameter is the stress resilience index, the value of which is determined by the change in the fluorescence signal ratio of the grain during environmental stress and the recovery rate of the fluorescence signal ratio after the stress is relieved. It can be calculated using the following formula: ; In its formula, The ratio of the maximum signal before coercion. The lowest signal-to-weight ratio during the period of coercion. The signal-to-weight ratio at the end of the observation period. The time when the coercion ends. This is the end time of the observation.

[0013] Preferably, the spatiotemporal nutrient kinetic parameter is a spatial allocation preference degree, and the value of the spatial allocation preference degree is determined by the ratio of the fluorescence signal of the target tissue to the reference tissue inside the grain; It can be determined by the ratio of the average fluorescence signal of the target tissue to the average fluorescence signal of the reference tissue: ; In its formula, and The sets of voxels representing the target tissue and the reference tissue, respectively. and These represent the number of voxels, The ratio of fluorescence signals of each voxel. Indicates the region All points function The sum, Indicates the region All points function The sum of .

[0014] Preferably, the fluorescence resonance energy transfer sensing protein comprises a first fluorescent protein, a second fluorescent protein, and a target nutrient binding domain; the target nutrient binding domain is located between the first and second fluorescent proteins and is capable of specifically binding the target nutrient. The target nutrient binding domain binds to the target nutrient, resulting in an alteration in fluorescence resonance energy transfer efficiency.

[0015] This invention discloses a method for selecting high-nutrient wheat using molecular markers. By employing fluorescence resonance energy transfer sensing proteins and four-dimensional live cell imaging technology, the dynamic accumulation process of nutrients is directly monitored and quantified in living grains. The calculated spatiotemporal nutrient kinetic parameters, such as peak flux rate and spatial allocation preference, are used as selection criteria. This method can directly reflect the actual functional expression and efficiency of genes under specific genetic backgrounds, avoiding the uncertainty of the association between traditional static DNA markers and final traits due to environmental interactions. As a result, the selected plant traits are more stable and reliable.

[0016] Furthermore, in a method for selecting high-nutrition wheat using molecular markers, microfluidic chip technology is used to rapidly and with high throughput simulate standardized environmental stresses under laboratory conditions. The environmental adaptability of plants is evaluated by calculating parameters such as stress resilience index. This method replaces the time-consuming and labor-intensive multi-location and multi-year field trials in traditional breeding, significantly advancing and accelerating the evaluation of environmental adaptability, thereby significantly shortening the breeding cycle of new varieties.

[0017] Furthermore, in a method for selecting high-nutrition wheat using molecular markers, this invention introduces gene silencing elements targeting specific candidate genes simultaneously with the introduction of fluorescence resonance energy transfer sensing proteins. This allows for direct observation of the impact of gene function suppression on the dynamic accumulation of nutrients in a single experiment. This design tightly integrates previously isolated and delayed gene function verification steps with high-throughput breeding screening steps, enabling rapid and in-situ confirmation of candidate gene function and providing a direct decision-making basis for precise molecular design breeding.

[0018] The above and other objects, advantages and features of the present invention will become more apparent to those skilled in the art from the following detailed description of specific embodiments of the invention in conjunction with the accompanying drawings. Attached Figure Description

[0019] The following sections will describe some specific embodiments of the invention in detail by way of example and not limitation, with reference to the accompanying drawings. The same reference numerals in the drawings denote the same or similar parts or portions. Those skilled in the art should understand that these drawings are not necessarily drawn to scale. In the drawings: Figure 1 This is a flowchart illustrating a method for selecting high-nutrient wheat using molecular markers according to an embodiment of the present invention. Figure 2 This is a schematic diagram of step S2 of a method for selecting high-nutrition wheat using molecular markers according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the bifunctional synergistic viral vector construction process in a method for selecting high-nutrition wheat using molecular markers according to an embodiment of the present invention; Figure 4 This is a schematic diagram of a live dynamic screening system in a method for selecting high-nutrition wheat using molecular markers according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the data processing flow in a method for selecting high-nutrition wheat using molecular markers according to an embodiment of the present invention; Figure 6This is a schematic diagram illustrating the application process of a method for selecting high-nutrition wheat using molecular markers according to an embodiment of the present invention. Detailed Implementation

[0020] Obviously, the accompanying drawings described below are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar scenarios based on these drawings without any inventive effort. Furthermore, it is understood that although the efforts made in this development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, any changes to design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as insufficient disclosure of the content of this application.

[0021] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that is mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0022] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may represent singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to such processes, methods, products, or apparatus.

[0023] Figure 1 This is a schematic flowchart of a method for selecting high-nutrient wheat using molecular markers according to an embodiment of the present invention, as shown below. Figure 1 As shown, this embodiment of the invention provides a method for selecting high-nutrient wheat using molecular markers, comprising the following steps: S1. Obtain grains from wheat plants that are in the developmental stage and introduce fluorescent resonance energy transfer sensing proteins that specifically respond to target nutrients into the grains. S2. Perform in vivo imaging on the seeds with introduced fluorescence resonance energy transfer sensing protein to obtain spatiotemporal fluorescence signal data characterizing the dynamic accumulation process of target nutrients inside the seeds. S3. Based on spatiotemporal fluorescence signal data, calculate one or more spatiotemporal nutrient kinetic parameters of the dynamic accumulation process; S4. Using spatiotemporal nutrient kinetic parameters as the selection criteria, wheat plants with excellent dynamic accumulation process characteristics were screened out.

[0024] In this embodiment, the dynamic accumulation process of nutrients in living seeds is directly monitored and quantified, and the dynamic process characteristics are used as the selection criteria, thereby improving the accuracy and efficiency of selection. Specifically, by using fluorescence resonance energy transfer sensing proteins and four-dimensional live cell imaging technology, the dynamic accumulation process of nutrients is directly monitored and quantified in living seeds. The calculated spatiotemporal nutrient kinetic parameters, such as peak flux rate and spatial allocation preference, are used as the selection criteria. This directly reflects the actual functional expression and efficiency of genes under specific genetic backgrounds, avoiding the uncertainty of the association between traditional static DNA markers and final traits due to environmental interactions, thus making the selected plant traits more stable and reliable.

[0025] In some embodiments of the present invention, such as Figure 2 As shown, in step S2, in vivo imaging is performed on the seeds infused with fluorescence resonance energy transfer sensing protein to obtain spatiotemporal fluorescence signal data characterizing the dynamic accumulation process of the target nutrient inside the seed, including: S21. Place the seeds on a microfluidic chip for perfusion culture; S22. Apply standardized environmental stress by altering the composition of the perfusion culture medium; S23. Obtain spatiotemporal fluorescence signal data of grains under stress and after stress relief.

[0026] Specifically, the seeds are placed on a microfluidic chip for perfusion culture, and standardized environmental stress is applied by switching the composition of the perfusion culture medium through program control, in order to obtain spatiotemporal fluorescence signal data of the seeds during the stress application, duration, and relief phases. Preferably, the environmental stress includes deficiency or excess of the target nutrient, or water stress.

[0027] In this embodiment, the present invention utilizes microfluidic chip technology to rapidly and with high throughput simulate standardized environmental stress under laboratory conditions, and evaluates the environmental adaptability of plants by calculating parameters such as stress resilience index. This method replaces the time-consuming and labor-intensive multi-location and multi-year field trials in traditional breeding, significantly advancing and accelerating the evaluation of environmental adaptability, thereby significantly shortening the breeding cycle of new varieties.

[0028] In some embodiments of the present invention, a method for selecting high-nutrient wheat using molecular markers further includes: In step S1, a gene silencing element targeting a specific candidate gene is introduced simultaneously with the introduction of the fluorescence resonance energy transfer sensing protein. In step S2, in vivo imaging is performed on the seeds in which fluorescence resonance energy transfer sensing protein and gene silencing element are introduced to obtain spatiotemporal fluorescence signal data characterizing the dynamic accumulation process of target nutrients inside the seeds. In step S3, based on the spatiotemporal fluorescence signal data of the imported fluorescence resonance energy transfer sensing protein and gene silencing element grains, one or more spatiotemporal nutrient kinetic parameters of the dynamic accumulation process are calculated. In step S4, the spatiotemporal nutrient kinetic parameters of the grains with and without gene silencing elements are used as selection criteria to screen wheat plants with excellent dynamic accumulation process characteristics.

[0029] Specifically, in step S1, a gene silencing element targeting a specific candidate gene is introduced simultaneously with the FRET sensing protein. Then, the screening in step S4 is further based on the changes in spatiotemporal nutrient dynamics parameters induced by the gene silencing element, thereby simultaneously verifying the function of the candidate gene.

[0030] In this embodiment, by introducing a gene silencing element targeting a specific candidate gene simultaneously with the introduction of a fluorescence resonance energy transfer sensing protein, the present invention can directly observe the effect of gene function suppression on the dynamic accumulation process of nutrients in the same experiment. This design closely combines the previously isolated and delayed gene function verification steps with high-throughput breeding screening steps, realizing rapid and in-situ confirmation of candidate gene function, and providing a direct decision basis for precise molecular design breeding.

[0031] In some embodiments of the present invention, a method for selecting high-nutrient wheat using molecular markers further includes: S5. Genotyping is performed on the wheat plants screened in step S4, and genome-wide association analysis is conducted on the spatiotemporal nutrient dynamics parameters and genotype data to identify molecular markers associated with the dynamic accumulation process.

[0032] In this embodiment, the wheat plants selected through step S4 are genotyped, and the spatiotemporal nutrient dynamics parameters are used as quantitative traits. A genome-wide association analysis is performed with the genotype data of the wheat plants to identify molecular markers associated with the dynamic accumulation process for subsequent marker-assisted breeding.

[0033] In some embodiments of the present invention, in step S1, the fluorescence resonance energy transfer sensor protein is introduced into the grain through a viral vector-mediated or Agrobacterium-mediated transient expression method to achieve rapid, high-throughput detection of non-transgenic breeding materials.

[0034] In some embodiments of the present invention, such as Figure 2 As shown, the spatiotemporal nutrient dynamics parameters include at least one of the following: peak flux rate, stress resilience index, spatial allocation preference, and accumulation initiation time.

[0035] Peak flux rate is used to characterize the maximum rate at which a target nutrient accumulates within the grain.

[0036] The stress resilience index is used to characterize the stability and resilience of grains during the accumulation of target nutrients when subjected to environmental stress.

[0037] Spatial allocation preference is used to characterize the distribution ratio of target nutrients among different tissues within the grain.

[0038] Accumulation initiation time is used to characterize the time required for a target nutrient to begin to accumulate significantly within the grain.

[0039] In some embodiments of the present invention, the spatiotemporal nutrient kinetic parameter is the peak flux rate; the value of the peak flux rate is determined by the maximum rate of change of the fluorescence signal ratio of the fluorescence resonance energy transfer sensing protein with respect to time. ; In its formula, The peak or maximum value of a quantity, typically representing the maximum response of a system in physics or engineering. The operator representing the maximum value is used to find the maximum value within the content specified in parentheses. Representation function The change, that is The derivative with respect to time t, It represents a small change in time and is commonly used in calculus as the denominator of the derivative. yes The derivative with respect to t represents The rate or slope of change over time.

[0040] In some embodiments of the present invention, the spatiotemporal nutritional kinetic parameter is the stress resilience index. The value of the stress resilience index is determined by the change amplitude of the fluorescence signal ratio of the grain during environmental stress and the recovery rate of the fluorescence signal ratio after the stress is relieved. It can be calculated by the following formula: ; In its formula, The ratio of the maximum signal before coercion. The lowest signal-to-weight ratio during the period of coercion. The signal-to-weight ratio at the end of the observation period. The time when the coercion ends. This is the end time of the observation.

[0041] In some embodiments of the present invention, such as Figure 2 As shown, the spatiotemporal nutrient kinetic parameter is the spatial allocation preference degree, and the value of the spatial allocation preference degree is determined by the ratio of the fluorescence signal of the target tissue to the reference tissue inside the grain. It can be determined by the ratio of the average fluorescence signal of the target tissue to the average fluorescence signal of the reference tissue: ; In its formula, and The sets of voxels representing the target tissue and the reference tissue, respectively. and These represent the number of voxels, The ratio of fluorescence signals of each voxel. Indicates the region All points function The sum, Indicates the region All points function The sum of .

[0042] In some embodiments of the present invention, the fluorescence resonance energy transfer sensing protein comprises a first fluorescent protein, a second fluorescent protein, and a target nutrient binding domain. The target nutrient binding domain is located between the first and second fluorescent proteins and is capable of specifically binding to a target nutrient.

[0043] The target nutrient binding domain binds to the target nutrient, leading to an alteration in fluorescence resonance energy transfer efficiency. Specifically, when the target nutrient binding domain binds to the target nutrient, its conformation changes, causing a change in the distance between the first and second fluorescent proteins, thereby altering the fluorescence resonance energy transfer efficiency.

[0044] Below, we will proceed according to each appendix. Figure 3-6 The following describes further examples of practical applications of the present invention.

[0045] See attached document Figure 3 , Figure 3 This is a schematic diagram illustrating the construction process of a bifunctional synergistic viral vector in a method for selecting high-nutrient wheat using molecular markers according to an embodiment of the present invention. The present invention provides a method for selecting high-nutrient wheat plants, the preparation stage of which may include the following: First, biological materials for subsequent screening experiments were prepared. A population of 200 wheat recombinant inbred lines (RILs) was selected, constructed by crossing a high-zinc-content parent with the main cultivated variety. Simultaneously, based on existing gene function annotation databases and differential expression data from parental transcriptomes, a list of 15 candidate genes related to zinc ion transport and compartmentalization within plants was identified. The nucleic acid sequence information of these genes was publicly available.

[0046] Next, the core functional components for constructing the analysis vector were designed and synthesized. These components include a reporting module and a perturbation module.

[0047] The function of the reporting module is to respond to the target nutrient (in this embodiment, ) The module detects changes in the concentration of fluorescence and generates a detectable fluorescence signal. It contains a gene sequence encoding a fluorescence resonance energy transfer (FRET) sensing protein. The gene sequence encodes: an enhanced cyan fluorescent protein (eCFP) gene sequence, a first flexible adapter gene sequence, a zinc ion binding domain gene sequence, a second flexible adapter gene sequence, and an enhanced yellow fluorescent protein (eYFP) gene sequence. The zinc ion binding domain binds to... The three-dimensional configuration will then change.

[0048] For example, the zinc ion binding domain can be selected from the zinc finger domain derived from human metallothionein or the zinc ion responsive domain derived from Escherichia coli ZntR protein. These domains have high affinity and specificity for binding zinc ions.

[0049] The perturbation module functions to specifically reduce the expression levels of endogenous candidate genes. For each gene in the candidate gene list, an online VIGS design tool is used to design and synthesize a 300bp specific gene silencing fragment sequence without off-target effects within its coding region.

[0050] Next, a bifunctional synergistic viral vector was constructed. This embodiment uses a vector system based on barley stripe mosaic virus (BSMV). Besides the BSMV vector system, other viral vector systems suitable for gramineous plants, such as systems based on wheat dwarf virus (WDV) or barley yellow dwarf virus (BYDV), can also be used as alternative vectors for transient expression in this invention. This system contains three plasmid vectors, each carrying... , and those that have undergone engineering modifications .

[0051] See attached document Figure 3 The gene sequence of the report module was cloned into GatewayLR via recombination reaction. The vector is placed in an expression cassette between the 35S promoter and the Nos terminator to form a screening vector. This screening vector only has FRET signal reporting functionality.

[0052] Simultaneously, the gene sequence of the report module and the gene sequence of the perturbation module targeting specific candidate genes are loaded together into the same [module / system] using multi-fragment recombination cloning technology. Within the vector, the reporter module and the perturbation module are located in different expression cassettes or functional regions, forming a validation vector. Fifteen different validation vectors were constructed for each of the 15 candidate genes.

[0053] Finally, carrying , The plasmid, and the modified plasmid. Plasmids (screening or validation vectors) were transformed into Agrobacterium GV3101 strain. Engineered Agrobacterium strains containing the corresponding plasmids were obtained through culture and used for subsequent transient transformation experiments on wheat grains.

[0054] See attached document Figure 4 , Figure 4 This is a schematic diagram of a live dynamic screening system in a method for selecting high-nutrient wheat using molecular markers according to an embodiment of the present invention. After the preparation of the analytical vector is completed, the method of the present invention further includes a live dynamic screening and perturbation response verification process.

[0055] The process begins with the instantaneous transformation of grain samples. Ten to fifteen days after wheat flowering, several uniformly developed young grains are collected under aseptic conditions from various wheat plants to be screened. The grains will contain… , And the modified After culturing the Agrobacterium strains containing plasmids separately, they were mixed in equal volumes to form an Agrobacterium suspension with a final OD600 of 1.0. Using a microinjector, this suspension was injected through the base of the grains, followed by co-culturing the injected grains at 25°C in the dark for 48 hours to facilitate transient gene expression mediated by the viral vector. Besides microinjection, a vacuum permeation method can also be used, placing the grains in the Agrobacterium suspension and applying a negative pressure of 0.5-0.8 bar for 5-10 minutes to introduce Agrobacterium. The co-culturing temperature can be adjusted between 22-28°C, and the time between 36-72 hours to suit different wheat varieties and specific experimental conditions. For gene function verification, the same procedure is performed using an Agrobacterium suspension containing the corresponding verification vector.

[0056] Next, four-dimensional in vivo imaging was performed under a microfluidic environment. The transiently transformed in vivo seeds were immobilized in the culture chamber of a microfluidic chip made of polydimethylsiloxane (PDMS). The microfluidic chip was connected to a high-precision microinjection pump via tubing, continuously perfusing the seeds with MS basal culture medium at a constant flow rate of 2 μL / min.

[0057] The microfluidic chip carrying the seeds was placed on the stage of a laser confocal microscope. The excitation wavelength of the eCFP channel was set to 405 nm, with an emission light acquisition range of 450-500 nm; the excitation wavelength of the eYFP channel was set to 514 nm, with an emission light acquisition range of 525-580 nm. The aleurone layer and sub-aleurone layer of the seeds were scanned along the Z-axis every 15 minutes, with a layer thickness of 1 μm, for a total of 50 layers, to obtain three-dimensional spatial information. The entire imaging process was continuously observed for 72 hours, thereby obtaining four-dimensional spatiotemporal fluorescence signal data.

[0058] Standardized environmental stresses were applied during the imaging process. In other embodiments of the invention, the type of environmental stress was not limited to zinc deficiency stress, but could also be high salt stress (e.g., adding 150 mM NaCl to MS basal culture medium) or drought stress (e.g., adding 10% polyethylene glycol PEG6000 to MS basal culture medium) to assess the dynamic nutritional response of plants under different abiotic stresses. At the 24-hour mark of imaging, the input of the microfluidic system was switched via program control to change the perfusion medium from MS basal culture medium to zinc-deficient culture medium. The composition of the zinc-deficient culture medium was the same as the basal culture medium, but it did not contain zinc sulfate. After 12 hours of zinc deficiency treatment, the perfusion medium was switched back to MS basal culture medium for recovery culture, and in vivo imaging continued until the 72-hour observation endpoint. This step obtained continuous spatiotemporal fluorescence signal data of the grains during the stress application, duration, and relief phases.

[0059] See attached document Figure 5 , Figure 5 This is a schematic diagram of the data processing flow in a method for selecting high-nutrient wheat using molecular markers according to an embodiment of the present invention. After acquiring four-dimensional spatiotemporal fluorescence signal data, the method of the present invention further includes data processing and quantification steps of spatiotemporal nutrient kinetic parameters. The flow first performs image preprocessing and FRET signal ratio calculation. For the acquired raw four-dimensional image sequence, background subtraction is first performed. Specifically, a cell-free region without autofluorescence is selected in the image as the background region, the average fluorescence intensity within this region is calculated, and this average value is subtracted from the intensity value of each pixel in the entire image. Subsequently, interchannel fluorescence leakage correction is performed to correct the signal deviation caused by partial leakage of the donor fluorescent protein (eCFP) emission spectrum into the acceptor fluorescent protein (eYFP) emission channel. Correction coefficients are used. The FRET signal ratio (R) was determined by imaging control samples expressing only eCFP protein. After background subtraction and leakage correction, the R ratio for each voxel at each time point was calculated. The formula for this ratio is: ; In its formula, and The fluorescence intensities were measured in the YFP and CFP channels after background subtraction, respectively.

[0060] After calculating the FRET signal ratio, spatiotemporal nutrient dynamics parameters are quantified. A deep learning model based on the U-Net structure is used to perform semantic segmentation on bright-field or autofluorescence images of grains, automatically identifying and dividing different tissue regions such as aleurone layer and endosperm, and generating corresponding three-dimensional masks.

[0061] As an alternative to deep learning models, traditional image segmentation algorithms, such as threshold-based methods, can also be used. The algorithm, or a region-growing-based algorithm, combined with manual correction by the operator, is used to divide the tissue regions. This deep learning model was trained on a dataset of 500 labeled seed slice images, achieving a segmentation accuracy of over 95%.

[0062] Based on the calculated FRET signal ratio and tissue region mask, four spatiotemporal trophic dynamics parameters were further calculated: Peak flux rate ( The first derivative of the time series data of the average FRET signal ratio in the aleurone layer region before stress application (0-24 hours) is taken, and its maximum value is... This parameter reflects the plant's maximum net nutrient inflow efficiency under normal conditions.

[0063] Stress resilience index ( This parameter comprehensively assesses the robustness and recovery ability of grains under stress. Its calculation method is as follows: first, determine the maximum signal ratio before stress (…). The lowest signal ratio during stress ( ) and the final signal ratio at the end of the observation ( Then, it is calculated using the ratio of the average recovery rate during the recovery phase to the magnitude of the stress response: ; In its formula, The ratio of the maximum signal before coercion. The lowest signal-to-weight ratio during the period of coercion. The signal-to-weight ratio at the end of the observation period. The time when the coercion ends. This is the end time of the observation.

[0064] Spatial allocation preference ( This parameter quantifies the distribution tendency of nutrients among different tissues. It is calculated by dividing the average FRT signal ratio of all voxels in the aleurone layer region by the average FRET signal ratio of all voxels in the endosperm region at the end of the observation period. For example, it can be determined by the ratio of the average fluorescence signal ratio of the target tissue (e.g., aleurone layer) to the average fluorescence signal ratio of the reference tissue (e.g., endosperm). ; In its formula, and The sets of voxels representing the target tissue and the reference tissue, respectively. and These represent the number of voxels, The ratio of fluorescence signals of each voxel. Indicates the region All points function The sum, Indicates the region All points function The sum of .

[0065] Accumulation start time This parameter reflects the timing of when the grain initiates the efficient nutrient accumulation process. It is calculated by first calculating the mean FRET signal ratio in the aleurone layer region during the initial observation phase (e.g., the first 2 hours). ) and standard deviation ( Then, throughout the entire time series, we search for the first instance where the average FRET signal ratio in the aleurone layer region consistently exceeds a threshold. The point in time that is ) .

[0066] See attached document Figure 6 , Figure 6 This is a schematic diagram illustrating the result application process in a method for selecting high-nutrient wheat using molecular markers according to an embodiment of the present invention. After quantifying the spatiotemporal nutrient kinetic parameters, the method of the present invention further includes a result application step, specifically plant screening and molecular marker development. This process first involves selecting superior individual plants based on dynamic parameters. For each line in the breeding population, four calculated spatiotemporal nutrient kinetic parameters (…) are used… Normalization is performed to eliminate the influence of dimensions. Based on the specific breeding objectives, a weighting coefficient is assigned to each normalized parameter, and a comprehensive selection index (CSl) is calculated through weighted summation. For example, when the breeding objective is to select plants with high efficiency, high resilience, high enrichment, and early initiation, the comprehensive selection index can be defined as a linear combination of the parameters. All lines in the population are ranked according to the calculated comprehensive selection index, and the lines ranking in the top 5% are selected as superior individual plants to enter the subsequent breeding process.

[0067] Simultaneously, this process allows for the concurrent validation of candidate gene functions. For a candidate gene to be validated... Seeds from the same plant were divided into two groups. The first group (control group) underwent transient transformation using a selection vector containing only the FRET sensor protein; the second group (experimental group) used a vector containing both the FRET sensor protein and the target gene. The validation vector for the gene silencing element was transiently transformed. After in vivo imaging and data processing, the spatiotemporal trophic kinetic parameters of the two experimental groups were obtained. An independent samples t-test was performed on each parameter between the two groups. If a certain parameter (e.g., If there is a statistically significant difference between the two groups (e.g., p-value < 0.05), then the candidate gene is identified. The function is directly related to the dynamic process represented by this parameter.

[0068] Finally, this process can be used for the development of novel molecular markers. Spatiotemporal nutritional kinetic parameters of all lines in the population are used as phenotypic data, where each parameter ( Each phenotypic trait is treated as an independent quantitative trait. Genome-wide association analysis (GWAS) is performed on this phenotypic data and the population's whole-genome high-density SNP (single nucleotide polymorphism) genotype data. High-density SNP genotype data can be obtained through simplified genome sequencing (e.g., GBS) or whole-genome resequencing of all individuals in the population. In addition to SNP markers, insertion / deletion (InDel) markers or structural variation (SV) markers can also be used for association analysis. Specifically, a mixed linear model (MLM) is used for association calculations, which can correct for false positive associations caused by population structure and inter-individual kinship. A strict significance threshold is set (e.g., based on a Bonferroni-corrected p-value < 0.01), and SNP sites exceeding this threshold are identified as molecular markers tightly linked to specific spatiotemporal nutrient kinetic parameters. These markers can be directly used for early auxiliary selection in future breeding practices.

[0069] This invention utilizes fluorescence resonance energy transfer sensing proteins and four-dimensional live cell imaging technology to directly monitor and quantify the dynamic accumulation process of nutrients in living seeds. By using calculated spatiotemporal nutrient kinetic parameters such as peak flux rate and spatial allocation preference as selection criteria, it can directly reflect the actual functional expression and efficiency of genes under specific genetic backgrounds. This avoids the uncertainty of the association between traditional static DNA markers and final traits due to environmental interactions, thus making the selected plant traits more stable and reliable.

[0070] Furthermore, this invention utilizes microfluidic chip technology to rapidly and with high throughput simulate standardized environmental stresses under laboratory conditions. It evaluates the environmental adaptability of plants by calculating parameters such as stress resilience index. This method replaces the time-consuming and labor-intensive multi-location and multi-year field trials in traditional breeding, significantly advancing and accelerating the evaluation of environmental adaptability, thereby significantly shortening the breeding cycle of new varieties.

[0071] Finally, by introducing a gene silencing element targeting a specific candidate gene simultaneously with the introduction of a fluorescence resonance energy transfer sensing protein, this invention enables direct observation of the impact of gene function suppression on the dynamic accumulation of nutrients in a single experiment. This design tightly integrates the previously isolated and delayed gene function verification steps with high-throughput breeding screening steps, achieving rapid and in-situ confirmation of candidate gene function and providing a direct decision-making basis for precise molecular design breeding.

[0072] Therefore, those skilled in the art should recognize that although numerous exemplary embodiments of the present invention have been shown and described in detail herein, many other variations or modifications conforming to the principles of the present invention can be directly determined or derived from the disclosure of the present invention without departing from the spirit and scope of the invention. Thus, the scope of the present invention should be understood and construed as covering all such other variations or modifications.

Claims

1. A method for selecting high-nutrient wheat using molecular marker-assisted selection, characterized in that, Includes the following steps: S1. Obtain wheat grains in the developmental stage from wheat plants, and introduce a fluorescent resonance energy transfer sensing protein that specifically responds to the target nutrient into the grains. S2. Perform in vivo imaging on the seeds in which the fluorescence resonance energy transfer sensing protein is introduced to obtain spatiotemporal fluorescence signal data characterizing the dynamic accumulation process of the target nutrient inside the seeds. S3. Based on the spatiotemporal fluorescence signal data, calculate one or more spatiotemporal nutrient kinetic parameters of the dynamic accumulation process; S4. Using the aforementioned spatiotemporal nutrient kinetic parameters as the selection criteria, wheat plants with excellent dynamic accumulation process characteristics are screened out.

2. The method for selecting high-nutrition wheat using molecular markers according to claim 1, characterized in that, In step S2, performing in vivo imaging on the seeds infused with the fluorescence resonance energy transfer sensing protein to obtain spatiotemporal fluorescence signal data characterizing the dynamic accumulation process of the target nutrient within the seeds includes: S21. The seeds are placed on a microfluidic chip for perfusion culture; S22. Apply standardized environmental stress by changing the composition of the perfusion culture medium; S23. Obtain the spatiotemporal fluorescence signal data of the seeds under stress and after stress relief.

3. The method for selecting high-nutrition wheat using molecular markers according to claim 1, characterized in that: Also includes: In step S1, a gene silencing element targeting a specific candidate gene is introduced simultaneously with the introduction of the fluorescence resonance energy transfer sensing protein. In step S2, in vivo imaging is performed on the grains in which the fluorescent resonance energy transfer sensing protein and gene silencing element have been introduced to obtain spatiotemporal fluorescence signal data characterizing the dynamic accumulation process of the target nutrient inside the grains. In step S3, based on the spatiotemporal fluorescence signal data of the grains obtained by importing the fluorescence resonance energy transfer sensing protein and the gene silencing element, one or more spatiotemporal nutrient kinetic parameters of the dynamic accumulation process are calculated. In step S4, wheat plants with excellent dynamic accumulation process characteristics are screened out based on the spatiotemporal nutrient kinetic parameters of the grains with and without the introduced gene silencing element.

4. The method for selecting high-nutrition wheat using molecular markers according to claim 1, characterized in that: Also includes: S5. Genotyping is performed on the wheat plants screened in step S4, and genome-wide association analysis is conducted between the spatiotemporal nutrient dynamics parameters and the genotype data. To identify molecular markers associated with the dynamic accumulation process.

5. The method for selecting high-nutrient wheat using molecular markers according to claim 1, characterized in that: In step S1, the fluorescence resonance energy transfer sensor protein is introduced into the grain via a viral vector-mediated or Agrobacterium-mediated transient expression method.

6. The method for selecting high-nutrition wheat using molecular markers according to claim 1, characterized in that: The spatiotemporal nutrient dynamics parameters include at least one of the following: peak flux rate, stress resilience index, spatial allocation preference, and accumulation initiation time; The peak flux rate is used to characterize the maximum rate at which the target nutrient accumulates within the grain. The stress resilience index is used to characterize the stability and resilience of the target nutrient accumulation process of the grain when subjected to environmental stress. The spatial allocation preference is used to characterize the distribution ratio of the target nutrient among different tissues within the grain; The accumulation start time is used to characterize the time required for the target nutrient to begin to accumulate significantly within the grain.

7. The method for selecting high-nutrition wheat using molecular markers according to claim 6, characterized in that: The spatiotemporal nutrient kinetic parameter is the peak flux rate; the value of the peak flux rate is determined by the maximum rate of change of the fluorescence signal ratio of the fluorescence resonance energy transfer sensing protein with respect to time. Peak flux rate ; In its formula, The peak or maximum value of a certain quantity represents the maximum response of the system. Operators that represent the maximum value Representation function The change, that is The derivative with respect to time t, Represents minute changes over time. yes The derivative with respect to t represents The rate or slope of change over time.

8. The method for selecting high-nutrition wheat using molecular markers according to claim 6, characterized in that, The spatiotemporal nutritional kinetic parameter is the stress resilience index. The value of the stress resilience index is determined by the change amplitude of the fluorescence signal ratio of the grain during environmental stress and the recovery rate of the fluorescence signal ratio after the stress is relieved. It can be calculated by the following formula: ； In its formula, The ratio of the maximum signal before coercion. The lowest signal-to-weight ratio during the period of coercion. The signal-to-weight ratio at the end of the observation period. The time when the coercion ends. This is the end time of the observation.

9. The method for selecting high-nutrition wheat using molecular markers according to claim 6, characterized in that, The spatiotemporal nutrient dynamics parameter is the spatial allocation preference degree, and the value of the spatial allocation preference degree is determined by the ratio of the fluorescence signal of the target tissue to the reference tissue inside the grain. It can be determined by the ratio of the average fluorescence signal of the target tissue to the average fluorescence signal of the reference tissue: ； In its formula, and The sets of voxels representing the target tissue and the reference tissue, respectively. and These represent the number of voxels, The ratio of fluorescence signals of each voxel. Indicates the region All points function The sum, Indicates the region All points function The sum of .

10. The method for selecting high-nutrition wheat using molecular markers according to claim 1, characterized in that, The fluorescence resonance energy transfer sensing protein comprises a first fluorescent protein, a second fluorescent protein, and a target nutrient binding domain; the target nutrient binding domain is located between the first and second fluorescent proteins and can specifically bind the target nutrient. The target nutrient binding domain binds to the target nutrient, resulting in an alteration in fluorescence resonance energy transfer efficiency.

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