Targeted GBS Technology and Precision Agriculture

As the core direction of modern agricultural development, precision agriculture is reshaping the production mode of traditional agriculture through the deep integration of genomics, the Internet of Things, and big data technology. Its core goal is to achieve "input on demand and accurate output", that is, to improve crop yield and quality while minimizing resource consumption and environmental impact. Genotyping technology, as a key tool to analyze crop genetic potential and link genotype and phenotype, directly determines the implementation accuracy of precision agriculture.

Targeted genotyping-by-sequencing (GBS) technology came into being under this background, which broke through the bottleneck of traditional genotyping technology in efficiency, cost, and accuracy by specifically capturing functional regions closely related to agronomic traits (such as disease resistance genes, yield regulation sites, environmental response genes, etc.) in the genome. Compared with the traditional method of genome-wide random sequencing, targeted GBS not only reduces the sequencing cost by more than 40%, but also improves the accuracy of genotype detection to more than 95% by focusing on key genetic regions, which perfectly meets the technical requirements of precision agriculture for "Qualcomm, low cost and high specificity".

The article explores targeted GBS technology, including its compatibility with precision agriculture, application in crop trait dissection and precision breeding, use in agricultural production, as well as the challenges it faces and future development directions.

Compatibility of Targeted GBS in Precision Agriculture

The core of precision agriculture is to achieve high efficiency and sustainability of agricultural production through accurate perception, accurate decision-making, and accurate implementation, and genotyping technology is the key foundation to support this system. Targeted genotyping-by-sequencing, as an upgraded version of traditional GBS technology, significantly improves the efficiency and accuracy of genotyping by specifically capturing target regions (such as functional genes and QTL intervals) in the genome for sequencing, which is highly adapted to the technical requirements of precision agriculture.

From the technical principle, targeted GBS focuses on genome regions directly related to agronomic traits (such as disease resistance genes and yield regulation genes) using probe capture or enzyme digestion enrichment, thus avoiding redundant data caused by random sequencing of the whole genome by traditional GBS. This feature makes the detection efficiency 3-5 times higher than that of traditional GBS, and the sequencing cost is reduced by 40%-60%, which is especially suitable for genotyping of large-scale breeding populations.

For application, the high specificity of targeted GBS enables it to directly meet the core needs of precision agriculture. Precision agriculture emphasizes "on-demand input", while targeted GBS can predict the response characteristics of crops to fertilizers, water, and pesticides by analyzing their genotypes, thus providing a basis for personalized management. By targeted detection of the variation types of maize nitrogen efficient utilization gene ZmNRT1.1B, the planting population can be divided into high, medium, and low nitrogen efficiency types, which are matched with 30%, 20% and 10% nitrogen reduction schemes, respectively, to reduce fertilizer input and maintain stable yield. This precise association of "genotype-phenotype-management measures" is a typical embodiment of the synergy between targeted GBS and precision agriculture.

Steps in GBS library construction (Elshire et al., 2011)

In addition, the technical flexibility of targeted GBS further enhances its adaptability. According to different crops (such as monocotyledons and dicotyledons) and different characters (such as quality and stress resistance), customized analysis can be realized by adjusting the capture area. In rice, we can design a targeting scheme focusing on taste quality genes (Wx, ALK), and in soybean, we can optimize the capture probe for the salt-tolerant gene (GmSALT3). This modular design enables it to quickly respond to the precise breeding needs of different crops and become a bridge between genome research and field management.

Targeted GBS in Precision Dissection of Crop Traits

Accurate analysis of crop traits is the basis of accurate breeding and management, and targeted GBS provides a high-resolution tool for genetic analysis of complex traits by focusing on functional gene regions, especially in the location of quality traits and quantitative traits.

Rapid Gene Verification

In the analysis of quality traits, targeting GBS can achieve efficient identification and typing of target genes. Taking the disease resistance of crops as an example, in the research on the mapping of powdery mildew resistance gene Pm21 of wheat and rice blast resistance gene Pi9, the traditional method needs to screen candidate regions through genome-wide association study, and then fine mapping, which takes up to 2-3 years. Targeted GBS can complete genotyping and verification within one growing season by directly capturing the chromosome interval where the known disease-resistant genes are located, combined with linkage analysis.

Multi-QTL Mapping in Maize

For quantitative traits (such as yield, quality, and stress resistance), targeted GBS can achieve accurate QTL location and effect analysis by integrating multi-environmental phenotypic data. In the study of maize yield traits, targeted GBS focused on 10 reported yield-related QTL regions, and sequenced 500 natural population materials. Combined with the phenotypic data of more than three years, three major QTLs (explaining phenotypic variation by 15%-20%) and eight minor QTLs were identified, among which the QTL interval on chromosome 4 contained the ZmYABBY15 gene encoding a yield regulatory protein. This accurate analysis not only provides a target for marker-assisted selection but also guides field management.

SNP Kit Development for Drought Tolerance

Targeted GBS is also outstanding in abiotic stress tolerance analysis. In the study of drought tolerance of soybean, 15 known drought tolerance related genes (such as GmDREB1 and GmNCED3) were targeted, and combined with the phenotypic data under drought stress, it was found that a SNP mutation in the promoter region of GmDREB1 was significantly related to the water retention rate of leaves, and the yield loss of varieties carrying this mutation was reduced by 12%-15% under drought conditions. Based on this discovery, the researchers developed a rapid detection kit, which can screen drought-tolerant varieties at the seedling stage and provide accurate guidance for variety layout in arid areas.

Future prospects of next generation sequencing for crop improvement (Sahu et al., 2020)

Targeted GBS-Driven Innovation in Precision Breeding

The core of precision breeding is to realize the precise selection of genotypes, thus shortening the breeding cycle and improving the breeding efficiency. Targeted GBS promotes the transformation of breeding technology from "empirical selection" to "precise design" by providing high-density and high-precision marker information, and initiates a series of innovations in marker-assisted selection, backcross breeding, heterosis prediction, and other fields.

From SSR to High-Density SNPs

In marker-assisted selection (MAS), targeted GBS solves the problems of an insufficient number of traditional markers and low coverage. Taking the improvement of rape fatty acid composition as an example, the FAD2 gene controlling erucic acid content and the GTR gene controlling glucosinolate content are the key targets of breeding. Traditional MAS relies on a few SSR markers, and the selection accuracy is only 60%-70%, while targeted GBS develops 15 closely linked SNP markers by capturing the whole sequence variation of these two genes, which improves the selection accuracy to over 95%. In actual breeding, the F2 population can be detected by targeted GBS, and double low (low erucic acid and low glucosinolate) plants can be screened within 3 months, which is 6 months shorter than the traditional phenotypic identification (waiting for detection after maturity), which significantly speeds up the breeding process.

Genome-wide association studies (GWAS) for identification of functional single nucleotide polymorphisms (SNPs) and development of FMs (Salgotra et al., 2020)

Background Recovery Optimization

In backcross breeding, the background selection function of targeted GBS greatly improves the efficiency of genetic background recovery. In the process of introducing cold-tolerant genes from wild rice into cultivated rice, it takes 6-8 generations for traditional backcross to make the genetic background recovery rate of cultivated species reach 95%, and using targeted GBS to detect the backcross population of each generation-not only monitoring the retention of the target cold-tolerant gene, but also evaluating the recovery ratio of the whole genome background-can achieve 98% background recovery rate within 4 generations, while avoiding the linkage burden near the target gene.

Predicting Genetic Distance Model

Heterosis prediction is an important application of targeted GBS in hybrid breeding. The yield performance of maize hybrids is closely related to the genetic distance between parents. The traditional method to predict heterosis by combining ability measurement is costly and has a long period. Targeted GBS can detect the variation of parents in heterosis group-related genes (such as ZmCCT and ZmKRN2), calculate the genetic distance, and build a prediction model, and the accuracy can reach 75%-80%. In maize breeding in Huang-Huai-Hai region, 200 inbred lines were analyzed by targeted GBS, and three hybrid combinations with strong heterosis were successfully predicted, among which the actual yield of "Zheng 58× Chang 7-2" increased by 18% compared with the control, which verified the value of this technology in the utilization of heterosis.

In addition, targeting GBS promotes the realization of "design breeding". By analyzing the genotype combination of excellent varieties, favorable alleles can be directionally selected. In wheat quality breeding, researchers analyzed the genotype of high-quality variety "Jimai 44" by targeted GBS and found that it carried high gluten gene Glu-D1d, low polyphenol oxidase gene Ppo-D1b, and pre-harvest sprouting resistance gene Vp-1Bc. By directional hybridization, these three genes were polymerized into new breeding materials, and the cultivated new varieties performed well in bread processing quality and stress resistance, realizing the precise improvement of multiple characters.

Construction of breeding populations (Medina-Lozano et al., 2022)

Applications of Targeted GBS in Agricultural Production

Targeted GBS not only serves the breeding process but also directly guides the agricultural production management, realizes the precise allocation of resources by analyzing the genetic characteristics of crops, and plays an important role in the fields of variety layout, pest control, fertilization, and irrigation.

In the regional distribution of varieties, targeted GBS matches ecological adaptability by analyzing genotype characteristics. Taking rice as an example, the variation of photoperiod genes Hd1 and Ehd1 was detected, and "early, middle, and late rice types" were classified, which improved the planting matching of varieties by 20% in the middle and lower reaches of the Yangtze River and reduced the risk of yield reduction.

In terms of pest control, GBS is targeted to detect crop resistance genotypes and guide the differential use of pesticides. For example, by detecting stripe rust resistance genes such as Yr24 and Yr26 in wheat and classifying the resistance levels, the amount of pesticides decreased by 25% and the control efficiency increased by 15% after adopting differentiated control in Gansu Province.

In precision fertilization and irrigation, GBS was targeted to analyze crop nutrition and water response genes. In maize planting, according to the genetic variation classification of ZmNRT1.1 and ZmGS2, different nitrogen fertilizer schemes were implemented, and the utilization rate of nitrogen fertilizer in the Shandong production area was increased by 12%, and the average nitrogen per mu was reduced by 5-8 kg. The irrigation amount was adjusted by detecting the GhbZIP62 gene in the Xinjiang cotton region, and the drought-tolerant varieties saved 18% water.

Challenges and Future Directions of Targeted GBS in Precision Agriculture

At present, the core challenges include: first, the limitations of target area design. Existing targeted GBS rely on known functional genes or QTL information, and it is difficult to design effective capture regions for traits with unknown genetic basis (such as complex metabolic traits), which leads to limited technical application. The second is the contradiction between the cost and popularization.

Target Design Limitations

Although the cost of targeted GBS is lower than that of traditional GBS, probe design and capture experiments still make the cost of a single sample higher than that of simple molecular markers (such as KASP), so it is difficult to be widely used in grassroots agricultural technology popularization. The third is the complexity of data analysis. Targeting GBS data needs to integrate multi-dimensional information such as phenotype and environment, and the existing analytical tools (such as TASSEL and GAPIT) have insufficient functions in multi-group correlation, so it is difficult to meet the in-depth analysis needs of precision agriculture.

In view of these challenges, the future development direction should focus on three aspects:

• First, optimize the target area design with artificial intelligence. A machine learning algorithm is used to integrate massive genome data (such as pan-genome and transcriptome), predict candidate regions with unknown functions, and expand the coverage of targeted GBS.
• Second, develop a low-cost, simple, targeted detection platform. Combining targeted GBS with loop-mediated isothermal amplification (LAMP), portable genotyping in the field can be realized, and the cost of a single sample can be reduced below 10 yuan, which is suitable for basic agricultural technicians.
• Thirdly, construct a multi-omics integrated analysis system. Develop an analysis platform integrating genotype, phenotype, and environmental data to realize the dynamic association of "gene-trait-management".

Multi-Omics Integration

In the long run, the integration of targeted GBS with the Internet of Things and big data will be an important trend. Through the linkage of gene chip and field sensor, the interaction between crop genotype response and environmental stress can be monitored in real time, and the closed loop of "genotype perception-environmental perception-intelligent decision-making" can be realized. In the intelligent greenhouse, tomato disease-resistant genotypes identified by GBS can be linked with disease monitoring sensors, and once the invasion of pathogenic bacteria is detected, targeted biological control measures will be automatically started, so as to realize the real "precision agriculture 2.0".

Precision agriculture technologies overview (Balafoutis et al., 2017)

Conclusion

Targeted GBS technology has become a key link between crop genome research and precision agriculture practice because of its high specificity and high efficiency. From trait analysis to breeding innovation, from production management to resource optimization, its application has penetrated into the whole chain of precision agriculture, providing strong support for the sustainable development of agriculture. Despite the dual challenges of technology and practice, with the innovation of methodology and the integration of multi-disciplines, targeted GBS will surely play a greater role in precision agriculture in the future, and push agricultural production towards a more precise, efficient, and greener direction.

References:

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