Triticeae Genomics and Genetics, 2025, Vol.16, No.6, 245-253 http://cropscipublisher.com/index.php/tgg 245 Research Insight Open Access High-Throughput Phenotyping Coupled with GWAS for Fusarium Head Blight Resistance in Wheat Bing Wang, Xiuhua Liu, Jie Zhang Tropical Microbial Resources Research Center, Cuixi Academy of Biotechnology, Zhuji, 311800, Zhejiang, China Corresponding email: jie.zhang@cuixi.org Triticeae Genomics and Genetics, 2025, Vol.16, No.6 doi: 10.5376/tgg.2025.16.0027 Received: 20 Sep., 2025 Accepted: 30 Oct., 2025 Published: 20 Nov., 2025 Copyright © 2025 Wang et al., This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Wang B., Liu X.H., and Zhang J., 2025, High-throughput phenotyping coupled with GWAS for fusarium head blight resistance in wheat, Triticeae Genomics and Genetics, 16(6): 245-253 (doi: 10.5376/tgg.2025.16.0027) Abstract Fusarium head blight (FHB) of wheat is a fungal disease that seriously affects global wheat yield and food safety. Its resistance breeding has always been limited by inaccurate phenotypic evaluation and low efficiency of resistance gene localization. This study introduced the prevalence mechanism of FHB and the resistance types of wheat, and analyzed the biological basis of its main phenotypic indicators. By constructing a GWAS model based on SNP chips and resequencing data, and conducting joint analysis in combination with multi-dimensional phenotypic information, multiple stably expressed resistance QTLS and candidate genes were identified. It further revealed the regulatory pathways related to the infection, spread and toxin accumulation of scab. In the practical case section, this study reviewed the resistance research practices of representative wheat groups in the United States, China and other places, and verified the application value of combined phenotypic-genotype analysis in the discovery of new resistance resources. This study demonstrates the significant role of high-throughput phenotypes and GWAS integration strategies in enhancing the efficiency of resistance gene mining and phenotypic accuracy, and is expected to achieve new breakthroughs in precise breeding of FHB resistance, providing technical support for ensuring global wheat production security. Keywords Wheat scab; High-throughput phenotype; Genome-wide association analysis (GWAS); Resistant QTL; Candidate gene 1 Introduction Wheat scab (FHB) has long been a headache for breeders, not only because of the yield loss it causes, but also because of the food safety risks it triggers. Fusarium graminearumis the "culprit" of this disease. It causes grains to accumulate a large amount of mycotoxins, such as trichothecene compounds. Contaminated grains may be inedible at all and even affect the health of humans and animals (Song et al., 2025; Wang et al., 2025). If it were merely a decrease in output, the problem might still be manageable, but unfortunately, this disease is very likely to break out. The climate has become increasingly unstable, and coupled with some changes in agricultural management methods, wheat scab has become more frequent and severe in many areas in recent years. Many people think that as long as they find disease-resistant genes, the problem can be solved. But the actual situation is much more complicated. Wheat resistance to scab is a typical quantitative trait regulated by multiple genes, and the contribution of each locus is usually not significant (Syed et al., 2025). What is even more difficult is that there are not many truly stable resistant germplasm resources. Even the resistance genes that have been cloned, such as Fhb1 and Fhb7, cannot be used at will in actual breeding projects. Most commercial varieties still lack resistance. Furthermore, the expression of resistance traits is also complex influenced by the environment, host and pathogenic bacteria, making phenotypic assessment difficult to standardize. This makes large-scale and precise screening extremely challenging (Buerstmayr et al., 2020). Of course, there are still breakthroughs. In recent years, the development of molecular marker technology and the wide application of GWAS have indeed made the identification of resistance sites much more efficient (Jiang et al., 2025). The problem lies in that whether the technological achievements in the laboratory can truly be implemented in the fields still needs to overcome a complete set of adaptation thresholds for the breeding system. Whether it is high-throughput assessment or genomic tools, if they cannot be integrated into the existing processes, they will be difficult to play a substantive role.
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