Triticeae Genomics and Genetics, 2024, Vol.15, No.3, 137-151 http://cropscipublisher.com/index.php/tgg 144 5.2.2 Fusarium head blight resistance Fusarium head blight (FHB) is a devastating disease in wheat, with direct negative impacts on grain yield, quality, and market value. Multiple studies have focused on mapping the quantitative trait loci (QTL) associated with FHB resistance. For example, researchers utilized the Canadian wheat cultivar AAC Tenacious to study FHB resistance (Dhariwal et al., 2020). The study found that AAC Tenacious possesses significant disease resistance, mainly due to the presence of two major resistance QTL located on chromosomes 2D and 2DS in its doubled haploid population. These QTL are not only related to FHB resistance but also associated with days to anthesis (DTA) and plant height (PHT) (Figure 3). The results indicate that the resistance genes in AAC Tenacious can be used in breeding FHB-resistant wheat, helping to enhance disease resistance and yield in wheat globally. Another genome-wide association study (GWAS) identified new type II FHB resistance loci on chromosomes 4AL and 5DL, which exhibit high collinearity in gene content and order. These findings are crucial for developing FHB-resistant wheat varieties through marker-assisted selection (Hu et al., 2020). 5.3 Yield improvement High-density genetic mapping has also been utilized to improve yield under drought conditions. Although specific studies on drought tolerance were not provided in the data, the methodologies used in disease resistance mapping can be similarly applied to identify QTLs associated with drought tolerance. The integration of high-density SNP markers allows for the precise identification of loci that contribute to yield stability under water-limited conditions. Improving nutrient use efficiency in wheat is another area where high-density genetic mapping can be beneficial. By identifying QTLs associated with efficient nutrient uptake and utilization, breeders can develop wheat varieties that require fewer inputs while maintaining high yields. The same high-density mapping techniques used for disease resistance and drought tolerance can be applied to this trait, leveraging the power of SNP markers to accelerate breeding programs. 6 Challenges and Limitations 6.1 Technical and analytical challenges 6.1.1 Marker density and coverage High-density genetic maps are essential for precise mapping of quantitative trait loci (QTL) in wheat. However, achieving sufficient marker density and coverage remains a significant challenge. For instance, the development of a high-density genetic linkage map with 6312 SNP and SSR markers was crucial for identifying QTL controlling kernel size and weight (Su et al., 2018). Similarly, a genetic map containing 10,739 loci was used to examine the genetic control of grain protein content and other quality traits (Guo et al., 2020). Despite these advancements, the complexity of the wheat genome, with its large size and polyploid nature, makes it difficult to achieve uniform marker coverage across all chromosomes (Gutierrez-Gonzalez et al., 2019; Ladejobi et al., 2019). 6.1.2 Data management and interpretation The vast amount of data generated from high-density genetic mapping poses significant challenges in data management and interpretation. For example, the use of genotyping-by-sequencing (GBS) derived markers resulted in the construction of maps with thousands of markers, necessitating robust data management systems (Gutierrez-Gonzalez et al., 2019). Additionally, the integration of various data types, such as genomic, epigenetic, and phenomic data, requires sophisticated analytical tools to interpret the results accurately (Borrill et al., 2018). The complexity of the data also makes it challenging to identify and validate candidate genes for marker-assisted selection (Rimbert et al., 2018). 6.2 Biological complexity 6.2.1 Polyploidy in wheat Wheat's polyploid nature adds another layer of complexity to genetic mapping. The presence of multiple sets of homologous chromosomes can lead to complications in marker development and QTL mapping. For instance, the identification of 3.3 million SNPs across the A, B, and D genomes of wheat highlights the challenges posed by polyploidy (Rimbert et al., 2018). Moreover, the genetic diversity and structural variations among the subgenomes further complicate the mapping process (Tyrka et al., 2021). The redundancy of homoeologous genes can mask the effects of individual loci, making it difficult to pinpoint specific genetic factors (Borrill et al., 2018).
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