Bioscience Method 2024, Vol.15, No.1, 8-19 http://bioscipublisher.com/index.php/bm 12 Inmaize (Zeamays L.), GWAS has achieved a major breakthrough and successfully identified many genetic loci and potential genes related to complex traits. These traits include responses to abiotic and biotic stresses, and their discovery holds promise for enhancing fitness and yield through effective breeding strategies. In addition, research using GWAS also involves how to use multi-omics methods including genomics, transcriptomics, proteomics, metabolomics, epigenomics and phenomics to deepen the understanding of complex traits of maize. understanding, thereby improving environmental stress tolerance and promoting maize production (Bhat et al., 2021). Haplotype-based models are an important method for GWAS that accurately capture allelic diversity by integrating high-density marker data, improving the ability to discover epistatic interactions and minimizing the need for multiple testing. This method has been developed and applied in major crops such as wheat, rice and soybeans. Compared with traditional single-site models, haplotype-based models are more efficient and reliable in identifying haplotypes associated with selected traits. In China , for example , the National Medium-Term Gene Bank at the Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences (OCRI-CAAS) preserves more than 8,000 sesame germplasm. Similarly, the Beijing National Long-term Gene Bank preserves approximately 4 500 parts of sesame material (Figure 1). Based on these large collections, a strategy to build a core collection of sesame began in the early 2000s using morphological descriptors and later molecular tools. Ultimately, OCRI established a sesame core germplasm bank, containing 705 different accessions, including 405 local varieties, 95 varieties from China, and 205 accessions from 28 other countries. The entire panel in Illumina HiSeq 2 000 (http://www.ncgr.ac.cn/SesameHapMap), a total of 5 were detected in the genome 407 981 SNPs, with an average of 2 SNPs every 50 bp (Figure 1) (Muez et al., 2021). It can be seen that in order to explore the genetic basis of economically important agronomic traits and identify possible causative genes, these developed GWAS panels need to be updated by providing more materials reflecting different agroecological contexts around the world. Figure 1 Process of key steps in Sesame GWAS implementation (Muez et al., 2021) For another example, Nouraei et al. (2024) used the 90KSNP array to conduct genome-wide association analysis and revealed the genetic determinants of key traits related to wheat drought tolerance, namely plant height, root length, and root and shoot dry weight. Using a mixed linear model (MLM) approach to analyze 125 well-watered and drought stress-treated wheat accessions, we identified 53 that were significantly related to the stress sensitivity (SSI) and tolerance index (STI) of the target traits. Related SNPs. Notably, chromosomes 2A and 3B have 10 and 9 relevant markers, respectively. On 17 chromosomes, 44 unique candidate genes were identified, mainly located in the distal ends of chromosomes 1A, 1B, 1D, 2A, 3A, 3B, 4A, 6A, 6B, 7A, 7B and 7D. These genes are involved in multiple functions related to plant growth, development, and stress response, providing a rich resource for future research. Clustering patterns emerged, especially 7 genes related to plant height SSI and 4
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