Plant Gene and Trait 2024, Vol.15, No.5, 220-229 http://genbreedpublisher.com/index.php/pgt 222 respectively, and identified 23 MTAs (Barreto et al., 2019). The breeding population study demonstrated the effectiveness of a novel mixed-model framework in identifying consistent markers across multiple years and locations, with 20 markers associated with CY and 12 with SC over two years (Racedo et al., 2016). The Louisiana sugarcane core collection study found high correlations between sucrose traits and identified 56 markers consistent across multiple traits, explaining up to 15% of the phenotypic variation (Fickett et al., 2019). 3.3 Identified genetic markers associated with important traits Several genetic markers have been identified as being associated with key agronomic traits in sugarcane. In the BPSG study, 23 MTAs were identified, including markers for soluble solid content, stalk height, stalk number, stalk weight, and cane yield (Barreto et al., 2019). The breeding population study identified 43, 42, and 41 markers associated with CY across three crop cycles, respectively, and 38, 34, and 47 markers associated with SC (Racedo et al., 2016). The Louisiana sugarcane core collection study identified 56 markers consistent across multiple sucrose traits, which could be used in marker-assisted selection (MAS) for breeding programs (Fickett et al., 2019). Additionally, a study on a diversity panel of polyploid sugarcane identified 217 nonredundant markers and 225 candidate genes associated with yield traits, providing a comprehensive genetic resource for future breeding efforts (Yang et al., 2020). These findings underscore the importance of GWAS in uncovering the genetic basis of yield and agronomic traits in sugarcane, facilitating the development of superior cultivars through marker-assisted selection and genomic prediction. 4 Functional Genomics and Candidate Gene Validation 4.1 Approaches for validating GWAS findings Genome-wide association studies (GWAS) have become a pivotal tool in identifying genetic loci associated with important agronomic traits in sugarcane. However, validating these findings is crucial to ensure their reliability and applicability in breeding programs. One common approach is to replicate the GWAS in different populations or environments to confirm the marker-trait associations (MTAs) (Racedo et al., 2016; Barreto et al., 2019; Fickett et al., 2019). Additionally, integrating GWAS with other genomic tools such as transcriptomics and proteomics can help in identifying candidate genes and understanding their functional roles (Khanbo et al., 2020). For instance, candidate gene association mapping using gene expression data can validate the functional significance of identified loci. 4.2 Role of functional genomics in understanding gene function Functional genomics plays a critical role in elucidating the biological mechanisms underlying the genetic associations identified by GWAS. By studying gene expression patterns, protein interactions, and metabolic pathways, researchers can gain insights into how specific genes influence phenotypic traits. For example, the integration of transcriptome and proteome data with GWAS findings can help in pinpointing the exact genes involved in sucrose metabolism and other yield-related traits in sugarcane (Khanbo et al., 2020). This comprehensive approach not only validates the GWAS findings but also enhances our understanding of the genetic architecture of complex traits (Liu and Yan, 2018). 4.3 Techniques for candidate gene validation Several techniques are employed to validate candidate genes identified through GWAS. Gene editing technologies such as CRISPR/Cas9 allow for precise modifications of target genes to study their effects on phenotypic traits. Overexpression studies, where candidate genes are introduced and expressed at higher levels in model organisms or crop plants, can also provide valuable insights into gene function (Liu and Yan, 2018). Additionally, RNA interference (RNAi) can be used to knock down the expression of candidate genes to observe resultant phenotypic changes. These techniques, combined with traditional breeding methods, can significantly accelerate the validation and utilization of candidate genes in sugarcane improvement programs. 5 Case Study: Detailed Analysis of a Specific GWAS in Sugarcane 5.1 Example: Brazilian Panel of Sugarcane Genotypes (BPSG) study The Brazilian Panel of Sugarcane Genotypes (BPSG) study aimed to dissect the genetic basis of yield traits in sugarcane through a comprehensive genome-wide association study (GWAS). The specific objectives were to
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