Molecular Microbiology Research 2024, Vol.14, No.6, 277-289 http://microbescipublisher.com/index.php/mmr 283 SNPs in parental, genetic or natural diversity populations at one time, which greatly improves the research efficiency. For example, a study using whole genome variation data revealed differentiated genes that account for the phenotypic and physiological differences between upland and irrigated rice (Lyu et al., 2014). Additionally, specific regions on chromosome 7 have been linked to traits such as tiller and panicle numbers, root growth angle, and drought response, which are critical for upland adaptation (Uddin and Fukuta, 2020). The use of molecular markers not only aids in understanding the genetic basis of these traits but also facilitates marker-assisted selection (MAS) in breeding programs aimed at developing stress-resistant upland rice varieties (Bernier et al., 2008). Figure 4 A Model for bsr-d1-Mediated Disease Resistance In Digu (bsr-d1), MYBS1 binds to the Bsr-d1 promoter with high affinity, suppressing Bsr-d1 expression; low BSR-D1 levels in turn downregulate expression of downstream genes including two peroxidases, resulting in accumulation of H2O2 and enhanced resistance to M. oryzae. In susceptible rice varieties (Bsr-d1), like LTH, Bsr-d1 is highly expressed, activating specific H2O2 degradation activities, leading to susceptibility (Adopted from Li et al, 2017) 5 Comparative Analysis of Blast Resistance 5.1 Methodologies for comparative genetic studies Comparative genetic studies on blast resistance in rice employ a variety of methodologies to identify and map resistance genes and QTLs. One common approach is the use of QTL mapping, which involves crossing resistant and susceptible rice varieties and analyzing the resulting populations. For instance, an F2 mapping population was developed from a cross between a resistant upland rice genotype UR0803 and a paddy rice susceptible cultivar Lijiang Xintuan Heigu (LTH), leading to the identification of a major QTL for leaf blast resistance on chromosome 11. Another method is bulked segregant analysis (BSA) combined with high-throughput sequencing, which helps in pinpointing candidate regions associated with disease resistance traits (Tan et al., 2022). Genome-wide meta-analyses also play a crucial role in understanding blast resistance. These analyses compile data from multiple studies to map resistance genes and QTLs across the rice genome, providing a comprehensive overview of known resistance loci (Ballini et al., 2008). Additionally, gene-specific markers are used to dissect genetic diversity at significant blast resistance loci, as demonstrated in studies involving Indian rice landraces (Yadav et al., 2019).
RkJQdWJsaXNoZXIy MjQ4ODYzNA==