Association Mapping of Gene Regions for Drought Tolerance and Agronomic Traits in Sorghum
Abstract
Genetic improvement of sorghum (Sorghum bicolor (L.) Moench) for drought tolerance and grain yield is challenging because of the complex nature of these traits. To make this process more tractable, studies were conducted to investigate the genetic architecture of these traits by employing a novel multi-parent advanced generation intercross (MAGIC) population. The population was formed from 19 founder lines through ten generations of random mating, aided by genetic male sterility (GMS) system. This was followed by seven cycles of self-pollination through single seed descent (SSD) to form 1000 MAGIC lines. Two hundred of these were genotyped using a high throughput genotyping-by-sequencing (GBS) platform. In the first study, genomic structure of the MAGIC population was dissected to depict its potential in breeding and genetic studies. A total of 79,728 SNPs were identified in gene rich regions across the genome. The MAGIC founders showed high genetic diversity, and 73% of their alleles were found to segregate within the MAGIC subset. Structure analyses provided no strong evidence for stratification within the MAGIC population. Linkage disequilibrium (LD) patterns showed the MAGIC subset to be highly recombined, with LD decaying to r 2 ≤ 0.2 at 40kb and down to r2 ≤ 0.1 at 220kb. Three known plant height genes: DWARF1 (Chr.9), DWARF2 (Chr.6) and DWARF3 (Chr.7) were identified through genome-wide association study (GWAS), demonstrating the mapping potential of the MAGIC panel. A second study assessed the magnitude of genotypic (G) variation vis-a-vis the environment (E) and genotype-by-environment interaction (GEI) variances, for drought tolerance and other agronomic traits in the MAGIC population. Post-anthesis drought-like stress was imposed on the MAGIC subset using a foliar spray of a salt desiccant (sodium chlorate). Stress tolerance levels of the MAGIC lines were quantified based on four stress response indices: grain yield reduction (GYR), stress tolerance index (STI), stress susceptibility index (SSI) and mean productivity (MP). In addition, phenotyping for grain yield (GY), days to half bloom (DHB) and plant height (PHT) was conducted across multiple environments. Significant G, E, and GEI were observed among MAGIC genotypes for all drought indices and other agronomic traits. The E component of variance had the highest proportion for all measured traits. GGE-biplot analysis identified adaptable and/or higher-yielding and stable genotypes. The study revealed high genetic variation for drought response and agronomic traits but also showed a significant presence of GEI, suggesting the need for detailed analyses and interpretations beyond the main effects to make the most gain from selection. The final study connected the DNA polymorphism information in the MAGIC population to phenotypic variability through GWAS to identify genomic regions associated with drought tolerance, grain yield (GY), yield stability (YS) and 100 seed weight (HSW). GWAS exposed four candidate genomic regions associated with drought tolerance. These regions harbored fourteen candidate genes, orthologous to genes in Arabidopsis thaliana, maize (Zea may ) and rice (Oryza sativa) with functional annotations depicted in abiotic stress defenses. Additionally, three suggestive association signals each for GY, YS and HSW were detected. The genes proximal to these regions were previously shown by maize transcriptomic analysis to be involved in phytohormone biosynthesis, carbohydrate metabolism, sugar transport and stress defense. The results of this study provide insights into the nature of genetic variations governing drought tolerance and grain yield traits in sorghum. Knowledge gained from GEI dissection may be utilized in breeding programs to select lines with improved yield and drought tolerance. Additionally, the information from the MAGIC panel SNP polymorphisms and candidate gene detection provide research avenues to further refine/narrow down genomic regions associated with these agronomically important traits, and also opens gates for genetic enhancement through genomic aided selections.
Degree
Ph.D.
Advisors
Ejeta, Purdue University.
Subject Area
Agronomy|Genetics|Plant sciences
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