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Allele Mining for Reproductive Stage Salinity Tolerance in Rice (Oryza sativa L.) Using Resources from 3K Rice Genome Project
Dissertation Abstract:
Salinity tolerance in rice is highly desirable to sustain production. Salinity affects rice growth in varying degree at all stages starting from germination through maturation. Excess salt adversely affects all major metabolic activities in rice, and causes overall decline in germination and seedling growth, leading ultimately to reduced growth and diminished grain yield. Therefore, allele mining elite genes within rice landrace is of importance for the improvement of the subset of 3K rice genomes using 438945 single nucleotide polymorphism (SNP) chips to identify significant SNPs associated with salinity tolerance at the reproductive stage. A genome-wide association study (GWAS) was implemented to identify loci controlling salinity tolerance in rice. Genetic association was analyzed with seven physiological traits and six agronomic traits recorded on the tested accessions under glass house condition and phytotron condition at the reproductive stage with electrical conductivity of 10 dSm-1 adjusted using sodium chloride.
The study observed 74 SNP markers significantly associated with the physiological traits and 52 SNP markers with the agronomic traits. GWAS peaks were found representing new (quantitative trait loci) QTLs on all chromosomes, except chromosome 8. Some SNP markers have pleiotropic effects; S1_30033431 was associated with carotenoids and chlorophyll A; S1_40818733 with carotenoids, chlorophyll A, and total chlorophyll; S12_364777754 and S4_128840998 with total chlorophyll, carotenoids, and chlorophyll B; S12_366909144 with total chlorophyll and chlorophyll B; S3_114307755 with carotenoid, chlorophyll A, chlorophyll B, and total chlorophyll; S9_283109263 with total chlorophyll, carotenoids, chlorophyll A, and chlorophyll B; S4_122084694 with number of filled grains per plant and number of unfilled grains per plant; S4_122088019, S4_122097529, and S4_122102971 with number of filled grains per plant, number of unfilled grains per plant and total filled grain weight per plant; and S9_283109263 with number of filled grains per plant and total filled grain weight per plant.
GWAS showed more advantages in increasing the resolution power for mapping QTLs and in detecting more alleles. The genes based SNP array found in the study was beneficial for mining of candidate genes regulating stress tolerance in rice. Candidate genes at the most significant associations are now being identified for further validation and for future use in molecular breeding programs to enhance rice salinity tolerance. Therefore, this study can report important information to the plant breeders in the future to develop salinity tolerant rice varieties at the reproductive stage.