Abstract:
The goals of this research have three main points: (i) to develop a rapid method for inorganic phosphorus quantification, (ii) to investigate spectral reflectance indices representing phosphorus deficiency in rice, and (iii) to determine SNPs associated with phosphorus deficiency tolerance in Thai rice via genome-wide association study (GWAS).
The punching method was developed to enhance the high throughput performance of the conventional Pi extraction and molybdate blue assay. Pi content can be extracted using equally small leaf areas without leaf grinding, balancing, and tedious transferring steps. The punching method provided comparable results to the conventional grinding method with a strong correlation in high and low accumulation rice cultivars under a phosphorus supplement series. Thousands’ Pi content of rice samples can be quantified within a few hours, exactly suited for large-scale phenotyping or screening experiments. P deficiency response of 172 Thai rice (Oryza sativa L.) accessions grown in three different P concentrations. I detected Pi content and spectral reflectance data by using the punching method and hyperspectral measurement, respectively. Pi content showed sensitive evaluation results to identify P deficient level in each different treatment. For hyperspectral analysis, ratio indices between NIR and VIS wavelength showed a strong correlation with Pi content without spectral interference. The 217 ratio indices and Pi content were associated with 113,114 SNPs derived from the whole-exome sequence. The 48 significant SNPs with low P-value were predicted from both R750/R700 and R740/R560. At the same time, Pi content association served 15 significant SNPs, which 3 SNPs of these superimposed from the index association. Interestingly, several known genes involving in P deficiency regulation were found that confirmed correct association affected by the performance of the novel phenotypic traits. Overall, the numerous candidate genes exposed their possibility in P deficiency modulation by considering previous gene expression, QTL mapping, and reported function.
