Deciphering the Genetic Basis of Allelopathy in japonica Rice Cultivated in Temperate Regions Using a Genome-Wide Association Study.

Allelopathy has been considered as a natural method of weed control. Despite the nature of allelochemical compounds has been studied, little is known about the genetic basis underlying allelopathy. However, it is known that rice exhibits diverse allelopathic potentials across varieties, and breeding for rice plants exhibiting allelopathic potential conferring an advantage against weeds in paddy fields would be highly desirable. Knowledge of the gene factors and the identification of the genomic regions responsible for allelopathy would facilitate breeding programs. Taking advantage of the existing genetic diversity in rice, particularly in temperate japonica rice, we conducted a comprehensive investigation into the genetic determinants that contribute to rice allelopathy. Employing Genome-Wide Association Study, we identified four Quantitative Trait Loci, with the most promising loci situated on chromosome 2 and 5. Subsequent inspection of the genes located within these QTLs revealed genes associated with the biosynthesis of secondary metabolites such as Phenylalanine Ammonia Lyase (PAL), a key enzyme in the synthesis of phenolic compounds, and two genes coding for R2R3-type MYB transcription factors. The identification of these two QTLs associated to allelopathy in rice provides a useful tool for further exploration and targeted breeding strategies.

Bioinformatics approach for developing a minimum set of SNP markers for identification of temperate japonica rice varieties cultivated in Spain.

The use of molecular markers for plant variety identification and protection is increasing. For this purpose, SNP markers have provided a reliable and stable tool for plant genotyping. The availability of small and low-cost SNP panels to accelerate the identification of the cultivated rice varieties should be beneficial for breeders, seed certification entities and rice industry. With the intention of providing of such a facility, we first developed a simple and easy-handle bioinformatics tool based on the widely used and freely available software R to generate small sets of SNPs that can discriminate varieties, by selecting markers from a larger genotyping dataset. By applying this algorithm to data from a previously genotyped collection of temperate japonica varieties from different countries, we identified a minimal set of 31 SNPs markers to distinguish 210 varieties. In addition, we used this algorithm to discriminate the 43 most cultivated in Spain rice varieties with minimal sets of 8 SNPs. We then developed and tested 22 Kompetitive Allele-Specific PCR (KASP) assays for the markers included in these panels, and obtained reliable genotype patterns for rice varieties identification. The complete 22 markers panel and the rice genotypes data could offer a useful and low-cost tool for rice breeders and industry to identify varieties and therefore to guarantee the quality of rice. The provided R-based algorithm can be applied to other genomic resources to develop core sets of discriminating markers.