Genetic Diversity Studies on Selected Rice (Oryza sativa L) Populations Based on Aroma and Cooked Kernel Elongation

Abstract

Rice (Oryza sativa L.) is the main staple food for more than half of the world's population. Improving cooking and eating quality of rice is one of the important objectives of many plant breeding programs. Aroma and cooked kernel elongation are two critical parameters that determine the market value, cooking and eating qualities of rice. The objective of this study was to evaluate the genetic diversity of thirteen (13) Oryza sativa L. populations from Kenyan and Tanzanian. Genetic diversity was determined using 8 simple sequence repeats (SSR) markers. Diversity data was analyzed using POWERMARKER version 3.25 and GENALEX v 6.5 software packages. The number of alleles per locus ranged from 2 to 4 alleles with an average of 3.12 across 8 loci. The polymorphic information content (pic) ranged from 0.2920 (RM 282) to 0.6409 (RM 339) in all loci with an average of 0.4821. Pair-wise genetic dissimilarity coefficients ranged from 0.1125 to 0.9003 with an average of 0.5312. The average gene diversity over all SSR loci for the 13 rice varieties was 0.6036, ranging from 0.3550 to 0.6391. Maximum genetic similarity was observed between Kilombero and Supa, BS 370 and BS 217. Minimum genetic similarity was observed between Kahogo and BS 217. Cluster analysis was used to group varieties by constructing dendrograms based on SSR data and morphological characterization of grains. The dendrogram based on SSR data formed two distinct clusters of the 13 rice varieties. RM 339 and RM 241 were the most informative markers and could be used for differentiating rice varieties from diverse geographical origins. Results obtained from this study demonstrated that use of trait specific SSR markers can be relied upon in diversity studies among diverse and closely related genotypes. RM 339 and RM 241 markers are recommended for use in diversity studies and in quality assurance for grading of rice varieties. Further analysis should be carried out using a larger number of samples and markers to come up a more conclusive report on the discriminating power of microsatellite markers based on rice grain quality traits.

Uniparental Inheritance of Salinity Tolerance and Beneficial Phytochemicals in Rice

“…A total of fifty SSR markers which were reported previously to be involved in growth parameters, yield, pest resistance, and the Saltol QTL (salinity tolerant) [7][8][9][10]12,[31][32][33][34][35][36][37][38][39][40][41][42][43][44][45] were selected to evaluate the differences among genotypes of the recurrent TBR1 and male KD18 cultivars (Supplementary Figure S3). These markers are distributed throughout 12 chromosomes of the rice genome (Supplementary Table S2).…”

Genetic Diversity Studies on Selected Rice (Oryza sativa L.) Genotypes based on Gel Consistency and Alkali Digestion

“…They are popularly known in the determination of the genetic diversity, generating gene map for tagging traits of interest, germplasm conservation and crop improvement [13]. Microsatellites also known as simple sequence repeats (SSR) markers have been applied in various studies to study rice genetic diversity [14][15][16], marker assisted selection [17,18] and in mapping of the QTLs [19,20]. In Kenyan and Tanzanian rice genotypes SSRs have been used to study diversity studies gelatinization temperature and amylose content [15].…”

“…Microsatellites also known as simple sequence repeats (SSR) markers have been applied in various studies to study rice genetic diversity [14][15][16], marker assisted selection [17,18] and in mapping of the QTLs [19,20]. In Kenyan and Tanzanian rice genotypes SSRs have been used to study diversity studies gelatinization temperature and amylose content [15]. This study was carried out using 12 rice genotypes selected on the basis of high farmer preference both in Kenya and Tanzania with inclusion of Philippines varieties as check varieties based on gel consistency and alkali digestion.…”