Diversity and population structure of red rice germplasm in Bangladesh

Abstract

While the functionality and healthy food value of red rice have increased its popularity, such that market demand for it is expected to rise, most strains suffer from low grain yield. To perform diversity and population structure analyses of red rice germplasm, therefore, becomes essential for improving yields for commercial production. In this study, fifty red rice germplasm from the Bangladesh Rice Research Institute (BRRI) genebank were characterized both morphologically and genetically using fifty simple sequence repeat (SSR) markers. Overall, 162 alleles were detected by the markers with the detected allele number varying from two to seven. Additionally, 22 unique alleles were identified for use as a germplasm diagnostic tool. The highest and lowest polymorphic information content (PIC) indices were 0.75 and 0.04 found in markers RM282 and RM304, respectively, and genetic diversity was moderate, varying from 0.05 to 0.78 (average: 0.35). While phylogenetic cluster analysis of the fifteen distance-based agro-morphological traits divided the germplasm into five clusters (I, II, III, IV and V), a similar SSR analysis yielded only three major groups (I, II, and III), and a model-based population structure analysis yielded four (A, B, C and D). Both principal component and neighbors joining tree analysis from the population structure method showed the tested germplasm as highly diverse in structure. Moreover, an analysis of molecular variance (AMOVA), as well as a pairwise FST analysis, both indicated significant differentiation (ranging from 0.108 to 0.207) among all pairs of populations, suggesting that all four population structure groups differed significantly. Populations A and D were the most differentiated from each other by FST. Findings from this study suggest that the diverse germplasm and polymorphic trait-linked SSR markers of red rice are suitable for the detection of economically desirable trait loci/genes for use in future molecular breeding programs.

Genetic Diversity, Population Structure, and Marker-Trait Association for Drought Tolerance in US Rice Germplasm

“…The PIC value with a range of 0.21-0.50 was observed in the US rice in previous studies [8,9]. A lower PIC value indicated the presence of low genetic diversity in US rice germplasm [3,8]. The genetic diversity of japonica subspecies was small compared to its indica counterpart.…”

“…Population structure analysis identified eight subgroups in the US germplasm ( Figure 3). Two to eight subpopulations were reported in earlier studies [3,6,25,26]. The threshold to assign a genotype into a specific subgroup varied from 60 to 80% similarity.…”

“…Identification of rice genotypes with high yield or yield stability under drought stress is an important prerequisite for breeding drought-tolerant varieties. Principal component analysis (PCA) and cluster analysis based on the phenotypic attributes can be used to assess the genetic variability [3]. Plant height, leaf rolling score, grain yield, spikelet fertility, and harvest index are some important traits commonly used for evaluating drought tolerance [4].…”

The Genetic Basis and Nutritional Benefits of Pigmented Rice Grain

“…Therefore, there is an urgent need to validate the traditional knowledge associated with these materials with scientific-based analyses. While the productivity of the landrace materials is undoubtedly lower than that of modern white rice varieties, their market value is potentially quite high, given the growing consumer preference for nutritious foods (Islam et al, 2018). Looking forward, there is a major opportunity for breeding programs to develop productive pigmented varieties (Voss-Fels et al, 2019).…”

Genetic Variability, Character Association and Path Analysis in Boro Rice (Oryza sativa L.) Germplasm from Bangladesh

“…Moreover, knowledge of correlation between yield and its contributing agro-morphological traits are basic requirement to find out guidelines for plant selection. In rice, large amount of genetic variability has been reported (Khatun et al, 2015;Ahmed et al, 2015;Islam et al, 2017;Akter et al, 2018;Islam et al, 2018) which indicates the potential for genetic improvement. Partitioning of total correlation into direct and indirect effect by path analysis helps in making the selection more meaningful way.…”