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Research Detail

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M. Z. Islam
Genetic Resources and Seed Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh,

M. Khalequzzaman
Genetic Resources and Seed Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh,

M. F. R. K. Prince
Genetic Resources and Seed Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh,

M. A. Siddique
Genetic Resources and Seed Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh,

E. S. M. H. Rashid
Genetic Resources and Seed Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh,

M. S. U. Ahmed
Genetic Resources and Seed Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh

B. R. Pittendrigh
Department of Entomology, Michigan State University, East Lansing, MI, United States of America

M. P. Ali
Entomology Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh

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.

  Diversity, Red rice, Germplasm, Bangladesh
  Bangladesh Rice Research Institute in Gazipur, Bangladesh
  00-03-2015
  00-06-2015
  Conservation and Biodiversity
  Rice

The present study set out to characterize the genetic variability, as well as the population structure, using fifty polymorphic SSR markers on fifty red rice germplasm grown at upland conditions in Bangladesh.

Plant materials Rice germplasm, including Aus, Aman and Boro rice cultivated throughout Bangladesh, have been collected and conserved by the Bangladesh Rice Research Institute (BRRI) genebank. To date, approximately 8,200 germplasm have been preserved by the BRRI genebank, of which 1,500 are Aus rice, with more than 30% of those considered red rice. For this study, we cultivated fifty red rice germplasm—collected by BRRI from the sites noted and designated as red due to their red-colored pericarp in upland conditions during the Aus growing season in Bangladesh. Agro-morphological characterization All experiments described here were conducted at the Bangladesh Rice Research Institute in Gazipur, Bangladesh during the March to June Aus rice growing season in 2015. Fifty red rice germplasm were seeded directly under upland conditions in two 5 m x 3 m plot replicated trials. Production practices, including fertilizers, intercultural operations, pest control, and grain harvesting, were conducted according to standard methods. Fifteen agro-morphological traits—leaf area index, culm diameter, effective tiller number, days to flowering, plant height, days to maturity, five panicles weight, filled grains per panicle, unfilled grains per panicle, grain length, grain breadth, 1000 grain weight, length-breadth ratio, and yield per hill—were recorded. Genetic diversity was worked out for the principal component analysis and Mahalanobis’ generalized distance (D2 ) analysis [48]. All multivariate analyses were performed using the GENSTAT 5.5 program. Molecular characterization We used fifty well-distributed SSRs for the diversity analysis; position (cM), repeat motifs, and chromosomal positions for the SSR markers can be found in the rice genome database. Most of these markers were obtained from a panel of fifty standard SSR markers, which has been proposed by CGIAR for rice diversity analysis. DNA was extracted from the young leaves of 14-day-old plants using the miniscale method [51]. The total PCR reaction was performed using the standard procedure. The 10 μL of each PCR product, with 2μL of a loading dye, were analyzed using 8% polyacrylamide gel electrophoresis in a 1 × TBE buffer, run at 75 V for between 2.0–2.5 h depending upon the allele size. The gels were then stained, using ethidium bromide solution (0.5 mg/mL), for 25 min and exposed to UV light using a molecular imager gel documentation unit (XR System, Uvitec Cambridge, France) for visualization. Data analysis The band-size for each of the markers was scored using the AlphaEaseFC 4.0 software. Using PowerMarker version 3.25, summary statistics included the following: the number of alleles, the major allele size and its frequency, gene diversity, and the polymorphism information content (PIC) value. For the unrooted phylogenic tree, the genetic distance was calculated using MEGA 6 based on Nei’s unbiased pairwise. Binary form for allele frequency was prepared using PowerMarker software and used for dendrogram construction by NTSYS-pc software. The unweighted pair grouping method using arithmetic average (UPGMA) was used to determine a similarity matrix following the Dice coefficient with the SAHN subprogram. Population STRUCTURE for germplasm was determined using STRUCTURE, (version 2.3.4). The number of clusters (K) investigated, in this study, ranged from one to fifteen, with five replications for analysis of each K value. The model following admixture and  correlated allele frequency with a 5,000 burn period and a run length of 50,000 were used for conducting model-based structure analysis. Output of analysis was collected using the STRUCTURE harvester [56] and identified 4 as the best K value based on the LnP(D) and Evanno’s ΔK. Principal components analysis (PCA) analysis was conducted also using the STRUCTURE software. In order to summarize the major patterns of variation within the multi-locus dataset, an analysis of molecular variance (AMOVA) using GenAlEx V6.5 was also performed.

  PLoS ONE 13 (5): e0196096. https://doi.org/10.1371/journal. pone.0196096
  PLOS ONE | https://doi.org/10.1371/journal.pone.0196096 May 2, 2018
Funding Source:
1.   Budget:  
  

In general, care should be taken when selecting germplasm for any breeding program attempting yield enhancement. Cluster analysis from the agro-morphological features grouped all the germplasm into five groups. Significant (at both p 0.05 and p 0.01) differences were found in all fifteen agro-morphological traits, which confirms the presence of diversification among the fifty red rice germplasm. From molecular analysis using SSR markers, three groups were found, while population structure analysis showed all tested germplasm constructed as four populations, each significantly differentiated and with their variation confirmed by AMOVA. From the findings of the population structure analysis, in particular, large genetic differences were also observed between two populations (group A and D), suggesting that these could be crossed to improve grain yield. As such, the germplasm, as well as the highly polymorphic SSR markers identified in this study, have the potential to facilitate a red rice breeding program for enhanced yield. Based on these findings, we are currently developing such a program to facilitate more desirable, novel trait-linked markers usable for not only the mapping of QTLs/genes against a diversity of abiotic and biotic stresses but also the breeding of socially and economically desirable traits in red rice. The findings of this study provide a solid foundation for such further work in the effort to increase the yields of this increasingly popular and both medically and nutritively beneficial red rice.

  Journal
  


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