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1.
Braz. arch. biol. technol ; 59: e16160282, 2016. tab, graf
Article in English | LILACS | ID: biblio-951304

ABSTRACT

ABSTRACT The presence of geneticdiversity is of great importance in improving wheat traits and developing strategies for optimal conservation of germplasm. Genetic diversity was assessed among common wheat cultivars using RAPD (Random Amplified Polymorphic DNA) markers at the Center of Agriculture, Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad. RAPD primers were used among 14 Pakistani wheat cultivars, to screen the progenies and for the identification of the genes of interest. The polymorphic information content (PIC), was measured as the percentage of polymorphic fragments for all primers. A total of 583 bands(84% polymorphic) in all 14 wheat cultivars was amplified and discriminated all the wheat genotypes. The number of fragments amplified per primer ranged from 35 to 69 with an average of 48.52 fragments per primer averagely was observed. Population structure analysis anddandrogram showed distinct clustering among different wheat genotypes. Millat-11, Punjab-11, PBW-222 generated the maximum level of polymorphism, standing alone in the cluster while others are scatteredin different group.As a result, genetically numerous progenies are known, increasing the quality of sorts collections by broadening the genetic base of wheat cultivars. This study additionally indicates that RAPD markers allow quicker response and provide high throughputprocedure of accessions from a variety assortment to assess genetic diversity among wheat genotypes.

2.
Br Biotechnol J ; 2015 8(4): 1-13
Article in English | IMSEAR | ID: sea-174783

ABSTRACT

Aim: This study aimed to uncover the diversity and population structure of 128 sesame genotypes using ISSR markers and identify highly diverse genotypes for the purposes of broadening the genetic base of sesame landraces grown in Ethiopia. Place and Duration of Study: The study was conducted in Botany research laboratory of Kasetsart University, Thailand, from April to July, 2013. Methodology: Genomic DNA of 128 sesame genotypes were subjected to PCR amplification and electrophoresis using seven ISSR markers and a binary data matrix prepared for each primer by scoring clear bands. The data generated were used to calculate the number of total bands (TB), polymorphic bands (PB), polymorphism percentage (P %) and polymorphic information content (PIC) for each locus. The number of different (Na) and effective (Ne) alleles, polymorphic loci (%), Shannon’s information index (I) and Nei’s gene diversity (He) for each population were calculated using GenAlEx 6.5 software. The data were also subjected to analysis of molecular variance (AMOVA) and principal coordinate analysis (PCoA) via distance matrix. Fixation index (Fst) was computed to measure genetic differentiation among populations. Genetic associations among individual genotypes were determined based on dissimilarity matrix using Darwin version 5.0 and a Neighbour-Joining hierarchal tree was constructed based on UPGMA. Results: The 7 ISSR primers in 128 sesame genotypes yielded 96 reproducible amplified bands. The number of amplified bands varied from 7 to 19. Out of 96 bands, 89 (92.2%) were polymorphic. Average number of bands and polymorphic bands per primer were 14 and 12.6 respectively. The polymorphic information content (PIC) value ranged between 0.26 and 0.76, showing the high informativeness of the selected primers. The overall gene diversity and Shannon’s information index were 0.37 and 0.54 respectively. Average dissimilarity value among the genotypes was 0.39. Maximum dissimilarity (0.88) was observed between genotypes Amr-NW6 and Amr-NG9 and less dissimilarity (0.014) was recorded between Amr-NW1 and Amr-NG1. SNNP-7 was the most diverse of all genotypes with highest average dissimilarity value of 0.77. AMOVA showed lower genetic divergence between populations (6%) than within population (94%) with average Fst of 0.061 across populations. The high intra-population variation could be because of large number of genotypes included and due to high out-crossing nature of sesame. Clustering and PCoA analyses clustered the genotypes into individual groups where most of the landraces were grouped in separate clusters irrespective of their geographic origins, while the cultivars were grouped in one cluster, suggesting less variability within the released varieties than the landraces. Accessions no. 56, 73, and 105 were out grouped from the rest. Conclusion: There exist considerable variations among sesame genotypes collected from different geographical regions of Ethiopia. Genotypes Amr-NSh-6, Benishangul-6 and SNNP-7 exhibited a good amount of genetic divergence and hence can be used in crossing program for genetic improvement of sesame in Ethiopia.

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