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Microsatellite and Minisatellite Markers Based DNA Fingerprinting and Genetic Diversity of Blast and Ufra Resistant Genotypes

Md. Abdul Latif
Principal Scientific Officer
Plant Pathology Division, Bangladesh Rice Research Institute, Gazipur-1701, Bangladesh

M. Motiur Rahman
Sher-e-Bangla Agricultural University, Dhaka, Bangladesh

M.R. Bashar Talukdar
Sher-e-Bangla Agricultural University, Dhaka, Bangladesh

Abstract/ Executive Summary:

A total of 78 alleles and 29 loci were detected from nine microsatellite and three minisatellite markers, respectively across 26 blast and ufra disease resistant genotypes. For blast resistant genotypes, the Polymorphic Information Content (PIC) values ranged from 0.280 to 0.726 and RM21 was considered as the best marker. PIC values ranged from 0.5953 to 0.8296 for ufra resistant genotypes and RM23 was the best marker for characterization of ufra resistant genotypes. The genetic similarity analysis using UPGMA clustering generated nine clusters with coefficient of 0.66 for blast resistant genotypes while five genetic clusters with similarity coefficient of 0.42 for ufra resistant genotypes. In order to develop resistant varieties of two major diseases of rice, hybridisation should be made using the parents, BR29 and NJ70507, BR36 and NJ70507 for blast, while BR11 and Aokazi, BR3 and Aokazi, Rayda and BR3 and Rayda and BR11 for ufra.

Keywords: Biodiversity, Microsatellite and minisatellite markers Blast, Ufra diseases r esistant genotypes rice.

Location: Molecular Lab, BRRI

Start Date:

End Date:

Program Area: Variety and Species

Commodity: Rice

Objectives:

To detect genetic diversity of both blast and ufra resistant genotypes.

Methodology:

A total of 14 blast and 12 ufra and resistant genotypes including susceptible cheeks were collected from the gene bank of Bangladesh Rice Research Institute (BRRI) and International Rice Blast Nursery (IRBN), International Network for Genetic Evaluation of Rice (INGER), International Rice Research Institute (IRRI) for this study. Five grams of germinated seed from each genotype was sown in pots. A total of nine microsatellite or SSR markers and three minisatellite or variable number tandem repeats (VNTR) markers with clear amplifications were selected for the variability study of 26 blast and ufra resistant rice genotypes. 2.3. Genotyping protocol Genomic DNA was extracted from young leaves of 3- weeks-old plants following a simple and modified protocol for PCR analysis which did not require liquid nitrogen and required only a very small amount of tissue samples [18]. PCR was performed in 12.5 ml reaction containing 5 to 25 ng of DNA template, 1.25ml of MgCl₂-free 10X PCR buffer (100mM Tris-HCl pH 9.0 at 25 8C, 500mM KCl, 0.1% Triton1 X-100 and H₂O), 1.5ml of 25mMMgCl_2, 0.25ml of 10mM dNTPs, 0.25ml of 5 U/ml Taq polymerase enzyme, 0.625ml each of 10mMforward and reverse primers using an MJ research single 96-well thermal cycler. The mixer was overlaid with a drop of mineral oil to prevent evaporation. After initial denaturation for 5 min at 94 8C, each cycle comprised of 1 min denaturation at 94 8C, 1 min annealing at 55 8C, and 2 min extension at 72 8C with a final extension for 7 min at 72 8C at the end of 35 cycles. The PCR products were mixed with bromophenol blue gel-loading dye and were analysed by electrophoresis on 8% polyacrylamide gel using mini vertical polyacrylamide gels for high throughput manual genotyping (CBS Scientific Co. Inc., CA, USA). PCR amplification products (2.5 ml) were resolved by running gel in 1 x TBE buffer for 2 to 2.5 hrs depending upon the allele size at around 75 V and 180mA current. The gels were stained in 0.5 mg/mL ethidium bromide and were documented using UVPRO (Uvipro Platinum, EU) gel documentation unit. Polymorphism information content (PIC) values were calculated with the following formula. Molecular weight for each amplified allele was measured in base pair using Alpha-EaseFC 5.0 software. The summary statistics including the number of alleles per locus, major allele frequency, gene diversity, PIC values were determined using Power Marker version 3.25 [20]. Genetic distance was calculated using the ‘‘Nei 1983’’ distance. The allele frequency data from Power Marker 3.25 was used to export the data in binary format (allele presence = ‘‘1’’ and allele absence = ‘‘0’’) for analysis with NTSYS-pc version 2.1 [21]. A similarity matrix was calculated with the ‘‘Simqual’’ subprogram using the Dice coefficient, followed by cluster analysis with the SAHN subprogram using the UPGMA clustering method as implemented in NTSYS-pc. The similarity matrix was also used for principal coordinate analysis (PCoA) in same program.

Source of Information: C. R. Biologies 334 (2011) 282–289.

Article Link (Online Journal):

Funding Source:

1. Government

Budget:

Total Budget (Tk.) :

Achievement/Findings:

To better understand the genetic diversity, a total of 26 blast and ufra disease resistant genotypes including susceptible checks were characterized using nine SSR and three VNTR markers. A total of 78 alleles and 29 loci were detected from 26 genotypes. PIC values ranged from 0.280 to 0.726 and 0.5953 to 0.8296 for blast and ufra resistant genotypes, respectively. UPGMA dendrograms showed nine genetic clusters with similarity coefficient of 0.66 for blast resistant genotypes, while five genetic clusters with similarity coefficient of 0.42 for ufra resistant genotypes. To create the variability as well as to develop disease resistant varieties against two major diseases of rice, hybridisation should be made using the parents, BR29 and NJ70507, BR36 and NJ70507 for blast while BR11 and Aokazi, BR3 and Aokazi, Rayda and BR3 and Rayda and BR11 for ufra. Disclosure of interest The authors declare that they have no conflicts of interest concerning this article. Acknowledgements The authors greatly acknowledge the authorities of Bangladesh Rice Research Institute (BRRI) and University Putra Malaysia (UPM) for providing research facilities and financial support.

Knowledge Management: Journal