Genetic diversity analysis of recombinant inbred lines of rice (Oryza sativa L.) using microsatellite markers

Document Type : Research paper

Authors

Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences, University of Guilan, P. O. Box: 41635-1314, Rasht, Iran.

Abstract

Estimation of genetic diversity is an important factor in germplasm conservation and characterization. In rice breeding programs, genetic diversity information on specific regions of genome can be very useful for the application of marker assisted selection (MAS) and for gene mapping. A total of 152 rice lines were considered for breeding programs using microsatellites (SSR) technique. The total number of polymorphic alleles was 206 with an average of 2 alleles per SSR locus. The PIC value for the SSR loci ranged from 0.479 to 0.5 with an average of 0.498. The highest PIC value was observed for primers RM60, RM6832, RM3838 and RM592. RM1, RM237, RM154 and RM84 had the lowest PIC values in a decreasing order. Nei’s gene diversity ranged from 0.479 to 0.5 with an average of 0.498. Using Shannon’s diversity index, a mean genetic diversity of 0.691 was obtained. The lowest diversity was found for RM1, RM237, RM246, RM154 and RM279 in an ascending order and 27 SSR markers had the highest value (0.693). Cluster analysis using the UPGMA method based on Jaccard’s similarity coefficient classified all lines into three clusters. Association analysis by general linear model (GLM) method revealed that 62 SSR markers showed a significant association with 10 studied morphological traits. Twenty eight markers were associated with more than one trait. These may be further investigated in rice breeding programs to be introduced as informative and useful markers. Results showed the potential of SSR markers to identify rice lines at the DNA level. The information will help the selection of lines to serve for efficient rice breeding programs.

Keywords


Allhgholipour M., Farshdfar E., and Rabiei B. (2014). Molecular characterization and genetic diversity analysis of different rice cultivars by microsatellite markers. Genetika, 46: 187-198.
Anandan A., Anumalla M., Pradhan S. K., and Ali J. (2016). Population structure, diversity and trait association analysis in rice (Oryza sativa L.) germplasm for early seedling vigor (ESV) using trait linked SSR markers. Plos One, 11(3): 1-22.
Anderson J. A., Churchill G. A., Autrique J. E., Tannksley S. D., and Sorrells M. E. (1993). Optimizing parental selection for genetic linkage map. Genome, 36: 181-186.
Botstein D., White R. L., Skolnick M., and Davis R. W. (1980). Construction of genetic linkage map in man using Restriction Fragment Length Polymorphisms. American Journal of Human Genetic, 32: 314-331.
Broman K. W. (2005). The genomes of recombinant inbred lines. Genetics, 169: 1133–1146.
Brondani C., Borba T. C. O., Rangel O. P. H. N., and Brondani R. P. V. (2006). Determination of genetic variability of traditional varieties of Brazilian rice using microsatellite markers. Genetics and Molecular Biology, 29: 676-684.
Brondani R. P. V., Zucchi M. I., Brondani C., Rangel P. H. N., Borba T. C. D. O., Rangel P. N., Magalhaes M. R., and Vencovsky R. (2005). Genetic structure of wild rice Oryza glumaepatula populations in three Brazilian biomes using microsatellite markers. Genetica, 125: 115-123. 
DeWoody J. A., Honeycutt R. L., and Skow L. C. (1995). Microsatellite markers in white-tailed deer. Journal of Heredity, 86:317-319. 
Fisher R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 76: 619-922. 
Hassan M. M., Shamsuddin A. K. M., Islam M. M., Khatun K., and Halder J. (2012). Analysis of genetic diversity and population structure of some bangladeshi rice landraces and HYV. Journal of Science Research, 4: 757-767. 
Jeung J. U., Hwang H. G., Moon H. P., and Jena K. K. (2005). Fingerprinting temperate japonica and tropical indica rice genotypes by comparative analysis of DNA markers. Euphytica, 146: 239-251. 
Khush G. S. (2005). What it will take to feed 5.0 billion rice consumers in 2030. Plant Molecular Biology, 59(1): 1–6. 
Kimura M., and Crow J. F. (1964). The number of alleles that can be maintained in a finite population. Genetics, 49: 725-738. 
Kumar P. P., Yau J. C. K., and Goh C. J. (1998). Genetic analysis of Heliconia species and cultivars with randomly amplified polymorphic DNA (RAPD) markers. Journal of American Society Horticulture Science, 123: 91-97. 
Kumar R., Singh A. K., Arun K., and Arun R. (2012). Evaluation of genetic diversity in rice using simple sequence repeats (SSR) markers. African Journal of Biotechnology, 11: 14956-14995. 
Lapitan V. C, Brar D. S., Abe T., and Redona E. D. (2007). Assessment of genetic diversity of Philippine rice cultivars carrying good quality traits using SSR markers. Breeding Science, 57: 263-270. 
Lewontin R. C. (1972). Testing the theory of natural selection. Nature, 236: 181-182.
Nachimuthu V. V., Muthurajan R., Duraialaguraja S., Sivakami R., Pandian B. A., Ponniah G., Gunasekaran K., Swaminathan M., Suji K. K., and Sabariappan R. (2015). Analysis of population structure and genetic diversity in rice germplasm using SSR markers: an initiative towards association mapping of agronomic traits in Oryza Sativa. Rice, 8: 2-24. 
Neeraja C. N., Hariprasad A. S., Malathi S., and Siddiq E. A. (2005). Characterization of tall landraces of rice (Oryza sativa L.) using gene derived simple sequence repeats. Current Science, 88: 149-152. 
Nei M. (1973). Analysis of gene diversity in subdivided populations. PNAS, USA, 70: 3321–3. 
Powell W., Machray G. C., and Provan J. (1996). Polymorphism revealed by simple sequence repeats. Trends in Plant Science, 1: 215–222. 
Rahman M. S., Sohag M. K. H., and Rahman L. (2010). Microsatellite based DNA fingerprinting of 28 local rice (Oryza sativa L.) varieties of Bangladesh. Journal of the Bangladesh Agricultural University, 8: 7–17. 
Rohlf F. (2002). NTSYS-pc: Numerical Taxonomy System, version 2.1 Exeter Publishing. Ltd., Setauket, New York, USA.
Saghai-Maroof M., Soliman K., Jorgensen R., and Allard R. (1984). Ribosomal DNA spacer-length polymorphisms in barley: Mendelian inheritance, chromosomal location, and population dynamics. Proceedings of The National Academy of Sciences of The United States of America, 81: 8014–8018. 
Shahriar M. H., Robin A. H. K., Begumand S. N., and Hoque A. (2014). Diversity analysis of some selected rice genotypes through SSR- based molecular markers. Journal of the Bangladesh Agricultural University, 12: 307–311. 
Silva P. I., Martins A. M., Gouvea E. G., Pessoa-Filho M., and Ferreira M. E. (2013). Development and validation of microsatellite markers for Brachiaria ruziziensis obtained by partial enome assembly of Illumina single-end reads. BMC Genomics, 14: 17. 
SPSS-Inc. (2010). IBM SPSS statistics 19 core system user’s guide. USA: SPSS Inc., an IBM Company Headquarters.
Tabkhkar N., Rabiei B., Samizadeh Lahiji1 H., and Hosseini Chaleshtori M. (2018). Genetic variation and association analysis of the SSR markers linked to the major drought yield QTLs of rice. Biochemical genetics, 56(4): 356-374.
Yeh F. C., Yang R. C., Boyle T., Ye Z. H., and Mao J. X. (1997). POPGENE: the user-friendly shareware for population genetic analysis. Molecular Biology and Biotechnology Centre, University of Alberta, Canada. [Available at http://www.ualberta.ca/~fyeh/].