Selection of diverse genotypes has been one of the most important aspects in breeding of many crop plants including rice. Recently, efforts have been made to predict the prospects of developing superior genotype(s) from a cross by measuring genetic similarity (GS) or genetic distance (GD) between parents (Burkhamer et al., 1998 ; Bohn et al., 1999). Many diversity studies have been undertaken in the past using morpho-physiological and agronomic traits, but with little success, because of the limited number of traits, influence of environment and genotype x environment interaction. On the other hand, molecular markers offer a distinct advantage due to their unlimited number and independent of environmental effect. The microsatellites or Simple Sequence Repeats (SSRs) are abundant, ubiquitous and hypervariable in nature. They have high Polymorphic Information Content (PIC) (Gupta et al., 1996). These positive aspects of SSRs have attracted the attention of several workers to utilize them across crop species for studying genetic variability based on DNA polymorphism. It has been shown that even limited number of SSRs is adequate to discriminate the most closely related genotypes (Plaschke et al., 1995 ; Russell et al., 1997 ; Struss and Plieske, 1998). The present study was undertaken to detect polymorphism and to assess the level of genetic diversity among 27 rainfed

lowland genotypes of rice that are potentially useful in further breeding program.

Forty-one microsatellite markers distributed over all chromosomes except chromosome 4 were selected for the molecular analysis of the 27 genotypes bred in India and at the International Rice Research Institute (IRRI). The genomic DNA was extracted and purified using modified CTAB procedure (Saghai-Maroof et al., 1984). The microsatellite assay followed the standard procedure as described by Panaud et al. (1996). Data were scored for the computer analysis on the basis of presence or absence of bands. The presence of each informative band was scored as one, while its absence scored as zero. The binary data was used to compute genetic distance (GD) using Nei and Li (1972) statistic and subjected to UPGMA cluster analysis by using a computer software NTSYSpc 2.02. The allelic polymorphic information content was calculated using the formula: PIC = 1- sigma(P_i)² , where, 'P_i' is the frequency of the i^th allele calculated for each microsatellite locus (Botstein et al., 1980).

The results of PCR amplification of a number microsatellite loci in 27 rainfed lowland genotypes using 41 primer pairs are summarized in Table 1. The amplified products were available in all the 27 genotypes with 41 primer pairs. A total of 128 alleles were detected over 41 marker loci. The number of alleles detected ranged from 1 to 6 with an average of 3.12 per locus. A maximum of 6 alleles were detected at one locus RM 206 located on chromosome 11. There were 18 loci with 4 or more number alleles. The PIC or gene diversity ranged from 0.07 (OSR 27, RM 6, RM 236) to 0.77 (OSR 22).The average gene diversity calculated over 35 polymorphic loci was 0.55 indicating substantial amount of diversity among 27 genotypes. There was a slight mismatch between number of alleles detected and gene diversity. For instance, at locus RM 206 six alleles were detected with a gene diversity of 0.69 which is less than 0.71 (RM 217) and 0.77 (OSR 22) with 4 and 5 alleles respectively. This indicates the presence of certain rare alleles at these two loci.

The genetic relationships among 27 rainfed lowland genotypes were further studied by UPGMA cluster analysis and the same is presented in Figure 1. The 27 genotypes were classified into 5 major clusters. A maximum of 12 genotypes were found in cluster 2 followed by 9 in cluster 1, 3 in cluster 4, 2 in cluster 3, while the cluster 5 contained only one genotype. The genotypes belonging to a particular cluster shared some common features, for instance, most of the genotypes found in cluster 1 possess submergence tolerance. Similarly, many of those found in cluster 2 are not suitable for delayed planting. The 3 genotypes found in cluster 4 included traditionally grown varieties such as Mahsuri which lack many of the key traits for their successful cultivation in rainfed lowlands. On the contrary the genotypes found in cluster 3 particularly Sabita is known to be tolerant for most of the key traits. The solitary genotype found in cluster 5 is tolerant to drought at reproductive stage and suitable for delayed planting.

The present study revealed a substantial amount of diversity among the 27 genotypes, which were effectively differentiated by the microsatellite markers.

References

Bohn, M., H. Friedrich Utz and A.E. Melchinger, 1999. Genetic similarities among winter wheat cultivars determined on the basis of RFLPs, AFLPs and SSRs and their use for predicting progeny variance. Crop Sci., 39: 228- 237.

Botstein, D. R.L. White, M. Skolnick and R.W. Davis, 1980. Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am. J. Hum. Genet.32: 314-331.

Burkhamer, R.L., S.P. Lanning, R.J. Martens, J.N. Martin and L.E. Talbert, 1998. Predicting progeny variance from parental divergence in hard red spring wheat. Crop Sci., 38: 243-248.

Gupta, P.K., H.S. Balyan, P.C. Sharma and B. Ramesh, 1996. Microsatellites in plants: a new class of molecular markers. Curr. Sci., 70: 45-54.

Panaud, O., X. Chen and S.R. McCouch, 1996. Development of microsatellite markers and characterization of simple sequence length polymorphism (SSLP) in rice (Oryza sativa L.) Mol. Gen. Genet., 252: 579-607.

Plaschke. J., M.W. Ganal and M.S. Roder, 1995. Detection of genetic diversity in closely related bread wheat using microsatellite markers. Theor. Appl. Genet., 91: 1001-1007.

Russell, J., J. Fuller, G. Young, B. Thomas, G. Taramin, M. Macaulay, M. Waugh and W. Powell, 1997. Discriminating between barley genotypes using microsatellite markers. Genome 40: 442-450.

Saghai-Maroof, M.F., K.M. Soliman, R.A. Jorgensen and R.W. Allard, 1984. Ribosomal DNA spacer length polymorphisms in barley: Mendelian inheritance, chromosomal location and population dynamics. Proc. Natl.
Acad. Sci., USA. 81: 8014-8018.

Struss, D. and J. Plieske, 1998. The use of microsatellite markers for detection of genetic diversity in barley populations. Theor. Appl. Genet., 97: 308-315.