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
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(Pi)2 , where, 'Pi' is the
frequency of the ith 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
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