Microsatellite (SSR) Based Assessment of Genetic Diversity among the Semi-dwarf Mutants of Elite Rice Variety WL112
Suresh Gopal Bhagwat
Success of semi-dwarf varieties in late 1960s lead breeders to depend heavily on these leading to narrow genetic base in todays rice varieties. Analysis of cultivated varieties in tropical Asia revealed sd1 gene from Dee-geo-woo-gen to be the major dwarfing source. High genetic similarity renders crop genetically vulnerable to potential epidemics. Efforts are underway to broaden the genetic base using alternate sources of dwarfing. Mutation breeding has been used to increase allelic diversity. In this study, twenty radiation induced mutants of rice (Oryza sativa L.) and parent variety WL112, showing morphological differences, were screened for variation in Simple Sequence Repeats (SSR). Thirty five polymorphic SSR primers, selected from all chromosomes of rice generated 115 polymorphic bands. Jaccards similarity coefficient revealed considerable genetic diversity among the mutants. The dissimilarity between the mutants was as high as 65%. The UPGMA based dendrogram showed five major clusters with sub-clusters. Mutant-specific polymorphic SSR markers either alone or in combination, were detected. Twelve mutants could be identified by using specific markers, while combination of two could identify six mutants and parent. The radiation induced mutants revealed diversity and short stature in elite background which could be used in breeding programme.
Received: November 05, 2011;
Accepted: March 26, 2012;
Published: June 08, 2012
Rice (Oryza sativa L.) is one of the most important staple foods for
the worlds population ranking third after Wheat and Maize in terms of
production and consumption (Akinbile et al., 2011).
Asia accounts for over 95% of global rice production with China (194.3 million
t) and India (148.3 million t), ranked first and second, respectively are by
far the largest producers of rice, producing half of the worlds rice (Upadhyay
et al., 2011). It is the second most important crop in the world
which has an annual cultivation area of 213 Mha, with an annual production of
593 million t and an average productivity of 3.91 t ha-1 (Rai,
2003). In India, rice is the most important crop occupying an area of 42
Mha and annual production of 133 mt. Tropical Asia, accounting for over 90%
of production and consumption of rice had been growing tall statured lodging
prone varieties with very low yields until the advent of the non-lodging, high
yielding and semi-dwarf varieties in sixties. The short statured varieties developed
using Dee-Geo-Woo-Gen (DGWG), have enabled many countries in the region to achieve
self-sufficiency in rice (Spielmeyer et al., 2002).
Up to now more than 60 dwarfing genes have been identified mostly in japonica
rice (Nagato and Yoshimura, 1998). Dwarfing genes are
often associated with agronomically undesirable traits which restrict their
use in rice breeding program. Also, genetic barriers between indica and japonica
cultivars restrict transfer of genes. Hence, there is an urgent need to look
for alternative sources of semi-dwarfing in indica back ground. Usefulness of
radiation induced mutations to alter the culm height has been well documented
(Songsri et al., 2011).
The success of DGWG gene based varieties such as IR8 and Taichung (Native)
1 have been excessively used by breeders all over the globe as source of dwarfing.
With over 90% of the high yielding varieties in cultivation today having DGWG
gene (Cho et al., 1994), the genetic base, as
result is quite narrow. Apprehending that high genetic similarity might render
the crop genetically vulnerable to biotic or abiotic stresses, many efforts
have been made for broadening the genetic base through identification and use
of alternate sources of dwarfing genes (Neeraja et al.,
2009). There is an urgent need to discover alleles of sd1 gene or
finding non-allelic semi-dwarfing genes. Molecular markers provide a powerful
tool for locating and distinguishing key genetic regions on the whole genome
and hence differentiating genotypes from each other (Puchooa
and Venkatasamy, 2005; Tertivanidis et al., 2008;
Yasmin et al., 2006; Nazari
and Pakniyat, 2008). A wide range of molecular markers have been applied
for genetic diversity studies in rice such as RFLP, microsatellite, RAPD and
AFLP (Ndjiondjop et al., 2006). These DNA based
molecular techniques helped in detecting genetic differences among mutants and
cultivars (Botstein et al., 1980; Williams
et al., 1990; Vos et al., 1995). Among
these, simple sequence repeat (SSR) markers are efficient, cost-effective and
detect a significantly higher degree of polymorphism. These are also highly
reproducible, multi-allelic, codominant, relatively abundant and cover whole
genome in rice (Guasmi et al., 2008). They are
ideal for genetic diversity studies and intensive genetic mapping. The present
investigation was aimed at assessing genetic diversity among dwarf and semi-dwarf
mutants of rice variety WL112 and to characterize these mutants with the help
of microsatellite based SSR markers.
MATERIALS AND METHODS
Rice material: WL112 is an important rice variety in India which is
extra tall type (plant height >150 cm) and extremely lodging susceptible
especially during late monsoon rains which can result in complete loss. With
an aim to get dwarf or semi-dwarf mutants, seeds of parent variety WL112 were
earlier subjected to gamma ray irradiation with 250 Gy dose in Gamma Cell 220
irradiator. Twenty dwarf and semi-dwarf mutants were identified in M2
generation and were stabilized in subsequent generations. These were stable
as judged from their uniformity in morphological traits. The mutants used in
this study are listed in Table 1. The parent variety WL112
and its mutants were grown in Trombay location in Kharif 2009 and 2010. Standard
agronomic practices were followed. Observations were recorded for various morphological
and agronomic traits. Data were taken from five randomly selected plants and
averaged. GA3 sensitivity test was carried out by spraying 12 day
old seedlings with GA3 at 10-4 M concentration. Control
plants were sprayed with distilled water. Seedling height was measured after
five days of GA3 spray. The symbol + or - in Table
1 indicates GA3 responsiveness or non-responsiveness, respectively.
Reaction to rice blast disease was monitored under field conditions at a hot
spot location in Rice Research Station, Ratnagiri. Scoring was based on 0-5
scale (Mohanta et al., 2003).
|| Morphological traits of parent WL112 and dwarf mutants
|+: Positive, -: Negative
Primer selection: A total of thirty five SSR primer pairs, synthesized
by M/s Allied Scientific Products, Kolkata, India, were used for PCR amplification.
These primers were selected based on their uniform distribution on all the 12
linkage groups and their polymorphic information content (PIC) value (http://gramene.org/markers/microsat/50_ssr.html).
Sequences of the SSR primers used in this study and their allelic information
are given in Table 2.
PCR amplification, data scoring and analysis: DNA was extracted as per
the protocol developed by Nalini et al. (2004).
The DNA was quantified using Cintra 2.2 UV-Vis spectrophotometer (GBC) at 260
nm wavelength. The DNA was diluted to 25 ng μL-1 and used as
working stock. PCR was conducted in a total reaction volume of 15 μL per
sample. The reaction mixture contained 10X PCR buffers 1.5 μL (10 mM tris-HCl
pH 9.0, 50 mM KCl and 15 mM MgCl2), dNTPs (2.5 mM) 1.5 μL,
Taq DNA polymerase (3 U μL-1) 0.17 μL, forward and reverse
primer (10.5 μM μL-1) 1 μL each and DNA 25 ng. Thermal
cycling conditions were as follows: Initial denaturation for 3 min at 94°C,
35 cycles of 1 min at 94°C, 1 min at 55°C (annealing temperature) and
1 min at 72°C. Annealing temperature was varied depending upon the specific
requirements of the SSR primer pairs. PCR was performed on Eppendorf master
gradient thermal cycler. The PCR amplified products were resolved on 6% denaturing
polyacrylamide gel (acrylamide:Bisacrylamide (30:1) 80 mL, urea (7.2 M) 20 mL,
10% ammonium per sulphate 400 μL and TEMED 170 μL). The gel was pre
run at 60 W (40 mA; 1500 V) with pre run dye for 60 min or until the gel temperature
reached 55°C in 1X TAE. Sample preparation was done by adding 7.5 μL
denaturing buffer (95% Formamide in 1X TAE, 0.05% xylene cyanol (w/v), 0.05%
bromophenol blue (w/v). To 200 μL of this mix, 30% formamide in glycerol
was added to 15 μL PCR product.
|| List of SSR primers used in the present investigation
|PIC: Polymorphic information content
The samples and ladders were denatured for 3 minutes at 94°C in the thermocycler
and immediately placed on ice. About 6 μL of sample was loaded quickly
and the gel was run at 60 W for 80-100 min at 50-55°C. The gel was silver
stained using improved modified protocol by Creste et
al. (2001). Bands on silver stained gels were scored as 1 (presence)
or 0 (absence). Data were entered in binary data matrix as discrete variables.
Data were analyzed for dissimilarity using DARwin 5.0 software (Perrier
et al., 2003). Pair wise genetic similarity were estimated using
Jaccards similarity co-efficient. Unweighted pair group method using arithmetic
averages (UPGMA) was employed for cluster analysis generating dendrogram.
|| Identification of dwarf and semi-dwarf mutants and parent
WL 122 with SSR markers
|Mutants D11 and D16 could not be differentiated, +: Present,
Mutant specific polymorphic bands were identified either singly or in combination
of two markers to identify and differentiate it from the rest of mutants and
the parent (Table 3). Only clear and unambiguous bands were
taken into consideration for differentiating mutants and parent variety.
Phenotypic diversity among genotypes: Morphological traits of each genotype
were recorded on five randomly chosen plants in each replication. Data on some
agronomic traits such as plant height, days to flowering, number of tillers
per plant, yield per plant, GA3 response and reaction to rice blast
disease of the mutants and parent were recorded (Table 1).
Mutants exhibited significant variability for these traits. Plant height ranged
from 27.0 to 90.0 cm among mutants as compared to parent WL112 which was 160
cm. Extreme dwarf mutants D1 and D2 were shortest with height 27.0 and 30.2
cm, respectively. Figure 1 shows field view of three of the
short culm mutants (mutant D5, D13 and D20) and the parent. The parent WL112
flowered in 120 days. Earliest flowering among the mutants was recorded in mutant
D1 (52 days) followed by mutant D12 (74 days). Most of the mutants were significantly
earlier in flowering except mutants D10, D15, D16, D18 and D20 which were at
par with the parent. Variability was also observed for tillering ability. Sparse
tillering with average 8.2 and 8.8 tillers per plant was observed for mutants
D13 and D19, respectively. Parent WL112 showed moderate number of tillers with
average 14.1 tillers per plant. Dwarf mutant D7 showed very high tillering with
27.0 tillers per plant. Mutant D9, D10 and D11 also exhibited increase in tiller
number with 20 tillers per plant. Some of the dwarf mutants were relatively
non-responsive to GA3 such as D1, D2, D4, D12, D13, D15, D19 and
D20, remaining mutants were responsive. Parent WL112 and mutant D17 and D18
showed high susceptibility to rice blast disease. Mutants D19 and D20 were found
to be highly resistant, rest of the mutants were moderately resistant. Grain
yield per plant also exhibited significant variation among dwarf mutants.
||Field view of the parent variety (a) WL112, (b) Mutant D5,
(c) Mutant D13 and (d) Mutant D20
Average yield for WL112 was 22.95 g per plant. Mutant D16 recorded almost
double the yield of the parent variety with 47.9 g seed yield per plant. Mutants
D8 and D14 also exhibited higher yield than parent with 30.9 and 29.4 g seed
yield per plant. Mutants D1 and D12 recorded low yield with 7.4 and 8.3 g seeds
Microsatellite polymorphism and genetic variability analysis among genotypes: A total of 35 SSR loci were used to detect polymorphism across 20 dwarf and semi-dwarf mutants and parent rice variety WL112. The 35 primer pairs were well distributed over all the 12 linkage groups of rice and were found to be highly polymorphic. The level of polymorphism among these 21 genotypes of rice was evaluated by calculating allele number and PIC values for each of the 35 SSR loci. The SSR primer pairs used for genetic diversity analysis, the number of alleles for each SSR locus and PIC values are given in Table 2. Average number of alleles was estimated to be 3.29 and ranged from two (RM 125) to five (RM 474, RM 162, RM 514, RM 452 and RM 1). The PIC values, a reflection of allele diversity and frequency among the varieties, were not uniformly high for all the SSR loci tested. The average PIC value was 0.474 and it ranged from 0.215 for RM 208 to 0.689 for RM 1. Similarity matrices were constructed based on shared allele analyses which revealed that the average genetic similarity between genotypes was 0.52 with SSR markers. Maximum similarity was observed between D7 and D9 (0.8108) and minimum between D12 and D20 (0.2666).
Identification based on presence of unique bands: Most of the genotypes used in the present study could be differentiated from each other by using a single marker or a combination of two markers. Out of twenty dwarf and semi-dwarf mutants, twelve mutants could be differentiated by the presence of specific band with specific SSR primer (Table 3). Remaining six mutants i.e. D3, D7, D10, D14, D18, D19 and parent WL112 could be differentiated and identified by a combination of two SSR primers. Mutants D11 and D16 were not distinguishable.
Genetic relationship between dwarf mutants and parent WL112: Cluster analyses were used to group mutants and parent to construct dendrogram based on SSR (Fig. 2). The dendrogram separated all the 21 genotypes into five distinct clusters. The first major cluster, cluster 1 consisted of eight mutants with three sub-clusters. Cluster 2 consisted of five dwarf mutants and was subdivided into two sub-clusters; cluster 3 contained only one mutant D19. Cluster 4 and 5 were of equal size with three mutants each. Parent WL112 was included in cluster 4 along with mutant D17 and D18. Mutant D20 was not included in any of the clusters.
||Dendrogram resulting from UPGMA cluster analysis of 20 dwarf
mutants and parent WL112
The present attempt was made to characterize 20 gamma ray induced short stature mutants and assess diversity among the mutants for their efficient utilization in breeding programme.
Phenotypic variability: The mutants exhibited significant variability
for plant height which ranged from 27.0 to 90.0 cm as compared to parent WL112
which was 160 cm. Significant reduction in plant height was achieved. Similar
reduction in plant height was also reported earlier (Jana
and Roy, 1973). The mutants were either responsive or non responsive to
spray of 10-4 M GA3 at early seedling stage. The responsive
dwarf mutants could be defective in the GA biosynthetic pathway, which could
be rescued by the application of GA3. Dwarf stature could also be
a result of other reasons. For instance, the D1 type dwarf is reported to be
defective in α-subunit of the heterotrimeric G protein which affects gibberellin
signal transduction (Ueguchi-Tanaka et al., 2000).
Likewise, loss of function mutation in the rice homeobox gene OSH15 is
reported to affect the architecture of internodes resulting in D6 dwarf plants
(Sato et al., 1999). Characterization of dwarfs
of D16 mutants revealed a protein kinase with high similarity to a putative
brassinosteroid receptor in Arabidopsis to be linked to prevention of
internode elongation (Yamamuro et al., 2000).
Some of the dwarf mutants used in this study (D1, D2, D4, D11, D12, D13, D15,
D19 and D20) were insensitive to gibberellin spray indicating mutation in pathway
other than GA synthesis.
Some of the mutants exhibited earliness in flowering by 20-70 days. This trait can be useful in reducing the duration of crop particularly in India where rice is cultivated in monsoon season (Kharif) which is followed by season which is important for winter (Rabi) crops.
The induced dwarf mutants D1 to D16 also exhibited moderate resistance to rice
blast disease while mutants D19 and D20 were highly resistant to blast. The
isolation of possible blast resistant mutants in adapted material is of agronomic
importance. Similar mutants with early flowering and resistance to rice blast
disease are reported (Wu et al., 2010). Mutation
in rice is known to change the tiller number per plant. High tillering mutation
ht1 in japonica rice variety Xindao18 was reported with tiller number three
times of the parent and was mapped on chromosome number 10 with SSR markers
(Li et al., 2010). In the present study, mutant
D7 exhibited almost double the tiller number of the parent variety WL112. Increase
in tiller number was also reported in mutant D9, D10 and D11. Increase in tillering
is ascribed to reduced tiller bud dormancy at the prophyll nodes as reported
for fc1 mutation in rice (Goto et al., 2005).
Among the mutants, significant variation for seed yield per plant was observed.
As a complex agronomic trait, grain yield per plant of rice is determined by
three component traits: Number of panicles per plant, number of grains per panicle
and grain weight. These traits in turn are controlled by many correlated traits
such as number of tillers, number of spikelets, grain dimension, degree and
rate of grain filling etc. Earlier studies have revealed presence of QTLs for
grain yield on almost all the rice chromosomes (Xing and
Zhang, 2010). Mutant D16, D8 and D14 exhibited significant change in grain
yield per plant. Dwarf mutant D16 showed almost double the yield of parent variety.
This major change is probably due to increased number of spikelets and more
number of grains per panicle as grain dimension and filling rate was more or
Genotypic variability among dwarf mutants and parent: The assessment
of genetic diversity is essential for germplasm characterization and utilisation.
The results derived from analyses of genetic diversity at the DNA level could
be used for designing effective breeding programs. Microsatellite diversity
analysis of 21 genotypes with 35 SSR primers pairs indicated a high level of
genetic diversity (0.65) and higher average number of alleles per primer of
3.29. These results support the finding that microsatellite markers are informative
and powerful to assess the genetic variability among closely related mutants
(Xu et al., 2004). Majority of the SSR primers
used in this study had the GA-dinucleotide repeat motif which has been reported
to display high level of variation among the rice genotypes (Temnykh
et al., 2000).
The present attempt was made to identify alternate sources to sd1 by
characterizing 20 induced (gamma rays) dwarf and semi dwarf genotypes along
with parent WL112 at molecular level. Genetic variability was observed among
the dwarf mutants and the parent using the SSR markers. Among the 21 genotypes
the average genetic similarity of 0.52 (based on similarity matrix in DARwin)
indicated creation of genetic diversity among the dwarf mutants. Herrera
et al. (2008) also reported average genetic similarity of all SSR
loci for 18 genotypes using 45 SSR primers to be 0.48.
SSR markers were highly informative and polymorphic as evident from its PIC
value of 0.474 (Chen et al., 2011). SSR markers
are normally hyper variable and hence the polymorphism estimate is generally
higher than other loci in the genome. It was seen that PIC values were relatively
higher for markers RM 1 (0.689), RM 510 (0.634) and RM 162 (0.626) having GA
and AC repeats which is because of the fact that these repeats are highly variable
and polymorphic in nature. The structure and length of simple sequence repeats
are considered to be one of the major factors affecting microsatellite variability.
In general, SSR loci such as RM 452, RM 1, RM 514, RM 162 and RM 474 with more
repeats tend to be more polymorphic and had larger amplitude of variation (Schug
et al., 1998).
An important application of molecular diversity study is to identify a marker
which can differentiate a desirable genotype from the rest. In the present study,
unique alleles were identified for twelve mutants and combination of two primers
could distinguish the rest of the six genotypes (Choudhary
et al., 2011). Generation of data base for morphological and molecular
variation of the mutants will help in their identification and utilization in
UPGMA clustering: The UPGMA cluster analysis showed that all 20 dwarf
mutants of rice variety WL112 could be distinguished based on the information
generated by the 35 SSR markers. Clusters generated showed a close association
with the morphological traits under study. The dendrogram indicated five major
clusters with different sub-clusters. Most of the semi-dwarf, mid-early maturity
with moderate resistance to rice blast mutants were included in cluster 1 and
2. The mutant D19 which showed high resistance to rice blast disease was the
only component of cluster 3. Cluster 4 contained all the entries susceptible
to blast which also included parent variety WL112. Extreme dwarf mutants D1,
D3 and D4 were included in cluster 5 and genetic distance of about 0.65 showed
wide genetic divergence from the rest of mutants. Kumar
and Bhagwat (2009) also reported distinct SSR clustering among the dwarf
mutants of rice variety Basmati 370. Similar SSR based clustering has been reported
in basmati and non-basmati rice varieties (Nagaraju et
al., 2002). Our results showed that the SSR markers could distinguish
genetically close breeding lines and mutants and the information generated can
be used in the characterization and utilization of rice mutant germplasm.
Although, it is common to obtain reduced height mutants in rice, they are often associated with reduced plant vigour. Some of the dwarf mutants in the present study have been found to have good phenotypic and agronomic attributes especially dwarf mutant D16 with high grain yield/plant and also earliness in maturity. This mutant could be used directly for further evaluation of grain yield. Other mutants (mutant D8, D14 and D16) could also serve as alternate source(s) of dwarfing with desirable agronomic and yield attributes for use in breeding programme. SSR markers proved to be effective in estimating genetic diversity among the mutants. These mutants could help in increasing the genetic diversity and allelic richness. Parent identification for a hybridization programme on the basis of estimated diversity is likely to be more effective than choosing parents randomly. Understanding of genetic relationship together with analysis of their agronomic performance will help in efficient utilization of these induced mutants in rice improvement programme.
The authors thank Dr. S. F. DSouza, Associate Director (A), BMG and Head, NABTD and Dr. U. B. Apte of Rice Research Station, Ratnagiri for providing field facility for testing resistance to rice blast and ICRISAT for providing DARwin 5.0 software. The authors also thank Shri Vikas and Sudhakar Mali for assisting in the field.
Akinbile, C.O., K.M. Abd El-Latif, R. Abdullah and M.S. Yusoff, 2011.
Rice production and water use efficiency for self-sufficiency in Malaysia: A review. Trends Applied Sci. Res., 6: 1127-1140.CrossRef |
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.PubMed | Direct Link |
Chen, C.X., S.C. Li, S.Q. Wang, H.N. Liu and Q.M. Deng et al
Assessment of the genetic diversity and genetic structure of rice core parent Guichao 2, its parents and derivatives. J. Plant Sci., 6: 66-76.CrossRef |
Choudhary, N., U. Ahuja, V. Chawla, R.K. Jain, P. Kumari and K.R. Batan, 2011.
Morphological and molecular variability in weedy rices of Haryana. Asian J. Agri. Res., 5: 250-259.CrossRef |
Creste, S., A.T. Neto and A. Figueira, 2001.
Detection of single sequence repeat polymorphisms in denaturing polyacrylamide sequencing gels by silver staining. Plant Mol. Biol. Rep., 19: 299-306.CrossRef | Direct Link |
Goto, Y., M. Tanabe, T. Ishibashi, N. Tsutsumi, A. Yoshimura and K. Nemoto, 2005.
Tillering behavior of the rice fine culm 1 mutant. Plant Prod. Sci., 8: 68-70.CrossRef |
Guasmi, F., L. Touil, K. Feres, W. Elfelah, T. Triki and A. Ferchichi, 2008.
Genetic diversity of Tunisian barley accessions based on microsatellite markers. Biotechnology, 7: 781-786.CrossRef | Direct Link |
Herrera, T.G., D.P. Duque, I.P. Almeida, G.T. Nunez, A.J. Pieters, C.P. Martinez and J.M. Tohme, 2008.
Assessment of genetic diversity in Venezuelan rice cultivars using simple sequence repeats markers. Electron. J. Biotechnol., Vol. 11, No. 5.CrossRef | Direct Link |
Jana, M.K. and K. Roy, 1973.
Induced quantitative mutation in rice. Radiat. Bot., 13: 245-257.CrossRef |
Kumar, V. and S.G. Bhagwat, 2009.
SSR based DNA fingerprinting and analysis of genetic diversity in radiation induced mutants of rice (Oryza sativa
L.). Proceedings of International Conference on Emerging Trends in Biotechnology, December 4-6, 2009, Banaras Hindu University, Varanasi, India, pp: 275-
Li, W.C., Y.F. Wang, S.M. Ma and S.W. Guo, 2010.
Genetic analysis and molecular mapping of a high-tillering mutant (ht1) in rice. Yi Chuan, 32: 1065-1070.PubMed |
Mohanta, B.K., M.R. Alam, M.E. Kabir, M.K. Anam, Md. K. Alam and M.A. Habib, 2003.
Performance of different genotypes/cultivars to blast disease of rice in boro and T. aman crop in Bangladesh. Asian J. Plant Sci., 2: 575-577.CrossRef | Direct Link |
Nagaraju, J., M. Kathirvel, R.R. Kumar, E.A. Siddiq and S.E. Hasnain, 2002.
Genetic analysis of traditional and evolved Basmati and non-basmati rice varieties by using fluorescence-based ISSR-PCR and SSR markers. Proc. Natl. Acad. Sci., 99: 5836-5841.CrossRef | Direct Link |
Nagato, Y. and A. Yoshimura, 1998.
Report of the committee on gene symbolization, nomenclature and linkage groups. Rice Genet. Newslett., 15: 13-74.Direct Link |
Nalini, E., N. Jawali and S.G. Bhagwat, 2004.
A simple method for isolation of DNA from plants suitable for long-term storage and DNA marker analysis. BARC Newslett., 249: 208-214.Direct Link |
Nazari, L. and H. Pakniyat, 2008.
Genetic diversity of wild and cultivated barley genotypes under drought stress using RAPD markers. Biotechnology, 7: 745-750.CrossRef | Direct Link |
Ndjiondjop, M.N., K. Semagn, M. Cissoko, H. Tsunematsu and M. Jones, 2006.
Genetic relationships among rice varieties based on expressed sequence tags and microsatellite markers. Asian J. Plant Sci., 5: 429-437.CrossRef | Direct Link |
Neeraja, C.N., L.R. Vemireddy, S. Malathi and E.A. Siddiq, 2009.
Identification of alternate dwarfing gene sources to widely used Dee-Gee-Woo-Gen allele of sd1
gene by molecular and biochemical assays in rice (Oryza sativa
L.). Electron. J. Biotechnol., Vol. 12.CrossRef | Direct Link |
Perrier, X., A. Flori and F. Bonnot, 2003.
Data Analysis Methods. In: Genetic Diversity of Cultivated Tropical Plants. Seguin, X. Perrier and J.C. Glaszmann (Eds.). Enfield Science Publishers, Montpellier, France, pp: 43-76
Puchooa, D. and K. Venkatasamy, 2005.
Detection of genetic diversity in Trochetia boutoniana
using random amplified polymorphic DNA (RAPD) markers. Biotechnology, 4: 267-274.CrossRef | Direct Link |
Rai, M., 2003.
Genetic diversity in rice production: Past contribution and the potential of utilization for sustainable rice production: Sustainable rice production for food security. Proceedings of the 20th Session of the International Rice Commission, July 23-26, 2002, Bangkok, Thailand, pp: 306-
Sato, Y., N. Sentoku, Y. Miura, H. Hirochika, H. Kitano and M. Matsuoka, 1999.
Loss-of-function mutations in the rice homeobox gene OSH15 affect the architecture of internodes resulting in dwarf plants. EMBO J., 18: 992-1002.CrossRef | Direct Link |
Schug, M.D., C.M. Hutter, K.A. Wetterstrand, M.S. Gaudette, T.F. Mackay and C.F. Aquadro, 1998.
The mutation rates of di-, tri- and tetranucleotide repeats in Drosophila melanogaster
. Mol. Biol. Evol., 15: 1751-1760.Direct Link |
Songsri, P., B. Suriharn, J. Sanitchon, S. Srisawangwong and T. Kesmala, 2011.
Effects of gamma radiation on germination and growth characteristics of physic nut (Jatropha curcas
L.). J. Biol. Sci., 11: 268-274.CrossRef | Direct Link |
Spielmeyer, W., M.H. Ellis and P.M. Chandler, 2002.
Semidwarf (sd-1), green revolution rice, contains a defective gibberellin 20-oxidase gene. Proc. Natl. Acad. Sci., 99: 9043-9048.Direct Link |
Temnykh, S., W.D. Park, N. Ayres, S. Cartinhour and N. Hauck et al
Mapping and genome organization of microsatellite sequences in rice (Oryza sativa
L.). Theor. Applied Genet., 100: 697-712.CrossRef | Direct Link |
Tertivanidis, K., O. Koutita, I.I. Papadopoulos, I.S. Tokatlidis, E.G. Tamoutsidis, V. Pappa-Michailidou and M. Koutsika-Sotiriou, 2008.
Genetic diversity in bean populations based on random amplified polymorphic DNA markers. Biotechnology, 7: 1-9.CrossRef | Direct Link |
Ueguchi-Tanaka, M., Y. Fujisawa, M. Kobayashi, M. Ashikari, Y. Iwasaki, H. Kitano and M. Matsuoka, 2000.
Rice dwarf mutant d1, which is defective in the alpha subunit of the heterotrimeric G protein, affects gibberellin signal transduction. Proc. Natl. Acad. Sci. USA., 97: 11638-11643.CrossRef | PubMed | Direct Link |
Upadhyay, P., V.K. Singh and C.N. Neeraja, 2011.
Identification of genotype specific alleles and molecular diversity assessment of popular rice (Oryza sativa
L.) varieties of India. Int. J. Plant Breed. Genet., 5: 130-140.CrossRef |
Vos, P., R. Hogers, M. Bleeker, M. Reijans and T. van de Lee et al
AFLP: A new technique for DNA fingerprinting. Nucleic Acids Res., 23: 4407-4414.CrossRef | PubMed | Direct Link |
Williams, J.G.K., A.R. Kubelik, K.J. Livak, J.A. Rafalski and S.V. Tingey, 1990.
DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucleic Acids Res., 18: 6531-6535.CrossRef | PubMed | Direct Link |
Wu, C.L., S.F. Li, B.X. Dong, Q.Q. Zhang and C.Q. Zhang, 2010.
Determination of the number of SSR alleles necessary for the analysis of genetic relationships between maize inbred lines. Agric. Sci. China, 9: 1713-1725.CrossRef | Direct Link |
Xing, Y. and Q. Zhang, 2010.
Genetic and molecular bases of rice yield. Annu. Rev. Plant Biol., 61: 421-442.CrossRef | PubMed | Direct Link |
Xu, Y., H. Beachell and S.R. McCouch, 2004.
A marker-based approach to broadening the genetic base of rice in the USA. Crop Sci., 44: 1947-1959.CrossRef | Direct Link |
Yamamuro, C., Y. Ihara, X. Wu, T. Noguchi and S. Fujioka et al
Loss of function of a rice Brassinosteroid insensitive
1 homolog prevents internode elongation and bending of the lamina joint. Plant Cell, 12: 1591-1606.CrossRef |
Yasmin, S., M.S. Islam, K.M. Nasiruddin and M.S. Alam, 2006.
Molecular characterization of potato germplasm by random amplified polymorphic DNA markers. Biotechnology, 5: 27-31.CrossRef | Direct Link |
Cho, Y.G., M.Y. Eun, S.R. McCouch and Y.A. Chae, 1994.
The semi-dwarf gene, sd-1 of rice (Orzo sativa
L.) II. Molecular mapping and marker-assisted selection. Theor. Applied Genet., 89: 54-59.CrossRef |