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Published online 1 March 2007
Published in Crop Sci 47:879-884 (2007)
© 2007 Crop Science Society of America
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PLANT GENETIC RESOURCES

Genetic Relatedness of Portuguese Rice Accessions from Diverse Origins as Assessed by Microsatellite Markers

P. Jayamania,b, S. Negrãoa, M. Martinsa, B. Maçãsc and M. M. Oliveiraa,d,*

a ITQB/IBET, Quinta do Marquês, 2784-505 Oeiras, Portugal
b CPBG, Tamil Nadu Agricultural Univ., Coimbatore 641003, India. M. Martins, Instituto Gulbenkian de Ciência, Apartado 14, P-2781-901, Oeiras, Portugal
c ENMP Apartado 6, 7350-951 Elvas, Portugal
d Univ. Lisboa, Fac. Ciências, Dep. Biologia Vegetal, 1749-016 Campo Grande, Lisboa Portugal

* Corresponding author (mmolive{at}itqb.unl.pt).


   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
Simple sequence repeat (SSR) markers detect a significantly high degree of polymorphism in rice (Oryza sativa L.) and are particularly suitable for evaluating genetic diversity among closely related cultivars. A total of 176 rice accessions originating from 19 countries in the Portuguese working germplasm collection and two standard rice varieties (IR36-indica and Nipponbare-japonica) were analyzed for DNA profile using 24 SSR loci covering two loci per chromosome. A total of 184 alleles were detected. The number of alleles per locus ranged from 3 to 16, with an average of 7.7, and the PIC value ranged from 0.179 to 0.894 with an average of 0.667. All the loci were polymorphic among the accessions and clearly distinguished the indica and japonica subspecies. At 20% similarity, cluster analysis of the 178 accessions revealed three major groups, japonica, basmati, and indica (Groups I, II, and III, respectively). The japonica group contained 87% of the accessions and showed a wide range of similarity values (0.21–0.92), revealing a high degree of diversity among the accessions. Many of the accessions included in this study are morphologically similar and lack pedigree information. Hence, identification of genetic distances among the accessions should improve their use in breeding programs. As a result of this study, genetically diverse parents can be identified, increasing the usefulness of germplasm collections by broadening the genetic base of rice varieties.

Abbreviations: COTArroz, Centro Operativo e Tecnológico do Arroz • EAN, Estação Agronómica Nacional • IRRI, International Rice Research Institute • NPT, new plant type • PCA, principal component analysis • PCR, polymerase chain reaction • PIC, polymorphism information content • RAPD, randomly amplified polymorphic DNA • SSR, simple sequence repeat • UPGMA, unweighted pair group mean average method.


   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
RICE (Oryza sativa L.) has one of the largest ex situ germplasm collections in the world (Jackson and Juggan, 1993; Ni et al., 2002), with 108000 accessions, mostly landraces or breeding materials of O. sativa plus a small number of O. glaberrima, 22 wild species of Oryza, and a few other related genera being housed at the International Rice Research Institute (IRRI) in the Philippines (Khush, 1997; Vaughan et al., 2003). To meet the continuously expanding needs of rice varietal improvement, the assembling, evaluation, and preservation of germplasm collections is essential. In addition to phenotypic characterization, DNA markers are being used to enhance the characterization and use of germplasm resources. For rice McCouch et al. (2002) reported that 2240 microsatellite markers or simple sequence repeats (SSR) were available, and this number has now doubled (http://www.gramene.org; verified 19 Feb. 2007). SSR markers have been effectively used to study genetic diversity among closely related rice cultivars (Yu et al., 2003; Saini et al., 2004; Spada et al., 2004; Zhu et al., 2004; Garris et al., 2005).

Cultivated rice can be divided in two different subspecies, japonica and indica, that can be distinguished based on agromorphological traits. Indica rice has longer and narrower grains that tend to remain separate after cooking, while japonica has shorter and rounded grains that tend to stick together after cooking. Rice was domesticated in Asia and brought to Europe (Mediterranean region) by returning members of Alexander the Great's expedition to India (324 BC). It was only in the 15th or 16th century, however, that rice became an established crop in the region (Khush, 1997). In Portugal, rice production was introduced by the Moors in the 10th century. Today the Portuguese consume the most rice in Europe, with 17.8 kg capita–1 yr–1, followed by the Spanish (7.1 kg capita–1 yr–1) (Vasconcelos et al., 2002). The Portuguese rice germplasm has mostly japonica varieties, which presently occupies 80% of the rice-growing area in Portugal, with the remaining area having indica-like varieties (indica grain type with japonica genetic background).

In Portugal, the rice breeding program was resurrected about 3 yr ago after being discontinued in the mid-1980s, with the aim of improving traditional japonica varieties. Traditional Portuguese landraces are very tall, have low productivity, and are sensitive to diseases, especially blast (Magnaporthe oryzae B. Couch), but the landraces have good grain quality and are well adapted to Portuguese preferences. The objective of the rice breeding work is to use traditional Portuguese japonica rice varieties as the recipient and IRRI varieties (indica varieties) as donors to introduce blast resistance, increase yield through introgression of the semidwarf gene (sd1), and further improve grain quality traits. Presently, all commercial varieties are either from Italy or from overseas. The renewed interest in rice led to the formation of COTArroz (Centro Operativo e Tecnológico do Arroz) in Salvaterra de Magos, Portugal, and included a range of people from producers to those in the rice industry. The working rice germplasm collection includes 176 rice accessions that are maintained in the Department of Breeding and Genetic Resources of Estação Agronómica Nacional (EAN), Oeiras, Portugal. The objective of our study was to assess the genetic diversity of rice accessions in the working germplasm collection using microsatellite markers so that diverse parents could be selected to broaden the genetic base of Portuguese rice varieties.


   MATERIALS AND METHODS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 REFERENCES
 
Plant Materials
The Portuguese germplasm collection has 1200 accessions, with several introductions made in the beginning of the 20th century. The accessions in collection were introduced from Asia and other European countries, as well as from USA and the IRRI. The materials include traditional varieties of Portugal, breeding lines, cultivars, etc., but most of them lack pedigree information. A total of 176 accessions from this set, corresponding to the Portuguese working germplasm collection and originated from 19 different countries, were used in this study. The material includes indica and japonica subspecies, basmati and new plant type (NPT) accessions that are accessions recently developed at IRRI, with low tillering and high-density panicle (Table 1). Two rice varieties, IR36 and Nipponbare, recently received from the IRRI in the Philippines were used as standard varieties representing typical indica and japonica subspecies, respectively.


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  		Table 1. List of accessions used for simple sequence repeat analysis. Standard varieties are indicated in italic type. Accessions in the table are ordered according to the dendrogram (Fig. 1).

 

Figure 1
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  		Figure 1. Dendrogram built from the simple sequence repeat data of 178 rice accessions of the working germplasm collection. Analyses were made by the unweighted pair group mean average method and were based on Lynch's coefficient. Bootstrap values (out of 100) are indicated at the main branch points. Subgroups in Group I (GI-1–GI-16) although not supported by bootstrap analyses were indicated for easier correlation with the list of accessions in Table 1. Names of the rice accessions refer to those in Table 1. Most accessions in Group I are japonicas, in GII are basmati, and in GIII are indicas.

 
DNA Extraction and PCR Analysis
Thirty-day-old whole seedlings of 178 accessions were collected from the field (COTArroz, Salvaterra de Magos). The seeds were sown continuously in two rows with 3-m length. Leaf samples were prepared in duplicate from mixtures of leaves taken from 10 seedlings per accession. For DNA extraction, after collection, the leaf samples were maintained in cold for up to 1 h until freezing in liquid N and preservation at –80°C. The DNA was isolated from all the accessions using the CTAB method (Doyle and Doyle, 1987). DNA from all samples was quantified by spectrophotometry. The quality of random samples was checked by agarose gel electrophoresis.

A total number of 24 SSR primer pairs (2 chromosome–1) were selected on the basis of a previous study we conducted involving seven japonica and two indica accessions and testing 165 SSRs (S. Negrão, unpublished data, 2004). The selected primers were originally mapped by Panaud et al. (1996), Chen et al. (1997) and Temnykh et al. (2000, 2001) (Table 2). The primer sequences and PCR conditions can be found in the rice database (http://www.gramene.org). Polymerase chain reaction amplification (Thermocycler Biometra UNO II; Biometra, Germany) using the SSR primers (Illumina, Inc., San Diego, CA) was conducted in a 25-µL reaction mixture containing 40 ng of template DNA, 1x PCR buffer (Invitrogen, Carlsbad, CA), 2 mM of magnesium chloride (MgCl2), 400µM of dNTPs, 0.3 µM of each primer, and 1.5 units of Taq DNA polymerase (Invitrogen, Carlsbad, CA). The PCR conditions were set at 94°C for 5 min, followed by 35 cycles of 94°C for 1 min, 55°C for 1 min, 72°C for 2 min, and 7 min at 72°C for the final extension. The same PCR conditions were adopted for all primers except for RM186 where the annealing temperature was set at 61°C as recommended in the Gramene Database. The products were detected using 6 or 8% polyacrylamide gels in 1x Tris-Borate EDTA buffer according to the size of the bands. The gel system used was the Double Wide Mini-Vertical Gel unit (16 by 33 cm), from CBS Scientific (Solana Beach, CA). After electrophoresis the gels were stained with ethidium bromide solution and were photographed under ultraviolet light using Gel-Doc 1000 (Biorad, Hercules, CA). The molecular size of the amplification products was estimated using a 25-bp ladder (Invitrogen, Carlsbad, CA). The experiments were repeated to confirm cases of null alleles and to verify reproducibility.


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  		Table 2. Data on number of alleles, allele size range, number of rare alleles, number of null alleles, number of multiple alleles, highest frequency alleles and polymorphism information content (PIC) found among 178 rice accessions for 24 microsatellites.

 
Data Analysis
Differences in molecular weight for products amplified from SSR markers were manually measured using image analysis software (Mocha 1.2, Jandal Scientific, San Rafael, CA). The molecular weights for the standard varieties IR36 and Nipponbare were confirmed with the sizes in the database (http://www.gramene.org). The molecular size was also confirmed by manual scoring. The polymorphism information content (PIC) for each microsatellite marker was calculated according to Nei (1973). A matrix was formed based on the allele size for each locus and accession. Two alleles per locus for SSR marker were considered. Genetic similarity was calculated with the band-sharing coefficient (Lynch 1990), using the formula: SD = 2Nab/Na + Nb, where Na and Nb are the number of bands in accessions A and B; Nab, the number of bands shared by the two accessions; and SD, standard deviation. The dendrogram was constructed after cluster analysis of the similarity coefficient by means of the unweighted pair group mean average (UPGMA) method. A principal component analysis (PCA) was performed to highlight the resolving power of the ordination. These calculations were performed with a statistical software package, NTSYS-pc version 2.1 (Rohlf, 2000). One hundred resamples were used to estimate bootstrap values, using the software PowerMarker Version 3.25 (Liu and Muse, 2005; www.powermarker.net), and a consensus tree with the bootstrap values was generated in PHYLIP Version 3.5 software (Felsenstein, 1993).


   RESULTS AND DISCUSSION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
REFERENCES
 
SSR Analysis
In the present investigation, 24 SSR markers were used to assess the genetic diversity of 178 accessions originating from 19 different countries (Table 2). This study was the first step for the characterization of the molecular diversity of a large set of rice accessions present in the Portuguese national germplasm collection. All the 24 SSR loci were polymorphic and produced a total of 184 alleles among the 178 accessions analyzed, with product sizes ranging from 98 to 372 bp. The PIC value ranged from a minimum of 0.179 (RM84) to a maximum of 0.894 (RM249), with an average of 0.667. The average number of alleles per locus was 7.7, with a range of 3 (RM208 and RM242) to 16 (RM249 and RM72). This is significantly higher than the average number of alleles reported by Zhu et al. (2004) (4.37) and Spada et al. (2004) (7.2). However, these authors used fewer accessions (85 and 96 accessions, respectively) and SSR loci (19 and 12 loci, respectively) than we used in the present work. Yu et al. (2003) studied 193 rice accessions from 26 countries with 101 SSR primer pairs and detected an average allele number of 6.3 per locus, which is also lower than the value reported here. Luce et al. (2001) analyzed 419 rice accessions from gene banks in five European countries, including Portugal, with 16 SSR loci (different from the ones we selected) and reported an average of 9.1 alleles per locus. This value is higher than we observed (7.7) and probably a result of the larger number of accessions used by these authors. Still, the high level of SSR polymorphism that we detected in the Portuguese collection could be attributed primarily to the diverse origins of the japonica accessions.

An allele observed in less than 5% of the 178 accessions was considered to be rare. A total of 46 rare alleles were observed. All but five loci (RM297, RM208, RM242, RM228, and RM536) exhibited one or more rare allele. In general, markers detecting a higher number of alleles per locus also detected more rare alleles. RM72 and RM481 produced the maximum of six rare alleles, with 16 and 15 alleles per locus, respectively. An accession was assigned a null allele for a locus whenever an amplification product was not observed for the particular marker. Of the 24 SSR loci used in this study, 12 had null alleles in one to four of the 178 accessions. Multiple alleles (2 or 3 alleles locus–1) were detected at one or more loci per accession even in standard varieties such as IR36 and Nipponbare. Accessions with 2 alleles locus–1 were identified when two different bands had the same intensity. Whenever the two bands had different intensities, the stronger band was considered as varietal norm. Eight loci produced two bands with different intensities (Table 2). Out of these, RM255, RM539, RM481, and RM72 had two bands with different intensities in all the accessions analyzed. RM20A produced an independent segregation of two allelic bands with equal intensity in all the accessions analyzed, which were considered as two different alleles. Multiple alleles with 3 bands locus–1 were produced by eight different SSR markers, ranging from 4 (RM574) to 92 (RM335) accessions, with the most intense band considered as the variety norm.

Genetic heterogeneity is a common feature of rice accessions, despite the high inbred nature of the species (Jain et al., 2004). Most of the varieties were derived from pedigree breeding programs. Pedigree selection involves homozygous breeding; this should fix the genetic material revealing no more than 1 allele locus–1. Nonetheless, in this study, we found that nearly all accessions had two bands in one or more loci and the two bands did not segregate, indicating the accessions were not mixed. An independent segregation of two loci (two alleles) produced by RM20A may be due to the presence of duplicated regions within the rice genome. Panaud et al. (1996) observed an independent segregation of two loci (RM20A and RM20B), which were mapped on different chromosomes in a subset of doubled-haploid lines. Three alleles locus–1 (multiple alleles) were detected in 8 of the 24 loci. The number of multiple alleles varied among the accessions and SSR loci. Several genetic hypotheses can explain the observed polymorphism (Jain et al., 2004). The major hypotheses are residual heterozygosity, accidental seed mixtures, and mixtures of landraces. Mutation and outcrossing also may contribute to heterozygosity in the genetic accessions. In this study, intravarietal polymorphism could not be detected because DNA samples were extracted from bulk leaf samples.

The average percentage of the high frequency alleles was 45.5. It ranged from 21.3 (RM249) to 90.3% (RM84). In general, a locus having a low frequency of the most common allele produced a higher number of alleles per locus. RM249 and RM72 produced the maximum number of alleles and they had the minimum frequency of a common allele, with 21.3 and 27.1%, respectively. All the frequent alleles were from japonica accessions. The most common allele at any given locus among the japonica accessions differed from the alleles in the indica and basmati accessions.

Genetic Relatedness of Accessions
We used UPGMA cluster analysis based on genetic similarity values for SSR alleles from all the rice accessions to construct a dendrogram and used 100 resamplings to estimate the bootstrap values (Fig. 1 ). The correlation between the similarity index and cophenetic value was estimated at r = 0.867, indicating a high level of reliability. The cluster analysis showed a significant genetic variation among the rice accessions studied, with a similarity coefficient varying between 0.09 and 1.00 (Fig. 1). The dendrogram revealed two distinct groups (indica plus basmati and japonica) at the similarity coefficient of 0.09. The first group clustered with 87% of accessions from japonica subspecies; a second group included 13% of the accessions corresponding to the indica subspecies and basmati accessions (Table 1). This is in agreement with results reported by Luce et al. (2001) who described the structure of rice from the European collection as almost exclusively bipolar, with 85 and 13% of the accessions belonging to the japonica and indica subspecies, respectively. The remaining 2% aggregated in an intermediate group between indica and japonica groups. In our study, the SSRs clearly showed the well-documented indica–japonica differentiation that was reflected by subspecies-specific alleles at all the loci studied.

However, the results were analyzed using 20% similarity value as the threshold for clustering where three major groups can be observed (Fig. 1). The selection of this threshold is supported by the bootstrap analysis, since the consensus tree obtained by PHYLIP, with the bootstrap values (data not shown) generated unambiguously the same three main groups that are shown in the dendrogram (Fig. 1). Group I contained mainly japonica accessions. Groups II and III represented the basmati and indica accessions, respectively. Group I (japonica) consisted of 155 accessions and had all the japonica accessions, including Nipponbare, a temperate japonica included as standard variety in the molecular analysis. The similarity coefficient among the accessions in Group I ranged from 0.21 (IR68552-100-1-2-2) to 0.92 (Ferónio and EAN N°3). Dourado (DO-88) from Brazil and the new plant type accession developed in the Philippines (IR68552-100-1-2-2) were the most genetically diverse accessions in Group I, with each one clustering independently from all other accessions. The presence of this high genetic diversity in Group I may be because of the multiple introductions of genotypes from 17 different countries into the Portuguese germplasm. Genetic diversity partitioning within and among different geographic regions was observed by Yu et al. (2003). These authors found a clear distinction in the japonica group between East and South Asia, although with a reduced number of plants tested (15 and 8 accessions, respectively). In our work, ecogeographical specific differentiation was not resolved, and accessions from different origins were mixed in the japonica group. Japonica accessions originating from Portugal were also distributed throughout Group I. Although several subgroups were formed, an intermediate subgroup (indica–japonica cross derivatives) could not be identified. However, the hybrid derivatives of indica and Portuguese japonica accessions, VB7, VB1-26, and VB36-49-3-3, grouped at a low similarity level (35%) in their subgroup. The low similarity level in intermediate accessions compared with japonica accessions was also reported by Luce et al. (2001). Furthermore, Dourado from Brazil and the intermediate new plant type accession (IR68552-100-1-2-2) developed at IRRI showed the lowest similarity coefficients (0.28 and 0.21, respectively) and were placed between the major japonica and indica groups. This also suggests the presence of intermediate accessions in the last few subgroups of the japonica group. The higher genetic distance observed for the new plant type was expected considering its highly complex genealogy (Virk et al., 2004).

Group II comprised eight basmati accessions originating from Pakistan (Table 1) and one solitary indica accession (IR56) developed in the Philippines. The similarity coefficient of this group ranged from 0.24 to 0.92, with Basmati 6129 and Basmati 6131 having the highest value. This result supports the concept that basmati rice had a long independent evolution and is genetically distinct from other groups within O. sativa, namely indica and japonica. Based on isozyme analysis, Glaszmann (1987) reported that the basmati genotypes are genetically distinct from the other groups. The same was observed by Jain et al. (2004) and Saini et al. (2004) while studying Indian basmati varieties using SSR markers. The accession IR56 had the lowest similarity coefficient (0.24) compared with other accessions in this group and was situated between the basmati and indica groups (Fig. 2 ).


Figure 2
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  		Figure 2. Two-dimensional scaling resulting from principal component analysis (NTSYS-pc) of 178 accessions using genetic diversity data for 184 alleles at 24 simple sequence response loci. Circles indicate the three major clusters formed.

 
Group III consisted of 14 indica accessions clustering at the similarity level of 0.39. In this group, 12 indica accessions were developed at IRRI, including IR74963-262-5-1-3-3 (NPT) and two entries of IR36 variety. One entry of IR 36 was available in the collection and the other one was recently obtained from IRRI and used as standard variety. These two accessions of IR 36 showed a 100% similarity. The other two accessions in this group were Milyang 40 and Suweon 281, originating from Korea. Varieties like Milyang 23 or Suweon 213, considered a Tongil-type, seem to have strong similarities to indicas. From a molecular study using SSRs and RAPDs, Kwon et al. (1999) considered the rice accessions of the Tongil-type (obtained from a crossing scheme indica/japonica/indica) as indicas. Our results with Milyang 40 and Suweon 281 are consistent with the data of Kwon et al. (1999).

The groupings identified by PCA analysis (Fig. 2) were comparable to those identified by the UPGMA tree cluster analysis (Fig. 1). The first and second principal coordinates, namely, Dim-1 and Dim-2, account for 3.23 and 2.67% respectively, of the total variation in the SSR data. Three major clusters were formed by japonica, basmati, and indica genetic accessions. Unlike the UPGMA analysis, where all accessions were assigned to a group, Ribatejo Sel.1, Rikuto-Norin 6, Riva, Sénia, Ribelo, IR56, and IR52 were out of the major clusters and appeared to be distinct from other accessions in the PCA, possibly indicating genetic differentiation. The first cluster included 150 of the 155 japonica accessions of Group I (Fig. 1). A second cluster observed in the PCA had eight basmati accessions from Pakistan (Fig. 2) as in the dendrogram (Group II). The accession IR56 was separated and placed between basmati and indica groups in the dendrogram, which is consistent with the result obtained in the PCA. Although this accession has previously clustered with the basmati group (Fig. 1), it had a low similarity value (0.24). In fact, IR56 was expected to group with indica accessions, since it does not have a basmati genetic background in its pedigree. The reason for the separation may be due to mislabeling or mixtures with basmati seeds. The remaining 14 indica accessions originated from the Philippines and Korea formed a separate cluster identified as Group III in the dendrogram, except for IR52, which was separated. In fact, IR52 was found to have a few different alleles from those of the other indica accessions studied here.

The correct determination of genetic diversity of varieties in the germplasm is important for rice breeding programs, allowing selection of the desired rice accessions for crossing. This will maximize the probability of transgressive segregation and increase the probability that unrelated accessions contribute with positive alleles at different loci. Usually, it is difficult to accurately identify varieties in the indica and japonica subspecies by their morphological characteristics; however the SSR markers used in this study detected a high level of polymorphism and were successful in distinguishing the indica and japonica accessions. Three major groups were identified based on the cluster analysis: (i) the japonica group (GI), which was the largest with 87% of the accessions and exhibited great diversity due to the diverse origins of japonica accessions, (ii) the basmati accessions (GII), and (iii) the indica accessions (GIII). Many of the accessions included in the study are morphologically similar and lack the pedigree information. Thus, the identification of the genetic distance among the accessions will be important to maximize their use in breeding programs. Furthermore, the assessment of genetic diversity of rice accessions present in the working germplasm collection will help the breeders to formulate crosses by choosing accessions with different genetic backgrounds and will assist in the development of gene-mapping populations with greater marker polymorphism.


   ACKNOWLEDGMENTS
 
We gratefully acknowledge financial support from the Fundação para a Ciência e a Tecnologia, Lisboa, Portugal, through postdoctoral and Ph.D. research fellowships to P. Jayamani (SFRH/BPD/14542/2003) and S. Negrão (SFRH/BD/10613/2002), respectively. We thank Isabel Marques (IGC) and Carla Ribeiro (EFN) for their help in the statistical analysis. We also thank scientists from the Departamento de Recursos Genéticos e Melhoramento, Estação Agronómica Nacional, Portugal, and COTArroz for providing plant materials and making available field conditions. IRRI is also acknowledged for providing seed material. We thank Dr. Dave Mackill (IRRI) for critical suggestions to improve this manuscript and Dr. Margarida O. Krause for revising the English. Finally, the reviewers of our paper are gratefully acknowledged for their comments.


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Received for publication April 11, 2006.


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