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Research Article

Genetic diversity of high performance cultivars of upland and irrigated Brazilian rice.

Received: August 11, 2017
Accepted: August 21, 2017
Published: September 21, 2017
Genet.Mol.Res. 16(3): gmr16039793
DOI: 10.4238/gmr16039793


The objective of this study was to analyze the diversity and discrimination of high-performance Brazilian rice cultivars using microsatellite markers. Twenty-nine rice cultivars belonging to EMBRAPA Arroz e Feijão germplasm bank in Brazil were genotyped by 24 SSR markers to establish their structure and genetic discrimination. It was demonstrated that the analyzed germplasm of rice presents an expressive and significant genetic diversity with low heterogeneity among the cultivars. All 29 cultivars were differentiated genetically, and were organized into two groups related to their upland and irrigated cultivation systems. These groups showed a high genetic differentiation, with greater diversity within the group that includes the cultivars for irrigated system. The genotyping data of these cultivars, with the morphological e phenotypical data, are valuable information to be used by rice breeding programs to develop new improved cultivars.


Rice (Oryza sativa L.), one of the world’s most cultivated cereals, is considered a staple of the diet of more than half the world population, with a huge socioeconomic significance (Cheng et al., 2017). World rice production has doubled over the past 25 years due to the use of advanced technologies such as new varieties with higher yields and better management practices (IRRI, 2017). However, estimates from the Food and Agriculture Organization of the United Nations indicate that rice production is expected to double with the aim to fulfil the world population needs over the next 50 years (Santos et al., 2006). The need for development of cultivars with greater productive potential stability of production is, therefore, evidenced.

Plant breeding performed by crossings among conventional varieties represents a good strategy to maximize productivity and maintain grain quality (Miranda et al., 2003; Zeng et al., 2017), as well as to reduce unwanted segregation. The available genetic diversity is an important component for the success of breeding programs favoring the selection of appropriate parents for crossings resulting on heterosis and for recombination (Breseghello and Coelho, 2013). Thus, detailed knowledge of the genetic divergence of known high-yield rice cultivars may increase the chance of developing new cultivars with higher productive capacity, resistance to diseases and pests, high grain quality, and adaptation to new environments (Yap et al., 2016; Zeng et al., 2017).

Historically, rice is one of the oldest domesticated cereals. However, official breeding programs for this crop in Brazil only began in the 1930’s. Then, the rice crop went through successive stages of selections and evaluations, producing, over the years, several cultivars of high performance and with advantages over those already existing in the market (Soares et al., 2004). In the period from 1983 to 2005, Embrapa Arroz e Feijão, and partner institutions, launched dozens of cultivars, recommended for different Brazilian regions (Breseghello et al., 1998; Abadie et al., 2005). Although there is a high proportion of parent-sharing in the rice cultivar development process, there is a morphological variation between them (Silva et al., 1999; Bueno et al., 2012), as for example cultivars that share two parents, as BR4 with the cultivars Emcapa and BRSMT Vencedora, and BRSM 1 with Jequitibá.

The narrow genetic base of the rice lines and cultivars, already discussed by several authors (Bonow et al., 2001; Pereira and Cruz, 2003; Abadie et al. 2005) has caused concern to the researchers due to the reduction of effective recombination and genetic gains. This may contribute to vulnerability to new pests, diseases and environmental changes, as well as to limit productivity levels (Abadie et al., 2005). Therefore, evaluating the genetic diversity and discrimination of the germplasm available is important to increase the efficiency of rice breeding programs.

Molecular markers are successfully used in selection of distinct genotypes for breeding, in order to increase the number of recombination events, resulting in new allelic combinations and greater chance of obtaining superior genotypes (Pereira et al., 2008). Microsatellite markers (SSR) are useful in the characterization of cultivars due to their reproducibility, multiallelism, codominant inheritance and good genome coverage, allowing the genetic discrimination even in related cultivars (Guichoux et al., 2011). SSRs have been used in the evaluation of diversity and the genetic relationship in several crops of agronomic interest, such as wheat (Mir et al., 2012), cotton (Menezes et al., 2010), maize (Qi-Lun et al., 2008), alfalfa (Flajoulot et al., 2005), soya (Brown-Guedira et al., 2000), beans (Cabral et al., 2011), and rice (Borba et al., 2009; Wei et al., 2009).

The objective of this study was to determine, through the use of microsatellite markers, the structure and genetic diversity of high performance rice cultivars, commercially released within the period from 1983 to 2005, and indicated for upland and irrigated cultivation systems.

Materials and Methods

Vegetable samples and DNA extraction

A total of 29 rice cultivars of high agronomic performance, developed and released by both private and public institutions in the period between 1983 and 2005 and recommended for several regions of the country, were analyzed. Accessions of these cultivars are stored in the germplasm bank of Embrapa Arroz e Feijão, and are available upon request (Table 1). Four plants per cultivar were analyzed separately, totaling 116 plants. The extraction of genomic DNA was obtained from young leaves according to the CTAB protocol, described by Brondani et al. (1998).

No Cultivar Year Genealogy Main characteristics Cultivation system SSR markers that detected heterogeneity
1 BR4 1983 IAC 5544/ Dourado Precoce Height of 110 cm, 70 days in average to flower, long grain class, Upland RM38, 4653, RM14
        moderately resistant to blast (leaf and neck), brown leaf spot, grain spot,    
        and scald.    
2 Encapa 1983 IAC 5544/ Dourado Precoce Height of 115 cm, 80 days in average to flower, long class, moderately Upland RM257, RM299, RM14, RM210, OG10, RM253,
        resistant to leaf and neck blast, brown leaf spot, grain spot, and scald.   RM207, RM55
3 Centro América 1987 63-83/ IAC 125 Good grain spot resistance, early flowering, 102 spikelets per panicle, Upland RM38, 4653, OG106, RM257, RM171, RM231,
        63.4% of whole grains.   OG44, RM07, RM229, RM14, RM210, RM222,
            RM309, RM253, RM207, RM252, RM11,
            RM55, RM263, RM248
4 Mearim 1989 Mutant of OS 6 from Nigeria Height from 100 cm to 110 cm, 77 days in average to flower, long grain Upland RM252, RM55
        class, moderately resistance to leaf and neck blast, and grain spot.    
        Susceptible to brown leaf spot.    
5 Rio Paraguai 1992 IAC 47/ 63-83 Height from 94 to 139 cm, 84 to 90 days in average to flower, long Upland RM38, 4653, RM14, RM222, RM11
        grain class, moderately resistant to leaf and neck blast. Moderately    
        resistant to brown leaf spot and grain spot.    
6 Acrefino 1993 Rustic/ Tapuripa Height of 120 cm, 95 days in average to flower, long class, moderately Upland RM14, RM210, RM55, RM248
        lodging resistant to, moderately resistant to leaf and neck blast, brown    
        leaf spot, grain spot and scald.    
7 Sapucaí 1994 P 901-22-7-3-2-1B/P 918-19-9-3 - 1-3-1 / / P Height of 80 cm. 126 grains per panicle. Moderately resistant to neck Irrigated 4653, OG106, RM257, RM287, RM07, RM14,
      918-25-1-4 - 2-3-IB/ P 882-12-6-5-3-1-1 blast.   RM222, RM55
8 BRSMT Vencedora 2003 IAC 5544/ Dourado Precoce Height of 73 cm, 76 days in average to flower, long-thin class, Upland RM38, 4653, OG44, RM07, RM229, RM14,
        moderately resistant to leaf and neck blast. Moderately susceptible to   RM222, RM309
        brown leaf spot, grain spot and scald.    
9 BRS Aroma 2004 Basmati370 /Lebonnet // CNA6874/ Height of 107 cm, 77 days in average to flower, long-thin class. Upland RM204, RM103, RM14
      CNA6682 Moderately resistant to leaf and neck blast and brown spot. Moderately    
        susceptible to grain leaf spot and scald.    
10 BRS Colosso 2004 Keybonnet x Aimoré (double-haploid from Height of 96 cm, 77 days in average to flower, long-thin class. Upland RM210, RM207, RM252, RM11, RM55,
      another culture) Moderately resistant to leaf and neck blast. Moderately susceptible to   RM263, RM248
        brown leaf spot, grain spot and scald.    
11 BRS MG Conai 2004 Confiança/ Aimoré Height of 87 cm, 76 days in average to flower, long-thin grain class. Upland 4653, RM14, RM210
        Moderately resistant to leaf and neck blast. Moderately susceptible to    
        brown spot, grain spot and scald.    
12 BRS MG Curinga 2005 CT 9978-12-2-2P-4/CT 10037-56-4-M-4-1- Height of 93 cm, 97 days in average to flowering, long-thin grain class. Upland 4653, RM257, OG10, RM248
      P-1//P5589-1-1-3P-1-1P/CT9356 Moderately resistant to leaf and neck blast. Moderately susceptible to    
        brown leaf spot, grain spot and scald    
13 MG-1 1984 P 1217 x P1232 Height from 85 to 100 cm, 90 to 115 days in average to flower, long- Irrigated RM38, 4653, OG106, RM257, RM287, OG44,
        thin grain class. Resistant to leaf blast, moderately resistant to neck   RM07, RM229, RM14, RM210, OG10, RM309,
        blast, brown leaf spot, grain spot and scald.   RM207, RM252, RM11, RM248
14 MG-2 1984 BG 66 x IR 26 Height from 85 to 100 cm, 90 to 115 days in average to flower, long- Irrigated RM38
        thin grain class. Resistant to leaf blast. Moderately resistant to neck    
        blast, grain spot and scald. Moderately susceptible brown leaf spot.    
15 Capivari 1994 CNA 5751 (CIAT P 4145 F3-31) Height of 80 cm, 130 days in average to flower, long-thin grain class. Irrigated RM171, RM287, OG44, RM07, RM299, RM222,
        Moderately resistant to leaf and neck blast. Grain spot resistant.   RM207, RM248
16 Ajuricaba 1986 BG 90-2 // 4440 / Colombia 1 Height from 100 to 115 cm, 75 to 95 days in average to flower, long Irrigated RM238, RM231, RM287, RM229, RM14,
        grain class. Moderately resistant to leaf and neck blast, brown leaf spot,   RM210, RM222, RM309, RM11, RM263
        grain spot, scald.    
17 Franciscano 1988 Cica 7 x F1(4440 x Pelita 1/1) Height of 92 cm, 105 to 115 days to flower, long-thin grain class. Irrigated RM287, RM14
        Moderately resistant to leaf and neck blast, brown leaf spot, grain spot,    
18 BRMS 1 1989 BR-Irga409/CICA 9 Long-thin grain class, short cycle, blast resistant, 58.7% of whole grainsIrrigated RM103, RM231, RM14, RM222, RM309
19 BRMS 2 1989 Chianung SEN 12/IR 22 Long-thin grain class, 58.1% of whole grains. Resistant to lodging, Irrigated RM171, RM231, RM287, RM07, RM229,
        blast, brown spot and narrow brown spot.   RM253, RM248
20 Aliança 1990 4440/BG90-2/TETEP Height of 90 cm, 115 days in average to flower, long-thin grain class. Irrigated RM07, RM248
        Moderately susceptible to leaf and neck blast. Moderately resistant to    
        brown leaf spot, grain spot and scald    
21 BR IPA 101 1992 Nay Lamp/IR 480/ TETEP Lodging resistant and tolerance to blast. Irrigated RM257, RM14
22 Javaé 1993 P 3085//IR 5853-118-5/IR19743-25-2-2-3-1 Height from 90 to 100 cm, 80 days in average to flower, long-thin grain Irrigated 4653, RM287, OG44, RM07, RM299, RM14,
        class. Resistant to leaf blast, susceptible neck blast, moderately resistant   RM263, RM248
        to brown leaf spot, grain spot and scald.    
23 Urucuia 1994 Nanicão/ cica 8/MG1 Height from 82 cm, 123 days in average to flower. Resistant to leaf and Irrigated RM38, RM14, RM55
        neck blast, grain spot.    
24 Samburá 1995 Nanicão/ BG 90-2//MG1 Flowering around 136 days after planting, maturation cycle 170 days. Lowland RM38, OG106, RM257, RM103, RM171,
        Moderately lodging resistant, resistant to leaf and neck, blast, brown   RM231, RM287, OG44, RM07, RM229, RM14,
        spot and moderately resistant to grain spot.   OG10, RM55, RM248
25 São Francisco 1996 5732// 3234/ Costa Rica Height of 80 cm, 100 days to bloom, long-thin grain class. Moderately Irrigated RM07, RM207, RM11, RM248
        resistant to leaf and neck blast, brown leaf spot, grain spot and scald.    
26 Jequitibá 1997 Cica 9 / BR-IRGA 409 Height of 92 cm, 94 days to bloom, long-thin grain class. Moderately Irrigated RM55
        resistant to leaf and neck blast, brown leaf spot, grain spot and scald.    
27 SCS BRS 113 Tio 2002 CAN 8644 (CN–IRAT 4M/2/1-75-B-B-2-2- Height of 98 cm, 111 days to bloom, long-thin grain class. Susceptible Irrigated RM14, RM248
  Taka   B) to leaf and neck blast.    
28 BRS MG 2002 17719,5739 x IR21015-72-3-3-3-1 Height of 90 cm, 94 to 105 days to bloom, long-thin grain class. Irrigated RM231, RM14, OG10, RM207, RM11, RM263
  OUROMINAS     Moderately susceptive to leaf and neck blast, brown spot, grain spot and    
29 BRS MG Seleta 2004 CT 7415 / P4743 // CT 8154 Height of 95 cm, 100 to 105 days to bloom, long-thin grain class. Irrigated RM07, RM14, RM252
        Moderately resistant to leaf and neck blast, grain spot and scald.    
        Resistant to brown leaf spot.    

Table 1. Main characteristics of 29 rice cultivars, released between the years 1983 to 2005, and the heterogeneity detected for the SSR markers.

Amplification of fragments

A total of 24 microsatellite primer pairs were used for genotyping in a multiplex amplification system (Table 2). The selection of these markers was based on their discriminative power, simple amplification pattern, and for having independent segregation (Borba et al., 2009). The reactions were prepared with Multiplex PCR Kit (Qiagen) at a final volume of 5 μL, containing 3 ng DNA, 1X Master mix, Q-solution 0.5X various primer pairs concentrations (forward and reverse) according to Borba et al. (2009), and RNase-free water. The amplification reactions were conducted in a thermocycler 9700 (Life Technologies) with the following schedule: initial denaturation at 95°C for 15 min, followed by 40 amplification cycles, with each cycle consisting of denaturation at 94°C for 30 s, annealing at 56°C for 90 s, and extension at 72°C for 90 s; and, finally, a final extension at 72°C for 10 min. The amplification products were separated by capillary electrophoresis on an ABI 3100 DNA sequencer (Life Technologies). Locus genotyping (in bp) was performed through the GeneMapper 3.5 program (Applied Biosystems), using the ROX 500 internal molecular weight marker (Life Technologies).

Panel Marker Fluorescence Amplitude (bp) Motif Chromosome Authors
1 4653 6-FAM 101-167 (AAG)25 12 Rangel et al., 2007
1 OG106 6-FAM 175-249 (CT)27 9 Brondani et al., 2001
1 RM103 NED 308-344 (GAA)5 6 Temnykh et al., 2000
1 RM257 NED 104-192 (CT)24 9 Chen et al., 1997
1 RM07 PET 170-186 (GA)19 3 Panaud et al., 1996
  RM287 PET 97-117 (GA)21 11 Temnykh et al., 2000
1 RM38 VIC 236-264 (GA)16 8 Chen et al., 1997
1 RM204 VIC 102-174 (CT)44 6 Chen et al., 1997
2 RM210 6-FAM 138-160 (CT)23 8 Chen et al., 1997
2 RM222 6-FAM 199-223 (CT)18 10 Chen et al., 1997
2 RM253 NED 113-143 (GA)25 6 Chen et al., 1997
2 RM309 NED 161-173 (GT)13 12 Temnykh et al., 2000
2 RM171 PET 325-349 (GATG)5 10 Akagi et al., 1996
2 RM231 PET 168-194 (CT)16 3 Chen et al., 1997
2 RM14 VIC 173-246 (GA)18 1 Panaud et al., 1996
2 OG10 VIC 88-124 (CT)29 9 Brondani et al., 2001
3 RM207 6-FAM 104-142 (CT)25 2 Chen et al., 1997
3 RM252 6-FAM 192-276 (CT)19 4 Chen et al., 1997
3 RM11 NED 100-142 (GA)17 7 Panaud et al., 1996
3 RM55 NED 217-237 (GA)17 3 Chen et al., 1997
3 OG44 PET 157-175 (CT)4-23bp- (CT)22-(GT)4(GC)6 3 Brondani et al., 2001
3 RM229 PET 82-132 (TC)11 (CT)5C3 (CT)5 11 Chen et al., 1997
3 RM248 VIC 79-109 (CT)25 7 Chen et al., 1997
3 RM263 VIC 145-201 (CT)34 2 Chen et al., 1997

Table 2. Microsatellite markers used in the evaluation of the 29 rice cultivars.

Data analysis

The descriptive analysis of the cultivars genetic diversity was carried out using estimates of the allelic frequencies of the polymorphic loci, number of alleles per locus (NA), number of private alleles (Ap - alleles found in a single plant or cultivar), gene diversity or expected heterozygosity (HE) and observed heterozygosity (HO), fixation index (FIS), probability of genetic identity (PI) and probability of paternity exclusion (PE) from single locus and multilocus using the GenAlEx v6.5 program (Peakall and Smouse, 2012).

Genetic divergence (GD) among cultivar pairs was calculated based on Wright’s modified Roger’s coefficient, using the NTSYS program. The GD matrix was then used to design a dendrogram employing neighbor joining clustering method using the MEGA7 program. The genetic structure was analyzed from the Bayesian model implemented by the program Structure (Pritchard et al., 2000), with the “admixture” options and correlated allelic frequencies. Ten runs were performed for the tested values of K (1 to 10), with burn-in of 50,000, followed by 500,000 interactions. The number of genetic groups (ΔK) was determined according to the method of Evanno et al. (2005), using the program Structure harvester (Earl and VonHoldt, 2012). The analysis of molecular variance (AMOVA) was performed to verify the partitioning of genetic variation between and within the cultivars, through the GenAlEx program (Peakall and Smouse, 2012). In this particular analysis, each allele was labeled with (1), when present, and (0) when absent. Later, an AMOVA was performed, based on the identification of the presence or absence of genetic structure by the Structure software, and the genetic diversity indexes were re-analyzed for the genetic structure found.

Results and Discussion

All the 24 microsatellite markers analyzed were polymorphic, totaling 163 alleles, with a mean of 6.83 alleles per locus, ranging from two (RM309) to ten alleles (4653, OG106 and RM248) per locus of SSR (Table 3). Similar numbers of alleles per locus (8.0 and 6.6) were found in accessions from an Indian germplasm bank of aromatic rice and traditional Cuban rice varieties, respectively (Roy et al., 2015). When compared for a germplasm formed of rice lines from different countries was lower (12 per locus) (Borba et al., 2010).

Loci Size (bp) NA HE HO FIS PI PE
RM204 106-176 6 0.359 0.026 0.928 0.430 0.348
RM038 240-261 8 0.764 0.000 1.000 0.079 0.783
4653 084-168 10 0.784 0.009 0.989 0.074 0.789
OG106 197-231 10 0.841 0.000 1.000 0.046 0.852
RM257 142-174 9 0.846 0.000 1.000 0.044 0.856
RM103 328-336 4 0.576 0.000 1.000 0.255 0.452
RM171 321-344 4 0.574 0.009 0.985 0.276 0.415
RM231 166-192 6 0.807 0.000 1.000 0.068 0.788
RM287 101-114 5 0.667 0.172 0.974 0.174 0.580
OG044 153-171 5 0.354 0.052 0.854 0.441 0.327
RM007 166-184 7 0.777 0.000 1.000 0.085 0.751
RM229 096-128 7 0.744 0.000 1.000 0.109 0.698
RM014 169-191 8 0.483 0.052 0.893 0.300 0.459
RM210 138-164 8 0.640 0.000 1.000 0.158 0.646
OG010 092-126 6 0.777 0.000 1.000 0.089 0.732
RM222 203-225 7 0.812 0.009 0.989 0.064 0.798
RM309 169-171 2 0.459 0.000 1.000 0.399 0.268
RM253 131-141 4 0.447 0.000 1.000 0.340 0.405
RM207 116-144 8 0.829 0.000 1.000 0.054 0.828
RM252 194-254 7 0.664 0.000 1.000 0.174 0.589
RM011 119-144 7 0.716 0.017 0.976 0.112 0.710
RM055 218-299 7 0.724 0.017 0.976 0.108 0.717
RM263 155-201 8 0.802 0.000 1.000 0.069 0.787
RM248 080-105 10 0.756 0.000 1.000 0.086 0.767
Total - 163 - - - 4.3 x 10-22 1.00
Mean   6.83 (±0.42) 0.675 (±0.032) 0.009 (±0.003) 0.982 (±0.008) - -

Table 3. Descriptive analysis for SSR markers in 29 rice cultivars.

The genetic diversity calculated in the 29 rice cultivars studied was high (HE = 0.675 ± 0.032), ranging from 0.354 in the locus OG44 to 0.846 in the locus RM257. Roy et al. (2015), Borba et al. (2009, 2010) also found expected average heterozygosity close to that found in the present study in different accessions of the germplasm bank in India (0.67) and foreign, traditional and improved accessions from the Embrapa Rice Core Collection (0.67). Although the material presents a high level of diversity, it also presents low levels of observed heterozygosity evidenced by the average value of HO = 0.009 (± 0.003). It was zero in 15 of the 24 SSRs locus evaluated, and in the others loci ranged from 0.009 in the SSR locus 4653, RM171, and RM222, to 0.128 in loci RM287. These low HO values corroborate with the predominantly autogamous reproductive system of the species, also indicated by the high fixation index, FIS = 0.982 (± 0.008). These values of HE, HO and FIS demonstrate that the genetic diversity found is organized in homozygous genotypes, indicating the purity of the cultivars released and thus their homogeneity and genetic stability.

The heterogeneity of the cultivars was evaluated considering genotype variation within the four individual plants per cultivar, for each locus. All rice cultivars included in this study had at least one heterogeneous SSR locus with heterogeneity. The number of heterogeneous loci ranged until 20, as in the case of the “Centro América cultivar (Table 1). For 11 of the 29 cultivars, the heterogeneity was attributed to heterozygotes observed in one or two locus. For the other cultivars the cause of heterogeneity were homozygotes for different alleles in the different plants of the cultivar, corroborating with the low value of HO.

The cultivars Centro América, Ajuricaba, MG-1 and Samburá presented higher number of SSR locus indicating heterogeneity, with 20 (83%), 17 (71%), 16 (67%), and 14 (58%) of the analyzed markers, respectively. The genetic variation found within each plant and cultivar corresponds to about 1.0 and 20%, respectively, as indicated by AMOVA, while 80% is concentrated among the cultivars, presenting a high genetic differentiation value (FST) of 0.796 (P value < 0.01 for 9999 permutations). Additionally, no identical cultivars were observed, therefore the 24 SSRs presented a high discriminatory power. This is reinforced by the average PI value (4.4 x 10-22) and multi locus PE value (1.00), as well as single locus values, which ranged from 0.044 (locus RM257) to 0.441 (loci OG044), and 0.268 (locus RM309) to 0.856 (locus RM257), respectively (Table 3).

Thirty-three alleles were private (Ap), those that were present only in a specific cultivar. This total Ap represents 20% of the amplified alleles. The cultivars BRS Aroma, BRS Colosso, and MG-1 presented the highest number of private alleles, with five, four, and four of these 33 private alleles, respectively (Table 4). The greater the number of private alleles found in a cultivar, the more divergent its origin, thus demonstrating a broader genetic base of the material analyzed, therefore relevant to breeding programs.

Cultivars AP Loci SSR_allele size (bp)
Acrefino 2 RM 204_176; RM 257_174
BR Aroma 5 RM204_152 e 154; RM38_257; 4653_146; RM103_334
BRS Colosso 4 RM229_128; RM210_140; RM253_131; RM252_246
BRS MG Curinga 1 OG10_100
Emcapa 1 RM229_126
BRMS2 1 OG10_126
Ajuricaba 1 RM210_164
Aliança 1 RM07_180
Capivari 1 RM171_321
BR IPA 101 1 RM263_185
Javaé 2 RM11_142; RM263_183
MG-1 4 OG106_209; RM257_154;OG44_155;RM248_095
São Francisco 1 RM207_124
Sapucaí 2 OG106_205; RM55_299
BRS MG Seleta 2 RM252_254; RM248_105
Urucuia 1 RM14_185
MG-2 1 RM204_118
BRSMT Vencedora 2 4653_156; RM210_158
Total 33  

Table 4. Description of the locus that presented private alleles (Ap) for cultivars and identification of the allele size.

The 29 rice cultivars showed an intermediate genetic divergence, as indicated by the estimated mean GD value of 0.535, and 68% of the pairwise comparisons between genotypes with GD greater than or equal to 0.50. The lowest value for the genetic distance (0.184) was found between cultivars Aliança and Urucuia, both cultivars of the upland crop system, while the highest distance value (0.666) was detected between cultivars BR4 and BRSMG Seleta, one of the cultivars of an upland system and another of an irrigated system, respectively. The evaluated cultivars were organized into two groups, both by neighbor joining cluster analysis (Figure 1) and Bayesian model (Figure 2). The green group (Figure 2) was formed by 9 cultivars of the upland system, and the red group by 18 cultivars of an irrigated system and 1 of the upland (Mearim). The cultivar Acrefino forms an intermediate branch to the upland and irrigated pools. The cultivar Acrefino was developed for cultivation in the state of Acre for the upland cultivation system, but is favored by an average rainfall of 2000 mm/year.


Figure 1: Dendrogram of 29 elite rice cultivars, based on Roger’s distance modified using the neighbor-joining method. The red spots represent irrigated rice cultivars, and the green spots represent rice cultivars of the upland system.

In the analysis by the Bayesian model, it was also verified the formation of two groups (ΔK = 2), identical to those observed in the dendrogram. The cultivars were classified into each group indicated by the upland or irrigated system, with high values of shared ancestry, with mean value of 0.997, except for the Mearim, an upland cultivar classified, but ascribed to the irrigated gene pool group in both cluster analyzes. The Acrefino cultivar and one of the four plants of the Central America cultivar presented intermediate values [0.477 (A), 0.523 (B), 0.458 (A), 0.542 (B), respectively] of shared ancestry, indicating admixture in similar proportions of both groups (Figure 2). Excluding the admixture plants, the structuring of the cultivars (ΔK=2) defined in the cluster analyzes was significantly elevated and different from zero, with a FST value of 0.349 (P < 0.05).


Figure 2: Genetic structure of the 116 rice plants representing 29 cultivars. Cultivars belonging to the irrigated cropping system are evidenced in red and cultivars from upland systems, in green.

A genetic structure similar and organized for cultivation (irrigated or upland) system was observed by Borba et al. (2010), when analyzed accessions from breeding programs of Brazil and other countries. The stratification observed demonstrated the driven and independent selection in breeding programs for each system of cultivation, that historically is based according the distinct genetic pool from indicate (irrigated) and japonica (upland) subspecies.

The diversity was greater within group composed by most of the irrigated rice cultivars, represented in red in Figure 2 (NA = 114, Ap = 73, HE = 0.547), when compared to the group of the upland rice represented in green (NA = 85, Ap = 44, HE = 0.475) (Table 5). Similar results were found by Borba et al. (2010) both in foreign and Brazilian accessions. Probably this was due to the use of genetically related parents in the upland rice group (japonica subspecies), which has narrow genetic variability in relation to indicate subspecies (Yu et al., 2013).

Cropping system Period S P% NA Ap HO HE
Upland 1980’s 4 70.8 59 4 0.008 (±0.006) 0.332 (±0.053)
  1990’s 1 20.8 30 0 0.000 (±0.000) 0.113 (±0.047)
  2000’s 4 83.3 68 14 0.008 (±0.008) 0.433 (±0.055)
  Subtotal 9 91.7 85 44 0.007 (±0.004) 0.475 (±0.049)
Irrigated 1980’s 9 100 91 20 0.010 (±0.006) 0.560 (±0.036)
  1990’s 7 87.5 75 10 0.012 (±0.007) 0.405 (±0.041)
  2000’s 3 62.5 49 2 0.003 (±0.003) 0.304 (±0.056)
  Subtotal 19 100 114 73 0.010 (±0.004) 0.547 (±0.036)

Table 5. Descriptors of genetic diversity of Brazilian rice cultivars released in the 1980’s, 1990’s, and 2000’s organized in upland and irrigated groups.

In the temporal comparison of the genetic diversity descriptors, separately by cultivation system, in the 1980’s, 1990’s, and 2000’s, there was a slight diversity increase in the cultivars of upland rice and a decline in the cultivars of irrigated rice (Table 5). The HO was similarly low and declining among the decades for the cultivars of both cultivation systems, demonstrating the rigor to produce pure seeds of these cultivars. A high and significant genetic differentiation of the cultivars in both systems was observed (upland FST = 0.326 and irrigated FST = 0.209, P value = 0.001), in addition to a significant and growing increase in genetic differentiation over the decades (Table 6).

Up-80 Up-90 Up-00 Ir-80 Ir-90 Ir-00
Up-80 0          
Up-90 0.195 0        
Up-00 0.212 0.319 0      
Ir-80 0.295 0.183 0.391 0    
Ir-90 0.376 0.238 0.480 0.137 0  
Ir-00 0.444 0.411 0.556 0.240 0.341 0

Table 6. Genetic differentiation (FST) among rice cultivars launched in the 1980’s, 1990’s, and 2000’s organized in upland (Up) and irrigated (IR) groups.

Based on a core set of 24 highly polymorphic SSR markers, we have determined the genetic relationship and the degree of genetic diversity among a collection of 29 rice cultivars possessing a wide variability of agromorphological and physiological traits. Together with this data, we indicated the occurrence of lower rates of admixture between irrigated and upland cultivars. The results of this study complement the phenotypical data of this important germplasm, and provide a valuable tool for use of rice breeding program.

Conflicts of interest

The authors declare no conflict of interest.

About the Authors

Corresponding Author

G.R.C. Coelho

Laboratório de Biotecnologia Vegetal, Embrapa Arroz e Feijão, Santo Antônio de Goiás, GO, Brasil

[email protected]


  • Abadie T, Cordeiro CMT, Fonseca JR, Alves RBN, et al. (2005). Construção de uma coleção nuclear de arroz para o Brasil. Pesqui. Agropecu. Bras. 40: 129-136.
  • Akagi H, Yokozeki Y, Inagaki A and Fujimura T (1996). Microsatellite DNA markers for rice chromosomes. Theor. Appl. Genet. 93: 1071-1077.
  • Bonow S, Augustin E, Franco DF, Peters JA, et al. (2001). Caracterização isoenzimática de genótipos de arroz. Pesqui. Agropecu. Bras. 36: 91-300.
  • Borba TC, Brondani RPV, Rangel PHN and Brondani C (2009). Microsatellite marker-mediated analysis of the EMBRAPA Rice Core Collection genetic diversity. Genetica 137: 293-304.
  • Borba TC, Brondani RPV, Breseghello F, Coelho ASG, et al. (2010). Association mapping for yield and grain quality traits in rice (Oryza sativa L.). Genet. Mol. Biol. 33: 515-524.
  • Breseghello F, Castro EM and Morais OP (1998). Cultivares de arroz. In: Tecnologias para o arroz de terras altas (Breseghello F and Stone LF, eds.). Embrapa Arroz e Feijão, Santo Antônio de Goiás, 41-53.
  • Breseghello F and Coelho ASG (2013). Traditional and modern plant breeding methods with examples in rice (Oryza sativa L.). J. Agric. Food Chem. 61: 8277-8286.
  • Brondani C, Brondani RPV, Rangel PHN and Ferreira ME (2001). Development and mapping of Oryza glumaepatula-derived microsatellite markers in the interspecific cross Oryza glumaepatula x O. sativa. Hereditas 134: 59-71.
  • Brondani RPV, Brondani C, Tarchini R and Grattapaglia D (1998). Development, characterization and mapping of microsatellite markers in Eucalyptus grandis and E. urophylla. Theor. Appl. Genet. 97: 816-827.
  • Brown-Guedira GL, Thompson JA, Nelson RL and Warburton ML (2000). Evaluation of genetic diversity of soybeans introductions and North American ancestors using RAPD and SSR markers. Crop Sci. 40: 815-823.
  • Bueno LG, Vianello RP, Rangel PHN, Utumi MM, et al. (2012). Adaptabilidade e estabilidade de acessos de uma coleção nuclear de arroz. Pesqui. Agropecu. Bras. 2: 216-226.
  • Cabral PD, Soares TC, Lima AB, de Miranda FD, et al. (2011). Genetic diversity in local and commercial dry bean (Phaseolus vulgaris) accessions based on microsatellite markers. Genet. Mol. Res. 10: 140-149. https://doi. org/10.4238/vol10-1gmr993
  • Chen X, Temnykh S, Xu Y, Cho YG, et al. (1997). Development of a microsatellite framework map providing genome-wide coverage in rice (Oryza sativa L.). Theor. Appl. Genet. 95: 553-567.
  • Cheng A, Mayes S, Dalle G, Demissew S, et al. (2017). Diversifying crops for food and nutrition security - a case of teff. Biol. Rev. Camb. Philos. Soc. 92: 188-198.
  • Earl DA and VonHoldt BM (2012). Structure harvester: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 4: 359-361.
  • Evanno G, Regnaut S and Goudet J (2005). Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol. Ecol. 14: 2611-2620.
  • Flajoulot S, Ronfort J, Baudouin P, Barre P, et al. (2005). Genetic diversity among alfalfa (Medicago sativa) cultivars coming from a breeding program, using SSR markers. Theor. Appl. Genet. 111: 1420-1429. s00122-005-0074-4
  • Guichoux E, Lagache L, Wagner S, Chaumeil P, et al. (2011). Current trends in microsatellite genotyping. Mol. Ecol. Resour. 11: 591-611.
  • IRRI (2017), International Rice Research Institute. Available at [].
  • Menezes IPP, Barroso PAV, Hoffmann LV, Lucena VS, et al. (2010). Genetic diversity of mocó cotton (Gossypium hirsutum race marie-galante) from the northeast of Brazil: implications for conservation. Botany 88: 1-9.
  • Mir RR, Kumar J, Balyan HS and Gupta PK (2012). A study of genetic diversity among Indian bread wheat (Triicumaestivum L.) cultivars released during last 100 years. Genet. Resour. Crop Evol. 59: 717-726.
  • Miranda GV, Coimbra RR, Godoy CL, Souza LV, et al. (2003). Potencial de melhoramento e divergência genética de cultivares de milho-pipoca. Pesqui. Agropecu. Bras. 38: 681-688.
  • Panaud O, Chen X and McCouch SR (1996). Development of microsatellite markers and characterization of simple sequence length polymorphism (SSLP) in rice (Oryza sativa L.). Mol. Gen. Genet. 252: 597-607.
  • Peakall R and Smouse PE (2012). GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research--an update. Bioinformatics 28: 2537-2539.
  • Pereira HS, Santos JB, Souza TP and Lima IA (2008). Seleção fenotípica e assistida por marcadores moleculares de famílias de feijoeiro-comum com alta produtividade. Pesqui. Agropecu. Bras. 43: 1551-1558.
  • Pereira JJ and Cruz CD (2003). Comparação de métodos de agrupamento para o estudo da diversidade genética de cultivares de arroz. Rev. Ceres 50: 41-60.
  • Pritchard JK, Stephens M and Donnelly P (2000). Inference of population structure using multilocus genotype data.Genetics 155: 945-959.
  • Qi-Lun Y, Ping F, Ke-Cheng K and Guang-Tang P (2008). Genetic diversity based on SSR markers in maize (Zea mays L.) landraces from Wuling mountain region in China. J. Genet. 87: 287-291.
  • Rangel PN, Brondani RPV, Coelho ASG, Rangel PHN, et al. (2007). Comparative linkage mapping of Oryza glumaepatula and Oryza sativa interspecific crosses based on microsatellite and expressed sequence tag markers. Genet. Mol. Biol.614622.
  • Santos AB, Stone LF and Vieira NRA (2006). A cultura do arroz no Brasil. 2nd edn. Embrapa Arroz e Feijão, Brazil. Silva EF, Montalván R and Ando A (1999). Genealogia dos cultivares brasileiros de arroz de sequeiro. Bragantia 2: 281-
  • Soares PC, Soares AA, Morais OP, Castro EM, et al. (2004). Cultivares de arroz de terras altas e de várzeas recomendadas para Minas Gerais. Informe Agropecuário. 222: 24-33.
  • Temnykh S, Park WD, Ayres N, Cartinhour S, et al. (2000). Mapping and genome organization of microsatellites in rice (Oryza sativa L.). Theor. Appl. Genet. 100: 697-712.
  • Zeng D, Tian Z, Rao Y, Dong G, et al. (2017). Rational design of high-yield and superior-quality rice. Nat. Plants 3: 17031.
  • Yap R, Hsu YC, Wu YP, Lin YR, et al. (2016). Multiplex PCR genotype for five bacterial blight resistance genes applied to marker-assisted selection in rice (Oryza sativa). Plant Breed. 135: 309-317.
  • Yu P, Yuan X, Xu Q, Wang C, et al. (2013). Genetic structure and Indica/Japonica component changes in major inbred rice varieties in China. Rice Sci. 20: 39-44.
  • Wei Z, Hu W, Lin Q, Cheng X, et al. (2009). Understanding rice plant resistance to the Brown Planthopper (Nilaparvata lugens): a proteomic approach. Proteomics 9: 2798-2808.

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