Research Article

Genetic diversity of Saccharum complex using ISSR markers

Received: July 28, 2017
Accepted: August 18, 2017
Published: September 21, 2017
Genet.Mol.Res. 16(3): gmr16039788
DOI: 10.4238/gmr16039788


Sugarcane (Saccharum sp, Poaceae) is native to Southeast Asia, and due to growing demand as raw material, its cultivation recently expanded to new frontiers. The genetic diversity analysis is essential for targeting strategies in the formation and maintenance of a germplasm. This study aimed to assess the genetic diversity of 26 accessions of sugarcane from the Active Germplasm Bank of Embrapa Coastal Tablelands, using inter-simple sequence repeat (ISSR) molecular markers. Sixteen primers were used, resulting in 87 fragments with 91.13% of polymorphism. The similarity of the individuals ranged between 0.22 and 0.87. Individuals RB867515 and RB92579 were closer genetically, and the most distant ones were PI240785 and NSL 291970. Four distinct clusters were formed, using UPGMA. This information can be used to prioritize the selection of accessions for the conduction of hybridization in breeding and germplasm exchange actions.


Sugarcane (Saccharum sp) is a plant of the Poaceae family, native to Southeast Asia, and cultivated in tropical and subtropical regions (Casu et al., 2004). Its cultivation expanded to new frontiers recently due to growing demand as raw material (biomass) for ethanol production and power generation, as a source of several new added-value products along with sugar production (Santos et al., 2012).

The genus Saccharum includes six species: noble cane, S. officinarum (2n = 80), two wild species, S. robustum (2n = 60-80) and S. spontaneum (2n = 40-128), and three secondary species, S. barberi (2n = 81-124), S. sinense (2n = 111-120) and S. edule (2n = 60, 70, 80). S. officinarum, S. spontaneum and S. robustum represent the basic species, and S. barberi and S. sinense are secondary species probably derived from the hybridization of S. officinarum and S. spontaneum. All species cited along with the genera Erianthus, Miscanthus, Narenga, and Sclerostachya constitute the “Saccharum complex” (Daniels et al., 1975).

As there is the need to diversify the genetic basis of modern cultivars to meet an increasingly competitive market, mainly because they derive from exclusive backcrosses involving a few clones of S. officinarum and S. spontaneum (Shrivastava and Srivastava, 2016), it is extremely important to characterize cultivars worldwide (Almeida et al., 2009).

As a result, breeding programs of sugarcane have emerged worldwide. In Brazil, the Brazilian Agricultural Research Corporation (EMBRAPA) started to study energy derived from sugarcane to provide genetic material with high levels of biomass adapted to different regions of cultivation. Embrapa Coastal Tablelands located in Sergipe, Northeast region, has kept 128 accessions in an Active Germplasm Bank, including the genera Saccharum, Erianthus, and Miscanthus, derived from collections in Brazil and from imports and exchanges with international institutions, where the molecular characterization for the identification of genetic diversity has been held.

The possibility of accessing the genetic variability directly at DNA level enables precise techniques that assist the process of intellectual protection of genetic materials. The molecular markers are important tools for the breeding of plants and aim at the mapping of genes, genetic diversity analysis, disease diagnostics, and taxonomic and evolutionary studies (Wünsch and Hormaza, 2007). In sugarcane, some studies have been conducted to identify the genetic diversity among genotypes using AFLP (Selvi et al., 2006), RAPD (Khan et al., 2009; Ullah et al., 2013), chloroplast microsatellite markers (coSSR) (Raj et al., 2016), SSR (Pandey et al., 2011) and inter-simple sequence repeat (ISSR) (Srisvastava and Gupta, 2008; Almeida et al., 2009; Devarumath et al., 2012; Rao et al., 2016). RAPD and ISSR have been amplified for water stress tolerance in sugarcane varieties (Fahmy et al., 2008).

The aim of this study was to assess the genetic diversity of sugarcane accessions from the Active Germplasm Bank of Embrapa Coastal Tablelands using ISSR molecular markers, for selection of accessions aiming the conduction of hybridization in breeding programs and germplasm exchange.

Materials and Methods

Twenty-four sugarcane accessions established in vitro were used, from the second subculture, provided by the National Center for Genetic Resources Preservation/ARS/ USDA, Fort Collins, CO, USA, and two varieties “RB” from Inter-University Network for the Development of Sugarcane Industry, characterized as varieties cultivated in Brazil (Table 1). All accessions are from the Active Germplasm Bank of the Saccharum Complex from Embrapa Coastal Tablelands, located in the Experimental Field Jorge Prado Sobral, located in Nossa Senhora das Dores, Sergipe, Brazil, (10°29’27’’S; 37°11’34’’W).

Number Identification of accession Species
1 Q 45866 Saccharum officinarum
2 Q 46199 Saccharum robustum
3 Q 45251 Saccharum robustum
4 Q 42509 Saccharum spp
5 Q 45911 Saccharum officinarum
6 Q 45864 Saccharum officinarum
7 Q 44830 Saccharum officinarum
8 Q 45337 Saccharum hybrid
9 Q 45416 Saccharum spp
10 Q 44890 Saccharum officinarum
11 Q 44833 Saccharum officinarum
12 Q 45869 Saccharum officinarum
13 Q 42433 Saccharum hybrid
14 PI 240785 Q 45923 NG 57-208 Saccharum robustum
15 PI 197800 Sumatra #2 Saccharum spontaneum
16 Q 36830 MOL 6091 Saccharum sp
17 GH-49 UNKR65P35 Saccharum robustum
18 MIA 35303 MOL 6091 Saccharum robustum
19 NSL 291970 Glagh 1286 Saccharum spontaneum
20 PI 88652 NG 28213 Saccharum officinarum
21 MIA 35301 MOL 6089 Saccharum robustum
22 RB 867515 Saccharum sp
23 RB 92579 Saccharum sp
24 PI 495109 Q46207 IN 84-045 Saccharum robustum
25 PI 286657 SES-006 Saccharum spontaneum
26 PI 29109 Saccharum sinensis

Table 1. Characteristics of 26 accessions of “Saccharum Complex” from the Active Germplasm Bank of Embrapa Coastal Tablelands, Brazil.

Young leaves from 26 accessions were collected, identified, packed in Styrofoam plastic bags with ice, and stored at -80°C at the Molecular Biology Laboratory of Embrapa Coastal Tablelands.

DNA extraction followed the 2% cetyltrimethyl ammonium bromide (CTAB) protocol (Romano and Brasileiro, 1999). Seventeen ISSR primers were used (University of British Columbia, Vancouver, Canada) to detect polymorphism at a concentration of 15 ng/ mL. Primers were randomly selected. Polymerase chain reaction (PCR) amplifications were carried out in a thermocycler (Veriti, Applied Biosystems). Samples were initially subjected to denaturation at 94°C for 4 min, followed by 37 amplification cycles. During each cycle, samples were subjected to denaturation at 94°C for 1 min, annealing at different temperatures for 2 min, and extension at 72°C for 2 min.

Each ISSR reaction was carried out in a final volume of 20 mL containing 1.5 mL 15 ng/mL DNA; 0.2 mL Taq DNA polymerase (Invitrogen); 0.6 mL MgCl2; 0.4 mL dNTP; 1 mL primer (oligonucleotides); 2 mL buffer; and 14.3 mL ultrapure water.

Fragments were visualized on 2% agarose gel (1X TBE; 89 mM Tris; 89 mM boric acid; 2.5 mM EDTA, pH 8.3) in a horizontal electrophoresis system run at a constant voltage of 182V, 91 mA, and 17 W for 115 min. For size standardization of bands, 5 μL 100-bp molecular weight marker was used. Gels were stained with ethidium bromide solution (0.02 mL/mL water), for approximately 30 min, and then visualized under UV light, using the Loccus L-pix HE photodocumentation device (Loccus Biotecnologia, Brazil).

Gel analysis resulted in a binary matrix according to the presence (1) or absence (0) of fluorescent bands. The percentage of polymorphic loci was calculated from the number of amplified bands. Similarity coefficients were calculated using the Jaccard index (Jaccard, 1908).

To determine the minimum number of amplified fragments needed for studies on genetic diversity, estimates were obtained from correlation (r) of similarity matrix values and the stress value (E), which indicates the adjustment between the original matrix and the simulated matrix. The optimal number of fragments was calculated by means of the GENES software (Cruz, 2007) and considered satisfactory for the analysis when the stress value was less than 0.05 (Kruskal, 1964) and the correlation closer to 1.

From the similarity matrix, a dendrogram was generated by the unweighted pairgroup method with arithmetic mean (UPGMA). Bootstrapping was carried out with 10,000 replicates using the FreeTree software (Pavlícek et al., 1999). The TreeView software was also used to generate the dendrogram (Pavlícek et al., 1999). Samples were clustered considering the principal coordinates analysis (PCoA), with the aid of the Genalex v.p software (Peakall and Smouse, 2006). The Shannon index (I) (Brown and Weir, 1983) and the expected heterozygosity (HE) (Lynch and Milligan, 1994) were also estimated using the Genalex 6.3 software (Peakall and Smouse, 2006).

Results and Discussion

The individuals were analyzed based on 87 loci obtained from 16 ISSR primers. The optimal number to obtain the desired precision in the analysis of genetic diversity from Saccharum sp was after 83 fragments, when the stress value was 0.055 and the correlation (r) 0.991 (Figure 1).


Figure 1: Correlation coefficient and number of fragments using ISSR markers between 26 individuals of sugarcane belonging to Embrapa Coastal Tablelands based on genetic similarities obtained by the bootstrap method.

In this study, there was a directly proportional relationship between the number of amplified fragments and the correlation magnitude of the values of the original similarity matrix obtained from resampling with different numbers of amplified fragments. Thus, from the optimal number of fragments obtained (83), the correlation coefficient value approached the maximum value, which proves the consistency of the data with the number of primers used and the number of fragments obtained, being sufficient for the analyses of genetic diversity.

Among the 16 primers tested in the amplification of samples, 87 loci were generated, of which 80 primers were polymorphic (91.13%). In each ISSR reaction, the total number of amplified fragments ranged from three (UBC-828, UBC-845, UBC-855) to twelve (UBC-815) (Table 2 and Figure 2).

Primers Sequence (5'-3') AT (°C) NFB %P I HE
807 AGA GAG AGA GAG AGA GT 47 4 100 0.53 0.36
812 GAG AGA GAG AGA GAG AA 54.8 7 100 0.48 0.31
815 CTC TTC TCT CTC TCT CTG 47.6 12 100 0.49 0.32
816 CAC ACA CAC ACA CAC AT 54.8 5 100 0.37 0.22
818 CAC ACA CAC ACA CAC AG 57.2 4 100 0.44 0.28
825 ACA CAC ACA CAC ACA CT 54.8 7 85.7 0.43 0.29
826 ACA CAC ACA CAC ACA CC 57.2 5 100 0.48 0.31
827 ACA CAC ACA CAC ACA CG 57.2 5 100 0.60 0.41
828 TGT GTG TGT GTG TGT GA 54.8 3 100 0.24 0.14
835 AGA GAG AGA GAG AGA GYC 58.8 7 100 0.56 0.38
841 GAG AGA GAG AGA GAG AYC 48.5 5 20 0.12 0.08
845 CTC TCT CTC TCT CTC TRG 48.1 3 66.7 0.38 0.26
851 GTG TGT GTG TGT GTG TYG 49.2 4 100 0.67 0.48
855 ACA CAC ACA CAC ACY T 53.1 3 100 0.60 0.41
856 ACA CAC ACA CAC ACA CYA 56.4 7 85.7 0.43 0.28
887 DVD TCT CTC TCT CTC CT 55.6 6 100 0.42 0.27
Total average     5.44 91.13 0.45 0.30

Table 2. Inter-simple sequence repeat (ISSR) primers used in 26 sugarcane accessions from the Active Germplasm Bank of Embrapa Coastal Tablelands, Brazil, with their respective sequences, annealing temperature (AT), number of fragmented bands (NFB), polymorphism percentage (%P), Shannon Index (I), and expected heterozygosity (HE).


Figure 2: Electrophoretic profiles of inter simple sequence repeats of 26 sugarcane accessions amplified in agarose gel using the primer UBC 887. Embrapa Coastal Tablelands, Brazil. Lane M = 100-bp marker; lane NC = negative control; lanes 1 to 26 = DNA samples.

Several markers have been used for studies on sugarcane diversity. AFLP, which presents advantages such as the detection of the highest number of locus, was used by Selvi et al. (2006) in species of the genus Saccharum and obtained 1323 bands with 12 pairs of primers, from which 1122 (84.8%) were polymorphic. Ullah et al. (2013) used eight RAPD markers and observed 73.5% polymorphism between the five varieties studied. In a study conducted with 20 accessions of S. officinarum in Pakistan, Khan et al. (2009) showed 86.8% polymorphism for 188 of the 210 polymorphic fragments obtained by the use of 21 RAPD primers. Raj et al. (2016), analyzing the genetic diversity of the Saccharum complex, using coSSR, found polymorphic amplifications (100%) in nine primers by amplifying 54 fragments. Pandey et al. (2011), however, found 148 polymorphic bands in five SSR primers.

Almeida et al. (2009) found high polymorphism (95%) using seven ISSR primers; of the 56 fragments obtained, 53 were polymorphic. Srivastava and Gupta (2008), when analyzing the diversity of 40 genotypes of sugarcane, found 79 bands amplified by 10 ISSR primers, from which 62 (78.48%) were polymorphic and 17 were monomorphic. Devarumath et al. (2012) found the production of 65 amplified fragments, with 96.5% polymorphism, in 13 ISSR primers used for PCR amplification. Rao et al. (2016), for ISSR analysis, used 19 primers in 14 genotypes of sugarcane for amplification of the PCR, a total of 164 bands were marked with 109 polymorphic bands and 55 monomorphic bands. These results, as well as in this study, prove the efficiency of ISSR when compared with other markers, revealing a high degree of polymorphism.

The I ranged from 0.12 to 0.67, with an average of 0.45. The HE ranged from 0.08 to 0.48, with an average of 0.30 (Table 3). Those indexes showed intermediate levels of genetic diversity. However, for some initiators, such as 827, 851 and 855, the values of I and HE can be considered high, showing high variability. According to Giustina et al. (2014), the value of I can vary between 0 and 1, with a value of 1 indicating the highest diversity of a population. The values found in this study are close to those verified by Nayak et al. (2014) in S. spontaneum, S. officinarum, S. hybrid, S. barberi, S. robustum, and S. sinense, in which the values of I found were between 0.38 and 0.49 and of HE were between 0.23 and 0.30.

  Q45866 Q46199 Q45251 Q42509 Q45911 Q45864 Q44830 Q45337 Q45416 Q44890 Q44833 Q45869 Q42433 PI240785 PI197800 Q36830 GH-49 MIA35303 NSL291970 PI88652 MIA35301 RB867515 RB92579 PI495109 PI286657 PI29109
Q45866 ˗                                                  
Q46199 0,77 ˗                                                
Q45251 0,57 0,58 ˗                                              
Q42509 0,64 0,70 0,52 ˗                                            
Q45911 0,46 0,52 0,47 0,60 ˗                                          
Q45864 0,74 0,71 0,52 0,58 0,54 ˗                                        
Q44830 0,60 0,63 0,55 0,61 0,54 0,66 ˗                                      
Q45337 0,60 0,61 0,48 0,46 0,40 0,58 0,63 ˗                                    
Q45416 0,59 0,52 0,56 0,51 0,46 0,56 0,51 0,59 ˗                                  
Q44890 0,61 0,61 0,58 0,62 0,54 0,64 0,65 0,53 0,54 ˗                                
Q44833 0,56 0,57 0,63 0,54 0,49 0,57 0,63 0,52 0,55 0,67 ˗                              
Q45869 0,57 0,60 0,54 0,53 0,48 0,60 0,52 0,60 0,59 0,50 0,54 ˗                            
Q42433 0,45 0,51 0,52 0,53 0,48 0,48 0,50 0,48 0,40 0,60 0,54 0,53 ˗                          
PI240785 0,41 0,44 0,34 0,43 0,40 0,47 0,45 0,54 0,46 0,48 0,43 0,41 0,42 ˗                        
PI197800 0,45 0,48 0,39 0,45 0,35 0,44 0,40 0,46 0,39 0,31 0,33 0,43 0,34 0,33 ˗                      
Q36830 0,44 0,54 0,47 0,53 0,44 0,45 0,46 0,52 0,38 0,46 0,39 0,42 0,43 0,41 0,53 ˗                    
GH-49 0,46 0,57 0,42 0,45 0,43 0,54 0,54 0,57 0,39 0,51 0,46 0,48 0,42 0,38 0,40 0,47 ˗                  
MIA35303 0,49 0,53 0,45 0,49 0,47 0,45 0,44 0,53 0,44 0,52 0,41 0,41 0,43 0,44 0,41 0,50 0,57 ˗                
NSL291970 0,34 0,38 0,34 0,38 0,35 0,33 0,31 0,31 0,32 0,32 0,33 0,36 0,31 0,22 0,62 0,42 0,41 0,48 ˗              
PI88652 0,41 0,50 0,48 0,46 0,33 0,40 0,44 0,43 0,42 0,46 0,47 0,39 0,40 0,35 0,38 0,42 0,47 0,55 0,48 ˗            
MIA35301 0,50 0,56 0,49 0,53 0,45 0,48 0,47 0,48 0,40 0,60 0,48 0,37 0,40 0,42 0,36 0,51 0,54 0,68 0,49 0,56 ˗          
RB867515 0,52 0,59 0,48 0,57 0,53 0,55 0,52 0,55 0,55 0,57 0,53 0,56 0,49 0,45 0,47 0,52 0,53 0,57 0,45 0,60 0,52 ˗        
RB92579 0,52 0,59 0,51 0,57 0,50 0,54 0,52 0,57 0,55 0,52 0,48 0,56 0,47 0,45 0,49 0,55 0,50 0,54 0,46 0,54 0,49 0,87 ˗      
PI495109 0,48 0,53 0,44 0,50 0,45 0,53 0,53 0,58 0,39 0,53 0,51 0,52 0,50 0,45 0,45 0,53 0,54 0,52 0,41 0,46 0,50 0,62 0,62 ˗    
PI286657 0,27 0,35 0,27 0,34 0,31 0,29 0,31 0,37 0,27 0,27 0,28 0,27 0,23 0,25 0,39 0,41 0,40 0,43 0,49 0,46 0,47 0,39 0,42 0,37 ˗  
PI29109 0,34 0,46 0,32 0,40 0,35 0,36 0,36 0,40 0,32 0,35 0,33 0,32 0,29 0,26 0,45 0,51 0,45 0,49 0,46 0,52 0,44 0,52 0,49 0,47 0,73 ˗

Table 3. Matrix generated based on the Jaccard similarity coefficient of 26 sugarcane accessions from the Active Germplasm Bank of Embrapa Coastal Tablelands, Brazil

The polymorphic information content (PIC) indicates how much the marker used shows of polymorphic information in studies on genetic diversity. Values above 0.5 are highly informative; those between 0.25 and 0.50 are moderately informative; and values below 0.25 are considered slightly informative (Botstein et al. 1980). In this study, the PIC value was 0.28, considered moderately informative.

The Jaccard similarity coefficient ranged between 0.22 and 0.87, with an average of 0.49, which indicates a relatively high genetic diversity. The accessions RB867515 and RB92579, both Saccharum sp, were the most similar genetically, with 0.87 index. On the other hand, the pair of accessions PI240785 and NSL 291970, S. robustum and S. spontaneum, respectively, showed less genetic similarity (0.22).

The polymorphism identified by the markers was used to create a matrix of genetic distance. Four main clusters were identified in UPGMA analysis based on the Jaccard coefficient (Figure 3). The further individual, PI240785, is in the cluster C1. Most of the accessions (all from Queensland, Australia) was allocated in a main cluster C2, with several subclusters, Q45866 and Q46199 being the closest ones (0.77) of that group.


Figure 3: Phylogenetic representation of unweighted pair group method using arithmetic averages (UPGMA) clustering estimated by the genetic similarity of the Jaccard coefficient and by the bootstrap analysis (10,000X) for 26 sugarcane accessions from the Active Germplasm Bank of Embrapa Coastal Tablelands, Brazil.

The second main cluster, C3, has eight separate individuals in subclusters, with individuals RB867515 and RB92579 possessing greater similarity (0.87). The cluster C4, however, was isolated from others and had all accessions of S. spontaneum and S. sinensis separated into two subclusters with similarity of 0.73 between PI286657 and PI29109.

Despite the large distribution of accessions in most groups, indicating great genetic diversity, these were not separated by a group of the same species in each subcluster, which can be explained by the existence of common alleles among different species, since they are of the same genus. Similar results were found by Raj et al. (2016), in which there was a close relationship among the different species that constitute the Saccharum complex; with S. spontaneum, however, contributing to greater diversity. According to the authors, S. spontaneum is known to be a highly variable species regarding morphology, geographical distribution, and chromosome number (2n = 48-128). High divergence of S. spontaneum from the rest of the species Saccharum was also reported by Alwala et al. (2006).

Selvi et al. (2006), however, found divergent results, in which the genus Saccharum was organized in a large cluster, but with each group of species in separate subclusters.

The genetic distances were also assessed by the PCoA (Figure 4). Four clusters were identified among the different accessions studied, and the amount of the first two main components was 49.30%. These results stress the efficiency of ISSR in genetic diversity detection among the accessions of sugarcane. According to the results of UPGMA, some pairs of individuals (RB867515/RB92579, PI286657/PI29109, Q45866/Q46199, Q44833/Q44890, Q45337/Q45869) were genetically very close in PCoA, showing that the use of more than one clustering method prevents interference to be adopted in the allocation of materials within a specific genotypic subcluster (Silva et al., 2011).


Figure 4: Principal coordinates analysis (PCoA) of 26 sugarcane accessions from the Active Germplasm Bank of Embrapa Coastal Tablelands, Brazil.


The genetic diversity of sugarcane genotypes from the Active Germplasm Bank of Embrapa Coastal Tablelands is considered high. The pair of individuals with less genetic similarity was PI240785 and NSL 291970, S. robustum and S. spontaneum respectively.

The results found in this study showed the level of genetic resolution and reliability obtained by analysis with ISSR molecular markers allowed the discrimination of different genetically accessions, which could be used for the management of genetic resources of the species and, once selected, will be important for breeding programs aimed at selection of superior genotypes.

About the Authors

Corresponding Author

L.A.R. Oliveira

Programa de Pós-Graduação em Agricultura e Biodiversidade, Universidade Federal de Sergipe, Aracaju, Sergipe, Brasil

[email protected]


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