Genetic Diversity of Selected Kenyan local cultivated sesame

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Abstract

Sesame (Sesamum indicum L.) is an important crop for excellent edible vegetabe oil. Genetic diversity of cultivated sesame and its wild relatives in Kenya has not been studied for efficient germplasm utilization, conservation and improvement. Genetic diversity and relatedness of cultivated sesame and its wild relatives was studied using inter-simple sequence repeats (ISSR). The six ISSR primers generated 51 amplification fragments of which 36 (70.6%) were polymorphic with 8.5 fragments per primer. The fragment sizes ranged from 200 to 3000 bp. An overall gene diversity of 0.26 and a coefficient of genetic differentiation of 0.75, which indicated that most of the genetic variation resides among accessions and species. The 46 sesame accessions were divided into six groups on the basis of unweighted pair-group method (UPGMA) cluster analysis. There was a clear separation between cultivated sesame and its wild relatives indicating that cultivated sesame are distantly related to its wild relatives. The high gene diversity as well as high level of polymorphism suggests that ISSR markers could be useful for the selection of parents in sesame breeding program in addition to differentiation of Sesamum species.

Key words: Wild relatives, ISSR, Genetic diversity, Breeding, Sesamum

Introduction

Sesame (Sesamum indicum L.) belongs to the Sesamum genus of Pedaliaceae family and contains over 30 species (Ashri, 1998; Bedigian, 2003). It is an important oil crop in Kenya, where it is mainly used as source of vegetables and also finds use in traditional medicine (Maundu et al., 1999). Sesame production in Kenya is constrained by both biotic and abiotic stress. There are several wild relatives of sesame in Kenya which might be tolerant to such stresses and may be used in breeding tolerant cultivated sesame. The genetic diversity and relatedness of cultivated sesame and its wild relatives has not been studied before. The insufficient genetic information about the Kenyan sesame has been cited as one of the factor contributing to limited cultivation of improved varieties and consequently low yield (Nyangweso, 1999; Hamid et al., 2003).

Recent studies have revealed that sesame germplasm collections from Kenya are highly variable for morphological and agronomic characters (Were et al., 2001; 2006; Hiremath et al., 2007). Similarly, Kenyan sesame has shown varying degree of resistance against fungal diseases (Ojiambo et al., 2003). Although morphological characters are inexpensive and simple to score, they lack adequate coverage of the genome, are strongly influenced by environmental factors, and are controlled by several genes (Karp et al., 1997), thus preventing the precise determination of the underlying genetic diversity.

Many studies have demonstrated that no single method is adequate for studying genetic diversity in germplasm collections (Semagn et al., 2006), because different methods sample genetic diversity at different levels and differ in their power of genetic resolution as well as quality of information content. In sesame and other crop plants, efforts to study genetic diversity have been greatly enhanced with the advent of molecular markers. Isozymes (Isshiki and Umezaki, 1997; Parani et al., 1997; Diaz et al., 1999), random amplified polymorphic DNA (RAPD) (Ercan et al., 2004; Pham et al., 2008), restriction fragment length polymorphism (RFLP) (Laurentin and Karlovsky, 2006) and inter simple sequence repeat (ISSR) (Kim et al., 2002) have been used to estimate genetic diversity in sesame. These markers differ in the level at which they detect genetic variation, extent of polymorphism, degree of environmental stability, number of loci, molecular basis of polymorphism, practicability and reproducibility (Semagn et al., 2006).

We have used the ISSR technique in order to complement the previous studies based on morphological and agronomic characters (Were et al., 2001; 2006). The objective of the study was to determine genetic diversity and relatedness among cultivated sesame and its wild relatives.

Materials and methods

Plant materials

A total of 46 sesame accessions, consisting of 38 cultivated and 8 wild relatives were assessed in this study (Table 1). Cultivated sesame seeds were obtained from a collection maintained at the Department of Biological Sciences, Moi University. Wild sesame seeds were collected from different localities in Kenya including Kitale, Busia, Marigat, Kabarnet and Kabimoi Centre.

Table 1. List of sesame accessions, seed source and seed colour.

S.No.

Accession

Seed source/ Locality

Seed colour

S. indicum L.

1.

Morogoro

Tanzania

Brown

2.

107UG

Nambale

White

3.

Tan 3

Tanzania

Brown

4.

102UG

Webuye

White

5.

Ug 7

Uganda

White

6.

109UG

Adungosi

White

7.

Mtwara1

Mtwara

White

8.

304BU

Ahero

Brown

9.

302TZ

Kisumu

Black

10.

110UG

Bumala

White

11.

Sik114

Breeder

White

12.

105BU

Mumias

Brown

13.

Ug2

Uganda

Brown

14.

Ug4

Uganda

White

15.

103UG

Kanduyi

White

16.

308KE

Ugenya

White

17.

Msambweni

Mombasa

White

18.

301TZ

Kisumu

Brown

19.

Mtwara2

Mtwara

White

20.

Tan7

Tanzania

White

21.

Tan6

Tanzania

Cream

22.

Ug5

Uganda

Cream

23.

303BU

Kisii

Brown

24.

306BU

Kisumu

White

25.

Ug3

Uganda

Brown

26.

Ug1

Uganda

Brown

27.

111BU

Luanda

White

28.

307KE-a

Ugenya

Black

29.

307KE-b

Ugenya

White

30.

101UG

Kitale

White

31.

108BU

Busia

White

32

106UG

Busia

White

33.

Stewa

Shimo la Tewa

Black

34.

113BU

Koyonzo

White

35.

New Indian

India

White

36.

Indian

India

White

37.

Lungalunga

Mombasa

Black

38.

Majengo

Kisumu

Black

S. angolense

39.

105aw

Kapropita (kabarnet)

Black

40.

202w

Kabarnet

Black

41.

105w

Kabarnet

Black

42.

108w

Busia air strip

Black

43.

109w

Kabimoi centre, Eldama Ravine Rd

Black

Sesamum spp

44.

103w

Kitale, Kitale Kapenguria Rd.

Black

S. latifolium

45.

104aw

Kambi ya Samaki (Marigat)

Black

46.

104w

Loboi, Marigat

Black

DNA extraction

Seeds samples were germinated in plastic pots and maintained in a greenhouse. Fresh young leaves were harvested from five randomly selected individuals per accession for DNA extraction. Genomic DNA was extracted from 100 mg of young leaf samples according to the procedure described by Were et al. (2006). DNA quality and quantity was assessed by electrophoresis in 1% agarose gels (Sambrook and Russell, 2001). Each DNA sample was diluted using sterile deionized distilled water to a final working concentration of approximately 10 ng/µl.

Amplification conditions

A total of 10 ISSR primers (Sigma-Aldrich) were used for PCR amplifications. Amplification reactions were performed in a final volume of 15 μl, containing 1 Ã- reaction buffer (200 mM Tris-HCl, pH 8.4, 500 mM KCl), 0.2 mM of each dNTPs (100 mM each of dATP, dCTP, dGTP and dTTP), 0.4µM primers, 2.5 mM MgCl2 supplied with reaction buffer, 1.0 unit of Taq DNA polymerase (Invitrogen®) and 10 ng of genomic DNA.

Amplifications were performed using a Crocodile III™ (Appligene Oncor) thermocycler. The amplifications were programmed for 4 min at 94°C for initial denaturation, followed by 35 cycles of 45 s at 94°C, 1 min at 47°C for annealing and 2 min at 72°C for polymerization, using the fastest transition times between each temperature, and final extension of 5 min at 72°C. Each reaction per primer was repeated and only reproducible fragments were scored for data analysis.

Electrophoresis

Amplification products were separated on 1.8% agarose gel (Sigma) and run in 1Ã- TAE buffer (40 mM Tris acetate, pH 7.5, 1 mM EDTA) for 2 hrs at 70 volts. The gels were stained with ethidium bromide (0.5μg/μl) and the DNA fragments were detected using UV trans-illumination and photographed under Bio Doc-Itâ„¢ (Ultra-Violet Products, Cambridge, UK).

Data scoring and Analysis

Each amplified fragment was assigned numbers in order of decreasing molecular weight. The size of each fragment was estimated using the DNA molecular weight marker (50 bp ladder). A fragment was scored as present (1) and absent (0). Though we observed differences in band intensity, such quantitative differences were not considered in the present data analysis.

Pair-wise genetic similarity matrix was generated among the 46 accessions using Jaccard's similarity coefficient (Jaccard, 1908; cited in Sneath and Sokal, 1973). The Jaccard similarity coefficient is given as:

Where a is the total number of fragments shared by between accessions I and J; b is the total number of fragments presented by I but not J; and c is the total number of fragments presented by J but not I. The Jaccards' coefficient was used because it calculates similarities based on shared presence but not the absence of DNA fragments. The cluster analysis was performed using the unweighted pair group method for arithmetic averages analysis (UPGMA) (Sneath and Sokal, 1973) and dendrogram was constructed for the 46 accessions. The analysis was done using NTSYS-pc ®version 2.1 (Rohlf, 2000). Gene diversity indices were calculated using POPGENE® software 1.32 as described by Yeh et al. (1997).

Results

Among the 10 ISSR primers screened for their ability to detect polymorphic fragments in a subset of sesame samples, 6 primers (Figure 1 and Table 2) generated interpretable polymorphic amplifications. The remaining four primers UBC 814, UBC 815, UBC 843 and UBC 874 were discarded as they produced ambigous and non-reproducible amplification profiles. The 6 primers produced a total of 51 scoreable fragments of which 36 (70.6%) were polymorphic across the 46 sesame accessions. Amplified fragments per primer varied from 7 to 12, with a mean of 8.5. The size of the fragments ranged from 200 to 3000 bp. The level of polymorphism ranged from 56% to 88%. The highest polymorphism level was obtained with primer UBC845 (88%) and the lowest was detected with primer UBC873 (56%). An example of the ISSR fragment profiles obtained with primer UBC 868 is shown in Figure 2.

Table 2. Primers used in ISSR analysis, their nucleotide sequence, number of amplified fragment (F), number of polymorphic fragments (PF), percent polymorphism (%P) and molecular size range.

Primer code

Sequence (5' - 3')

F

PF

% P

Molecular size (bp)

UBC 811

(GA)8C

12

9

75

350-2000

UBC825

(AC)8T

7

5

71

300-2000

UBC 845

(CT)8R*G

8

7

88

300-3000

99ikUBC868

(GAA)6

7

5

71

450-2000

UBC873

(GACA)4

9

5

56

200-3000

UBC900

-5*

8

5

63

350-3000

Total

51

36

70.6

Range

7-12

5-9

56-88

200-3000

*R = (A, G), -5 = ACTTCCCCACAGGTTAACACA

Figure 1. Properties of ISSR products obtained with selected primers in cultivated sesame and its wild relatives.

Figure 2. Amplification products from 8 sesame accessions amplified with primer UBC868. Molecular weight marker (50 bp) is shown in the left lane.

The result of the Nei (1987) analysis of genetic diversity among cultivated sesame and its wild relatives is shown in Table 3. A large proportion of the total variation was found among the accessions and species indicating a high genetic differentiation among the accessions and species.

Sesame similarity ratio revealed that high degree of similarity to the extent of 96% exists between 111BU and 303BU implying a narrow genetic diversity between the two accessions. The lowest similarity value of 16% exists between Lungalunga (S. indicum) and 104w (S. latifolium) indicating a high genetic divergence between the two species. Figure 3 displays UPGMA dendrogram obtained using similarity coefficients. Six main groups were identified comprising of 2 to 21 accessions with two accessions (New Indian and Indian) remaining grouped as single

accession. Group I was formed by twenty one accessions namely, Morogoro, 107UG, 102UG, Ug7, 109UG, Mtwara1, 304BU, 302TZ, 110UG, SIK114, 105BU, Ug2, Ug4, 103UG, 308KE, Msambweni, 301TZ, Mtwara2, Tan7 and Tan6. Group II consisted of ten accessions; Ug5, 303BU, 306BU, Ug3, Ug1, 111BU, 307KE-a, 307KE-b, 106UG and101UG. Group III had three accessions consisting of 108BU, Stewa and 113BU. Group IV comprised of two accessions Lungalunga and Majengo. Group V consisted of six accessions of Sesamum angolense namely 105w-a, 108w, 202w, 105w, 109w and 103w. Group VI contained two accessions of S. latifolium namely 104w-a and 104w.

Figure 3. UPGMA dendrogram showing the relationships among cultivated sesame and its wild relatives.

Table 3. Genetic diversity estimates based on Nei (1987) among the cultivated sesame and its wild relatives.

Locus

Sample size

HT

HS

GST

Nm*

900-1

230

0.000

0.000

****

****

900-2

230

0.197

0.118

0.403

0.740

900-3

230

0.033

0.008

0.771

0.149

900-4

230

0.484

0.073

0.850

0.088

900-5

230

0.437

0.072

0.835

0.099

900-6

230

0.470

0.133

0.717

0.197

845-1

230

0.083

0.000

1.000

0.000

845-2

230

0.457

0.233

0.491

0.518

845-3

230

0.208

0.018

0.915

0.047

845-4

230

0.207

0.051

0.752

0.165

845-5

230

0.355

0.044

0.875

0.071

845-6

230

0.399

0.037

0.908

0.051

845-7

230

0.440

0.028

0.937

0.034

873-1

230

0.268

0.012

0.954

0.024

873-2

230

0.379

0.100

0.736

0.179

873-3

230

0.500

0.144

0.713

0.202

873-4

230

0.318

0.084

0.737

0.179

873-5

230

0.240

0.036

0.851

0.087

825-1

230

0.069

0.010

0.852

0.087

825-2

230

0.302

0.100

0.670

0.246

825-3

230

0.162

0.029

0.818

0.111

825-4

230

0.373

0.199

0.467

0.571

825-5

230

0.175

0.020

0.886

0.064

868-1

230

0.079

0.004

0.948

0.027

868-2

230

0.407

0.301

0.262

1.410

868-3

230

0.027

0.010

0.627

0.297

868-4

230

0.069

0.010

0.852

0.087

868-5

230

0.273

0.048

0.823

0.107

811-1

230

0.255

0.022

0.916

0.046

811-2

230

0.459

0.069

0.850

0.088

811-3

230

0.103

0.039

0.627

0.298

811-4

230

0.250

0.047

0.813

0.115

811-5

230

0.223

0.004

0.982

0.009

811-6

230

0.186

0.008

0.959

0.021

811-7

230

0.264

0.026

0.902

0.054

811-8

230

0.381

0.236

0.379

0.818

811-9

230

0.175

0.019

0.890

0.062

Mean

230

0.262

0.065

0.754

0.163

S.D

0.021

0.006

HT = total genetic diversity HS = genetic diversity within populations GST = coefficient of genetic differentiation, S.D = standard deviation

Discussion

Molecular markers have been widely used for genetic diversity and species identification in a large number of species. Reliability and reproducibility are essential features for a technique to be used in fingerprinting. In the present study, the amplification of ISSR markers used because over 99% of the scoreable ISSR fragments were reproducible. The reproducibility of ISSR may be due to longer primers (Semagn et al., 2006) and they are anchored at the 5' or 3' end with a few nucleotides to increase specificity of priming. The ISSR markers generate a large number of polymorphisms per primer because variable regions in the genome are targeted (Goulão and Oliveira, 2001).

The level of polymorphism observed in this study is higher than those reported (33-66%) in previous studies (Kim et al., 2002; Abdellatef et al., 2008). However, the level of polymorphism is comparable with that reported by Ercan et al. (2004). The high level of polymorphism may partly be due to our sampling procedure, which took into account not only different Sesamum species but also results of morphological variation (Were et al., 2001; 2006). Sampling germplasm based on morphological variations has been considered to be a more effective means of capturing genetic diversity (Ayana et al., 2000). Additional explanation may be due to biasness in scoring fragments of different intensity.

The level of genetic diversity was high in the present study. Most of the variation was found among the accessions and species. Sesame is mainly self-pollinated but it may experience between 5 to 60% out-crossing (Yermanos, 1980; Pathirana, 1994). Out-crossing plant species tend to present between 10 to 20% of the genetic variation between populations (Hamrick and Godt, 1989). Hence, out-crossing in sesame may be contributing to the high genetic variation observed. The high genetic diversity observed may also be attributed to the nature of ISSR. The ISSR can be highly variable regions of DNA within species (Salimath et al., 1995). The simple sequence repeats, which are the basis for primer sites of ISSRs are known to have a high rate of gaining and losing sequence repeat units due to DNA slippage (Schlötterer, 1998), and may account for the ISSR variations observed in this study. Mutation and chromosomal structural rearrangements have been suggested also as a source of ISSR variation (Wolfe and Liston, 1998).

Although a high genetic diversity exists among the sesame accessions and species from various localities, it was found that some accessions from different localities were clustered together. This could be a consequence of substantial migration of people in East African states carrying sesame seeds for cultivation in their new localities. The human factor has been cited as one of the factor responsible for the lack of correlation between genetic and geographical distance in some cases (Stankiewicz et al., 2001; Kim et al., 2002, Pham et al., 2008).

Cluster analysis has shown that wild relatives are genetically distant from the cultivated sesame and therefore cannot be used as bridging species in the improvement of cultivated sesame. Genetic divergence between wild and cultivated species has been reported in a number of crops including Pigeon pea (Panguluri et al., 2006), Lens species (Duràn and Pérez de la Vega, 2004) and mulberry accessions (Zhao et al., 2004). This distinctness could be due to different modes of evolution coupled with sexual incompatibility barriers that exist in genus Sesamum (Kobayashi, 1981; Kumar and Hiremath, 2008). The high chromosome number observed in wild Sesamum species may also explain the genetic divergence between cultivated sesame and its wild relatives.

Conclusion

The ISSR analysis revealed a high level of genetic diversity among the cultivated sesame and its wild relatives. These results also demonstrated that cultivated sesame is genetically distant from the wild relatives. The level of diversity reported in this study suggests that ISSR can be useful for the selection of parents in sesame breeding programs.

Acknowledgement

The authors would like to thank East African Regional Programme and Research Network for Biosafety, Biotechnology and Policy Development Program (BIO-EARN) for partially financing this research. The authors are grateful to the Department of Biological Sciences, Moi University for providing laboratory space and technical support for this research.We are also thankful to Mr. Josiah Chiveu for his assistance in data analysis.

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