Assessment of Genetic Diversity and Identification ...

Indian J Agric Biochem 24 (2), 110-116, 2011

Assessment of Genetic Diversity and Identification of Species Specific Marker for Wheat Cultivars (Triticum aestivum and T.durum L.) Grown in India using RAPD Marker VISHAL R PATIL*, JG TALATI, ABHISHEK SINGH, SARANG S SAPRE, CHANDRAKANT SINGH1, GAUTAM SARIPALLI1 and DHARMENDRA PATIDAR2

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Department of Agricultural Biochemistry, 1Department of Agricultural Biotechnology, 2Bidi Tobacco Research Station, B.A. College of Agriculture, Anand Agricultural University, Anand 388 110, Gujarat, India Wheat (Triticum aestivum and T. durum L.) is one of the most important cereal crop worldwide and is used to produce various end use products like chapati, bread, biscuits, pasta etc. Due to its food and industrial importance there is need for the improvement of wheat crop to market suitable for different traits. Random amplified polymorphic DNA (RAPD) marker can be effectively used for identification and differentiation of the cultivars. PCR amplification of genomic DNA of 12 wheat cultivars using 17 RAPD primers generated 1656 scorable bands with an average of 97.41 bands per primer in which OPF-15 generated highest number of scorable bands. Total 213 loci were observed, out of that 143 were found polymorphic. Primer OPA-18 showed highest (14) polymorphic loci. Polymorphism percentage in all primers ranged from 33.33% (OPE-01) to 100 % (OPE-10). Dendrogram produced by pooled RAPD data showed cultivars of T. aestivum and T. durum into two separate clusters. RAPD amplification produced 31 aestivum and durum species specific bands, these bands can be further explored to develop more specific markers like SCARs for identification of wheat species. Key words: Wheat, RAPD, genetic diversity, species identification

Wheat (T. aestivum and T. durum L.) is one of the most globally important cereal crop in terms of production and utilization and support nearly 35% of the world population

Most of the wheat varieties possess much similarity with respect to growth, morphology and yield related characteristics. Genetic diversity patterns can provide

(1). Wheat is a major contributor of food self sufficiency in India. It has been estimated that about 65% of wheat

insights into evolutionary and demographic history of a taxon. The study of structural genetic diversity within

grain is directly used as a food for humans, 21% as a feed for livestock and 8% as seed material which shows its acceptance as main staple food (2). Wheat belongs

and among populations might avoid future risk of diversity erosion (5), there is a need to develop markers for an unambiguous identification and differentiation of the

with the sub-tribe Triticinae of tribe Triticeae in the family Poaceae. The sub-tribe Triticinae is of recent origin and contains about 35 genera including Triticum, Aegilops, Thinopyrum etc., (3). India presently holds the second position after China in the world for wheat production. In India three types of wheat are grown T. aestivum L. (Bread/common wheat, 2n=6x=42), T. durum L. (Durum wheat, 2n=4x=28) and T. dicoccum L. (Dicoccum wheat, 2n=2x=28). Large numbers of end use products such

varieties which facilitate registration, protection and maintenance of purity of the seeds and testing the quality of industrial important seed lots (6). Molecular markers are more stable as compared to morphological and cytogenetic traits which are time consuming and affected by environmental conditions. Biochemical markers such as, protein, isozyme and DNA-based markers such as, restriction fragment length polymorphism (RFLPs) and random amplified polymorphic DNA (RAPD) have been

as chapatti, bread, biscuits, pasta, noodles, macaroni, spaghetti, cakes, pizzas and doughnuts are made from wheat, which shows its importance in food and baking industries (4). In view of its industrial importance, a special emphasis is given to wheat crop.

used to evaluate the genetic diversity among wheat landraces (7-10). In recent years, RAPD markers have been extensively used for the identification of genotypes in crop plants due to its simplicity and efficiency even without the prior knowledge of sequence information (11).

*Author for correspondence: Email : [email protected]

Assessment of Genetic Diversity and Identification of Species Specific Marker for Wheat Cultivars 111

RAPD technique has been successfully used for the evaluation of plant genetic resources (12-16), assessing genetic diversity (17-20) and also for the characterization and grouping of wheat genotypes (21). In the present study RAPD markers have been employed to assess the genetic diversit y of 12 wheat cult ivar s and identification of aestivum and durum wheat species specific markers.

Materials and Methods Plant material: The plant material used in the present




study consisted of 6 cultivars each of T.aestivum and T.durum wheat species (Table 1) which were received from Regional Research Station, Anand Agricultural University, Anand, Gujarat, India. Table 1: List of 12 cultivars of wheat evaluated for genetic diversity using RAPD marker

Sr.No. 1 2 3 4 5 6

T. aestivum cultivars LOK-1 GW-173 GW-273 GW-322 GW-366 GW-496

Sr.No. 7 8 9 10 11 12

T. durum cultivars GW-1139 GW-1246 GW-1255 GW-1256 GW-1257 GW-1258

Genomic DNA extraction: Genomic DNA was extracted from seven days old seedlings according to procedure described by Zidani et al., (22). RAPD amplification: Amplification of RAPD fragments was performed according to Rashed et al., (23) using decamer arbitrary primer (Operon technologies Inc. USA). Initially 120 primers were screened for their repeatable amplification with two cultivars. Primers were selected for further analysis based on their ability to detect distinct polymorphic amplified products across the cultivars. In order to ensure reproducibility, the primers generating weak products were discarded. The lists of primers used in this study are presented in Table 2. Amplifications were performed in a 25ìl reaction volume containing 2.5ìl templates DNA (20ng/ìl), 2.5ìl Taq buffer (10X), 0.5ìl Taq polymerase (5U/ìl) (Sigma Aldrich, USA), 0.5ìl dNTPs (10mM) (Fermentas, USA) and 1ìl primers. Amplif icat ion was perf or med in a progr ammed thermocycler (Whatman Biometra T-Gradient, Germany) with initial denaturation at 94 oC for 2 min, 40 cycles of

denaturation at 94 oC for 1 min, annealing at 40 oC for 2 min, extension at 72 oC for 2 min, and final extension at 72 oC for 10 min. Amplified products were electrophoresed in 1.5 % agarose in 1X TBE buffer. The gel was stained with ethidium bromide and documented using Alpha EaseFC4. 0. 0 G el document at ion system (Alpha Innotech Corporation, USA). Data analysis: The RAPD bands were scored as present (1) or absent (0) each of which was treated as an independent character regardless of its intensity. The data was entered into binary matrix and subsequently analyzed using NTSYS-pc version 2.02 (24). Pair-wise similar ity matrices w ere gener ated by Jaccar d’s coefficient of similarity by using the SIMQUAL format of NTSYS-pc. The dendrogram was constructed by using the UPGMA (Un-weighted Pair Group Method with Arithmetic Mean) with the SAHN module of NTSYS-pc. The binary data was also subject ed t o pr incipal component analysis (PCA) using the EIGEN and PROJ modules of NTSYS-pc. PCA plots the relationships between distance matrix elements based on their first two principal components (25). The polymorphism information content (PIC) was calculated by the formula: PIC= 2Pi (1-Pi) (26) where, Pi is the frequency of occurrence of polymorphic bands in different primers. The resolving power (RP) was calculated by the formula: RP= S Ib (27) where, Ib represents the informative fragments. The Ib can be represented on a scale of 0-1 by the formula: Ib= 1-[2×(0.5-P)] where, P is the proportion of cultivars containing the band. The cophenetic correlation analysis was carried out using the COPH function of NTSYS-pc. Plots of one matrix against the other and the association statistics were made and calculated by MAXCOMP function of NTSYS-pc (28).

Results and Discussion RAPD marker can be efficiently used to study the genetic diversity and to find out genetic relationship among the cultivars, which is an essential component in germplasm characterization and conservation. RAPD based DNA fingerprints of those varieties which are under process of seed certification can be useful to breeders, traders, growers and seed certification agencies. Analysis of higher number of parental genotypes by using RAPD

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Indian J Agric Biochem 24(2), 2011

marker assists for rapid prediction of genetic diversity among their crosses (29). The present investigation also conf irmed the eff iciency of RAPD t echnique f or determination and estimation of genetic distances and relatedness among different cultivars. RAPD banding pattern and genetic diversity details across all the cultivars: The details of amplification products and polymorphism data are given in the




Table 2 and Fig. 1. PCR amplification of genomic DNA of 12 wheat cultivars, using 17 RAPD primers generated 1656 scorable bands with an average of 97.41 bands per primer. These results are in contrast with the previous reports by Thomas et al., (6) and Rashed et al., (23). OPF-15 generated highest (145) scorable bands, whereas OPH-10 produced lowest (61) scorable bands. The size of the bands ranged from 213 (OPB-10) to 3054 (OPF-15) base pairs (bp).Total of 213 bands were found with 12.52 average bands per primer. OPF-17 produced lowest (6) bands, whereas OPF-15 produced highest (19) bands. Out of the total bands, 143 were polymorphic with an average of 8.41 bands per primer and 68 bands were monomorphic with an average of 4 bands per primer. OPA-18 generated highest (14), whereas OPE-01 lowest (3) polymorphic bands. OPF-15 generated maximum (7)

monomorphic bands and OPE-10 showed complete absence of monomor phic bands. Percent age of polymorphism ranged from 33.33% (OPE-01) to 100% (OPE-10) with an average polymorphism of 66.70%. The polymorphism percentage observed in present study was low when compared with previous reports by Muhammad et al., (11), Thomas et al., (6), Rashed et al., (23) and Sajida et al., (1) which may be due to the selection of cultivars and primers for investigation. PIC value ranged from 0.80 (OPF-17) to 0.93 (OPF-15) with an average of 0.88 per primer. Resolving power of OPF-15 was found to be highest 24.33, whereas OPF-17 showed lowest 6.80 with an average of 16.25. The Jaccard’s similarity coefficient across all aestivum cultivars ranged from 0.80 to 0.90, whereas all durum cultivars ranged from 0.73 to 0.87 (Table 3). Similarity coefficient between T. aestivum and T. durum cultivars ranged from 0.45 to 0.58. In cluster ‘A’ the highest genetic similarity (0.90) was found between aestivum cultivars GW-173 and GW-496, while lowest genetic similarity (0.80) was found between LOK-1 and GW-322. In cluster ‘B’ the highest genetic similarity (0.87) was found between durum cultivars GW-1255 and GW-1139 as well as GW-1255 and GW-1256, while lowest genetic similarity (0.73) was found between GW-1246 and GW-

Table 2: Amplification details and Polymorphism data of 17 RAPD primers obtained from 12 wheat cultivars

Sr. No.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Primer name

OPA-18 OPB-01 OPB-03 OPB-05 OPB-10 OPC-01 OPD-12 OPE-01 OPE-10 OPE-17 OPF-13 OPF-14 OPF-15 OPF-17 OPF-20 OPH-10 OPH-11 Total Average

Sequence (5’ to 3’) AGGTGACCGT GTTTCGCTCC CATCCCCCTG TGCGCCCTTC CTGCTGGGAC TTCGAGCCAG CACCGTATC CCCAAGGTCC CACCAGGTGA CTACTGCCG GGCTGCAGAA TGCTGCAGGT CCAGTACTCC AACCCGGGAA GGTCTAGAGG CCTACGTCAG CTTCCGCAGT

Molecular weight range (bp) 188 -2337 453- 2170 278- 2582 451- 994 213- 1543 254- 1744 591-2406 466- 2233 240- 2176 241-2474 251-2406 253- 1968 253- 3054 286- 1577 354- 1902 256- 2602 311- 2735 -

Total scorable bands 105 90 112 126 96 91 97 87 94 100 121 120 145 41 66 61 104 1656 97.41

T

16 10 17 14 12 13 14 9 11 10 14 15 19 6 10 9 14 213 12.52

P

14 5 12 8 6 10 10 3 11 4 11 9 12 5 7 7 9 143 8.41

M

2 5 5 6 6 3 4 6 0 6 3 6 7 1 3 2 3 68.0 4.00

% polymorphism (P/T)×100

PIC value

RP

87.5 50 70.58 57.14 50 76.92 71.42 33.33 100 40 78.57 60 63.15 83.33 70 77.77 64.28 66.70

0.91 0.88 0.91 0.92 0.89 0.90 0.90 0.87 0.89 0.89 0.91 0.91 0.93 0.80 0.85 0.85 0.90 0.88

17.50 15.00 18.67 21.17 16.00 15.17 16.17 14.50 15.67 16.66 20.16 20.00 24.33 6.80 11.00 10.16 17.33 16.25

T- Total bands, P- Polymorphic bands, M- Monomorphic bands, PIC- Polymorphism information content, RP- Resolving power





Fig. 1: PCR amplification products of 12 wheat cultivars produced with RAPD primers (a) OPB-01, (b)OPD-12, (c) OPH-10, (d) OPF-15. Lane M is 100bp ladder and lanes 1-12 represent wheat cultivars as listed in Table 1.

1257. These results suggested the presence of high interspecific variation as compared to intraspecific

RAPD data separated aestivum and durum cultivars into two major clusters ‘A’ and ‘B’ (Fig. 2). Similar results

variation among selected wheat cultivars. Similarity coefficient among cultivars can be useful for breeders during selection of highly genetically diverse cultivars for wheat breeding.

were reported in durum and aestivum wheat varieties using RAPD marker (5) and in Old Portuguese wheat cultivars using ISSR marker (30). Cluster ‘A’ included all T.aestivum cultivars, while cluster ‘B’ included all T.durum cultivars. Cluster ‘A’ was resolved into two sub

Clustering pattern of dendrogram generated by pooled

Table 3: Jaccard’s similarity coefficient of 12 wheat cultivars based on RAPD data analysis

CULTIVARS 1 2 3 4 5 6 7 8 9 10 11 12

1 1 0.88 0.85 0.80 0.85 0.88 0.56 0.50 0.54 0.54 0.56 0.53

2

3

4

5

6

7

8

9

10

11

12

1 0.88 0.85 0.86 0.90 0.54 0.50 0.53 0.54 0.55 0.54

1 0.81 0.81 0.82 0.52 0.48 0.50 0.52 0.53 0.51

1 0.81 0.83 0.53 0.45 0.50 0.51 0.52 0.51

1 0.88 0.57 0.51 0.55 0.57 0.58 0.55

1 0.57 0.50 0.55 0.57 0.58 0.54

1 0.79 0.87 0.80 0.79 0.81

1 0.79 0.77 0.73 0.77

1 0.87 0.84 0.83

1 0.80 0.84

1 0.82

1

1-LOK-1, 2-GW-173, 3-GW-273, 4-GW-322, 5-GW-366, 6-GW-496, 7-GW-1139, 8-GW-1246, 9-GW-1255, 10-GW-1256, 11-GW-1257, 12-GW-1258

114


cluster ‘A1’ and ‘A2’. Sub cluster ‘A1’ further resolved into two different groups ‘A1a’ and ‘A1b’. Cultivars LOK1, GW-173 and GW-496 were included in group ‘A1a’, while GW-273 and GW-366 in group ‘A1b’. Cultivar GW322 remained separately in sub cluster ‘A2’. Cluster ‘B’ was resolved into two sub clusters ‘B1’ and ‘B2’. Sub cluster ‘B1’ further resolved into ‘B1a’, ‘B1b’ and ‘B1c’. Cultivars GW-1139, GW-1255 were included into group ‘B1a’, GW-1256, GW-1258 were in group ‘B1b’ and GW1257 in group ‘B1c’. Cultivar GW-1246 remained alone in sub cluster ‘B2’.




The genetic relationships among the 12 wheat cultivars were also revealed by PCA (Fig. 3). The results of PCA analysis were in accordance with the clustering pattern of the dendrogram. The first three most informative principal components explained 56.74% of the total variation. The cophenetic correlation values for the dendrogram based on RAPD data was high (r=0.98). Species specific RAPD bands: RAPD amplification produced species specific bands in either most of all cultivars of T.aestivum or T.durum (Fig. 1). Out of the 17 RAPD primers, 14 showed 18 specific bands for T.aestivum, while 13 for T.durum species (Table 4). Pr imer s OPC- 01, O PD-12 and O PH-11 show ed maximum of three specific bands for T.aestivum species. Primers O PB-01, O PF-20 and OPH- 10 showed

maximum of two specific bands for T.durum species. OPA-18, OPB-03, OPF-13 and OPF-14 amplified specific band only in aestivum cultivars, whereas OPB-01, OPE01, OPE-17 and OPF-20 amplified specific band in only durum cultivars. These species specific bands need to be sequenced for development of SCARs marker and to find out its chromosomal location. Vaillancourt et al., (31) has developed species specific SCARs using ISSR marker for rapid screening of rye introgression in wheat lines, for further use in breeding. The SCAR marker is better reproducible than RAPD marker and allows comparative mapping or homology studies among related species Results of the present investigation indicated that RAPD is considerably informative marker in assessment of genetic diversity among wheat cultivars of different species but not so much informative for same species. Hence, more specific markers like SSR should be employed. RAPD can be useful marker to define intraand inter specific genetic variation and it helps to detect hybrids. For this purpose, a large number of cultivars should be analysed with more numbers of primers. Knowledge of genetic diversity among wheat cultivars can be applied in future breeding program for the improvement of wheat crop with respect to yield and different quality traits, to meet the increasing demand of

Fig. 2: Dendrogram generated using UPGMA analysis based on Jaccard’s coefficient, showing relationships among 12 wheat cultivars using RAPD data.





Fig. 3: Three-dimensional plot of 12 wheat cultivars obtained using principal component analysis of RAPD data.

Table 4: Species specific bands generated by RAPD primers in 12 wheat cultivars

Sr.No.

RAPD Primers

1 2 3 4 5 6 7 8 9 10 11 12 13 14

OPA-18 OPB-01 OPB-03 OPB-05 OPC-01 OPD-12 OPE-01 OPE-17 OPF-13 OPF-14 OPF-15 OPF-20 OPH-10 OPH-11

T. aestivum cultivars Base pairs (bp) 777 631,1660 1322 254,626,903 739,860,2172 545 1591, 1968 1881 847 1361,1683,1837

T. durum cultivars Base pairs (bp) 544,687

R.S. Fougat, Professor and Head, Department of Agricultural Biotechnology, Anand Agricultural University, Anand, Gujarat for providing laboratory facilities. Received June 14, 2011; accepted October 04, 2011

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various industries and consumers. RAPD marker can be further explored to develop species specific markers like SCARs for unambiguous identification of different wheat species.

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