Genetic Diversity of Durum Wheat Genotypes Using Morpho-protein Analysis

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Genetic Diversity of Durum Wheat Genotypes Using Morpho-protein Analysis

M. RAJABIHASHJIN¹, M.H. FOTOKIAN¹*, M. AGAHEESARBRZEH², M. MOHAMMADI² and D. TALEI³*

1Department of Agricultural Biotechnology, Shahed University, Tehran, Iran

2Seed and Plant Improvement Institute, Karaj, Iran

3Medicinal Plant Research Center, Shahed University, Tehran 3319118651, Iran (Received 11 November 2013; Accepted 9 January 2014;

Communicated by F. Békés)

Knowledge of morpho-protein patterns of genetic diversity improves the efficiency of germplasm conservation and development. The objective of present study was to evaluate 116 genotypes ofTriticum turgidumfrom seven countries in terms of morphological traits and seed protein banding patterns. The results showed highly significant differences among the genotypes for the traits. The correlation between grain yield and weight per spike was significant and positive, while the correlation between days to heading, length of peduncle and plant height was significant and negative. The factor analysis classified the traits in to four main groups which accounted for 74.4% of the total variability. Sixteen allelic compositions were identified in the genotypes for high molecular weight glutenin subunits. The three alleles were present at the Glu-A1 locus and 8 alleles at Glu-B1. The null allele was observed more fre- quently than the 1 and 2 alleles. Two alleles, namely 17 + 18 and 20, represented more frequent alleles at Glu-B1 locus. The genetic variability in Glu-A1and Glu-B1 loci were 0.42 and 0.81, respectively. The cluster analysis based on morphological traits and HMW-GS clustered the genotypes in to six and seven groups, respectively. The results indicated the presence of high genetic variability among the genotypes. Our findings suggest that the plants belong to different clusters can be used for hybridization to generate useful recombinants in the segregating generations, the genetics and breeding programs for improvement of durum wheat.

Keywords:cluster analysis, durum wheat, genetic diversity, morphological trait, seed storage protein

Abbreviations:DHE: days to heading; FLL: flag leaf length; FLW: flag leaf width; GS:

genomic score; GWS: grain weight per spike; 1000GW: 1000-grain weight; GY: grain yield;

HMWG: high molecular weight glutenin; NGS: number of grain per spike; NSS: number of spikelet per spike; PL: peduncle length; PPL: peduncle projection length; PM: physiological maturity; PH: plant height; SL: spike length; SW: spike weight

* Corresponding authors; E-mails: [email protected], [email protected]; Phone: +982151212178;

Fax: +982151213600

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Introduction

Evolution of genotypes with high yield potential accompanied with desirable combination of traits has always been the major objective of wheat breeding programs. Genetic variability of wheat has been well evaluated using morphological traits, protein pattern and molecular markers. The genetic variation coefficient, which expresses the amount of ex- isting genetic variation as a percentage of the general mean, are of great importance for genetic improvement programs. The genetic variation coefficient shows the range of genetic variation for a trait, in view of its improvement potential (Mohammadi et al. 2011). How- ever, morphological traits have a number of limitations, including low polymorphism, low heritability, late expression, and may be controlled by epistasis and pleiotropic gene ef- fects (Nakamura 2001). While molecular markers such as seed storage proteins reflect the genotype more directly, independent of environmental influences (Brown and Weir 1983). Protein markers are useful tools to identify cultivar, registration of new varieties and classification of crop species to study genetic diversity, thereby improving the efficiency of wheat breeding programs in cultivar development (Gianibelli et al. 2001). Pro- teins are grouped into four classes according to their solubility: albumins, globulins, prolamins and glutenins (Naghavi et al. 2009). According to the proteins quantity and quality, mainly gluten, wheat varieties are regrouped in different classes (Naghavi et al.

2009). Gluten, comprising of about 78–85% of total wheat endosperm protein, is a very large complex composed mainly of polymeric and proteins known, respectively, as glutenins and gliadins. Gliadins and glutenins have been extensively studied and the genetics and biochemistry are relatively well known (Shuaib et al. 2007). The high molecular weight glutenin (HMWG) subunits account for about 25–35% of the total glutenins (Seilmeier et al. 1991) and have been studied extensively. The HMWG subunits are mainly responsible for dough strength in wheat. Dough strength determines the quality of bread and pasta made from bread and durum wheat, respectively (Ram 2003). Genetic studies have revealed that glutenins are encoded at several, complex and highly polymor- phic loci (Branlard et al. 1989). In tetraploid wheat, Glu-A1 loci code for one (1Ax) or none, Glu-B1 usually code for one (1Bx) or both (1Bx and 1By) subunits. Thus a tetraploid wheat genotype produces one to three subunits (Payne and Lawrence 1983).

Therefore the aim of this study was to determine genetic diversity in landraces and cultivars of wheat durum using morphological traits and seed storage proteins. This infor- mation will be useful to improve techniques for sampling wheat genetic variation, which might increase efficiency of conservation of germplasm.

Materials and Methods

The experiment was conducted at Seed and Plant Improvement Research Institute, in the field of Karaj, 1321 meters above sea level in 2011–2012 cropping season. A total of 116 genotypes of durum wheat(Triticum turgidum)from seven countries (Iran, Bulgaria, Por- tugal, Italy, Yugoslavia, Iraq and Afghanistan) were provided by the National Plant Gene

Cereal Research Communications

RAJABIHASHJINet al.: Genetic Diversity of Wheat Genotypes

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Bank of Iran (Table S1*). Each genotype was sown in one meter long row. After eight months all plants were harvested and data on morphological traits such as days to heading, leaf length, leaf width, length of peduncle, length of peduncle projection, spike length, plant height, physiological maturity, number of spikelet/spike, grain weight/spike, 1000-grain weight were measured from three plants from each row randomly. Protein extraction and electrophoresis were carried out according to Singh et al. (1991) with some modifications.

Gel preparation, pattern and quality scores nomenclature

The protein samples were run on SDS-PAGE separation following the method described by Singh et al. (1991). Identification of banding patterns of the HMWG subunits giving quality scores were conducted according to Payne and Lawrence (1983) and Gupta et al.

(1990), respectively. Alvand (1allele in Glu-A1 locus and 7 + 8 in the Glu-B1 locus), Falat (1allele in Glu-A1 locus and 7 + 9 in the Glu-B1 locus), Chamran (2*allele in Glu-A1 locus and 7 in the Glu-B1 locus), Eagle (2*allele in Glu-A1 locus and 17 + 18 in the Glu-B1 locus) and Veerinac (1allele in Glu-A1 locus and 17 + 18 in the Glu-B1 locus) were used for scoring as control varieties.

Statistical analysis

The SPSS software version 20 was used for all statistical analyses including analysis of variance, factor analysis, multiple regression analysis and cluster analysis. Genetic variability and the average genetic diversity in genotypes were assessed using the Nei (1978) index.

Results

Evaluation of genetic diversity of durum wheat genotypes based on morphological traits

Analysis of variance of studied morphological traits showed significant differences among the genotypes except days to heading (P£0.01) (Table 1). Most of the bivariate correlation between the traits was significant atP£0.01 (Table 2). The highest correlation was between grain weight per spike and spike weight (0.947**) and peduncle projection length and peduncle length (0.809**). There was a significant correlation between grain yield and the number of grains per spikelet (0.411*). There was a significant correlation between grain yield and weight per spike (0.441**) and negative correlation between day to heading (–0.464**), length of peduncle (–0.337**) and plant height (–0.327**).

Factor analysis of the 14 morphological studied traits generated four main factors that were accounted for 74.4% of the total variability in the dependent structure (Table 3). The first factor (group) included spike weight, number of grain per spike, and weight of grains/spike which accounted for 24.85% of the total variability in the dependent structure. This factor could be assigned as grain yield factor. In the second factor, plant height,

Cereal Research Communications RAJABIHASHJINet al.: Genetic Diversity of Wheat Genotypes

* Further details about the Electronic Supplementary Material (ESM) can be found at the end of the article.

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CerealResearchCommunications RAJABIHASHJINetal.:GeneticDiversityofWheatGenotypes Table 1. Variance analysis of 116 genotypes of durum wheat

S.O.V df Mean square

DHE FLL FLW PL PPL SL PH PM NSS SW NGS GWS 1000GW GY

Between groups 28 46.16^ns 0.436** 6.02** 21.36** 0.08** 0.07** 27.59* 3.89* 4.62** 0.17** 2.13** 1.81** 0.52** 0.32**

Within groups 13 1.79 1.11 0.86 1.52 0.58 0.93 1.42 1.12 0.55 0.62 0.89 0.74 0.87 0.81

*, ** are significant at 5 and 1% level of probability, respectively;^nsNon-significant; DHE: days to heading; FLL: flag leaf length; FLW: flag leaf width; PL:

peduncle length; PPL: peduncle projection length; SL: spike length; SW: spike weight; PH: plant height; PM: physiological maturity; NSS: number of spikelet per spike; SW: spike weight; NGS: number of grain per spike; GWS: grain weight per spike; 1000GW: 1000-grain weight; GY: grain yield.

Table 2. Phenotypic correlation coefficient among 14 characters of 116 genotypes of durum wheat

DHE FLL FLW PL PPL SL PH PM NSS SW NGS GWS 1000GW GY

DHE 1

FLL .025 1

FWL .115 .362** 1

PL –.046 .144 .104 1

PPL –.311** –.027 –.051 .809** 1

SL .387** .134 .059 –.176 –.388** 1

PH .403** .179 .147 .651** .461** .073 1

PM .555** –.082 .463** –.369** –.544** .377** –.116 1

NSS .515** –.093 .403* –.038 –.464** .392** .151 .500** 1

SW .175 .064 .303** –.498* –.363** .369** –.021 .470** .612** 1

NGS .157 –.115 .138 –.346** –.468** .443** –.245** .474** .609** .742** 1

GWS .130 .065 .280** –.429* –.368** .363** –.083 .445** .558** .947** .803** 1

1000GW .000 .468** .271** .121 .054 –.012 .417* .065 .086 .537** –.045 .550** 1

GY –.464** –.078 –.002 –.337** –.480** .081 –.327** .172 –.141 .148 .411* .441** .114 1

*, ** are significant atp£0.05 andp£0.01, respectively; DHE: days to heading; FLL: flag leaf length; FLW: flag leaf width; PL: peduncle length; PPL: peduncle projection length; SL: spike length; SW: spike weight; PH: plant height; PM: physiological maturity; NSS: number of spikelet per spike; SW: spike weight; NGS:

number of grain per spike; GWS: grain weight per spike; 1000GW: 1000-grain weight; GY: grain yield.

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CerealResearchCommunications RAJABIHASHJINetal.:GeneticDiversityofWheatGenotypes Table 3.Factor analysis for morphological traits in the 116 genotypes of durum wheat

FA DHE FLL FLW PL PPL SL PH PM NSS SW NGS GWS 1000GW

FA1 0.414 0.014 0.292 –0.486 –0.687 0.572 –0.186 0.736 0.695 0.852 0.832 0.858 0.266

FA2 0.370 0.374 0.420 0.733 0.485 0.099 0.828 –0.025 0.339 0.247 –0.102 0.182 0.461

FA3 –0.682 0.289 0.260 0.390 0.158 –0.294 –0.214 –0.291 –0.315 –0.320 0.013 0.384 0.630

FA4 0.219 0.705 0.422 –0.244 –0.368 0.155 –0.024 0.168 –0.286 –0.215 –0.320 –0.224 0.059

DHE: days to heading; FLL: flag leaf length; FLW: flag leaf width; PL: peduncle length; PPL: peduncle projection length; SL: spike length; SW: spike weight;

PH: plant height; PM: physiological maturity; NSS: number of spikelet per spike; SW: spike weight; NGS: number of grain per spike; GWS: grain weight per spike; 1000GW: 1000-grain weight.

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spike length and length of peduncle with about 22.4% of the total variability were ap- peared therefore it was named as height factor. The third factor included 1000-grain weight which accounted for 15.62% of the total variability in the dependence structure, which named as grain weight factor. The fourth factor included leaf length and leaf wide which accounted for 11.39% of the total variability in the dependence structure and it was named as leaf size factor.

The multiple regression analysis using stepwise method indicated that grain weight per spike and PM with positive effect, while NSS and PH with negative effect remained in the model. The model fitted for yield was fallow as:

Y (yield) = –188.32** + 0.36 (GWS) ** – 0.29 (NSS) ** + 0.38 (PM) ** – – 0.39 (PH) **, R²= 0.38

This four character accounting jointly with grain yield approximately 38% of yield variations. Grain weight per spike (GWS), number of spikelet per spike (NSS), physiological maturity (PM) and plant height (PH) entered in the equation in second, third and fourth po- sition, respectively, accounting jointly with grain yield approximately 32.7% of yield variations.

Evaluation of genetic diversity of durum wheat genotypes based on storage protein The SDS-PAGE analysis indicated three types of alleles at locus Glu-A1, eight types of alleles at locus Glu-B1 and 16 combine type alleles in high molecular weight glutenin subunits (Fig. 1). The locus Glu-A1 showed 75.2% ‘null’ allele, 8.2% allele 1 and 16.4% alleles 2* (Table S2).

The results showed that 48.75% and 18.56% of genotypes had allele 20 and 7 + 8 alleles on the locus GluB1, respectively. The 17 + 18 allele was detected in 18.8% of genotypes.

The genotype No. 15 (Wc-45501) carried a unique allele which was not fitted with the standard model. Moreover, 3.5% of the genotypes had allele 7, one genotype allele 22, 5.8% allele 6 + 8, 7% allele 13 + 16 and two genotypes showed 7 + 9 allele. At Glu-B1 lo-

Figure 1. SDS-PAGE polypeptide profile of the seed protein of durum wheat genotypes.

Lane 1 represents Falat, 2; Wc-45501, 3; P.S.No3, 4; Kc-678, 5; Wc-45012, 6; P.S.No29, 7; Wc-3122, 8; Eagle, 9; Kc-3653, 10; Wc-45648 and 11; Kc-3653. Protein samples were loaded

with equal amount of 15 µg

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cus, the allele 7 + 8 with 64.2% frequency was the most frequent allele. According to Nei (1978) index the genetic diversity in Glu-A1 and Glu-B1 locus was 0.42 and 0.81, respectively.

Cluster analysis

The Unweighted Pair Group Method with Arithmetic Average (UPGMA) cluster analysis of the 116 durum wheat genotypes based on the protein profiles using the Ward method generated seven clusters (Fig. S1). The first, second, and third clusters consisted of 14, 11, and 8 genotypes, respectively, while the fourth cluster included 63 genotypes, indicating the close similarity among more than a half of the genotypes. The rest of the genotypes distributed in the remaining groups. The alleles 21 and 22 were only found in genotypes Wc-45648 and Kc-1478, respectively. These genotypes were located separately in two different clusters. The distance between the extreme genotype in cluster analysis based on the protein profiles was 14.72.

The cluster analysis of 116 genotypes of durum wheat based on the morphological traits using the ward method produced six clusters at a Euclidean distance of 18.8. The first cluster included 13 genotypes, the second cluster contained 14 genotypes, the third cluster indicates 17 genotypes, the fourth cluster comprised of 11 genotypes, the fifth cluster comprised of 17 genotypes and the sixth cluster comprised of 44 genotypes.

The average values of genotypes in the first cluster for genomic score of HMW-GS, flag leaf length, day to heading, flag leaf width, plant height, spike length, number of spikelet per spike, spike weight, number of grain per spike, grain weight per spike, 1000-grain weight and grain yield were higher than the mean of total. In the first cluster line No. 85 (TN-12635), with the highest 1000-grain weight (64.04 g), 2* allele in the Glu-A1 locus and 17 + 18 allele in the Glu-B1 locus were the desirable genotype. The mean of heading time (a criterion for prematurity) in second and third group was signifi- cantly lower than the total average. Selected genotypes that grow faster to reach the final stage (to escape the stress of last season) and have a good yield, which was considered as a suitable method. In the sixth cluster, number 20 (wc-45501) and 77 (kc-4128) with an average of 181 days to heading a short time can be modified for prematurity breeding programs. The genotypes Wc-45648 and Kc-1478, which indicated a certain alleles, were located in the sixth cluster. The mean of plant height in second cluster was lower than the total average. Thus, the genotypes of second group can be used for breeding program with hybridization for a dwarf stem and increase in yield. Moreover, in this group the traits that were positively correlated with yield were higher than the total mean in the first group.

Thus, members of this group are suitable for breeding programs aimed at improving the yield.

Discussion

Characterization of diversity in crops is primarily based on morphometric evaluation, which is susceptible to ontogeny and environmental condition. It is desirable to compare any morphological characterization with molecular markers to realize the degree of asso-

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ciation between the two approaches. In the present study a positive correlation between the seed protein pattern and the morphometric traits was observed, indicating the similarity of the two approaches. The result also showed the negative and significant correlation between days to heading and grain yield. This result showed that the earliness has vital role in stability of durum wheat yield within the dry zones. In agreement with the reports of Housley et al. (1982) and Bruckner and Frohberg (1987), the findings of this study indicated that a significant correlation between days to maturity, length of peduncle and plant height, and a negative correlation between plant height and yield, while there was no significant correlation between grain yield and thousand-kernel weight. Shahid et al. (2002) reported that negative high significant correlation between plant height and grain yield, while Kashif and Khaliq (2004) reported that positive high significant correlation between plant height, spike length, spikelet per spike and 1000-grain weights with grain yield. The extent of genetic diversity observed in the present material is in conformity with breeding behaviour of the genotypes.

Factor analysis is a useful method to identify growth and morphological traits relevant to yield, which has been applied by Walton (1971). The factor analysis produced four main groups, which accounted for 74.4% of the total variability in the dependent structure.

A high correlation between FA1 and a variable indicates that the variable is associated with the direction of the maximum amount of variation in the data set. In agreement with the results of Naghavi et al. (2009), our results indicated high frequency of null allele at the Glu-A1 locus. Bellil et al. (2012) reported that the null allele was less than the 2* and 1 alleles. The most frequent allele at the Glu-B1 locus was the 20 allele. Boggini and Pogna (1989) and Carrillo et al. (1990) revealed that allele 20 had a negative effect on gluten strength. Our results showed that the HMWG subunit 20, coded at Glu-B1, had a differen- tial and negative effect on gluten strength and mixing properties similar to the results of Ram (2003). In addition the positive correlation of 13 + 16 and 7 + 8 subunits with the dough strength reported by Ram (2003). Moreover, previous studies showed that the HMWG subunit genes on chromosome 1A appear to have a negligible relationship with durum quality parameters in comparison to genes on chromosome 1B (Pogna et al. 1990;

Raciti et al. 2003). The genetic variability in Glu-A1 and Glu-B1 locus were 0.42 and 0.81, respectively. Hamdi et al. (2010) in a study conducted on 856 lines of durum wheat reported 0.04 and 0.57 genetic diversity for locus GluA1 and GluB1, respectively. High genetic variability at the Glu-B1 locus in comparison to locus Glu-A1 might be due to the variety and number of alleles at this gene locus. In agreement with the reports of Carmona et al. (2010) on Spanish emmer wheat and Turchetta et al. (1995) on Turkish and Italian durum wheat, our results indicated a high variability for the HMWG subunit with up to 16 allelic variants. In addition a high genetic variability was also observed for the HMWG subunit compositions in the studied genotypes. Raciti et al. (2003) showed that the HMWG subunit genes on chromosome 1A were a negligible relationship with durum quality parameters in comparison to the genes on chromosome 1B, while Boggini and Pogna (1989) and Carrillo et al. (1990) reported that the certain HMWG subunits were correlated with the quality of durum wheat. The ultimate aim of exploring the genetic potential of the isolated crops in germplasm banks is to make an informed decision on their

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conservation. Therefore, the genetic erosion of these materials could be higher than ex- pected (Hammer 2003). Several studies have suggested that the maintenance of genetic integrity of germplasm bank depend on handling of data, regeneration and storage (Steiner et al. 1997; Borner et al. 2000). In this respect, the evaluation and characterization of these germplasm bank by morphological and protein markers could be a great usefulness. Ac- cording to Franco et al. (2001) the study of phenotypic and genetic diversity to identify similar genotypes is important to protect, evaluate and utilize genetic resources to produce sufficient food for the population in the world. Consequently, the morphological and protein markers could be useful approaches to formulate crosses by selecting efficient genotypes to study the genetic diversity in different wheat genotypes to identify diverse paren- tal combinations and creating segregating progeny with high genetic variability. Despite, the plant breeding strategies have not resulted very much in the reduction of genetic (allelic) diversity. Therefore, an analysis of the agronomic characteristics, including their qualities, must be undertaken.

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Electronic Supplementary Material (ESM)

Electronic Supplementary Material (ESM) associated with this article can be found at the website of CRC at http://www.akademiai.com/content/120427/

Electronic SupplementaryTable S1. The genotype code and origin of 116 durum wheat genotypes Electronic SupplementaryTable S2.Glu-A1 and Glu-B1 locus alleles and rated quality of native durum wheat

Electronic SupplementaryFigure S1. Dendrogram generated by UPGMA clustering method based on seed protein profiles showing the phylogenetic relationships of the 116 genotypes of durum wheat