Research Report

Assessment of Genetic Diversity in Wheat (Triticum aestivum L.) under Elevated Yellow Rust Pressure  

 Izharullah1 , Amin Ur Rehman2 ,  Zakiullah1 , Shahid Iqbal1 ,  Shehzad1 , Muhammad Mohibullah3 ,  Irfanullah3
1 Faculty of Agriculture, University of Poonch Rawalakot, Azad Jammu and Kahmir (AJ&K)
2 National Agricultural Research Centre (NARC) Islamabad, Pakistan
3 Faculty of Agriculture, Gomal University Dera Ismail Khan (K.P.K), Pakistan
Author    Correspondence author
International Journal of Horticulture, 2017, Vol. 7, No. 5   doi: 10.5376/ijh.2017.07.0005
Received: 07 Jan., 2017    Accepted: 28 Feb., 2017    Published: 31 Mar., 2017
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Preferred citation for this article:

Izharullah, Rehman A.U., Zakiullah, Iqbal S., Shehzad, Mohibullah M., and Irfanullah, 2017, Assessment of genetic diversity in wheat (Triticum aestivum L.) under elevated yellow rust pressure, International Journal of Horticulture, 7(5): 33-39 (doi: 10.5376/ijh.2017.07.0005)

Abstract

The research work was carried out at national agriculture research center Islamabad (NARC) and Pakistan council of scientific and industrial research (PCSIR) Peshawar. The research was comprised of biochemical characterization SDS page and PCA to estimate the genetic diversity. The cultivar were consisted of cultivated varieties, elite varieties and advance line of (30) genotypes. To absorb Fe, Cr, Ca, Mn, Zn, Pb, Cu, Na, K, protein, moisture, concentration. Sodium Dodeceylsulphate Poly Acraylamide Gel Electrophoresis of wheat genotypes was conducted. The data was collected and subjected to analysis of un weighted pair group method with arithmetic averages (UPGMA) with statistica software package 0.5. In multivariate data analysis have 11 variables which have maximum variability. The more variation was observed among Inqilab-91, Bars-2009, Shafaq-2006, NARC-2009, Wc-24, and Sahakar-95. To produce more diverse genotypes we should cross among these varieties.

Keywords
Genetic Diversity; SDS; PCA

1 Introduction

Wheat a cereal grass of the Graminae (Poaceae) family and of the genus Triticum, is the world’s largest cereal crop. It has been described as the ‘King of cereals’ because of the acreage it occupies, high productivity and the prominent position it holds in the international food grain trade. Wheat is a rich source of carbohydrates, protein, essential amino acids except lysine, minerals such as phosphorus, magnesium, iron, copper & zinc and vitamins like thiamin, riboflavin, niacin and vitamin E (Khan and Zeb, 2007). Wheat holds a distinct position in Pakistani diet contributing more than 60% of the total protein & calorie requirements and about 80% of total dietary intake (Bostan and Naeem, 2002).

 

Bread wheat seed-storage proteins represent an important source of food and energy, being involved in the determination of bread-making quality (Cooke and Law, 1998). It is unique among cereals since its milled product “flour” is capable of forming the dough due to its gluten content. The unique characteristics of wheat can be attributed to the ability of its proteins gliadin and glutenin, which upon hydration form viscoelastic network gluten: the actual substance that imparts gas retention property to dough (Shah et al., 2008).

 

The polyacrylamide-gel electrophoresis has been used to show that large size variation exists among LMW and HMW glutenin subunits, and it has been suggested that deletions and insertions within the repetitive region are responsible for these variations in length (Benmoussa et al., 2000). Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) is widely used technique due to its validity and simplicity to describe genetic structure of crop germplasm (Laemmli, 1970). SDS-PAGE is considered to be reliable method because seed storage proteins are not influenced by environmental changes. Seed protein patterns obtained by electrophoresis have been successfully used to resolve the taxonomic and evolutionary problems of several crop plants (Ladizinsky and Hymowitz, 1979; Das and Mukherjee, 1995). In the recent years Principal component analysis (PCA) has been used for evaluation and characterization of data of foods as: cereal, honey, wine and others (Araujo et al., 2008).

 

Calcium is the most abundant mineral in the body. It constitutes 1.5% to 2% of the total body weight with more than 99% of the calcium being present in it. Phosphorus participates in many other body functions including energy metabolism, DNA synthesis, and calcium absorption and utilization. Magnesium is an extremely important mineral. Next to potassium, it is the second most predominate mineral within our cells. Magnesium also functions very closely with calcium and phosphorus. Approximately 60% of the magnesium in the body is found in bone, 26% in muscle, and the remainder in soft tissue and body fluids. Potassium, sodium, and chloride are electrolytes: mineral salts that can conduct electricity when they are dissolved in water. Chromium functions in the "glucose tolerance factor," a critical enzyme system involved in blood sugar regulation. Copper functions as an important factor in the manufacture of hemoglobin; collagen structures, particularly joints and arteries; and energy. Iron is critical to human life. It plays the central role in the hemoglobin molecule of our red blood cells (RBC), where it functions in transporting oxygen from the lungs to the body's tissues, and also transports carbon dioxide from the tissues to the lungs. In addition, iron also functions in several key enzymes in energy production and metabolism including DNA synthesis. Manganese functions in many enzyme systems, including enzymes involved in blood sugar control, energy metabolism, and thyroid hormone function. Zinc is a component in over 200 enzymes in our bodies. In fact, zinc functions in more enzymatic reactions than any other mineral Zinc may be critical to healthy male sex hormone and prostate function, as well. Male infertility may be caused by a decreased sperm count due to zinc deficiency, and zinc supplementation may increase sperm count and motility, particularly in men with low testosterone. Zinc deficiency may be a contributing factor in the high rate of prostate enlargement in this country.

 

2 Materials and Methods

The proposed Seed material was collected from various sources including NARC, BARS, AARI, UAF and CIMMYT were used to study the genetic variability in wheat (Triticum aestivum L) under elevated yellow rust pressure (Table 1). The research project was conducted at the National Agricultural Research Centre (NARC) Islamabad and PCSIR Laboratories, Peshawar. The research work was comprised of biochemical characterization and SDS-PAGE.

 

Table 1 Wheat germplasm used for genetic variability of wheat genotypes under elevated yellow rust pressure

 

Preparation of Seed Samples for Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE)

Single seed of each genotype was taken, crushed and grinded in mortar and pestle. 10 mg (0.01 g) seed flour was weighed by an electronic balance and was put into 1.5 ml Eppendorff’s tubes. To extract proteins from flour, 400 µl of the protein extraction buffer was put into the Eppendorff’s tube and mixed well with the help of vortex. This sample was preserved in a freezer (-20ºC).

 

Preparation of Electrophoretic Gel

Glass plates were used for electrophoresis after cleaning up from internal side with 80% Ethanol. Sets of glass plates were fixed with in a casting tray and marked 2 cm from the top. To make sure that there was no leakage; glass plate set ups was filled with water and placed for some time.

 

2.1 Electrophoresis

Electrophoresis procedure was carried out using slab type SDS-PAGE with 12.25% polyacrylamide gel. Electrode buffer solution was put into the bottom pool of the apparatus. Gel plates were placed in the apparatus, here again air bubble formation was avoided. Electrode buffer solution was also put into the top pool of the apparatus; was formed by combs were washed with distilled water using a syringe. 6.5 µl of supernatant of seed samples (Vortexed and centrifuged at 12,000 rpm for 10 minutes), was put into wells with the help of micropipette. Protein molecular weight marker was put in first well of each glass plate. The numbering of seed samples and wells was noted to avoid repetition. The apparatus was connected with + (red) and – (black) electrodes of power supply. The voltage of apparatus was kept constant at 50 V in stacking gel and 80 V at separation gel; apparatus was left until a blue line of BPB will reach at the bottom (2 mm above bottom) of the gel plates.

 

2.2 Detection of seed protein

Staining and De-staining of Separation gel

When blue line will reach at the bottom of the gel plates, electric supply was disconnected. Gel plates was taken out from the apparatus and separated by spatula. Stacking gel was removed with the help of same spatula. Separation gel was put in the tray which contained staining solution and was put on the shaker for two hours. Staining solution was exchanged by distaining solution and the tray was shacked gently overnight until the background of the gel disappeared to absorb excess CBB.

 

2.3 Drying of separation Gel

Wet filter paper was placed on the plate of gel dryer. Separation gel was carefully placed on the paper and was covered with a wrap. It was dried in a drier for about 1.5 hours at 60°C. When gel sheet was completely dried it was taken out. All gels were dried with the same manner. The gels will then be analyzed and photographed.

 

3 Results and Discussion

Results and discussion comprises of nutritional composition of wheat genotypes, estimation of genetic diversity of wheat genotypes by using SDS-PAGE of 30 genotypes of wheat grain minerals and nutrients. Each of them is separately discussed below:

 

Sodium Dodecylsulphate Poly acrylamide Gel Electrophoresis

The data presented in the Table 2 revealed from SDS-PAGE of 30 wheat genotypes (Figure 1; Figure 2; Figure 3) showed that the total number of banding fragments were 33, which were differently distributed in all the genotypes under studied. Advance wheat line 8973 generated 17 scorable bands, Tatara and Mehran-89 produced 16, 03FJ-26, Pirsabak-91 and Zarlashta have 15 bands, 9870, Bakhtawar-93, Noshera-96 and WC-24 produced 14 bands, Shafaq-2006, Shahkar-95, Sarsabz and Kohistan-97 contains 13 bands, Shafaq-2006, Shahkar-95, Sarsabz, BARS-2009, AS-2002, 98FJ13, Lasani-2008 and WC 13, generated 12 bands, GA-2002, NARC-2009 and GA-2002 generated 11 scorable bands, genotypes WC-25, WC 26 Pasban-90 contained 10 scorable bands, genotypes Sahar-2006, WC-4 and WC-11 hade 9 bands, genotypes WC 20 and Inqilab-91 contained 8 and 7 bands respectively.

 

Table 2 Distribution of seed storage protein variable bands in the examined genotypes resulted from SD S-PAGE (+ = present, - + absent.)

Note: * Molecular weight Marker, ** Names of genotypes mentioned in Table. 1

 

Figure 1 SDS PAGE in 10 Genotypes of Wheat

Note: 1= 94 R3, 2 = FJ 13, 3= 02FJ02, 4= FJ05, 5= 03FJ 26, 6= 04 FJ 26, 7= 04 FJS 35, 8= 8970, 9= 9073, 10 = WC-4

 

Figure 2 SDS PAGE in 10 Genotypes of Wheat

Note: 11= WC-7, 12= WC-9, 13= WC-8, 14= WC-11, 15= WC-13, 16= WC-15, 17= WC-18, 18= WC-19, 19= WC-20, 20= WC22

 

Figure 3 SDS PAGE in 10 Genotypes of Wheat

Note: 21= WC-24, 22= WC-25, 23= WC-26, 24= Mehran 89, 25= Inqilab 91, 26= Pirsabak 91, 27= Shahkar 95, 28= Bakhtawar 93, 29= Kohistan-97, 30= AS 2000

 

4 Cluster Analysis

Data revealed from SDS-PAGE of seed storage protein were subjected to the cluster analysis, which is an appropriated method for the assessment of similar and divergent genotypes by data matrix. Figure 4 showed that genotypes were grouped in to three clusters on the basis of protein banding pattern.

 

Figure 4 Dendrogram representing the genetic diversity on the basis of polypeptide banding pattern among 30 bread wheat genotypes

 

Cluster I

Cluster 1 contains eight genotypes; Marvi-2000, Shahkar-95, Inqilab-91, BARS-2009, Shafaq 2006, AS-2002, WC11 and Zarlashta at linkage distance of 0.40. Marvi 2000 and Zarlashta were outliers; these genotypes showed divergence as compare to other genotypes in this cluster. This cluster contains 26.66% of total genotypes under study. This cluster further contained three sub-clusters at linkage distance 0.25. Sub-cluster 1 comprises of genotypes Marvi-2000, Shahkar-95 and Inqlab-91. Theses genotypes have close association and less divergent among themselves. Sub-group 2 contains BARS-09, WC-25 and Shafaq-06. Sub-group 3 have only two genotypes; AS-2002 and WC-11 while Zarlasht is an outlier of main cluster. Most of the genotypes in this group showed similar banding pattern which indicate that they may have same parentage, so it is concluded that the genotypes should not be used for further breeding program as a parents among each other.

 

Cluster II

Cluster II contained 18 genotypes; GA-2002, Lasani-2008, 98FJ13, 9870, Noshera-96, WC-20, WC-24, WC-4, WC-13, WC-26, Baktawar-93, Sarsabz, Sahar-2006, Pasban-90, NARC-2009, Kohistan-97, Mehran-89 and Tatara. This cluster constitutes about 60 percent of the total genotypes used in the study. GA-2000 and Tatara are the outliers. At the linkage distance of 0.30 this cluster contains three sub-clusters. Sub-cluster 1 has ten genotypes; GA-2002, Lasani-2008, 98FJ13, 9870, Noshera-96, WC-20, WC-24, WC-4 and WC-13. These genotypes showed close affiliation with each other with less variability. Sub-cluster 2 comprises of three genotypes WC-26, Baktawar-93, Sarsabz and Sahar-2006. Theses genotypes have association with the sub-cluster 1 but disassociation with sub-cluster 3, which constituted about five genotypes; Pasban-90, NARC-2009, Kohistan-97, Mehran-89 and Tatara. Tatara is an outlier of the main cluster II. All the genotypes included in cluster II have close association with each other but have a divergence as compare to cluster I and cluster III. Hence these genotypes can be put under hybridization program for the future breeding strategies.

 

Cluster III

Figure 2 showed three genotypes; 03FJ-26, Pirsabak-91 and 8973 which constituted about 10 percent of the total genotypes used in the study. Advanced breeding line 8973 is an outlier in this cluster and overall genotypes under investigation. This can be concluded that 8973 is a much diverse genotype and showed great genetic variability.

 

Kakaei et al. (2011)­ done the cluster analysis with UPGMA method separated the genotypes into 2 clusters with banding pattern and fragment size ranged from 78, 70, 54, 35, 23, 24 and 16 kDa. Our findings are not very much similar to these results, fragment size of 150 KDa and above were isolated in our study. The studies of Yoon et al. (2010) showed the protein fragment sizes range from 160 to 22 KDa, these finding are very much in accordance with our findings. Alnaddaf et al. (2011) also used SDS-PAGE for the quality assessment protein fragments for the detection of suitable breeding line for the future breeding program. Ahmed et al. (2010) assessed genetic diversity among 32 advanced breeding lines wheat using biochemical markers (SDS-PAGE) and concluded higher molecular weight subunits (120 KDa) showed immense polymorphism than the lesser molecular weight. These results are not in association with our findings because in our findings lowers molecular weight protein fragments generated much polymorphic banding patterns i.e; 60 KDa to 20 KDa. Ayed et al. (2010) assessed genetic variability by using seed storage-proteins through sodium dodecylsulphate polyacrylamide gel electrophoresis SDS-PAGE and concluded that the seed storage protein profiling can be supportive markers in the studies of genetic divergence and germplasm classification, which can be used to enhance the competency of wheat breeding programs. It is finally concluded in the light of above mentioned studies that genotypes present in three clusters have higher genetic variability and can be used for the further breeding programs.

 

References

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