مطالعه ارتباط بین الگوی پروتئین دانه با صفات کمّی در برخی ارقام زراعی نخود (Cicer arietinum L.)

نوع مقاله : مقالات پژوهشی

نویسنده

دانشگاه پیام نور

چکیده

از جمله روش‌های مطالعه وجود تنوع‌ژنتیکی میان گونه‌های گیاهی، استفاده از روش الکتروفورز پروتئین‌های بذر می‌باشد. استفاده از نشانگرهای پروتئینی در جداسازی ارقام نخود به‌عنوان یک منبع ارزشمند غذایی مهم است. الگوی پروتئین‌های ذخیره‌ای چهار رقم نخود (آرمان، هاشم، ILC-482 و آزاد) با روش SDS-PAGE بررسی شد. برای این منظور از ژل 5/12درصد پلی‌اکریل‌آمید استفاده گردید. نتایج الکتروفورز نشان داد که تفاوت الگوی پروتئینی ارقام مورد مطالعه بیشتر مربوط به باندهای پروتئینی موقعیت 17 و 25کیلودالتون است. بر اساس نتایج SDS-PAGE، به‌طور میانگین 75/28باند پروتئینی، در محدود 14 تا 100کیلودالتون شناسایی گردید. حضور باندهای پروتیئنی با وزن تقریبی 17کیلودالتون در الگوی پروتئینی ارقامILC-482 ، هاشم و آزاد می‌تواند به‌عنوان نشانگرهای پروتئینی برای این ارقام و باند پروتئینی 14کیلودالتون برای رقم آرمان معرفی شوند. دو رقم ILC-482 و آرمان و نیز هاشم، به‌ترتیب بیشترین و کمترین تعداد باند را داشتند و بیشترین فاصله ژنتیکی بین ارقام ILC-482 و آرمان مشاهده شد. ماتریس تشابه محاسبه و تجزیه خوشه‌ای بر اساس ضریب تشابه جاکارد به روش UPGMA انجام گردید. در رنگ‌آمیزی با کوماسی‌بلو دامنه ضرایب تشابه از 78/0 تا 87/0 متغیر بود. جهت تعیین همبستگی بین صفات زراعی و مولکولی از آزمون مانتل-هانزل (Mantel-Hansel) استفاده شد و همبستگی بین صفات زراعی در شرایط تنش خشکی و شرایط آبیاری تکمیلی با داده‌های مولکولی مشاهده گردید P<%5)). با بررسی شاخص‌های تنش خشکی و نتایج حاصل از بای‌پلات رقم آرمان به‌عنوان متحمل‌ترین رقم شناخته شد و در هر دو شرایط محیطی تنش خشکی و بدون تنش عملکرد بالاتری نسبت به سایر ارقام از خود بروز داد. همچنین تجزیه بای‌پلات نشان داد که شاخص‌های YI و HAM بهترین شاخص‌های تحمل به خشکی بودند.

کلیدواژه‌ها

عنوان مقاله [English]

Study of relationship among seed proteins pattern with quantitative traits in some of chickpea (Cicer arietinum L.) cultivars

نویسنده [English]

  • Mehdi Kakaei
Payam-e- Noor
چکیده [English]

Introduction
Abiotic stress limits crop productivity, and plays a major role in determining the distribution of plant species across different types of environments. Chickpea (Cicer arietinum L.) is an important legume crop in Iran. Genetic diversity information is crucial for the choice of proper parents to establish new breeding programs. A number of molecular techniques have been developed to unveil the genetic potentials of plant materials. One of the most important methods for studying genetic diversity is using of Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE) analysis of seed protein.SDS-PAGE seems to be a reliable molecular marker to investigate the genetic diversity of chickpea genotypes in IRAN. SDS-PAGE is practically a reliable method because seed storage proteins are largely independent of environmental fluctuation. The main objectives of present research was: (1) to investigate the power of SDS-PAGE markers for estimation of genetic diversity among some chickpea genotypes in west of Iran, (2) to investigate the genetic relationships between chickpea genotypes and (3) to determine and studying main drought indexes in chickpea genotypes could be selected main cultivars in drought and non-drought condition. This information will be useful to improve techniques for sampling chickpea genetic variation which might increase efficiency of conservation of germplasm.
 
Materials & Methods
Field experiment was carried out with four chickpea cultivars, based on randomized complete blocks design (RCBD) with three replications at the research farm of the Payame Noor University center of Asadabad in two different conditions (Drought conditions and supplementary irrigation) during 2010 cropping season. The cultivars were taken from Dryland Agricultural Research Institute, Sararood. In this study, seed protein profile of four chickpea cultivars include Arman, Hashem, Azad and ILC-482, were analyzed by Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE using 12/5% polyacrylamide). Protein extraction and gel electrophoresis was done By Laemmle (1970) Method. The seeds were powdered separately by liquid nitrogen. Cultivars seed protein were extracted by extraction buffer. At end of electrophoresis, protein bands were revealed by Coomassie Brilliant Blue R-250 staining. Biplot, 3D Plot, coefficient jaccard, cluster analysis and other analyses were done using the statistical software MSTAT-C, NTSYS and SPSS. The data for each cultivar was collected on a plot basis.
 
Results & Discussion
SDS-PAGE analysis showed significant differences between four cultivars chickpea at 17 and 25 kilo Dalton (kDa) bands. There are strong and weak proteins bands differences between cultivars. On the basis of SDS-PAGE results, 28.75 protein bands were observed with the Molecular Weight (MW) of 14 to 100 kDa. The presence of protein bands about 17 (kDa) in protein pattern of ILC-482, Hashem and Azad Cultivars and the absence of protein bands with approximate molecular weight 14 (kDa) in protein pattern of Arman cultivar can be used as protein markers for these chickpea cultivars. The specific proteins bands of seed may be used as markers for identification of the genotypes. Correlation between agronomic and molecular traits was assessed using Mantel test and significant positive correlation was observed between them. The results of drought stress indices and Biplot analysis suggested Arman genotype was the most tolerant. Biplot analysis also showed HAM and YI selection indices were the best to identify drought tolerant genotypes.
 
Conclusion
In most cases, an intermediate level of polymorphism have been reported with SDS-PAGE markers, and this study showed a considerable amount of polymorphism. We recommend further studies to be conducted by using number of chickpea genotypes as well as bigger and DNA molecular markers. Results of this study can be used in germplasm management practices, developing plant geneticist and breeders for planning future explorations, and crop improvement purposes.

کلیدواژه‌ها [English]

  • Drought tolerance indices
  • Biplot
  • Supplementary irrigation
  • Quantitative traits
  • Protein detection
  • Mantel test

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