بررسی تنوع و ویژگی های ژنتیکی تعدادی از توده برنج رقم هاشمی با استفاده از صفات مورفولوژیک و نشانگرهای ریزماهواره

نوع مقاله: علمی پژوهشی

نویسندگان

1 دانشجوی کارشناسی‌ارشد ژنتیک، دانشکده علوم پایه، دانشگاه آزاد اسلامی واحد تنکابن، تنکابن، ایران

2 استادیار پژوهش، موسسه تحقیقات برنج کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، رشت، ایران

چکیده

برنج مهم‌ترین منبع غذایی بیش از نیمی از جمعیت جهان است. برنج هاشمی در حال حاضر در استان گیلان بیشترین میزان سطح زیر کشت را داشته و از لحاظ کیفیت پخت و مشتری پسندی بهتر از سایر ارقام می باشد. در این تحقیق به‌منظور بررسی تنوع ژنتیکی موجود در 20 توده محلی برنج هاشمی به‌همراه ارقام شاهد گوهر و هاشمی (معرفی‌شده توسط مؤسسه تحقیقات برنج کشور)، از 21 نشانگر ریز‌ماهواره، صفات مورفولوژیک و کیفیت دانه استفاده شد. نتایج نشان داد که تمامی صفات مورد مطالعه دارای اختلاف معنی‌داری در سطح احتمال یک درصد بودند. تجزیه خوشه‌ای با کمک نرم‌افزار R، ژنوتیپ‌های مورد مطالعه را به 4 گروه تقسیم کرد. بر اساس اطلاعات حاصل از نشانگرها در مجموع 96 آلل چند شکل با میانگین 57/4 آلل به‌ازای هر جفت آغازگر تکثیر شد. کمترین تعداد مربوط به نشانگر‌ RM249 با 3 آلل و بیشترین آن به‌ترتیب مربوط به نشانگر‌های RM19 و RM1109 با 6 آلل بود. میانگین تعداد آلل مؤثر 97/3 بود که RM249 با داشتن مقدار 25/2 کمترین و نشانگرهای RM413 و RM1109 با داشتن مقادیر 65/5 و 21/5 بیشترین مقادیر را دارا بودند. میانگین محتوای اطلاعات چند شکل (PIC) بدست آمده برای نشانگرهای ریز‌ماهواره، 69/0 بود. در تجزیه‌ی خوشه‌ای با ضریب تشابه جاکارد بر اساس نشانگرهای ریزماهواره، ژنوتیپ‌ها در 4 کلاستر طبقه‌بندی شدند. در مجموع نتایج تجزیه خوشه‌ای صفات مورفولوژیک و نشانگرهای ریزماهواره با هم مطابقت خوبی داشتند و توانستند افراد را بر اساس منشأ جغرافیایی خود گروه‌بندی نمایند. وجود تنوع ژنتیکی در توده‌های محلی برنج هاشمی، امکان خالص‌سازی و گزینش لاین‌های برتر، حفظ و استفاده از ژنوتیپ‌های مختلف را در برنامه‌های اصلاحی فراهم می‌کند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Evaluation of genetic diversity and genetic characteristics of some of Hashemi rice cultivars using morphological traits and microsatellite markers

نویسندگان [English]

  • ََAyda Dorreshte 1
  • Alireza Tarang 2
1 M.Sc. Student, Department of Science, Islamic Azad University of Tonekabon, Tonekabon, Iran
2 Assistant Professor, Rice Research Institute of Iran, Agricultural Research, Education and Extension Organization (AREEO), Rasht, Iran
چکیده [English]

Rice is the most important source of food for more than half of the world's population. Currently, Hashemi rice has the highest area under rice in Guilan province and is better than other varieties in terms of cooking quality and customer satisfaction. In this study, for the study the genetic diversity of 20 Hashemi cultivars genotypes and two varieties as control (Hashemi and gowhar- introduced by the Rice Research Institute of Iran), 21 polymorphic markers, morphological traits and grain quality were used. The results showed that all of studied traits had a significant difference at 1% level. The cluster analysis with the help of software R divided the studied genotypes into four groups. Based on the data from 21 markers, in total, 96 alleles were detected with the average of 4.57 alleles per locus. The highest number of alleles was observed in markers RM19 and RM1109 with 6 alleles and minimum number of alleles in marker RM249 with 3 alleles. The average number of effective alleles was 3.97. The RM249 had the lowest value of 2.25 and the RM413 and RM1109 markers had the highest values of 5.65 and 5.21, respectively. The average value of polymorphic information content (PIC) was 0.69 for SSR markers. Based on cluster analysis by using Jaccard coefficient and UPGMA method on the SSR markers, the genotypes were grouped in 4 clusters. In general, the results of cluster analysis of morphological traits and microsatellite markers were in good agreement and they could group individuals based on their geographical origin. Understanding the genetic diversity can further help to breeders in their breeding programs, especially in purification the best genotypes and preserving these genotypes in Iran's rice gene bank.

کلیدواژه‌ها [English]

  • Hashemi rice cultivar
  • Cluster analysis
  • Microsatellite
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