تجزیه ارتباط و ساختار بخشی از ذخایر ژنتیکی برنج (Oryza sativa L.) بر اساس نشانگرهای ریزماهواره

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانش آموخته دکتری، گروه زراعت و اصلاح نباتات، دانشکده علوم کشاورزی دانشگاه گیلان، رشت، ایران

2 استادیار، گروه زراعت و اصلاح نباتات، دانشکده علوم کشاورزی دانشگاه گیلان، رشت، ایران

3 استاد، گروه زراعت و اصلاح نباتات، دانشکده علوم کشاورزی دانشگاه گیلان، رشت، ایران

4 استادیار پژوهش، بخش اصلاح و تهیه بذر، موسسه تحقیقات برنج کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، رشت، ایران

چکیده

ارزش اقتصادی یک رقم به صفات مختلف آن بستگی دارد و از این­رو اطلاع دقیق از رفتار ژنتیکی و شناسایی مکان­های ژنومی دخیل در کنترل این صفات می­تواند به به­نژادگر در اصلاح ارقام کمک کند. در این تحقیق، ارتباط و پیوستگی بین 25 نشانگر ریزماهواره با برخی از صفات مهم زراعی و مرفولوژیک در 121 لاین و رقم مختلف برنج از طریق مدل­های ارتباط­یابی شامل مدل خطی عمومی (GLM) و مدل خطی مخلوط (MLM) با استفاده از نرم­افزارهای Structure و Tassel مورد ارزیابی قرار گرفت. بر اساس 25 نشانگر ریزماهواره مورد استفاده در این مطالعه، ساختار ژنتیکی جمعیت به پنج زیرجمعیت فرعی (5=K) تقسیم شد که نتایج حاصل از رسم بارپلات نیز آن­را تایید کرد. در تجزیه ارتباطی با دو روش GLM و MLM، به­ترتیب 26 و 30 نشانگر، ارتباط معنی­داری را با صفات مورد مطالعه نشان دادند و تغییرات قابل توجهی از این صفات را توجیه کردند. وجود نشانگرهای مشترک در میان برخی صفات بررسی شده مانند ارتباط معنی­دار نشانگر RM5 با صفات طول و عرض برگ پرچم و نشانگر RM3355 با صفات تعداد روز تا 50 درصد گلدهی و ارتفاع بوته می­تواند ناشی از آثار پلیوتروپی و یا پیوستگی نواحی ژنومی دخیل در این صفات باشد. همچنین، نشانگرهای RM190 و RM6080 با ضریب تبیین بالابه­ترتیب با صفات طول شلتوک و عملکرد دانه منتسب شدند که می­توانند پس از آزمایش­های تکمیلی و تأیید نتایج، به­منظور شناسایی ژن­های رمزکننده این صفات، ناحیه ژنومی مربوطه اشباع و توالی­یابی شوند.

کلیدواژه‌ها


عنوان مقاله [English]

Association and structure analysis of some of rice (Oryza sativa L.) genetic resources based on microsatellite markers

نویسندگان [English]

  • Heydar Azizi 1
  • Ali Aalami 2
  • Masoud Esfahani 3
  • Ali Akbar Ebadi 4
1 Ph. D. Graduated, Dept. of Agronomy and Plant Breeding, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
2 Assist. Prof., Dept. of Agronomy and Plant Breeding, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
3 Prof., Dept. of Agronomy and Plant Breeding, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
4 Research Assist. Prof., Dept. of Seed Improvement, Rice Research Institute of Iran, Agricultural Research, Education and Extension Organization (AREEO), Rasht, Iran
چکیده [English]

The economic value of cultivar depends on different characteristics. Thus detailed knowledge on genetic behavior and identification of genomic loci involved in control of these traits could help to breeder to improve plant cultivars. In this investigation, relation and linkage among 25 microsatellite markers with some of important agromorphological traits in 121 different rice cultivars and lines were evaluated based on GLM and MLM association models using the Structure and Tassel software. Based on the 25 microsatellite markers used in this study, population genetic structure divided into five subpopulations (K=5) that barplat results also confirmed it. In association analysis based on GLM and MLM models, 26 and 30 loci showed significant relations with the evaluated traits, respectively, and confirmed considerable variations of this studied traits. In the present study, identified common markers between of some of assayed traits such as significant relation of RM5 marker with flag leaf length and width traits and RM3355 with days to 50% flowering and plant height traits can be due to pleiotropic effects or linkage between of genomic regions involved in these traits. Also RM190 and RM6080 markers with higher R2 were related to paddy length and grain yield, respectively, that these related region could be saturated and sequenced after complementary experiments and confirmation for identification of coding genes of these traits.

کلیدواژه‌ها [English]

  • Linkage disequilibrium
  • Pleiotropic
  • Population genetic structure
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