بررسی تنوع ژنتیکی گوسفند نژادهای بومی (افشاری، قزل و مغانی) و خارجی (دورپر، مرینوس و رامنی) با استفاده از اطلاعات نشانگری متراکم

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی سابق کارشناسی ارشد ژنتیک و اصلاح نژاد دام، گروه علوم دامی، دانشکده کشاورزی، دانشگاه زنجان

2 استادیار، گروه علوم دامی، دانشکده کشاورزی، دانشگاه زنجان

3 دانشیار، گروه علوم دامی، دانشکده کشاورزی، دانشگاه زنجان

چکیده

استفاده از نشانگرهای مولکولی در سال­های اخیر جهت تعیین تنوع ژنتیکی بین جمعیت­ها و گونه­های مختلف جانوری کاربرد گسترده­ای یافته است. مطالعات ژنتیک مولکولی، مقایسه تنوع ژنتیکی درون و بین نژادها و بازسازی از تاریخ نژاد و جمعیت اجدادی را امکان­پذیر می­نماید .این تحقیق با بررسی ساختار ژنتیکی در نژادهای بومی و خارجی با استفاده از 50000 نشانگر SNP با هدف شناسایی تنوع ژنتیکی انجام شد. اطلاعات ژنوتیپی مورد نیاز از پروژه Ovine HapMapشامل نژادهای بومی (نژاد افشاری، مغانی و قزل) و خارجی (نژاد دورپر، مرینوس و رامنی) اخذ گردید. آنالیز آماری با استفاده از چندین روش لایه­بندی جمعیت، بررسی ساختار جمعیت با استفاده از آمار چند متغیره بیزی و روش مبتنی بر مدل بررسی شد. نتایج به‌دست‌آمده از آنالیز مشخص مؤلفه­های اصلی، تفکیک نژادهای ایرانی و خارجی را به‌خوبی نشان داد و هر دو تصویر آشکاری از ساختار ژنتیکی جمعیت­های مورد بررسی را نشان داد. در روش DAPC، برای ارزیابی شمار بهینه خوشه با معیار ارزیابی BIC، 4K=بهترین نتیجه را نشان داد. علی‌رغم این‌که در این مطالعه از روش­های مختلف برای بررسی ساختار جمعیت استفاده شد، همه این روش­ها توانستند ساختار جمعیت­های بومی و خارجی را متمایز از هم نشان دهند که نژادهای ایرانی بررسی‌شده (افشاری، مغانی و قزل) در مقایسه با نژادهای خارجی دارای تشابه ژنتیکی بیشتری بوده و در یک گروه نژادی و نژادهای دورپر، مرینوس و رامنی در گروه­های مجزای ژنتیکی قرار گرفتند. البته زمانی‌که نژادهای داخلی به تنهایی مورد بررسی قرار گرفتند. این نژادها از لحاظ ژنتیکی کاملاً از هم متمایز بودند و میزان آماره تمایز جمعیتی Fst برای نژادهای افشاری، مغانی و قزل به‌ترتیب 038/0، 107/0 و 298/0 برآورد شد.

کلیدواژه‌ها


عنوان مقاله [English]

Study of Genetic diversity of indigenous (Afshari, Moghani and Ghezel) and exotic (Romney, Merinos and Dorper) sheep breeds using high-density SNP markers

نویسندگان [English]

  • Roghayyeh Nabiloo 1
  • Mohammad Bagher Zandi Baghcheh Maryam 2
  • Mohammad Taher Harakinezhad 3
1 Former M. Sc. Student, Department of Animal Science, Faculty of Agriculture, University of Zanjan, Iran
2 Assistant Professor, Department of Animal Science, Faculty of Agriculture, University of Zanjan, Iran
3 Associate Professor, Department of Animal Science, Faculty of Agriculture, University of Zanjan, Iran
چکیده [English]

The use of molecular markers in recent years has been widely used to determine the genetic diversity between populations and animal species. Molecular genetics studies allow a comparison of genetic diversity within and across breeds and make a new insight to reconstruct the breed history and history of ancestral populations. The aim of this study was to investigate the genetic structure and genetic variation of indigenous and exotic sheep breeds using 50,000 SNP markers. Genotype data of indigenous breeds (Afshari, Ghezel and Moghani) and exotic breeds (Dorper, Merinos and Romney) were obtained from the Ovin HapMap project. Multiple population stratification analysis such as, population structure using multivariate statistics and model-based approach were applied. The result of all methods obviously showed the correct population differentiation. In DAPC K=4 inferred best cluster results by BIC. Despite the use of different methods, all of these methods showed a distinct structure for indigenous and exotic populations and it can be concluded that Iranian sheep breeds has more genetic similarity rather than exotic breeds and Iranian sheep breeds grouped as one category and Romney, Merinos and Dorper breeds were separated as distant groups. However, when the indigenous breeds were studied alone, the breeds were genetically separated and population differentiation statistic (Fst) for Afshari, Moghani and Qezel was 0.038, 0.107, and 0.298, respectively.

کلیدواژه‌ها [English]

  • Genetic diversity
  • indigenous breed
  • Population Stratification Analysis
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