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بررسی اثر متقابل ژنوتیپ و محیط با جانهی داده ژنومی شبیه سازی شده با استفاده از مدل های حیوانی مختلف

نوع مقاله : مقاله پژوهشی

نویسنده

استادیار و عضو هیات علمی دانشگاه آزاد اسلامی واحد آستارا

چکیده

هدف از این تحقیق ارزیابی مدل­های تک-صفتی و چند-صفتی در سناریوهای مختلف ژنومی با در نظر گرفتن جانهی جهت برآورد صحت پیش­بینی ژنومی و تشخیص وجود اثر متقابل ژنوتیپ و محیط (G × E) بود. داده‌های ژنومی با تعداد متفاوت جایگاه­های صفات کمی (90 و 900) و سطوح مختلف عدم تعادل پیوستگی (کم و زیادLD = ) برای تراکم K50 شبیه‌سازی شدند. سپس به‌طور تصادفی 90 درصد نشانگرها حذف و در مرحله بعد این نشانگرها از طریق نرم‌افزار Flmpute (نسخه 2/2) جانهی شدند. میانگین صحت جانهی در سناریوهای با LD زیاد و کم به‌ترتیب 976/0 و 943/0 بود. در همه سناریوهای شبیه‌سازی‌شده تفاوت جزئی بین صحت ژنومی داده‌های اصلی و جانهی مشاهده شد. صحت ژنومی با کاهش سطح LD، وراثت­پذیری و همبستگی ژنتیکی بین صفات کاهش یافت. استفاده از مدل چند-صفتی نسبت به مدل تک- صفتی باعث افزایش صحت ژنومی شد. سطح LD و همبستگی ژنتیکی بین محیط­های مختلف، در صورت وجود اثر متقابل محیط و ژنوتیپ نقش مهمی را ایفا کردند. لحاظ کردن اثر متقابل ژنوتیپ و محیط و تأثیر آن بر افزایش صحت ژنومی از یک طرف و جانهی تراشه‌های با تراکم کم به تراکم زیاد (خصوصاً در سناریوهای با LD بالا) جهت کاهش هزینه‌های ژنومی از طرف دیگر، می‌تواند راه حل مناسب و کاربردی جهت بهبود انتخاب ژنومی باشد.

کلیدواژه‌ها

عنوان مقاله [English]

Investigation of genotype × environment interaction with considering imputation in simulated genomic data via different animal models

نویسنده [English]

  • Yousef Naderi

Assistant Professor, Islamic Azad University, Astara Branch

چکیده [English]

The objective of this study was evaluating single-trait and multiple-trait animal models with considering imputation in simulated genomic data to estimate the accuracies of genomic prediction across various genomic scenarios and to detect genotype × environment (G × E) interaction. Genomic data were simulated to reflect variations in number of QTL (90 and 900) and linkage disequilibrium (LD = low and high) using 50K SNP panel. Afterwards, 90 percent of the markers randomly removed and imputation was performed using FImpute software (version 2.2). The average accuracy of imputation for scenarios with high and low LD was 0.976 and 0.943, respectively. In all scenarios, negligible difference on the genomic accuracies was evident, when original genotypes and imputed genotypes were compared. The genomic accuracy reduced with decreasing the LD, heritability and the genetic correlation among the traits. Comparing to single-trait animal model, using multiple-trait animal model increased genomic accuracy. The level of LD and genetic correlation across environments play important roles providing genotype × environment interaction exists. On the one hand, considering genotype × environment interaction and its effect on increasing of genomic accuracy and imputation of low to high density marker panels (especially high LD scenarios) to reduce of the cost of genomic evaluation on the other hand could be a suitable and practical approach to improve genomic selection.

کلیدواژه‌ها [English]

  • Genomic accuracy
  • Genomic correlation
  • imputation accuracy
  • Linkage Disequilibrium
  • Multiple-trait animal model
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تولیدات دامی
دوره 20، شماره 3
آبان 1397
صفحه 375-387
فایل ها
هم رسانی
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