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استراتژیهای ژنتیکی و اصلاح نژادی برای بهبود صفات رشد و مقاومت به بیماری در آبزیپروری | ||
فصلنامه علمی زیست شناسی جانوری تجربی | ||
دوره 13، شماره 3 - شماره پیاپی 51، تیر 1404، صفحه 13-24 اصل مقاله (1.1 M) | ||
نوع مقاله: مقاله مروری | ||
شناسه دیجیتال (DOI): 10.30473/eab.2025.73409.1977 | ||
نویسندگان | ||
مجید پسندیده* 1؛ رضا پسندیده2 | ||
1گروه علوم دامی، دانشکده کشاورزی، دانشگاه شهرکرد، شهرکرد، ایران | ||
2پژوهشکده میگوی کشور، مؤسسه تحقیقات علوم شیلاتی کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی (AREEO)، بوشهر، ایران | ||
چکیده | ||
در آبزیپروری، پیشگیری از بیماری از طریق حذف، ریشهکنی و کنترل پرورشی راهکارهایی ناکارآمد، پرهزینه و ناپایدار هستند. برنامههای اصلاح نژادی برای بهبود ژنتیکی مقاومت به بیماری باعث کنترل طولانیمدت بیماری میشوند. انتخاب تودهای از بازماندگان در استخرهای آلوده از روشهای کلاسیک برای بهبود مقاومت به بیماری میباشد. در این روش، با جمعآوری بازماندگان از استخرهای آلوده به ویروس و پس از چند نسل انتخاب، افزایش میزان بازماندگی ایجاد میشود. روش دیگر، استفاده از آزمایش مواجههسازی با بیماری است که با در معرض قراردادن خانوادههای مختلف با ویروس زنده، خانوادههای برتر انتخاب میشوند. روشهای ژنتیکی مدرن برای مقاومت به بیماری شامل استفاده از نشانگرهای ریزماهواره، مطالعات گسترده ارتباط ژنومی (GWAS)، انتخاب ژنومی (GS) و کریسپر (CRISPR) میباشند که در این مقاله بررسی میشوند. از نشانگرهای ریزماهواره برای تعیین ژنوتیپ مولدین و نظارت بر تنوع ژنتیکی جمعیتها استفاده میشود. مطالعات گسترده ارتباط ژنومی با بررسی ارتباط ژنوتیپ و فنوتیپ باعث شناسایی مناطق ژنومی مؤثر بر مقاومت به بیماری میشوند. انتخاب ژنومی پیشرفتهترین روش برای استفاده در برنامههای اصلاح نژادی آبزیپروری میباشد. ویرایش ژنوم با واسطه کریسپر و تراریختی با ژنهای پپتید ضد میکروبی (AMGs) روی سیستم ایمنی ذاتی ماهی مؤثر است. توسعه لاینهای مقاوم در برابر بیماریهای خاص و کراسینگ آنها برای تولید هیبرید از راهکارهای در دسترس و تولید ماهی تراریخته مقاوم به بیماری بهعنوان دورنمای بهبود مقاومت به بیماری در آبزیان میباشند. | ||
کلیدواژهها | ||
آبزیپروری؛ برنامههای اصلاح نژادی؛ مطالعات گسترده ارتباط ژنومی؛ ویرایش ژنومی | ||
عنوان مقاله [English] | ||
Genetic and breeding strategies for improving growth traits and disease resistance in aquaculture | ||
نویسندگان [English] | ||
Majid Pasandideh1؛ Reza Pasandideh2 | ||
1Department of Animal Science, Faculty of Agriculture, Shahrekord University, Shahrekord, Iran | ||
2Iranian Shrimp Research Center, Iranian Fisheries Science Research Institute, Agricultural Research, Education & Extension Organization (AREEO), Bushehr, Iran | ||
چکیده [English] | ||
In aquaculture, disease prevention through elimination, eradication and cultural control are inefficient, costly and unstable solutions. Breeding programs for genetic improvement of disease resistance lead to a long-term sustainable disease control. Mass selection of survivors in contaminated ponds is a classic method for improving disease resistance. In this method, by collecting survivors from virus-infected pools and selecting after several generations, an increase in survival rate is created. Another method is to use a disease challenge test, which exposes different families to live virus and selects the best families. Modern genetic approaches for disease resistance include the use of microsatellite markers, Genome-wide association studies (GWAS), Genomic selection (GS) and CRISPR, which are reviewed in this article. Microsatellite markers are used for genotyping of breeding stock and monitor the genetic diversity of populations. GWAS to survey genotype-phenotype association lead to the identification of genomic regions affecting disease resistance. GS is the most advanced method for use in aquaculture breeding programs. CRISPR/Cas9-mediated genome editing and transgenesis by antimicrobial peptide genes (AMGs) have been found to be effective on the innate immune system of fish. Development of lines resistant to specific diseases and crossing them to produce hybrids are available solutions, and producing disease-resistant transgenic fish is a prospect for improving disease resistance in aquatic animals. | ||
کلیدواژهها [English] | ||
Aquaculture, Breeding programs, Genome editing, GWAS | ||
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