استراتژی‌های اصلاح جو تحت تنش خشکی: پاسخ‌ها، رویکردها و مدیریت

نوع مقاله : مروری

نویسندگان

1 گروه‎ ‎زیست سلولی مولکولی،‎ ‎دانشکده‎ ‎علوم‎ ‎و‎ ‎فناوری ‏زیستی،‎ ‎دانشگاه‎ ‎شهید‎ ‎بهشتی،‎ ‎تهران،‎ ‎ایران.

2 گروه زیست‌شناسی سیستم‌ها، پژوهشگاه بیوتکنولوژی کشاورزی ایران، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران.

چکیده

گیاهان بسته به نوع و رشد گیاه، از استراتژی‌های مختلفی برای مقابله با استرس غیر زنده استفاده می‌کنند. تنش خشکی یکی از مهمترین تنش‌های غیر زنده می‌باشد که بر عملکرد محصولات کشاورزی تأثیر می‌گذارد. علاوه بر این، تنش خشکی یکی از اصلی ترین عوامل محدود کننده در رشد گیاه است و می تواند تنفس و فتوسنتز را مهار کند و بنابراین بر رشد و متابولیسم فیزیولوژیکی گیاهان تأثیر گذارد. گیاهان چندین مکانیسم مانند تغییرات مورفولوژیک کنند. خشکیُ پیری برگ را تسریع و بیان هزاران ژن را تغییر داده و بر میزان پروتئین دانه و عملکرد دانه تأثیر می‌گذارد. با این حال، تنوع ژنوتیپی برای تحمل ناشی از خشکی در جو وجود دارد. در این بررسی ، این رویکردها می‌توانند به بهبود ژنوتیپ‌های جو در پاسخ به تنش خشکی از طریق اصلاح و صفات فیزیولوژیکی ، مهندسی ژنتیک و انتخاب به کمک نشانگر (MAS) کمک کنند. ژن ها و پروتئین های دخیل در پاسخ به تحمل خشکی را با استفاده از پروتئومیکس، ترنسکریپتومبکس و رویکردهای متابولومیکس در این مطالعه آورده شد. همچنین،QTL (مکان صفات کمی) های معرفی شده مربوط به عملکرد و صفات سبزماندگاری و فیزیولوژیکی موجود در این مطالعه می‌توانند برای بهبود جو در تحمل خشکی در آینده استفاده شوند. ابزارهای امیکس قدرتمندی برای تجزیه و تحلیل واکنش های گیاه به محرک های مختلف محیطی وجود دارد. به‌ویژه مطالعات مقایسه‌ای ژرم‌پلاسم‌های متنوع ژنتیکی که در معرض شرایط نامطلوب مانند خشکی قرار می‌گیرند، بینش‌های ارزشمندی را در مورد پاسخ‌های گیاه به تنش ارائه می‌دهند و ارزیابی مناسب داده های امیکس می تواند به فرآیند کشف نشانگرهای زیستی کمک کند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Strategies of Barley Improvement under water stress: Responses, ‎Approaches and Management ‎

نویسندگان [English]

  • Zohreh Hajibarat 1
  • Abbas Saidi 1
  • MohammadReza Ghaffari 2
  • Mehrshad Zeinalabedini 2
1 Department of Molecular Cell Biology, Faculty of Biotechnology, Shahid Beheshti University, Tehran, Iran.
2 Agricultural Biotechnology Research Institute of Iran, Department of Systems and Synthetic Biology, Karaj, Iran
چکیده [English]

Plants use a variety of strategies to cope with abiotic stress, depending on the species and the growth of the plant. Abiotic stresses such as drought is the most important stress that affects yield of agricultural products. In addition, drought stress is one of the main limiting factors in plant growth, it can also inhibit respiration, photosynthesis, and thus affects the growth and physiological metabolism of plants. Plants activate several mechanisms such as morphological and structural changes as well as the expression of drought-resistant genes, the synthesis of hormones and osmotic regulators to reduce drought stress. Drought accelerates grain leaf senescence, altering the expression of thousands of genes and ultimately affecting grain protein content and grain yield. However, the genotypic variability exists for drought induced disruption and tolerance in barley. In this review, the approaches can help for improving barley genotypes in response to drought stress through breeding and physiological traits, genetic engineering, and marker-assisted selection (MAS). We detected genes and proteins involved in response to drought-tolerance using proteomics, transcriptomics and metabolomics approaches. Also, the introduced Quatitatives Traits Loci (QTLs) related to yield and Stay green and physiological traits found in this study can be used for MAS in barley improvement for drought tolerance in the future. In particular, comparative studies of genetically diverse germplasm exposed to adverse conditions such as drought provide valuable insights into plant responses to stress and create information on biochemical pathways involved in adaptation to environmental limitations. Proper evaluation of omics data can help the biomarker discovery.

کلیدواژه‌ها [English]

  • Barley
  • Omics
  • Physiological Traits
  • Seed Filling
  • Marker-Assisted Selection
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