تجزيه داي آلل و نقشه يابي ژن هاي كمي مرتبط با تنش شوري در برنج

(Diallel analysis and QTL mapping of salinity tolerance in rice (Oryza sativa L

برنج يكي از مهمترين گياهان زراعي مي باشد كه به شوري حساس مي باشد و در مراحل مختلف رشد واكنش متفاوتي به شوري دارد. اين تحقيق به منظور آناليز ژنتيكي تحمل به شوري در برنج با استفاده از تجزيه داي آلل كامل با 7 والد در موسسه تحقيقات بين المللي برنج انجام گرديد. والدين شاملIR4630-22-2-5-1-3, FL478 (IR66946-3R-178-1-1), Pusa Basmati1 (PB1), CSR28, IR64, IR70023-4B-R-12-3-1, و Sadri (IRGC acc. 32329) بودند. در مرحله دوم تحقيق 232 گياه از جمعيت F2 حاصل از تلاقي×FL478 Sadri و 123 نشانگر SSRچند شكل براي نقشه يابي ژن هاي كمي مرتبط با تنش شوري استفاده گرديد. تنش شوري در مرحله رويشي در گلخانه dSm-1 12 و براي مرحله زايشي در مزرعه dSm-1 8-6 اعمال گرديد. نتايج تجزيه داي آلل نشان داد كه اثر تركيب پذيري عمومي ((GCA و خصوصي ( (SCAبراي همه صفات معني دار است. بر اساس اين نتايج والد FL478 بالاترين تركيب پذيري عمومي را براي صفات مرتبط با تحمل شوري مانند وزن ساقه چه و نسبت K-Na در مرحله رويشي و والد Sadri بالاترين تركيب پذيري عمومي را براي صفات مرتبط با تحمل به شوري در مرحله زايشي مانند عملكرد بذر را داشت. نسبت GCA- SCA براي بيشتر صفات حاكي از وجود هر دو واريانس غالبيت و افزايشي بود. براي نقشه يابي ژن هاي كمي از نرم افزار Qgene و روش CIM استفاده گرديد. بر اساس نتايج نقشه يابي ژن¬هاي كمي مرتبط با تنش شوري تعداد 35 QTL براي عملكرد و اجزاي آن بر روي 9 كروموزوم به جز كرموزوم هاي 11 و 12 به دست آمد. هشت QTL نقشه يابي شده بيش از 10 درصد از واريانس فنوتيپي صفت مرتبط را كنترل مي كردند كه مي توانند كانديد خوبي براي نقشه يابي دقيق باشند و در به نژادي برنج براي تنش شوري مورد استفاده قرار گيرند و همچنين در شناسايي ژن هاي درگير در تنش شوري به كار روند.

Salinity is one of the major environmental stresses that limits the productivity of rice. Salinity tolerance in rice varies with the growth stages. Seedling and reproductive stages are the most sensitive growth stages. Tolerance at reproductive stage is very closely associated with grain yield hence believed to be most crucial. The objectives of this study were to determine the genetic components of salinity tolerance using a seven-parent complete diallel analysis and to map major QTLs for reproductive-stage salinity tolerance in rice. The parental lines involved were IR4630-22-2-5-1-3, FL478 (IR66946-3R-178-1-1), Pusa Basmati1, CSR28, IR64, IR70023-4B-R-12-3-1 and Sadri. For the seedling stage experiment, the resulting 42 F1’s and seven parents were exposed to salinity stress 4 days after germination at EC 12 dS m-1 in IRRI greenhouse. For the reproductive stage experiment, the seven parents and 42 F1’s were exposed to salinity stress in the field condition after active tillering stage to maturity at EC 6 to 8 dS m-1. Data recording for seedling stage experiment was done 14 days after salinization, when the susceptible parents were severely affected. The general combining ability estimates revealed that among the parents, FL478 was good general combiner for salinity tolerance traits like shoot dry weight and K-Na ratio. Estimates of genetic parameters revealed that both additive and dominance effects were significant for all traits. The general combining ability estimates at reproductive stage revealed that among the parents, Sadri was the best general combiner for grain yield and good to average combiner for most of the yield components. Estimate of genetic parameters at reproductive stage revealed that both additive and dominance effects were significant for all traits. The 232 F2 progenies produced from the cross between Sadri and FL478, were used for phenotyping under salinity stress at reproductive stage and identification of associated QTL regions. The experiment was conducted in the artificially salinized field condition using salt stress of 6-8 dS m-1. A genetic linkage map was constructed using 123 microsatellite markers on 232 F2 progenies. The QTL identification was done through composite interval mapping using QGENE software. In total35 QTLs for yield components under salinity stress. These QTLs were distributed on all rice chromosomes except chromosomes 11 and 12. Of all 35 QTLs, eight QTLs accounted for more than 10% of the phenotypic variation. The QTLs detected in this study will be useful for fine-mapping, molecular breeding and for identifying useful genes for salinity tolerance.