شناسایی مکان‌‌های ژنی مرتبط با تحمّل به تنش خشکی در لاین‌‌های نوترکیب برنج ایرانی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناسی ارشد، رشته بیوتکنولوژی کشاورزی، دانشگاه گنبد کاووس، گلستان، ایران

2 دانشیار، گروه تولیدات گیاهی، دانشگاه گنبد کاووس، گلستان، ایران

3 استادیار، گروه تولیدات گیاهی، دانشگاه گنبد کاووس، گلستان، ایران

چکیده

هدف: این پژوهش با هدف شناسایی نشانگرهای پیوسته با ژن‌‌های کنترل‌‌کننده تحمّل به خشکی با استفاده از لاین‌های نوترکیب برنج انجام شد.
مواد و روش‌ها: 99 لاین نوترکیب نسل هشتم حاصل از تلاقی ارقام برنج طارم محلی × خزر در گلدانه‌‌های 5 کیلوگرمی کشت شدند. وزن دانه و خوشه، طول خوشه، تعداد خوشه بارور و نابارور، تعداد خوشه‌‌چه اولیه، طول، عرض و تعداد روزنه، وزن، حجم و طول ریشه ثبت شد. برای تهیه نقشه ژنتیکی از 65 نشانگر SSR و 12 نشانگر ISSR (با 44 آلل چند شکل) و 5 نشانگر iPBS (با 22 آلل چند شکل) و
2 نشانگر IRAP (با 8 آلل چند شکل) استفاده گردید.
یافته‌ها: نشانگرهای مورد استفاده 12 کروموزوم و 4/1047 سانتی‌مورگان از ژنوم برنج را پوشش
دادند. به ترتیب هفت و یازده QTL برای صفات در شرایط تنش خشکی و غرقاب مکان‌‌یابی شدند. QTLهای مربوط به تعداد خوشه نابارور و وزن خوشه در شرایط تنش خشکی در فاصله نشانگری
ISSR57-6-ISSR58-2 روی کروموزوم 1 همپوشانی داشتند. همچنین از بین QTLهای یافت شده در شرایط غرقاب دو QTL مربوط به تعداد خوشه‌‌چه اولیه و وزن خوشه روی کروموزوم 5 در فاصله نشانگری IRAP30-1 - ISSR2-1 هم‌مکانی نشان دادند. با توجه به اینکه qFGW-5، qPB-5، qSWD-5، qPLD-8، qFCN-3 و qSP-7a درصد قابل توجیهی از تغییرات را توجیه نمودند، بعد از تعییین اعتبار می‌‌توان از آن‌‌ها در برنامه‌‌های انتخاب به کمک نشانگر استفاده نمود.
 

کلیدواژه‌ها


عنوان مقاله [English]

Detection of gene loci related to drought tolerance in Iranian rice recombinant inbred lines

نویسندگان [English]

  • Fatemeh Amirkolaei 1
  • Hossein Sabouri 2
  • Liela Ahangar 3
  • Mehdi Zarei 3
  • Hossein Hossein Moghaddam 3
1 MA., Agricultural Biotechnology, Gonbad Kavous University, Golestan, Iran.
2 Associate Professor, Department of Plant Production, Gonbad Kavous University, Golestan, Iran.
3 Assistants Professor, Department of Plant Production, Gonbad Kavous University, Golestan, Iran.
چکیده [English]

Objectives: The aim of this study was to determine the linked markers to genes controlling drought tolerance using Iranian rice recombinant inbred lines.
Materials and Methods:In this study, 99 Recombinant Inbred Lines of Iranian rice population derived from the cross of Tarom and Khazar were planted based on randomized complete design in 5 kg pots at the greenhouse of Gonbad Kavous University in 2017. The studied traits were grain weight, Panicle weight, Panicle length, number of Panicle fertile, number of Panicle infertile and number of primary branches. To prepare a genetic map 265 SSR markers, 12 ISSR markers (44 polymorphic alleles), 5 iPBS markers (22 polymorphic alleles) and 2 IRAP markers (8 polymorphic alleles) were used.
Results:The markers were used belonged to 12 chromosomes and 1047.4 cM of rice genome were covered. Five QTLs for drought condition and nine QTLs in flooding were located. QTLs related to number of infertile panicle and panicle weight in drought condition mapped between ISSR57-6 and ISSR58-2 markers, on chromosome 1. Also, out of QTLs identified in flooding condition, two QTLs related to the number of primary branches collocated to panicle weights QTLs on chromosomes 5 in IRAP30-1-ISSR2-1 region. qFGW-5, qPB, qFCN-3 and qSP explained a high percentage of phenotypic variation. The detected major effect QTLs in this study can be used in marker-assisted selection breeding programs after validation.
 

کلیدواژه‌ها [English]

  • Rice
  • QTL marker
  • Recombinant Iranian rice lines
  • Gene loci
  • Drought stress
Lu C, Shen L, Tan Z, Xu Y, Chen Y, & et al. Comparative mapping of QTLs for agronomic traits of rice across environments using a doubled-haploid population. Theoretical and Applied Genetics. 2002; 93: 1211-1217.
Moradi A, Younesi O. Effects of osmo- and hydro- priming on seed parameters of grain sorghum (Sorghum bicolor L.). Australian Journal of Basic and Applied Sciences. 2009; 3:1696-1700.
FAO. FAOstat. Agriculture database. Rome: Food and Agriculture Organization; 2006. Available at: http://www.fao.org/faostat.
Pospisilova J, Synkova H & Rulcova J. Cytokinins and water stress. BiologiaPlantarum. 2000; 43: 321-328.
Haq TU, Akhtar J, Gorham J, Steele KA & Khalid M. Genetic mapping of QTLs, controlling shoot fresh and dry weight under salt stress in rice (Oryza sativa L.) Cross between CO39×Moroberekan. Pakistan Journal of Botany. 2008; 40(6): 2369-2381.
Gregorio GB, Senadhira D & Mendoza RD. Screening rice for salinity tolerance. IRRI Discussion Paper Series.1997; No. 22. Manila (Philippines): ln1erna1ional Rice Research Institute.
Gorantla M, Babu PR, Reddy Lachagari VB, Reddy AMM, Wusirika R, Bennetzen JL & Reddy AR. Identification of stress-responsive genes in an indica rice (Oryza sativa L.) Using ESTs generated from drought- stressed seedlings. Journal of Experimental Botany. 2007; 58: 253-265.
Voorrips RE. Map Chart: Software for the graphical presentation of linkage maps and QTLs. Journal of Heredity. 2002; 93(1): 77-78.
Sabouri H, Sabouri A & Khatami-Nejad R. Determination of QTLs of some traits related to drought tolerance in rice. Journal of Production and Processing of Crop and Gardening. 2011; 2(4): 1-12.
Cardinal AJ, Lee M & Moore KJ. Genetic mapping and analysis of quantitative trait loci affecting fiber and lignin content in maize. Theoritical and Appllied Genetics. 2003; 106: 866-874.
Collard BC & Mackill DJ. Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Philosophical Transactions of the Royal Society B:Biological Sciences. 2008; 363: 557-572.
Sabouri H & Mohammadalegh Sh. Dadras AIdentification of knowledgeable markers related to rice root characteristics in early stages of growth under drought stress conditions using relationship analysis. Iranian Crop Science. 2016; 48(1): 182-171.
Mei HW, Luo LJ, Ying CS & Wang YO. Gene actions of QTLs affecting several agronomic traits resolved in a recombinant inbred population and two testcross populations. Theoretical and Applied Genetics, 2003; 107: 89-101.
MacMillan K, Emrich K, Piepho HP, Mullins CE & Price AH. Assessing the importance of genotype × environment interaction for root traits in rice using a mapping population. II: Conventional QTL analysis. Theoretical and Applied Genetics. 2006; 113: 953-964.
Ahmadi J, Photokian MH & Fabrici Orang P. Investigation of the Relationship between Microsatellite Markers (SSR) and Functional Components QTLs in Rice (Oriza Sativa). Modern Genetic. 2008; 3(4): 55-45.
Sabouri H & Mohammadinejad Gh. Genetic Analysis of Rice Yield Components and Agronomic Traits Using QTL Mapping. 11th Iranian Congress of Agronomy and Plant Breeding. Tehran: Shahid Beheshti University; 2010.
Sabouri H, Mohammadalegh Sh, Karim Koshteh R & Najar Ajam M. Detection of genes controlling the morphological traits of rice root in Iranian rice recombinant inbred lines population caused Amberbo and Sepidrood cross. Cell and Molecular Research. 2016; 2(3): 233-218.
Price AH, Steele KA, Moo BJ & Jones RGW. Upland rice grown in soil-filled chambers and exposed to contrasting water deficit regimes. II. Mapping quantitative trait loci for root morphology and distribution. Field Crops Research. 2002; 76: 25-43.
Srividhya A, Vemireddy LR, Ramanarao PV, Sridhar S, Jayaprada M, Anuradha G, Srilakshmi B, Reddy HK, Hariprasad AS & ESiddiq A. Molecular Mapping of QTLs for Drought Related Traits at Seedling Stage under PEG Induced Stress Conditions in Rice. American Journal of Plant Sciences. 2011; 2: 190-201.
Miskin KE, Rasmusson DC, Moss DN. Inheritance and physiological effects of stomatal frequency in barley. Crop Science. 1972; 12: 780-783.
SaghiMaroof MA, Biyashev RM, Yang GP, Zhang Q, Allard RW. Extraordinarily polymorphic microsatellites DNA in barely species diversity, choromosomal location, and population dynamics. Proceeding of the Academy of Sciences, USA. 1994; 91: 5466-5570.
Manly KF & Olson JM. Overview of QTL mappingintroduction to Map Manager QTX. Mammalian Genome. 1999; 10: 327-334.
Takehisa H, Shimodate T, Fukuta Y, Ueda T, Yano M, Yamaya T, Kameya T & Sato T. Identification of quantitative trait loci for plant growth of rice in paddy field flooded with salt water. Field Crops Research. 2004; 89: 85-95.
Nelson JC. QGENE: Software for marker-based genomic analysis and breeding. Molecular Breeding. 1997; 3(3): 239-245.