بررسی همخوانی گروه‌بندی ژنوتیپ‌های برنج آپلند و لولند با استفاده از نشانگرهای ریزماهواره و شاخص‌های تحمل به تنش خشکی

نوع مقاله: علمی پژوهشی

نویسندگان

1 دانشیار گروه زراعت و اصلاح نباتات دانشکده کشاورزی و منابع طبیعی دانشگاه محقق اردبیلی، اردبیل

2 دانش آموخته کارشناسی ارشد گروه زراعت و اصلاح نباتات دانشکده کشاورزی و منابع طبیعی دانشگاه محقق اردبیلی

3 دانشبار ژنتیک و به نژادی گیاهی دانشکده کشاورزی دانشگاه گیلان، رشت

4 دانشیار گروه زراعت و اصلاح نباتات دانشکده کشاورزی و منابع طبیعی دانشگاه محقق اردبیلی، اردبیل، ایران.

5 دانشجوی دکتری اصلاح نباتات، دانشکده کشاورزی، دانشگاه محقق اردبیلی، اردبیل، ایران

چکیده

یکی از روش‌هایی که می‌تواند میزان اعتبار نشانگرهای شناسایی شده را ارزیابی کند، بررسی هم‌خوانی گروه بندی افراد برپایه نشانگر‌های مولکولی و داده‌های فنوتیپی به‌دست‌آمده از آزمایش در شرایط عادی و تنش خشکی است. این پژوهش به منظور بررسی وجود ارتباط احتمالی بین نشانگر‌ SSR و شاخص‌های تحمل به تنش خشکی در ژنوتیپ‌های مورد نظر و همچنین گروه‌بندی ژنوتیپ‌ها بر اساس این نشانگر SSR و شاخص‌های تحمل به تنش خشکی با 40 ژنوتیپ برنج در دو محیط تنش و بدون تنش در قالب طرح بلوک‌های کامل تصادفی با سه تکرار به همراه 26 نشانگر ریزماهواره مرتبط با تحمل به تنش خشکی اجرا شد. در مجموع، 128 آلل چندشکل با میانگین 92/4 آلل به ازای هر جایگاه نشانگری تکثیر شد. بالاترین میزان PIC مربوط به نشانگر RM5672 (829/0) و کم‌‌ترین آن مربوط به نشانگر RM523(047/0) بود. تحلیل همبستگی بین عملکرد و شاخص‌های تحمل به تنش در دو شرایط تنش و بدون تنش، شاخص‌های تحمل به تنش (STI)، میانگین هندسی بهره‌وری (GMP)، شاخص میانگین عملکرد (MP) و شاخص عملکرد (YI) را به عنوان شاخص برتر در شناسایی ژنوتیپ‌های متحمل و حساس معرفی کرد. تجزیه خوشه‌ای ژنوتیپ‌های برنج مورد مطالعه به روش Ward براساس شاخص‌های تحمل به خشکی، آن‌ها را به سه گروه متحمل نیمه متحمل و حساس تقسیم کرد. با توجه به‌ این‌که ژنوتیپ‌های گروه دوم از لحاظ شاخص‌های فوق، دارای ارزش بالاتر از میانگین کل بودند، به عنوان ژنوتیپ‌های متحمل معرفی شدند که اغلب شامل ژنوتیپ‌های آپلند و یک ژنوتیپ هاشمی بودند. گروه اول نیمه متحمل و گروه سوم حساس شناخته شدند. تجزیه خوشه ای برپایه نشانگر‌های ریزماهواره نیز ژنوتیپ‌ها را به دو گروه تقسیم کرد. مقایسه این دو نوع گروه‌بندی بیانگر همخوانی شایان توجهی بین آن‌ها بود، طوری که در هر دو گروه‌بندی ژنوتیپ هاشمی قرابت نزدیکی با ژنوتیپ‌های آپلند نشان داد و همراه آن‌ها در یک گروه قرار گرفت.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Consistency of upland and Lowland rice genotypes grouping by microsatellite markers and drought tolerance indices

نویسندگان [English]

  • Omid Sofalian 1
  • Fatemeh Ajri 2
  • Atefeh Sabouri 3
  • Ali Asghari 4
  • Samira Hasanian 5
1 Assistant professor of Plant Breeding of Department of Agronomy & Plant Breeding, Faculty of Agricultural and Natural Resources, University of Mohaghegh Ardabili, Ardabil
2 MSc student of Plant Breeding of Department of Agronomy & Plant Breeding, Faculty of Agricultural and Natural Resources, University of Mohaghegh Ardabili, Ardabil.
3 Associate professor Genetic and Plant Breeding of Faculty of Agricultural Sciences, University of Guilan, Rasht
4 Associate professor of Plant Breeding of Department of Agronomy & Plant Breeding, Faculty of Agricultural and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran.
5 Ph.D Student of Plant Breeding, Department of Agronomy and Plant Breeding Dept., Faculty of Agricultural Sciences, University of Mohaghegh Ardabili, Ardabil 179
چکیده [English]

One way to assessing the validity of recognized markers is studing the consistency of case grouping based on molecular markers and phenotypic data obtained from the normal and drought stress conditions. In this study in order to assessing probable relationship between SSR molecular markers and drought tolerance indices in studding genotypes and grouping these genotypes based on SSR molecular markers and tolerance indices, 40 rice genotypes was used based on randomized complete block design with three replications in both normal and stress conditions. In addition, 26 microsattelite markers in relation with drought tolerance were used. Our results showed that 128 polymorphic alleles with 4.92 mean allele for each marker locus were amplified. The highest PIC value related to RM5672 (0.829) and the least related to RM523 (0.047). The corelation analysis between yield and tolerance indices in both two conditions confirmed that four indices; mean productivity (MP), geometric mean productivity (GMP), stress tolerance index (STI) and yield index (YI) were the best indices for sensitive and tolerant genotype discrimination. Grouping of genotypes based on cluster analysis using WARD method divided all of studding genotypes into three groups including tolerant, semi tolerant and sensitive. Considering the higher values of second group than the mean of the above indicators, they were introduced as tolerant genotypes, which often included upland genotypes and a Hashemi genotype. Based on our results thre firs group represent semi tolerant genotypes ant the third group represents sensitive genotypes. The cluster analysis based on microsatellite markers also divided genotypes into two groups. Comparison of these two types of grouping showed a significant correlation between them, so that in both groups the Hashemi genotype showed close proximity to the upland genotypes and was associated with them in one group.

کلیدواژه‌ها [English]

  • Cluster analysis
  • rice
  • principle component analysis
  • water deficient
  • SSR marker
Allahgholipor M, Mohamadsaleh, MS, Eebadi GHA (2004) Genetic variation in the classification of varieties of rice. J. Agri. Sci. 35(4), 973-981.

Arif M (2002) Molecular mapping of genes/QTLs affecting resistance to Xanthomonas oryzae pv. Oryzae and grain quality traits in rice (Oryza sativa L.). PhD thesis. University of Philippines in Los Banos. Philippines

Babu RCh (2010) Breeding for throught resistance in rice: An integrated view from physiology to genomics. J. Plant Breed. 1(4): 1133-1141.

Bernier J, kumar a, Ramaiah V, Spaner D, Atlin G (2007) A large-effect QTL for grain yield under reproductive-stage drought stress in upland rice. Crop sci. 47(2): 507-518.

Blum A (1996) Crop responses to drought and the interpretation of adaptation. Plant Growth Regul. 20: 135-148.

Bouslama M, Schapaugh WT (1984) Stress tolerance in soybean. Part 1: Evaluation of three screening techniques for heat and drought tolerance. Crop Sci. 24, 933-937.

Collard BCY, Mackill DJ (2008) Marker assisted selection: an approach for precision plant breeding in the twenty-first century. Phil. Trans. Biol. Sci. 363, 557-572.

David CSC (1991) The world rice economy, Challenges ahead. In: Khush, GS., Toenniessen, GH (eds) Rice Biotechnology. CAB International. UK. PP 19-54.

Diwan JM, Channbyregowda V, Shenoy P, Salimath Bhat R (2013) Molecular mapping of early vigor related QTLs in rice. Res. J. Biol. 1: 24-30.

Don RH, Cox PT, Wainwright BJ, Mattick JS (1991) Touchdown PCR to circumvent spurious priming during gene amplification. Nucleic Acids Res. 19:4008-4009.

Farshadfar E, Zamani M, Motallebi M, Imamjomeh A (2001) Selection for drought resistance in chickpea lines. Iran J. Agric. Sci. 32: 65-77.

Fernandez GC (1992) Effective selection criteria for assessing plant stress tolerance. In: Kuo, C. G. (ed.). Proceedings of the International Symposium on Adaptation of Vegetables and other Food Crop to Temperature and Water Stress, Taiwan, 13-18 August, pp. 257-270.

Fischer RA, Maurer R (1978) Drought resistance in spring wheat cultivars. I. Grain yield response. J. Agri. Res. 29, 897-912.

Gavuzzi P, Rizza F, Palumbo M, Campaline RG, Ricciardi GL, Borghi B (1997) Evaluation of field and laboratory predictors of drought and heat tolerance in winter cereals. J. Plant Sci. 77, 523-53.

Gravandy M, Farshadfar E, Kahrizi D (2010) Evaluation of drought tolerance in bread weat advanced genotypes in field and laboratory conditions. Seed Plant Improv. J. 26(2): 233-252.

Jabbari H, Akbari GA, Daneshian J, Alahdadi I, Shahbazian N (2009) Utilization ability of drought resistance indices in sunflower (Heliantus annus L.) hybrids. Electron. J. Crop Prod. 1(4), 1-17.

Kanagara, P., Silvas, K. & Babu, C. (2010) Microsatellite markers linked to drought resistance in rice (Oryza sativa L.). J. Current Sci. 98, 836-839.

Khorshidi Benam MB, Khoei F, Mirhadi MJ, Nourmohammadi Q (2001) Studying the effect of drought stress in different growth stages of potato. J. national agri. sci. 4(1): 48-58.

Lapitan VC, Brar DS, Abe T, Redona ED (2007) Assessment of genetic diversity of Pilippine rice carrying good quality traits using SSR markers. J. Breed. Sci. 57: 263-270.

Luan l, Wang X, Long WB, Liu YH, Tu SB, Zhao ZP, Kong FL, Yu MQ (2008) Microsatellite analysis of genetic variation and population genetic differentiation in autotetraploid and diploid rice. Bio. Genet. 46: 248-266.

Mackill, D.J. and Coffman, W.R. and Garrity, D.P. (1996) Rainfed lowland rice improvement. IRRI. P.O.BOX 933, 1099 Manila, Philippines.

Mackill D J, Ekanayake I J (1986) Rice backcross progeny differing in heat and drought tolerance at anthesis. Agro. Abstracts. p. 71.

Maleki A, Majidi-Hrvan I, Heidari-Sharif-Abad H, Nur-Mohammadi GH (2009) Evaluation of drought tolerance in bread wheat landraces and improved water conditions and drought stress. J. Agric. Sci. 5: 81-91.

McCouch SR, Teytelman L, Xu Y, Lobos K, Clare K, Walton M (2002) Development of 2243 new SSR markers for rice by the international rice microsatellite initiative. Proc. First International Rice Congress. China. 150-152.

Ming H, Fang-Min X, Li-Yun CH, Xiang-Qian ZH, Jojee L, Madonna D (2010) Comparative analysis of genetic diversity and structure in rice using ILP and SSR markers. Rice Sci. 17 (4): 257-268.

Mohammadi SA (2006) Analysis of molecular data from the view point of genetic diversity. Proceedings of Keynote Papers, 9th Iranian Crop Science Congress. 27-29 Aug. Aboreyhan Pardis, University of Tehran, Tehran, Iran. pp. 96-119.

Nazari L, Pakniat H (2010) Assessment of Drought Tolerance in Barley Genotypes. J. Appl. Sci. 10(2): 151-156.

Nourmand-Moay'yed F, Rostami MA, Ghonadha MR )2002( Evaluation of drought stress indices at bread wheat. J. Iran Agric Sci. 22: 4. 795-805.

Nori Z (2006) Molecular genetic diversity of rice varieties using microsatellite markers in comparison with the results of quantitative methods. MSc. Thesis. University of Gilan. pp 120.

Ni J, Colowit PM, Mackill DJ (2002) Evaluation of genetic diversity in rice subspecies using microsatellite markers. Crop Sci. 42: 601-607.

Pervaiz Z H, Rabbani MA, Khaliq I, Pearce S, Malik SA (2010) Genetic diversity associated with agronomic traits using microsatellite markers in Pakistani rice landraces. Electron. J. Biotech. 13 (3): 1-12.

Rabbani MA, Masood MSH, Shinwari ZKh, Shinozaki KY (2010) Genetic analysis of basmati and non-basmati Pakistani rice (Oryza sativa L.) cultivars using microsatellite markers. Pak. J. Bot. 42 (4): 2551-2564.

Rashidi V, Majidi I, Mohamadi SA, Moghadam Vahed M (2007) Determine of genetic relationship in durum wheat lines by cluster analysis and identity of morphological main characters in each gropes. J. Agri. Sci. 13(2): 441-450.

Rezaei M, Motamed MK, Yousefi A, Amiri E (2010) Evaluation of different irrigation management on rice yield. J. Water Soil. 24(3): 565-573.

Ribeiro-Carvalho C, Guedes-Pinto H, Igregas G (2004) High levels of genetic diversity throughout the range of Portuguese wheat landrace Barbela. Annal. Botan. 94: 699-705.

Rosielle AA, Hamblin J (1981) Theoretical aspect of selection for yield in stress and non-stress environment. Crop Sci. 21, 943-946.

Sabouri H, Sabouri A, Katami Nejad R (2011) Genetic analysis of agronomic traits in rice under drought stress using Inclusive Composite Interval Mapping. The 7thNational Biotechnology Congress of I.R. Iran.

Sabouri (2015) Study of genetic diversity of rice varieties based on tolerance to drought stress. Report of technical review of National project. Gonbad University. Golestan. Iran.

Safaei Chaeikar S, Rabiei B, Samizadeh H, Esfahani M (2008) Evaluation of tolerance to terminal drought stress in rice (Oryza sativa L.) genotypes. Iran J. Crop Sci. 9 (4): 315-331.

Sagha Maroof MA, Biyashev RM, Yang GP, Zhang Q, Allard RW (1994) Extraordinarily polymorphic microsatellite DNA in barely: Species diversity, chromosomal locations and population dynamics. P. Natl. Acad. Sci. USA. 91: 5466-5570.

Sheng-jun W, Zuo-mei L, Jian-min W (2006) Genetic diversity among parents of hybrid rice based on cluster analysis of morphological traits and simple sequence repeat markers. Rice Sci. 13(3): 155-160.

Song-ping HU, Hua YANG, Gui-hua ZOU, Hong-yan LIU, Guo-lan LIU, Han-wei MEI, Run CAI, Ming-shou LI, Li-junL UO (2007) Relationship Between Coleoptile Length and Drought Resistance and Their QTL Mapping in Rice. Rice Sci.14(1):13-20.

Sori J, Dehghani H, Sabaghpor SH (2005) Study of genotypes of chickpea in water stress condition. Iran J. Agri. Sci. 6: 1517-1527.

Switzer RC, Merril CR, Shifrin S (1979) A highly sensitive silver stain for detecting proteins and peptides in polyacrylamide gel. Anal. Biochem. 98: 231-237.

Tabkhkar N, Rabiei B, Sabouri A (2011) Evaluation allele frequency and polymorphism of microsatellite markers linked to gene loci controlling rice grain quality. Iran. J. Field Crop Sci. 42(3): 495-507.

Thomson MJ, de Ocampo M, Egdane J, Akhlasor Rahman M, Godwin Sajise A, Adorada DL, Tumimbang Raiz E, Blumwald E, Seraj ZI, Singh RK, Gregorio GB, Ismail AM (2010) Characterizing the Saltol quantitative trait locus for salinity tolerance in rice. Rice. 3(2): 148-160.

Venuprasad R, Bool ME, Quiatchon L, Atlin GN (2011) A QTL for rice grain yield in aerobic environments with large effects in three genetic backgrounds. Theor. Appl. Genet. 124 (2), 323-32.

Vikram P, Mallikarjuna Swamy BP, Dixit S, Ahmed HU, Sta Cruz MT, Singh AK, Kumar A (2011) qDTY 1.1, a major QTL for rice grain yield under reproductivestage- drought stress with a consistent effect in multiple elite genetic backgrounds. BMC Genet. 12: 89.

Wang XS, Zhu J, Mansueto L, Bruskiewich (2005) Identification of candidate genes for drought stress tolerance in rice by the integration of a genetic (QTL) map with the rice genome physical map. J. Zhejiang Univ. Sci. 6B (5): 382-388.

Yang X, Yan J, Shah T, Warburton ML, Li Q, Li L, Gao Y, Chai Y, Fu Z, Zhou Y, Xu S, Bai G, Meng Y, Zheng Y, Li J (2010) Genetic analysis and characterization of a new maize association mapping panel for quantitative trait loci dissection. Theor. Appl. Genet. 121, 417-431.