[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
Journal Information::
Articles archive::
For Authors::
For Reviewers::
Registration::
Contact us::
Site Facilities::
::
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
:: Volume 21, Issue 4 (Winter 2020 2020) ::
علوم زراعی 2020, 21(4): 368-385 Back to browse issues page
Identification of main and epistatic QTLs for grain yield related traits in a recombinant inbred lines population of rice (Oryza sativa L.)
Hossein Rahimsoroush , Farhand Nazarian Firouzabadi , Maryam Hosseini Chaleshtari , Ahmad Esmaeili , Ali Akbar Ebadi
Pofessor, Lorestan University, Khorramabad, Iran
Abstract:   (2218 Views)
Rice yield as a complex trait is the main target in most rice breeding programs. To map the main and epistatic QTLs controlling grain yield and yield components, an experiment was carried out using a 129 F6 recombinant inbred lines population (IRA population) originated from a cross between Alikazemi / IR67017-180-2-1-2, in 2015 growing season in two locations, Rasht and Tonekabon, Iran.  The experimental design was augmented design arrangment with five check cultivars in randomized complete block design with five replications. Analysis of variance showed that the linkage map consisted of 87 Single Sequence Repeats (SSRs) covering 1356.0 cM of rice genome in 12 linkage groups with an average distance of 15.58 cM spamming two markers. The results of combined analysis of variance for two locations, using composite interval mapping method, identified a total of 13 main QTLs on rice chromosomes for five measured traits. The qTN3 with 13.9% for tiller number per plant, the qFG4 with 11.6% for filled grain per panicle and the qGY6 with 15.6% for grain yield had significant positive additive effect. Furthermore, the qSG1 with 19.9% phenotypivc variation had a negative additive effect on the number of unfilled grain.panicle-1. These finding suggest that these QTLs can be used in rice breeding programs for improving grain yield. The interaction between additive effect (A) of QTLs and environment (E) was significant on grain yield and number of unfilled grain.panicle-1, but it was not significan on other traits. A total of 18 QTL pairs with significant additive × additive (AA) epistatic effect were identified for all traits. The highest epistasic effects were related to grain yield and number of unfilled grain.panicle-1 with six pairs of QTLs for each of these traits. Only one of the epistatic effects between qSG1-2 and qSG6 had significant AAE effect with a R2aae = of 3.4%. In addition, some QTLs were identified as three gene clusters controlling the grain yield, number of tiller.plant-1 and number of filled grain.panicle-1. Furthermore, five microsatellite markers including RM7551, RM8218-RM3417 and RM5302- RM283 0.2 to 5 cM distance from were identified as linked markers with qGY6, qFG4 and qSG1, respectively. These markers can be considered in the marker-assisted rice breeding program.
Keywords: Epistasis, Gene cluster, Phenotypic variation, QTL mapping and Rice.
Full-Text [PDF 1180 kb]   (1060 Downloads)    
Type of Study: Scientific & Research | Subject: Special
Received: 2020/03/3 | Accepted: 2020/03/3 | Published: 2020/03/3
References
1. Chaudhary, R. C. 1996. Standard Evaluation System for Rice. International Rice Research Institute, Manila. Philippines.##Hosseini Chaleshtari, M., S. Houshmand, S. Mohammadi, A. Tarang, M. Khoddambashi and H. R. Soroush. 2012. Mapping quantitative trait loci for plant height, heading time, growth duration and grain yield in two advanced back cross populations of rice. Iran. J. Crop Sci. 14(3): 235-249. (In Persian with English abstract).##Hosseini Chaleshtari, M., H. Rahimsourosh and S. Houshmand. 2014. Estimation of epistasis and interaction with environment to control of rice yield over four years. First International and 13th National Iranian Crop Science Congress, 26-28 Aug. 2014, Karaj, Iran. (In Persian with English abstract).##Hosseini, M., S. Houshmand, S. Mohamadi, A. Tarang, M. Khodambashi and H. Rahimsoroush. 2012. Detection of QTLs with main, epistatic and QTL × environment interaction effects for rice grain appearance quality traits using two populations of backcross inbred lines (BILs). Field Crops Res. 135: 97-106.##Manly, K. F., R. H. Cudmore Jr and J. M. Meer. 2001. Map Manager QTX, cross-platform software for genetic mapping. Mammalian Genome. 12: 930-932.##McCouch, S. R., L. Teytelman, Y. Xu, K. B. Lobos, K. Clare, M. Walton, B. Fu, R. Maghirang, Z. Li and Y. Xing. 2002. Development and mapping of 2240 new SSR markers for rice (Oryza sativa L.). DNA Res. 9: 199-207.##Murray, M. G. and W. F. Thompson. 1980. Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res. 8: 4321-4326.##Rabiei, B., M. Masaeli and A. Tarang. 2013. Identification of QTLs for grain yield and yield component in rice (Oryza sativa L.). Iran. J. Field Crop Sci. 44: 293-304. (In Persian with English abstract).##Rabiei, B., M. Valizadeh, B. Ghareyazie, M. Moghaddam and A. Ali. 2004. Identification of QTLs for rice grain size and shape of Iranian cultivars using SSR markers. Euphytica. 137: 325-332.##Rahimi, M., B. Rabiei, H. Dehghani and A. Tarang. 2014. Mapping main and epistatic QTLs for drought tolerance indices in F5 population of rice. New Genetic J. 4: 435-448.##Sabouri, A., M. Toorchi, B. Rabiei, S. Aharizad, A. Moumeni and R. Singh. 2010. Identification and mapping of QTLs for agronomic traits in indica-indica cross of rice (Oryza sativa L.). Cereal Res. Commun. 38: 317-326.##Satagopan, J. M., B. S. Yandell, M. A. Newton and T. C. Osborn. 1996. A Bayesian approach to detect quantitative trait loci using Markov Chain Monte Carlo. Genetics. 144: 805-816.##Singh, A., J. Carandang, Z. J. C. Gonzaga, B. C. Collard, A. M. Ismail and E. M. Septiningsih. 2017. Identification of QTLs for yield and agronomic traits in rice under stagnant flooding conditions. Rice. 10: 15.##Temnykh, S., W. D. Park, N. Ayres, S. Cartinhour, N. Hauck, L. Lipovich, Y. G. Cho, T. Ishii and S. R. McCouch. 2000. Mapping and genome organization of microsatellite sequences in rice (Oryza sativa L.). Theor. Appl. Genet. 100: 697-712.##Thomson, M., T. Tai, A. McClung, X. Lai, M. Hinga, K. Lobos, Y. Xu, C. Martinez and S. R. McCouch. 2003. Mapping quantitative trait loci for yield, yield components and morphological traits in an advanced backcross population between Oryza rufipogon and the Oryza sativa cultivar Jefferson. Theor. Appl. Genet. 107: 479-493.##Wang, C., J. Rutledge and D. Gianola. 1994. Bayesian analysis of mixed linear models via Gibbs sampling with an application to litter size in Iberian pigs. Genet. Select. Evol. 26: 91.##Wang, D., J. Zhu, Z. Li and A. Paterson. 1999. Mapping QTLs with epistatic effects and QTL× environment interactions by mixed linear model approaches. Theor. Appl. Genet. 99: 1255-1264.##Wang, P., Y. Xing, Z. Li and S. Yu. 2012a. Improving rice yield and quality by QTL pyramiding. Mol. Breed. 29: 903-913.##Wang, P., G. Zhou, K. Cui, Z. Li and S. Yu. 2012b. Clustered QTL for source leaf size and yield traits in rice (Oryza sativa L.). Mol. Breed. 29: 99-113.##Wang, X., Y. Pang, J. Zhang, Q. Zhang, Y. Tao, B. Feng, T. Zheng, J. Xu and Z. Li. 2014. Genetic background effects on QTL and QTL× environment interaction for yield and its component traits as revealed by reciprocal introgression lines in rice. The Crop J. 2: 345-357.##Wu, B., Z. Han and Y. Xing, 2013. Genome Mapping, Markers and QTLs. In: Q. Zhang and R.A. Wing (Eds.), Genetics and Genomics of Rice. Crops and Models, vol 5. Springer, New York, NY.##Xing, Y., Y. Tan, J. Hua, X. Sun, C. Xu and Q. Zhang. 2002. Characterization of the main effects, epistatic effects and their environmental interactions of QTLs on the genetic basis of yield traits in rice. Theor. Appl. Genet. 105: 248-257.##Yang, J., C. Hu, H. Hu, R. Yu, Z. Xia, X. Ye and J. Zhu. 2008. QTLNetwork: mapping and visualizing genetic architecture of complex traits in experimental populations. Bioinformatics. 24: 721-723.##Yang, J. and J. Zhu. 2005. Methods for predicting superior genotypes under multiple environments based on QTL effects. Theor. Appl. Genet. 110: 1268-1274.##Ye, Z., J. Wang, Q. Liu, M. Zhang, K. Zou and X. Fu. 2009. Genetic relationships among panicle characteristics of rice (Oryza sativa L.) using unconditional and conditional QTL analyses. J. Plant Biol. 52: 259-267.##You, A., X. Lu, H. Jin, X. Ren, K. Liu, G. Yang, H. Yang, L. Zhu and G. He. 2006. Identification of quantitative trait loci across recombinant inbred lines and testcross populations for traits of agronomic importance in rice. Genetics. 172: 1287-1300.##Yue, F., Z. Rong-rong, L. Ze-chuan, C. Li-yong, W. Xing-hua and C. Shi-hua. 2015. Quantitative trait locus analysis for rice yield traits under two nitrogen levels. Rice Sci. 22: 108-115.##Zhang, J., X. Ou, H. Hu, B. Du, W. Lv, L. Yang, D. Xing, J. Xu, X. Qiu and T. Zheng. 2018. Identification of QTLs for yield-related traits using two sets of introgression lines with a common donor parent in rice. Int. J. Agric. Biol. 20: 15-24.##Zhao, F., H. Zhu, R. Zeng, G. Zhang and S. Xu. 2016. Detection of additive and additive× environment interaction effects of QTLs for yield‐component traits of rice using single‐segment substitution lines (SSSLs). Plant Breed. 135: 452-458.##Zhao, J., K. Jiang, L. Yang, Q. Yang, X. Wan, Y. Cao, S. You, J. LUO, T. ZHANG and J. Zheng. 2013. QTL mapping for yield related components in a RIL population of rice. Chinese J. Rice Sci. 27: 344-352.##Zhu, M., D. Liu, W. Liu, D. Li, Y. Liao, J. Li, C. Fu, F. Fu, H. Huang and X. Zeng. 2017. QTL mapping using an ultra-high-density SNP map reveals a major locus for grain yield in an elite rice restorer R998. Sci. Reports. 7: 10914.##Zhuang, J. Y., Y. Y. Fan, Z. M. Rao, J. L. Wu, Y. W. Xia and K. L. Zheng. 2002. Analysis on additive effects and additive-by-additive epistatic effects of QTLs for yield traits in a recombinant inbred line population of rice. Theor. Appl. Genet. 105: 1137-1145.##Zou, G., H. Mei, H. Liu, G. Liu, S. Hu, X. Yu, M. Li, J. Wu and L. Luo. 2005. Grain yield responses to moisture regimes in a rice population: association among traits and genetic markers. Theor. Appl. Genet. 112: 106-113.##
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA



XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Rahimsoroush H, Nazarian Firouzabadi F, Hosseini Chaleshtari M, Esmaeili A, Ebadi A A. Identification of main and epistatic QTLs for grain yield related traits in a recombinant inbred lines population of rice (Oryza sativa L.). علوم زراعی 2020; 21 (4) :368-385
URL: http://agrobreedjournal.ir/article-1-1082-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 21, Issue 4 (Winter 2020 2020) Back to browse issues page
نشریه علوم زراعی ایران Iranian Journal of Crop Sciences
Persian site map - English site map - Created in 0.05 seconds with 37 queries by YEKTAWEB 4645