Refine your search
Collections
Co-Authors
Journals
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Deshmukh Vivek, V.
- Fine mapping of consistent quantitative trait loci for yield under drought stress using rice (Oryza sativa) recombinant inbred lines adapted to rainfed environment
Abstract Views :320 |
PDF Views:115
Authors
Affiliations
1 Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641 003, IN
1 Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641 003, IN
Source
Current Science, Vol 109, No 5 (2015), Pagination: 910-917Abstract
Drought stress is a serious constraint, especially in rainfed rice production, and breeding for drought tolerance by selection based on yield under stress, though effective, is slow Mapping quantitative trait loci (QTLs) for yield and its components under drought stress predominant in rainfed target populations of environment (TPE) will help overcome this limitation. In the present study, a subset of 143 F8 and F9 recombinant inbred (RI) lines derived from IR62266-42-6-2 (IR62266), a high-yielding indica ecotype and Norungan, a landrace from TPE, was used to map QTLs for yield and its components under drought predominant in TPE. A large effect yield QTL observed under drought stress in TPE was consistent across two years with a phenotypic variation of 31.3% and 37.9% and additive effect of 629.2 and 424.9 kg/ha Further, this region was fine-mapped to 94.0 kb with positive effect on grain yield under stress.Keywords
Comparative genomics, drought stress, fine mapping, quantitative trait locus, rice.Full Text
References
- Food and Agriculture Organization, 2012; http://www.fao.org/economic/est/publications/rice-publications/rice-market-monitorrmm/en/
- Food and Agriculture Organization, 2013; http://www.fao.org/economic/est/publications/rice-publications/rice-market-monitorrmm/en/
- Hanson, A. D., Peacock, W. J., Evans, L. T., Arntzen, C. J. and Khush, G. S., Drought resistance in rice. Nature, 1990, 345, 26–27.
- Pandey, S. and Bhandari, H., Introduction. In Economic Costs of Drought and Rice Farmers’ Coping Mechanisms. A Cross-Country Comparative Analysis (eds Pandey, S., Bhandary, H. and Hardy, B), International Rice Research Institute/World Scientific,Singapore, 2007, pp. 1–9.
- Kumar, A., Dixit, S., Ram, T., Yadaw, R. B., Mishra, K. K. and Mandal, N. P., Breeding high-yielding drought-tolerant rice:genetic variations and conventional and molecular approaches. J.Exp. Bot., 2014, 65, 6265–6278.
- Jongdee, B., Fukai, S. and Cooper, M., Genotypic variation for grain yield of rice under water-deficit conditions. In Proceedings of 9th Australian Agronomy Conference (eds Michalk, D. and Pratley, J.), Wagga Wagga, NSW, Australia, 1998, pp. 403–406.
- Salunkhe, A. S. et al., Fine mapping QTL for drought resistance traits in rice (Oryza sativa L.) using bulk segregant analysis. Mol.Biotechnol., 2011, 49, 90–95.
- Dixit, S., Singh, A. and Kumar, A., Rice breeding for high grain yield under drought: a strategic solution to a complex problem. Int. J. Agron., 2014, 863683, 13; doi:10.1155/2014/863683.
- Kumar, A., Bernier, J., Verulkar, S., Lafitte, H. R. and Atlin, G. N., Breeding for drought tolerance: direct selection for yield, response to selection and use of drought-tolerant donors in upland and lowland-adapted populations. Field Crops Res., 2008, 107,221–231.
- Venuprasad, R., Lafitte, H. R. and Atlin, G. N., Response to direct selection for grain yield under drought stress in rice. Crop Sci., 2007, 47, 285–293.
- Xu, Y. B., Molecular Breeding, CAB International, Wallingford UK, 2010.
- Bernier, J., Kumar, A., Ramaiah, V., Spaner, D. and Atlin, G., A large-effect QTL for grain yield under reproductive-stage drought stress in upland rice. Crop Sci., 2007, 47, 507–518.
- Kumar, R., Venuprasad, R. and Atlin, G. N., Genetic analysis of rainfed lowland rice drought tolerance under naturally-occurring stress in eastern India: heritability and QTL effects. Field Crops Res., 2007, 103, 42–52.
- Venuprasad, R., Bool, M. E., Dalid, C. O., Bernier, J., Kumar, A. and Atlin, G. N., Genetic loci responding to two cycles of divergent selection for grain yield under drought stress in a rice breeding population. Euphytica, 2009, 167, 261–269.
- Vikram, P., Swamy, B. P. M., Dixit. S., Ahmed, H. U., Sta Cruz, M. T., Singh, A. K. and Kumar, A., qDTY1.1, a major QTL for rice grain yield under reproductive-stage drought stress with a consistent effect in multiple elite genetic backgrounds. BMC Genet.,2011, 12(1), 89.
- Mishra, K. K. et al., qDTY12.1: a locus with a consistent effect on grain yield under drought in rice. BMC Genet., 2013, 14, 12.
- Courtois, B. et al., Locating QTLs controlling constitutive ischolar_main traits in the rice population IAC165xCo39. Euphytica, 2003, 134,335–345.
- Salekdeh, G. H., Siopongco, J., Wade, L. J., Ghareyazie, B. and Bennett, J., Proteomic analysis of rice leaves during drought stress and recovery. Proteomics, 2002, 2, 1131–1145.
- Dixit, S. et al., Fine mapping of QTLs for rice grain yield under drought reveals sub-QTLs conferring a response to variable drought severities. Theor. Appl. Genet., 2012, 125, 155–169.
- Lafitte, H. R. et al., Improvement of rice drought tolerance through backcross breeding: evaluation of donors and selection in drought nurseries. Field Crops Res., 2006, 97, 77–96.
- Atlin, G. N., Lafitte, H. R., Tao, D., Laza, M., Amante, M.and Courtois, B., Developing rice cultivars for high-fertility upland systems in the Asian tropics. Field Crops Res., 2006, 97,43–52.
- Tanksley, S. D. and McCouch, S. R., Seed banks and molecular maps: unblocking genetic potential from the wild. Science, 1997,277, 1063–1066.
- Babu, R. C. et al., Variation in ischolar_main penetration ability, osmotic adjustment and dehydration tolerance among accessions of rice adapted to rainfed lowland and upland ecosystems. Plant Breed.,2001, 120, 233–238.
- Babu, R. C., Pathan, M. S., Blum, A. and Nguyen, H. T., Comparison of measurement methods of osmotic adjustment in rice cultivars. Crop Sci., 1999, 39, 150–158.
- Siopongco, J. D. L. C., Sekiya, K., Yamauchi, A., Egdane, J., Ismail, A. M. and Wade, L. J., Stomatal responses in rainfed lowland rice to partial soil drying; comparison of two lines. Plant Prod. Sci., 2009, 12, 17–28.
- IRRI, International network for genetic evaluation of rice: standard evaluation system for rice. International Rice Research Institute, Los Banos, the Philippines, 1996.
- Gawel, N. J. and Jarret, R. L., A modified CTAB DNA extraction procedure for Musa and Ipomoea plant. Mol. Biol. Rep., 1991, 9, 262–266.
- SAS Institute Inc, SAS® 9.3. SAS Institute Inc, Cary, NC, USA, 2012.
- Lander, E. S., Green, P., Abrahamson, J., Barlow, A., Daly, M. J., Lincoln, S. E. and Newberg, L., MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics, 2009, 1, 174–181.
- Kosambi, D. D., The estimation of map distances from recombination values. Ann. Eugenet., 1944, 12(1), 172–175.
- Voorrips, R. E., MapChart: software for the graphical presentation of linkage maps and QTLs. J. Hered., 2002, 93, 77–78.
- Wang, S., Basten, J. and Zeng, Z. B., Windows QTL Cartographer 2.5. North Carolina State University, Raleigh, NC, 2013.
- Churchill, G. A. and Doerge, R. W., Empirical threshold values for quantitative trait mapping. Genetics, 1994, 138, 963–971.
- Suji, K. K. et al., Mapping QTLs for plant phenology and production traits using indica rice (Oryza sativa L.) lines adapted to rainfed environment. Mol. Biotechnol., 2012, 52, 151–160.
- Thongjuea, S., Ruanjaichon, V., Bruskiewich, R. and Vanavichit, A., RiceGeneThresher: a web-based application for mining genes underlying QTL in rice genome. Nucleic Acids Res., 2009, 37, D996–D1000.
- Berloo, R. V., GGT 2.0: versatile software for visualization and analysis of genetic data. J. Hered., 2008, 99, 232–236.
- Babu, R. C. et al., Genetic analysis of drought resistance in rice by molecular markers: association between secondary traits and field performance. Crop Sci., 2003, 43, 1457–1469.
- Cho, Y. G. et al., Identification of quantitative trait loci in rice for yield, yield components and agronomic traits across years and locations. Crop Sci., 2007, 47, 2403–2417.
- Zhuang, J. Y., Fan, Y. Y., Wu, J. L., Xia, Y. W. and Zheng, K. L., Comparison of the detection of QTL for yield traits in different generations of a rice cross using two mapping approaches. Yi Chuan Xue Bao, 2001, 28, 458–464.
- Zhou, S. X., Tian, F., Zhu, Z. F., Fu, Y. C., Wang, X. K. and Sun, C. Q., Identification of quantitative trait loci controlling drought tolerance at seedling stage in Chinese Dongxiang common wild rice (Oryza rufipogon G.). Acta Genet. Sin., 2006, 33, 551–558.
- Khowaja, F. S., Norton, G. J., Courtois, B. and Price, A. H., Improved resolution in the position of drought-related QTLs in a single mapping population of rice by meta-analysis. BMC Genomics, 2009, 10, 276–290.
- Swamy, B. P. M. and Sarla, N., Meta-analysis of yield QTLs derived from inter-specific crosses of rice reveals consensus regions and candidate genes. Plant Mol. Biol. Rep., 2010, 29, 663–680.
- Cho, Y. C. et al., QTLs analysis of yield and its related traits in wild rice relative Oryza rufipogon. Treat Crop Res., 2003, 4, 19–29.
- Brondani, C., Rangel, N., Brondani, V. and Ferreira, E., QTL mapping and introgression of yield-related traits from Oryza glumaepatula to cultivated rice (Oryza sativa) using microsatellite markers. Theor. Appl. Genet., 2002, 104, 1192–1203.
- Marri, P. R., Sarla, N., Reddy, L. V. and Siddiq, E., Identification and mapping of yield and yield related QTLs from an Indian accession of Oryza rufipogon. BMC Genet., 2005, 6, 33.
- Moncada, P., Martinez, C. P., Borrero, J., Chatel, M., Gauch Jr, H., Guimaraes, E., Tohme, J. and McCouch, S. R., Quantitativetrait loci for yield and yield components in an Oryza sativa × Oryza rufipogon BC2F2 population evaluated in an upland environment. Theor. Appl. Genet., 2001, 102, 41–52.
- Qu, Y., Mu, P., Zhang, H., Chen, C.Y., Gao, Y., Tian, Y., Wen, F.and Li, Z., Mapping QTLs of ischolar_main morphological traits at different growth stages in rice. Genetica, 2008, 133, 187–200.
- Robin, S. et al., Mapping osmotic adjustment in an advanced back-cross inbred population of rice. Theor. Appl. Genet., 2003,107, 1288–1296.
- Li, W. et al., Proteomics analysis of alfalfa response to heat stress. PLoS ONE, 2013, 8, e82725; doi:10.1371/journal.pone.0082725.
- Zhang, H., Shen, G., Kuppu, S., Gaxiola, R. and Payton, P., Creating drought- and salt-tolerant cotton by overexpressing a vacuolar pyrophosphatase gene. Plant Signal Behav., 2011, 6, 861–863.
- Du, Z. Y., Chen, M. X., Chen, Q. F., Xiao, S. and Chye, M. L., Overexpression of Arabidopsis acyl-CoA-binding protein ACBP2 enhances drought tolerance. Plant Cell Environ., 2013, 36, 300–314.
- Hao, Z. F., Li, X. H., Xie, C. X., Li, M. S., Zhang, D. G., Bai, L. and Zhang, S. H., Two consensus quantitative trait loci clusters controlling anthesis–silking interval, ear setting and grain yield might be related with drought tolerance in maize. Ann. Appl. Biol.,2008, 153, 73–83.
- Yadav, R. S., Hash, C. T., Bidinger, F. R., Cavan, G. P. and Howarth, C. J., Quantitative trait loci associated with traits determining grain and stover yield in pearl millet under terminal drought-stress conditions. Theor. Appl. Genet., 2002, 104, 67–83.
- Wyrich, R. et al., The molecular basis of C4 photosynthesis in sorghum: isolation, characterization and RFLP mapping of mesophyll-and bundle-sheath-specific cDNAs obtained by differential screening. Plant Mol. Biol., 1998, 37, 319–335.
- Forster, B. P. et al., Genotype and phenotype associations with drought tolerance in barley tested in North Africa. Ann. Appl.Biol., 2004, 144, 157–168.
- Von Korff, M., Grando, S., Del Greco, A., This, D., Baum, M. and Ceccarelli, S., Quantitative trait loci associated with adaptation to Mediterranean dryland conditions in barley. Theor. Appl. Genet.,2008, 117, 653–669.