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QTL Mapping for Early Ground Cover in Wheat (Triticum aestivum L.) under Drought Stress


Affiliations
1 Division of Crop Improvement, Indian Institute of Pulses Research, Kanpur 208 024, India
2 Bioseeds Research Pvt Ltd, ICRISAT Campus, Hyderabad 500 033, India
3 Department of Genetics and Plant Breeding, College of Agriculture, GB Pant University of Agriculture and Technology, Pantnagar 263 145, India
4 ICAR-National Research Center for Plant Biotechnology, Pusa, New Delhi 110 012, India
5 Division of Genetics, Indian Agricultural Research Institute, Pusa, New Delhi 110 012, India
6 Indian Institute of Wheat and Barley Research, Karnal 132 001, India
7 Directorate of Research, Indian Agricultural Research Institute, Pusa, New Delhi 110 012, India
 

Early vigour had been a target trait for developing wheat varieties tolerant to moisture stress. Manifestation of this trait depends on the relative efficiency of a genotype to utilize the residual soil moisture and dew precipitation, thereby developing a good canopy in lesser time after emergence. Lack of proper quantification system had always prevented the use of early vigour as a dependable selection parameter under field conditions. Digital imaging intervention has facilitated phenotyping this parameter in the form of early ground cover (EGC). Utilizing this phenotyping strategy, we have identified a quantitative trait locus for EGC located on the chromosome 6A (short arm) with a significant additive component under moisture stress in the north western plain zone of India.

Keywords

Digital Ground Cover, Drought Tolerance, Early Ground Cover, Quantitative Trait Loci, Wheat.
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  • Department of Agriculture and Cooperation, Understanding drought. In Manual for Drought Management, Ministry of Agriculture, Government of India, 2009.

  • Mullan, D. J. and Garcia, M. B., Crop ground cover. In Physiological Breeding II: A Field Guide to Wheat Phenotyping (eds Pask, A. J. D. et al.), Mexico, 2012, DF, CIMMYT.

  • Mullan, D. J. and Reynolds, M. P., Quantifying genetic effects of ground cover on soil water evaporation using digital imaging. Funct. Plant Biol., 2010, 37(8), 703–712.

  • Federer, W. T. and Raghavarao, D., On augmented designs. Biometrics, 1975, 31, 39–45.

  • Zadoks, J. C., Chang, T. T. and Konzak, C. R., A decimal code for the growth stages of cereals. Weed Res., 1974, 14, 415–421.

  • R Core Team, R: A language and environment for statistical computing. R Foundation for statistical computing, Vienna, Austria, 2013; http://www.R-project.org

  • Somers, D. J., Isaac, P. and Edwards, K., A high-density microsatellite consensus map for bread wheat (Triticum aestivum L.). Theor. Appl. Genet., 2004, 109, 1105–1114.

  • Prabhu, K. V., Somers, D. J., Rakow, G. and Gugel, R. K., Molecular markers linked to white rust resistance in mustard Brassica juncea. Theor. Appl. Genet., 1998, 97, 865–870.

  • Singh, A., Pallavi, J. K., Gupta, P. and Prabhu, K. V., Identification of microsatellite markers linked to leaf rust adult plant resistance (APR) gene Lr48 in wheat. Plant Breed., 2011, 130, 31–34.

  • Lander, E. S., Green, P., Abrahamson, J., Barlow, A., Daly, M. J., Lincoln, S. E. and Newburg, I., MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics, 1987, 1, 174–218.

  • Wang, S., Basten, C. J. and Zeng, Z., Windows QTL cartographer. V2.0 Program in statistical genetics, North Carolina State University, North Carolina, 2004; http://www.statgen.ncsu.edu/qtlcart/WQTLCart.html

  • Evers, J. B., Vos, J, Fournier, C., Andrieu, B., Chelle, M. and Struik, P. C., Towards a genetic architectural modeling of tillering in Gramineae, as explified by spring wheat (Triticum aestivum). New Phytologist, 2005, 166, 801–812.

  • Ott, A., Trautschold, B. and Sandhu, D., Using microsatellites to understand the physical distribution of recombination on soybean chromosomes. PLoS ONE, 2011, 6(7), e22306; doi:10.1371/journal.pone.0022306

  • Collard, B. C. Y., Jahufer, M. Z. Z. and Pang, E. C. K., An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: The basic concepts. Euphytica, 2005, 142, 169–196.

  • Pinto, R. S., Mathews, K. L., Reynolds, M. P., McIntyre, C. L., Olivares-Villegas, J. J. and Chapman, S. C., Heat and drought adaptive QTL in a wheat population designed to minimize confounding agronomic effects. Theor. Appl. Genet., 2010, 121, 1001–1021.

  • Yang, D. L., Jing, R. L., Chang, X. P. and Li, W., Quantitative trait loci mapping for chlorophyll fluorescence and associated traits in wheat (Triticum aestivum). J. Int. Plant Biol., 2007, 49(5), 646–654.

  • Kumar, S., Kumar, U., Joshi, A. K., Sehgal, S. K., Vara Prasad, P. V. and Gill, B. S., Genomic characterization of drought tolerancerelated traits in spring wheat. Euphytica, 2012, 186, 265–276.


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  • QTL Mapping for Early Ground Cover in Wheat (Triticum aestivum L.) under Drought Stress

Abstract Views: 378  |  PDF Views: 165

Authors

Biswajit Mondal
Division of Crop Improvement, Indian Institute of Pulses Research, Kanpur 208 024, India
Anupam Singh
Bioseeds Research Pvt Ltd, ICRISAT Campus, Hyderabad 500 033, India
Aneeta Yadav
Department of Genetics and Plant Breeding, College of Agriculture, GB Pant University of Agriculture and Technology, Pantnagar 263 145, India
Ram Sewak Singh Tomar
ICAR-National Research Center for Plant Biotechnology, Pusa, New Delhi 110 012, India
Vinod
Division of Genetics, Indian Agricultural Research Institute, Pusa, New Delhi 110 012, India
Gyanendra Pratap Singh
Indian Institute of Wheat and Barley Research, Karnal 132 001, India
Kumble Vinod Prabhu
Directorate of Research, Indian Agricultural Research Institute, Pusa, New Delhi 110 012, India

Abstract


Early vigour had been a target trait for developing wheat varieties tolerant to moisture stress. Manifestation of this trait depends on the relative efficiency of a genotype to utilize the residual soil moisture and dew precipitation, thereby developing a good canopy in lesser time after emergence. Lack of proper quantification system had always prevented the use of early vigour as a dependable selection parameter under field conditions. Digital imaging intervention has facilitated phenotyping this parameter in the form of early ground cover (EGC). Utilizing this phenotyping strategy, we have identified a quantitative trait locus for EGC located on the chromosome 6A (short arm) with a significant additive component under moisture stress in the north western plain zone of India.

Keywords


Digital Ground Cover, Drought Tolerance, Early Ground Cover, Quantitative Trait Loci, Wheat.

References





DOI: https://doi.org/10.18520/cs%2Fv112%2Fi06%2F1266-1271