R. Abbai, V. K. Singh, V. V. Nachimuthu, P. Sinha, R. Selvaraj et al., Haplotype analysis of key genes governing grain yield and quality traits across 3K RG panel reveals scope for the development of tailor-made rice with enhanced genetic gains, Plant Biotechnol J, vol.5, pp.1612-1622, 2019.

H. A. Agrama, G. C. Eizenga, and W. Yan, Association mapping of yield and its components in rice cultivars, Mol Breed, vol.19, issue.4, pp.341-356, 2007.

D. H. Alexander, J. Novembre, and K. Lange, Fast model-based estimation of ancestry in unrelated individuals, Genome Res, vol.19, issue.9, pp.1655-1664, 2009.

Z. Bao, A. Watanabe, K. Sasaki, T. Okubo, T. Tokida et al., A rice gene for microbial symbiosis, OsCCaMK, reduces CH 4 flux in a paddy field with low nitrogen input, Appl Environ Microbiol, vol.80, issue.6, pp.1995-2003, 2014.

R. Bernardo, Molecular markers and selection for complex traits in plants: learning from the last 20 years, Crop Sci, vol.48, issue.5, pp.1649-1664, 2008.

R. Bernardo and A. Charcosset, Usefulness of gene information in markerassisted recurrent selection: a simulation appraisal, Crop Sci, vol.46, issue.2, pp.614-621, 2006.

A. Bhandari, J. Bartholomé, T. V. Cao-hamadoun, N. Kumari, J. Frouin et al., Selection of trait-specific markers and multi-environment models improve genomic predictive ability in rice, PLoS ONE, vol.14, issue.5, p.208871, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02618975

P. Bhatnagar-mathur, V. Vadezm, and K. K. Sharmam, Transgenic approaches for abiotic stress tolerance in plants: retrospect and prospects, Plant Cell Rep, vol.27, pp.411-424, 2008.

D. G. Bonnett, G. J. Rebetzke, and W. Spielmeyer, Strategies for efficient implementation of molecular markers in wheat breeding, Mol Breed, vol.15, pp.75-85, 2005.

P. J. Bradbury, Z. Zhang, D. E. Kroon, T. M. Casstevens, Y. Ramdoss et al., TASSEL: software for association mapping of complex traits in diverse samples, Bioinformatics, vol.23, pp.2633-2635, 2007.

L. Chen, G. Xiong, X. Cui, M. Yan, T. Xu et al., OsGRAS19 may be a novel component involved in the brassinosteroid signaling pathway in rice, Mol Plant, vol.6, issue.3, pp.988-91, 2013.

S. Dixit, A. Singh, and A. Kumar, Rice breeding for high grain yield under drought: a strategic solution to a complex problem, Int J Agron, vol.863683, p.15, 2014.

R. L. Fernando and M. Grossman, Marker assisted selection using best linear unbiased prediction, Genet Sel Evol, vol.21, pp.467-477, 1989.
URL : https://hal.archives-ouvertes.fr/hal-00893817

R. M. Francis, Pophelper: an R package and web app to analyze and visualize population structure, Mol Ecol Resour, vol.17, issue.1, pp.27-32, 2017.

J. F. Gu, X. Y. Yin, P. C. Struik, T. J. Stomph, and H. Q. Wang, Using chromosome introgression lines to map quantitative trait loci for photosynthesis parameters in rice (Oryza sativa L.) leaves under drought and well-watered field conditions, J Exp Bot, vol.40, pp.455-469, 2012.

G. T. Hoang, L. Van-dinh, T. T. Nguyen, N. K. Ta, F. Gathignol et al., Genome-wide association study of a panel of Vietnamese rice landraces reveals new QTLs for tolerance to water deficit during the vegetative phase, Rice, vol.12, p.4, 2019.

N. K. Howes, S. M. Woods, and T. F. Townley-smith, Simulations and practical problems of applying multiple marker assisted selection and doubled haploids to wheat breeding programs, Euphytica, vol.100, pp.225-230, 1998.

X. Huang, Y. Zhao, X. Wei, C. Li, A. Wang et al., Genome-wide association study of flowering time and grain yield traits in a worldwide collection of rice germplasm, Nat Genet, vol.44, pp.32-39, 2012.

R. E. Huke and E. H. Huke, Estimation of a significance threshold for genomewide association studies, BMC Genomics, vol.20, p.618, 1997.

M. Kondo, M. Murty, and D. V. Aragones, Characteristics of root growth and water uptake from soil in upland rice and maize under water stress, Soil Sci Plant Nutr, vol.46, pp.721-732, 2000.

A. Kumar, J. Bernier, S. Verulkar, H. R. Laffite, and G. N. Atlin, 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, vol.107, issue.3, pp.221-231, 2008.

A. Kumar, S. Dixit, T. Ram, R. B. Yadaw, K. K. Mishra et al., Breeding highyielding drought-tolerant rice: genetic variations and conventional and molecular approaches, J Exp Bot, vol.65, issue.21, pp.6265-6278, 2014.

A. Kumar, N. Sandhu, S. Dixit, S. Yadav, B. Swamy et al., Marker-assisted selection strategy to pyramid two or more QTLs for quantitative trait-grain yield under drought, Rice, vol.11, p.35, 2018.

A. Kumar, S. B. Verulkar, S. Dixit, B. Chauhan, J. Bernier et al., Yield and yield-attributing traits of rice (Oryza sativa L.) under lowland drought and suitability of early vigor as a selection criterion, Field Crops Res, vol.114, issue.1, pp.99-107, 2009.

R. Lande and R. Thompson, Efficiency of marker-assisted selection in the improvement of quantitative traits, Genetics, vol.124, issue.3, pp.743-756, 1990.

M. D. Lazar, C. D. Salisbury, and W. D. Worrall, Variation in drought susceptibility among closely related wheat lines, Field Crop Res, vol.41, pp.147-53, 1995.

J. Y. Li, J. Wang, and R. S. Zeigler, The 3,000 rice genomes project: new opportunities and challenges for future rice research, vol.3, p.8, 2014.

X. Li, W. Yan, H. Agrama, L. Jia, A. Jackson et al., Unraveling the complex trait of harvest index with association mapping in rice, Oryza sativa L.). PLoS ONE, vol.7, issue.1, p.29350, 2012.

A. E. Lipka, F. Tian, Q. Wang, J. Peiffer, M. Li et al., GAPIT: genome association and prediction integrated tool, Bioinformatics, vol.28, issue.18, pp.2397-2399, 2012.

K. L. Mcnally, K. L. Childs, R. Bohnert, R. M. Davidson, K. Zhao et al., Genomewide SNP variation reveals relationships among landraces and modern varieties of rice, PNAS, vol.106, issue.30, pp.12273-12278, 2009.

K. Miyoshi, Y. Ito, A. Serizawa, and N. Kurata, OsHAP3 genes regulate chloroplast biogenesis in rice, Plant J, vol.36, issue.4, pp.532-572, 2003.

S. Mondal, J. E. Rutkoski, G. Velu, P. K. Singh, L. A. Crespo-herrera et al., Harnessing diversity in wheat to enhance grain yield, climate resilience, disease and insect pest resistance and nutrition through conventional and modern breeding approaches, MSU database, vol.7, pp.1-15, 2016.

K. Nath, R. S. Poudyal, J. S. Eom, Y. S. Park, I. S. Zulfugarov et al., Loss-of-function of OsSTN 8 suppresses the photosystem II core protein phosphorylation and interferes with the photosystem II repair mechanism in rice (Oryza sativa), Plant J, vol.76, issue.4, pp.675-86, 2013.

T. L. Nguyen and C. B. Bui, Fine mapping for drought tolerance in rice, Oryza sativa L.). Omonrice, vol.16, pp.9-15, 2008.

J. C. O'toole, Adaptation of rice to drought prone environments, Drought resistance in crops with emphasis on rice. IRRI, pp.95-213, 1982.

S. A. Ordonez, J. Silva, and J. H. Oard, Association mapping of grain quality and flowering time in elite japonica rice germplasm, J Cereal Sci, vol.51, issue.3, pp.337-380, 2010.

A. D. Palanog, B. Swamy, N. Shamsudin, S. Dixit, J. E. Hernandez et al., Grain yield QTLs with consistent-effect under reproductive-stage drought stress in rice, Field Crops Res, vol.161, pp.46-54, 2014.

S. Pandey, H. Bhandari, S. Ding, P. Prapertchob, R. Sharan et al., Coping with drought in rice farming in Asia: insights from a crosscountry comparative study, Agric Econ, vol.37, pp.213-224, 2007.

D. Pauli, G. J. Muehlbauer, K. P. Smith, B. Cooper, D. Hole et al., Association mapping of agronomic QTLs in US spring barley breeding germplasm, Plant Genome, vol.7, p.3, 2014.

A. Price and B. Courtois, Mapping QTLs associated with drought resistance in rice: progress, problems, and prospects, QTARO database, vol.29, pp.123-133, 1999.

R. Package, , 2019.

A. Raman, S. Verulkar, N. P. Mandal, M. Variar, V. Shukla et al., Drought yield index to select high yielding rice lines under different drought stress severities, Rice, vol.5, p.31, 2012.

A. Rambaut and A. Drummond, , 2016.

H. Samejima, A. G. Babiker, A. Mustafa, and Y. Sugimoto, Identification of Striga hermonthica-resistant upland rice varieties in Sudan and their resistance phenotypes, Front Plant Sci, vol.7, p.634, 2016.

N. Sandhu and A. Kumar, Bridging the rice yield gaps under drought : QTLs, genes and their use in breeding programs, Agron, vol.7, p.27, 2017.

N. Sandhu, A. Singh, S. Dixit, S. Cruz, M. T. Maturan et al., Identification and mapping of stable QTL with main and epistasis effect on rice grain yield under upland drought stress, BMC Genet, vol.15, p.63, 2014.

N. Sandhu, S. R. Subedi, V. K. Singh, P. Sinha, S. Kumar et al., Deciphering the genetic basis of root morphology, nutrient uptake, yield, and yield-related traits in rice under dry direct-seeded cultivation systems, Sci Rep, vol.9, issue.1, p.9334, 2019.

N. Sandhu, R. O. Torres, S. Cruz, M. T. Maturan, P. C. Jain et al., Traits and QTLs for development of dry direct-seeded rainfed rice varieties, J Exp Bot, vol.66, issue.1, pp.225-244, 2015.

R. Serraj, A. Kumar, K. L. Mcnally, I. Slamet-loedin, R. M. Bruskiewich et al., Improvement of drought resistance in rice, Adv Agron, vol.103, pp.41-98, 2009.

C. Sas-institute-inc, S. R. Subedi, N. Sandhu, V. K. Singh, P. Sinha et al., Genome-wide association study reveals significant genomic regions for improving yield, adaptability of rice under dry direct seeded cultivation condition, Statistical Analysis Systems, vol.20, p.471, 2002.

R. O. Torres and A. Henry, Yield stability of selected rice breeding lines and donors across conditions of mild to moderately severe drought stress, Field Crops Res, vol.220, pp.37-45, 2018.

J. N. Tripathy, J. Zhang, S. Robin, T. T. Nguyen, and H. T. Nguyen, QTLs for cellmembrane stability mapped in rice (Oryza sativa L.) under drought stress, Theor Appl Genet, vol.100, pp.1197-1202, 2000.

R. K. Varshney, A. Graner, and M. E. Sorrells, Genomics-assisted breeding for crop improvement, Trends Plant Sci, vol.10, issue.12, pp.621-630, 2005.

R. K. Varshney, R. Terauchi, and S. R. Mccouch, Harvesting the promising fruits of genomics: applying genome sequencing technologies to crop breeding, PLoS Biol, vol.12, issue.6, p.1001883, 2014.

R. Venuprasad, H. R. Lafitte, and G. N. Atlin, Response to direct selection for grain yield under drought stress in rice, Crop Sci, vol.47, pp.285-293, 2007.

S. B. Verulkar, N. P. Mandal, J. L. Dwivedi, B. N. Singh, P. K. Sinha et al., Breeding resilient and productive genotypes adapted to drought-prone rainfed ecosystem of India, Field Crops Res, vol.117, pp.197-208, 2010.

P. Vikram, B. Swamy, S. Dixit, H. U. Ahmed, S. Cruz et al., qDTY 1.1 , a major QTL for rice grain yield under reproductive-stage drought stress with a consistent effect in multiple elite genetic backgrounds, BMC Genet, vol.12, p.89, 2011.

Z. Wang, J. Cheng, Z. Chen, J. Huang, Y. Bao et al., Identification of QTL with main epistatic and QTL×environment interaction effects for salt tolerance in rice seedlings under different salinity conditions, Theor Appl Genet, vol.125, pp.807-815, 2012.

R. Wassmann, S. Jagadish, K. Sumfleth, H. Pathak, G. Howell et al., Regional vulnerability of climate change impacts on Asian rice production and scope for adaptation, Adv Agron, vol.102, pp.91-133, 2009.

T. Wei and V. Simko, , 2017.

H. Xia, W. X. Huang, J. Xiong, T. Tao, X. G. Zheng et al., Adaptive epigenetic differentiation between upland and lowland rice ecotypes revealed by methylation-sensitive amplified polymorphism, PLoS ONE, vol.11, issue.7, p.157810, 2016.

, XLSTAT, 2019.

Q. Xu, X. P. Yuan, H. Y. Yu, Y. P. Wang, S. X. Tang et al., Mapping QTLs for drought tolerance at seedling stage in rice using doubled haploid population, Rice Sci, vol.18, issue.1, pp.23-28, 2011.

Y. Xu and J. H. Crouch, Marker-assisted selection in plant breeding: from publications to practice, Crop Sci, vol.48, issue.2, pp.391-407, 2008.

Y. Xu, T. Yang, Y. Zhou, S. Yin, P. Li et al., Genome-wide association mapping of starch pasting properties in maize using single-locus and multi-locus models, Front Plant Sci, vol.9, p.1311, 2018.

D. Xue, Y. Huang, X. Zhang, K. Wei, S. Westcott et al., Identification of QTLs associated with salinity tolerance at late growth stage in barley, Euphytica, vol.169, issue.2, pp.187-196, 2009.

S. Yadav, N. Sandhu, R. R. Majumder, S. Dixit, S. Kumar et al., Epistatic interactions of major effect drought QTLs with genetic background loci determine grain yield of rice under drought stress, Sci Rep, vol.9, issue.1, p.2616, 2019.

J. Yang, B. Benyamin, B. P. Mcevoy, S. Gordon, A. K. Henders et al., Common SNPs explain a large proportion of the heritability for human height, Nat Genet, vol.42, issue.7, pp.565-69, 2010.

S. Yang, B. Vanderbeld, J. Wan, and Y. Huang, Narrowing down the targets: towards successful genetic engineering of drought tolerant crops, Mol Plant, vol.3, pp.469-90, 2010.

C. Zhang, S. S. Dong, J. Y. Xu, W. M. He, and T. L. Yang, PopLDdecay: a fast and effective tool for linkage disequilibrium decay analysis based on variant call format files, Bioinformatics, vol.35, issue.10, pp.1786-1788, 2019.

L. Zhang, X. Cui, K. Schmitt, R. Hubert, W. Navidit et al., Whole genome amplification from a single cell: implications for genetic analysis, Proc Natl Acad Sci, vol.89, issue.13, pp.5847-5851, 1992.

K. Zhao, C. W. Tung, G. C. Eizenga, M. H. Wright, M. L. Ali et al., Genomewide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa, Nat Commun, vol.2, p.467, 2011.

C. Zhu, M. Gore, E. S. Buckler, and J. Yu, Status and prospects of association mapping in plants, Plant Genome J, vol.1, issue.1, pp.5-20, 2008.

, Publisher's Note

, Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations