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Genome-Wide Consistent Molecular Markers Associated with Phenology, Plant Production and Root Traits in Diverse Rice (Oryza sativa L.) Accessions under Drought in Rainfed Target Populations of the Environment


Affiliations
1 Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641 003, India
2 Agricultural Research Station, Tamil Nadu Agricultural University, Paramakudi 623 707, India
 

Drought is the most predominant constraint to rainfed rice production. Identifying molecular markers associated with drought resistance traits and deploying them in marker-assisted breeding will hasten the development of drought-resilient cultivars. A total of 49 diverse rice accessions, including traditional landraces, were evaluated for plant production and ischolar_main traits under natural drought stress in rainfed target populations of environment (TPE) in six successive field trials from 2010 to 2015. Significant variation for phenology, plant production and ischolar_main traits under drought was noticed among the accessions. Genotyping of the rice accessions using 599 polymorphic simple sequence repeat (SSR) markers showed considerable variation among them. STRUCTURE analysis grouped the 49 accessions into three subpopulations. Similarly, three clusters were observed in Neighbor joining tree created using Nei’s genetic distance. The subpopulation POP1 consisted mostly of landraces, while subpopulation POP3 consisted of advanced breeding lines and POP2 accessions from all groups. Genome-wide association mapping detected 61 markers consistently associated in two or more trials with phenology, plant production and ischolar_main traits under drought in TPE. The markers PSM52 (Chr 3), RM6909 (Chr 4), RM242 (Chr9) and RM444 (Chr 9) were consistently associated with grain yield and ischolar_main traits under drought. The markers PSM127 (Chr 3) and PSM133 (Chr 4) were consistently associated with yield, plant height and spikelet fertility. These markers with pleiotropic and consistent associations with yield and secondary traits under drought in TPE may be robust candidates for marker-assisted breeding for drought resistance in rice.

Keywords

Association Mapping, Drought Resistance, Molecular Markers, Rice.
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  • Hadiarto, T. and Tran, L. P., Progress studies of drought-responsive genes in rice. Plant Cell Rep., 2011, 30, 297–310.

  • Global Rice Science Partnership, Rice almanac. International Rice Research Institute, Los Banos, Philippines, 2013, 4th edn.

  • Farooq, M., Kobayashi, N., Wahid, A., Ito, O. and Basra, S. M. A., Strategies to produce more rice with less water. Adv. Agron., 2009, 101, 351–387.

  • Pandey, S. et al., Coping with drought in rice farming in Asia: insights from a cross-country comparative study. Agric. Econ., 2007, 37, 213–224.

  • Venuprasad, R. et al., Identification and characterization of large-effect quantitative trait loci (QTL) for grain yield under lowland drought stress in rice using bulk-segregant analysis. Theor. Appl. Genet., 2009, 120, 177–190.

  • Bengough, A. G., McKenzie, B. M., Hallett, P. D. and Valentine, T. A., Root elongation, water stress, and mechanical impedance: a review of limiting stresses and beneficial ischolar_main tip traits. J. Exp. Bot., 2011, 62, 59–68.

  • 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.

  • Henry, A., Gowda, V. R. P., Torres, R. O., McNally, K. L. and Serraj, R., Variation in ischolar_main system architecture and drought response in rice (Oryza sativa): phenotyping of the OryzaSNP panel in rainfed lowland fields. Field Crops Res., 2011, 120, 205–214.

  • Lafitte, H. R., Champoux, M. C., McLaren, G. and O’Toole, J. C., Rice morphological traits are related to isozyme group and adaptation. Field Crops Res., 2001, 71, 57–70.

  • Pennisi, E., Getting to the ischolar_main of drought responses. Science, 2008, 320(5873), 173–173.

  • Bernier, J. et al., Characterization of the effect of a QTL for drought resistance in rice, qtl12.1, over a range of environments in the Philippines and eastern India. Euphytica, 2008, 166, 207–217.

  • Zhao, K. et al., Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa. Nature Commun., 2011, 2, 467.

  • Garris, A. J., McCouch, S. R. and Kresovich, S., Population structure and its effects on haplotype diversity and linkage disequilibrium surrounding the xa5 locus of rice (Oryza sativa L). Genetics, 2003, 165, 759–769.

  • Yan, W. G., Li, Y., Hesham, A., Luo, D., Gao, F., Lu, X. and Ren, G., Association mapping of stigma and spikelet characteristics in rice (Oryza sativa L.). Mol. Breed., 2009, 24, 277–292.

  • Ordonez, S. A., Silva, J. and Oard, J. H., Association mapping of grain quality and flowering time in elite japonica rice germplasm. J. Cereal Sci., 2010, 51, 337–343.

  • Borba, C. et al., Association mapping for yield and grain quality traits in rice (Oryza sativa L.). Genet. Mol. Biol., 2010, 33, 515–524.

  • Huang, X. et al., Genome-wide association studies of 14 agronomic traits in rice landraces. Nature Genet., 2010, 42, 961–967.

  • Ram, S. G., Thiruvengadam, V. and Vinod, K. K., Genetic diversity among cultivars, landraces and wild relatives of rice as revealed by microsatellite markers. J. Appl. Genet., 2007, 48, 337–345.

  • Hanamaratti, N. G., Prashanthi, S. K., Salimath, P. M., Hanchinal, R. R., Mohankumar, H. D., Parameshwarappa, K. G. and Raikar, S. D., Traditional land races of rice in Karnataka: reservoirs of valuable traits. Curr. Sci., 2008, 94, 242–247.

  • Lisa, L. A., Elias, S. M., Rahman, M. S., Shahid, S., Iwasaki, T. and Hasan, A. K. M. M., Physiology and gene expression of the rice landrace under salt stress. Funct. Plant Biol., 2011, 38, 282–292.

  • McNally, K. L. et al., Genome-wide SNP variation reveals relationships among landraces and modern varieties of rice. Proc. Natl. Acad. Sci. USA, 2009, 106, 12273–12278.

  • IRRI, International network for genetic evaluation of rice: standard evaluation system for rice. International Rice Research Institute, Los Banos, Philippines, 1996.

  • Champoux, M. C., Wang, G., Sarkarang, S., Mackill, D. J., O’Toole, J. C., Huang, N. and McCouch, S. R., Locating genes associated with ischolar_main morphology and drought avoidance in rice via linkage to molecular markers. Theor. Appl. Genet., 1995, 90, 961–981.

  • 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.

  • Sambrook, J. and Russell, D. W., The Condensed Protocols from Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Laboratory Press, New York, 2006.

  • http://www.gramene.org/markers/

  • Liu, K. and Muse, S. V., PowerMarker: integrated analysis environment for genetic marker data. Bioinformatics, 2005, 21, 2128–2129; http://statgen.ncsu.edu/powermarker/

  • Nei, M, Tajima, F. A. and Tateno, Y., Accuracy of estimated phylogenetic trees from molecular data. J. Mol. Evol., 1983, 19, 153–170.

  • Tamura, K., Dudley, J., Nei, M. and Kumar, S., MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol. Biol. Evol., 2007, 24, 1596–1599; http://www.megasoftware.net/.

  • Pritchard, J. K. and Wen, W., Documentation for STRUCTURE Software, The University of Chicago Press, Chicago, USA, 2004; http://pritch.bsd.uchicago.edu/ software.html

  • Falush, D., Stephens, M. and Pritchard, J. K., Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics, 2003, 164, 1567–1587.

  • Falush, D., Stephens, M. and Pritchard, J. K., Inference of population structure using multilocus genotype data: dominant markers and null alleles. Mol. Ecol. Notes, 2007, 7, 574–578.

  • Hubisz, M. J., Falush, D., Stephens, M. and Pritchard, J. K., Inferring weak population structure with the assistance of sample group information. Mol. Ecol. Resour., 2009, 9, 1322–1332.

  • Bradbury, P. J., Zhang, Z., Kroon, D. E., Casstevens, T. M., Ramdoss, Y. and Buckler, E. S., TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics, 2007, 23, 2633–2635.

  • Zhang, Z. et al., Mixed linear model approach adapted for genome-wide association studies. Nature Genet., 2010, 42, 355–360; doi:http://www.nature.com/ng/journal/v42/n4/suppinfo/ng.546_S1.html.

  • Lu, Q. et al., Genetic variation and association mapping for 12 agronomic traits in indica rice. BMC Genomics, 2015, 16, 1067; doi:10.1186/s12864-015-2245-2.

  • Wade, L. J. et al., Environmental response and genomic regions correlated with rice ischolar_main growth and yield under drought in the OryzaSNP panel across multiple study systems. PLoS ONE, 2015, 10(4): e0124127.

  • Muthukumar, C., Subathra, T., Aiswarya, J., Gayathri, V. and Babu, R. C., Comparative genome-wide association studies for plant production traits under drought in diverse rice (Oryza sativa L) lines using SNP and SSR markers. Curr. Sci., 2015, 109, 139–147.

  • Wassmann, R. et al., Climate change affecting rice production: the physiological and agronomic basis for possible adaptation strategies. Adv. Agron., 2009, 101, 59–122.

  • Warburton, M. L. et al., Genetic diversity in CIMMYT nontemperate maize germplasm: landraces, open pollinated varieties, and inbred lines. Crop Sci., 2008. 48, 617–624; doi:10.2135/cropsci2007.02.0103.

  • Biji, K. R., Jeyaprakash, P., Ganesh, S. K., Senthil, A. and Babu, R. C., Quantitative trait loci linked to plant production traits in rice under drought stress in a target environment. Sci. Asia, 2008, 34, 265–272.

  • Gomez, M. S. et al., Mapping QTLs linked to physio-morphological and plant production traits under drought stress in rice (Oryza sativa L.) in the target environment. Am. J. Biochem. Biotechnol., 2006, 2(4), 161–169.

  • Gomez, M. S. et al., Molecular mapping and location of QTLs for drought-resistance traits in indica rice (Oryza sativa L.) lines adapted to target environments. Acta Physiol. Plant., 2010, 32, 355–364.

  • 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.

  • Sarvestani, Z. T., Pirdashti, H., Sanavy, S. A. and Balouchi, H., Study of water stress effects in different growth stages on yield and yield components of different rice (Oryza sativa L.) cultivars. Pak. J. Biol. Sci., 2008, 11, 1303–1309.

  • 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(1), 42–52.

  • Gowda, V. R. P., Henry, A., Yamauchi, A., Shashidhar, H. E. and Serraj, R., Root biology and genetic improvement for drought avoidance in rice. Field Crops Res., 2011, 122, 1–13.

  • 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.

  • Courtois, B., Shen, L., Petalcorin, W., Carandang, S., Mauleon, R. and Li, Z., Locating QTLs controlling constitutive ischolar_main traits in the rice population IAC 165× Co39. Euphytica, 2003, 134(3), 335–345.

  • Kamoshita, A., Wade, J., Ali, L., Pathan, S., Zhang, J., Sarkarung, S. and Nguyen, T., Mapping QTLs for ischolar_main morphology of a rice population adapted to rainfed lowland conditions. Theor. Appl. Genet., 2002, 104, 880–893.

  • Henry, A., Cal, A. J., Batoto, T. C., Torres, R. O. and Serraj, R., Root attributes affecting water uptake of rice (Oryza sativa) under drought. J. Exp. Bot., 2012, 63(13), 4751–4763.

  • Cho, Y. G. et al., Diversity of microsatellites derived from genomic libraries and GenBank sequences in rice (Oryza sativa L.). Theor. Appl. Genet., 2000, 100(5), 713–722.

  • Swamy, B. M., Shamsudin, N. A. A., Rahman, S. N. A., Mauleon, R., Ratnam, W., Cruz, M. T. S. and Kumar, A., Association mapping of yield and yield-related traits under reproductive stage drought stress in rice (Oryza sativa L.). Rice, 2017, 10 (1), 21; doi:10.1186/s12284-017-0161-6.

  • Jain, S., Jain, R. K. and McCouch, S. R., Genetic analysis of Indian aromatic and quality rice (Oryza sativa L.) germplasm using panels of fluorescently-labeled microsatellite markers. Theor. Appl. Genet., 2004, 109(5), 965–977.

  • Jin, L., Lu, Y., Xiao, P., Sun, M., Corke, H. and Bao, J., Genetic diversity and population structure of a diverse set of rice germplasm for association mapping. Theor. Appl. Genet., 2010, 121, 475–487.

  • Agrama, H. A., Eizenga, G. C. and Yan, W., Association mapping of yield and its components in rice cultivars. Mol. Breed., 2007, 19, 341–356; doi:10.1007/s11032-006-9066-6.

  • Zhou, J., You, A., Ma, Z., Zhu, L. and He, G., Association analysis of important agronomic traits in japonica rice germplasm. Afr. J. Biotechnol., 2012, 11, 2957–2970; http://dx.doi.org/10.5897/AJB11.1912.

  • Bailey-Serres, J., Fukao, T., Ronald, P., Ismail, A., Heuer, A. and Mackill, D., Submergence tolerant rice: SUB1’s journey from landrace to modern cultivar. Rice, 2010, 3(2), 138–147.

  • Thomson, M. J. et al., Characterizing the Saltol quantitative trait locus for salinity tolerance in rice. Rice, 2010, 3, 148–160.

  • Ghimire, K. H. et al., Identification and mapping of a QTL (qDTY1.1) with a consistent effect on grain yield under drought. Field Crops Res., 2012, 131, 88–96.

  • Kamoshita, A., Babu, R. C., Boopathi, N. M. and Fukai, S., Phenotypic and genotypic analysis of drought-resistance traits for development of rice cultivars adapted to rainfed environments. Field Crops Res., 2008, 109, 1–23.

  • Courtois, B. et al., Rice ischolar_main genetic architecture: meta-analysis from a drought QTL database. Rice, 2009, 2, 115–128.

  • Price, A. H., Steele, K. A., Moore, B. J. and Jones, R. G. W., Upland rice grown in soil-filled chambers and exposed to contrasting water-deficit regimes: II. Mapping quantitative trait loci for ischolar_main morphology and distribution. Field Crops Res., 2002, 76, 25–43.

  • Zhang, J. et al., Locating genomic regions associated with components of drought resistance in rice: comparative mapping within and across species. Theor. Appl. Genet., 2001, 103, 19–29; doi:10.1007/s001220000534.

  • Steele, K. A., Price, A. H., Shashidhar, H. E. and Witcombe, J. R., Marker-assisted selection to introgress rice QTLs controlling ischolar_main traits into an Indian upland rice variety. Theor. Appl. Genet., 2006, 112, 208–221.

  • Suji, K. K. et al., Evaluation of rice (Oryza sativa L.) near iso-genic lines with ischolar_main QTLs for plant production and ischolar_main traits in rainfed target populations of environment. Field Crops Res., 2011, 137, 89–96.

  • This, D. et al., Genetic analysis of water use efficiency in rice (Oryza sativa L.) at the leaf level. Rice, 2010, 3, 72–86.

  • Sandhu, N., Singh, A., Dixit, S., Sta Cruz, M. T., Maturan, P. C., Jain, R. K. and Kumar, A., Identification and mapping of stable QTL with main and epistasis effect on rice grain yield under upland drought stress. BMC Genet., 2014, 15, 63.

  • Vikram, P., Swamy, B. M., Dixit, S., Ahmed, H. U., Teresa Sta Cruz, M., 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, 1–15.

  • Swamy, B. M., Vikram, P., Dixit, S., Ahmed, H. and Kumar, A., Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus. BMC Genomics, 2011, 12, 1–18.


Abstract Views: 408

PDF Views: 128




  • Genome-Wide Consistent Molecular Markers Associated with Phenology, Plant Production and Root Traits in Diverse Rice (Oryza sativa L.) Accessions under Drought in Rainfed Target Populations of the Environment

Abstract Views: 408  |  PDF Views: 128

Authors

Vivek Deshmukh
Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641 003, India
Sumeet Prabakar Mankar
Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641 003, India
C. Muthukumar
Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641 003, India
P. Divahar
Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641 003, India
A. Bharathi
Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641 003, India
Helen Baby Thomas
Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641 003, India
Ashish Rajurkar
Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641 003, India
Reena Sellamuthu
Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641 003, India
R. Poornima
Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641 003, India
S. Senthivel
Agricultural Research Station, Tamil Nadu Agricultural University, Paramakudi 623 707, India
R. Chandra Babu
Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641 003, India

Abstract


Drought is the most predominant constraint to rainfed rice production. Identifying molecular markers associated with drought resistance traits and deploying them in marker-assisted breeding will hasten the development of drought-resilient cultivars. A total of 49 diverse rice accessions, including traditional landraces, were evaluated for plant production and ischolar_main traits under natural drought stress in rainfed target populations of environment (TPE) in six successive field trials from 2010 to 2015. Significant variation for phenology, plant production and ischolar_main traits under drought was noticed among the accessions. Genotyping of the rice accessions using 599 polymorphic simple sequence repeat (SSR) markers showed considerable variation among them. STRUCTURE analysis grouped the 49 accessions into three subpopulations. Similarly, three clusters were observed in Neighbor joining tree created using Nei’s genetic distance. The subpopulation POP1 consisted mostly of landraces, while subpopulation POP3 consisted of advanced breeding lines and POP2 accessions from all groups. Genome-wide association mapping detected 61 markers consistently associated in two or more trials with phenology, plant production and ischolar_main traits under drought in TPE. The markers PSM52 (Chr 3), RM6909 (Chr 4), RM242 (Chr9) and RM444 (Chr 9) were consistently associated with grain yield and ischolar_main traits under drought. The markers PSM127 (Chr 3) and PSM133 (Chr 4) were consistently associated with yield, plant height and spikelet fertility. These markers with pleiotropic and consistent associations with yield and secondary traits under drought in TPE may be robust candidates for marker-assisted breeding for drought resistance in rice.

Keywords


Association Mapping, Drought Resistance, Molecular Markers, Rice.

References





DOI: https://doi.org/10.18520/cs%2Fv114%2Fi02%2F329-340