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Assessing the leaf shape dynamic through marker–trait association under drought stress in a rice germplasm panel

Published online by Cambridge University Press:  07 January 2022

Mayuri D. Mahalle Open the ORCID record for Mayuri D. Mahalle [Opens in a new window] ,
S. K. Chetia ,
P. C. Dey ,
R. N. Sarma ,
A. R. Baruah ,
R. C. Kaldate ,
Rahul K. Verma  and
M. K. Modi
Mayuri D. Mahalle
Affiliation:
Department of Agricultural Biotechnology, Assam Agricultural University, Jorhat, Assam 785013, India
S. K. Chetia
Affiliation:
Regional Agricultural Research Station, Assam Agricultural University, Titabor, Assam 785630, India
P. C. Dey
Affiliation:
Regional Agricultural Research Station, Assam Agricultural University, Titabor, Assam 785630, India
R. N. Sarma
Affiliation:
Department of Plant Breeding and Genetics, Assam Agricultural University, Jorhat 785013, India
A. R. Baruah
Affiliation:
Department of Agricultural Biotechnology, Assam Agricultural University, Jorhat, Assam 785013, India
R. C. Kaldate
Affiliation:
Department of Agricultural Biotechnology, Assam Agricultural University, Jorhat, Assam 785013, India
Rahul K. Verma
Affiliation:
Department of Agricultural Biotechnology, Assam Agricultural University, Jorhat, Assam 785013, India
M. K. Modi*
Affiliation:
Department of Agricultural Biotechnology, Assam Agricultural University, Jorhat, Assam 785013, India
*
Author for correspondence: M. K. Modi, E-mail: [email protected]
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Abstract

The flag leaf acts as a functional leaf in rice, Oryza sativa L., primarily supplying photosynthate to the developing grains and influencing yields to a certain extent. Drought stress damages the leaf physiology, severely affecting grain fertility. Autumn rice of northeast India is called locally as ‘ahu’ rice, and is known for its drought tolerance. Exploring diverse germplasm resources at the morphological level using an association mapping approach can aid in identifying the genomic regions influencing leaf shape dynamics. A marker–trait association (MTA) study was carried out using 95 polymorphic SSR markers and a panel of 273 ahu rice germplasm accessions in drought stress and irrigated conditions. The trials suggest that at the vegetative stage, drought stress significantly affects leaf morphology. The leaf physiology of some tolerant accessions was relatively little affected by stress and these can be considered as ideal varieties for drought conditions. The phenotypic coefficient of variance and genotypic coefficient of variance values implied moderate to high variability for the leaf traits studied. Analysis of molecular variance inferred that 11% of variation in the germplasm panel was due to differences between populations, while the remaining 89% may be attributed to a difference within subgroups formed through STRUCTURE analysis. Using the mixed linear model approach revealed 11 MTAs explaining between 4.5 and 20.0% of phenotypic variance at P > 0.001 for all the leaf traits. The study concludes that ahu rice germplasm is extremely diverse and can serve as a valuable resource for mining desirable alleles for drought tolerance.

Keywords

Ahu riceflag leafgrain yieldlandracesmarker–trait associationOryza sativa L
Type
Research Article
Information
Plant Genetic Resources , Volume 19 , Issue 6 , December 2021 , pp. 477 - 483
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press on behalf of NIAB

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References

Abebe, T, Alamerew, S and Tulu, L (2019) Traits association and path coefficient analysis of yield and related traits in rainfed lowland rice (Oryza sativa L.) genotypes in North Western Ethiopia. African Journal of Plant Science 13, 1–8.Google Scholar
Abou-Khalifa, AA, Misra, AN and Salem, KM (2008) Effect of leaf cutting on physiological traits and yield of two rice cultivars. African Journal of Plant Science 2, 147–150.Google Scholar
Al-Tahir, M (2014) Flag leaf characteristics and relationship with grain yield and grain protein percentage for three cereals. Journal of Medicinal Plants Studies 2, 1–7.Google Scholar
Ashrafuzzaman, M, Islam, MR, Ismail, MR, Shahidullah, SM and Hanafi, MM (2009) Evaluation of six aromatic rice varieties for yield and yield contributing characters. International Journal of Agriculture and Biology 11, 616–620.Google Scholar
Barik, SR, Pandit, E, Pradhan, SK, Mohanty, SP and Mohapatra, T (2019) Genetic mapping of morpho-physiological traits involved during reproductive stage drought tolerance in rice. PLoS ONE 14, e0214979.CrossRefGoogle ScholarPubMed
Basu, S, Jongerden, J and Ruivenkamp, G (2017) Development of the drought tolerant variety SahbhagiDhan: exploring the concepts commons and community building. International Journal of the Commons 11, 144–170.CrossRefGoogle Scholar
Bernier, J, Kumar, A, Ramaiah, V, Spaner, D and Atlin, G (2007) A large-effect QTL for grain yield under reproductive-stage drought stress in upland rice. Crop Science 47, 507–516.CrossRefGoogle Scholar
Cabuslay, GS, Ito, O and Alejar, AA (2002) Physiological evaluation of responses of rice (Oryza sativa L.) to water deficit. Plant Science 163, 815–827.CrossRefGoogle Scholar
Cutler, JM, Steponkus, PL, Wach, MJ and Shahan, KW (1980) Dynamic aspects and enhancement of leaf elongation in rice. Plant Physiology 66, 147–152.CrossRefGoogle ScholarPubMed
Dong, Z, Li, D, Hu, X, Liang, L, Wu, G, Zeng, S, Liu, E, Wu, Y, Wang, H, Bhanbhro, LB and Dang, X (2018) Mining of favorable marker alleles for flag leaf inclination in some rice (Oryza sativa L.) accessions by association mapping. Euphytica 214, 117.CrossRefGoogle Scholar
Farooq, M, Kobayashi, N, Ito, O, Wahid, A and Serraj, R (2010) Broader leaves result in better performance of Indica rice under drought stress. Journal of Plant Physiology 167, 1066–1075.CrossRefGoogle ScholarPubMed
Federer, HT (1956) Augmented (or hoonuiaka) designs. Hawaii Plant 55, 191–208.Google Scholar
Fujita, D, Santos, RE, Ebron, LA, Telebanco-Yanoria, MJ, Kato, H, Kobayashi, S, Uga, Y, Araki, E, Takai, T, Tsunematsu, H and Imbe, T (2009) Development of introgression lines of an Indica-type rice variety, IR64, for unique agronomic traits and detection of the responsible chromosomal regions. Field Crops Research 114, 244–254.CrossRefGoogle Scholar
Gladun, L and Karpov, EA (1993) Distribution of assimilates from the flag leaf of rice during the reproductive period of development. Russian Plant Physiology 40, 215–218.Google Scholar
Inthapan, P and Fukai, S (1988) Growth and yield of rice cultivars under sprinkler irrigation in south-eastern Queensland. 2. Comparison with maize and grain sorghum under wet and dry conditions. Australian Journal of Experimental Agriculture 28, 243–248.CrossRefGoogle Scholar
Khush, GS (1995) Breaking the yield frontier of rice. GeoJournal 35, 329–332.CrossRefGoogle Scholar
Kumar, A, Dixit, S, Ram, T, Yadaw, RB, Mishra, KK and Mandal, NP (2014) Breeding high-yielding drought-tolerant rice: genetic variations and conventional and molecular approaches. Journal of Experimental Botany 65, 6265–6278.CrossRefGoogle ScholarPubMed
Mahalle, MD, Dey, PC, Chetia, SK, Baruah, AR, Ahmed, T, Sarma, RN, Kaldate, RC, Kumar, A, Singh, SK and Modi, MK (2020) Association mapping for yield traits under drought stress in Autumn rice germplasm collection of Assam. Journal of Plant Biochemistry and Biotechnology 22, 1–1.Google Scholar
Maheswari, M, Sarkar, B, Vanaja, M, Srinivasa Rao, M, Prasad, JV, Prabhakar, M, Ravindra Chary, G, Venkateswarlu, B, Ray Choudhury, P, Yadava, DK and Bhaskar, S (2019) Climate resilient crop varieties for sustainable food production under aberrant weather conditions. ICAR-Central Research Institute for Dryland Agriculture, Hyderabad 64.Google Scholar
Misra, AN (1987) Physiological aspects of grain formation in sorghum and pearl millet. In: Production technology for sorghum and pearl millet. ICAR/Sukhadia University, Jaipur, India:1–6.Google Scholar
Mukesh, M, JhaVidyabhushan, KA, Mankesh, K and Shweta, K (2018) Correlation and path coefficient analysis in rice (Oryza sativa L.) genotypes for yield and its attributing traits. Journal of Pharmacognosy and Phytochemistry 7, 285–290.Google Scholar
Nachimuthu, VV, Muthurajan, R, Duraialaguraja, S, Sivakami, R, Pandian, BA, Ponniah, G, Gunasekaran, K, Swaminathan, M, Suji, KK and Sabariappan, R (2015) Analysis of population structure and genetic diversity in rice germplasm using SSR markers: an initiative towards association mapping of agronomic traits in Oryza sativa. Rice 8, 1–25.CrossRefGoogle ScholarPubMed
Nonami, H (1988) Plant water relations and control of cell elongation at low water potentials. Journal of Plant Research 111, 373–382.CrossRefGoogle Scholar
Oladosu, Y, Rafii, MY, Magaji, U, Abdullah, N, Miah, G, Chukwu, SC, Hussin, G, Ramli, A and Kareem, I (2018) Genotypic and phenotypic relationship among yield components in rice under tropical conditions. BioMed Research International 15, 2018.Google Scholar
Peakall, RO and Smouse, PE (2006) GenAlEx 6: genetic analysis in Excel. Population genetic software for teaching and research – an update. Molecular Ecology Notes 6, 288–295.CrossRefGoogle Scholar
Peakall, R and Smouse, PE (2012) GenAlEx SP. 6: genetic analysis in Excel. Population genetic software for teaching and research. Bioinformatics: 28:19.CrossRefGoogle Scholar
Qiao, W, Qi, L, Cheng, Z, Su, L, Li, J, Sun, Y, Ren, J, Zheng, X and Yang, Q (2016) Development and characterization of chromosome segment substitution lines derived from Oryza rufipogon in the genetic background of O. sativa spp. indica cultivar 9311. BMC Genomics 17, 1–2.CrossRefGoogle Scholar
Sahebi, M, Hanafi, MM, Rafii, MY, Mahmud, TM, Azizi, P, Osman, M, Abiri, R, Taheri, S, Kalhori, N, Shabanimofrad, M and Miah, G (2018) Improvement of drought tolerance in rice (Oryza sativa L.): genetics, genomic tools, and the WRKY gene family. BioMed Research International 2018, 3158474.CrossRefGoogle ScholarPubMed
Sahu, VK, Sunil, KN, Vishwakarma, AK, Verulkar, SB and Chandel, G (2017) QTL hotspots detected for yield contributing traits in rice (Oryza sativa L.) using composite interval mapping analysis. Biosciences Biotechnology Research Asia 14, 329–341.CrossRefGoogle Scholar
Singh, RK and Chaudhary, BD (1977) Biometrical methods in quantitative genetic analysis.Google Scholar
Stocker, O (1960) Physiological and morphological changes in plants due to water deficiency. Arid Zone Research 15, 63–104.Google Scholar
Swamy, BM, Vikram, P, Dixit, S, Ahmed, HU and Kumar, A (2011) Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus. BMC Genomics 12, 1–8.CrossRefGoogle ScholarPubMed
Verma, RK, Chetia, SK, Dey, PC, Baruah, AR and Modi, MK (2017) Mapping of QTLs for grain yield and its component traits under drought stress in elite rice variety of Assam. International Journal of Current Microbiology and Applied Sciences 6, 1443–1455.CrossRefGoogle Scholar
Verma, H, Borah, JL and Sarma, RN (2019) Variability assessment for root and drought tolerance traits and genetic diversity analysis of rice germplasm using SSR markers. Scientific Reports 9, 1–9.CrossRefGoogle ScholarPubMed
Watson, DJ (1952) The physiological basis of variation in yield. In Advances in Agronomy 4, 101–145.CrossRefGoogle Scholar
Wu, J, Qi, Y, Hu, G, Li, J, Li, Z and Zhang, H (2017) Genetic architecture of flag leaf length and width in rice (Oryza sativa L.) revealed by association mapping. Genes & Genomics 39, 341–352.CrossRefGoogle Scholar
Xuebiao, P, Yuepeng, H, Zongxiang, C and Hongxi, Z (2004). Progress in genetic improvement of rice plant morphological characters. Journal of Yangzhou University (Agricultural and Life Sciences Edition) 25, 36–40.Google Scholar
Yang, L, Wang, J, Lei, L, Wang, J, JunaidSubhani, M, Liu, H, Sun, J, Zheng, H, Zhao, H and Zou, D (2018) QTL mapping for heading date, leaf area and chlorophyll content under cold and drought stress in two related recombinant inbred line populations (Japonica rice) and meta-analysis. Plant Breeding 137, 527–545.CrossRefGoogle Scholar
Yoshida, S (1981) Fundamentals of rice crop science. International Rice Research Institute, Manila, Philippines. Los Baños, Laguna. 269 p.Google Scholar
Yuan, LP (1997) Super-high yield hybrid rice breeding. Hybrid Rice 12, 1–6.Google Scholar
Yue, B, Xue, W, Luo, L and Xing, Y (2008) Identification of quantitative trait loci for four morphologic traits under water stress in rice (Oryza sativa L.). Journal of Genetics and Genomics 35, 569–575.CrossRefGoogle Scholar
Zeng, D, Hu, J, Dong, G, Liu, J, Zeng, L, Zhang, G, Guo, L, Zhou, Y and Qian, Q (2009) Quantitative trait loci mapping of flag-leaf ligule length in rice and alignment with ZmLG1 gene. Journal of Integrative Plant Biology 51, 360–366.CrossRefGoogle ScholarPubMed
Zhang, GH, Li, SY, Wang, L, Ye, WJ, Zeng, DL, Rao, YC, Peng, YL, Hu, J, Yang, YL, Xu, J and Ren, DY (2002) LSCHL4 from japonica cultivar, which is allelic to NAL1, increases yield of indica super rice. Molecular Plant 7, 1350–1364.CrossRefGoogle Scholar
Zhang, P, Li, J, Li, X, Liu, X, Zhao, X and Lu, Y (2011) Population structure and genetic diversity in a rice core collection (Oryza sativa L.) investigated with SSR markers. PLoS ONE 6, e27565.CrossRefGoogle Scholar
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