Rajesh Yogi

Linkage planning of qtl for agronomic and root qualities utilizing ib370 × mas25 (oryza sativa l.)‑f2 population developed under water restricted conditions

• Authors Details :  
• Rajesh Yogi Naveen Kumar Ravinder Kumar Mukesh Kumar

Journal title : Acta Physiologiae Plantarum

Publisher : Springer Science and Business Media LLC

Online ISSN : 1861-1664

Journal volume : 45

Journal issue : 5

415 Views Original Article

Abstract In the existing investigation, experiments were carried out to assess the F2 population’s resultant of crosses between improved Basmati 370 and MAS25 for various agronomical and root traits cultivated under aerobic water conditions. Large variations for grain yield, root length, root dry biomass, root thickness and length/breadth ratio of grain have been displayed in segregating F2 populations. A close examination of phenotypic correlation exhibited that in the F2 population, root length was certainly matched up (r = 0.496) with root thickness. A DNA fingerprinting catalog for the currently studied F2 generation was arranged using 61 polymorphic SSR markers. Composite Interval Mapping (CIM) inspection with WinQTL cartographer version 2.5 disclosed 13 putative QTL (Quantitative Trait Loci), out of which 6 QTL were for root characters 7 QTL for agronomical characters situated on 1, 2, 3, 8 and 10 chromosomes. The QTL documented in the above-said generation, some promising F2 plants were also scrutinized and found in the homozygous or heterozygous state with high repetitions.

Article DOI & Crossmark Data

DOI : https://doi.org/10.1007/s11738-023-03547-2

Article Subject Details

• Biochemistry
• Biological Sciences
• Biotechnology

Article Keywords Details

• Aerobic rice · Linkage mapping · QTL · SSR markers

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Article References

• (1). APEDA (2020) Agricultural & processed food products export development authority, Government of India, New Delhi. https://apeda.gov.in/apedawebsite/six_head_product/cereal.htm
• (2). Baisakh N, Yabes J, Gutierrez A, Mangu V, Ma P, Famoso A, Pereira A (2020) Genetic mapping identifies consistent quantitative trait loci for yield traits of rice under greenhouse drought conditions. Genes 11:62. https://doi.org/10.3390/genes11010062
• (3). Bradbury LMT, Henry RJ, Jin Q, Reinke F, Waters DLE (2005) A perfect marker for fragrance genotyping in rice. Mol Breed 16:279–283. https://doi.org/10.1007/s11032-005-0776-y
• (4). Catolos M, Sandhu N, Dixit S, Shamsudin NAA, Kumar A et al (2017) Genetic loci governing grain yield and root development under variable rice cultivation conditions. Front Plant Sci 8:1763. https://doi.org/10.3389/fpls.2017.01763
• (5). Champoux MC, Wang G, Sarkarung S, Mackill DJ, O’Toole JC, Huang N, McCouch SR (1995) Locating genes associated root morphology and drought avoidance in rice via linkage to molecular markers. Theor Appl Genet 90:969–981. https://doi.org/10.1007/BF00222910
• (6). Connor R (2015) The United Nations world water development report 2015: water for a sustainable world, vol 1. UNESCO Publishing, Paris
• (7). Corales M, Nguyen NTA, Abiko T, Mochizuki T (2020) Mapping quantitative trait loci for water uptake of rice under aerobic conditions. Plant Prod Sci 23(4):436–451. https://doi.org/10.1080/1343943X.2020.1766361
• (8). Dhawan G, Kumar A, Dwivedi P, Krishnan SG et al (2021) Introgression of qDTY1.1 governing reproductive stage drought tolerance into an elite basmati rice variety “Pusa Basmati 1” through marker assisted backcross breeding. Agronomy 11:202. https://doi.org/10.3390/agronomy11020202
• (9). Dixit S, Swamy BPM, Vikram P, Bernier J, Sta Cruz MT, Kumar A (2012) Increased drought tolerance and wider adaptability of qDTY12.1 conferred by its interaction with qDTY2.3 and qDTY3.2. Mol Breed 30:1767–1779. https://doi.org/10.1007/s11032-012-9760-5
• (10). Dixit S, Singh A, Cruz MTS, Maturan PT, Amante M, Kumar A (2014) Multiple major QTL lead to stable yield performance of rice cultivars across varying drought intensities. BMC Genet 15:16. https://doi.org/10.1186/1471-2156-15-16
• (11). Jain S, Jain RK, McCouch SR (2004) Genetic analysis of Indian aromatic and quality rice (Oryza sativa L.) germplasm using panels of fluorescently-labeled microsatellite markers. Theor Appl Genet 109:965–977. https://doi.org/10.1007/s00122-004-1700-2
• (12). Kharb A, Sandhu N, Jain S, Jain R (2015) Linkage mapping of quantitative trait loci for traits promoting aerobic adaptation on chromosome 8 in indica rice (Oryza sativa L.). Rice Genom Genet 6:1–5. https://doi.org/10.5376/rgg.2015.06.0006
• (13). Khush GS, Dela CN (2002) Developing Basmati rices with high yield potential. In: Duffy R (ed) Speciality rices of the world: breeding, production and marketing. Science Pub, Inc, Enfield, pp 15–18
• (14). Li J, Han Y, Liu L, Chen Y, Du Y, Zhang J, Sun H, Zhao Q (2015) qRT9, a quantitative trait locus controlling root thickness and root length in upland rice. J Exp Bot 66:2723–2732. https://doi.org/10.1093/jxb/erv076
• (15). Lin MH, Lin CW, Chen JC, Lin YC, Cheng SY, Ku HM et al (2007) Tagging rice drought-related QTL with SSR DNA markers. Crop Environ Bioinform 4:65–76
• (16). Liu L, Mu P, Li X, Qu Y, Wang Y, Li Z (2008) Localization of QTL for basal root thickness in japonica rice and effect of marker-assisted selection for a major QTL. Euphytica 164:729–737
• (17). Monaco F, Sali G, Ben Hassen M, Facchi A, Romani M, Valè G (2016) Water management options for rice cultivation in a temperate area: a multi-objective model to explore economic and water saving results. Water 8:336–355. https://doi.org/10.3390/w8080336
• (18). Nagaraju J, Kathirvel M, Rameshkumar R, Siddiq EA, Hasnain SE (2002) Genetic analysis of traditional and evolved Basmati and non-Basmati rice varieties by using fluorescence-based ISSR-PCR and SSR markers. Proc Natl Acad Sci USA 99:5836–5841
• (19). Prasad GSV, Padmavathi G, Suneetha K, Madhav MS, Muralidharan K (2020) Assessment of diversity of Indian aromatic rice germplasm collections for morphological, agronomical, quality traits and molecular characters to identify a core set for crop improvement. CABI Agric Biosci 1:13. https://doi.org/10.1186/s43170-020-00013-8
• (20). Roy S, Banerjee A, Mawkhlieng B, Misra AK, Pattanayak A, Harish GD, Singh SK, Ngachan SV, Bansal KC (2015) Genetic diversity and population structure in aromatic and quality rice (Oryza sativa L.) landraces from north-eastern India. PLoS ONE 10(6):e0129607. https://doi.org/10.1371/journal.pone.0129607
• (21). Saghai-Maroof MA, Soliman KM, Jorgensen RA, Allard RW (1984) Ribosomal spacer length polymorphism in Barley: Mendelian inheritance, chromosomal location and population dynamics. PNAS 81:8014–8019
• (22). Sandhu N, Jain S, Kumar A, Mehla BS, Jain RK (2013) Genetic variation, linkage mapping of QTL and correlation studies for yield, root, and agronomic traits for aerobic adaptation. BMC Genet 14:104–120. https://doi.org/10.1186/1471-2156-14-104
• (23). Sandhu N, Dixit S, Swamy BPM, Vikram P, Venkateshwarlu C, Catolos M et al (2018) Positive interactions of major-effect QTLs with genetic background that enhances rice yield under drought. Sci Rep 8:1626. https://doi.org/10.1038/s41598-018-20116-7
• (24). Shamsudin NA, Swamy BM, Ratnam W, Cruz MTS, Raman A, Kumar A (2016) Marker assisted pyramiding of drought yield QTLs into a popular Malaysian rice cultivar, MR219. BMC Genet 17:30. https://doi.org/10.1186/s12863-016-0334-0
• (25). Vikram P, Swamy BPM, Dixit S, Ahmed HU, Sta Cruz MT, Singh AK, Kumar A (2011) 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 12:89–104. https://doi.org/10.1186/1471-2156-12-89
• (26). Vinarao R, Proud C, Zhang X, Snell P, Fukai S, Mitchell J (2021) Stable and novel quantitative trait loci (QTL) confer narrow root cone angle in an aerobic rice (Oryza sativa L.) production system. Rice 14:28. https://doi.org/10.1186/s12284-021-00471-2
• (27). Wakte K, Zanan R, Hinge V, Khandagale K, Nadaf A, Henry R (2017) Thirty-three years of 2-acetyl-1-pyrroline, a principal basmati aroma compound in scented rice (Oryza sativa L.): a status review. J Sci Food Agric 97(2):384–395. https://doi.org/10.1002/jsfa.7875
• (28). Wang D, Shi J, Carlson SR, Cregan PB, Ward RW, Diers BW (2003) A low cost, high throughput polyacrylamide gel electrophoresis system for genotyping with microsatellite DNA markers. Crop Sci 43:1828–1832. https://doi.org/10.2135/cropsci2003.1828
• (29). WWAP (2016) The United Nations world water development report (2016): water and jobs. United Nations World Water Assessment Programme. UNESCO, Paris
• (30). Xu P, Yang J, Ma Z, Yu D, Zhau J, Tao D, Li Z (2020) Identification and validation of aerobic adaptation QTLs in upland rice. Life 10:65. https://doi.org/10.3390/life10050065
• (31). Yogi R, Kumar N, Kumar R, Jain RK (2020) Genetic diversity analysis among important rice (Oryza sativa L.) genotypes using SSR markers. Adv Bioresour 11(2):68–74. https://doi.org/10.15515/abr.0976-4585.11.2.6874
• (32). Yogi R, Naveen Kumar N, Meena RK, Jain RK (2021) Phenotyping, microsatellite marker analysis and linkage mapping of QTL for agronomic and root traits using IB370 × MAS-ARB25 F2 rice (Oryza sativa L.) population grown under aerobic conditions. Indian J Biotechnol 20:91–100
• (33). Zhao Y, Zhang H, Xu J, Jiang C, Yin Z, Xiong H, Xie J, Wang X, Zhu X, Li Y, Zhao W, Rashid R, Li J, Wang W, Fu B, Ye G, Guo Y, Hu Z, Li Z (2018) Loci and natural alleles underlying robust roots and adaptive domestication of upland ecotype rice in aerobic conditions. Genet 14(8):e1007521. https://doi.org/10.1371/journal.pgen.1007521
• (34). Zhu C, Kobayashi K, Loladze I, Zhu J, Jiang Q, Xu X, Liu G, Seneweera S, Ebi KL, Drewnowski A, Fukagawa NK, Ziska LH (2018) Carbon dioxide (CO2) levels this century will alter the protein, micronutrients, and vitamin content of rice grains with potential health consequences for the poorest rice-dependent countries. Sci Adv 4(5):eaaq1012. https://doi.org/10.1126/sciadv.aaq1012