, Volume 248, Issue 1, pp 155–169 | Cite as

Mining of favorable alleles for lodging resistance traits in rice (oryza sativa) through association mapping

  • Ognigamal Sowadan
  • Dalu Li
  • Yuanqing Zhang
  • Shangshang Zhu
  • Xiaoxiao Hu
  • Lal Bux Bhanbhro
  • Wisdom M. Edzesi
  • Xiaojing Dang
  • Delin Hong
Original Article


Main conclusion

Fourteen new quantitative trait loci (QTLs) and ten favorable alleles were identified for lodging resistance traits in a natural population of rice. Parental combinations were designed to improve lodging resistance.

Lodging is one of the most critical constraints to rice yield, and therefore, mining favorable alleles for lodging resistance traits is imperative for the advancement of cultivated rice and selection for market demand. This investigation was performed on a selected sample of 521 rice cultivars using 262 SSR markers in 2016 and 2017. Lodging resistance traits were evaluated by plant height (PH), stem length (SL), stem diameter (SD), anti-thrust per stem (AT/S), and stem index (SI), with AT/S, used as the lodging resistance index. A genome-wide association map was generated by combining phenotypic and genotypic data. Eight subpopulations were found by structure software, and the linkage disequilibrium (LD) ranged from 30 to 80 cM. Identification of 68 marker–trait associations (MTAs) linking in 64 SSR markers for five traits was done. QTL were detected, including 15 for PH, 14 for SL, 14 for SD, 7 for AT/S, and 18 for SI. A number of favorable alleles were also discovered, including 22, 24, 19, 12, and 28 alleles for PH, SL, SD, AT/S, and SI, respectively. These favorable alleles might be used to design parental combinations, and the predictable results found by relieving the favorable alleles per QTL. The accessions containing favorable alleles for lodging resistant traits mined in this study could be useful for breeding superior rice cultivars.


Oryza sativa Lodging resistance Linkage disequilibrium Association mapping Favorable allele Phenotypic and genetic diversities 



Analysis of variance


Anti-thrust per stem


Genome-wide association


Heritability in the broad sense


Linkage disequilibrium


Marker-assisted selection


Marker–trait associations


Plant height


Polymorphic information content


Proportion of phenotypic variance explained


Quantitative trait locus


Stem diameter


Stem index


Stem length


Simple sequence repeat



We thank Jianhua Ji, a technician at Nanjing Agricultural University Farm, for help with the daily management of the paddy field.


Funding support was a grant provided by National Natural Science Foundation of China (31671658), a Grant from doctoral found of Educational Ministry (B0201300662), and a Grant from the China national “863” program (2010AA101301).

Compliance with ethical standards

Consent for publication

Not applicable.

Availability of data and materials

The raw genotypic data are available in Supplementary Table 5.

Conflict of interest

The authors declare no competing financial interests.

Supplementary material

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Supplementary material 6 (XLSX 11 kb)


  1. Ashikari M, Wu J, Yano M, Sasaki T, Yoshimura A (1999) Rice gibberellin-insensitive dwarf mutant gene Dwarf 1 encodes the α-subunit of GTP-binding protein. PNAS 96:10284–10289CrossRefPubMedGoogle Scholar
  2. Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES (2007) TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23:2633–2635CrossRefPubMedGoogle Scholar
  3. Breseghello F, Sorrells ME (2006) Association mapping of kernel size and milling quality in wheat (Triticum aestivum L.) cultivars. Genetics 172:1165–1177CrossRefPubMedPubMedCentralGoogle Scholar
  4. Carter PR, Hudelson KD (1988) Influence of simulated wind lodging on corn growth and grain yield. J Prod Agric 1:295–299. CrossRefGoogle Scholar
  5. Chandler RF Jr (1969) Plant morphology and stand geometry in relation to nitrogen. Agronomy and Horticulture Department (Digital Commons), University of Nebraska–Lincoln. 196. Accessed 2 Feb 2018
  6. Chang T-T, Vergara BS (1972) Ecological and genetic information on adaptability and yielding ability in tropical rice varieties. In: Rice breeding. International Rice Research Institute, Los Baños, Philippines, pp 431–453Google Scholar
  7. Chen GH, Deng HB, Zhang GL, Tang WB, Huang H (2016) The correlation of stem characters and lodging resistance and combining ability analysis in rice. Sci Agric Sin 49:407–417. (in Chinese) CrossRefGoogle Scholar
  8. Dang XJ, Tran TTG, Dong GS, Wang H, Edzesi MW, Hong DL (2014) Genetic diversity and association mapping of seed vigor in rice (Oryza sativa L.). Planta 239:1309–1319CrossRefPubMedGoogle Scholar
  9. Dang X, Liu E, Liang Y, Liu Q, Breria CM, Hong D (2016) QTL detection and elite alleles mining for stigma traits in Oryza sativa by association mapping. Front Plant Sci 7:1188. CrossRefPubMedPubMedCentralGoogle Scholar
  10. Edzesi WM, Dang X, Liang L, Liu E, Zaid IU, Hong D (2016) Genetic diversity and elite allele mining for grain traits in rice (Oryza sativa L.) by association mapping. Front Plant Sci 7:787CrossRefPubMedPubMedCentralGoogle Scholar
  11. De Koeyer D, Tinker N, Wight C, Deyl J, Burrows V, O’Donoughue L, Lybaert A, Molnar S, Armstrong K, Fedak G (2004) A molecular linkage map with associated QTLs from a hulless × covered spring oat population. Theor Appl Genet 108:1285–1298CrossRefPubMedGoogle Scholar
  12. Easson D, White E, Pickles S (1993) The effects of weather, seed rate and cultivar on lodging and yield in winter wheat. J Agric Sci 121:145–156CrossRefGoogle Scholar
  13. Ebbs SD, Kochian LV (1998) Phytoextraction of zinc by oat (Avena sativa), barley (Hordeum vulgare), and indian mustard (Brassica juncea). Environ Sci Technol 32:802–806. CrossRefGoogle Scholar
  14. Evans JR (1983) Nitrogen and photosynthesis in the flag leaf of wheat (Triticum aestivum L.). Plant Physiol 72:297–302. CrossRefPubMedPubMedCentralGoogle Scholar
  15. Excoffier L, Laval G, Schneider S (2005) Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evol Bioinform Online 1:47–50CrossRefGoogle Scholar
  16. Falush D, Stephens M, Pritchard JK (2007) Inference of population structure using multilocus genotype data: dominant markers and null alleles. Mol Ecol Resour 7:574–578CrossRefGoogle Scholar
  17. Fan S, Brzeska J (2014) Feeding more people on an increasingly fragile planet: China’s food and nutrition security in a national and global context. J Integr Agric 13:1193–1205CrossRefGoogle Scholar
  18. FAO I (2016) WFP (2015) The state of food insecurity in the world 2015. Meeting the 2015 international hunger targets: Taking stock of uneven progress. Food and Agriculture Organization Publications, RomeGoogle Scholar
  19. Farnir F, Coppieters W, Arranz J-J, Berzi P, Cambisano N, Grisart B, Karim L, Marcq F, Moreau L, Myriam M et al (2000) Extensive genome-wide linkage disequilibrium in cattle. Genome Res 10:220–227CrossRefPubMedGoogle Scholar
  20. Fernandez L, Le Cunff L, Tello J, Lacombe T, Boursiquot JM, Fournier-Level A, Bravo G, Lalet S, Torregrosa L, This P (2014) Haplotype diversity of VvTFL1A gene and association with cluster traits in grapevine (V. vinifera). BMC Plant Biol 14:209CrossRefPubMedPubMedCentralGoogle Scholar
  21. Flint-Garcia SA, Thornsberry JM, Buckler ES IV (2003) Structure of linkage disequilibrium in plants. Annu Rev Plant Biol 54:357–374CrossRefPubMedGoogle Scholar
  22. Fujisawa Y, Kato T, Ohki S, Ishikawa A, Kitano H, Sasaki T, Asahi T, Iwasaki Y (1999) Suppression of the heterotrimeric G protein causes abnormal morphology, including dwarfism, in rice. PNAS 96:7575–7580CrossRefPubMedGoogle Scholar
  23. GRiSP (2013) Rice almanac, 4th edn. International Rice Research Institute, Los BañosGoogle Scholar
  24. Hirano K, Ordonio RL, Matsuoka M (2017) Engineering the lodging resistance mechanism of post-green revolution rice to meet future demands. Proc Jpn Acad Ser B Phys Biol Sci 93:220–233CrossRefPubMedPubMedCentralGoogle Scholar
  25. Hojyo Y (1974) Lodging and stiffness of culms in crops. Agric Technol 29:157–162Google Scholar
  26. Holland JB, Moser HS, O’donoughue LS, Lee M (1997) QTLs and epistasis associated with vernalization responses in oat. Crop Sci 37:1306–1316CrossRefGoogle Scholar
  27. Huang X, Sang T, Zhao Q, Feng Q, Zhao Y, Li C, Zhu C, Lu T, Zhang Z, Li M et al (2010) Genome-wide association studies of 14 agronomic traits in rice landraces. Nat Genet 42:961–967CrossRefPubMedGoogle Scholar
  28. Islam MS, Peng S, Visperas RM, Ereful N, Bhuiya MSU, Julfiquar A (2007) Lodging-related morphological traits of hybrid rice in a tropical irrigated ecosystem. Field Crops Res 101:240–248CrossRefGoogle Scholar
  29. Kashiwagi T, Ishimaru K (2004) Identification and functional analysis of a locus for improvement of lodging resistance in rice. Plant Physiol 134:676–683. CrossRefPubMedPubMedCentralGoogle Scholar
  30. Kashiwagi T, Sasaki H, Ishimaru K (2005) Factors responsible for decreasing sturdiness of the lower part in lodging of rice (Oryza sativa L.). Plant Prod Sci 8:166–172. CrossRefGoogle Scholar
  31. Kashiwagi T, Madoka Y, Hirotsu N, Ishimaru K (2006) Locus prl5 improves lodging resistance of rice by delaying senescence and increasing carbohydrate reaccumulation. Plant Physiol Biochem 44:152–157CrossRefPubMedGoogle Scholar
  32. Kashiwagi T, Togawa E, Hirotsu N, Ishimaru K (2008) Improvement of lodging resistance with QTLs for stem diameter in rice (Oryza sativa L.). Theor Appl Genet 117:749–757CrossRefPubMedGoogle Scholar
  33. Khush GS (1999) Green revolution: preparing for the 21st century. Genome 42:646–655CrossRefPubMedGoogle Scholar
  34. Kwak M, Kami JA, Gepts P (2009) The putative Mesoamerican domestication center of is located in the Lerma–Santiago Basin of Mexico. Crop Sci 49:554–563CrossRefGoogle Scholar
  35. Lang Y-Z, Yang X-D, Wang M-E, Zhu Q-S (2012) Effects of lodging at different filling stages on rice yield and grain quality. Rice Sci 19:315–319CrossRefGoogle Scholar
  36. Larson JC, Maranville JW (1977) Alterations of yield, test weight, and protein in lodged grain sorghum. Agron J 69:629–630. CrossRefGoogle Scholar
  37. Liu K, Muse SV (2005) PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 21:2128–2129CrossRefPubMedGoogle Scholar
  38. Liu F, Wang P, Zhang X, Li X, Yan X, Fu D, Wu G (2017) The genetic and molecular basis of crop height based on a rice model. Planta 247:1–26CrossRefPubMedGoogle Scholar
  39. Matsuda T, Kawahara H, Chonan N (1983) Histological studies on breaking resistance of lower internodes in rice culm. IV. The rules of each tissue of internode and leaf sheath in breaking resistance. Proc Crop Sci Soc Jpn 52:355–361CrossRefGoogle Scholar
  40. McCouch SR, Teytelman L, Xu Y, Lobos KB, Clare K, Walton M, Bingying FM, Maghirang R, Li Z, Xing Y, Zhang Q et al (2002) Development and mapping of 2240 new SSR markers for rice (Oryza sativa L.). DNA Res 9:199–207CrossRefPubMedGoogle Scholar
  41. Monna L, Kitazawa N, Yoshino R, Suzuki J, Masuda H, Maehara Y, Tanji M, Sato M, Nasu S, Minobe Y (2002) Positional cloning of rice semidwarfing gene, sd-1: rice “green revolution gene” encodes a mutant enzyme involved in gibberellin synthesis. DNA Res 9:11–17CrossRefPubMedGoogle Scholar
  42. Morris GP, Ramu P, Deshpande SP, Hash CT, Shah T, Upadhyaya HD, Oscar R-L, Brown PJ, Acharya CB, Mitchell SE et al (2013) Population genomic and genome-wide association studies of agroclimatic traits in sorghum. PNAS 110:453–458CrossRefPubMedGoogle Scholar
  43. Mulder EG (1954) Effect of mineral nutrition on lodging of cereals. Plant Soil 5:246–306CrossRefGoogle Scholar
  44. Murray MG, Thompson WF (1980) Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res 8:4321–4326CrossRefPubMedPubMedCentralGoogle Scholar
  45. Muthayya S, Sugimoto JD, Montgomery S, Maberly GF (2014) An overview of global rice production, supply, trade, and consumption. Ann N Y Acad Sci 1324:7–14. CrossRefPubMedGoogle Scholar
  46. Nei M, Tajima F, Tateno Y (1983) Accuracy of estimated phylogenetic trees from molecular data. J Mol Evol 19:153–170CrossRefPubMedGoogle Scholar
  47. Noor RBM, Caviness CE (1980) Influence of induced lodging on pod distribution and seed yield in soybeans. Agron J 72:904–906. CrossRefGoogle Scholar
  48. Ookawa T, Ishihara K (1992) Varietal difference of physical characteristics of the culm related to lodging resistance in paddy rice. Jpn J Crop Sci 61:419–425CrossRefGoogle Scholar
  49. Ookawa T, Hobo T, Yano M, Murata K, Ando T, Miura H, Asano K, Ochiai Y, Ikeda M, Nishitani R (2010) New approach for rice improvement using a pleiotropic QTL gene for lodging resistance and yield. Nat Commun 1:132CrossRefPubMedPubMedCentralGoogle Scholar
  50. Oraguzie NC, Wilcox PL (2007) An overview of association mapping. In: Oraguzie NC, Rikkerink EHA, Gardiner SE, De Silva HN (eds) Association mapping in plants. Springer, New York, USA, pp 1–9CrossRefGoogle Scholar
  51. Ostrander EA, Kruglyak L (2000) Unleashing the canine genome. Genome Res 10:1271–1274CrossRefPubMedGoogle Scholar
  52. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedPubMedCentralGoogle Scholar
  53. Ramya P, Chaubal A, Kulkarni K, Gupta L, Kadoo N, Dhaliwal HS, Chhuneja P, Lagu M, Gupt V (2010) QTL mapping of 1000-kernel weight, kernel length, and kernel width in bread wheat (Triticum aestivum L.). J Appl Genet 51:421–429CrossRefPubMedGoogle Scholar
  54. Rogers SO, Bendich AJ (1994) Extraction of total cellular DNA from plants, algae and fungi. In: Gelvin, SB, Schilperoort, RA (eds) Plant molecular biology manual. Springer, Dordrecht, pp 183–190CrossRefGoogle Scholar
  55. Saitou N, Nei M (1987) The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 4:406–425Google Scholar
  56. Sakata I, Sakai M, Imbe T (2003) The correlation of the resistance to root lodging with growth angle, diameter and pulling strength of crown roots in rice (Oryza sativa) seedlings. Jpn J Crop Sci (Jpn) 72:56–61CrossRefGoogle Scholar
  57. Sasaki A, Ashikari M, Ueguchi-Tanaka M, Itoh H, Nishimura A, Swapan D, Ishiyama K, Saito T, Kobayashi M, Khush GS et al (2002) Green revolution: a mutant gibberellin-synthesis gene in rice. Nature 416:701CrossRefPubMedGoogle Scholar
  58. Siripoonwiwat W, O’Donoughue LS, Wesenberg D, Hoffman DL, Barbosa-Neto JF, Sorrells ME (1996) Chromosomal regions associated with quantitative traits in oat. J Quant Trait Loci 2:830Google Scholar
  59. Spielmeyer W, Ellis MH, Chandler PM (2002) Semidwarf (sd-1), “green revolution” rice, contains a defective gibberellin 20-oxidase gene. PNAS 99:9043–9048CrossRefPubMedGoogle Scholar
  60. Tai TH, Tanksley SD (1990) A rapid and inexpensive method for isolation of total DNA from dehydrated plant tissue. Plant Mol Biol Rep 8:297–303CrossRefGoogle Scholar
  61. Tamura K, Dudley J, Nei M, Kumar S (2007) MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol Biol Evol 24:1596–1599CrossRefPubMedGoogle Scholar
  62. Temnykh S, Park WD, Ayres N, Cartinhour S, Hauck N, Lipovich L, Cho YG, Ishii T, McCouch SR (2000) Mapping and genome organization of microsatellite sequences in rice (Oryza sativa L.). Theor Appl Genet 100:697–712CrossRefGoogle Scholar
  63. Temnykh S, DeClerck G, Lukashova A, Lipovich L, Cartinhour S, McCouch S (2001) Computational and experimental analysis of microsatellites in rice (Oryza sativa L.): frequency, length variation, transposon associations, and genetic marker potential. Genome Res 11:1441–1452CrossRefPubMedPubMedCentralGoogle Scholar
  64. Terashima K, Akita S, Sakai N (1992) Eco-physiological characteristics related with lodging tolerance of rice in direct sowing cultivation I. Comparison of the root lodging tolerance among cultivars by the measurement of pushing resistance. Jpn J Crop Sci 61:380–387CrossRefGoogle Scholar
  65. Varshney RK, Graner A, Sorrells ME (2005) Genic microsatellite markers in plants: features and applications. Trends Biotechnol 23:48–55CrossRefPubMedGoogle Scholar
  66. Weber CR, Fehr WR (1966) Seed yield losses from lodging and combine harvesting in soybeans. Agron J 58:287–289. CrossRefGoogle Scholar
  67. Wooten D, Livingston D, Lyerly H, Holland J, Jellen E, Marshall D, Murphy JP (2009) Quantitative trait loci and epistasis for oat winter-hardiness component traits. Crop Sci 49:1989–1998CrossRefGoogle Scholar
  68. Yu J, Buckler ES (2006) Genetic association mapping and genome organization of maize. Curr Opin Biotechnol 17:155–160CrossRefPubMedGoogle Scholar
  69. Yu J, Holland JB, McMullen MD, Buckler ES (2008) Genetic design and statistical power of nested association mapping in maize. Genetics 178:539–551CrossRefPubMedPubMedCentralGoogle Scholar
  70. Zanke CD, Ling J, Plieske J, Kollers S, Ebmeyer E, Korzun V, Argillier O, Stiewe G, Hinze M, Neumann K (2014) Whole genome association mapping of plant height in winter wheat (Triticum aestivum L.). PLoS One 9:e113287CrossRefPubMedPubMedCentralGoogle Scholar
  71. Zhang Z, Ersoz E, Lai C-Q, Todhunter RJ, Tiwari HK, Gore MA, Bradbury PJ, Yu J, Arnett DK, Ordovas JM, Buckler ES (2010) Mixed linear model approach adapted for genome-wide association studies. Nat Genet 42:355–360CrossRefPubMedPubMedCentralGoogle Scholar
  72. Zhu C, Gore M, Buckler ES, Yu J (2008) Status and prospects of association mapping in plants. Plant Genome 1:5–20CrossRefGoogle Scholar
  73. Zhu G, Li G, Wang D, Yuan S, Wang F (2016) Changes in the lodging-related traits along with rice genetic improvement in China. PLoS One 11:e0160104CrossRefPubMedPubMedCentralGoogle Scholar
  74. Zuber U, Winzeler H, Messmer M, Keller M, Keller B, Schmid J, Stamp P (1999) Morphological traits associated with lodging resistance of spring wheat (Triticum aestivum L.). J Agron Crop Sci 182:17–24CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Ognigamal Sowadan
    • 1
  • Dalu Li
    • 1
  • Yuanqing Zhang
    • 1
  • Shangshang Zhu
    • 1
  • Xiaoxiao Hu
    • 1
  • Lal Bux Bhanbhro
    • 1
  • Wisdom M. Edzesi
    • 1
  • Xiaojing Dang
    • 1
  • Delin Hong
    • 1
  1. 1.State Key Laboratory of Crop Genetics and Germplasm EnhancementNanjing Agricultural UniversityNanjingChina

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