Skip to main content
Log in

Association of molecular markers with physio-biochemical traits related to seed vigour in rice

  • Research Article
  • Published:
Physiology and Molecular Biology of Plants Aims and scope Submit manuscript

Abstract

Eighteen physio-biochemical traits influencing seed vigour were studied for their association with molecular markers using a mini core set constituted from 120 germplasm lines. High genetic variation was detected in the parameters namely chlrophyll a, Chlrophyll b, total chlorophyll, carotenoids, total anthocyanin content, gamma-oryzanols, total phenolics content, superoxide dismutase, catalase, guaicol peroxidase, total soluble sugar, total protein, seed vigour index -I and seed vigour index -II. Strong positive correlation of seed vigour index II was observed with amylose content, total anthocyanin content, catalase, total phenolic content and total flavonoid content while a negative association was observed for gamma-oryzanol content. High gene diversity (0.7169) and informative markers value (0.6789) were estimated from the investigation. Three genetic structure groups were observed in the panel population and genotypes were grouped in the subpopulations based on the seed vigour trait. Differences in the fixation indices of the three sub populations indicated existence of linkage disequilibrium in the studied panel population. Association of the traits namely total flavonoids, superoxide dismutase, catalase, chlorophyll a, Chlorophyll b, total chlorophyll, carotenoids, starch, amylose, total anthocyanin, gamma-oryzanol, total phenolics with the molecular markers were detected by Generalized Linear Model and Mixed Linear Model showing > 0.10 R2 value. Association of the trait, total flavonoids with marker RM7364 located on chromosome 8 reported in earlier study was validated in this investigation. The validated markers and the novel markers detected showing higher R2 value will be useful for improvement of seed vigour in rice.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data availability

The data generated or analyzed in this study are included in this article.

References

  • Aebi H (1984) Catalase in vitro methods. In: Colowick SP, Kaplan NO (eds) Methods in enzymology. Academic Press, Cambridge, p 105, 114–121

    Google Scholar 

  • Agrama HA, Eizenga GC, Yan W (2007) Association mapping of yield and its components in rice cultivars. Mol Breed 19:341–356. https://doi.org/10.1007/s11032-006-9066-6

    Article  Google Scholar 

  • Allard RW (1960) Principles of plant breeding. Wiley, New York

    Google Scholar 

  • Anandan A, Pradhan SK, Das SK, Behera L, Sangeetha G (2015) Differential responses of rice genotypes and physiological mechanism under prolonged deepwater flooding. Field Crops Res 172:153–163

    Google Scholar 

  • Anandan A, Anumalla M, Pradhan SK, Ali J (2016) Population structure, diversity and trait association analysis in rice (Oryza sativa L.) germplasm for early seedling vigour (ESV) using trait linked SSR markers. PLoS ONE 11(3):406. https://doi.org/10.1371/journal.pone.0152406

    Article  CAS  Google Scholar 

  • Arnon DI (1994) Copper enzymes in isolated chloroplasts Polyphenoloxidasein Beta vulgaris. Plant Physiol 24:1–15

    Google Scholar 

  • Baek J, Cho EE, Lee D, Chung N (2018) Evaluation of seed vigor tests for predicting seedling establishment at low temperature in rice (Oryza sativa L.). J Crop Sci Biotechnol 21(2):155–163

    Google Scholar 

  • Barik SR, Pandit E, Pradhan SK, Mohanty SP, Mohapatra T (2019) Genetic mapping of morpho-physiological traits involved during reproductive stage drought tolerance in rice. PLoS ONE 14(12):e0214979

    CAS  PubMed  PubMed Central  Google Scholar 

  • Barik SR, Pandit E, Mohanty SP, Nayak DK, Pradhan SK (2020) Genetic mapping of physiological traits associated with terminal stage drought tolerance in rice. BMC Genet 21:76. https://doi.org/10.1186/s12863-020-00883-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Bolivar C, Luis C (2010) Impact of germination on phenolic content and antioxidant activity of 13 edible seed species. Food Chem 119:1485–1490

    Google Scholar 

  • 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 23:2633–2635. https://doi.org/10.1093/bioinformatics/btm308

    Article  CAS  Google Scholar 

  • Bucci R, Magri AD, Magri AL, Marini F (2003) Comparison of three spectrophotometric methods for the determination of gamma-oryzanol in rice bran oil. Anal Bioanal Chem 375(8):1254–1259

    CAS  PubMed  Google Scholar 

  • Chen H, He H, Zou Y, Chen W, Yu R, Liu X, Yang Y, Gao YM, Xu JL, Fan LM (2011) Development and application of a set of breeder-friendly SNP markers for genetic analyses and molecular breeding of rice (Oryza sativa L.). Theor Appl Genet 123(6):869–879. https://doi.org/10.1007/s00122-011-1633-5

    Article  PubMed  Google Scholar 

  • Cui KH, Peng SB, Xing YZ, Xu CG, Yu SB, Zhang Q (2002) Molecular dissection of seedling-vigour and associated physiological traits in rice. Theor Appl Genet 105:745–753

    CAS  PubMed  Google Scholar 

  • Dang X, Thi TGT, Dong G, Wang H, Edzesi WM, Hong D (2014) Genetic diversity and association mapping of seed vigour in rice (Oryza sativa L.). Planta 239:1309–1319. https://doi.org/10.1007/s00425-014-2060-z

    Article  CAS  PubMed  Google Scholar 

  • Daniel OI (2017) Biology of seed vigor in the light of -omics tools. In: Jimenez- Lopez JC (ed) Advances in seed biology 6. https://doi.org/10.5772/intechopen.71258. https://www.intechopen.com/books/advances-in-seed-biology/biology-of-seed-vigor-in-the-light-of-omics-tools

  • Davis BH (1976) Carotenoids. In: Goodwin TW (ed) Chemistry and biochemistry of plant pigments, 2nd edn. Academic Press Inc, London, pp 38–165

    Google Scholar 

  • Dingkuhn M, Johnson DE, Sow A, Audebert AY (1999) Relationship between upland rice canopy characteristics and weed competitiveness. Field Crop Res 61:71–95

    Google Scholar 

  • Eberhardt MV, Lee CY, Liu RH (2000) Antioxidant activity of fresh apples. Nature 405:903–904

    CAS  PubMed  Google Scholar 

  • Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14(8):2611–2620 PMID: 15969739

    CAS  PubMed  Google Scholar 

  • Finch-Savage WE, Bassel GW (2016) Seed vigour and crop establishment: extending performance beyond adaptation. J Exp Bot 67(3):567–591

    CAS  PubMed  Google Scholar 

  • Flint-Garcia SA, Thuillet AC, Yu J, Pressoir G, Romero SM, Mitchell SE et al (2005) Maize association population: a high-resolution plat form for quantitative trait locus dissection. Plant J 44(6):1054–1064 PMID:16359397

    CAS  PubMed  Google Scholar 

  • Fujino K, Sekiguchi H, MatsudaY Sugimoto K, Ono K, Yano M (2008) Molecular identification of a major quantitative trait locus, qLTG3-1, controlling low-temperature germinability in rice. Proc of Natl Acad Sci USA 105:12623–12628

    CAS  Google Scholar 

  • Fuleki T, Francis FJ (1968) Quantitative methods for anthocyanins, extraction and determination of total anthocyanin in cranberries. J Food Sci 33:72–77

    CAS  Google Scholar 

  • Furukawa T, Maekawa M, Oki T, Suda I, Iida S, Shimada H, Takamure I, Kadowaki KI (2007) The Rcand Rd genes are involved in proanthocyanidin synthesis in rice pericarp. Plant J 49:91–102

    CAS  PubMed  Google Scholar 

  • Garris AJ, Thomas HT, Jason C, Steve K, Susan MC (2005) Genetic structure and diversity in Oryza sativa L. Genetics 169(3):1631–1638. https://doi.org/10.1534/genetics.104.035642

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hampl V, Pavlicek A, Flegr J (2001) Construction and bootstrap analysis of DNA finger printing-based phylogenetic trees with the freeware program FreeTree: application to trichomonadparasites. Int J Syst Evol Microbiol 51:731–735

    CAS  PubMed  Google Scholar 

  • Hasanuzzaman M (2015) Concept note. http://hasanuzzaman.weebly.com/uploads/9/3/4/0/934025/seed quality

  • Huang X, Zhao Y, Wei X, Li C, Wang A, Zhao Q, LiW GuoY, Deng L, Zhu C, Fan D, Lu Y, Weng Q, Liu K, Zhou T, Jing Y, Si L, Dong G, Huang T, Lu T, Feng Q, Qian Q, Li J, Han B (2011) Genome wide association study of flowering time and grain yield traits in a worldwide collection of rice germplasm. Nat Genet 44(1):32–39. https://doi.org/10.1038/ng.1018

    Article  CAS  PubMed  Google Scholar 

  • Huang X, Yang S, Gong J, Zhao Y, Feng Q, Gong H et al (2015) Genomic analysis of hybrid rice varieties reveals numerous superior alleles that contribute to heterosis. Nat Commun 6:6258. https://doi.org/10.1038/ncomms7258

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Huang M, Zhang R, Chen J, Cao F, Jiang L, Zou Y (2017) Morphological and physiological traits of seeds and seedlings in two rice cultivars with contrasting early vigor. Plant Prod Sci 20:95–101. https://doi.org/10.1080/1343943X.2016.1229571

    Article  Google Scholar 

  • Jayaraman J (1981) Laboratoy manual in biochemistry. Wiley Estern Ltd., New Delhi

    Google Scholar 

  • Jin L, Xiao P, Lu Y, Shao YF, Shen Y, Bao JS (2009) Quantitative trait loci for brown rice color, total phenolics and flavonoid contents and antioxidant capacity in rice grain. Cereal Chem 86:609–615

    CAS  Google Scholar 

  • Jin L, Lu Y, Xiao P, Sun M, Corke H, Bao J (2010) Genetic diversity and population structure of a diverse set of rice germplasm for association mapping. Theor Appl Genet 121(3):475–487. https://doi.org/10.1007/s00122-010-1324-7

    Article  PubMed  Google Scholar 

  • Kumar A, Bimolata W, Kannan M, Kirti PB, Qureshi IA, Ghazi IA (2015) Comparative proteomics reveals differential induction of both biotic and abiotic stress response associated proteins in rice during Xanthomonas oryzae pv. oryzae infection. Funct Integr Genomics 15:425–437. https://doi.org/10.1007/s10142-014-0431-y

    Article  CAS  PubMed  Google Scholar 

  • Latha M, Abdul Nizar M, Abraham Z, Joseph John K, Asokan Nair R, Mani S, Dutta M (2013) Rice landraces of Kerala State of India: a documentation. Int J Biodivers Conserv 5(4):250–263. https://doi.org/10.5897/IJBC12.138

    Article  Google Scholar 

  • Liu K, Muse SV (2005) PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 21(9):2128–2129

    CAS  PubMed  Google Scholar 

  • Liu LF, Lai YY, Cheng JP, Wang L, Du WL, Wang ZF, Zhang HS (2014) Dynamic quantitative trait locus analysis of seed vigor at three maturity stages in rice. PLoS ONE 9:e115732

    PubMed  PubMed Central  Google Scholar 

  • Madamanchi NR, Donahue JL, Cramer CL, AlscherRG Pedersen K (1994) Differential response of Cu, Zn SOD in two pea cultivars during a short term exposure to SO2. Plant Mol Biol 26:95–103

    CAS  PubMed  Google Scholar 

  • Mahender A, Anandan A, Pradhan SK (2015) Early seedling vigor, an imperative trait for direct seeded rice: an overview on physio-morphological parameters and molecular markers. Planta 241:1027–1050 pmid:25805338

    CAS  PubMed  Google Scholar 

  • Mahender A, Anandan A, Pradhan SK, Pandit E (2016) Rice grain nutritional traits and their enhancement using relevant genes and QTLs through advanced approaches. SpringerPlus. 5:2086. https://doi.org/10.1186/s40064-016-3744-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Manners R, Etten JV (2018) Are agricultural researchers working on the right crops to enable food and nutrition security under future climates? Glob Environ Chang 53:182–194. https://doi.org/10.1016/j.gloenvcha.2018.09.010

    Article  Google Scholar 

  • Miura K, Lin S, Yano M, Nagamine T (2002) Mapping quantitative trait loci controlling seed longevity in rice (Oryza sativa L.). Theor Appl Genet 104:981–986

    CAS  PubMed  Google Scholar 

  • Murray MG, Thompson WF (1980) Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res 8:4321–4325 PMID: 7433111

    CAS  PubMed  PubMed Central  Google Scholar 

  • Muthukumar C, Subathra T, Aiswarya GV, Babu RC (2015) Comparative genomewide association studies for plant production traits under drought in diverse rice (Oryza sativa L.) lines using SNP and SSR markers. Curr Sci 109(1):139–147

    Google Scholar 

  • Pan Y, Zhang H, Zhang D, Li J, Xiong H, Yu J et al (2015) Genetic analysis of cold tolerance at the germination and booting stages in rice by association mapping. PLoS ONE 10:e0120590. https://doi.org/10.1371/journal.pone.0120590

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Pandit E, Tasleem S, Barik SR, Mohanty DP, Nayak DK, Mohanty SP, Das S, Pradhan SK (2017) Genome-wide association mapping reveals multiple QTLs governing tolerance response for seedling stage chilling stress in indica rice. Front Plant Sci 8:552. https://doi.org/10.3389/fpls.2017.00552

    Article  PubMed  PubMed Central  Google Scholar 

  • Pandit E, Panda RK, Sahoo A, Pani DR, Pradhan SK (2020) Genetic relationship and structure analyses of root growth angle for improvement of drought avoidance in early and mid-early maturing rice genotypes. Rice Sci 27(2):124–132

    Google Scholar 

  • Patra BC, Dhua SR (2003) Agro-morphological diversity scenario in upland rice germplasm of Jeypore tract. Genet Resour Crop Evol 50(8):825–828. https://doi.org/10.1023/A:1025963411919

    Article  Google Scholar 

  • Pavalicek A, Hrda S, Flegr J (1999) Free Tree—freeware program for construction of phylogenetic trees on the basis of distance data and bootstrap/jackknife analysis of the tree robustness. Application in the RAPD analysis of genus Frenkelia. Folia Biol (Praha) 45:97–99

    Google Scholar 

  • Pradhan SK, Barik SR, Sahoo A, Mohapatra S, Nayak DK, Mahender A, Meher J, Anandan A, Pandit E (2016) Population structure, genetic diversity and molecular marker-trait association analysis for high temperature stress tolerance in rice. PLoS ONE 11(8):123. https://doi.org/10.1371/journal.pone.0160027

    Article  CAS  Google Scholar 

  • Pradhan SK, Pandit E, Pawar S, Bharati B, Chatopadhyay K, Singh S, Dash P, Reddy JN (2019) Association mapping reveals multiple QTLs for grain protein content in rice useful for biofortification. Mol Genet Genomics 294(4):963–983. https://doi.org/10.1007/s00438-019-01556-w

    Article  CAS  PubMed  Google Scholar 

  • Pradhan SK, Pandit E, Pawar S, Naveenkumar R, Barik SR, Mohanty SP, Nayak DK, Ghritlahre SK, Rao DS, Reddy JN, Patnaik SSC (2020) Linkage disequilibrium mapping for grain Fe and Zn enhancing QTLs useful for nutrient dense rice breeding. BMC Plant Biol 20(1):57. https://doi.org/10.1186/s12870-020-2262-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Putter J (1974) Peroxidase. In: Bergmeyer HU (ed) Methods of enzymatic analysis. Academic Press, Cambridge, pp 685–690

    Google Scholar 

  • Rao AN, Johnson DE, Sivaprasad B, Ladha JK, Mortimer AM (2007) Weed management in direct-seeded rice. Adv Agron 93:153–255

    CAS  Google Scholar 

  • Salgotra RK, Gupta BB, Bhat JA, Sharma S (2015) Genetic diversity and population structure of basmati rice (Oryza sativa L.) germplasm collected from North Western Himalayas using trait linked SSR markers. PLoS ONE 10(7):0131858. https://doi.org/10.1371/journal.pone.0131858

    Article  CAS  Google Scholar 

  • Sanghamitra P, Bagchi TB, Sah RP, Sharma SG, Sarkar S, Basak N (2017) Characterization of red and purple-pericarp rice (Oryza sativa L) based on physico-chemical and antioxidative properties of grains. Oryza-An Int J Rice 54(1):57–64

    Google Scholar 

  • Sanghamitra P, Sah RP, Bagchi TB, Sharma SG, Kumar A, Munda S, Sahu RK (2018) Evaluation of variability and environmental stability of grain quality and agronomic parameters of pigmented rice (O. sativa L.). J Food Sci Technol 55(3):879–890

    CAS  PubMed  PubMed Central  Google Scholar 

  • Shao Y, Jin L, Zhang G, Lu Y, Shen Y, Bao J (2011) Association mapping of grain color, phenolic content, flavonoid content and antioxidant capacity in dehulled rice. Theor Appl Genet 122:1005. https://doi.org/10.1007/s00122-010-1505-4

    Article  CAS  PubMed  Google Scholar 

  • Singh RK, Chaudhary BD (1985) Biometrical methods in quantitative analysis. Kalayani Publishers, New Delhi

    Google Scholar 

  • Singh N, Choudhury, Singh AK, Kumar S, Srinivasan K, Tyagi RK et al (2013) Comparison of SSR and SNP markers in estimation of genetic diversity and population structure of Indian rice varieties. PLoS ONE 8(12):84136. https://doi.org/10.1371/journal.pone.0084136

    Article  CAS  Google Scholar 

  • Swamy BPM, Noraziyah AAS, Site NAR, Ramil M, Wickneswari R, Teressa SC, Arvind K (2017) Association mapping of yield and yield-related traits under reproductive stage drought stress in rice (Oryza sativa L). Rice 10:21. https://doi.org/10.1186/s12284-017-0161-6©

    Article  PubMed  PubMed Central  Google Scholar 

  • Sweeney MT, Thomson MJ, Pfeil BE, McCouch SR (2006) Caught red-handed: rc encodes a basic helix–loop–helix protein conditioning red pericarp in rice. Plant Cell 18:283–294

    CAS  PubMed  PubMed Central  Google Scholar 

  • Vanlalsanga SSP, Singh YT (2019) Rice of Northeast India harbor rich genetic diversity as measured by SSR markers and Zn/Fe content. BMC Genet 20:79. https://doi.org/10.1186/s12863-019-0780-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Wang Z, Wan J, Bao Y, Wang F, Zhang H (2010) Quantitative trait loci analysis for rice seed vigor during the germination stage. J Zhejiang Univ-Sci B (Biomed Biotechnol). 11(12):958–964

    Google Scholar 

  • Yamauchi M, Winn T (1996) Rice seed vigor and seedling establishment in anaerobic soil. Crop Sci 36:680–686

    Google Scholar 

  • Zhang ZH, Qu XS, Wan S, Chen LH, Zhu YG (2005) Comparison of QTL controlling seedling vigor under different temperature conditions using recombinant inbred lines in rice (Oryza sativa). Ann Bot 95(3):423–429

    CAS  PubMed  Google Scholar 

  • Zhang P, Li J, Li X, Liu X, Zhao X, Lu Y (2011) Population structure and genetic diversity in a rice core collection (Oryza sativa L.) investigated with SSR markers. PLoS ONE 6(12):e27565. https://doi.org/10.1371/journal.pone.0027565

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhang Y, Zou M, De T (2012) Association analysis of rice cold tolerance at tillering stage with SSR markers in japonica cultivars in Northeast China. Chin J Rice Sci 26:423–430

    Google Scholar 

  • Zhang P, Zhong K, Shahid MQ, Tong H (2017) Association analysis in rice: from application to utilization. Front Plant Sci 7:1202. https://doi.org/10.3389/fpls.2016.01202

    Article  Google Scholar 

  • Zhao K, Tung CW, Eizenga GC, Wright MH, Ali ML, Price AH (2011) Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa. Nat Commun 2:467. https://doi.org/10.1038/ncomms1467

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhao WG, Jong WC, Soon WK, Jeong HL, Kyung HM, Yong JP (2013) Association analysis of physicochemical traits on eating quality in rice (Oryza sativa L.). Euphytica 191:9–21

    Google Scholar 

  • Zilic S, Hadzi-Taskovic SV, Dodig D, Maksimovic V, Maksimovic M, Basic Z (2011) Antioxidant activity of small grain cereals caused by phenolics and lipid soluble antioxidants. J Cereal Sci 54:417–424

    CAS  Google Scholar 

Download references

Acknowledgements

The authors are highly grateful to the Director, ICAR-National Rice Research Institute, Cuttack and Head, Crop Improvement Division of the Institute for providing all the necessary facilities including the funding for conducting the experiment.

Funding

This work was internal project of the Institute under program1; Project No.1.6 of ICAR- National Rice Research Institute Cuttack, Odisha, India. Institute fund was utilized for completion of the Project work. No externally aided fund was received for this study.

Author information

Authors and Affiliations

Authors

Contributions

SKP conceived the idea, PS and SKP wrote, and PS, EP and SKP revised the paper. SS, NN, SP, EP and RB generated phenotypic and genotypic data. EP and KCM performed data analyses. SKP interpreted the data. All authors reviewed and approved the final manuscript.

Corresponding authors

Correspondence to Elssa Pandit or Sharat Kumar Pradhan.

Ethics declarations

Competing interests

We declare that there is no competing interest among the authors.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Guidelines were followed in the ethics approval and consent to participate.

Additional information

Publisher's Note

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

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sahoo, S., Sanghamitra, P., Nanda, N. et al. Association of molecular markers with physio-biochemical traits related to seed vigour in rice. Physiol Mol Biol Plants 26, 1989–2003 (2020). https://doi.org/10.1007/s12298-020-00879-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12298-020-00879-y

Keywords

Navigation