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Journal of Crop Science and Biotechnology

, Volume 22, Issue 5, pp 451–464 | Cite as

Sensitivity of Seeds to Chemical Mutagens, Detection of DNA Polymorphisms and Agro-Metrical Traits in M1 Generation of Coffee (Coffea arabica L.)

  • César Vargas-Segura
  • Emmanuel López-Gamboa
  • Emanuel Araya-Valverde
  • Marta Valdez-Melara
  • Andrés Gatica-AriasEmail author
Research Article
  • 6 Downloads

Abstract

Coffee (Coffea Arabica L.) is threatened by biotic and abiotic stresses. Nevertheless, the breeding of Arabica coffee is restricted due to its low genetic diversity. Crop improvement via mutagenesis represents an alternative for increasing genetic variability and facilitating breeding. In this sense, coffee seeds cv. Catuaí were treated for 8 h with a solution of sodium azide (NaN3) (0, 50, 75, 100, and 125 mM) and ethyl methane sulfonate (EMS) (0, 80, 160, 240, 320, and 400 mM). The genetic variability induced in coffee plants after mutagenic treatment with sodium azide was determined by RAPD and AFLP analyses. As the concentration of applied NaN3 and EMS increased, the germination, seedling height, and root length decreased. The LD50 values for NaN3 and EMS were between 50-75 mM and 160-240 mM, respectively. For the 12 RAPD primers evaluated, a total of 46 fragments were obtained of which 34 were polymorphic bands (74%). The amplification with six AFLP selective primer combinations allowed the identification of 36 polymorphisms (17.8%). The analysis revealed that both NaN3 and EMS induced variability within the DNA regions amplified with AFLP and RAPD markers. Finally, under field conditions, significant differences were noticed with respect to plant height, number of nodes in the orthotropic stem, and number of branches of the M1 mutant (NaN3-treated) plants compared to the non-mutant plants. Optimal conditions for NaN3 and EMS mutagenesis using seeds were determined and the optimized conditions have been used to generate a NaN3 mutant M1 coffee var. Catuaí population.

Key words

Coffee chemical mutagenesis EMS sodium azide AFLP RAPD M1 generation 

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Notes

Acknowledgments

This study was financed by the University of Costa Rica, the Ministerio de Ciencia, Tecnology Telecomunicaciones (MICITT) and the Consejo Nacional para Investigaciones Cientcas y Tecnolas (CONICIT) (project No. 111-B5- 140; FI-030B-14). The authors would like to thank Dr. Paul Hanson (School of Biology, University of Costa Rica) for language correction of the manuscript.

Author contributions

C.V.S designed and performed the experiments and analyzed data; E.L.G performed the phenotyping of the M1 mutants; E.A.V. performed AFLPs and analyzed data; M.V.M. discussed the results and edited the paper; A.G.A conceived the project, designed and coordinated the experiments, analyzed data, and wrote the paper.

References

  1. Abuzayed M, El-Dabba N, Frary A, Doganlar S. 2017. GDdom: An online tool for calculation of dominant marker gene diversity. Biochem. Genet. 55(2):155–157PubMedCrossRefPubMedCentralGoogle Scholar
  2. Aerts R, Berecha G, Gijbels P, Hundera K, Glabeke S, Vandepitte K, Muys B, Roldán-Ruiz I, Honnay O. 2013. Genetic variation and risks of introgression in the wild Coffea arabica gene pool in south-western Ethiopian montane rainforests. Evol. Appl. 6(2): 243–252PubMedCrossRefPubMedCentralGoogle Scholar
  3. Ali A, Yubey K, Deka UKr, Tomar SMS. 2014. Effect of sodium azide on seed germination and related agro-metrical traits in M1 lentil (Lens culinaris Medik.) generation. World J. Agric. Sci. 10 (3): 95–102Google Scholar
  4. Arena C, Turano M, Hay Mele B, Cataletto PR, Furia M, Pugliese M, De Micco V. 2017. Anatomy, photochemical activity, and DNA polymorphism in leaves of dwarf tomato irradiated with X-rays. Biol. Plant 61(2): 305–314CrossRefGoogle Scholar
  5. Arisha MH, Liang BK, Shah SNM, Gong ZH, Li DW. 2014. Kill curve analysis and response of first generation Capsicum annuum L. B12 cultivar to ethyl methane sulfonate. Genet. Mol. Res. 13: 10049–10061PubMedCrossRefGoogle Scholar
  6. Arisha MH, Shah SNM, Gong ZH, Jing H, Cao L, Zhang HX. 2015. Ethyl methane sulfonate induced mutations in M2 generation and physiological variations in M1 generation of peppers (Capsicum annuum L.). Front. Plant Sci. 6: 399. doi:10.3389/fpls.2015.00399PubMedPubMedCentralCrossRefGoogle Scholar
  7. Aslam R, Bhat TM, Choudhary S, Ansari MYK, Shahwar D. 2017. Estimation of genetic variability, mutagenic effectiveness and efficiency in M2 flower mutant lines of Capsicum annuum L. treated with caffeine and their analysis through RAPD markers. J King Saud Univ. Sci. 29: 274–283CrossRefGoogle Scholar
  8. Aslam M, Saeed MS, Sattar S, Rehan M, Sajjad M. 2018. Result of chemical mutagenesis on quantitative as well as qualitative traits of maize (Zea mays (L.) Int. J. Pure App. Biosci. 6 (1): 12–15CrossRefGoogle Scholar
  9. Atienzar FA, Jha AN. 2006. The random amplified polymorphic DNA (RAPD) assay and related techniques applied to genotoxicity and carcinogene-sis studies: a critical review. Mutat. Res. 613: 76–102PubMedCrossRefGoogle Scholar
  10. Aviya K, Mullainathan L. 2018. Studies on effect of induced mutagenesis on finger millet (Eleusine coracana (L.) Gaertn.) var-CO 13 in M1 generation. Hortic Biotech Res 4: 23–25Google Scholar
  11. Behera M, Panigrahi J, Mishra RR, Rath SP. 2012. Analysis of EMS induced in vitro mutants of Asteracantha longifolia (L.) Nees using RAPD markers. Ind. J. Biotech. 11(1): 39–47Google Scholar
  12. Bolívar-González A, Valdez-Melara M, Gatica-Arias A. 2018. Responses of Arabica coffee (Coffea arabica L. var. Catuaí) cell suspensions to chemically induced mutagenesis and salinity stress under in vitro culture conditions. In Vitro Cell Dev. Biol. Plant 54: 576CrossRefGoogle Scholar
  13. Campos NA, Panis B, Carpentier SC. 2017. Somatic embryogenesis in coffee: The evolution of biotechnology and the integration of omics technologies offer great opportunities. Front. Plant Sci. 8: 1460PubMedPubMedCentralCrossRefGoogle Scholar
  14. da Cunha Galvão LM, Lages-Silva E. 2008. Randomly amplified polymorphic DNA (RAPD) In Molecular Biomethods Handbook, pp 133–147, Totowa, NJ, Humana Press https://doi.org/101007/978-1-60327-375-6_10 CrossRefGoogle Scholar
  15. Dada KE, Anagbogu CF, Forster BP, Muyiwa AA, Adenuga OO, Olaniyi OO, Bado S. 2018. Biological effect of gamma irradiation on vegetative propagation of Coffea arabica L. Afr. J. Plant Sci. 12(6): 122–128CrossRefGoogle Scholar
  16. Dhakshanamoorthy D, Selvaraj R, Chidambaram A. 2015. Utility of RAPD marker for genetic diversity analysis in gamma rays and ethyl methane sulphonate (EMS)-treated Jatropha curcas plants. CR Biol. 338(2):75–82CrossRefGoogle Scholar
  17. dos Santos TB, Budzinski IGF, Marur CJ, Petkowicz CLO, Pereira LFP, Vieira LGE. 2011. Expression of three galactinol synthase isoforms in Coffea arabica L. and accumulation of raffinose and stachyose in response to abiotic stresses Plant Physiol. Biochem. 49(4): 441–448Google Scholar
  18. Doyle JJ. 1990. Isolation of plant DNA from fresh tissue. Focus 12: 13–15Google Scholar
  19. Dhumal KN, Bolbhat SN. 2012. Induction of genetic variability with gamma radiation and its applications in improvement of horsegram. In: Adrovic, Feriz (Ed.), Gamma Radiation. In Tech Publisher, Croatia, pp. 207–228Google Scholar
  20. Fain SJ, Quiñones M, Álvarez-Berríos NL, Parés-Ramos IK, Gould WA. 2018. Climate change and coffee: assessing vulnerability by modeling future climate suitability in the Caribbean island of Puerto Rico. Climatic Change 146: 175–186CrossRefGoogle Scholar
  21. Gandhi ES, Sri Devi A, Mullainathan L. 2014. The effect of ethyl methane sulphonate and diethyl sulphate on chilli (Capsicum annuum L.) in M1 generation. Int. Lett. Nat. Sci. 5: 18-3Google Scholar
  22. Garrido-Cardenas JA, Mesa-Valle C, Manzano-Agugliaro F. 2018. Trends in plant research using molecular markers. Planta 247: 543–557PubMedCrossRefGoogle Scholar
  23. Gatica A, Farag M, Häntzschel K, Matoušek J, Weber G. 2012. The transcription factor AtMYB75/PAP1 regulates the expression of flavonoid biosynthesis genes in transgenic hop (Humulus lupulus L.) Brew. Sci. 65: 103–111Google Scholar
  24. Gruszka D, Szarejko I, Maluszynski M. 2012. Sodium azide as a mutagen. In Plant mutation breeding and biotechnology, pp 159–168, Wallingford: CABI https://doi.org/101079/97817806408530159 CrossRefGoogle Scholar
  25. Hofmann NE, Raja R, Nelson RL, Korban SS. 2004. Mutagenesis of embryogenic cultures of soybean and detecting polymorphisms using RAPD markers Biol. Plant 48(2): 173–177Google Scholar
  26. Imran M, Dash M, Das TR, Kabi M. 2018. Analysis of induced genetic variability for morphological and floral characters with male sterility in sesame (Sesamum indicum L.). Electron J. Plant Breed. 9(3): 801–807CrossRefGoogle Scholar
  27. Ivamoto ST, Reis O, Domingues DS, dos Santos TB, de Oliveira FF, et al. 2017. Transcriptome analysis of leaves, flowers and fruits perisperm of Coffea arabica L reveals the differential expression of genes involved in raffinose biosynthesis. PloS One 12(1): e0169595PubMedPubMedCentralCrossRefGoogle Scholar
  28. Jankowicz-Cieslak J, Till BJ. 2017. Chemical mutagenesis and chimera dissolution in vegetatively propagated banana. In J Jankowicz-Cieslak, TH Tai, J Kumlehn, BJ Till, eds., Biotechnologies for Plant Mutation Breeding, Springer International Publishing, ChamCrossRefGoogle Scholar
  29. Jones C, Kortenkamp A. 2000. RAPD library fingerprinting of bacterial and human DNA applications in mutation detection. Carcinog. Mutagen 20: 49–63CrossRefGoogle Scholar
  30. Joshi N, Ravindran A, Mahajan V. 2011. Investigations on chemical mutagen sensitivity in onion (Allium cepa L.) Int. J. Bot. 7(3): 243–248CrossRefGoogle Scholar
  31. Kannan B, Davila-Olivas NH, Lomba P, Altpeter F. 2015. In vitro chemical mutagenesis improves the turf quality of bahiagrass. Plant Cell Tiss. Organ Cult. 120: 551–561CrossRefGoogle Scholar
  32. Khan IA, Dahot MU, Seema N, Yasmin S, Bibi S, Raza S, Khatri A. 2009. Genetic variability in sugarcane plantlets developed through in vitro mutagenesis. Pak. J. Bot. 41(1): 153–166Google Scholar
  33. Kumar AP, Boualem A, Bhattacharya A, Parikh S, Desai N, Zambelli A, et al. 2013. SMART–Sunflower mutant population and reverse genetic tool for crop improvement. BMC Plant Biol. 13: 38–46PubMedPubMedCentralCrossRefGoogle Scholar
  34. Laskar RA, Laskar AA, Raina A, Khan S, Younus H. 2018. Induced mutation analysis with biochemical and molecular characterization of high yielding lentil mutant lines. Int. J. Biol. Macromol. 109: 167–179PubMedCrossRefPubMedCentralGoogle Scholar
  35. Lee DK, Kim YS, Kim JK. 2017. Determination of the optimal condition for ethylmethane sulfonate-mediated mutagenesis in a Korean commercial rice, Japonica cv. Dongjin. Appl. Biol. Chem. 60(3): 241–247CrossRefGoogle Scholar
  36. Lu G, Zhang X, Zou Y, Zou Q, Xiang X, Cao J. 2007. Effect of radiation on regeneration of Chinese narcissus and analysis of genetic variation with AFLP and RAPD markers. Plant Cell Tiss. Organ Cult. 88: 319–327CrossRefGoogle Scholar
  37. Mba C, Afza R, Bado S, Mohan J. 2010. Induced mutagenesis in plants using physical and chemical agents In: MR Davey, P Anthony P, eds., Plant Cell Culture: Essential Methods 1st ed Wiley-Blackwell, New Jersey, pp 111–130CrossRefGoogle Scholar
  38. Nadeem MA, Nawaz MA, Shahid MQ, Doğan Y, Comertpay G, et al. 2018. DNA molecular markers in plant breeding: current status and recent advancements in genomic selection and genome editing. Biotechnol. Biotechnol. Equip. 32(2): 261–285CrossRefGoogle Scholar
  39. Parry MAJ, Madgwick PJ, Bayon C, Tearall K, Hernandez-Lopez A, et al. 2009. Mutation discovery for crop improvement J. Exp. Bot. 60(10): 2817–2825PubMedCrossRefPubMedCentralGoogle Scholar
  40. Peakall R, Smouse PE. 2012. GenAlEx 65: genetic analysis in Excel Population genetic software for teaching and research —an update. Bioinformatics Applications Note 28: 2537–2539CrossRefGoogle Scholar
  41. Perrier X, Flori A, Bonnot F. 2003. Methods of data analysis. In: P Hamon, M Seguin, X Perrier, JC Glaszmann, eds., Genetic diversity of cultivated tropical plants, 1st ed Science Publishers, Montpellier, pp 43–76Google Scholar
  42. Powell W, Morgante M, Andre C, Hanafey M, Vogel J, Tingey S, Rafalski A. 1996. The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis. Mol. Breed. 2: 225–238CrossRefGoogle Scholar
  43. Ribas AF, Pereira LFP, Vieira LGE. 2006. Genetic transformation of coffee. Braz. J. Plant Physiol. 18(1): 83–94CrossRefGoogle Scholar
  44. Roldan-Ruiz I, Dendauw J, Van Bockstaele E, Depicker A, De Loose M. 2000. AFLP markers reveal high polymorphic rates in ryegrasses (Lolium spp) Mol. Breed. 6: 125–134CrossRefGoogle Scholar
  45. Roychowdhury R, Tah J. 2011. Germination behaviors in M2 generation Dianthus after chemical mutagenesis. Int. J. Adv. Sci.Technol. Res. 1(2): 448–454Google Scholar
  46. Sagastume H, Molina L, Ávalos A. 2003. Caracterización molecular, mediante AFLP, de la colección de variedades de frijol (Phaseolus vulgaris L) liberadas por el ICTA Proyecto FODECYT No15-01 Guatemala: ICTA SENACYTGoogle Scholar
  47. Sandhu SS, Bastos CR, Azini LE, Tulmann Neto A, Colombo C. 2002. RAPD analysis of herbicide-resistant Brasilian rice lines produced via mutagenesis. Genet. Mol. Res. 1(4): 359–70PubMedGoogle Scholar
  48. Senapati SK, Rout GR. 2011. In vitro mutagenesis in Rosa hybrida using oryzalin as a mutagen and screening of mutants by randomly amplified polymorphic DNA (RAPD) marker. Afr. J. Biotech. 10(30): 5705–5712Google Scholar
  49. Serrat X, Esteban R, Guibourt N, Moysset L, Nogués S, Lalanne E. 2014. EMS mutagenesis in mature seed-derived rice calli as a new method for rapidly obtaining TILLING mutant populations. Plant Methods 10: 5PubMedPubMedCentralCrossRefGoogle Scholar
  50. Silva M do C, Várzea V, Guerra-Guimarães L, Azinheira HG, Fernandez D, et al. 2006. Coffee resistance to the main diseases: leaf rust and coffee berry disease. Braz. J. Plant Physiol. 18(1): 119–147CrossRefGoogle Scholar
  51. Sivolap YM, Volkodav VV, Balvinska MS, Kozhukhova NE, Solodenko AE, Chebotar SV. 2004. Identification and registration of genotypes of common wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), maize (Zea mays L.), and sunflower (Helianthus annuus L.) using microsatellite locus analysis: guide lines manual, Odessa, p. 14Google Scholar
  52. Suprasanna P, Mirajkar S, Bhagwat S. 2015. Induced mutations and crop improvement. In: B Bahadur, M Rajam, L Sahijram, K Krishnamurthy, eds., Plant Biology and Biotechnol Vol I: Plant Diversity, Organization, Function and Improvement, 1st ed Springer International Publishing, New York, pp 593–617CrossRefGoogle Scholar
  53. Talebi AB, Talebi AB, Shahrokhifar B. 2012. Ethyl methane sulphonate (EMS) induced mutagenesis in Malaysian rice (cv. MR219) for lethal dose determination. Am. J. Plant Sci. 3: 1661–1665CrossRefGoogle Scholar
  54. Tellez E, Herrera RR, Saucedo AEM. 2009. Genotipificación de 2 mutantes de la variedad “golden delicious” de manzano utilizando AFLP´S Retrieved from http://wwwuaqmx/investigacion/difusion/veranos/memorias-2009/11VCRC_46/33_Tellez_Chavezpdf Google Scholar
  55. Thomas CM, Vos P, Zabeau M, Jones DA, Norcott KA, Chadwick BP, Jones JD. 1995. Identification of amplified restriction fragment polymorphism (AFLP) markers tightly linked to the tomato Cf-9 gene for resistance to Cladosporium fulvum. Plant J. 8(5): 785–94PubMedCrossRefPubMedCentralGoogle Scholar
  56. Tomlekova N, Spasova-Apostolova V, Panchev I. 2016. RAPD analysis of Bulgarian pepper induced mutant. Compt. Rend. Acad. Bulg. Sci. 69(6): 731–738Google Scholar
  57. van Harten AM. 1998. Mutation breeding: theory and practical applications. Cambridge University Press, New YorkGoogle Scholar
  58. Wang LN, Zhang B, Li JR, Yang XY, Ren ZH. 2014. Ethyl Methane sulfonate (EMS)-mediated mutagenesis of cucumber (Cucumis sativus L.) Agric. Sci. 5: 716–721Google Scholar
  59. Wannajindaporn A, Poolsawat O, Chaowiset W, Tantasawat P. 2014. Evaluation of genetic variability in in vitro sodium azide-induced Dendrobium “Earsakul” mutants. Genet Mol. Res. 13(3): 5333–5342PubMedCrossRefPubMedCentralGoogle Scholar
  60. Wu D, Shu QY, Li C. 2012. Applications of DNA marker techniques in plant mutation research. In Plant Mutation Breeding and Biotechnology, pp 287–298, Wallingford: CABI https://doi.org/101079/97817806408530287 Google Scholar

Copyright information

© Korean Society of Crop Science and Springer 2019

Authors and Affiliations

  • César Vargas-Segura
    • 1
  • Emmanuel López-Gamboa
    • 1
  • Emanuel Araya-Valverde
    • 2
  • Marta Valdez-Melara
    • 1
  • Andrés Gatica-Arias
    • 1
    Email author
  1. 1.Laboratorio Biotecnología de Plantas, Escuela de BiologíaUniversidad de Costa RicaSan PedroCosta Rica
  2. 2.Centro Nacional de Innovaciones Biotecnológicas (CENIBiot)CeNAT-CONARESan JoséCosta Rica

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