Multiscale Phenotyping and Decision Strategies in Breeding for Resistance

Trends in Plant Science

Volumn 22, Issue 5, 2017, Pages 420-432

  Willocquet, Laetitia ^a   Savary, Serge ^a   Yuen, Jonathan ^b  

^a UNIVERSITÉ DE TOULOUSE   (France)

^b SWEDISH UNIVERSITY OF AGRICULTURAL SCIENCES   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

BREEDING; DISEASE RESISTANCE; GENETICS; GENOTYPE; IMMUNOLOGY; PHENOTYPE; PLANT DISEASE; QUANTITATIVE TRAIT LOCUS;

BREEDING; DISEASE RESISTANCE; GENOTYPE; PHENOTYPE; PLANT DISEASES; QUANTITATIVE TRAIT LOCI;

EID: 85014114764     PISSN: 13601385     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.tplants.2017.01.009     Document Type: Review

References (83)

1. 1 Mundt, C.C., Durable resistance: a key to sustainable management of pathogens and pests. Inf. Genet. Evol. 27 (2014), 446–455.
2. 2 McDonald, B.A., Using dynamic diversity to achieve durable disease resistance in agricultural ecosystems. Trop. Plant Pathol. 39 (2014), 191–196.
3. 3 Brown, J.K.M., Durable resistance of crops to disease: a Darwinian perspective. Annu. Rev. Phytopathol. 53 (2015), 513–539.
4. 4 Lannou, C., Variation and selection of quantitative traits in plant pathogens. Annu. Rev. Phytopathol. 50 (2012), 319–338.
5. 5 Zhan, J., et al. Playing on a pathogen's weakness: using evolution to guide sustainable plant disease control strategies. Annu. Rev. Phytopathol. 53 (2015), 19–43.
6. 6 McDonald, B.A., Linde, C., Pathogen population genetics, evolutionary potential, and durable resistance. Annu. Rev. Phytopathol. 40 (2002), 349–379.
7. 7 Zhan, J., et al. Achieving sustainable plant disease management through evolutionary principles. Trends Plant Sci. 19 (2014), 570–575.
8. 8 Parlevliet, J.E., Components of resistance that reduce the rate of epidemic development. Annu. Rev. Phytopathol. 17 (1979), 203–222.
9. 9 Bonman, J.M., et al. Breeding rice for resistance to pests. Annu. Rev. Phytopathol. 30 (1992), 507–528.
10. 10 Niks, R., et al. Quantitative resistance to biotrophic filamentous plant pathogens: concepts, misconceptions, and mechanisms. Annu. Rev. Phytopathol. 53 (2015), 445–470.
11. 11 Stuthman, D.D., et al. Breeding crops for durable resistance to disease. Adv. Agron. 95 (2007), 319–367.
12. 12 Poland, J.A., et al. Shades of gray: the world of quantitative disease resistance. Trends Plant Sci. 14 (2009), 21–29.
13. 13 St Clair, D.A., Quantitative disease resistance and quantitative resistance loci in breeding. Annu. Rev. Phytopathol. 48 (2010), 27–268.
14. 14 Huang, X., Han, B., Natural variations and genome-wide association studies in crop plants. Annu. Rev. Plant Biol. 65 (2014), 531–551.
15. 15 Varshney, R.K., et al. Harvesting the promising fruits of genomics: applying genome sequencing technologies to crop breeding. PLoS Biol., 12, 2014, e1001883.
16. 16 Cobb, J.N., et al. Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype–phenotype relationships and its relevance to crop improvement. Theor. Appl. Genet. 126 (2013), 867–887.
17. 17 Yin, X., et al. Role of crop physiology in predicting gene-to-phenotype relationships. Trends Plant Sci. 9 (2004), 426–432.
18. 18 Hammer, G., et al. Models for navigating biological complexity in breeding improved crop plants. Trends Plant Sci. 11 (2006), 587–593.
19. 19 Yin, X., Struik, P.C., Applying modelling experiences from the past to shape crop systems biology: the need to converge crop physiology and functional genomics. New Phytol. 179 (2008), 629–642.
20. 20 Cooper, M., et al. Use of crop growth models with whole-genome prediction: application to a maize multienvironment trial. Crop Sci. 56 (2016), 1–16.
21. 21 Hammer, G., et al. Molecular breeding for complex adaptive traits: how integrating crop ecophysiology and modelling can enhance efficiency. Yin, X., Struik, P.C., (eds.) Crop Systems Biology, 2016, Springer International Publishing, 147–162.
22. 22 Gaeümann, E., Pflanzische Infektionslehre. 1946, Birkhaeuser.
23. 23 Kranz, J., Epidemics, their mathematical analysis and modeling: an introduction. Kranz, J., (eds.) Epidemics of Plant Diseases, 2nd edn, 1990, Springer Verlag, 1–11.
24. 24 Parlevliet, J.E., van Ommeren, A., Partial resistance of barley to leaf rust, Puccinia hordei. II. Relationship between field trials, micro plot tests and latent period. Euphytica 24 (1975), 293–303.
25. 25 Zadoks, J.C. (1972) Modern concepts in disease resistance in cereals. The way ahead in plant breeding In Proceedings of Sixth Congress of Eucarpia (Lupton, F.A.G.H. et al. eds.), pp. 89–98, Eucarpia.
26. 26 Villareal, R.L., et al. Some components of slow blasting resistance in rice. Phytopathology 71 (1981), 608–611.
27. 27 Yeh, W.H., Bonman, J.M., Assessment of partial resistance to Pyricularia oryzae in six rice cultivars. Plant Pathol. 35 (1986), 319–323.
28. 28 Savary, S., et al. Peanut rust in West Africa: a new component in a multiple pathosystem. Plant Dis. 72 (1988), 1001–1009.
29. 29 Savary, S., Zadoks, J.C., Analyse des composantes de l'interaction hôte–parasite chez la rouille de l'arachide. I. Définition et mesure des composantes de résistance. Oléagineux 44 (1989), 163–174.
30. 30 Savary, S., Zadoks, J.C., Analyse des composantes de l'interaction hôte–parasite chez la rouille de l'arachide. II. Mesure de la résistance intermédiaire par un essai en micro-parcelles. Oléagineux 44 (1989), 215–224.
31. 31 Sandoval-Islas, J.S., et al. Quantitative resistance and its components in 16 barley cultivars to yellow rust, Puccinia striiformis f. sp. hordei. Euphytica 153 (2007), 295–308.
32. 32 Azzimonti, G., et al. Components of quantitative resistance to leaf rust in wheat cultivars: diversity, variability and specificity. Plant Pathol. 62 (2013), 970–981.
33. 33 Díaz-Lago, J.E., et al. Evaluation of components of partial resistance to oat crown rust using digital image analysis. Plant Dis. 87 (2003), 667–674.
34. 34 Mahlein, A.K., Plant disease detection by imaging sensors – parallels and specific demands for precision agriculture and plant phenotyping. Plant Dis. 100 (2016), 241–251.
35. 35 Green, D.E. II, et al. Components of resistance to Rhizoctonia solani associated with two tall fescue cultivars. Plant Dis. 83 (1999), 834–838.
36. 36 Willocquet, L., et al. Quantification of the components of resistance to rice sheath blight using a detached tiller test under controlled conditions. Plant Dis. 95 (2011), 1507–1515.
37. 37 Burlakoti, R.R., et al. Combining different resistance components enhances resistance to Fusarium head blight in spring wheat. Euphytica 172 (2010), 197–205.
38. 38 Schwanck, A.A., et al. Predicting quantitative host plant resistance against Phoma black stem in sunflower. Plant Pathology 65 (2016), 1366–1379.
39. 39 Das, M.K., et al. Associations and genetics of three components of slow rusting in leaf rust of wheat. Euphytica 68 (1993), 99–109.
40. 40 Herrera-Foessel, S.A., et al. Evaluation of slow rusting resistance components to leaf rust in CIMMYT durum wheats. Euphytica 155 (2007), 361–369.
41. 41 Savary, S., et al. Modelling and mapping potential epidemics of rice diseases globally. Crop Prot. 34 (2012), 6–17.
42. 42 Savary, S., et al. Modelling and mapping potential epidemics of wheat diseases – examples on leaf rust and Septoria tritici blotch using EPIWHEAT. Eur. J. Plant Pathol. 142 (2015), 771–790.
43. 43 Savary, S., Willocquet, L., Simulation modeling in botanical epidemiology and crop loss analysis. Plant Health Instructor, 2014, 10.1094/PHI-A-2014-0314-01 Published online March 14, 2014.
44. 44 van Oijen, M., Selection and use of a mathematical model to evaluate components of resistance to Phytophthora infestans in potato. Neth. J. Plant Pathol. 98 (1992), 192–202.
45. 45 Luo, Y., Zeng, S.M., Simulation studies on epidemics of wheat stripe rust (Puccinia striiformis) on slow-rusting cultivars and analysis of effects of resistance components. Plant Pathol. 44 (1995), 340–349.
46. 46 Rossi, V., et al. A model integrating components of rate-reducing resistance to Cercospora leaf spot in sugar beet. J. Phytopathol. 147 (1999), 339–346.
47. 47 Chenu, K., et al. Simulating the yield impacts of organlevel quantitative trait loci associated with drought response in maize: a ‘gene-to-phenotype’ modeling approach. Genetics 183 (2009), 1507–1523.
48. 48 Messina, C.D., et al. Yield–trait performance landscapes: from theory to application in breeding maize for drought tolerance. J. Exp. Bot. 62 (2011), 855–868.
49. 49 Marcel, T.C., et al. Isolate specificity of quantitative trait loci for partial resistance of barley to Puccinia hordei confirmed in mapping populations and near-isogenic lines. New Phytol. 177 (2008), 743–755.
50. 50 Yuen, J., et al. Calibration and verification of risk algorithms using logistic regression. Eur. J. Plant Pathol. 102 (1996), 847–854.
51. 51 Hughes, G., et al. Decision-making and diagnosis in disease management. Plant Pathol. 48 (1999), 147–153.
52. 52 Yuen, J., Hughes, G., Bayesian analysis of plant disease prediction. Plant Pathol. 51 (2002), 407–412.
53. 53 Madden, L.V., Botanical epidemiology: some key advances and its continuing role in disease management. Eur. J. Plant Pathol. 115 (2006), 3–23.
54. 54 Yuen, J., Deriving decision rules. Plant Health Instructor, 2006, 10.1094/PHI-A-2006-0517-01 Published online May 17, 2006.
55. 55 Yuen, J., Mila, A., Landscape-scale disease risk quantification and prediction. Annu. Rev. Phytopathol. 53 (2015), 471–484.
56. 56 Esker, P.D., et al. Comparison of models for forecasting of Stewart's disease of corn in Iowa. Plant Dis. 90 (2006), 1353–1357.
57. 57 Savary, S., et al. Risk factors for crop health under global change and agricultural shifts: a framework of analyses using rice in tropical and subtropical Asia as a model. Phytopathology 101 (2011), 696–709.
58. 58 Yuen, J.E., Forbes, G.A., Estimating the level of susceptibility to Phytophthora infestans in potato genotypes. Phytopathology 99 (2009), 782–786.
59. 59 Waggoner, P.E., Berger, R.D., Defoliation, disease, and growth. Phytopathology 77 (1987), 393–398.
60. 60 Bergamin Filho, A., Amorim, L., Doenças de Plantas Tropicais: Epidemiologia e Controle Econômico. 1996, Editora Agrônomica Ceres.
61. 61 Srinivasachary, et al. Resistance to rice sheath blight (Rhizoctonia solani Kühn) [(teleomorph: Thanatephorus cucumeris (A.B. Frank) Donk.] disease: current status and perspectives. Euphytica 178 (2011), 1–22.
62. 62 Zadoks, J.C., Schein, R.D., Epidemiology and Plant Disease Management. 1979, Oxford University Press.
63. 63 Ando, K., et al. Manipulation of plant architecture to enhance crop disease control. CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, 2007, CABI, 2 026.
64. 64 Willocquet, L., et al. Susceptibility of rice to sheath blight: an assessment of the diversity of rice germplasm according to genetic groups and morphological traits. Euphytica 183 (2012), 227–241.
65. 65 Andrivon, D., et al. Defining and designing plant architectural ideotypes to control epidemics?. Eur. J. Plant Pathol. 135 (2013), 611–617.
66. 66 Srinivasachary, et al. A strategy to identify sources of quantitative resistance in pathosystems involving disease escape and physiological resistance: the case study of rice sheath blight. Plant Pathol. 62 (2013), 888–899.
67. 67 Burdon, J.J., et al. Guiding deployment of resistance in cereals using evolutionary principles. Evol. Appl. 7 (2014), 609–624.
68. 68 Schlösser, I., et al. Characterization of plant type and epidemiological development in the pathosystem upland rice/rice blast (Pyricularia grisea) by means of multivariate statistical methods. Z. Pflanzenkrank. Pflanzenschutz 107 (2000), 12–32.
69. 69 Arraiano, L.S., et al. Contributions of disease resistance and escape to the control of Septoria tritici blotch of wheat. Plant Pathol. 58 (2009), 910–922.
70. 70 Zhu, H., et al. Does function follow form? Principal QTLs for Fusarium head blight (FHB) resistance are coincident with QTLs for inflorescence traits and plant height in a doubled-haploid population of barley. Theor. Appl. Genet. 99 (1999), 1221–1232.
71. 71 Schwanck, A.A., et al. Effects of plant morphological traits on Phoma black stem in sunflower. Eur. J. Plant Pathol. 145 (2016), 345–361.
72. 72 Zadoks, J.C., The role of epidemiology in modern phytopathology. Phytopathology 64 (1974), 918–923.
73. 73 Andrivon, D., et al. The hard life of Phytophthora infestans: when trade-offs shape evolution in a biotrophic plant pathogen. Plant Pathol. 62:Suppl. 1 (2013), 28–35.
74. 74 Brun, H., et al. Quantitative resistance increases the durability of qualitative resistance to Leptosphaeria maculans in Brassica napus. New Phytol. 185 (2010), 285–299.
75. 75 Quenouille, J., et al. Quantitative trait loci from the host genetic background modulate the durability of a resistance gene: a rational basis for sustainable resistance breeding in plants. Heredity 112 (2014), 579–587.
76. 76 de Wit, C.T., Goudriaan, J.G., Simulation of Ecological Processes. 1978, Pudoc.
77. 77 Meadows, D., Thinking in Systems: A Primer. 2008, Chelsea Green Publishing.
78. 78 Djurle, A., Yuen, J., A simulation model for Septoria nodorum in winter wheat. Agric. Syst. 37 (1991), 193–218.
79. 79 Lannou, C., et al. Host mixture efficacy in disease control: effects of lesion growth analyzed through computer-simulated epidemics. Plant Pathol. 43 (1994), 651–662.
80. 80 Berger, R.D., et al. Lesion expansion as an epidemic component. Phytopathology 87 (1997), 1005–1013.
81. 81 Zadoks, J.C., Systems analysis and the dynamics of epidemics. Phytopathology 61 (1971), 600–610.
82. 82 Forrester, J.W., Industrial Dynamics. 1961, MIT Press.
83. 83 Parlevliet, J.E., Zadoks, J.C., The integrated concept of disease resistance: a new view including horizontal and vertical resistance in plants. Euphytica 26 (1977), 5–21.