The statistical analysis of multi-environment data: Modeling genotype-by-environment interaction and its genetic basis

Frontiers in Physiology

Volumn 4 MAR, Issue , 2013, Pages

  Malosetti, Marcos ^a   Ribaut, Jean Marcel ^b   van Eeuwijk, Fred A ^a  

^a WAGENINGEN UNIVERSITY   (Netherlands)

^b Generation Challenge Programme   (Mexico)

Author keywords

Adaptation; Genotype by environment interaction; Multi environment trials; QTL by environment interaction; QTL mapping methodology; REML

Indexed keywords

NITROGEN;

ARTICLE; CORRELATION ANALYSIS; DROUGHT STRESS; ENVIRONMENTAL FACTOR; FACTORIAL ANALYSIS; GENETIC VARIABILITY; GENOTYPE ENVIRONMENT INTERACTION; MAIZE; MATHEMATICAL ANALYSIS; PLANT BREEDING; PLANT STRESS; PREDICTION; QUANTITATIVE TRAIT LOCUS; REGRESSION ANALYSIS; STATISTICAL ANALYSIS; STATISTICAL MODEL;

EID: 84879467512     PISSN: None     EISSN: 1664042X     Source Type: Journal    
DOI: 10.3389/fphys.2013.00044     Document Type: Article

References (55)

1. Akaike, H. (1974). A new look at the statistical model identification. IEEE Trans. Automat. Contr. 19, 716-723.
2. Basten, C. J., Weir, B. S., and Zeng, Z.-B. (2002). QTL Cartographer, Version 1.16. Department of Statistics, North Carolina State University, Raleigh, NC.
3. Bernardo, R. (2002). Breeding for Quantitative Traits in Plants. Woodbury, MN: Stemma Press.
4. Boer, M. P., Wright, D., Feng, L., Podlich, D. W., Luo, L., Cooper, M., et al. (2007). A mixed-model quantitative trait loci (QTL) analysis for multiple-environment trial data using environmental covariables for QTL-by-environment interactions, with an example in maize. Genetics 177, 1801-1813.
5. Broman, K. W., Wu, H., Sen, Ś., and Churchill, G. A. (2003). R/qtl: QTL mapping in experimental crosses. Bioinformatics 19, 889-890.
6. Cheverud, J. M. (2001). A simple correction for multiple comparisons in interval mapping genome scans. Heredity 87, 52-58.
7. Cooper, M., and Hammer, G. L. (eds.). (1996). Plant Adaptation and Crop Improvement. Wallingford, UK: CAB International.
8. Cullis, B. R., Thomson, F. M., Fisher, J. A., Gilmour, A. R., and Thompson, R. (1996a). The analysis of the NSW wheat variety database. I. Modelling trial error variance. Theor. Appl. Genet. 92, 21-27.
9. Cullis, B. R., Thomson, F. M., Fisher, J. A., Gilmour, A. R., and Thompson, R. (1996b). The analysis of the NSW wheat variety database. II. Variance component estimation. Theor. Appl. Genet. 92, 28-39.
10. Denis, J. B. (1988). Two-way analysis using covariables. Statistics 19, 123-132.
11. Falconer, D. S., and Mackay, T. F. C. (1996). Introduction to Quantitative Genetics. 4th Edn. Harlow: Longman.
12. Finlay, K. W., and Wilkinson, G. N. (1963). The analysis of adaptation in a plant-breeding programme. Aust. J. Agric. Res. 14, 742-754.
13. Gabriel, K. (1978). Least squares approximation of matrices by additive and multiplicative models. J. R. Stat. Soc. B 40, 186-196.
14. Galwey, N. W. (2006). Introduction to Mixed Modeling: Beyond Regression and Analysis of Variance. Chichester: John Wiley and Sons Ltd.
15. Gauch, H. G. (1988). Model selection and validation for yield trials with interaction. Biometrics 44, 705-715.
16. Gilmour, A. R., Cullis, B. R., and Verbyla, A. P. (1997). Accounting for natural and extraneous variation in the analysis of field experiments. J. Agric. Biol. Environ. Stat. 2, 269-293.
17. Gollob, H. (1968). A statistical model which combines features of factor analysis and analysis of variance techniques. Psychometrika 33, 73-115.
18. Graffelman, J., and van Eeuwijk, F. A. (2005). Calibration of multivariate scatter plots for exploratory analysis of relations within and between sets of variables in genomic research. Biom. J. 47, 863-879.
19. Griffiths, A. J. F., Miller, J. H., Suzuki, D. T., Lewontin, R. C., and Gelbart, W. M. (1996). An Introduction to Genetic Analysis. New York, NY: WH Freeman and Company.
20. Haley, C. S., and Knott, S. A. (1992). A simple regression method for mapping quantitative trait loci in line crosses using flanking markers. Heredity 69, 315-324.
21. Huang, X., Paulo, M. J., Boer, M., Effgen, S., Keizer, P., Koornneef, M., et al. (2011). Analysis of natural allelic variation in Arabidopsis using a multiparent recombinant inbred line population. Proc. Natl. Acad. Sci. U.S.A. 108, 4488-4493.
22. Jansen, R. C., and Stam, P. (1994). High resolution of quantitative traits into multiple loci via interval mapping. Genetics 136, 1447-1455.
23. Jiang, C., and Zeng, Z.-B. (1995). Multiple trait analysis of genetic mapping for quantitative trait loci. Genetics 140, 1111-1127.
24. Jiang, C. J., and Zeng, Z. B. (1997). Mapping quantitative trait loci with dominant and missing markers in various crosses from two inbred lines. Genetica 101, 47-58.
25. Kang, M. S., and Gauch, H. G. (1996). Genotype-by-Environment Interaction. Boca Raton, FL: CRC Press Inc.
26. Li, J., and Ji, L. (2005). Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix. Heredity 95, 221-227.
27. Lynch, M., and Walsh, B. (1998). Genetics and Analysis of Quantitative Traits. Sunderland, MA: Sinauer Associates Inc.
28. Malosetti, M., van der Linden, C. G., Vosman, B., and van Eeuwijk, F. A. (2007). A mixed-model approach to association mapping using pedigree information with an illustration of resistance to Phytophthora infestans in potato. Genetics 175, 879-889.
29. Malosetti, M., Voltas, J., Romagosa, I., Ullrich, S. E., and van Eeuwijk, F. A. (2004). Mixed models including environmental covariables for studying QTL by environment interaction. Euphytica 137, 139-145.
30. Mandel, J. (1969). The partitioning of interaction in analysis of variance. J. Res. Natl. Bur. Stand. Math. Sci. 73B, 309-328.
31. Martínez, O., and Curnow, R. N. (1992). Estimating the locations and the sizes of the effects of quantitative trait loci using flanking markers. Theor. Appl. Genet. 85, 480-488.
32. Mathews, K., Malosetti, M., Chapman, S., McIntyre, L., Reynolds, M., Shorter, R., et al. (2008). Multi-environment QTL mixed models for drought stress adaptation in wheat. Theor. Appl. Genet. 117, 1077-1091.
33. Mohring, J., and Piepho, H. P. (2009). Comparison of weighting in two-stage analysis of plant breeding trials. Crop Sci. 49, 1977-1988.
34. Pastina, M. M., Malosetti, M., Gazaffi, R., Mollinari, M., Margarido, G. R., Oliveira, K. M., et al. (2012). A mixed model QTL analysis for sugarcane multiple-harvest-location trial data. Theor. Appl. Genet. 124, 835-849.
35. Patterson, H. D., and Thompson, R. (1971). Recovery of inter-block information when block sizes are unequal. Biometrika 58, 545-554.
36. Payne, R. W., Murray, D. A., Harding, S. A., Baird, D. B., Soutar, D. M., and Lane, P. (2007). GenStat for Windows, 10th Edition Introduction. Hertfordshire, UK: VSN International.
37. Przystalski, M., Osman, A., Thiemt, E. M., Rolland, B., Ericson, L., østerga, H., et al. (2008). Comparing the performance of cereal varieties in organic and non-organic cropping systems in different European countries. Euphytica 163, 417-433.
38. Ribaut, J.-M., Hoisington, D. A., Deutsch, J. A., Jiang, C., and Gonzalez de Leon, D. (1996). Identification of quantitative trait loci under drought conditions in tropical maize. 1. Flowering parameters and the anthesis-silking interval. Theor. Appl. Genet. 92, 905-914.
39. Ribaut, J.-M., Jiang, C., Gonzalez de Leon, D., Edmeades, G. O., and Hoisington, D. A. (1997). Identification of quantitative trait loci under drought conditions in tropical maize. 2. Yield components and marker-assisted selection strategies. Theor. Appl. Genet. 94, 887-896.
40. Sabadin, P., Malosetti, M., Boer, M., Tardin, F., Santos, F., Guimarães, C., et al. (2012). Studying the genetic basis of drought tolerance in sorghum by managed stress trials and adjustments for phenological and plant height differences. Theor. Appl. Genet. 124, 1389-1402.
41. Servin, B., Dillmann, C., Decoux, G., and Hospital, F. (2002). MDM: a program to compute fully informative genotype frequencies in complex breeding schemes. J. Hered. 93, 227-228.
42. Smith, A. B., Cullis, B. R., and Thompson, R. (2005). The analysis of crop cultivar breeding and evaluation trials: an overview of current mixed model approaches. J. Agric. Sci. 143, 449-462.
43. van Eeuwijk, F. A. (1995). Linear and bilinear models for the analysis of multi-environment trials: I. An inventory of models. Euphytica 84, 1-7.
44. van Eeuwijk, F. A. (2006). "Genotype by environment interaction: basics and beyond," in Plant Breeding: The Arnell Hallauer International Symposium, eds K. Lamkey and M. Lee (Oxford, UK: Blackwell Publishing), 155-170.
45. van Eeuwijk, F. A., Bink, M. C. A. M., Chenu, K., and Chapman, S. C. (2010). Detection and use of QTL for complex traits in multiple environments. Curr. Opin. Plant Biol. 13, 193-205.
46. van Eeuwijk, F. A., Denis, J. B., and Kang, M. S. (1996). "Incorporating additional information on genotypes and environments in models for two-way genotype by environment tables," in Genotype-by-Environment Interaction, eds M. S. Kang and H. G. Gauch (Boca Raton, FL: CRC Press Inc.), 15-50.
47. van Eeuwijk, F. A., Malosetti, M., and Boer, M. P. (2007). "Modeling the genetic basis of response curves underlying genotype x environment interaction," in Scale and Complexity in Plant Systems Research. Gene-Plant-Crop Relations, eds J. H. J. Spiertz, P. C. Struik, and H. H. van Laar (Dordrecht: Springer), 115-126.
48. Verbeke, G., and Molenberghs, G. (2000). Linear Mixed Models for Longitudinal Data. New York, NY: Springer-Verlag.
49. Voltas, J., van Eeuwijk, F. A., Araus, J. L., and Romagosa, I. (1999a). Integrating statistical and ecophysiological analysis of genotype by environment interaction for grain filling of barley in Mediterranean areas. II. Grain growth. Field Crops Res. 62, 75-84.
50. Voltas, J., van Eeuwijk, F. A., Sombrero, A., Lafarga, A., Igartua, E., and Romagosa, I. (1999b). Integrating statistical and ecophysiological analysis of genotype by environment interaction for grain filling of barley in Mediterranean areas. I. Individual grain weight. Field Crops Res. 62, 63-74.
51. Voltas, J., van Eeuwijk, F., Igartua, E., del Moral, L. G., Molina-Cano, J. L., and Romagosa, I. (2002). "Genotype by environment interaction and adaptation in barley breeding: basic concepts and methods of analysis," in Barley Science: Recent Advances from Molecular Biology to Agronomy of Yield and Quality, ed G. Slafer (Binghampton, NY: Food Products Press), 205-241.
52. VSN International. (2012). GenStat for Windows, 15th Edn. Hemel Hempstead: VSN International. Web page: GenStat.co.uk
53. Welham, S. J., Beverley, J. G., Smith, A. B., Thompson, R., and Cullis, B. R. (2010). A Comparison of analysis methods for late-stage variety evaluation trials. Aust. N.Z. J. Stat. 52, 125-149.
54. Yan, W., Hunt, L. A., Sheng, Q., and Szlavnics, Z. (2000). Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Sci. 40, 597-605.
55. Zeng, Z. B. (1994). Precision mapping of quantitative trait loci. Genetics 136, 1457-1468.