A comparative study on segregation analysis and QTL mapping of quantitative traits in plants—with a case in soybean

Abstract

Two approaches of genetic analysis of quantitative traits were compared with a case study on soybean. One approach was the segregation analysis developed by Gai et al. (2003), which utilized information from individuals of one or multiple segregation populations as well as that from parents based on the principles of the major-gene plus polygene inheritance model, mixture distribution, joint maximum-likelihood function, IECM (Iterated Expectation and Conditional Maximization) algorithm, and Akaike’s information criterion and goodness of fit tests. Another approach was quantitative trait locus (QTL) mapping with molecular markers. A recombinant inbred line (RIL) population with 201 families derived from (Kefeng No.1x1138-2) F_2:7:10 along with their parents were tested in a randomized block design experiment. The 171 RFLP, 60 SSR, and 79 AFLP molecular markers were used to mark the 201 families. The data of nine traits, i.e., number of days to flowering, number of days to maturity, plant height, number of nodes on main stem, number of pods per node, 100-seed weight, protein content, oil content, and plot yield, were analyzed with the segregation analysis procedure of RIL population with parents (Gai et al., 2003; Zhang and Gai, 2000; Zhang et al., 2001) to detect their genetic system, and those along with the molecular marker data were analyzed with WinQTL Cartographer (Basten et al., 1999; Zeng, 1993, 1994) to detect their QTL system. The results showed that both procedures could detect the main major genes or QTLs, and therefore, could be used as a mutual check and supplement. From the results that most of the traits were mainly controlled by three or four QTLs, it was impressed that the segregation analysis procedure of four major-gene plus polygene mixed inheritance model should be developed to fit the requirements. The results also showed that the QTLs of the involved traits concentrated on several linkage groups, such as C2, B1, F1, M, and N. Finally, the results showed that the experimental sample was not necessarily coincident with the theoretical population according to equality test, symmetry test, and representation test, and therefore, the sample should be checked, tested and then adjusted to fit the theoretical requirements through deleting the extra-biased families and markers.

Keywords

inheritance of quantitative trait / segregation analysis / QTL mapping / soybean

References

[[1]] Akaike H (1977). On entropy maximum principle. In: Krishnaiah P R, ed. Applications of Statistics. Amsterdam: North-Holland Publishing Company, 27-41

[[2]] Basten C J, Weir B S, Zeng Z B (1999). QTL Cartographer. Version 1.13. Raleigh (NC): Department of Statistics, North Carolina State University

[[3]] Choi K (1969). Estimators for the parameters of distributions. Ann Inst Statist Math, 21: 107-116

[[4]] Cockerham C C (1954). An extension of the concept of partitioning hereditary variance for analysis of covariance among relatives when epistasis is present. Genetics, 39: 859-882

[[5]] Comstock R C, Robinson H F (1948). The component of quantitative variance in populations. Biometrics, 4: 254-266

[[6]] Cregan P B, Jarvik T, Bush A L, Shoemaker R C, Lark K G, Kahler A L, Kaya N, Van Toai T T, Lohnes D G, Chung J, Specht A L (1999). An integrated genetic linkage map of the soybean genome. Crop Sci, 39: 1464-1490

[[7]] Dempster A P, Laird N M, Robin D B (1977). Maximum likelihood from incomplete data via the EM algorithm. J R Statist Soc B, 39: 1-38

[[8]] Dick N P, Bowden D C (1973). Maximum likelihood estimation for mixtures of two normal distributions. Biometrics, 29: 781-790

[[9]] Elkind Y, Cahaner A (1986). A mixed model for the effects of single gene, polygenes and their interaction on quantitative traits. 1. The model and experimental design. Theor Appl Genet, 72: 377-383

[[10]] Elkind Y, Cahaner A (1990). A mixed model for the effects of single gene, polygenes and their interaction on quantitative traits. 2. The effects of the major gene and polygenes on tomato fruit softness. Heredity, 64: 205-213

[[11]] Fisher R A (1918). The correlations between relatives on the supposition of Mendelian inheritance. Trans Roy Soc Edin, 52: 399-433

[[12]] Gai J Y, Wang J (1998). Identification and estimation of a QTL model and its effects. Theor Appl Genet, 97(7): 1162-1168

[[13]] Gai J Y, Zhang Y, Wang J (2000). A joint analysis of multiple generations for QTL models extended to mixed two major genes plus polygene. Acta Agronomica Sinica, 26(4): 385-391 (in Chinese)

[[14]] Gai J Y, Zhang Y, Wang J (2003). Genetic System of Quantitative Traits in Plants. Beijing: Academic Press (in Chinese)

[[15]] Gai J Y (2006). Segregation analysis on genetic system of quantitative traits in plants. Front Biol China, 1: 85-92

[[16]] Hasselblad V (1966). Estimation of parameters for a mixture of normal distributions. Technometrics, 8: 431-444

[[17]] Jiang C, Pan X, Gu M (1994). The use of mixture models to detect effects of major genes on quantitative characters in plant breeding experiment. Genetics, 136: 383-394

[[18]] Kempthorne O (1957). An Introduction to Genetics Statistics. New York: Wiley

[[19]] Lander E S, Bostein D R (1989). Mapping Mendelian factors underlying quantitative traits using RFLP linkage map. Genetics, 121: 185-189

[[20]] Lander E S, Green P, Abrahamson J, Barlow A, Daly M J, Lincoln S E, Newburg L (1987). Mapmaker: An interactive computer package for constructing genetic linkage maps of experimental and natural populations. Genomics, 1: 174-181

[[21]] Liu C, Rubin D R (1994). The ECME algorithm: A simple extension of ECM with faster monotone convergence. Biometrika, 81(4): 633-648

[[22]] Mather K (1949). Biometrical Genetics. London: Methum

[[23]] Mather K, Jinks J L (1989). Biometrical Genetics. 3rd ed. London: Chapman and Hall Tanksley S D, Nelson J C (1996). Advanced backcross QTL analysis: A method for the simultaneous discovery and transfer of valuable QTLs from unadapted germplasm into elite breeding lines. Theor Appl Genet, 92: 191-203

[[24]] Wang J, Gai J Y (1997a). Identification of major-polygene mixed inheritance model of quantitative traits from F2 population. Acta Genetica Sinica, 24(3): 181-190 (in Chinese)

[[25]] Wang J, Gai J Y (1997b). EM algorithm in the analysis of major gene and polygene mixed inheritance. Journal of Biomathmatics, 12(5): 540-548 (in Chinese)

[[26]] Wang J, Gai J Y (1998). Identification of major gene and polygene mixed inheritance model of quantitative traits by using joint analysis of P1, F1, P2, F2 and F2:3. Acta Agronomica Sinica, 24(6): 651-659 (in Chinese)

[[27]] Wang Y (2001). Establishment and adjustment of RIL population and its application to map construction, mapping genes resistant to SMV, and QTL analysis of agronomic and quality traits in soybeans. Dissertation for the Doctoral Degree. Nanjing: Nanjing Agricultural University (in Chinese)

[[28]] Zeng Z B (1993). Theoretical basis of separation of multiple linked gene effects on mapping quantitative trait loci. Proc Natl Sci USA, 90: 10972-10976

[[29]] Zeng Z B (1994). Precision mapping of quantitative trait loci. Genetics, 136: 1457-1468

[[30]] Wu X L, He C Y, Wang Y J, Chen S Y, Gai J Y, Wang S C (2001). Construction and analysis of a genetic linkage map of soybean. Acta Genetica Sinica, 28(11): 1051-1061 (in Chinese)

[[31]] Zhang Y, Gai J Y (2000a). Identification of mixed major-gene and polygene inheritance model of quantitative traits by using DH or RIL population. Acta Genetica Sinica, 27(7): 634-640 (in Chinese)

[[32]] Zhang Y, Gai J Y (2000b). The IECM algorithm for estimation of component distribution parameters in segregating analysis of quantitative traits. Acta Agronomica Sinica, 26(6): 699-706 (in Chinese)

[[33]] Zhang Y, Gai J Y, Qi C (2001a). The precision of segregating analysis of quantitative trait and its improving methods. Acta Agronomica Sinica, 27(6): 787-793 (in Chinese)

[[34]] Zhang Y, Gai J Y, Wang Y (2001b). An expansion of joint segregation analysis of quantitative trait for using P1, P2 and DH or RIL populations. Hereditas (Beijing), 23(5): 467-470 (in Chinese)

Acknowledgements

The project was supported by the National Natural Science Foundation of China (No. 30490250), the National Key Basic Research Program (No. 2002CB111304, No. 2004CB7206. No. 2006CB101708), the National “863” Program (No. 2002AA211052, 2006AA100104) and the Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT).

RIGHTS & PERMISSIONS

2007 Higher Education Press