Predicting progeny means from quantitative genetic parameters of parents: models and their use for winter rye
Wiesław Mądry
wieslaw_madry@sggw.edu.pl`Katedra Biometrii SGGW w Warszawie (Poland)
Tadeusz Śmiałowski
Zakład Oceny Jakości i Metod Hodowli Zbóż, IHAR Oddział w Krakowie (Poland)
Krzysztof Ukalski
Katedra Biometrii SGGW w Warszawie (Poland)
Abstract
Experimental evaluation of the means for agricultural traits in a great number of F1 progenies (as hybrids or segregating populations) and in inbred generations of F1 hybrids is expensive and time-consuming. Then, the progeny means should be predicted using statistical models based on genetic parameters of parents, derived from genetic (molecular markers) and phenotypic parents per se or their offspring data. In the paper, statistical (regression) prediction models involving the estimators of quantitative genetic parameters of parents are presented. The application and usefulness of these models are shown using as an example 7 agronomic characters of 27 F1 winter rye progeny populations obtained in factorial mating design between 9 population varieties (females) and 3 testers (male populations). Two types of models were considered. Models representing the first type include either a mid-parent value of the predicted character only as a predictor variable or both a mid-parent value and parental genetic distance (Mahalanobis distance, D2, of characters studied or absolute difference between parents for the traits studied, |D|) as two predictor variables. Two of the models representing the second type are similar to those of the first type. One of them is based on GCA effects of parents only, whereas the other includes both GCA effects and parental genetic distance. In the studies on winter rye the largest accuracy in predicting progeny means using the model based on the mid-parent value was found for two traits characterized by a relatively larger variation of both parents and F1 progeny families, and their whose performance was affected predominantly by genetic additive effects. The model based on GCA effects of parents was much more efficient for all characters than the other one. Both genetic distances of parents, incorporated into each of the reference models as the additional predictor variables, weakly increased the efficiency of predicting means for F1 winter rye progeny populations.
Keywords:
factorial mating design, Mahalanobis’ distance, GCA effects, mid-parent value, predicting means of F1 progeny populations, regression models for predicting, winter ryeReferences
Ajmone Marsan P., Castiglioni P., Fusari F., Kuiper M., Motto M. 1998. Genetic diversity and its relationship to hybrid performance in maize as revealed by RFLP and AFLP markers. Theor. Appl. Genet. 96: 219 — 227.
DOI: https://doi.org/10.1007/s001220050730
Google Scholar
Argillier O., Méchin V., Barrière Y. 2000. Inbred line evaluation and breeding for igestibility-related traits in forage maize. Crop Sci. 40: 1596 — 1600.
DOI: https://doi.org/10.2135/cropsci2000.4061596x
Google Scholar
Bains, K. S., Sood K. C. 1984. Resolution of genetic divergence for choice of parents in soybean breeding. Crop Improv. 11: 20 — 24.
Google Scholar
Balzarini M. 2002. Applications of mixed models in plant breeding. In: M. S. Kang (Ed), Quantitative Genetics, Genomics and Plant Breeding, CAB International Wallingford, UK: 353 — 363.
DOI: https://doi.org/10.1079/9780851996011.0353
Google Scholar
Beattie A. D., Michaels T. E., Pauls K. P. 2003. Predicting progeny performance in common bean (Phaseolus vulgaris L.) using molecular marker-based cluster analysis. Genome 46: 259 — 267.
DOI: https://doi.org/10.1139/g03-002
Google Scholar
Bednarek P. T., Chwedorzewska K., Króliczak., Puchalski J., Zawada M. 1999. Wykorzystanie markerów genetycznych typu ALFP do badań zmienności genetycznej linii wsobnych żyta. Biul. IHAR 211: 219 — 228.
Google Scholar
Bernardo R. 1995. Genetic models for predicting maize single-cross performance in unbalanced yield trial data. Crop Sci. 35: 141–147.
DOI: https://doi.org/10.2135/cropsci1995.0011183X003500010026x
Google Scholar
Bhatt G. M. 1973. Comparison of various methods of selecting parents for hybridization in common bread wheat (Triticum aestivum L.). Aust. J. Agric. Res. 24: 457 — 464.
DOI: https://doi.org/10.1071/AR9730457
Google Scholar
Bohn M., Utz H. F., Melchinger A. E. 1999. Genetic similarities among winter wheat cultivars determined on the basis of RFLPs, AFLPs, and SSRs and their use for predicting progeny variance. Crop Sci. 39: 228 — 237.
DOI: https://doi.org/10.2135/cropsci1999.0011183X003900010035x
Google Scholar
Camussi A., Ottaviano E., Caliński T., Kaczmarek Z. 1985. Genetic distances based on quantitative traits. Genetics 111: 945 — 962.
DOI: https://doi.org/10.1093/genetics/111.4.945
Google Scholar
Charcosset A., Bonnisseau B., Touchebeuf O., Burstin J., Dubreuil P., Barrière Y., Gallais A., Denis J. B. 1998. Prediction of maize hybrid silage performance using marker data: comparison of several models for specific combining ability. Crop Sci. 38: 38 — 44.
DOI: https://doi.org/10.2135/cropsci1998.0011183X003800010007x
Google Scholar
Charcosset A., Denis J. B., Lefort-Buson M., Gallais A. 1993. Modelling interaction from top-cross data and prediction of F1 hybrid value. Agronomie 13: 597 — 608.
DOI: https://doi.org/10.1051/agro:19930704
Google Scholar
Charcosset A., Essioux L. 1994. The effect of population structure on the relationship between heterosis and heterozygosity at marker loci. Theor. Appl. Genet. 89: 336 — 343.
DOI: https://doi.org/10.1007/BF00225164
Google Scholar
Charcosset A., Lefort-Buson M., Gallais A. 1991. Relationship between heterosis and heterozygosity at marker loci: a theoretical computation. Theor. Appl. Genet. 81: 571 — 575.
DOI: https://doi.org/10.1007/BF00226720
Google Scholar
Charcosset A., Lefort-Buson M., Gallais A. 1990. Use of top-cross design for predicting performance of maize single cross hybrid. Maydica 35: 23 — 27.
Google Scholar
Corbellini M., Perenzin M., Accerbi M., Vaccino P., Borghi B. 2002. Genetic diversity in bread wheat, as revealed by coefficient of parentage and molecular markers, and its relationship to hybrid performance. Euphytica 123: 273 — 285.
DOI: https://doi.org/10.1023/A:1014946018765
Google Scholar
Dias L. A. S., Picoli E. A. T., Rocha R. B., Alfenas A. C. 2004. A priori choice of hybrid parents in plants. Genet. Mol. Res. 3: 356 — 368.
Google Scholar
Falconer D. S., Mackey T. F. 1996. Introduction to quantitative genetics. Longman Group Ltd, Londyn.
Google Scholar
Geleta L. F., Labuschagne M. T., Viljoen C. D. 2004. Relationship between heterosis and genetic distance based on morphological traits and AFLP markers in pepper. Plant Breeding 123: 467 — 473.
DOI: https://doi.org/10.1111/j.1439-0523.2004.01017.x
Google Scholar
Gopal J., Minocha J. L. 1997. Genetic divergence for cross prediction in potato. Euphytica 97: 269 — 275.
DOI: https://doi.org/10.1023/A:1003076207221
Google Scholar
Gopal J. 1998. Identification of superior parents and crosses in potato breeding programmes. Theor. Appl. Genet. 96: 287 — 293.
DOI: https://doi.org/10.1007/s001220050738
Google Scholar
Gumber R. K., Schill B., Link W., Kittlitz E., Melchinger A. E. 1999. Mean, genetic variance, and usefulness of selfing progenies from intra- and inter-pool crosses in faba beans (Vicia faba L.) and their prediction from parental parameters. Theor. Appl. Genet. 98: 569 — 580.
DOI: https://doi.org/10.1007/s001220051106
Google Scholar
Kaczmarek J., Bujak H., Kadłubiec W. 2001. Ocena podobieństwa linii wsobnych żyta ozimego na podstawie analizy wybranych cech. Biul. IHAR 218/219: 379 — 387.
Google Scholar
Łuczkiewicz T., Kaczmarek Z. 2004. The influence of morphological differences between sunflower inbred lines on their SCA effects for yield components. J. Appl. Genet. 45: 175 — 182.
Google Scholar
Maris B. 1989. Analysis of an incomplete diallel cross among three ssp. tuberosum varieties and seven long day adapted ssp. andigena clones of the potato (Solanum tuberosum L.). Euphytica 41: 163 — 182.
DOI: https://doi.org/10.1007/BF00022425
Google Scholar
Mather K., Jinks J. L.1982. Biometrical genetics. Chapman and Hall, Londyn.
DOI: https://doi.org/10.1007/978-1-4899-3406-2
Google Scholar
Mądry W., Krajewski P., Pluta S., Żurawicz E. 2004. Wielocechowa analiza wartości hodowlanej i zróżnicowania genetycznego odmian porzeczki czarnej (Ribes nigrum L.) na podstawie efektów ogólnej zdolności kombinacyjnej. Acta Scient. Polon. Hortorum. Cultus 3: 93 — 109.
Google Scholar
Melchinger A. E., Gumber R. K., Leipert R. B., Vuylsteke M., Kuiper M. 1998. Prediction of testcross means and variances among F3 progenies of F1 crosses from testcross means and genetic distances of their parents in maize. Theor. Appl. Genet. 96: 503 — 512.
DOI: https://doi.org/10.1007/s001220050767
Google Scholar
Menkir A., Ayodele M. 2005. Genetic analysis of resistance to gray leaf spot of midaltitude maize inbred lines. Crop Sci. 45: 163 — 170.
DOI: https://doi.org/10.2135/cropsci2005.0163a
Google Scholar
Oettler G., Burger H., Melchinger A.E. 2003. Heterosis and combining ability for grain yield and other agronomic traits in winter triticale. Plant Breeding 122: 318 — 321.
DOI: https://doi.org/10.1046/j.1439-0523.2003.00877.x
Google Scholar
Oury F. X., Brabant P., Bérard P., Pluchard P. 2000. Predicting hybrid value in bread wheat: biometric modelling based on a ”top-cross" design. Theor. Appl. Genet. 100: 96 — 104.
DOI: https://doi.org/10.1007/PL00002905
Google Scholar
Reif J. C., Melchinger A. E., Xia X. C., Warburton M. L., Hoisington D. A., Vasal S. K., Beck D., Bohn M., Frisch M. 2003. Use of SSRs for establishing heterotic groups in subtropical maize. Theor. Appl. Genet. 107: 947 — 957.
DOI: https://doi.org/10.1007/s00122-003-1333-x
Google Scholar
Riday H., Brummer E. C., Campbell T. A, Luth D., Cazcarro P.M. 2003. Comparisons of genetic and morphological distance with heterosis between Medicago sativa subsp. sativa and subsp. falcata. Euphytica 131: 37 — 45.
DOI: https://doi.org/10.1023/A:1023050126901
Google Scholar
Riday H., Brummer E. C. 2005. Heterosis in a broad range of alfalfa germplasm Crop Sci. 45: 8 — 17.
DOI: https://doi.org/10.2135/cropsci2005.0008a
Google Scholar
Rodriguez-Burruezo A., Prohens J., Nuez F. 2003. Performance of hybrid segregating populations of pepino (Solanum mulic × atum) and its relation to genetic distance among parents. J. Hort. Sci. Biot. 78: 911 — 918.
DOI: https://doi.org/10.1080/14620316.2003.11511718
Google Scholar
SAS/STAT User's Guide, Version 8.2. 2002. SAS Institute, Cary NC.
Google Scholar
Schut J. W., Dourleijn C. J. 2000. Prediction of barley progeny performance in the presence of genotype-environment interaction. Plant Breeding 119: 47 — 50.
DOI: https://doi.org/10.1046/j.1439-0523.2000.00445.x
Google Scholar
Smith J. S. C. and Smith O. S.. 1989. The description and assessment of distances between inbred lines of maize: I. The use of morphological traits as descriptors. Maydica 34: 141 — 150.
Google Scholar
Śmiałowski T., Węgrzyn S. 2001. Addytywno-dominujący sposób działania genów odpowiedzialnych za dziedziczenie różnych cech rolniczych u żyta ozimego. Pam. Puł. 128: 247 — 256.
Google Scholar
Śmiałowski T., Węgrzyn S. 2003. Genetyczno-statystyczne parametry dziedziczenia cech użytkowych żyta ozimego (Secale cereale L.). Biul. IHAR 230: 205 — 214.
Google Scholar
Utz H. F., Bohn M., Melchinger A. E. 2001. Predicting progeny means and variances of winter wheat crosses from phenotypic values of their parents. Crop Sci. 41: 1470 — 1478.
DOI: https://doi.org/10.2135/cropsci2001.4151470x
Google Scholar
Van Esbroeck G. A., Bowman D. T., May O. L., Calhoun D. S. 1999. Genetic similarity indices for ancestral cotton cultivars and their impact on genetic diversity estimates of modern cultivars. Crop Sci. 39:323–328.
DOI: https://doi.org/10.2135/cropsci1999.0011183X003900020003x
Google Scholar
Vuylsteke M., Kuiper M., Stam P. 2000. Chromosomal regions involved in hybrid performance and heterosis: their AFLP®-based identification and practical use in prediction models. Heredity 85: 208 — 218.
DOI: https://doi.org/10.1046/j.1365-2540.2000.00747.x
Google Scholar
Yan W., Rajcan I. 2003. Prediction of cultivar performance based on single vs. multiple year trials. Crop Sci. 43: 549 — 555.
DOI: https://doi.org/10.2135/cropsci2003.5490
Google Scholar
Authors
Tadeusz ŚmiałowskiZakład Oceny Jakości i Metod Hodowli Zbóż, IHAR Oddział w Krakowie Poland
Authors
Krzysztof UkalskiKatedra Biometrii SGGW w Warszawie Poland
Statistics
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