Browsing by Subject "Varianzkomponenten"

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Response to modified recurrent full-sib selection in two European F2 maize populations analyzed with quantitative genetic methods
(2006) Flachenecker, Christian; Melchinger, Albrecht E.
Many plant breeding strategies lead to a reduction in the genetic variance of the source population. However, a sufficient genetic variance is essential for the long-term selection response. Hence, the aim of recurrent selection (RS) is a continuous increase in the frequencies of favorable alleles while maintaining genetic variability in the population. Several intrapopulation RS methods have been proposed in maize: e.g., mass selection, half-sib selection, full-sib (FS) selection, S1 selection. Among them, recurrent FS selection is characterized by a short cycle length, complete parental control, and a high selection response. The goal of this thesis was to investigate the changes in the population structure over several cycles of a modified recurrent FS selection program in two European F2 maize populations. In detail, the objectives were to (i) monitor trends across selection cycles in the estimates of population mean, inbreeding coefficients, and variance components, (ii) determine selection response for per se and testcross performance, (iii) compare predicted with realized selection response, (iv) extend the population diallel analysis under full consideration of inbreeding depression due to random genetic drift, (v) separate genetic effects due to selection from those due to random genetic drift, and (vi) investigate the usefulness of best linear unbiased prediction (BLUP) estimates of parents for predicting progeny performance under the recurrent FS selection scheme applied. Four early maturing European flint inbreds were used as parents to produce two F2 populations (A×B and C×D). Both populations were three times intermated by chain crossing to reduce the gametic phase disequilibrium. Starting from the F2Syn3 population obtained in this manner, a modified recurrent FS selection program was conducted over four cycles in population A×B and over seven cycles in population C×D. In each cycle, 144 FS families were tested in field trials and, in parallel, six plants from each FS family were selfed. The selfed ears of the 36 families with the highest selection index (SI = 2 × dry matter content + grain yield) were selected and intermated according to a pseudo-factorial mating scheme. In this mating scheme, the gametic contribution of the best selected FS families is doubled compared with the gametic contribution of the remaining selected FS families. Afterwards, all cycles of both populations were tested in two population diallel analyses in six environments. Based on the known pedigree records, the inbreeding coefficient of each FS family and the coancestry coefficients among them were calculated. Variance components and BLUP values were obtained using phenotypic means and coancestry coefficients. For grain yield, the selection response per cycle, which could be expected after correcting for the effects of random genetic drift, was higher than reported in the literature (14.1% and 8.3% in populations A×B and C×D, respectively). We ascribe the comparatively high selection response mainly to the pseudo-factorial mating scheme. This mating scheme is expected to increase the selection response compared with commonly applied random mating schemes, without a major reduction in the effective population size (Ne). In this study, the expected Ne was 32, suggesting a minor influence of random genetic drift compared with that of selection. This assumption was verified by an extended population diallel analysis, showing that random genetic drift reduced the selection response only by about 1-2% in both populations. In contrast to an estimation of variance components with moment estimators, the REML procedure has no special requirements on the mating scheme and accounts for any relationship among families in a breeding population. As expected from the high Ne applied in our study, we observed only a moderate decrease in additive variance for grain yield and grain moisture in both populations. Nevertheless, the variance components were still associated with high standard errors, which prevented the revealing of trends across cycles. A larger number of test locations and larger population size would reduce the standard errors of variance components at the cost of oversized and expensive field trials. Methods for predicting the performance of progenies are important to optimize RS programs. Due to simplifying assumptions, a prediction with phenotypic means is often inaccurate. An alternative method is BLUP, which was suggested for predicting the performance of untested single-cross hybrids but has not been applied in RS programs. In our study, the prediction of progeny performance based on BLUP was only marginally better than prediction based on the phenotypic mean. However, higher degree of relationship between the entries and lower heritabilities would increase the advantage of BLUP compared with phenotypic means.