The proportion of genetic deviates in the tails of a normal population

Robson, D. S.; Powers, LeRoy; Urquhart, N. Scott

doi:10.1007/bf00329530

Cited by 16 publications

(11 citation statements)

References 2 publications

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“…In the context of multistage selection, this leads to the erroneous conclusion that selecting fewer entries in the PYT increases genetic gain, when in fact, the more entries that are selected in the PYT, the greater the probability of finding a superior entry in advanced testing. To address this shortcoming, several groups have instead optimized the probability of selecting an entry with genotypic value greater than some threshold (Robson et al, 1967;Johnson, 1989;Knapp, 1998;Longin et al, 2006), but this metric has the drawback of requiring the specification of a threshold. We propose instead to optimize the expected maximum genotypic value of the selected entries, denoted by R max , which is readily interpreted as a measure of genetic gain.…”

Section: Introductionmentioning

confidence: 99%

Optimal Design of Preliminary Yield Trials with Genome‐Wide Markers

Endelman¹,

et al. 2014

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Previous research on genomic selection (GS) has focused on predicting unphenotyped lines. Genomic selection can also improve the accuracy of phenotyped lines at low heritability, e.g., in a preliminary yield trial (PYT). Our first objective was to estimate this effect within a biparental family, using multilocation yield data for barley (Hordeum vulgare L.) and maize (Zea mays L.). We found that accuracy increased with training population size and was higher with an unbalanced design spread across multiple locations than when testing all entries in one location. The latter phenomenon illustrates that when seed is limited, genome‐wide markers enable broader sampling from the target population of environments. Our second objective was to explore the optimum allocation of resources at a fixed budget. When PYT selections are advanced for further testing, we propose a new metric for optimizing genetic gain: Rmax, the expected maximum genotypic value of the selections. For budgets up to 250 yield plot equivalents per family, the optimal design did not involve genotyping more progeny than were phenotyped, even when the cost of creating and genotyping each line was only 0.25 the cost of one yield plot unit (YPU). At a genotyping cost of 0.25 YPU, GS offered up to a 5% increase in genetic gain compared with phenotypic selection. To increase genetic gains further, the training population must be expanded beyond the full‐sib family under selection, using close relatives of the parents as a source of prediction accuracy.

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Section: Introductionmentioning

confidence: 99%

Optimal Design of Preliminary Yield Trials with Genome‐Wide Markers

Endelman¹,

et al. 2014

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“…These can be estimated from the observed phenotypic distributions by the method of Robson, Powers and Urquhart (1967) but we prefer to await the outcome of current experiments on a replicated full diallel set of second cycle hybrids.…”

Section: And Conclusionmentioning

confidence: 99%

Predicting and observing the properties of second cycle hybrids using basic generations and inbred line × F1 crosses

1985

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The phenotypic and genotypic properties of second cycle hybrids are predicted from the means and variances of the F2 generation of two crosses between pairs of inbred varieties of Nicotiana rustica (V1 x V5 and V2 x V12). The predicted properties are compared with the observed properties of the second cycle hybrids generated by crossing the first cycle recombinant inbred lines with the F1 of the original cross (the L3 generation of an inbred line triple test cross) which, in the absence of a linkage disequilibrium, are identical with the second cycle hybrids produced as a diallel set of crosses among the first cycle inbred lines. In the presence of a linkage disequilibrium the diallef set of crosses has a smaller linkage bias than the inbred line x F1 crosses.The agreement between the predicted and observed phenotypic properties of the second cycle hybrids is good over a wide range of characters in both crosses. The overall correlations between the observed and expected proportions are O81 and O88 for the V1 x V5 and V2x V12 crosses, respectively. Furthermore, the genotypic predictions show that only few of the second cycle hybrids and second cycle inbred lines will be superior to the best first cycle inbred lines which were themselves superior to their own better parents and their heterotic F1's.Genetical explanations of the origins of the superior derivatives of an initial cross are explored using a development of the standard notation of Mather and Jinks (1982).

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“…Although genetic differences in phenotype potential exist among individuals, environmental effects make it difficult to identify genetically superior individuals. The heritabilities of quantitative traits tend to be low (Robson et al, 1967;Johnson, 1989).…”

Section: Literature Reviewmentioning

confidence: 99%

“…The plant breeder intermates plants with different genetic backgrounds and attempts to select progeny with superior performance. A difficulty for plant breeders is the accurate identification of the superior offspring for some traits (Robson et al, 1967;Johnson, 1989). Many traits of importance, such as grain yield, are quantitatively inherited (Hallauer and Miranda, 1981).…”

Section: Introductionmentioning

confidence: 99%

“…The plant breeder must rely on phenotypic measurements to determine the genotype of an individual (Robson et al, 1967). Phenotypic evaluations of individuals for quantitative traits typically display non-discrete distributions that are the result of multiple genetic factors and enviroimiental effects that render the phenotype a weak predictor of the genotype (Churchill and Doerge,.…”

Section: Introductionmentioning

confidence: 99%

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Selection for soybean seed yield with molecular markers

Byrum

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This manuscript has been reproduced from the microfilm master. UMI films the text directly firom the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type of computer printer.The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedthrough, substandard margins, and improper alignment can adversely affect reproduction.In the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion.Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand comer and continuing from left to right in equal sections with small overiaps. Each original is also photographed in one exposure and is included in reduced form at the back of the book.

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The proportion of genetic deviates in the tails of a normal population

Cited by 16 publications

References 2 publications

Optimal Design of Preliminary Yield Trials with Genome‐Wide Markers

Optimal Design of Preliminary Yield Trials with Genome‐Wide Markers

Predicting and observing the properties of second cycle hybrids using basic generations and inbred line × F1 crosses

Selection for soybean seed yield with molecular markers

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