Expected Selection Differentials for Directional Selection

-Genetic variability in small populations is affected by specific phenomena. The joint effects of genetic drift and selection, in addition to the decrease in genetic variance due to the mere selection (Bulmer effect), enhance the risk of losing alleles at selected or unselected genes and increase the inbreeding in the population by changing the family structure. Criteria for measuring this change in genetic variability are derived from the three approaches to describe the genetic variability. At the genealogical level, the kinship and inbreeding coefficients, or the effective population size, can be used. At the trait level, the estimation of its heritability is a good measure of remaining genetic variance. At the genome level, studying the polymorphism of known genetic markers can inform on the degree of genetic diversity. These criteria are to be integrated in specific tools for the management of the genetic variability. After a short introduction on the basic concepts needed for the study of genetic variability in small populations, the main criteria available to measure its change in populations is exposed and their relative efficiencies discussed. The strategies for monitoring genetic variability, deriving from the previous criteria, are illustrated through different examples. small population / genetic variability / genetic drift / genetic management / conservation programme Résumé -Mesure et gestion de la variabilité génétique dans les petites populations. Plusieurs phénomènes spécifiques modifient la variabilité génétique dans les petites populations. Les effets combinés de la dérive génétique et de la sélection, auxquels s'ajoutent la réduction de la variance géné-tique due spécifiquement à la sélection (Effet Bulmer), renforcent le risque de perdre des allèles à des loci sélectionnés et non sélectionnés et augmentent la consanguinité de la population du fait de la modification de la structure familiale. Les critères de mesure de la variabilité génétique dérivent des 3 approches utilisées pour la décrire. Les coefficients de consanguinité et de parenté ou l'effectif génétique résument l'information généalogique. L'estimation de l'héritabilité d'un caractère synthétise la variabilité génétique restante. L'étude du polymorphisme pour des marqueurs génétiques Ann. Zootech. 49 (2000) 77-93 77

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“…For normally distributed traits, the selection intensity must be calculated or approximated using order statistics theory [4,21].…”

Section: Consequences On Genetic Variabilitymentioning

confidence: 99%

Measuring and managing genetic variability in small populations

2000

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“…(John et al, 1972) or to 16 dams with a partially balanced incomplete block design (Cochran and Cox, 1957 (Hill, 1976). In addition, by selecting more sires the effect of finite numbers on male selection intensities (Burrows, 1972) (Bulmer, 1971).…”

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confidence: 99%

“…Inbreeding rates with factorial and hierarchical mating designs are relatively similar because the increased probability of coselecting half sibs with factorial designs is balanced by the reduced probability of coselecting full sibs. Woolliams (1989) (Burrows, 1972) and population structure (Hill, 1976) As a consequence of the balance between intensities and accuracies of selection, the effect of using more than 1 male per selected sibship on genetic response depended on the number of sibships selected and the number of males per sibship used. The effect on response was most favourable when few sibships were selected and when 2 males per sibship were used.…”

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confidence: 99%

The effect of alternative mating designs and selection strategies on adult multiple ovulation and embryo transfer (MOET) nucleus breeding schemes in dairy cattle

Ruane¹

1991

Genet. Sel. Evol.

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“…Pour tout modèle de distribution, sa valeur peut être déterminée, le modèle habituellement invoqué étant celui de la distribution normale des X. BURROWS (1972BURROWS ( , 1975 a étudié l'espé-rance et la variance de ∆ dans des cas d'échantillons finis ; NAGARAJA (1982) a considéré d'autres aspects limites de ∆. BROGDEN (1951) semble être le premier et le seul à avoir développé l'idée d'un avantage spécifique de la sélection différentielle.…”

Section: Documentationsunclassified

Le différentiel de sélection multiple

Laurencelle¹

2015

TQMP

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An important aim of personnel selection is to maintain and hopefully increase the company's productivity, a similar rationale underlying the recruiting of athletes in a sports league or the admission of students or candidates in limited enrolment programs. To help raise the 'performance' of the organization, one of many ways is to submit candidates to an aptitude test and select only those whose score exceeds some predetermined threshold value. The eventual 'performance' of such abler candidates should be superior to that of un-selected personnel, inasmuch as there is a positive relation between performance in the organization and the score obtained at the aptitude test. The expected gain in performance, i.e. the positive score difference between the sub-population of selected and abler persons and the whole pool of candidates is called 'selection differential', a very old concept. Brogden, in 1951, introduced the idea of differential selection in the specific sense of testing candidates on two or more aptitude tests in order to assign each meritorious candidate to the job wherein the expected gain is higher. Taking up this idea, we propose and develop the concept and mathematics of the multivariate selection differential, with three variants. A few worked-out examples and tables of differentials of order 2 to 5 complete the paper.

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Expected Selection Differentials for Directional Selection

Cited by 93 publications

References 6 publications

Measuring and managing genetic variability in small populations

Measuring and managing genetic variability in small populations

The effect of alternative mating designs and selection strategies on adult multiple ovulation and embryo transfer (MOET) nucleus breeding schemes in dairy cattle

Le différentiel de sélection multiple

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