Economic Efficiency of One Cycle of Marker‐Assisted Selection

Abstract

The efficiency of molecular markers to improve genetic prediction has been proved by many studies. Nevertheless, the additional cost due to marker genotyping is seldom considered in the comparison between marker‐assisted selection (MAS) and phenotypic selection. In the context of plant breeding, the relative cost efficiency of MAS in the first cycle of selection is evaluated through an analytical approach taking into account the effect of the experimental design (population size, number of trials, and replications per trial) on quantitative trait loci (QTL) detection. The same global cost is assumed for both methods. In a first step, the optimal allocation of the experimental resources is studied for each method before comparing them at their optimum. For traits sensitive to genotype × environment interactions, unreplicated trials are optimal for both methods but the optimal number of trials is different. It increases with the investment for phenotypic selection while it becomes nearly equal to one for MAS. The loss of efficiency due to non‐optimal designs is evaluated. The expected economic return of MAS compared with phenotypic selection decreases with the cost of genotyping. When this cost is high, MAS interest is limited to traits with a low heritability, provided that the investment is high enough to evaluate a large population size, which is the necessary condition to explain with markers a large part of genetic variation. The maximal genotyping cost that is acceptable for MAS to be efficient is given for different values of investment and trait heritability.

A Molecular Selection Index Method Based on Eigenanalysis

“…The MQTL effects can be identified and estimated through the linkage disequilibrium that arises when crossing inbred lines or divergent populations Smith 1992, 1993;Xie and Xu 1998). The MSI depends on various factors, such as number and density of molecular markers associated with QTL, population size, trait heritability, additive genetic variances that can be explained by molecular markers, and precision of the estimated effect of gene substitution (Dekkers and Dentine 1991;Moreau et al 2000).…”

“…The MQTL effects can be identified and estimated through the linkage disequilibrium that arises when crossing inbred lines or divergent populations Smith 1992, 1993;Xie and Xu 1998). The MSI depends on various factors, such as number and density of molecular markers associated with QTL, population size, trait heritability, additive genetic variances that can be explained by molecular markers, and precision of the estimated effect of gene substitution (Dekkers and Dentine 1991;Moreau et al 2000).The MSI is an application of the selection index methodology proposed by Smith (1936), in which MQTL effects are incorporated. As proposed by Lande and Thompson (1990), the MSI performs a linear regression of phenotypic values on the coded values of the molecular markers such that selected molecular markers are those statistically linked to QTL that explain most of the variability in regression models.…”

SELECTION Etude de l’efficacité de la sélection assistée par marqueurs par rapport à la sélection classique

“…À coût expérimental constant, la sélection conventionnelle, qui ne nécessite pas de marquage, permet d'évaluer une population de plus grande taille et d'augmenter la pression de sélection ou d'évaluer mieux les performances des individus en augmentant, par exemple, le nombre de lieux d'essais. Les résultats théoriques montrent que, au premier cycle de sélection, la sélection C est plus efficace économiquement que la sélection conventionnelle lorsque l'héritabilité des caractères est faible (< 0,3-0,4), que le coût du marquage est modéré par rapport au coût de l'évaluation agronomique et les moyens expérimentaux disponibles suffisants pour évaluer les performances et les génotypes aux marqueurs d'une population de grande taille (au moins 200 individus) [27]. Ainsi, l'intérêt de la SAM (C ou M) apparaît relativement limité au premier cycle.…”

SELECTION VARIETALE ET MILIEU Sélection pour l’adaptation au milieu et prise en compte des interactions génotype/milieu

“…Toutefois, la triple interaction génotype/année/lieu reste de même importance dans les deux réseaux. En présence d'interaction génotype/milieu, il est économiquement plus intéressant de réduire les essais à une seule répétition, ce qui permet d'augmenter le nombre de milieux [34]. Ceci rejoint la constatation que la réponse à la sélection n'est pas trop affectée lorsque le nombre de répétitions n'est pas optimal [35].…”