Marker-assisted Selection Method Research Articles

Money matters (I): costs of field and laboratory procedures associated with conventional and marker-assisted maize breeding at CIMMYT

This article presents selected results of a study carried out in Mexico at the International Maize and Wheat Improvement Center (CIMMYT) to compare the cost-effectiveness of conventional and marker-assisted maize breeding. Costs associated with use of conventional and marker-assisted selection (MAS) methods were estimated using a spreadsheet-based budgeting approach. This information was used to compare the cost of using conventional screening and MAS to achieve a well-defined breeding objective—identification of plants carrying a mutant recessive form of the opaque2 gene in maize that is associated with Quality Protein Maize (QPM). In addition to generating empirical cost information that will be of use to CIMMYT research managers, the study produced four important insights. First, for any given breeding project, detailed budget analysis will be needed to determine the cost-effectiveness of MAS relative to conventional selection. Second, direct comparisons of unit costs for MAS methods and conventional selection methods provide useful information for research managers, but factors other than cost are likely to play an important role in driving the choice of screening methods. Third, the choice between MAS and conventional selection may be complicated by the fact that the two are not always direct substitutes. Fourth, when used with empirical data from actual breeding programs, spreadsheet-based budgeting tools can be used by research managers to improve the efficiency of existing protocols and to inform decisions about future technology choices.

Money matters (II): costs of maize inbred line conversion schemes at CIMMYT using conventional and marker-assisted selection

This article presents selected results of a study carried out in Mexico at the International Maize and Wheat Improvement Center (CIMMYT) to compare the cost-effectiveness of conventional and biotechnology-assisted maize breeding. Costs associated with the use of conventional and marker-assisted selection (MAS) methods at CIMMYT were estimated using a spreadsheet-based budgeting approach. This information was used to compare the costs of conventional and MAS methods for a particular breeding application: introgressing an elite allele at a single dominant gene into an elite maize line (line conversion). At CIMMYT, neither method shows clear superiority in terms of both cost and speed: conventional breeding schemes are less expensive, but MAS-based breeding schemes can be completed in less time. For applications involving tradeoffs between time and money, relative profitability can be evaluated using conventional investment theory. Using a simple model of a plant breeding program, we show that the optimal choice of a breeding technology depends on the availability of operating capital. If operating capital is abundantly available, the "best" breeding method will be the one that maximizes the net present value (i.e., MAS), but if operating capital is constrained, the "best" breeding method will be the one that maximizes the internal rate of return (i.e., conventional selection). This insight may help to explain why private firms tend to invest more aggressively in biotechnology than public breeding programs, which are more likely to face budgetary constraints.

Comparison of potentials between genotype-based selection and genotypic value-based selection of quantitative traits

According to the difference of selection criteria, methods of marker-assisted selection (MAS) of quantitative traits can be divided into genotype-based selection (GS) and genotypic value-based selection (GVS). By means of computer simulation, potentials of the two methods were compared. Results showed that the two methods had similar basic laws and their efficiencies were not significantly different except that GS behaved better in the case where the number of QTLs was large and QTL effects were equal. From the application point of view, combination of GS and GVS should be the development direction of MAS research in the future.

Optimal marker-assisted selection to increase the effective size of small populations.

An approach to the optimal utilization of marker and pedigree information in minimizing the rates of inbreeding and genetic drift at the average locus of the genome (not just the marked loci) in a small diploid population is proposed, and its efficiency is investigated by stochastic simulations. The approach is based on estimating the expected pedigree of each chromosome by using marker and individual pedigree information and minimizing the average coancestry of selected chromosomes by quadratic integer programming. It is shown that the approach is much more effective and much less computer demanding in implementation than previous ones. For pigs with 10 offspring per mother genotyped for two markers (each with four alleles at equal initial frequency) per chromosome of 100 cM, the approach can increase the average effective size for the whole genome by approximately 40 and 55% if mating ratios (the number of females mated with a male) are 3 and 12, respectively, compared with the corresponding values obtained by optimizing between-family selection using pedigree information only. The efficiency of the marker-assisted selection method increases with increasing amount of marker information (number of markers per chromosome, heterozygosity per marker) and family size, but decreases with increasing genome size. For less prolific species, the approach is still effective if the mating ratio is large so that a high marker-assisted selection pressure on the rarer sex can be maintained.

Marker-assisted selection to increase effective population size by reducing Mendelian segregation variance.

Using both the genetic drift and inbreeding approaches, we derive more general equations for effective size (N(e)) of a diploid species under random mating. These equations show explicitly that inbreeding or genetic drift comes from two sources, the variation in the number of offspring from each parent and the variation in contribution between these parents' own paternally and maternally derived genes to their offspring. The first source can be easily and effectively controlled by choosing an equal number of offspring from each family, while the second can be manipulated by using information on genetic markers to reduce the variance due to Mendelian segregation. Marker-assisted selection (MAS) methods to increase N(e) for the whole genome with single or multiple marker loci per chromosome, different numbers of males, and females are developed and implemented in stochastic simulations. The analytical and simulation results show that, although in principle N(e) can be increased indefinitely, the efficiency of MAS is restricted in practice by the amount of marker information, the genome size, and the number of marker-genotyped offspring per family. The assumptions made in developing the theory and methods and the applications of MAS in conservation are discussed.

More on the efficiency of marker-assisted selection

Computer simulations were used to study the efficiency of marker-assisted selection (MAS) based on an index combining the phenotypic value and the molecular score of individuals. The molecular score is computed from the effects attributed to markers by multiple regression of phenotype on marker genotype. The results show that in the first generation the ratio RE of the expected efficiency of MAS over the expected efficiency of purely phenotypic selection generally increases when considering: (1) larger population sizes, (2) lower heritability values of the trait, and (3) a higher type-I error risk of the regression. This is consistent with previously published results. However, at low heritabilities our results point out that response to MAS is more variable than response to phenotypic selection. Hence, when the difference of genetic gains is considered instead of their ratio, RE, the heritability values corresponding to maximal advantage of using MAS rather than phenotypic selection are still low, but higher than predicted based on RE. The study over several successive generations of the rate of fixation of QTLs shows that the higher efficiency of MAS on QTLs with large effects in early generations is balanced by a higher rate of fixation of unfavourable alleles at QTLs with small effects in later generations. This explains why MAS may become less efficient than phenotypic selection in the long term. MAS efficiency therefore depends on the genetic determinism of the trait. Finally, we investigate a modified MAS method involving an alternation of selection on markers with and without phenotypic evaluation. Our results indicate that such a selection method could at low cost, provide an important increase in the genetic gain per unit of time in practical breeding programs.

Mom1 is a semi-dominant modifier of intestinal adenoma size and multiplicity in Min/+ mice.

The intestinal tumor multiplicity in mice heterozygous for ApcMin is strongly modulated by genetic background. On the sensitive C57BL/6J (B6) background, mice develop large numbers of intestinal adenomas. The AKR/J (AKR) strain carries alleles that correlate with a strong reduction in tumor multiplicity. To study the effect of one of these modifiers, Mom1, we have generated a mouse line in which the AKR allele of Mom1 is carried on the sensitive B6 genetic background. This strain was produced by using a marker-assisted selection method to eliminate unlinked AKR alleles more rapidly. The application and efficiency of this method are discussed. We used this strain to determine that Mom1 affects both tumor multiplicity and tumor size in a semi-dominant fashion.

Using marker-maps in marker-assisted selection

A method of using information on the location of markers to improve the efficiency of marker-assisted selection (MAS) in a population produced by a cross between two inbred lines is developed. The method is closer to mapping QTL than the selection index approaches to MAS described by previous authors. We use computer simulations to compare our method with phenotypic selection and two selection index approaches, simulations being performed on three genetic maps. The simulations show that whilst MAS can be considerably more efficient than phenotypic selection differences between the three MAS methods are slight. Which of the MAS methods is best depends on a number of factors: in particular the genetic map, the time scale under consideration ant the population size are of importance.