Introduction
Developing elite breeding lines and varieties often requires plant breeders to combine desirable traits from multiple parental lines, particularly in the case of disease resistance. The process of combining traits, known as gene pyramiding, can be accelerated by using molecular markers to identify and keep plants that contain the desired allele combination and discard those that don't.
Selection based on molecular marker data (genotypic data) as opposed to traditional phenotypic data can confer many advantages. First, selection based on genotype allows breeders to identify and select desirable plants very early, such as the seedling stage, resulting in obvious savings of resources including greenhouse and/or field space, water, and fertilizer. Second, selection based on genotype can be cost effective when the cost of phenotyping is high and/or labor intensive. Third, when combining genes for resistance to the same disease, it can be difficult to distinguish, based on phenotype alone, those plants that carry all desired alleles from those that only have some of them. Fourth, unlike phenotypic selection, genotypic selection is not affected by environmental factors.

When using molecular markers to aid in the plant selection process, it is important to know where the molecular marker is located relative to the gene of interest. The genetic distance between marker and trait is calculated in genetic mapping studies (learn more about genetic mapping in an introduction to this topic provided by Wheat CAP). The farther a marker is from the DNA sequence polymorphism responsible for the trait, the greater the chance for recombination between the marker and the gene with each generation. If recombination occurs, selecting for a marker will not select for the trait, as the genetic linkage between the marker and the gene has been broken. This introduction to genetic mapping also outlines the process of genetic recombination.

Minimum Population Size
When pyramiding genes, breeders must calculate the probability of an individual plant containing the desired combination of alleles. This probability dictates the population size required to have a high probability of finding at least one plant with the desired combination of alleles. Muller (1923) and Sedcole (1977) promote use of the following equation to determine the minimum population size required to recover an individual with the desired combination of traits:

N = loge(1-P)/loge(1-f)

where
• N is the minimum population size
• P is the desired probability of success (e.g. 99%, 95%, 90%)
• f is the frequency of the event (i.e., an individual plant having all desired alleles).

The frequency depends on the number of genes the breeder wants combined, whether the genes are genetically linked, and the breeding scheme being utilized. What follows are two examples of calculating f, as well as the minimum population size, for two scenarios: (1) combining two unlinked genes, and (2) combining two linked genes.

Conclusion
Since MAS is expensive and breeding programmes are mostly funded by the local governments, the national governments can start some MAS based gene pyramiding projects with committed funding. In India the Indian Council of Agricultural Research (ICAR) has already taken the initiative and MAS based gene pyramiding projects are successfully undergoing in rice, maize, wheat etc. This has been an integral part of the breeding programme and not just any other backcross programme.
Breeders are not much excited about gene pyramiding for simply inherited traits, and not many QTL (especially the productivity related ones) with tightly linked markers are available. This will take some more time, especially the productivity related QTL from the wild species germplasm, to become available to breeders. However, with development and access to reliable PCR based markers like SSPs and SNPs in several crop plants, efficiency of pyramiding large populations or breeding materials has significantly increased. QTL pyramiding requires using better scoring methods, appropriate quantitative genetic analysis, and independent verifications through parallel populations. Appropriate DNA markers should be used at a definite stage to maximize the efficiency of MAS.
Gene pyramiding is an important strategy for germplasm improvement. Pyramiding requires that breeders consider the minimium population size that must be evaluated to have a reasonable chance of obtaining the desired genotype. Molecular marker genotyping can facilitate the gene pyramiding process by reducing the number of generations that breeders must evaluate to ensure they have the desired gene combination.

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