Association mapping (genetics), also known as "linkage disequilibrium mapping", is a method of mapping quantitative trait loci (QTLs) that takes advantage of historic linkage disequilibrium to link phenotypes (observable characteristics) to genotypes (the genetic constitution of organisms), uncovering genetic associations.
The advantages of population based association mapping, utilizing a sample of individuals from the germplasm collections or a natural population, over traditional QTL-mapping in biparental crosses, primarily are due to availability of broader genetic variations with wider background for marker and trait correlations.
In family based association mapping instead of multiple unrelated individuals multiple unrelated families or pedigrees are used. The family-based association mapping can be used in situations where the mutant alleles have been introgressed in populations. One popular family-based association mapping is the transmission disequilibrium test.
The resolution of the mapping depends on the extent of LD, or non-random association of markers, that has occurred across the genome. Association mapping offers the opportunity to investigate diverse genetic material and potentially identify multiple alleles and mechanisms of underlying traits.
Association mapping allows the possibility of exploiting historically measured trait data for association, and lastly has no need for the development of expensive and tedious biparental populations that makes approach timesaving and cost-effective.
In genetics, association mapping, also known as " linkage disequilibrium mapping ", is a method of mapping quantitative trait loci (QTLs) that takes advantage of historic linkage disequilibrium to link phenotypes ( observable characteristics) to genotypes (the genetic constitution of organisms), uncovering genetic associations .
Populations showing a desired trait also carry a specific gene variant not because the variant actually controls the trait, but due to genetic relatedness. In particular, indirect associations that are not causal will not be eliminated by increasing the sample size or the number of markers.