Agriculture Reference
In-Depth Information
studies. Association studies in general terms offer interesting approaches
for the genetic analysis of oligo or multigenic traits because of high
theoretical power of resolution and the possibility to study various regions
of the genome simultaneously without the construction of mapping
populations. Association studies are based on germplasm collections
that ideally present either very well-characterized population or race
structure, minimal genetic structure, and that are made up of useful
genotypes that vary for a single or multiple traits of interest.
These germplasm collections can be made to prioritize gene discovery
and be made of landraces put together by a geneticist or germplasm
curator to be contrasting as done for bulked segregant analysis (BSA)
studies but with intermediate, low, and high phenotypes. Alternatively,
a germplasm collection can be a pool of genotypes from a breeding
program where traits of interest have for the most part been identi
ed
and in some cases pyramided together, resulting in a set of breeding lines
that already have multiple traits of interest for the association study.
These are the most important reasons for considering association
approaches as useful options today for studying agronomic traits in
multiple germplasm collections. AM is also a useful approach for
identifying the statistical associations between a marker and a quantita-
tive trait. Considering that almost all agronomic traits are quantitative
and of either oligo or multigenic inheritance, association analysis should
have a similar or stronger power to identify the loci involved in these
traits as quantitative trait loci (QTL) studies as long as certain criteria are
met, which we will discuss in greater detail later on in this chapter. As a
preview, the level of linkage disequilibrium (LD), the recombinational
history, and the representativeness of the germplasm panel affect AM
studies.
The principle of association genetics relies on LD. Association genet-
ics or AM offers a high resolution power when there is a high amount of
recombination and diversity in the individuals from the population
under study. This methodology was initially applied in human genetics
because in it linkage mapping is dif
cult since construction of mapping
populations is not feasible. In human genetics, the
first wave of large-
scale, high-density genome-wide association (GWA) studies improved
the understanding of the genetic basis of many complex traits. especially
the inheritance of susceptibility to several diseases such as prostate
cancer, type 1 and 2 diabetes, in
ammatory bowel disease, and breast
cancer (McCarthy et al. 2008).On the other hand, just a few loci have
been found to be associated with susceptibility to diseases such as
asthma, coronary heart ailments, and atrial
fibrillation. Even though
the ultimate objective of using GWA studies to cure human disease is
