Geoscience Reference
In-Depth Information
illustrated in Figure 17.4. The closer a marker is from a QTL,
the lower the prospect of recombination occurring between
marker and QTL. Therefore, the QTL and marker will usu-
ally be inherited together in the progeny, and the mean of the
group with the tightly linked are going to be considerably
totally different (
P
< 0.05) to the mean of the group without
the marker and will be the reverse in case if there is no sig-
niicant
P
value for unlinked QTLs. If the unlinked mark-
ers are located far apart or on different chromosomes for the
QTL of a particular trait indicates non-significant variation
among the genotypes.
Statistical methods to detect QTLs
The fundamental
objective in QTL mapping studies is to identify QTL, whereas
minimising the prevalence of false positives (Type I errors,
i.e. declaring an association between a marker and QTL
once in reality one does not exist). Tests for QTL/trait asso-
ciation are usually performed by the subsequent approaches:
Single-marker analysis (also 'single-point analysis')
This is
the simplest method for detecting QTLs related to single mark-
ers. Linear regression, analysis of variance and
t
-tests are gen-
erally used for this analysis. Among these, the most frequently
used technique is linear regression because the coefficient
of determination (R2) from the marker explains the pheno-
typic variation generating from the QTL linked to the marker.
This method does not need a complete linkage map and can
be accomplished with basic statistical software programs.
However, the key disadvantage associated with this process
is that the further a QTL is from a marker, the less likely it
will be detected. This can be as a result of recombination that
could occur between the marker and also the QTL. This causes
the magnitude of the effect of a QTL to be underestimated.
The utilisation of a large number of segregating DNA mark-
ers covering the entire genome (usually at intervals <15 cM)
may minimise both problems. The results from single-marker
analysis are commonly presented in a table, which indicates
the chromosome (if known) or linkage group encompassing
the markers, probability values and the percentage of phe-
notypic variation elucidated by the QTL (R2) (Table 17.3).
Sporadically, the allele size of the marker is also described. To
execute a single-marker analysis, Q Gene and MapManager
QTX most frequently used computer programs (Manly et al.
2001; Nelson 1997).
