Principles of Plant Genetics and Breeding

location, genetic effects, and the interactions of these
QTLs for better use in plant breeding. Knowledge of
the location of a QTL of agronomic importance will
allow breeders to target specific chromosome intervals
in other species that have been less studied (the concept
of synteny).
Methods of QTL mapping
The basic approach to QTL analysis is to attempt to
correlate their genetic variation in a specific quantitative
trait with polymorphic genomic regions that are
identified by molecular markers. Just like Mendelian
genes, the degree of co-segregation of genes at different
loci indicates the genetic distance between the loci of
interest. In Mendelian analysis, there is a one to one
correspondence between phenotype and genotype,
making it relatively easy to construct a gene map based
on the frequency of recombination. In the case of quantitative
traits, the phenotype is the result of several to
many genes, plus the environment, making the one to
one relationship between phenotype and genotype not
valid. Consequently, phenotypic variation only provides
partial information about the segregation of the genes
that control them, making it necessary to use statistical
methods to acquire additional genotypic information
about each QTL–marker relationship.
As summarized by M. J. Kearsey and Z. W. Luo, the
three key requirements for mapping QTLs are: (i) trait
phenotype; (ii) polymorphic markers; and (iii) genetic
structure of populations. The phenotypic record of an
individual for traits of interest reflects the genetic effects
of QTL alleles present in the individual and the environmental
contribution to the development of the trait.
Molecular markers can be tracked and mapped like
major genes, because they have uniquely identifiable
effects. The third resource for mapping, the genetic
structure of the mapping population, defines the
domain in which the genes at a specific QTL segregate,
as well as the pattern of recombination between the
genes at linked loci. Appropriate statistical tools are used
to bridge the relationship between the trait phenotype
and the genotype at the genomic region that is specified
by marker loci.
The choice of the mapping population is critical in
QTL mapping. The breeder generates a segregating
population by crossing lines with extreme phenotypic
performance for the quantitative trait of interest. The
most frequently used populations are derived from
crossing two inbred lines that are assumed to be
homozygous with different alleles at both QTLs and
genetic markers. These materials include F2s, backcrosses,
BIOTECHNOLOGY IN PLANT BREEDING 251
recombinant inbred lines, and doubled haploids. Strong
linkage disequilibrium at marker loci and alleles of linked
loci controlling the trait is needed, making the F 2 ,
the generation with the strongest expression of linkage
disequilibrium, the one most desirable to use.
Two basic types of analysis are used in QTL mapping
to determine the association between different marker
genotypes and their trait mean values.
Single marker analysis
The simplest way of identifying QTLs is to compare
homozygous marker classes to the marker loci (i.e.,
compare the trait means of different classes for each
marker locus individually in the form of a single factor
analysis of variance (ANOVA); the error term in this
procedure is the individual value, while the marker
classes are the factor). Statistical methods commonly
used for single marker analysis are the simple t-test,
ANOVA, linear regression, and the maximum likelihood
estimation. Single marker analysis has certain
drawbacks (produces ambiguities regarding both location
of QTLs and the estimates of their effects).
Specifically, a significant association of trait mean with a
specific marker indicates the presence of a QTL at or
near the marker, but does not indicate on which side of
the marker it is located.
Interval mapping
The method of flanking markers is based on the hypothesis
that a QTL lies between linked marker loci. The
statistical package, MapMaker/QTL developed by Eric
Lander and colleagues, is used for this analysis. Several
modifications have been proposed to interval mapping
that consider a single segregating QTL on a chromosome.
This has drawbacks. By assessing the likelihood
for a single putative QTL at each map location on the
genome separately, the method ignores the effects of
other mapped or yet to be mapped QTLs. The hypothesis
of one putative QTL is unrealistic because a large number
of genes distributed throughout the genome are
suspected to be involved in quantitative trait expression.
Subsequently, methods for mapping multiple QTLs
simultaneously have been proposed.
Marker-assisted breeding
Molecular markers may be used in several ways to make
the plant breeding process more efficient. The adoption
of a marker-assisted selection (MAS) or marker-aided