Molecular Breeding - Genetics, Genomics and Breeding of Crop Plants - page 235

phenotypic variance contributed by each QTL, among others. Many of these
variables can be optimized through marker validation and refinement.
For markers associated with simply inherited traits, marker validation
and reducing the distance between the marker and the gene of interest is
fairly straightforward. In these cases, the effect of the genetic background is
usually minimal, and the ease of phenotyping makes fine-mapping of the
gene simpler (Dwivedi et al. 2007). In mapping studies, genes for simply
inherited traits can be mapped with an adequate accuracy in a mapping
population of 100-150 individuals. This can then be followed by fine-
mapping using larger populations of targeted recombinants, and eventually,
by map-based cloning of the target gene. For example, fine-mapping of the
Rf1 gene responsible for restoring pollen fertility in sunflower PET1-based
material was accomplished using enlarged mapping populations (Kusterer
et al. 2005), followed by a map-based cloning approach (Kusterer et al. 2004;
Hamrit et al. 2006a). In addition, validation in different genetic backgrounds
for markers associated with major resistance genes has been accomplished
for those associated with the Pl 2 gene determining resistance to different
downy mildew races (Brahm et al. 2000), with the R 1 and the R adv genes
conferring rust resistance (Lawson et al. 1998), and with the Or5 gene
conferring resistance to race E of broomrape (Tang et al. 2003; Pérez-Vich et
al. 2004).
Unfortunately, in many instances the marker identified through the
process of fine-mapping may not be polymorphic in all the populations
tested, thus requiring the identification of alternative markers for those
populations. The “perfect” marker for selection would be one that provides
100% accurate prediction of the phenotype in all genetic backgrounds. These
markers, described as functional markers in previous sections, are based on
the gene mutations that have been demonstrated to be responsible for the
trait of interest. In sunflower, functional markers have been developed for
oil quality traits and other simple traits. For oil quality, Tang et al. (2006b)
determined that a non-lethal knockout mutation in a 2-methyl-6-phytyl-1,4-
benzoquinone/2-methyl-6-solanyl-1,4-benzoquinone methyltransferase
locus (MT-1) caused by the insertion of a 5.2 kb Ty3/gypsy -like
retrotransposon was underlying β-tocopherol accumulation in sunflower
seeds, and robust STS markers diagnostic for wild type and mutant MT-1
alleles were developed. For herbicide resistance, Kolkman et al. (2004)
identified mutations in codons 197 and 205 in the acetohydroxyacid
synthase gene AHAS-1 that confers resistance to sulfonylurea (SU) and
imidiazolonone (IMI) herbicides, and developed a SNP genotyping assay
diagnostic for the codon 205 mutation.
In the case of QTL markers for complex traits, the situation is far more
complicated. Factors such as population structure and size, parental
selection and genetic background effects, epistasis, inaccurate phenotyping,