The
use of molecular genetic markers for selection and genetic improvement is based
on genetic linkage between these markers and a quantitative trait locus (QTL)
of interest. Thus, linkage analyses between markers and QTLs and between the
proper multiple markers are essential for genetic selection from genomic
information. It must be made clear that by definition, a QTL refers only to the
statistical association between a genomic region and a trait.
In
classical genetics, linkage between genetic factors or genes has been reported
since 1906 and means that closely linked genes on a chromosome are inherited
together. In other words, these genes do not segregate independently and thus
they do not obey Mendel’s Second Law or the Law of Independent Assortment. When
these genes are close to each other on a chromosome or linkage group, the
linkage is complete. When the genes are part of the same linkage group but are
distant from each other, there is a partial linkage.
The
calculated genetic distance between two genes is a function of the recombination
frequency between the genes and forms the basis for linkage map construction.
For linkage between loci to be detected and used in selection, there must be
linkage disequilibrium (LD) in the studied population or family. LD or gametic phase
disequilibrium is a measurement of the allele interdependdence at two or more
loci. In a group of individuals, if two alleles from distinct loci are found
together more often than would be expected, based on the product of their
frequencies, it can be inferred that such alleles are in LD. Disequilibrium values
near zero suggest equilibrium or independence between alleles from different
genes, and values near one indicate disequilibrium or strong linkage.
LD
between markers and QTLs is essential for QTL detection, MAS, and GWS. Of
particular importance is the extent of this disequilibrium in a chromosome in a
selected population. If a marker and a QTL are in equilibrium in the population,
this marker will segregate independently from the QTL. Thus, the marker
genotype of an individual has no informative value for selection. The persistence
in the population of LD among linked loci depends on the distance between the
loci; in other words, it depends on the recombination rate between the two
loci. For closely linked loci, any LD that has been created will persist for
many generations. However, for weakly linked loci (a recombination rate greater
than 0.1), the LD will decrease rapidly. Although a marker (locus m) linked to
a QTL (locus q) might be in linkage equilibrium in a population, there is
always disequilibrium within families or crosses, even for weakly linked loci.
Additionally, this disequilibrium can extend over large distances because it comes
from only one recombination performed to produce the descendants of a heterozygous
F 1 individual.
For
example, take two linked loci, m (marker) and q (QTL), in four individuals who
are heterozygous for the marker and have the following genotypes: MQ//mq,
Mq//mQ, MQ//mQ, and Mq//mq. The families coming from the two first individuals
will be in LD (because, for linked loci, parental gametes are more common than
recombinant ones) but in opposite directions because the phase of the QTL
marker differs in the two parents. The families from the two last individuals
will not be in LD because the QTL does not segregate in these families. When
combined across families, the four types of disequilibrium will cancel each
other out, creating linkage equilibrium in the population. Thus, LD within each
family is useful for QTL analysis as long as different linkage phases are
considered.
In
population genetics, disequilibrium generically refers to the discrepancy between
the joint frequency of a combination of alleles and the product of the alleles’
individual frequencies. The term normally refers to alleles from different loci
in the same gamete, but can also refer to pairs of alleles of the same locus
that show a lack of Hardy-Weinberg equilibrium.
QTL
mapping, MAS, proposed by Lande and Thompson (1990), and GWS, proposed by
Meuwissen et al. (2001), are based on the presence of linkage disequilibrium in
the studied population (or cross). In this situation, marker alleles provide
information about the existence and effects of loci that control quantitative
traits, providing ways to estimate the effects of QTLs and allowing them to be
used efficiently in genetic selection. The causes of LD in a population are
mutation, migration, selection, and a small effective population size (genetic drift due to sampling).
In other words, all of the factors that affect Hardy-Weinberg equilibrium in a
population also affect linkage equilibrium.
Recently,
molecular genetic markers that consist of SNPs (single-nucleotide polymorphisms),
which are based on the detection of polymorphisms that arise from a single base
change in the genome, have been used. Generally, for an SNP to be considered
genetically derived, the polymorphism must occur in at least
1%
of the population. SNPs are the most common form of genomic DNA variation and
are preferred over other genetic markers due to their low mutation rates and
ease and low cost of genotyping. Thousands of SNPs can be used to cover the
entire genome of an organism with markers that are not more than 1 cM apart
from each other. Microsatellite markers can also be used. These markers are
efficient because they are codominant, multi-allelic, abundant, and highly transferable
between individuals and species. However, the marker density of microsatellites
is usually limited to a few hundred markers. This density can compromise the
association study especially in populations with lower LD. SNP markers are most
often bi-allelic, as shown below:
Individual
1: TCACCGCG
Individual
2: TCATCGCG
In
this example, there is an SNP polymorphism between the two individuals. A
single base change in the DNA sequence results in a polymorphism. More than 1.5
million SNPs have been identified in the human genome. These SNPs exist at an
average spacing of 2 × 10 −3 cM (Hartl and Jones, 2002).
DArT
(Diversity Array Technology) markers are also bi-allelic and well suited for GWS
because they are abundant, like SNPs, and can be determined rapidly and in large
numbers. However, these markers are dominant, which may be a disadvantage when
compared to the codominant SNPs. GWS or GS (see Chapter 5) was proposed by
Meuwissen et al. (2001) as a way to accelerate and increase the effectiveness of
genetic improvement programs. GWS emphasizing the simultaneous prediction (without
using significance tests for individual markers) of the genetic effects of thousands
of DNA genetic markers that are spread throughout the genome of an organism, in
order to the capture the effects of all loci (both small and large effects) and
explain all genetic variation of a quantitative trait. To accomplish this,
population level LD between the marker alleles and the genes that control the
trait is essential.
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