Comparison: Quantitative Trait Locus (QTL) and Haplotype-Based
Computational Genetic Analysis
Haplotype-based
Method QTL analysis computational analysisProcess Produce, genotype
and Order and phenotype phenotype 200–1000 F2 10–20 strains or BC1
Reproducibility Each F2 is unique Can reorder strains Resolution 10–
100 Mb Individual genes Effort 3–5 scientists 3–10 yr 1 scientist < 1 d
Detection power Handles high complexity Handles limited complexity
BC, backcross. The commonly used inbred mouse strains were
developed from a limited number of founder mice. The genome of each
inbred mouse strain resembles a patchwork of a small number of
ancestral chromosomes (6). The observed linkage disequilibrium among
the inbred mouse strains is much greater than that in the population of
mice in the wild. This strong linkage disequilibrium means that the
pattern of genetic variation within a genomic region can be
characterized by knowing the alleles at a relatively few positions. The
genome of the inbred strains can be efficiently organized into
semiindependent regions, and each region contains a relatively small
number of distinct genetic patterns. This drastically reduces the
number of comparisons required for computational genetic analysis.
Instead of comparing a phenotypic pattern with individual SNP alleles,
the haplotype-based method compares the phenotype with different
haplotypes that extend across larger genomic regions (4). We will
describe how a map of the haplotypic structure of the mouse genome
was constructed and how this enabled computational analysis of genetic
traits to be performed. Following this, a quantitative model for
haplotype-based computational mapping method is presented.
2. A HAPLOTYPE MAP FOR INBRED MOUSE STRAINS:
As previously noted in the human genome, SNP alleles in close physical
proximity in the genome of inbred mouse strains were often correlated,
resulting in the presence of “SNP haplotypes” appearing within blocklike structures (7). Each haplotype within a block apparently originated
from a common ancestral chromosome, whereas block size reflects
other processes, including recombination and mutation. In general, the
block structure and haplotype diversity depends on the genealogical
history of the population used to construct the block structure and the
local mutation and recombination rate. An appropriate haplotype map
for QTL mapping purpose should be constructed using inbred strains
with similar overall genetic background, yet display sufficient
phenotypic differences. Because linkage disequilibrium decays as the
distance between markers increase, it cannot be fully characterized
by any simple block structure. When methods that produce very large
blocks are used, the linkage disequilibrium among alleles within a large
haplotype block is relatively weak. In this case, finer structures within
the block are not identified, and distinct haplotypes within the block
may be missed. However, when methods that produce very short blocks
are used, then strong linkage disequilibrium between neighboring
blocks will be missed. There are many different ways to define the block
structure. All of these methods produce haplotype blocks that balance
two desired proprieties. The size of the block should be as large as
possible, but all distinct haplotypes within the
54 Wang and Peltz