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Haplotyping is an alternative approach to SNP genotyping. Haplotyping
information makes it possible to highlight the structure of the genome, notably
through haploblocks which correspond to segments of chromosomes unlikely to
undergo a crossing-over event. Haplotyping is a way of characterizing combinations
of SNPs that might infl uence response and is considered to be a more accurate mea-
sure of phenotypic variation. However, SNP-based tests have greater power when
the number of causative SNPs (a subset of the total set of SNPs) is smaller than the
total number of haplotypes. One limitation of haplotyping is that haplotypes need to
be determined for each individual, as SNPs detected from a pool of DNA from a
number of individuals cannot yield haplotypes.
Until whole-genome sequencing of individual patients becomes feasible clini-
cally, the identifi cation of SNPs and haplotypes will prove instrumental in efforts to
use genomic medicine to individualize health care. When an extensive inventory of
genome-wide SNP scans has been assembled across diverse population samples,
maps using SNP and/or haplotypes will dictate that it will not be necessary to iden-
tify the precise genes involved in determining therapeutic effi cacy or an adverse
reaction. Linkage disequilibrium (LD) methods can provide robust statistical cor-
relations between a patients response/risk index for a given drug class and a specifi c
LD-SNP/haplotype profi le.
Candidate gene-based haplotype approach has been applied to the pharmacoge-
netics of drug response and adverse events. Clinical trials using haplotyped indi-
viduals were the fi rst genetically personalized medical treatments.
Haplotyping for Whole Genome Sequencing
Despite considerable advances in whole-genome sequencing (WGS) in recent years
haplotype information was still inadequate from whole genome sequencing. Only
two genomes were completely haplotyped: the reference human genome and Craig
Venter’s genome, both of which relied on Sanger sequencing and clone mapping to
resolve the haplotypes, which is a labor-intensive and costly process. Although the
newer sequencing technologies enabled cost reductions and higher throughput, the
shorter reads are not amenable to obtaining haplotype information, which will be
critical in the fi elds of personalized medicine and population genetics. Disease risk
prediction is diffi cult without haplotype information. Now two different but compli-
mentary methods have been used to haplotype whole genomes; (1) combining NGS
with large insert cloning to achieve a sequenced genome with haplotype informa-
tion; and (2) using microfl uidics technology in combination with genotyping to
obtain haplotype information at the single-cell level.
The fi rst method was used to determine the haplotype-resolved genome of a
South Asian individual (Kitzman et al. 2011 ). A single fosmid library was split into
a modest number of pools, each providing ∼3 % physical coverage of the diploid
genome. Sequencing of each pool yielded reads overwhelmingly derived from only
one homologous chromosome at any given location. These data were combined
with whole-genome shotgun sequence to directly phase 94 % of ascertained
2 Molecular Diagnostics in Personalized Medicine