A haplotype (Greek haploos = simple) is a combination of alleles at multiple linked loci that are transmitted together. Haplotype may refer to as few as two loci or to an entire chromosome depending on the number of recombination events that have occurred between a given set of loci. The term haplotype is a portmanteau of "haploid genotype."
In a second meaning, haplotype is a set of single nucleotide polymorphisms (SNPs) on a single chromatid that are statistically associated. It is thought that these associations, and the identification of a few alleles of a haplotype block, can unambiguously identify all other polymorphic sites in its region. Such information is very valuable for investigating the genetics behind common diseases, and is collected by the International HapMap Project.
An organism's genotype may not uniquely define its haplotype. For example, consider a diploid organism and two bi-allelic loci on the same chromosome such as Single-Nucleotide Polymorphisms (SNPs). The first locus has alleles A and T with three possible genotypes AA, AT, and TT, the second locus having G and C, again giving three possible genotypes GG, GC, and CC. For a given individual, there are therefore nine possible configurations for the genotypes at these two loci, as shown in the latin square below, which shows the possible genotypes that an individual may carry and the corresponding haplotypes that these resolve to. For individuals that are homozygous at one or both loci, it is clear what the haplotypes are; it is only when an individual is heterozygous at both loci that the phase is ambiguous.
|GG||AG AG||AG TG||TG TG|
|GC||AG AC||AG TC
|CC||AC AC||AC TC||TC TC|
The only unequivocal method of resolving phase ambiguity is by sequencing. However, it is possible to estimate the probability of a particular haplotype when phase is ambiguous using a sample of individuals.
Given the genotypes for a number of individuals, the haplotypes can be inferred by haplotype resolution or haplotype phasing techniques. These methods work by applying the observation that certain haplotypes are common in certain genomic regions. Therefore, given a set of possible haplotype resolutions, these methods choose those that use fewer different haplotypes overall. The specifics of these methods vary - some are based on combinatorial approaches (e.g., parsimony), whereas others use likelihood functions based on different models and assumptions such as the Hardy-Weinberg principle, the coalescent theory model, or perfect phylogeny. These models are combined with optimization algorithms such as expectation-maximization algorithm (EM) or Markov chain Monte Carlo (MCMC).
Y-DNA haplotypes from genealogical DNA tests
Unlike other chromosomes, Y chromosomes do not come in pairs. Every human male has one copy only that chromosome. This means that there is no lottery from which copy to inherit, and also (for much of the chromosome) no shuffling between copies by recombination; so, unlike autosomal haplotypes, there is therefore effectively no randomisation of the Y-chromosome haplotype between generations, and a human male should largely share the same Y chromosome as his father, give or take a few mutations.
In particular, the Y-DNA that is the numbered results of a Y-DNA genealogical DNA test should match, barring mutations. Within genealogical and popular discussion, this is sometimes referred to as the "DNA signature" of a particular male human, or of his paternal bloodline.
UEP results (SNP results)
The results that make up the full Y-DNA haplotype from the Y chromosome DNA test can be divided into two parts: the results for unique event polymorphisms (UEPs), sometimes loosely called the SNP results as most UEPs are single nucleotide polymorphisms, and the results for microsatellite short tandem repeat sequences (Y-STRs), often designated by DYS numbers.
The UEP results reflect the inheritance of events it is believed can be assumed to have happened only once in all human history. These can be used to directly identify the individual's Y-DNA haplogroup, his place on the broad family tree of the whole of humanity. Different Y-DNA haplogroups identify genetic populations which are often intricately geographically orientated, reflecting the migrations of current individuals' direct patrilineal ancestors tens of thousands of years ago.
The other possible part of the genetic results is the Y-STR haplotype, the set of results from the Y-STR markers tested.
Unlike the UEPs, the Y-STRs mutate much more easily, which gives them much more resolution to distinguish recent genealogy. But it also means that, rather than the population of descendents of a genetic event all sharing the same result, the Y-STR haplotypes are likely to have spread apart, to form a cluster of more or less similar results. Typically, this cluster will have a definite most probable center, the modal haplotype (presumably close to the haplotype of the original founding event), and also a haplotype diversity - the degree to which it has become spread out. The further in the past the defining event occurred, and the more that subsequent population growth occurred early, the greater the haplotype diversity for a particular number of descendents will be. On the other hand, if the haplotype diversity is smaller for a particular number of descendents, this may indicate a more recent common ancestor, or that a population expansion has occurred more recently.
It is important to note that, unlike for UEPs, there is no guarantee that two individuals with a similar Y-STR haplotype will necessarily share a similar ancestry. There is no uniqueness about Y-STR events. Instead, the clusters of Y-STR haplotype results inheriting from different events and different histories all tend to overlap.
Thus, although sometimes a Y-STR haplotype may be directly indicative of a particular Y-DNA haplogoup, it is in most cases a long time since the haplogoups' defining events, so typically the cluster of Y-STR haplotype results associated with descendents of that event has become rather broad, and will tend to significantly overlap the (similarly broad) clusters of Y-STR haplotypes associated with other haplogroups, making it impossible to predict with absolute certainty to which Y-DNA haplogroup a Y-STR haplotype would point. All that can be done from the Y-STRs, if the UEPs are not actually tested, is to predict probabilities for haplogroup ancestry (as this online program does), but not certainties.
A similar scenario exists for surnames. A cluster of similar Y-STR haplotypes may indicate a shared common ancestor, with an identifiable modal haplotype, but only if the cluster is sufficiently distinct from what may have arisen by chance from different individuals historically having adopted the same name independently. This may require the typing of quite an extensive haplotype to establish, which has fuelled DNA testing companies to offer ever-larger sets of markers - 24 then 37 then 67, and perhaps soon even more.
Plausibly establishing relatedness between different surnames data-mined from a database is significantly harder, because now it must be established not that a randomly-selected member of the population is unlikely to have such a close match by accident, but rather that the very nearest member of the population in question, chosen purposely from the population for that very reason, would even under those circumstances be unlikely to match by accident. This is for the foreseeable future likely to be impossible, except in special cases where there is further information to drastically limit the size of that population of candidates under consideration.
The following software is available for estimating hapltoypes
- snphap — EM based software for estimating haplotype frequencies from unphased genotypes.
- Haploview — Visualisation of linkage disequilibrium, haplotype estimation and haplotype tagging (Homepage).
The following software is available for testing haplotypes for disease associations
- HelixTree — Haplotype analysis software - Haplotype Trend Regression (HTR), haplotypic association tests, and haplotype frequency estimation using both the expectation-maximization (EM) algorithm and composite haplotype method (CHM).
- The International HapMap Consortium (2003). "The International HapMap Project" (PDF). Nature. 426: 789–796.
- The International HapMap Consortium (2005). "A haplotype map of the human genome" (PDF). Nature. 437: 1299–1320.
- Barrett J.C., Fry B., Maller J., Daly M.J. (2005). "Haploview: analysis and visualization of LD and haplotype maps". Bioinformatics. 21: 263–265.
- Purcell S., Daly M. J., Sham P. C. (2007). "WHAP: haplotype-based association analysis". Bioinformatics. 23: 255–256.
- HapMap — homepage for the International HapMap Project.
- Haplotype versus Haplogroup — the difference between haplogroup & haplotype explained.