GENE GENEALOGIES WITHIN THE ORGANISMAL PEDIGREES OF RANDOM-MATING POPULATIONS

Using computer simulations, we generated and analyzed genetic distances among selectively neutral haplotypes transmitted through gene genealogies with random-mating organismal pedigrees. Constraints and possible biases on haplotype distances due to correlated ancestry were evaluated by comparing observed distributions of distances to those predicted from an inbreeding theory that assumes independence among haplotype pairs. Results suggest that: 1) mean time to common ancestry of neutral haplotypes can be a reasonably good predictor of evolutionary effective population size; 2) the nonindependence of haplotype paths of descent within a given gene genealogy typically produces significant departures from the theoretical probability distributions of haplotype distances; 3) frequency distributions of distances between haplotypes drawn from “replicate” organismal pedigrees or from multiple unlinked loci within an organismal pedigree exhibit very close agreement with the theory for independent haplotypes. These results are relevant to interpretations of current molecular data on genetic distances among nonrecombining haplotypes at either nuclear or cytoplasmic loci.     

Use of closely related affected individuals for the genetic study of complex diseases in founder populations

We propose a method, the maximum identity length contrast (MILC) statistic, to locate genetic risk factors for complex diseases in founder populations. The MILC approach compares the identity length of parental haplotypes that are transmitted to affected offspring with the identity length of those that are not transmitted to affected offspring. Initially, the statistical properties of the method were assessed using randomly selected affected individuals with unknown relationship. Because both nuclear families with multiple affected sibs and large pedigrees are often available in founder populations, we performed simulations to investigate the properties of the MILC statistic in the presence of closely related affected individuals. The simulation showed that the use of closely related affected individuals greatly enhances the power of the statistic. For a given sample size and type I error, the use of affected sib pairs, instead of affected individuals randomly selected from the population, could increase the power by a factor of two. This increase was related to an increase of kinship-coefficient contrast between haplotype groups when closely related individuals were considered. The MILC approach allows the simultaneous use of affected individuals from a founder population and affected individuals with any kind of relationship, close or remote. We used the MILC approach to analyze the role of HLA in celiac disease and showed that the effect of HLA may be detected with the MILC approach by typing only 11 affected individuals, who were part of a single large Finnish pedigree.     

Haplotype sharing analysis using mantel statistics

OBJECTIVE: The potential value of haplotypes has attracted widespread interest in the mapping of complex traits. Haplotype sharing methods take the linkage disequilibrium information between multiple markers into account, and may have good power to detect predisposing genes. We present a new approach based on Mantel statistics for spacetime clustering, which is developed in order to improve the power of haplotype sharing analysis for gene mapping in complex disease. METHODS: The new statistic correlates genetic similarity and phenotypic similarity across pairs of haplotypes for case-only and case-control studies. The genetic similarity is measured as the shared length between haplotypes around a putative disease locus. The phenotypic similarity is measured as the mean-corrected cross-product based on the respective phenotypes. We analyzed two tests for statistical significance with respect to type I error: (1) assuming asymptotic normality, and (2) using a Monte Carlo permutation procedure. The results were compared to the chi(2) test for association based on 3-marker haplotypes. RESULTS: The results of the type I error rates for the Mantel statistics using the permutational procedure yielded pointwise valid tests. The approach based on the assumption of asymptotic normality was seriously liberal. CONCLUSION: Power comparisons showed that the Mantel statistics were better than or equal to the chi(2) test for all simulated disease models.     

Strong signature of natural selection within an FHIT intron implicated in prostate cancer risk

Previously, a candidate gene linkage approach on brother pairs affected with prostate cancer identified a locus of prostate cancer susceptibility at D3S1234 within the fragile histidine triad gene (FHIT), a tumor suppressor that induces apoptosis. Subsequent association tests on 16 SNPs spanning approximately 381 kb surrounding D3S1234 in Americans of European descent revealed significant evidence of association for a single SNP within intron 5 of FHIT. In the current study, re-sequencing and genotyping within a 28.5 kb region surrounding this SNP further delineated the association with prostate cancer risk to a 15 kb region. Multiple SNPs in sequences under evolutionary constraint within intron 5 of FHIT defined several related haplotypes with an increased risk of prostate cancer in European-Americans. Strong associations were detected for a risk haplotype defined by SNPs 138543, 142413, and 152494 in all cases (Pearson's chi(2) = 12.34, df 1, P = 0.00045) and for the homozygous risk haplotype defined by SNPs 144716, 142413, and 148444 in cases that shared 2 alleles identical by descent with their affected brothers (Pearson's chi(2) = 11.50, df 1, P = 0.00070). In addition to highly conserved sequences encompassing SNPs 148444 and 152413, population studies revealed strong signatures of natural selection for a 1 kb window covering the SNP 144716 in two human populations, the European American (pi = 0.0072, Tajima's D = 3.31, 14 SNPs) and the Japanese (pi = 0.0049, Fay & Wu's H = 8.05, 14 SNPs), as well as in chimpanzees (Fay & Wu's H = 8.62, 12 SNPs). These results strongly support the involvement of the FHIT intronic region in an increased risk of prostate cancer.     

Bayesian spatial modeling of haplotype associations

We review methods for relating the risk of disease to a collection of single nucleotide polymorphisms (SNPs) within a small region. Association studies using case-control designs with unrelated individuals could be used either to test for a direct effect of a candidate gene and characterize the responsible variant(s), or to fine map an unknown gene by exploiting the pattern of linkage disequilibrium (LD). We consider a flexible class of logistic penetrance models based on haplotypes and compare them with an alternative formulation based on unphased multilocus genotypes. The likelihood for haplotype-based models requires summation over all possible haplotype assignments consistent with the observed genotype data, and can be fitted using either Expectation-Maximization (E-M) or Markov chain Monte Carlo (MCMC) methods. Subtleties involving ascertainment correction for case-control studies are discussed. There has been great interest in methods for LD mapping based on the coalescent or ancestral recombination graphs as well as methods based on haplotype sharing, both of which we review briefly. Because of their computational complexity, we propose some alternative empirical modeling approaches using techniques borrowed from the Bayesian spatial statistics literature. Here, space is interpreted in terms of a distance metric describing the similarity of any pair of haplotypes to each other, and hence their presumed common ancestry. Specifically, we discuss the conditional autoregressive model and two spatial clustering models: Potts and Voronoi. We conclude with a discussion of the implications of these methods for modeling cryptic relatedness, haplotype blocks, and haplotype tagging SNPs, and suggest a Bayesian framework for the HapMap project.     

Transmission/Disequilibrium Tests for Extended Marker Haplotypes

A generalization of the transmission/disequilibrium test to detect association between polymorphic markers and discrete or quantitative traits is discussed, with particular emphasis on marker haplotypes formed by several adjacent loci. Furthermore, strategies for testing haplotype association, using methods from spatial statistics, are developed. This approach compares the "similarity" of transmitted and untransmitted haplotypes, with the aim of determining the regions where there is greater similarity within the transmitted set. This arises from the fact that, although the original haplotypes carrying the mutation will be broken down by recombination, there may be a subset of markers near the mutation that are common to many of the recombinant haplotypes. Thus, by examination of each marker in turn and by measurement of the average size of the region shared identically by state in the transmitted and untransmitted haplotypes, it may be possible to detect regions of linkage disequilibrium that encompass the susceptibility gene.     

Frequency and origin of haplotypes associated with the beta-globin gene cluster in individuals with trait and sickle cell anemia in the Atlantic and Pacific coastal regions of Colombia

Sickle cell anemia is a genetic disease with high prevalence in people of African descent. There are five typical haplotypes associated with this disease and the haplotypes associated with the beta-globin gene cluster have been used to establish the origin of African-descendant people in America. In this work, we determined the frequency and the origin of haplotypes associated with hemoglobin S in a sample of individuals with sickle cell anemia (HbSS) and sickle cell hemoglobin trait (HbAS) in coastal regions of Colombia. Blood samples from 71 HbAS and 79 HbSS individuals were obtained. Haplotypes were determined based on the presence of variable restriction sites within the β-globin gene cluster. On the Pacific coast of Colombia the most frequent haplotype was Benin, while on the Atlantic coast Bantu was marginally higher than Benin. Eight atypical haplotypes were observed on both coasts, being more diverse in the Atlantic than in the Pacific region. These results suggest a differential settlement of the coasts, dependent on where slaves were brought from, either from the Gulf of Guinea or from Angola, where the haplotype distributions are similar. Atypical haplotypes probably originated from point mutations that lost or gained a restriction site and/or by recombination events.     

Detection of parent-of-origin effects in nuclear families using haplotype analysis

Despite the potential pitfalls of stratification, population-based association studies nowadays are being conducted more often than family-based association studies. However, the mechanism of genomic imprinting has lately been implicated in the etiology of genetic complex diseases and can be detected using statistics only in family-based designs. Powerful tests for association and imprinting have been proposed previously for case-parent trios and single markers. Since the power of association studies can be improved if multiple affected children and haplotypes are considered, we extended the parental asymmetry test (PAT) for imprinting to a test that is suited for both general nuclear families and haplotypes, called HAP-PAT. Significance of the HAP-PAT is determined via a Monte-Carlo simulation procedure. In addition to the HAP-PAT, we modified a haplotype-based association test, proposed by us before, in such a way that either only paternal or maternal transmissions contribute to the test statistic. The approaches were implemented in FAMHAP and we evaluated their performance under a variety of disease models. We were able to demonstrate the usefulness of our haplotype-based approaches to detect parent-of-origin effects. Furthermore, we showed that also in the presence of imprinting it is more reasonable to consider all affected children of a nuclear family, than to randomly select one affected child from each family and to conduct a trio study using the selected individuals.     

Within- and between-individual sequence variation among ITS1 copies in the meadow grasshopper Chorthippus parallelus indicates frequent intrachromosomal gene conversion

Sequencing multiple copies of the ITS1 region revealed the coexistence of two or more haplotypes within the genome of Chorthippus parallelus. Using a PCR-RFLP approach, the ITS1 numbers and frequencies of haplotypes present in each of 40 individuals were investigated, revealing a consistent lack of homogeneity. For each individual, the level of intra-individual variation was estimated from a sample of 20 ITS1 copies. The level of differentiation in haplotype frequency among individuals was then estimated by maximum likelihood using models based on the Dirichlet distribution. This confirmed the existence of significant levels of variation among individuals within each population studied. The most likely turnover mechanism that could generate this pattern of variation is gene conversion, operating at the intrachromosomal level. Furthermore, the discovery of linkage disequilibrium among the ITS1 haplotypes of C. parallelus suggests that intrachromosomal gene conversion occurs more frequently than interchromosomal recombination. Subspecies of C. parallelus showed significantly different haplotype distributions following about 0.5 Myr of divergence. With respect to the process of concerted evolution, we show that homogenization of repeats is slow relative to speciation, and the standing variation among individuals is sufficient for selection to operate.     

The influence of maternal lineages on social affiliations among humpback whales (Megaptera novaeangliae) on their feeding grounds in the southern gulf of Maine

Humpback whales on their feeding grounds in the Gulf of Maine typically form fluid fission/fusion groups of two to three individuals characterized by noncompetitive and, at times, cooperative behavior. Here we test the hypothesis that, despite the apparent absence of close kinship bonds, the fluid associations between feeding whales are influenced by "maternal lineages" as represented by mtDNA haplotypes. Using skin samples collected with a biopsy dart, variation in the hypervariable segment of the mtDNA control region identified 17 unique haplotypes among 159 individually identified whales from the southern Gulf of Maine. The haplotypes of a further 143 individuals were inferred from known direct maternal (cow-calf) relationships. The frequencies of associations among these 302 individuals were calculated from 21,617 sighting records collected from 1980 to 1995, excluding associations between a cow and her dependent calf. For groups of two where the haplotypes of both individuals were known (n = 3,151), individuals with the same haplotype were together significantly more often (26%) than expected by random association (20%). To account for different group sizes and associations with individuals of unknown haplotype and sex, we used Monte Carlo simulations to test for nonrandom associations in the full data set, as well as known female-only (n = 1,512), male-only (n = 730), and mixed-sex (n = 2,745) groups. Within-haplotype associations were significantly more frequent than expected at random for all groups (P = .002) and female-only groups (P = .011) but not male-only groups, while mixed-sex groups approached significance (P = .062). A Mantel test of individual pairwise association indices and haplotype identity confirmed that within-haplotype associations were more frequent than expected for all sex combinations except male-male associations, with females forming within-haplotype associations 1.7 times more often than expected by random assortment. Partial matrix correlations and permutation analyses indicated that the skew toward within-haplotype associations could not be accounted for by short-term temporal co-occurrence or fine-scale spatial distributions of individuals with shared haplotypes. While the mechanism by which individuals with a common mtDNA haplotype assort remains unknown, our results strongly suggest an influence of maternal lineages on the social organization of humpback whales within a regional feeding ground.     

Haplotype-sharing analysis using Mantel statistics for combined genetic effects

We applied a new approach based on Mantel statistics to analyze the Genetic Analysis Workshop 14 simulated data with prior knowledge of the answers. The method was developed in order to improve the power of a haplotype sharing analysis for gene mapping in complex disease. The new statistic correlates genetic similarity and phenotypic similarity across pairs of haplotypes from case-control studies. The genetic similarity is measured as the shared length between haplotype pairs around a genetic marker. The phenotypic similarity is measured as the mean corrected cross-product based on the respective phenotypes. Cases with phenotype P1 and unrelated controls were drawn from the population of Danacaa. Power to detect main effects was compared to the X2-test for association based on 3-marker haplotypes and a global permutation test for haplotype association to test for main effects. Power to detect gene x gene interaction was compared to unconditional logistic regression. The results suggest that the Mantel statistics might be more powerful than alternative tests.     

Haplotype-based linkage disequilibrium mapping via direct data mining

MOTIVATION: With the availability of large-scale, high-density single-nucleotide polymorphism markers and information on haplotype structures and frequencies, a great challenge is how to take advantage of haplotype information in the association mapping of complex diseases in case-control studies. RESULTS: We present a novel approach for association mapping based on directly mining haplotypes (i.e. phased genotype pairs) produced from case-control data or case-parent data via a density-based clustering algorithm, which can be applied to whole-genome screens as well as candidate-gene studies in small genomic regions. The method directly explores the sharing of haplotype segments in affected individuals that are rarely present in normal individuals. The measure of sharing between two haplotypes is defined by a new similarity metric that combines the length of the shared segments and the number of common alleles around any marker position of the haplotypes, which is robust against recent mutations/genotype errors and recombination events. The effectiveness of the approach is demonstrated by using both simulated datasets and real datasets. The results show that the algorithm is accurate for different population models and for different disease models, even for genes with small effects, and it outperforms some recently developed methods.     

Power studies for the transmission/disequilibrium tests with multiple alleles.

Case-control studies compare marker-allele distributions in affected and unaffected individuals, and significant results suggest linkage but may simply reflect population structure. For markers with m alleles (m > or = 2), a McNemar-like statistic, I, estimates the level of population association between marker and disease loci. To test for linkage after significant case-control tests, within-family tests are performed. These operate on the contingency table, with i, jth element equal to the number of parents that transmit marker allele Mi and do not transmit marker allele Mi to an affected offspring. The dimension of the table is the number of alleles at the marker locus. Three test statistics have recently been proposed in the literature: Tc compares symmetric pairs of cells (i, j) and (j, i), Tm compares row and column totals for the same marker allele, and a likelihood ratio statistic Tl uses all the cells in the table. In addition, we consider a new statistic, Tmhet, that uses only the heterozygous parents and is approximately chi2 with (m - 1) df. We use a Monte Carlo test to guarantee valid tests and to demonstrate the inferiority of Tc and the equality of Tm and Tl in terms of power. The power of the Tmhet test is close but not always equal to the power of the Tm test. We also show that under the alternative hypothesis of linkage, Tm is approximately noncentral chi2 with (m - 1) df and noncentrality parameter 2NT(1 - 2theta)2I*, when data on single affecteds in NT families are used. If the disease has a low population frequency, then I* is estimated using the case-control statistic I. This offers a basis for choosing sample size, or choosing a marker system.     

Association of cytochrome P450 genes polymorphisms (CYP1A1 and CYP1A2) with the development of chronic obstructive pulmonary disease in Bashkortostan

To assess the role that polymorphisms of cytochrome P450 genes play in genetic predisposition to chronic obstructive pulmonary disease (COPD), the allele and genotype distributions of CYPIA1 (2455 A/G, 3801T/C) and CYP1A2 (-2464T/delT, -163C/A) genes were studied in Tatar and Russian COPD patients and in cases of healthy individuals (Russian, Tatar and Bashkir), residents of Bashkortostan. It was shown that the CYP1A1 and CYP1A2 genes haplotypes frequency distribution patterns do not differed between Tatars and Russians ethnic groups (chi2 = 0.973, df = 3, p = 1.00 and chi2 = 1.546, df = 3, p = 0.92, respectively). Analysis of the the CYP1A1 and CYP1A2 genes haplotypes revealed statistically significant differences in the haplotypes frequency distributions between Bashkirs versus Russians and Tatars (chi2 = 12.328, df= 3,p = 0.008; chi2 = 9.218, df=3, p = 0.034, respectively for CYP1A1 gene and (chi2 = 18.779, df=3, p = 0.0001, chi = 14.326, df=3, p = 0.003, respectively for CYP1A2 gene). The (-2467)delT allele and CYP1A2*1D haplotype of CYPIA2 gene was associated with higher risk of COPD in Tatar ethnic group (OR = 1.83, 95% CI 1.24-2.71, chi2 = 9.48, p = 0.003 and chi2 = 9.733, p = 0.0027, Pcor = 0.008; OR = 3.908, 95% CI 1.56-10.19, respectively). On the other hand the CYP1A2*1A haplotype had protective effect (chi2 = 6.319, p = 0.0127, Pcor = 0.038; OR = 0.6012, 95% CI 0.402-0.898). But at the same time we did not find any differences in the genotypes and haplotypes frequency distributions of the CYP1A2 gene within the patients and healthy groups in Russian ethnic group. We also did not find any association of CYP1A1 gene with COPD in ethnic groups of Bashkortostan.     

The major histocompatability complex (MHC) contains conserved polymorphic genomic sequences that are shuffled by recombination to form ethnic-specific haplotypes

The major histocompatibility complex (MHC) consists of polymorphic frozen blocks (PFBs) that are linked to form megabase haplotypes. These blocks consist of polymorphic sequences and define regions where recombination appears to be inhibited. We have been able to show, using a highly polymorphic sequence centromeric of HLA-B (within the beta block), that PFBs are conserved and contain specific insertions/deletions and substitutions that are the same for individuals with the same MHC haplotype but that differ between at least most different haplotypes. A sequence comparison between ethnic-specific haplotypes shows that these sequences have remained stable and predate the formation of these haplotypes. To determine whether the same conserved block has been involved in the generation of multiple haplotypes, we compared the block typing profiles of different ethnic specific haplotypes. Block typing profiles have previously been shown to be identical in individuals with the same MHC haplotype but, generally, to differ between different haplotypes. It was found that some PFBs are common to more than one haplotype, implying a common ancestry. Subsequently, haplotypes have been generated by the shuffling and exchange of these PFBs. The regions between these PFBs appear to permit the recombination sites and therefore could be expected to exhibit either low polymorphism or a localized ``hotspot.' Received: 20 January 1997 / Accepted: 11 March 1997     

A further study of a possible locus for schizophrenia on the X chromosome

Several studies suggest that the X chromosome may contain a gene for schizophrenia. In the present study, we recruited 142 male schizophrenic patients and their biological mothers from all parts of the United Kingdom to detect a genetic association for the SYP/CACNA1F locus in the Xp11 region and the FACL4 locus in the Xq22.3-Xq23 region. The haplotype-based haplotype relative risk (HHRR) analysis showed allelic association for rs2071316 (chi2=6.85, P=0.009) and rs5905724 (chi2=5.3, P=0.021) at the CACNA1F locus, but not for rs5943414 and rs1324805 at the FACL4 locus and rs3817678 at the SYP locus. The haplotype analysis showed a weak association for the rs3817678-rs2071316-rs5905724 haplotypes (chi2=12.19, df=4, P=0.016) but did not show such an association for the rs5943414-rs1324805 haplotypes (chi2=3.96, df=2, P=0.138). Because the linkage disequilibrium signal was detected only at the CACNA1F locus, this gene should perhaps be considered as being a candidate for schizophrenia although further work is needed to draw firm conclusions.     

HAPLOFREQ--estimating haplotype frequencies efficiently.

A commonly used tool in disease association studies is the search for discrepancies between the haplotype distribution in the case and control populations. In order to find this discrepancy, the haplotypes frequency in each of the populations is estimated from the genotypes. We present a new method HAPLOFREQ to estimate haplotype frequencies over a short genomic region given the genotypes or haplotypes with missing data or sequencing errors. Our approach incorporates a maximum likelihood model based on a simple random generative model which assumes that the genotypes are independently sampled from the population. We first show that if the phased haplotypes are given, possibly with missing data, we can estimate the frequency of the haplotypes in the population by finding the global optimum of the likelihood function in polynomial time. If the haplotypes are not phased, finding the maximum value of the likelihood function is NP-hard. In this case, we define an alternative likelihood function which can be thought of as a relaxed likelihood function. We show that the maximum relaxed likelihood can be found in polynomial time and that the optimal solution of the relaxed likelihood approaches asymptotically to the haplotype frequencies in the population. In contrast to previous approaches, our algorithms are guaranteed to converge in polynomial time to a global maximum of the different likelihood functions. We compared the performance of our algorithm to the widely used program PHASE, and we found that our estimates are at least 10% more accurate than PHASE and about ten times faster than PHASE. Our techniques involve new algorithms in convex optimization. These algorithms may be of independent interest. Particularly, they may be helpful in other maximum likelihood problems arising from survey sampling.     

Nonlinear tests for genomewide association studies

As millions of single-nucleotide polymorphisms (SNPs) have been identified and high-throughput genotyping technologies have been rapidly developed, large-scale genomewide association studies are soon within reach. However, since a genomewide association study involves a large number of SNPs it is therefore nearly impossible to ensure a genomewide significance level of 0.05 using the available statistics, although the multiple-test problems can be alleviated, but not sufficiently, by the use of tagging SNPs. One strategy to circumvent the multiple-test problem associated with genome-wide association tests is to develop novel test statistics with high power. In this report, we introduce several nonlinear tests, which are based on nonlinear transformation of allele or haplotype frequencies. We investigate the power of the nonlinear test statistics and demonstrate that under certain conditions, some nonlinear test statistics have much higher power than the standard chi2-test statistic. Type I error rates of the nonlinear tests are validated using simulation studies. We also show that a class of similarity measure-based test statistics is based on the quadratic function of allele or haplotype frequencies, and thus they belong to nonlinear tests. To evaluate their performance, the nonlinear test statistics are also applied to three real data sets. Our study shows that nonlinear test statistics have great potential in association studies of complex diseases.     

Mapping the locus for hereditary hemochromatosis: localization between HLA-B and HLA-A.

We studied a family with HLA-linked hereditary hemochromatosis in which an informative recombination occurred within the HLA region. The father, an obligate heterozygote for hereditary hemochromatosis, had HLA haplotypes A2,B13 and A11,B27. The mother, also an obligate heterozygote, had HLA haplotypes A29,B44 and A2,B7. Three haplotypes were found among three homozygous affected offspring. Two affected siblings were HLA-identical with haplotypes A2,B13 and A29,B44. The proband had HLA haplotypes A2,B13 and A2,B44, the latter a recombinant haplotype inherited from her mother. Since the maternal hemochromatosis allele was linked to the A29,B44 haplotype, and since the proband has hemochromatosis, the maternal hemochromatosis allele was transmitted to the proband with the B44 antigen. This is the first known example of recombination in an individual with HLA-linked hemochromatosis in whom the hemochromatosis allele appeared to segregate with the HLA-B antigen instead of the -A antigen. The possibility of either a double reciprocal recombination event or a gene conversion event cannot be excluded. Combined with earlier observations of segregation of the hemochromatosis allele with the A locus in HLA recombinants, the findings in this pedigree map the hemochromatosis locus between the HLA-B and HLA-A loci rather than outside the HLA region.     

Combining markers into haplotypes can improve population structure inference

High-throughput genotyping and sequencing technologies can generate dense sets of genetic markers for large numbers of individuals. For most species, these data will contain many markers in linkage disequilibrium (LD). To utilize such data for population structure inference, we investigate the use of haplotypes constructed by combining the alleles at single-nucleotide polymorphisms (SNPs). We introduce a statistic derived from information theory, the gain of informativeness for assignment (GIA), which quantifies the additional information for assigning individuals to populations using haplotype data compared to using individual loci separately. Using a two-loci-two-allele model, we demonstrate that combining markers in linkage equilibrium into haplotypes always leads to nonpositive GIA, suggesting that combining the two markers is not advantageous for ancestry inference. However, for loci in LD, GIA is often positive, suggesting that assignment can be improved by combining markers into haplotypes. Using GIA as a criterion for combining markers into haplotypes, we demonstrate for simulated data a significant improvement of assigning individuals to candidate populations. For the many cases that we investigate, incorrect assignment was reduced between 26% and 97% using haplotype data. For empirical data from French and German individuals, the incorrectly assigned individuals can, for example, be decreased by 73% using haplotypes. Our results can be useful for challenging population structure and assignment problems, in particular for studies where large-scale population-genomic data are available.