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PubMed2004

Haplotype block definition and its application.

We present a simple two-stage procedure to define haplotype blocks and construct a statistic to test whether a polymorphism belongs to a block. Applying this method to the data of Gabriel et al. [2002] yielded longer haplotype blocks than were originally reported with a similar average percentage of common haplotypes in blocks. Furthermore, across regions of the genome and among the four populations that were studied, we found that linkage disequilibrium between a given single nucleotide polymorphism (SNP) and the haplotype block was a monotonic function of distance. This correlation was essentially independent of the minor allele frequency of the putative causal SNP when it fell outside of the block, however it was strongly dependent on the minor allele frequency when the SNP was internal to the block. These results have direct application to the design of candidate gene or region-wide association studies.

Algorithms↗

PubMed2002

The structure of haplotype blocks in the human genome.

Haplotype-based methods offer a powerful approach to disease gene mapping, based on the association between causal mutations and the ancestral haplotypes on which they arose. As part of The SNP Consortium Allele Frequency Projects, we characterized haplotype patterns across 51 autosomal regions (spanning 13 megabases of the human genome) in samples from Africa, Europe, and Asia. We show that the human genome can be parsed objectively into haplotype blocks: sizable regions over which there is little evidence for historical recombination and within which only a few common haplotypes are observed. The boundaries of blocks and specific haplotypes they contain are highly correlated across populations. We demonstrate that such haplotype frameworks provide substantial statistical power in association studies of common genetic variation across each region. Our results provide a foundation for the construction of a haplotype map of the human genome, facilitating comprehensive genetic association studies of human disease.

Africa↗

PubMed2005

Inference of missing SNPs and information quantity measurements for haplotype blocks.

MOTIVATION: Missing data in genotyping single nucleotide polymorphism (SNP) spots are common. High-throughput genotyping methods usually have a high rate of missing data. For example, the published human chromosome 21 data by Patil et al. contains about 20% missing SNPs. Inferring missing SNPs using the haplotype block structure is promising but difficult because the haplotype block boundaries are not well defined. Here we propose a global algorithm to overcome this difficulty. RESULTS: First, we propose to use entropy as a measure of haplotype diversity. We show that the entropy measure combined with a dynamic programming algorithm produces better haplotype block partitions than other measures. Second, based on the entropy measure, we propose a two-step iterative partition-inference algorithm for the inference of missing SNPs. At the first step, we apply the dynamic programming algorithm to partition haplotypes into blocks. At the second step, we use an iterative process similar to the expectation-maximization algorithm to infer missing SNPs in each haplotype block so as to minimize the block entropy. The algorithm iterates these two steps until the total block entropy is minimized. We test our algorithm in several experimental data sets. The results show that the global approach significantly improves the accuracy of the inference. AVAILABILITY: Upon request.

Algorithms↗

PubMed2005

Characterisation of the genomic architecture of human chromosome 17q and evaluation of different methods for haplotype block definition.

BACKGROUND: The selection of markers in association studies can be informed through the use of haplotype blocks. Recent reports have determined the genomic architecture of chromosomal segments through different haplotype block definitions based on linkage disequilibrium (LD) measures or haplotype diversity criteria. The relative applicability of distinct block definitions to association studies, however, remains unclear. We compared different block definitions in 6.1 Mb of chromosome 17q in 189 unrelated healthy individuals. Using 137 single nucleotide polymorphisms (SNPs), at a median spacing of 15.5 kb, we constructed haplotype block maps using published methods and additional methods we have developed. Haplotype tagging SNPs (htSNPs) were identified for each map. RESULTS: Blocks were found to be shorter and coverage of the region limited with methods based on LD measures, compared to the method based on haplotype diversity. Although the distribution of blocks was highly variable, the number of SNPs that needed to be typed in order to capture the maximum number of haplotypes was consistent. CONCLUSION: For the marker spacing used in this study, choice of block definition is not important when used as an initial screen of the region to identify htSNPs. However, choice of block definition has consequences for the downstream interpretation of association study results.

Chromosomes, Human, Pair 17↗

PubMed2005

Analysis of concordance of different haplotype block partitioning algorithms.

BACKGROUND: Different classes of haplotype block algorithms exist and the ideal dataset to assess their performance would be to comprehensively re-sequence a large genomic region in a large population. Such data sets are expensive to collect. Alternatively, we performed coalescent simulations to generate haplotypes with a high marker density and compared block partitioning results from diversity based, LD based, and information theoretic algorithms under different values of SNP density and allele frequency. RESULTS: We simulated 1000 haplotypes using the standard coalescent for three world populations--European, African American, and East Asian--and applied three classes of block partitioning algorithms--diversity based, LD based, and information theoretic. We assessed algorithm differences in number, size, and coverage of blocks inferred under different conditions of SNP density, allele frequency, and sample size. Each algorithm inferred blocks differing in number, size, and coverage under different density and allele frequency conditions. Different partitions had few if any matching block boundaries. However they still overlapped and a high percentage of total chromosomal region was common to all methods. This percentage was generally higher with a higher density of SNPs and when rarer markers were included. CONCLUSION: A gold standard definition of a haplotype block is difficult to achieve, but collecting haplotypes covered with a high density of SNPs, partitioning them with a variety of block algorithms, and identifying regions common to all methods may be the best way to identify genomic regions that harbor SNP variants that cause disease.

Algorithms↗

PubMed2002

A dynamic programming algorithm for haplotype block partitioning.

We develop a dynamic programming algorithm for haplotype block partitioning to minimize the number of representative single nucleotide polymorphisms (SNPs) required to account for most of the common haplotypes in each block. Any measure of haplotype quality can be used in the algorithm and of course the measure should depend on the specific application. The dynamic programming algorithm is applied to analyze the chromosome 21 haplotype data of Patil et al. [Patil, N., Berno, A. J., Hinds, D. A., Barrett, W. A., Doshi, J. M., Hacker, C. R., Kautzer, C. R., Lee, D. H., Marjoribanks, C., McDonough, D. P., et al. (2001) Science 294, 1719-1723], who searched for blocks of limited haplotype diversity. Using the same criteria as in Patil et al., we identify a total of 3,582 representative SNPs and 2,575 blocks that are 21.5% and 37.7% smaller, respectively, than those identified using a greedy algorithm of Patil et al. We also apply the dynamic programming algorithm to the same data set based on haplotype diversity. A total of 3,982 representative SNPs and 1,884 blocks are identified to account for 95% of the haplotype diversity in each block.

Algorithms↗

PubMed2003

Robustness of inference of haplotype block structure.

In this report, we examine the validity of the haplotype block concept by comparing block decompositions derived from public data sets by variants of several leading methods of block detection. We first develop a statistical method for assessing the concordance of two block decompositions. We then assess the robustness of inferred haplotype blocks to the specific detection method chosen, to arbitrary choices made in the block-detection algorithms, and to the sample analyzed. Although the block decompositions show levels of concordance that are very unlikely by chance, the absolute magnitude of the concordance may be low enough to limit the utility of the inference. For purposes of SNP selection, it seems likely that methods that do not arbitrarily impose block boundaries among correlated SNPs might perform better than block-based methods.

Algorithms↗

PubMed2002

Haplotype block structure and its applications to association studies: power and study designs.

Recent studies have shown that the human genome has a haplotype block structure, such that it can be divided into discrete blocks of limited haplotype diversity. In each block, a small fraction of single-nucleotide polymorphisms (SNPs), referred to as "tag SNPs," can be used to distinguish a large fraction of the haplotypes. These tag SNPs can potentially be extremely useful for association studies, in that it may not be necessary to genotype all SNPs; however, this depends on how much power is lost. Here we develop a simulation study to quantitatively assess the power loss for a variety of study designs, including case-control designs and case-parental control designs. First, a number of data sets containing case-parental or case-control samples are generated on the basis of a disease model. Second, a small fraction of case and control individuals in each data set are genotyped at all the loci, and a dynamic programming algorithm is used to determine the haplotype blocks and the tag SNPs based on the genotypes of the sampled individuals. Third, the statistical power of tests was evaluated on the basis of three kinds of data: (1) all of the SNPs and the corresponding haplotypes, (2) the tag SNPs and the corresponding haplotypes, and (3) the same number of randomly chosen SNPs as the number of tag SNPs and the corresponding haplotypes. We study the power of different association tests with a variety of disease models and block-partitioning criteria. Our study indicates that the genotyping efforts can be significantly reduced by the tag SNPs, without much loss of power. Depending on the specific haplotype block-partitioning algorithm and the disease model, when the identified tag SNPs are only 25% of all the SNPs, the power is reduced by only 4%, on average, compared with a power loss of approximately 12% when the same number of randomly chosen SNPs is used in a two-locus haplotype analysis. When the identified tag SNPs are approximately 14% of all the SNPs, the power is reduced by approximately 9%, compared with a power loss of approximately 21% when the same number of randomly chosen SNPs is used in a two-locus haplotype analysis. Our study also indicates that haplotype-based analysis can be much more powerful than marker-by-marker analysis.

Algorithms↗

PubMed2003

Finding haplotype block boundaries by using the minimum-description-length principle.

We present a method for detecting haplotype blocks that simultaneously uses information about linkage-disequilibrium decay between the blocks and the diversity of haplotypes within the blocks. By use of phased single-nucleotide polymorphism data, our method partitions a chromosome into a series of adjacent, nonoverlapping blocks. The partition is made by choosing among a family of Markov models for block structure in a chromosomal region. Specifically, in the model, the occurrence of haplotypes within blocks follows a time-inhomogeneous Markov process along the chromosome, and we choose among possible partitions by using the two-stage minimum-description-length criterion. When applied to data simulated from the coalescent with recombination hotspots, our method reliably situates block boundaries at the hotspots and infrequently places block boundaries at sites with background levels of recombination. We apply three previously published block-finding methods to the same data, showing that they either are relatively insensitive to recombination hotspots or fail to discriminate between background sites of recombination and hotspots. When applied to the 5q31 data of Daly et al., our method identifies more block boundaries in agreement with those found by Daly et al. than do other methods. These results suggest that our method may be useful for designing association-based mapping studies that exploit haplotype blocks.

Algorithms↗

PubMed2006

Linkage disequilibrium blocks, haplotype structure, and htSNPs of human CYP7A1 gene.

BACKGROUND: Cholesterol 7-alpha-hydroxylase (CYP7A1) is the rate limiting enzyme for converting cholesterol into bile acids. Genetic variations in the CYP7A1 gene have been associated with metabolic disorders of cholesterol and bile acids, including hypercholesterolemia, hypertriglyceridemia, arteriosclerosis, and gallstone disease. Current genetic studies are focused mainly on analysis of a single nucleotide polymorphism (SNP) at A-278C in the promoter region of the CYP7A1 gene. Here we report a genetic approach for an extensive analysis on linkage disequilibrium (LD) blocks and haplotype structures of the entire CYP7A1 gene and its surrounding sequences in Africans, Caucasians, Asians, Mexican-Americans, and African-Americans. RESULT: The LD patterns and haplotype blocks of CYP7A1 gene were defined in Africans, Caucasians, and Asians using genotyping data downloaded from the HapMap database to select a set of haplotype-tagging SNPs (htSNP). A low cost, microarray-based platform on thin-film biosensor chips was then developed for high-throughput genotyping to study transferability of the HapMap htSNPs to Mexican-American and African-American populations. Comparative LD patterns and haplotype block structure was defined across all test populations. CONCLUSION: A constant genetic structure in CYP7A1 gene and its surrounding sequences was found that may lead to a better design for association studies of genetic variations in CYP7A1 gene with cholesterol and bile acid metabolism.

Black or African American↗

PubMed2006

Distinguishable haplotype blocks in the HTR3A and HTR3B region in the Japanese reveal evidence of association of HTR3B with female major depression.

BACKGROUND: Genetic variations in the serotonin receptor 3A (HTR3A) and 3B (HTR3B) genes, positioned in tandem on chromosome 11q23.2, have been shown to be associated with psychiatric disorders in samples of European ancestry. But the polymorphisms highlighted in these reports map to different locations in the two genes, therefore it is unclear which gene exerts a stronger effect on susceptibility. METHODS: To determine the haplotype block structure in the genomic regions of HTR3A and HTR3B, and to examine whether genetic variations in the region show evidence of association with schizophrenia and affective disorder in the Japanese, we performed haplotype-based case-control analysis using 29 polymorphisms. RESULTS: Two haplotype blocks each were revealed for HTR3A and HTR3B in Japanese samples. In HTR3B, haplotype block 2 that included a nonsynonymous single nucleotide polymorphism (SNP), yielded evidence of association with major depression in females (global p = .0023). Analysis employing genome-wide SNPs using the STRUCTURE program did not detect population stratification in the samples. CONCLUSIONS: Our results suggest an important role for HTR3B in major depression in women and also raise the possibility that previously proposed disease-associated SNPs in the HTR3A/B region in Caucasians are in linkage disequilibrium with haplotype block 2 of HTR3B in the Japanese.

Adult↗

PubMed2004

Genomic haplotype blocks may not accurately reflect spatial variation in historic recombination intensity.

Recently, genomic data have revealed a "block-like" structure of haplotype diversity on human chromosomes. This structure is anticipated to facilitate gene mapping studies, because strong associations among loci within a block may allow haplotype variation to be tagged with a limited number of markers. But its usefulness to mapping efforts depends on the consistency of the block structure within and among populations, which in turn depends on how the block structure arises. Recombination hot spots are generally thought to underlie the block structure, but haplotype blocks can also develop stochastically under random recombination, in which case the block structure will show limited consistency among populations. Using coalescent models, which we upscaled to simulate the evolution of haplotypes with many markers at fixed distances, we show that the relationship between block boundaries and historic recombination intensity may be surprisingly weak. The majority of historic recombinations do not leave a footprint in present-day linkage disequilibrium patterns, and the block structure is sensitive to factors that affect the timing of recombination relative to marker mutation events in the genealogy, such as marker frequency bias and historic population size changes. Our results give insight into the potential of stochastic events to affect haplotype block structure, which can limit the usefulness of the block structure to mapping studies.

Animals↗

PubMed2026

Haplotype Blocks Are Associated With Rapid Local Adaptation to Environmental Shifts in Wild Barley.

Genomic mechanisms of local adaptation must be highly responsive in geographic regions where climate is changing rapidly. The Levant region is a critical biodiversity hotspot and the distribution edge for many species, including the wild ancestor of domesticated barley. This region is under an accelerated desertification process, thus enforcing a rapid genomic response to the projected environmental changes. To elucidate the genomic basis of rapid local adaptation, we studied wild barley populations using an ecological-genetic sampling design that decouples environmental variation from demographic background. We collected and sequenced 300 wild barley individuals and evaluated the phenotypes of 3600 progeny plants over 3 years. Our genomic analyses revealed that local adaptation is associated with clusters of candidate genes forming haplotype blocks. These clusters are enriched with environment and stress responsive genes, including flowering time regulators, drought and heat responsive genes. We identified six candidate adaptive haplotype blocks which span 1-8 Mbp and are distributed across chromosomes 1H, 2H, 4H and 5H, each segregating as two major haplotypes. Additionally, we integrated over 2600 occurrence records into ecological and evolutionary modelling to assess the genomic vulnerability of populations to projected future climates. Our study identifies candidate genomic regions and environmental drivers of local adaptation in wild barley and highlights the advantage of haplotype blocks architecture in orchestrating an efficient response to rapid environmental change. We highlight the ecological factors most strongly associated with the observed evolutionary responses and provide insights and guidelines for biodiversity conservation and implementation of crop wild relatives in breeding.

Hordeum↗

PubMed2004

HapBlock: haplotype block partitioning and tag SNP selection software using a set of dynamic programming algorithms.

UNLABELLED: Recent studies have revealed that linkage disequilibrium (LD) patterns vary across the human genome with some regions of high LD interspersed with regions of low LD. Such LD patterns make it possible to select a set of single nucleotide polymorphism (SNPs; tag SNPs) for genome-wide association studies. We have developed a suite of computer programs to analyze the block-like LD patterns and to select the corresponding tag SNPs. Compared to other programs for haplotype block partitioning and tag SNP selection, our program has several notable features. First, the dynamic programming algorithms implemented are guaranteed to find the block partition with minimum number of tag SNPs for the given criteria of blocks and tag SNPs. Second, both haplotype data and genotype data from unrelated individuals and/or from general pedigrees can be analyzed. Third, several existing measures/criteria for haplotype block partitioning and tag SNP selection have been implemented in the program. Finally, the programs provide flexibility to include specific SNPs (e.g. non-synonymous SNPs) as tag SNPs. AVAILABILITY: The HapBlock program and its supplemental documents can be downloaded from the website http://www.cmb.usc.edu/~msms/HapBlock.

Algorithms↗

PubMed2007

Significant variation in haplotype block structure but conservation in tagSNP patterns among global populations.

The initial belief that haplotype block boundaries and haplotypes were largely shared across populations was a foundation for constructing a haplotype map of the human genome using common SNP markers. The HapMap data document the generality of a block-like pattern of linkage disequilibrium (LD) with regions of low and high haplotype diversity but differences among the populations. Studies of many additional populations demonstrate that LD patterns can be highly variable among populations both across and within geographic regions. Because of this variation, emphasis has shifted to the generalizability of tagSNPs, those SNPs that capture the bulk of variation in a region. We have examined the LD and tagSNP patterns based upon over 2000 individual samples in 38 populations and 134 SNPs in 10 genetically independent loci for a total of 517 kb with an average density of 1 SNP/5 kb. Four different 'block' definitions and the pairwise LD tagSNP selection algorithm have been applied. Our results not only confirm large variation in block partition among populations from different regions (agreeing with previous studies including the HapMap) but also show that significant variation can occur among populations within geographic regions. None of the block-defining algorithms produces a consistent pattern within or across all geographic groups. In contrast, tagSNP transferability is much greater than the similarity of LD patterns and, although not perfect, some generalizations of transferability are possible. The analyses show an asymmetric pattern of tagSNP transferability coinciding with the subsetting of variation attributed to the spread of modern humans around the world.

Genetic Variation↗

PubMed2003

Selection of minimum subsets of single nucleotide polymorphisms to capture haplotype block diversity.

We present a simple numerical algorithm to select the minimal subset of SNPs required to capture the diversity of haplotype blocks or other genetic loci. This algorithm can be used to quickly select the minimum SNP subset with no loss of haplotype information. In addition, the method can be used in a more aggressive mode to further reduce the original SNP set, with minimal loss of information. We demonstrate the algorithm performance with data from over 11,000 SNPs with average spacing of 6 to 11 Kb, across all the genes of chromosomes 6, 21, and 22, genotyped on DNA samples of 45 unrelated African-Americans and 45 Caucasians from the Coriell Human Diversity Collection. With no loss of information, we reduced the number of SNPs required to capture the haplotype block diversity by 25% for the African-American and 36% for the Caucasian populations. With a maximum loss of 10% of haplotype distribution information, the SNP reduction was 38% and 49% respectively for the two populations. All computations were performed in less than 1 minute for the entire dataset used.

Algorithms↗

PubMed2005

Mutation screening of a haplotype block around the insulin degrading enzyme gene and association with Alzheimer's disease.

Genetic and biological studies point to a role for insulin-degrading enzyme (IDE) in Alzheimer's disease (AD). Two SNP-based studies recently reported evidence for association with AD using markers in a approximately 270 kb haplotype block on chromosome 10q. This haplotype block region harbors three known genes; insulin-degrading enzyme (IDE), kinesin family member 11 (KIF11), and hematopoietically expressed homeobox (HHEX). In an attempt to search for susceptibility variants we have sequenced all coding exons, 2 kb of 5' and 3'-flanking sequence, and all regions showing a high degree of human-mouse conservation in these three genes in 30 individuals. We found a total of 40 single nucleotide polymorphisms and 8 insertion/deletion polymorphisms. No coding variants were identified in any of the three genes. Nine polymorphisms in IDE and four polymorphisms in KIF11 situated in conserved regions or near coding exons were subsequently genotyped in a set of AD cases and controls. Two markers in KIF11 yielded borderline significant results in the ApoE4 non-carrier subgroup, but the results were otherwise not significant in this small set of samples. This study of multiple new markers in the region will facilitate further association studies in this important AD region.

Alzheimer Disease↗

PubMed2005

Modeling haplotype block variation using Markov chains.

Models of background variation in genomic regions form the basis of linkage disequilibrium mapping methods. In this work we analyze a background model that groups SNPs into haplotype blocks and represents the dependencies between blocks by a Markov chain. We develop an error measure to compare the performance of this model against the common model that assumes that blocks are independent. By examining data from the International Haplotype Mapping project, we show how the Markov model over haplotype blocks is most accurate when representing blocks in strong linkage disequilibrium. This contrasts with the independent model, which is rendered less accurate by linkage disequilibrium. We provide a theoretical explanation for this surprising property of the Markov model and relate its behavior to allele diversity.

Chromosome Mapping↗