Randomly distributed crossovers may generate block-like patterns of linkage disequilibrium: an act of genetic drift

Genome wide association mapping and candidate gene analysis for pod shatter resistance in Brassica juncea and its progenitor species

We investigated phenotypic variations for pod shattering, pod length and number of seeds per pod in large germplasm collections of Brassica juncea (2n = 36; AABB) and its progenitor species, B. rapa (2n = 20; AA) and B. nigra (2n = 16; BB). Pod shatter resistance was measured as energy required for rupturing a mature dry pod, with a specially fabricated pendulum machine. Rupture energy (RE) ranged from 3.3 to 11.0 mJ in B. juncea. MCP 633, NR 3350 and Albeli required maximum energy to shatter a pod. It ranged from 2.5 to 7.8 mJ for B. rapa with an average of 5.5 mJ. B. nigra possessed easy to rupture pods. Correlation analysis showed strong associations among these traits in B. juncea and B. rapa. Genome wide association studies were conducted with select sets of B. juncea and B. rapa germplasm lines. Significant and annotated associations predict the role of FRUITFULL, MANNASE7, and NAC secondary wall thickening promoting factor (NST2) in the genetic regulation of shatter resistance in B. juncea. NST2 and SHP1 appeared important for pod length and seeds per pod in B. rapa. Candidate gene based association mapping also confirmed the role of SHP1 and NST2 in regulating pod shattering and related pod traits in B. rapa and B. juncea. Footprints of selection were detected in SHP1, SHP2 (B. rapa, B. nigra and B. juncea), RPL (B. rapa) and NAC (B. juncea). Our results provide insights into the genetic architecture of three pod traits. The identified genes are relevant to improving and securing crop productivity of mustard crop.

Linkage disequilibrium and haplotype block structure in a composite beef cattle breed

Background

The development of linkage disequilibrium (LD) maps and the characterization of haplotype block structure at the population level are useful parameters for guiding genome wide association (GWA) studies, and for understanding the nature of non-linear association between phenotypes and genes. The elucidation of haplotype block structure can reduce the information of several single nucleotide polymorphisms (SNP) into the information of a haplotype block, reducing the number of SNPs in a coherent way for consideration in GWA and genomic selection studies.

Results

The maximum average LD, measured by r² varied between 0.33 to 0.40 at a distance of < 2.5 kb, and the minimum average values of r² varied between 0.05 to 0.07 at distances ranging from 400 to 500 kb, clearly showing that the average r² reduced with the increase in SNP pair distances. The persistence of LD phase showed higher values at shorter genomic distances, decreasing with the increase in physical distance, varying from 0.96 at a distance of < 2.5 kb to 0.66 at a distance from 400 to 500 kb. A total of 78% of all SNPs were clustered into haplotype blocks, covering 1,57 Mb of the total autosomal genome size.

Conclusions

This study presented the first high density linkage disequilibrium map and haplotype block structure for a composite beef cattle population, and indicates that the high density SNP panel over 700 k can be used for genomic selection implementation and GWA studies for Canchim beef cattle.

BLOCK-BASED BAYESIAN EPISTASIS ASSOCIATION MAPPING WITH APPLICATION TO WTCCC TYPE 1 DIABETES DATA

Interactions among multiple genes across the genome may contribute to the risks of many complex human diseases. Whole-genome single nucleotide polymorphisms (SNPs) data collected for many thousands of SNP markers from thousands of individuals under the case-control design promise to shed light on our understanding of such interactions. However, nearby SNPs are highly correlated due to linkage disequilibrium (LD) and the number of possible interactions is too large for exhaustive evaluation. We propose a novel Bayesian method for simultaneously partitioning SNPs into LD-blocks and selecting SNPs within blocks that are associated with the disease, either individually or interactively with other SNPs. When applied to homogeneous population data, the method gives posterior probabilities for LD-block boundaries, which not only result in accurate block partitions of SNPs, but also provide measures of partition uncertainty. When applied to case-control data for association mapping, the method implicitly filters out SNP associations created merely by LD with disease loci within the same blocks. Simulation study showed that this approach is more powerful in detecting multi-locus associations than other methods we tested, including one of ours. When applied to the WTCCC type 1 diabetes data, the method identified many previously known T1D associated genes, including PTPN22, CTLA4, MHC, and IL2RA. The method also revealed some interesting two-way associations that are undetected by single SNP methods. Most of the significant associations are located within the MHC region. Our analysis showed that the MHC SNPs form long-distance joint associations over several known recombination hotspots. By controlling the haplotypes of the MHC class II region, we identified additional associations in both MHC class I (HLA-A, HLA-B) and class III regions (BAT1). We also observed significant interactions between genes PRSS16, ZNF184 in the extended MHC region and the MHC class II genes. The proposed method can be broadly applied to the classification problem with correlated discrete covariates.

Bayesian models for detecting epistatic interactions from genetic data

Current disease association studies are routinely conducted on a genome-wide scale, testing hundreds of thousands or millions of genetic markers. Besides detecting marginal associations of individual markers with the disease, it is also of interest to identify gene-gene and gene-environment interactions, which confer susceptibility to the disease risk. The astronomical number of possible combinations of markers and environmental factors, however, makes interaction mapping a daunting task both computationally and statistically. In this paper, we review and discuss a set of Bayesian partition methods developed recently for mapping single-nucleotide polymorphisms in case-control studies, their extension to quantitative traits, and further generalization to multiple traits. We use simulation and real data sets to demonstrate the performance of these methods, and we compare them with some existing interaction mapping algorithms. With the recent advance in high-throughput sequencing technologies, genome-wide measurements of epigenetic factor enrichment, structural variations, and transcription activities become available at the individual level. The tsunami of data creates more challenges for gene-gene interaction mapping, but at the same time provides new opportunities that, if utilized properly through sophisticated statistical means, can improve the power of mapping interactions at the genome scale.

Haplotypes of the human RET proto-oncogene associated with Hirschsprung disease in the Italian population derive from a single ancestral combination of alleles

The RET proto-oncogene is the major gene involved in the complex genetics of Hirschsprung disease (HSCR), or aganglionic megacolon, showing causative loss-of-function mutations in 15-30% of the sporadic cases. Several RET polymorphisms and haplotypes have been described in association with the disease, suggesting a role for this gene in HSCR predisposition, also in the absence of mutations in the coding region. Finally, the presence of a functional variant in intron 1 has repeatedly been proposed to explain such findings. Here we report a case-control study conducted on 97 Italian HSCR sporadic patients and 85 population matched controls, using 13 RET polymorphisms distributed throughout the gene, from the basal promoter to the 3'UTR. Linkage disequilibrium and haplotype analyses have shown increased recombination between the 5' and 3' portions of the gene and an over-representation, in the cases studied, of two haplotypes sharing a common allelic combination that extends from the promoter up to intron 5. We propose that these two disease-associated haplotypes derive from a single founding locus, extending up to intron 19 and successively rearranged in correspondence with a high recombination rate region located between the proximal and distal portions of the gene. Our results suggests the possibility that a common HSCR predisposing variant, in linkage disequilibrium with such haplotypes, is located further downstream than the previously suggested interval encompassing intron 1.

Polymorphism in the activity of human crossover hotspots independent of local DNA sequence variation

Meiotic crossovers in the human genome cluster into highly localized hotspots identifiable indirectly from patterns of DNA diversity and directly by high-resolution sperm typing. Little is known about factors that control hotspot activity and the apparently rapid turnover of hotspots during recent evolution. Clues can, however, be gained by characterizing variation in sperm crossover activity between men. Previous studies have identified single nucleotide polymorphisms within hotspots that appear to suppress crossover activity and which may be involved in hotspot attenuation/extinction. We now analyse a closely spaced pair of hotspots (MSTM1a, MSTM1b) on chromosome 1q42.3, the former being a candidate for a young hotspot that has failed to leave a significant mark on haplotype diversity. Extensive surveys of different men revealed substantial polymorphism in sperm crossover frequencies at both hotspots, but with very different patterns of variation. Hotspot MSTM1b was active in all men tested but with widely differing crossover frequencies. In contrast, MSTM1a was active in only a few men and appeared to be recombinationally inert in the remainder, providing the first example of presence/absence polymorphism of a human hotspot. Haplotype analysis around both hotspots identified active and suppressed men sharing identical haplotypes, establishing that these major variations in the presence/absence of a hotspot and in quantitative activity are not caused by local DNA sequence variation. These findings suggest a role for distal regulators or epigenetic factors in hotspot activity and provide the first direct evidence for the rapid evolution of recombination hotspots in humans.

A detailed Hapmap of the Sitosterolemia locus spanning 69 kb; differences between Caucasians and African-Americans

Background

Sitosterolemia is an autosomal recessive disorder that maps to the sitosterolemia locus, STSL, on human chromosome 2p21. Two genes, ABCG5 and ABCG8, comprise the STSL and mutations in either cause sitosterolemia. ABCG5 and ABCG8 are thought to have evolved by gene duplication event and are arranged in a head-to-head configuration. We report here a detailed characterization of the STSL in Caucasian and African-American cohorts.

Methods

Caucasian and African-American DNA samples were genotypes for polymorphisms at the STSL locus and haplotype structures determined for this locus

Results

In the Caucasian population, 13 variant single nucleotide polymorphisms (SNPs) were identified and resulting in 24 different haplotypes, compared to 11 SNPs in African-Americans resulting in 40 haplotypes. Three polymorphisms in ABCG8 were unique to the Caucasian population (E238L, INT10-50 and G575R), whereas one variant (A259V) was unique to the African-American population. Allele frequencies of SNPs varied also between these populations.

Conclusion

We confirmed that despite their close proximity to each other, significantly more variations are present in ABCG8 compared to ABCG5. Pairwise D' values showed wide ranges of variation, indicating some of the SNPs were in strong linkage disequilibrium (LD) and some were not. LD was more prevalent in Caucasians than in African-Americans, as would be expected. These data will be useful in analyzing the proposed role of STSL in processes ranging from responsiveness to cholesterol-lowering drugs to selective sterol absorption.

Allelic recombination and de novo deletions in sperm in the human beta-globin gene region

Meiotic recombination is of fundamental importance in creating haplotype diversity in the human genome and has the potential to cause genomic rearrangements by ectopic recombination between repeat sequences and through other changes triggered by recombination-initiating events. However, the relationship between allelic recombination and genome instability in the human germline remains unclear. We have therefore analysed recombination and DNA instability in the delta-, beta-globin gene region and its associated recombination hotspot. Sperm typing has for the first time accurately defined the hotspot and shown it to be the most active autosomal crossover hotspot yet described, although unusually inactive in non-exchange gene conversion. The hotspot just extends into a homology block shared by the delta- and beta-globin genes, within which ectopic exchanges can generate Hb Lepore deletions. We developed a physical selection method for recovering and validating extremely rare de novo deletions in human DNA and used it to characterize the dynamics of these Hb Lepore deletions in sperm as well as other deletions not arising from ectopic exchanges between homologous DNA sequences. Surprisingly, both classes of deletion showed breakpoints that avoided the beta-globin hotspot, establishing that it possesses remarkable fidelity and does not play a significant role in triggering these DNA rearrangements. This study also provides the first direct analysis of de novo deletion in the human germline and points to a possible deletion-controlling element in the beta-globin gene separate from the crossover hotspot.

Localized breakdown in linkage disequilibrium does not always predict sperm crossover hot spots in the human MHC class II region

To investigate the relationship between meiotic crossover hot spots and block-like linkage disequilibrium (LD), we have extended our high-resolution studies of the human MHC class II region to a 90-kb segment upstream of the HLA-DOA gene. LD blocks in this region are not as well defined as in the neighboring 210-kb DNA segment but do show two regions of LD breakdown in which coalescent analysis indicates substantial historical recombination. Sperm crossover analysis of one region revealed a novel localized hot spot similar in intensity and morphology to most other MHC hot spots. Crossovers at this hot spot are not obviously affected by a large insertion/deletion polymorphism near the hot spot. The second region of LD breakdown, within the DPB1 gene, shows an extremely low level of sperm crossover activity and does not contain a sperm crossover hot spot. These results highlight the complexity of LD patterns and the importance of experimentally verifying crossover hot spots.

Linkage disequilibrium patterns vary substantially among populations

A major initiative to create a global human haplotype map has recently been launched as a tool to improve the efficiency of disease gene mapping. The 'HapMap' project will study common variants in depth in four (and to a lesser degree in up to 12) populations to catalogue haplotypes that are expected to be common to all populations. A hope of the 'HapMap' project is that much of the genome occurs in regions of limited diversity such that only a few of the SNPs in each region will capture the diversity and be relevant around the world. In order to explore the implications of studying only a limited number of populations, we have analyzed linkage disequilibrium (LD) patterns of three 175-320 kb genomic regions in 16 diverse populations with an emphasis on African and European populations. Analyses of these three genomic regions provide empiric demonstration of marked differences in frequencies of the same few haplotypes, resulting in differences in the amount of LD and very different sets of haplotype frequencies. These results highlight the distinction between the statistical concept of LD and the biological reality of haplotypes and their frequencies. The significant quantitative and qualitative variation in LD among populations, even for populations within a geographic region, emphasizes the importance of studying diverse populations in the HapMap project to assure broad applicability of the results.

Haplotype diversity in 11 candidate genes across four populations

Analysis of haplotypes based on multiple single-nucleotide polymorphisms (SNP) is becoming common for both candidate gene and fine-mapping studies. Before embarking on studies of haplotypes from genetically distinct populations, however, it is important to consider variation both in linkage disequilibrium (LD) and in haplotype frequencies within and across populations, as both vary. Such diversity will influence the choice of "tagging" SNPs for candidate gene or whole-genome association studies because some markers will not be polymorphic in all samples and some haplotypes will be poorly represented or completely absent. Here we analyze 11 genes, originally chosen as candidate genes for oral clefts, where multiple markers were genotyped on individuals from four populations. Estimated haplotype frequencies, measures of pairwise LD, and genetic diversity were computed for 135 European-Americans, 57 Chinese-Singaporeans, 45 Malay-Singaporeans, and 46 Indian-Singaporeans. Patterns of pairwise LD were compared across these four populations and haplotype frequencies were used to assess genetic variation. Although these populations are fairly similar in allele frequencies and overall patterns of LD, both haplotype frequencies and genetic diversity varied significantly across populations. Such haplotype diversity has implications for designing studies of association involving samples from genetically distinct populations.

Genome amplification of single sperm using multiple displacement amplification

Sperm typing is an effective way to study recombination rate on a fine scale in regions of interest. There are two strategies for the amplification of single meiotic recombinants: repulsion-phase allele-specific PCR and whole genome amplification (WGA). The former can selectively amplify single recombinant molecules from a batch of sperm but is not scalable for high-throughput operation. Currently, primer extension pre-amplification is the only method used in WGA of single sperm, whereas it has limited capacity to produce high-coverage products enough for the analysis of local recombination rate in multiple large regions. Here, we applied for the first time a recently developed WGA method, multiple displacement amplification (MDA), to amplify single sperm DNA, and demonstrated its great potential for producing high-yield and high-coverage products. In a 50 mul reaction, 76 or 93% of loci can be amplified at least 2500- or 250-fold, respectively, from single sperm DNA, and second-round MDA can further offer >200-fold amplification. The MDA products are usable for a variety of genetic applications, including sequencing and microsatellite marker and single nucleotide polymorphism (SNP) analysis. The use of MDA in single sperm amplification may open a new era for studies on local recombination rates.

Gametic phase estimation over large genomic regions using an adaptive window approach

The authors present ELB, an easy to programme and computationally fast algorithm for inferring gametic phase in population samples of multilocus genotypes. Phase updates are made on the basis of a window of neighbouring loci, and the window size varies according to the local level of linkage disequilibrium. Thus, ELB is particularly well suited to problems involving many loci and/or relatively large genomic regions, including those with variable recombination rate. The authors have simulated population samples of single nucleotide polymorphism genotypes with varying levels of recombination and marker density, and find that ELB provides better local estimation of gametic phase than the PHASE or HTYPER programs, while its global accuracy is broadly similar. The relative improvement in local accuracy increases both with increasing recombination and with increasing marker density. Short tandem repeat (STR, or microsatellite) simulation studies demonstrate ELB's superiority over PHASE both globally and locally. Missing data are handled by ELB; simulations show that phase recovery is virtually unaffected by up to 2 per cent of missing data, but that phase estimation is noticeably impaired beyond this amount. The authors also applied ELB to datasets obtained from random pairings of 42 human X chromosomes typed at 97 diallelic markers in a 200 kb low-recombination region. Once again, they found ELB to have consistently better local accuracy than PHASE or HTYPER, while its global accuracy was close to the best.

Recovering frequencies of known haplotype blocks from single-nucleotide polymorphism allele frequencies

Prospects for large-scale association studies rely on economical methods and powerful analysis. Representing available SNPs by small subsets and measuring allele frequencies on pooled DNA samples each improve genotyping cost effectiveness, while haplotype analysis may highlight associations in otherwise underpowered studies. This manuscript provides the mathematical framework to integrate these methodologies.

Applying a new generation of genetic maps to understand human inflammatory disease

The sequencing of the human genome and the intense study of its variation in different human populations have improved our understanding of the genome's architecture. It is now becoming clear that segments of the genome that are unbroken by reshuffling or recombination during meiosis create a mosaic of DNA 'haplotype blocks'. Here, we discuss the advantages and limitations of this block structure. Haplotype blocks hold the promise of reducing the complexity of analysing the human genome for association with disease. But can they deliver on this promise? First generation maps of these block patterns, such as the admixture and haplotype maps, are now emerging and, it is to be hoped, will accelerate the discovery of alleles that contribute to susceptibility to human inflammatory diseases.

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.

Advances in pharmacogenomics and individualized drug therapy: exciting challenges that lie ahead

Between the 1930s and 1990s, several dozen predominantly monogenic, high-penetrance disorders involving pharmacogenetics were described, fueling the crusade that gene-drug interactions are quite simple. Then, in 1990, the Human Genome Project was established; in 1995, the term pharmacogenomics was introduced; finally, the complexities of determining an unequivocal phenotype, as well as an unequivocal genotype, have recently become apparent. Since 1965, more than 1000 reviews on this topic have painted an overly optimistic picture-suggesting that the advent of individualized drug therapy used by the practicing physician is fast approaching. For many reasons listed here, however, we emphasize that these high expectations must be tempered. We now realize that the nucleotide sequence of the genome represents only a starting point from which we must proceed to a more difficult stage: knowledge of the function encoded and how this affects the phenotype. To achieve individualized drug therapy, a high level of accuracy and precision is required of any clinical test proposed in human patients. Finally, we suggest that metabonomics, perhaps in combination with proteomics, might complement genomics in eventually helping us to achieve individualized drug therapy.

Human haplotype block sizes are negatively correlated with recombination rates

The International Haplotype Map ("HapMap") Project is motivated, in part, by the belief that the organization of the human genome, the mechanics of recombination, and the population-level behavior of alleles at adjacent loci should allow researchers to parse the genome into small segments, or "blocks," that show strong linkage disequilibrium (LD) between alleles at loci within those segments. The discovery and evidence for these blocks is to be based solely on the observed LD strength and patterns between alleles at adjacent loci throughout the genome. Although there are many factors that contribute to LD strength, we assessed the correlation between block structure, in terms of length and percentage of the genome assembled into blocks within a region, and recombination rate obtained from two independent sources. We found evidence of a striking negative correlation between the average recombination rate and average block length, suggesting that recombination rate is a strong contributor to haplotype block structure within the genome. We discuss the potential implications of this negative correlation in the context of the organization, properties, and potential ubiquity of a block-like structure in the human genome.

Comparative high-resolution analysis of linkage disequilibrium and tag single nucleotide polymorphisms between populations in the vitamin D receptor gene

A genome-wide map of single nucleotide polymorphisms (SNP) and a pattern of linkage disequilibrium (LD) between their alleles are being established in three main ethnic groups. An important question is the applicability of such maps to different populations within a main ethnic group. Therefore, we have developed high-resolution SNP, haplotype and LD maps of vitamin D receptor gene region in large samples from five populations. Comparative analysis reveals that the LD patterns are identical in all four European populations tested with two small regions of 1.3 and 5.7 kb at which LD is disrupted completely resulting in three block-like regions over which there is significant and extensive LD. In an African population the pattern is similar, but two additional LD-breaking spots are also apparent. This LD pattern suggests combined action of recombination hotspots and founder effects, but cannot be explained by random recombination and genetic drift alone. Direct comparison indicates that the tag SNPs selected in one European population effectively predict the non-tag SNPs in the other Europeans, but not in the Gambians, for this region.

Haplotype diversity across 100 candidate genes for inflammation, lipid metabolism, and blood pressure regulation in two populations

Recent studies have suggested that a significant fraction of the human genome is contained in blocks of strong linkage disequilibrium, ranging from ~5 to >100 kb in length, and that within these blocks a few common haplotypes may account for >90% of the observed haplotypes. Furthermore, previous studies have suggested that common haplotypes in candidate genes are generally shared across populations and represent the majority of chromosomes in each population. The conclusions drawn from these preliminary studies, however, are based on an incomplete knowledge of the variation in the regions examined. To bridge this gap in knowledge, we have completely resequenced 100 candidate genes in a population of African descent and one of European descent. Although these genes have been well studied because of their medical importance, we demonstrate that a large amount of sequence variation has not yet been described. We also report that the average number of inferred haplotypes per gene, when complete data is used, is higher than in previous reports and that the number and proportion of all haplotypes represented by common haplotypes per gene is variable. Furthermore, we demonstrate that haplotypes shared between the two populations constitute only a fraction of the total number of haplotypes observed and that these shared haplotypes represent fewer of the African-descent chromosomes than was expected from previous studies. Finally, we show that restricting variation discovery to coding regions does not adequately describe all common haplotypes or the true haplotype block structure observed when all common variation is used to infer haplotypes. These data, derived from complete knowledge of genetic variation in these genes, suggest that the haplotype architecture of candidate genes across the human genome is more complex than previously suggested, with important implications for candidate gene and genomewide association studies.

Will haplotype maps be useful for finding genes?

From its introduction into the literature, the idea of haplotype map-based linkage disequilibrium (LD) studies has been the subject of disputes. These queries involve the extent to which the haplotype blocks exist, the validity of fundamental concepts such as the recombination hotspot, and the application of this idea in the form of the HapMap project. In this article, we review the relevant literature to evaluate the potential importance of haplotype maps for psychiatric genetics. We first take a closer look at the nature of haplotype blocks and then address the impact of block definitions and methodological factors, such as single-nucleotide polymorphism density and sample size, on findings from haplotype block studies. After distinguishing between two types of haplotype map-based LD studies, we discuss the importance of the recombination hotspot and the nature of the disease mutations affecting complex traits. In the final section, we summarize our main conclusions and comment on the usefulness of haplotype maps for finding genes.

Patterns of linkage disequilibrium in the MHC region on human chromosome 6p

Single nucleotide polymorphisms (SNPs) in the human genome are thought to be organised into blocks of high internal linkage disequilibrium (LD), separated by intermittent recombination hotspots. Since understanding haplotype structure is critical for an accurate assessment of inter-individual genetic differences, we investigated up to 968 SNPs from a 10-Mb region on chromosome 6p21, including the human major histocompatibility complex (MHC), in five different population samples (45-550 individuals). Regions of well-defined block structure were found to coexist alongside large areas lacking any clear structure; occasional long-range LD was observed in all five samples. The four white populations analysed were remarkably similar in terms of the extend and spatial distribution of local LD. In US African Americans, the distribution of LD was similar to that in the white populations but the observed haplotype diversity was higher. The existence of large regions without any clear block structure renders the systematic and thorough construction of SNP haplotype maps a crucial prerequisite for disease-association studies.

The impact of SNP density on fine-scale patterns of linkage disequilibrium

Linkage disequilibrium (LD) is a measure of the degree of association between alleles in a population. The detection of disease-causing variants by association with neighbouring single nucleotide polymorphisms (SNPs) depends on the existence of strong LD between them. Previous studies have indicated that the extent of LD is highly variable in different chromosome regions and different populations, demonstrating the importance of genome-wide accurate measurement of LD at high resolution throughout the human genome. A uniform feature of these studies has been the inability to detect LD in regions of low marker density. To investigate the dependence of LD patterns on marker selection we performed a high-resolution study in African-American, Asian and UK Caucasian populations. We selected over 5000 SNPs with an average spacing of approximately 1 SNP per 2 kb after validating ca 12 000 SNPs derived from a dense SNP collection (1 SNP per 0.3 kb on average). Applications of different statistical methods of LD assessment highlight similar areas of high and low LD. However, at high resolution, features such as overall sequence coverage in LD blocks and block boundaries vary substantially with respect to marker density. Model-based linkage disequilibrium unit (LDU) maps appear robust to marker density and consistently influenced by marker allele frequency. The results suggest that very dense marker sets will be required to yield stable views of fine-scale LD in the human genome.

Population-genetic basis of haplotype blocks in the 5q31 region

We investigated patterns of nucleotide variation in the 5q31 region identified by Daly et al. as containing haplotype blocks, to determine whether the blocklike pattern requires the assumption of hotspots in recombination. Using extensive simulations that generate data matched to the Daly et al. data set in (a) the method of ascertainment of single-nucleotide polymorphisms, (b) the heterozygosity of ascertained markers, (c) the number of block boundaries, and (d) the diversity of haplotypes within blocks, we show that the patterns found in the Daly et al. data are not consistent with the assumption of uniform recombination in a population of constant size but are consistent either with the presence of hotspots in a population of constant size or with the absence of hotspots if there was a period of rapid population growth. We further show that estimates of local recombination rate can distinguish between population growth and hotspots as the primary cause of a blocklike pattern. Estimates of local recombination rates for the Daly et al. data do not indicate the presence of recombination hotspots.

Defining haplotype blocks and tag single-nucleotide polymorphisms in the human genome

Recent studies suggest that the genome is organized into blocks of haplotypes, and efforts to create a genome-wide haplotype map of single-nucleotide polymorphisms (SNPs) are already underway. Haplotype blocks are defined algorithmically and to date several algorithms have been proposed. However, little is known about their relative performance in real data or about the impact of allele frequencies and parameter choices on the detection of haplotype blocks and the markers that tag them. Here we present a formal comparison of two major algorithms, a linkage disequilibrium (LD)-based method and a dynamic programming algorithm (DPA), in three chromosomal regions differing in gene content and recombination rate. The two methods produced strikingly different results. DPA identified fewer and larger haplotype blocks as well as a smaller set of tag SNPs than the LD method. For both methods, the results were strongly dependent on the allele frequency. Decreasing the minor allele frequency led to an up to 3.7-fold increase in the number of haplotype blocks and tag SNPs. Definition of haploytpe blocks and tag SNPs was also sensitive to parameter changes, but the results could not be reconciled simply by parameter adjustment. These results show that two major methods for detecting haplotype blocks and tag SNPs can produce different results in the same data and that these results are sensitive to marker allele frequencies and parameter choices. More information is needed to guide the choice of method, marker allele frequencies, and parameters in the development of a haplotype map.

On the applicability of a haplotype map to un-assayed populations

The rationale for mapping all common haplotypes in our species relies on reports of the conservation of haplotype blocks across human populations. Recent findings indicate that these blocks may, at least in part, be a random artifact of genetic drift. This raises the concern that the latter process may challenge the general applicability of a human haplotype map to case-by-case population-specific association studies. We develop arguments indicating that even stochastic drift-originated blocks will, under many conditions, be shared across populations, supporting the utilization of a panhuman haplotype map.