Assessing the feasibility of linkage disequilibrium methods for mapping complex traits: an initial screen for bipolar disorder loci on chromosome 18.

Linkage disequilibrium (LD) analysis has been promoted as a method of mapping disease genes, particularly in isolated populations, but has not yet been used for genome-screening studies of complex disorders. We present results of a study to investigate the feasibility of LD methods for genome screening using a sample of individuals affected with severe bipolar mood disorder (BP-I), from an isolated population of the Costa Rican central valley. Forty-eight patients with BP-I were genotyped for markers spaced at approximately 6-cM intervals across chromosome 18. Chromosome 18 was chosen because a previous genome-screening linkage study of two Costa Rican families had suggested a BP-I locus on this chromosome. Results of the current study suggest that LD methods will be useful for mapping BP-I in a larger sample. The results also support previously reported possible localizations (obtained from a separate collection of patients) of BP-I-susceptibility genes at two distinct sites on this chromosome. Current limitations of LD screening for identifying loci for complex traits are discussed, and recommendations are made for future research with these methods.     

Wide variation in ploidy level and genome size in a New Zealand freshwater snail with coexisting sexual and asexual lineages

Natural animal populations are rarely screened for ploidy-level variation at a scale that allows detection of potentially important aberrations of common ploidy patterns. This type of screening can be especially important for the many mixed sexual/asexual systems in which sexuals are presumed to be dioecious diploids and asexuals are assumed to be triploid and all-female. For example, elevation of ploidy level above triploidy can be a source of genetic variation and raises the possibility of gene flow among ploidy levels and to asexual lineages. We used flow cytometry and mtDNA sequencing to characterize ploidy level and genome size in Potamopyrgus antipodarum, a New Zealand freshwater snail where obligate sexual (presumed diploid and dioecious) and obligate apomictic asexual (presumed triploid and nearly all female) individuals frequently coexist. We documented the widespread occurrence and multiple origins of polyploid males and individuals with >3× ploidy, and find that both are likely to be descended from asexual females. Our survey also suggested the existence of extensive variation in genome size. The discovery of widespread variation in ploidy level and genome size in such a well-studied system highlights the importance of broad, extensive, and ecologically representative sampling in uncovering ploidy level and genome-size variation in natural populations.     

PSEUDOMARKER: a powerful program for joint linkage and/or linkage disequilibrium analysis on mixtures of singletons and related individuals

A decade ago, there was widespread enthusiasm for the prospects of genome-wide association studies to identify common variants related to common chronic diseases using samples of unrelated individuals from populations. Although technological advancements allow us to query more than a million SNPs across the genome at low cost, a disappointingly small fraction of the genetic portion of common disease etiology has been uncovered. This has led to the hypothesis that less frequent variants might be involved, stimulating a renaissance of the traditional approach of seeking genes using multiplex families from less diverse populations. However, by using the modern genotyping and sequencing technology, we can now look not just at linkage, but jointly at linkage and linkage disequilibrium (LD) in such samples. Software methods that can look simultaneously at linkage and LD in a powerful and robust manner have been lacking. Most algorithms cannot jointly analyze datasets involving families of varying structures in a statistically or computationally efficient manner. We have implemented previously proposed statistical algorithms in a user-friendly software package, PSEUDOMARKER. This paper is an announcement of this software package. We describe the motivation behind the approach, the statistical methods, and software, and we briefly demonstrate PSEUDOMARKER's advantages over other packages by example.     

High-Resolution Multipoint Linkage-Disequilibrium Mapping in the Context of a Human Genome Sequence

A new method is presented for fine-scale linkage disequilibrium (LD) mapping of a disease mutation; it uses multiple linked single-nucleotide polymorphisms, restriction-fragment-length polymorphisms, or microsatellite markers and incorporates information from an annotated human genome sequence (HGS) and from a human mutation database. The method takes account of population demographic effects, using Markov chain Monte Carlo methods to integrate over the unknown gene genealogy and gene coalescence times. Information about the relative frequency of disease mutations in exons, introns, and other regions, from mutational databases, as well as assumptions about the completeness of the gene annotation, are used with an annotated HGS, to generate a prior probability that a mutation lies at any particular position in a specified region of the genome. This information is updated with information about mutation location, from LD at a set of linked markers in the region, to generate the posterior probability density of the mutation location. The performance of the method is evaluated by simulation and by analysis of a data set for diastrophic dysplasia (DTD) in Finland. The DTD disease gene has been positionally cloned, so the actual location of the mutation is known and can be compared with the position predicted by our method. For the DTD data, the addition of information from an HGS results in disease-gene localization at a resolution that is much higher than that which would be possible by LD mapping alone. In this case, the gene would be found by sequencing a region < or =7 kb in size.     

Improving power in contrasting linkage-disequilibrium patterns between cases and controls

Genetic association studies offer an opportunity to find genetic variants underlying complex human diseases. The success of this approach depends on the linkage disequilibrium (LD) between markers and the disease variant(s) in a local region of the genome. Because, in the region with a disease mutation, the LD pattern among markers may differ between cases and controls, in some scenarios, it is useful to compare a measure of this LD, to map disease mutations. For example, using the composite correlation to characterize the LD among markers, Zaykin et al. recently suggested an "LD contrast" test and showed that it has high power under certain haplotype-driven disease models. Furthermore, it is likely that individual variants observed at different positions in a gene act jointly with each other to influence the phenotype, and the LD contrast test is also a useful method to detect such joint action. However, the LD among markers introduced by mutations and their joint action is usually confounded by background LD, which is measured at the population level, especially in a local region with disease mutations. Because the measures of LD that are usually used, such as the composite correlation, represent both effects, they may not be optimal for the purpose of detecting association when high background LD exists. Here, we describe a test that improves the LD contrast test by taking into account the background LD. Because the proposed test is developed in a regression framework, it is very flexible and can be extended to continuous traits and to incorporate covariates. Our simulation results demonstrate the validity and substantially higher power of the proposed method over current methods. Finally, we illustrate our new method by applying it to real data from the International Collaborative Study on Hypertension in Blacks.     

Navigating the HapMap

With the availability of the HapMap--a resource which describes common patterns of linkage disequilibrium (LD) in four different human population samples, we now have a powerful tool to help dissect the role of genetic variation in the biology of the genome. HapMap is entirely complimentary to the human genome map and so it is particularly fitting that it should be viewed in a full genomic context. However, characterization of high resolution LD across the genome can be a challenging task, owing in part to the sheer volume of data and the inherent dimensionality that its analysis entails. However, a number of tools are now available to make this task easier for researchers. This review will examine tools for viewing and analysing haplotype and LD data, enabling a number of tasks; including identification of optimal sets of haplotype tagging single nucleotide polymorphisms (SNPs); drawing links between associated SNPs and putative causal alleles; or simply viewing LD and haplotypes across a gene or region of interest. The data generated by the HapMap also has other important applications, informing, for example, on the demographic history and evidence of selection in human populations and on previously undetected regulatory relationships and gene networks. All of these properties make the HapMap no less an important resource than the human genome sequence itself and so this makes it essential viewing for all in the field of human biology.     

Autosomal dominant myopathy with proximal weakness and early respiratory muscle involvement maps to chromosome 2q

Two Swedish families with autosomal dominant myopathy, who also had proximal weakness, early respiratory failure, and characteristic cytoplasmic bodies in the affected muscle biopsies, were screened for linkage by means of the human genome screening set (Cooperative Human Linkage Center Human Screening Set/Weber version 6). Most chromosome regions were completely excluded by linkage analysis (LOD score <-2). Linkage to the chromosomal region 2q24-q31 was established. A maximum combined two-point LOD score of 4.87 at a recombination fraction of 0 was obtained with marker D2S1245. Haplotype analysis indicated that the gene responsible for the disease is likely to be located in the 17-cM region between markers D2S2384 and D2S364. The affected individuals from these two families share an identical haplotype, which suggests a common origin.     

An isochore transition in the NF1 gene region coincides with a switch in the extent of linkage disequilibrium

Whole-genome association studies will be a powerful tool to identify genes responsible for common human diseases. A crucial task for association-mapping studies is the evaluation of the relationship between linkage disequilibrium (LD) and physical distance for the genomic region under study. Since it is known that the extent of LD is nonuniformly distributed throughout the human genome, the required marker density has to be determined specifically for the region under study. These regions may be related to isochores and chromosomal bands, as indicated by earlier cytogenetic findings concerning chiasma distribution in meiosis. Therefore we analyzed the neurofibromatosis type 1 (NF1) gene region on chromosome 17q11.2, which is characterized by a nonuniform LD pattern and an L1-to-H2 isochore transition. Long-range LD within the NF1 gene was found to extend over 200 kb (D' = 0.937) in the L1 isochore, whereas, in the neighboring H2 isochore, no LD is apparent between markers spaced by 26 kb (D' = 0.144). Recombination frequencies derived from the LD are at.00019 (high LD) and.01659 (low LD) per megabase, the latter identical to the average value from segregation analysis. The boundary between these regions coincides precisely with a transition in the GC content of the sequences, with low values (37.2%) in the region with long-range LD and high values (51%) in the other. Our results suggest a correlation between the LD pattern and the isochores, at least in the NF1 region. If this correlation can be generalized, the marker densities required for association studies have to be adjusted to the regional GC content and may be chosen according to the isochores.     

Using haplotype blocks to map human complex trait loci

Understanding of linkage disequilibrium (LD) in human populations could facilitate the discovery of genes that influence complex human diseases. The "HapMap" project is now underway to characterize patterns of LD in the human genome. A pilot study showed "haplotype blocks" in 51 regions scattered throughout the genome. These intriguing results raise important questions about the nature of recombination, and highlight practical issues of marker collection, the influence of statistical modelling on apparent block structure, and the levels of genotyping necessary for studies of common diseases. Knowledge of local disequilibrium patterns may help identify common polymorphisms involved in complex disease, but completely new analytical methods and experimental designs will be required to identify important rare variants.     

Novel linkage mapping approach using DNA pooling in human and animal genetics. I. Detection of complex disease loci

DNA pooling is a potential methodology for genetic loci with small effect contributing to complex diseases and quantitative traits. This is accomplished by the rapid preliminary screening of the genome for the allelic association with the most common class of polymorphic short tandem repeat markers. The methodology assumes as a common founder for the linked disease locus of interest and searches for a region of a chromosome shared between affected individuals. The general theory of DNA pooling basically relies on the observed differences in the allelic distribution between pools from affected and unaffected individuals, including a reduction in the number of alleles in the affected pool, which indicate the sharing of a chromosomal region. The power of statistic for associated linkage mapping can be determined using two recently developed strategies, firstly, by measuring the differences of allelic image patterns produced by two DNA pools of extreme character and secondly, by measuring total allele content differences by comparing between two pools containing large numbers of DNA samples. These strategies have effectively been utilized to identify the shared chromosomal regions for linkage studies and to investigate the candidate disease loci for fine structure gene mapping using allelic association. This paper outlines the utilization of DNA pooling as a potential tool to locate the complex disease loci, statistical methods for accurate estimates of allelic frequencies from DNA pools, its advantages, drawbacks and significance in associate linkage mapping using pooled DNA samples.     

Extensive linkage disequilibrium,a common 16.7-kilobase deletion,and evidence of balancing selection in the human protocadherin alpha cluster

Regions of extensive linkage disequilibrium (LD) appear to be a common feature of the human genome. However, the mechanisms that maintain these regions are unknown. In an effort to understand whether gene density contributes to LD, we determined the degree of promoter sequence variation in a large tandem-arrayed gene family, the human protocadherin alpha cluster, on chromosome 5. These genes are expressed at synaptic junctions in the developing brain and the adult brain and may be involved in the determination of synaptic complexity. We sequenced the promoters of all 13 alpha protocadherin genes in 96 European Americans and identified polymorphisms in the promoters alpha 1, alpha 3, alpha 4, alpha 5, alpha 7, alpha 9, alpha 11, and alpha 13. In these promoters, 11 common SNPs are in extensive LD, forming two 48-kb haplotypes of equal frequency, in this population, that extend from the alpha1 through alpha 7 genes. We sequenced these promoters in East Asians and African Americans, and we estimated haplotype frequencies and calculated LD statistics for all three populations. Our results indicate that, although extensive LD is an ancient feature of the alpha cluster, it has eroded over time. SNPs 3' of alpha 7 are involved in ancestral recombination events in all populations, and overall alpha-cluster LD is reduced in African Americans. We obtained significant positive values for Tajima's D test for all alpha promoter SNPs in Europeans (D=3.03) and East Asians (D=2.64), indicating an excess of intermediate-frequency variants, which is a signature of balancing selection. We also discovered a 16.7-kb deletion that truncates the alpha 8 gene and completely removes the alpha 9 and alpha 10 genes. This deletion appears in unaffected individuals from multiple populations, suggesting that a reduction in protocadherin gene number is not obviously deleterious.     

Analytical correction for multiple testing in admixture mapping

Admixture mapping, using unrelated individuals from the admixture populations that result from recent mating between members of each parental population, is an efficient approach to localize disease-causing variants that differ in frequency between two or more historically separated populations. Recently, several methods have been proposed to test linkage between a susceptibility gene and a disease locus by using admixture-generated linkage disequilibrium (LD) for each of the genotyped markers. In a genome scan, admixture mapping usually tests 2,000 to 3,000 markers across the genome. Currently, either a very conservative Sidak (or Bonferroni) correction or a very time consuming simulation-based method is used to correct for the multiple tests and evaluate the overall p value. In this report, we propose a computationally efficient analytical approach for correction of the multiple tests and for calculating the overall p value for an admixture genome scan. Except for the Sidak (or Bonferroni) correction, our proposed method is the first analytical approach for correction of the multiple tests and for calculating the overall p value for a genome scan. Our simulation studies show that the proposed method gives correct overall type I error rates for genome scans in all cases, and is much more computationally efficient than simulation-based methods.     

Enhanced Localization of Genetic Samples through Linkage-Disequilibrium Correction

Characterizing the spatial patterns of genetic diversity in human populations has a wide range of applications, from detecting genetic mutations associated with disease to inferring human history. Current approaches, including the widely used principal-component analysis, are not suited for the analysis of linked markers, and local and long-range linkage disequilibrium (LD) can dramatically reduce the accuracy of spatial localization when unaccounted for. To overcome this, we have introduced an approach that performs spatial localization of individuals on the basis of their genetic data and explicitly models LD among markers by using a multivariate normal distribution. By leveraging external reference panels, we derive closed-form solutions to the optimization procedure to achieve a computationally efficient method that can handle large data sets. We validate the method on empirical data from a large sample of European individuals from the POPRES data set, as well as on a large sample of individuals of Spanish ancestry. First, we show that by modeling LD, we achieve accuracy superior to that of existing methods. Importantly, whereas other methods show decreased performance when dense marker panels are used in the inference, our approach improves in accuracy as more markers become available. Second, we show that accurate localization of genetic data can be achieved with only a part of the genome, and this could potentially enable the spatial localization of admixed samples that have a fraction of their genome originating from a given continent. Finally, we demonstrate that our approach is resistant to distortions resulting from long-range LD regions; such distortions can dramatically bias the results when unaccounted for.     

Linkage disequilibrium and heritability of copy-number polymorphisms within duplicated regions of the human genome

Studies of copy-number variation and linkage disequilibrium (LD) have typically excluded complex regions of the genome that are rich in duplications and prone to rearrangement. In an attempt to assess the heritability and LD of copy-number polymorphisms (CNPs) in duplication-rich regions of the genome, we profiled copy-number variation in 130 putative "rearrangement hotspot regions" among 269 individuals of European, Yoruba, Chinese, and Japanese ancestry analyzed by the International HapMap Consortium. Eighty-four hotspot regions, corresponding to 257 bacterial artificial chromosome (BAC) probes, showed evidence of copy-number differences. Despite a predisposing genetic architecture, no polymorphism was ever observed in the remaining 46 "rearrangement hotspots," and we suggest these represent excellent candidate sites for pathogenic rearrangements. We used a combination of BAC-based and high-density customized oligonucleotide arrays to resolve the molecular basis of structural rearrangements. For common variants (frequency >10%), we observed a distinct bias against copy-number losses, suggesting that deletions are subject to purifying selection. Heritability estimates did not differ significantly from 1.0 among the majority (30 of 34) of loci analyzed, consistent with normal Mendelian inheritance. Some of the CNPs in duplication-rich regions showed strong LD with nearby single-nucleotide polymorphisms (SNPs) and were observed to segregate on ancestral SNP haplotypes. However, LD with the best available SNP markers was weaker than has been reported for deletion polymorphisms in less complex regions of the genome. These observations may be accounted for by a low density of SNP data in duplicated regions, challenges in mapping and typing the CNPs, and the possibility that CNPs in these regions have rearranged on multiple haplotype backgrounds. Our results underscore the need for complete maps of genetic variation in duplication-rich regions of the genome.     

Genome-wide association filtering using a highly locus-specific transmission/disequilibrium test

Multimarker transmission/disequilibrium tests (TDTs) are powerful association and linkage tests used to perform genome-wide filtering in the search for disease susceptibility loci. In contrast to case/control studies, they have a low rate of false positives for population stratification and admixture. However, the length of a region found in association with a disease is usually very large because of linkage disequilibrium (LD). Here, we define a multimarker proportional TDT (mTDT _P ) designed to improve locus specificity in complex diseases that has good power compared to the most powerful multimarker TDTs. The test is a simple generalization of a multimarker TDT in which haplotype frequencies are used to weight the effect that each haplotype has on the whole measure. Two concepts underlie the features of the metric: the ‘common disease, common variant’ hypothesis and the decrease in LD with chromosomal distance. Because of this decrease, the frequency of haplotypes in strong LD with common disease variants decreases with increasing distance from the disease susceptibility locus. Thus, our haplotype proportional test has higher locus specificity than common multimarker TDTs that assume a uniform distribution of haplotype probabilities. Because of the common variant hypothesis, risk haplotypes at a given locus are relatively frequent and a metric that weights partial results for each haplotype by its frequency will be as powerful as the most powerful multimarker TDTs. Simulations and real data sets demonstrate that the test has good power compared with the best tests but has remarkably higher locus specificity, so that the association rate decreases at a higher rate with distance from a disease susceptibility or disease protective locus.     

QTL fine mapping by measuring and testing for Hardy-Weinberg and linkage disequilibrium at a series of linked marker loci in extreme samples of populations

It has recently been demonstrated that fine-scale mapping of a susceptibility locus for a complex disease can be accomplished on the basis of deviations from Hardy-Weinberg (HW) equilibrium at closely linked marker loci among affected individuals. We extend this theory to fine-scale localization of a quantitative-trait locus (QTL) from extreme individuals in populations, by means of HW and linkage-disequilibrium (LD) analyses. QTL mapping and/or linkage analyses can establish a large genomic region ( approximately 30 cM) that contains a QTL. The QTL can be fine mapped by examination of the degree of deviation from HW and LD at a series of closely linked marker loci. The tests can be performed for samples of individuals belonging to either high or low percentiles of the phenotype distribution or for combined samples of these extreme individuals. The statistical properties (the power and the size) of the tests of this fine-mapping approach are investigated and are compared extensively, under various genetic models and parameters for the QTL and marker loci. On the basis of the results, a two-stage procedure that uses extreme samples and different tests (for HW and LD) is suggested for QTL fine mapping. This two-step procedure is economic and powerful and can accurately narrow a genomic region containing a QTL from approximately 30-1 cM, a range that renders physical mapping feasible for identification of the QTL. In addition, the relationship between parameterizations of complex diseases, by means of penetrance, and those of complex quantitative traits, by means of genotypic values, is outlined. This means that many statistical genetic methods developed for searching for susceptibility loci of complex diseases can be directly adopted and/or extended to QTL mapping for quantitative traits.     

Common 5' beta-globin RFLP haplotypes harbour a surprising level of ancestral sequence mosaicism

Blocks of linkage disequilibrium (LD) in the human genome represent segments of ancestral chromosomes. To investigate the relationship between LD and genealogy, we analysed diversity associated with restriction fragment length polymorphism (RFLP) haplotypes of the 5' beta-globin gene complex. Genealogical analyses were based on sequence alleles that spanned a 12.2-kb interval, covering 3.1 kb around the psibeta gene and 6.2 kb of the delta-globin gene and its 5' flanking sequence known as the R/T region. Diversity was sampled from a Kenyan Luo population where recent malarial selection has contributed to substantial LD. A single common sequence allele spanning the 12.2-kb interval exclusively identified the ancestral chromosome bearing the "Bantu" beta(s) (sickle-cell) RFLP haplotype. Other common 5' RFLP haplotypes comprised interspersed segments from multiple ancestral chromosomes. Nucleotide diversity was similar between psibeta and R/T-delta-globin but was non-uniformly distributed within the R/T-delta-globin region. High diversity associated with the 5' R/T identified two ancestral lineages that probably date back more than 2 million years. Within this genealogy, variation has been introduced into the 3' R/T by gene conversion from other ancestral chromosomes. Diversity in delta-globin was found to lead through parts of the main genealogy but to coalesce in a more recent ancestor. The well-known recombination hotspot is clearly restricted to the region 3' of delta-globin. Our analyses show that, whereas one common haplotype in a block of high LD represents a long segment from a single ancestral chromosome, others are mosaics of short segments from multiple ancestors related in genealogies of unsuspected complexity.     

Genomic complexity of the variable region-containing chitin-binding proteins in amphioxus

Background

Genetic isolates such as the Ashkenazi Jews (AJ) potentially offer advantages in mapping novel loci in whole genome disease association studies. To analyze patterns of genetic variation in AJ, genotypes of 101 healthy individuals were determined using the Affymetrix EAv3 500 K SNP array and compared to 60 CEPH-derived HapMap (CEU) individuals. 435,632 SNPs overlapped and met annotation criteria in the two groups.

Results

A small but significant global difference in allele frequencies between AJ and CEU was demonstrated by a mean F _ST of 0.009 (P < 0.001); large regions that differed were found on chromosomes 2 and 6. Haplotype blocks inferred from pairwise linkage disequilibrium (LD) statistics (Haploview) as well as by expectation-maximization haplotype phase inference (HAP) showed a greater number of haplotype blocks in AJ compared to CEU by Haploview (50,397 vs. 44,169) or by HAP (59,269 vs. 54,457). Average haplotype blocks were smaller in AJ compared to CEU (e.g., 36.8 kb vs. 40.5 kb HAP). Analysis of global patterns of local LD decay for closely-spaced SNPs in CEU demonstrated more LD, while for SNPs further apart, LD was slightly greater in the AJ. A likelihood ratio approach showed that runs of homozygous SNPs were approximately 20% longer in AJ. A principal components analysis was sufficient to completely resolve the CEU from the AJ.

Conclusion

LD in the AJ versus was lower than expected by some measures and higher by others. Any putative advantage in whole genome association mapping using the AJ population will be highly dependent on regional LD structure.     

Genome screens using linkage disequilibrium tests: optimal marker characteristics and feasibility.

Linkage disequilibrium (LD) testing has become a popular and effective method of fine-scale disease-gene localization. It has been proposed that LD testing could also be used for genome screening, particularly as dense maps of diallelic markers become available and automation allows inexpensive genotyping of diallelic markers. We compare diallelic markers and multiallelic markers in terms of sample sizes required for detection of LD, by use of a single marker locus in a case-control study, for rare monophyletic diseases with Mendelian inheritance. We extrapolate from our results to discuss the feasibility of single-marker LD screening in more-complex situations. We have used a deterministic population genetic model to calculate the expected power to detect LD as a function of marker density, age of mutation, number of marker alleles, mode of inheritance of a rare disease, and sample size. Our calculations show that multiallelic markers always have more power to detect LD than do diallelic markers (under otherwise equivalent conditions) and that the ratio of the number of diallelic to the number of multiallelic markers needed for equivalent power increases with mutation age and complexity of mode of inheritance. Power equivalent to that achieved by a multiallelic screen can theoretically be achieved by use of a more dense diallelic screen, but mapping panels of the necessary resolution are not currently available and may be difficult to achieve. Genome screening that uses single-marker LD testing may therefore be feasible only for young (<20 generations), rare, monophyletic Mendelian diseases, such as may be found in rapidly growing genetic isolates.