The extent of linkage disequilibrium in four populations with distinct demographic histories

The association of gene polymorphisms with milk production and mastitis resistance phenotypic traits in dairy cattle

The aim of this study was to evaluate the association between gene polymorphisms (SNPs) and mastitis indicators and their relationship with milk production profitability in dairy herd.A functional analysis was also performed of five genes containing the studied SNPs and those located close by. DNA was isolated from the hair bulb of 320 dairy cows kept in three herds and SNP-microarray analysis was performed. The data on 299 cows was subjected to final statistical analysis using AI-REML method with one-trait repeatability test-day animal model and pedigree information using the DMU4 package. Five from 35 SNPs significantly associated with mastitis indicators or production traits and located within a gene or no more than 500,000 nucleotides from the gene were selected for the functional and economic analysis. A questionnaire was also developed to collect associated economic data of 219 cows from three herds, such as the value of milk production and direct costs incurred over three years; this allowed the gross margin, direct profitability index and direct costs incurred to produce one liter of milk to be determined, among others. None of the five studied SNPs were related to protein content. The rs110785912(T/A), found near CXCR4, and rs136813430(T/C), located in the TLR4 gene exon, were associated with lnSCC, while rs110455063(C/G), located near IGFI, was associated with milk yield, fat and total solid contents. rs109421300(T/C), associated with fat/protein content ratio, as well as fat and total solid content, is located in the DGAT1 gene intron. rs41587003(A/C), located in the DLG2 gene intron, was associated with lactose content. The economic analysis revealed differences between the variants of the three tested SNPs. The T/C variant of the rs136813430(T/C) SNP was characterized by the highest gross margin, the highest direct profitability index and the lowest costs incurred to produce 1 liter of milk. The T/A variant of rs110785912(T/A) was related to low lnSCC and was characterized by the highest direct profitability index. In turn, the C/C variant of the rs41587003(T/C) was related to the lowest level of lactose and the highest costs of milk production. It appears that rs136813430(T/C) may be the most promising of the tested SNPs for increasing the profitability of milk production. To our knowledge, it is the first effort to assess directly a correlation between the DNA polymorphism and economic output of a dairy enterprise.

Comparing Different Statistical Models and Multiple Testing Corrections for Association Mapping in Soybean and Maize

Association mapping (AM) is a powerful tool for fine mapping complex trait variation down to nucleotide sequences by exploiting historical recombination events. A major problem in AM is controlling false positives that can arise from population structure and family relatedness. False positives are often controlled by incorporating covariates for structure and kinship in mixed linear models (MLM). These MLM-based methods are single locus models and can introduce false negatives due to over fitting of the model. In this study, eight different statistical models, ranging from single-locus to multilocus, were compared for AM for three traits differing in heritability in two crop species: soybean (Glycine max L.) and maize (Zea mays L.). Soybean and maize were chosen, in part, due to their highly differentiated rate of linkage disequilibrium (LD) decay, which can influence false positive and false negative rates. The fixed and random model circulating probability unification (FarmCPU) performed better than other models based on an analysis of Q-Q plots and on the identification of the known number of quantitative trait loci (QTLs) in a simulated data set. These results indicate that the FarmCPU controls both false positives and false negatives. Six qualitative traits in soybean with known published genomic positions were also used to compare these models, and results indicated that the FarmCPU consistently identified a single highly significant SNP closest to these known published genes. Multiple comparison adjustments (Bonferroni, false discovery rate, and positive false discovery rate) were compared for these models using a simulated trait having 60% heritability and 20 QTLs. Multiple comparison adjustments were overly conservative for MLM, CMLM, ECMLM, and MLMM and did not find any significant markers; in contrast, ANOVA, GLM, and SUPER models found an excessive number of markers, far more than 20 QTLs. The FarmCPU model, using less conservative methods (false discovery rate, and positive false discovery rate) identified 10 QTLs, which was closer to the simulated number of QTLs than the number found by other models.

Potential of Genome-Wide Studies in Unrelated Plus Trees of a Coniferous Species, Cryptomeria japonica (Japanese Cedar)

A genome-wide association study (GWAS) was conducted on more than 30,000 single nucleotide polymorphisms (SNPs) in unrelated first-generation plus tree genotypes from three populations of Japanese cedar Cryptomeria japonica D. Don with genomic prediction for traits of growth, wood properties and male fecundity. Among the assessed populations, genetic characteristics including the extent of linkage disequilibrium (LD) and genetic structure differed and these differences are considered to be due to differences in genetic background. Through population-independent GWAS, several significant SNPs found close to the regions associated with each of these traits and shared in common across the populations were identified. The accuracies of genomic predictions were dependent on the traits and populations and reflected the genetic architecture of traits and genetic characteristics. Prediction accuracies using SNPs selected based on GWAS results were similar to those using all SNPs for several combinations of traits and populations. We discussed the application of genome-wide studies for C. japonica improvement.

A Dementia-Associated Risk Variant near TMEM106B Alters Chromatin Architecture and Gene Expression

Neurodegenerative diseases pose an extraordinary threat to the world's aging population, yet no disease-modifying therapies are available. Although genome-wide association studies (GWASs) have identified hundreds of risk loci for neurodegeneration, the mechanisms by which these loci influence disease risk are largely unknown. Here, we investigated the association between common genetic variants at the 7p21 locus and risk of the neurodegenerative disease frontotemporal lobar degeneration. We showed that variants associated with disease risk correlate with increased expression of the 7p21 gene TMEM106B and no other genes; co-localization analyses implicated a common causal variant underlying both association with disease and association with TMEM106B expression in lymphoblastoid cell lines and human brain. Furthermore, increases in the amount of TMEM106B resulted in increases in abnormal lysosomal phenotypes and cell toxicity in both immortalized cell lines and neurons. We then combined fine-mapping, bioinformatics, and bench-based approaches to functionally characterize all candidate causal variants at this locus. This approach identified a noncoding variant, rs1990620, that differentially recruits CTCF in lymphoblastoid cell lines and human brain to influence CTCF-mediated long-range chromatin-looping interactions between multiple cis-regulatory elements, including the TMEM106B promoter. Our findings thus provide an in-depth analysis of the 7p21 locus linked by GWASs to frontotemporal lobar degeneration, nominating a causal variant and causal mechanism for allele-specific expression and disease association at this locus. Finally, we show that genetic variants associated with risk of neurodegenerative diseases beyond frontotemporal lobar degeneration are enriched in CTCF-binding sites found in brain-relevant tissues, implicating CTCF-mediated gene regulation in risk of neurodegeneration more generally.

Killer-cell immunoglobulin-like receptor (KIR) and human leukocyte antigen (HLA) class I genetic diversity in four South African populations

Killer-cell Immunoglobulin-like Receptor (KIR) and Human Leukocyte Antigen (HLA) genotypes vary considerably between individuals and populations due to KIR/HLA allelic variation and variable haplotype configurations of KIR. HLA mediate natural killer cell activity by serving as KIR ligands. KIR/HLA polymorphisms associate with both disease susceptibility and severity. We determined the frequencies of KIR, KIR genotypes and KIR-HLA combinations in 364 healthy individuals from four South African populations. Study participants included black African (n=167), Caucasian (n=97), Mixed ancestry (n=50) and Indian (n=50) individuals. We identified 48 KIR genotypes that included two genotypes not previously reported. Based on KIR gene content, Indian individuals represented the most distinct group, showing the highest frequencies of KIR2DL2, KIR2DL5, KIR2DS1, KIR2DS2, KIR2DS3 and KIR3DS1, the lowest frequencies of KIR2DL3, KIR2DS4 and KIR3DL1; and a KIR2DL4-negative individual. KIR2DS1 and KIR3DS1 were infrequent in black African populations. HLA-C2 was more common in black African individuals, while HLA-C1 predominated in the other populations. Indian individuals were more likely to possess KIR2DL2 paired with HLA-C1, while Caucasian individuals exhibited the highest frequencies of KIR2DL3 paired with HLA-C1. This report provides comprehensive reference data for further study of the roles of KIR/HLA in non-communicable and infectious diseases in South African populations.

Colocalization of GWAS and eQTL Signals Detects Target Genes

The vast majority of genome-wide association study (GWAS) risk loci fall in non-coding regions of the genome. One possible hypothesis is that these GWAS risk loci alter the individual's disease risk through their effect on gene expression in different tissues. In order to understand the mechanisms driving a GWAS risk locus, it is helpful to determine which gene is affected in specific tissue types. For example, the relevant gene and tissue could play a role in the disease mechanism if the same variant responsible for a GWAS locus also affects gene expression. Identifying whether or not the same variant is causal in both GWASs and expression quantitative trail locus (eQTL) studies is challenging because of the uncertainty induced by linkage disequilibrium and the fact that some loci harbor multiple causal variants. However, current methods that address this problem assume that each locus contains a single causal variant. In this paper, we present eCAVIAR, a probabilistic method that has several key advantages over existing methods. First, our method can account for more than one causal variant in any given locus. Second, it can leverage summary statistics without accessing the individual genotype data. We use both simulated and real datasets to demonstrate the utility of our method. Using publicly available eQTL data on 45 different tissues, we demonstrate that eCAVIAR can prioritize likely relevant tissues and target genes for a set of glucose- and insulin-related trait loci.

Combined effects of multiple linked loci on pairwise sibling tests

The advanced multiplex STR system, PowerPlex Fusion, includes four linked locus pairs. The conventional Identifiler system has one pair of linked loci. Therefore, sibling tests conducted using the advanced system might be more affected by linkage than those conducted using the conventional system. This study simulated single and combined effects of the four linked locus pairs on pairwise sibling tests. Simulated genotypes of 100,000 pairs of full siblings and nonrelatives were constructed according to allele frequencies of the Japanese population. The single linkage effect was evaluated for simulated genotype data by calculating both the likelihood ratio accounting for the linkage between two loci and the likelihood ratio ignoring the linkage. The combined effect was obtained by multiplication of the respective single effects. Furthermore, we investigated the possibility that ignoring the linkage affects subject classification by introducing a scale of the likelihood ratio into sibling tests. The single effect in the Identifiler analysis was 0.645-1.746 times if the linkage was ignored. Overestimations and underestimations were predictable from the identical-by-state status at two linked loci. The combined effect in the PowerPlex Fusion analysis was 0.217-7.390 times. Ignoring the linkage rarely caused a false conclusive or inconclusive result, even from PowerPlex Fusion analysis. Application of the advanced system improved sibling tests considerably. The additional examined loci were more beneficial than the adverse effect of the linkage derived from the four linked locus pairs.

Detecting a hierarchical genetic population structure via Multi-InDel markers on the X chromosome

Detecting population structure and estimating individual biogeographical ancestry are very important in population genetics studies, biomedical research and forensics. Single-nucleotide polymorphism (SNP) has long been considered to be a primary ancestry-informative marker (AIM), but it is constrained by complex and time-consuming genotyping protocols. Following up on our previous study, we propose that a multi-insertion-deletion polymorphism (Multi-InDel) with multiple haplotypes can be useful in ancestry inference and hierarchical genetic population structures. A validation study for the X chromosome Multi-InDel marker (X-Multi-InDel) as a novel AIM was conducted. Genetic polymorphisms and genetic distances among three Chinese populations and 14 worldwide populations obtained from the 1000 Genomes database were analyzed. A Bayesian clustering method (STRUCTURE) was used to discern the continental origins of Europe, East Asia, and Africa. A minimal panel of ten X-Multi-InDels was verified to be sufficient to distinguish human ancestries from three major continental regions with nearly the same efficiency of the earlier panel with 21 insertion-deletion AIMs. Along with the development of more X-Multi-InDels, an approach using this novel marker has the potential for broad applicability as a cost-effective tool toward more accurate determinations of individual biogeographical ancestry and population stratification.

Imputing Phenotypes for Genome-wide Association Studies

Genome-wide association studies (GWASs) have been successful in detecting variants correlated with phenotypes of clinical interest. However, the power to detect these variants depends on the number of individuals whose phenotypes are collected, and for phenotypes that are difficult to collect, the sample size might be insufficient to achieve the desired statistical power. The phenotype of interest is often difficult to collect, whereas surrogate phenotypes or related phenotypes are easier to collect and have already been collected in very large samples. This paper demonstrates how we take advantage of these additional related phenotypes to impute the phenotype of interest or target phenotype and then perform association analysis. Our approach leverages the correlation structure between phenotypes to perform the imputation. The correlation structure can be estimated from a smaller complete dataset for which both the target and related phenotypes have been collected. Under some assumptions, the statistical power can be computed analytically given the correlation structure of the phenotypes used in imputation. In addition, our method can impute the summary statistic of the target phenotype as a weighted linear combination of the summary statistics of related phenotypes. Thus, our method is applicable to datasets for which we have access only to summary statistics and not to the raw genotypes. We illustrate our approach by analyzing associated loci to triglycerides (TGs), body mass index (BMI), and systolic blood pressure (SBP) in the Northern Finland Birth Cohort dataset.

Genetic diversity, linkage disequilibrium, population structure and construction of a core collection of Prunus avium L. landraces and bred cultivars

BACKGROUND

Depiction of the genetic diversity, linkage disequilibrium (LD) and population structure is essential for the efficient organization and exploitation of genetic resources. The objectives of this study were to (i) to evaluate the genetic diversity and to detect the patterns of LD, (ii) to estimate the levels of population structure and (iii) to identify a 'core collection' suitable for association genetic studies in sweet cherry.

RESULTS

A total of 210 genotypes including modern cultivars and landraces from 16 countries were genotyped using the RosBREED cherry 6 K SNP array v1. Two groups, mainly bred cultivars and landraces, respectively, were first detected using STRUCTURE software and confirmed by Principal Coordinate Analysis (PCoA). Further analyses identified nine subgroups using STRUCTURE and Discriminant Analysis of Principal Components (DAPC). Several sub-groups correspond to different eco-geographic regions of landraces distribution. Linkage disequilibrium was evaluated showing lower values than in peach, the reference Prunus species. A 'core collection' containing 156 accessions was selected using the maximum length sub tree method.

CONCLUSION

The present study constitutes the first population genetics analysis in cultivated sweet cherry using a medium-density SNP (single nucleotide polymorphism) marker array. We provided estimations of linkage disequilibrium, genetic structure and the definition of a first INRA's Sweet Cherry core collection useful for breeding programs, germplasm management and association genetics studies.

Evaluation of power of the Illumina HumanOmni5M-4v1 BeadChip to detect risk variants for human complex diseases

Although emerging sequencing technologies can characterize all genetic variants, the cost is still high. Illumina released the HumanOmni5M-4v1 (Omni5) genotype array with ~4.3M assayed SNPs, a much denser array compared with other available arrays. The Omni5 balances both cost and array density. In this article, we illustrate the power of Omni5 to detect genetic associations. The Omni5 includes variants with a wide range of minor allele frequencies down to <1%. The theoretical power calculation examples indicate the increased power of the Omni5 array compared with other arrays with lower density when evaluating associations with some known loci, although there are exceptions. We further evaluate the genetic associations between known loci and several quantitative traits in the Framingham Heart Study: femoral neck bone mineral density, lumbar spine bone mineral density and hippocampal volume. Finally, we search genome wide for novel associations using the Omni5 genotypes. We compare our association results from Affymetrix 500K+MIPS 50K arrays and two imputed data sets: (1) HapMap Phase II and (2) 1000 Genomes reference panel. We observed increased evidence for genotype-phenotype associations with smaller P-values for selected known loci using the Omni5 genotypes. With limited sample sizes, we identify novel variants with genome-wide significant P-values. Our observations support the notion that dense genotyping using the Omni5 can be powerful in detecting novel associated variants. Comparison with imputed data with higher density also suggests that imputation helps but cannot replace genotyping, especially when imputation quality is low.

Systematic fine-mapping of association with BMI and type 2 diabetes at the FTO locus by integrating results from multiple ethnic groups

BACKGROUND/OBJECTIVE

The 16q12.2 locus in the first intron of FTO has been robustly associated with body mass index (BMI) and type 2 diabetes in genome-wide association studies (GWAS). To improve the resolution of fine-scale mapping at FTO, we performed a systematic approach consisting of two parts.

METHODS

The first part is to partition the associated variants into linkage disequilibrium (LD) clusters, followed by conditional and haplotype analyses. The second part is to filter the list of potential causal variants through trans-ethnic comparison.

RESULTS

We first examined the LD relationship between FTO SNPs showing significant association with type 2 diabetes in Japanese GWAS and between those previously reported in European GWAS. We could partition all the assayed or imputed SNPs showing significant association in the target FTO region into 7 LD clusters. Assaying 9 selected SNPs in 4 Asian-descent populations--Japanese, Vietnamese, Sri Lankan and Chinese (n≤26,109 for BMI association and n≤24,079 for type 2 diabetes association), we identified a responsible haplotype tagged by a cluster of SNPs and successfully narrowed the list of potential causal variants to 25 SNPs, which are the smallest in number among the studies conducted to date for FTO.

CONCLUSIONS

Our data support that the power to resolve the causal variants from those in strong LD increases consistently when three distant populations--Europeans, Asians and Africans--are included in the follow-up study. It has to be noted that this fine-mapping approach has the advantage of applicability to the existing GWAS data set in combination with direct genotyping of selected variants.

Beyond GWASs: illuminating the dark road from association to function

Genome-wide association studies (GWASs) have enabled the discovery of common genetic variation contributing to normal and pathological traits and clinical drug responses, but recognizing the precise targets of these associations is now the major challenge. Here, we review recent approaches to the functional follow-up of GWAS loci, including fine mapping of GWAS signal(s), prioritization of putative functional SNPs by the integration of genetic epidemiological and bioinformatic methods, and in vitro and in vivo experimental verification of predicted molecular mechanisms for identifying the targeted genes. The majority of GWAS-identified variants fall in noncoding regions of the genome. Therefore, this review focuses on strategies for assessing likely mechanisms affected by noncoding variants; such mechanisms include transcriptional regulation, noncoding RNA function, and epigenetic regulation. These approaches have already accelerated progress from genetic studies to biological knowledge and might ultimately guide the development of prognostic, preventive, and therapeutic measures.

Predicting signatures of "synthetic associations" and "natural associations" from empirical patterns of human genetic variation

Genome-wide association studies (GWAS) have in recent years discovered thousands of associated markers for hundreds of phenotypes. However, associated loci often only explain a relatively small fraction of heritability and the link between association and causality has yet to be uncovered for most loci. Rare causal variants have been suggested as one scenario that may partially explain these shortcomings. Specifically, Dickson et al. recently reported simulations of rare causal variants that lead to association signals of common, tag single nucleotide polymorphisms, dubbed "synthetic associations". However, an open question is what practical implications synthetic associations have for GWAS. Here, we explore the signatures exhibited by such "synthetic associations" and their implications based on patterns of genetic variation observed in human populations, thus accounting for human evolutionary history -a force disregarded in previous simulation studies. This is made possible by human population genetic data from HapMap 3 consisting of both resequencing and array-based genotyping data for the same set of individuals from multiple populations. We report that synthetic associations tend to be further away from the underlying risk alleles compared to "natural associations" (i.e. associations due to underlying common causal variants), but to a much lesser extent than previously predicted, with both the age and the effect size of the risk allele playing a part in this phenomenon. We find that while a synthetic association has a lower probability of capturing causal variants within its linkage disequilibrium block, sequencing around the associated variant need not extend substantially to have a high probability of capturing at least one causal variant. We also show that the minor allele frequency of synthetic associations is lower than of natural associations for most, but not all, loci that we explored. Finally, we find the variance in associated allele frequency to be a potential indicator of synthetic associations.

Evidence of an association between the scavenger receptor class B member 2 gene and Parkinson's disease

Lysosomal protein 2 (LIMP2), the product of the scavenger receptor class B member 2 (SCARB2) gene, is a ubiquitously expressed transmembrane protein that is the mannose-6-phosphate-independent receptor for glucocerebrosidase (β-GCase); a deficiency in this protein causes Gaucher disease. Several studies have shown a link between mutations in the β-GCase gene and diseases characterized clinically by Parkinsonism and by the presence of Lewy body-related pathology. We hypothesized that genetic variants in the SCARB2 gene could be risk factors for Parkinson's disease (PD). A candidate-gene study of 347 Greek patients with sporadic PD and 329 healthy controls was conducted to investigate the association between 5 polymorphisms in the SCARB2 gene (rs6824953, rs6825004, rs4241591, rs9991821, and rs17234715) and the development of PD. The single-locus analysis for the 5 polymorphisms revealed an association only for the rs6825004 polymorphism: the generalized odds ratio (OR(G) ) was 0.68 (95% confidence interval [CI], 0.51-0.90), and the OR for the allelic test was OR = 0.71 (95% CI, 0.56-0.90). Haplotype analysis showed an association for the GCGGT haplotype (P < .01). Our study supports a genetic contribution of the SCARB2 locus to PD; future studies in larger cohorts are necessary to verify this finding.

Genome-Wide Linkage Disequilibrium from 100,000 SNPs in the East Finland Founder Population

Information about linkage disequilibrium (LD) is important in understanding the genome structure and has its applications in association studies. Here we present the first genome-wide LD study based on a founder population (East Finland). The LD data consist of 118 unrelated individuals and around 480,000 SNP pairs genotyped with the Affymetrix 100K genotyping assay. Using the minor allele frequency (MAF) limit of .05, the squared correlation coefficient between two loci (r2) was .48, .37, .28, and .20 for distances of 5, 10, 20, and 40 kb respectively. MAF had a significant effect on the mean r2 so that the extent of useful LD (r2 > .3) varied from 17 kb to 80 kb depending on the limit set for the MAF. For D' the effect of MAF was smaller but reflected the possible age of the mutation: SNPs with high MAF had lower D' than those with low MAF. The X chromosome showed higher D' values than autosomes and the extent of useful LD (r2 > .3) was twice as long on the X chromosome than on the autosomes. Based on the results, LD varies across the genome and is correlated to local recombination rate between and within chromosomes. However, the recombination rate does not explain all the variation found in LD. We also report a number of long chromosomal regions where exceptionally high or low LD were detected.

Genetic variation in the Sorbs of eastern Germany in the context of broader European genetic diversity

Population isolates have long been of interest to genetic epidemiologists because of their potential to increase power to detect disease-causing genetic variants. The Sorbs of Germany are considered as cultural and linguistic isolates and have recently been the focus of disease association mapping efforts. They are thought to have settled in their present location in eastern Germany after a westward migration from a largely Slavic-speaking territory during the Middle Ages. To examine Sorbian genetic diversity within the context of other European populations, we analyzed genotype data for over 30 000 autosomal single-nucleotide polymorphisms from over 200 Sorbs individuals. We compare the Sorbs with other European individuals, including samples from population isolates. Despite their geographical proximity to German speakers, the Sorbs showed greatest genetic similarity to Polish and Czech individuals, consistent with the linguistic proximity of Sorbian to other West Slavic languages. The Sorbs also showed evidence of subtle levels of genetic isolation in comparison with samples from non-isolated European populations. The level of genetic isolation was less than that observed for the Sardinians and French Basque, who were clear outliers on multiple measures of isolation. The finding of the Sorbs as only a minor genetic isolate demonstrates the need to genetically characterize putative population isolates, as they possess a wide range of levels of isolation because of their different demographic histories.

Genomic Diversity in Pig (Sus scrofa) and its Comparison with Human and other Livestock

We have reviewed the current pig (Sus scrofa) genomic diversity within and between sites and compared them with human and other livestock. The current Porcine 60K single nucleotide polymorphism (SNP) panel has an average SNP distance in a range of 30 - 40 kb. Most of genetic variation was distributed within populations, and only a small proportion of them existed between populations. The average heterozygosity was lower in pig than in human and other livestock. Genetic inbreeding coefficient (F(IS)), population differentiation (F(ST)), and Nei's genetic distance between populations were much larger in pig than in human and other livestock. Higher average genetic distance existed between European and Asian populations than between European or between Asian populations. Asian breeds harboured much larger variability and higher average heterozygosity than European breeds. The samples of wild boar that have been analyzed displayed more extensive genetic variation than domestic breeds. The average linkage disequilibrium (LD) in improved pig breeds extended to 1 - 3 cM, much larger than that in human (~ 30 kb) and cattle (~ 100 kb), but smaller than that in sheep (~ 10 cM). European breeds showed greater LD that decayed more slowly than Asian breeds. We briefly discuss some processes for maintaining genomic diversity in pig, including migration, introgression, selection, and drift. We conclude that, due to the long time of domestication, the pig possesses lower heterozygosity, higher F(IS), and larger LD compared with human and cattle. This implies that a smaller effective population size and less informative markers are needed in pig for genome wide association studies.

Evaluating differences in linkage disequilibrium between populations

We propose two methods to evaluate the statistical significance of differences in linkage disequilibrium (LD) between populations, where LD is measured by the standardised parameter D'. The first method is based on bootstrapping individuals within populations in order to test LD differences for each pair of loci. Using this approach we propose a solution to the problem of testing multiple locus-pairs by means of a single test for the number of pairs that exhibit significant LD differences among populations. The second method provides the Bayesian posterior probability that one population has greater LD than the other for each locus pair. Both methods can handle genotypes with unknown phase, and are demonstrated using two data sets. For the purpose of demonstration, we apply the methods to two different sets of data from humans. First, we explore the issue of LD differences between reproductively isolated populations using a new data set of twelve Xq25 microsatellites, typed in four European populations. Second, we examine evidence for LD differences between Alzheimer cases and controls from the Icelandic population using 19 single nucleotide polymorphisms (SNPs) from a 97 kb region flanking the Apolipoprotein E (APOE) gene on chromosome 19.

Shades of gray: a comparison of linkage disequilibrium between Hutterites and Europeans

Founder or isolated populations have advantages for genetic studies due to decreased genetic and environmental heterogeneity. However, whereas longer-range linkage disequilibrium (LD) in these populations is expected to facilitate gene localization, extensive LD may actually limit the ability for gene discovery. The North American Hutterite population is one of the best characterized young founder populations and members of this isolate have been the subjects of our studies of complex traits, including fertility, asthma and cardiovascular disease, for >20 years. Here, we directly assess the patterns and extent of global LD using single nucleotide polymorphism genotypes with minor allele frequencies (MAFs) > or =5% from the Affymetrix GeneChip Mapping 500 K array in 60 relatively unrelated Hutterites and 60 unrelated Europeans (HapMap CEU). Although LD among some marker pairs extends further in the Hutterites than in Europeans, the pattern of LD and MAF are surprisingly similar. These results indicate that (1) identifying disease genes should be no more difficult in the Hutterites than in outbred European populations, (2) the same common susceptibility alleles for complex diseases should be present in the Hutterites and outbred European populations, and (3) imputation algorithms based on HapMap CEU should be applicable to the Hutterites.

Interlocus non-random association of multiallelic polymorphisms spanning the coagulation factor VIII gene on human chromosome distalmost Xq28

The most common severe hereditary bleeding disorder phenotype in humans, the coagulation factor VIII (F8) deficiency haemophilia A (HEMA), maps on Xq28 band, a region that comprises 11.7% of genes and 14.2% of phenotypes on X chromosome. Information about the distribution and extent of gametic disequilibrium (GD) covering the F8 gene is scarce, despite its relevance for linkage and association studies. The aim of this study was to determine the patterns, by frequency and strength, of non-random multiallelic interallelic associations between two-locus combinations of seven microsatellite loci (REN90833, F8Int25.2, F8Int22, F8Int13.2, HEMA154311.3, TMLHEInt5 and HEMA154507.3, in that physical order) spanning 0.813 Mb on distalmost Xq28. We measured sign-based interallelic D' coefficients in 106 men and in 100 women drawn from a single unrelated Brazilian population. Significance and patterns of GD using haploid and phased diploid sample probabilities were close to conformity. Only 9.18% of the variance of D' could be accounted for by changes in length, indicating that GD is not a monotonically decreasing function of length. We defined two regions of overlapping long-range GD extending 698 735 base pairs (bp) (REN90833/TMLHEInt5 block) and 689 900 bp (F8Int13.2/HEMA154507.3 block) The extent of GD overlap is 575 637 bp (F8Int13.2/TMLHEInt5 interstice). Extended haplotype homozygosity analysis centred at the F8 intronic loci revealed that the most frequent core haplotypes decay the least in the flanking GD. The F8 intronic loci attend distinct non-random association forces; F8Int13.2 serves at maintenance of the long-range overlapping pattern of GD, whereas F8Int25.2 and F8Int22 serve at lessening it in force or effect.

The pattern of linkage disequilibrium in German Holstein cattle

This study presents a second generation of linkage disequilibrium (LD) map statistics for the whole genome of the Holstein-Friesian population, which has a four times higher resolution compared with that of the maps available so far. We used DNA samples of 810 German Holstein-Friesian cattle genotyped by the Illumina Bovine SNP50K BeadChip to analyse LD structure. A panel of 40 854 (75.6%) markers was included in the final analysis. The pairwise r(2) statistic of SNPs up to 5 Mb apart across the genome was estimated. A mean value of r(2) = 0.30 +/- 0.32 was observed in pairwise distances of <25 kb and it dropped to 0.20 +/- 0.24 at 50-75 kb, which is nearly the average inter-marker space in this study. The proportion of SNPs in useful LD (r(2) > or = 0.25) was 26% for the distance of 50 and 75 kb between SNPs. We found a lower level of LD for SNP pairs at the distance < or =100 kb than previously thought. Analysis revealed 712 haplo-blocks spanning 4.7% of the genome and containing 8.0% of all SNPs. Mean and median block length were estimated as 164 +/- 117 kb and 144 kb respectively. Allele frequencies of the SNPs have a considerable and systematic impact on the estimate of r(2). It is shown that minimizing the allele frequency difference between SNPs reduces the influence of frequency on r(2) estimates. Analysis of past effective population size based on the direct estimates of recombination rates from SNP data showed a decline in effective population size to N(e) = 103 up to approximately 4 generations ago. Systematic effects of marker density and effective population size on observed LD and haplotype structure are discussed.

Legacy of mutiny on the Bounty: founder effect and admixture on Norfolk Island

The population of Norfolk Island, located off the eastern coast of Australia, possesses an unusual and fascinating history. Most present-day islanders are related to a small number of the 'Bounty' mutineer founders. These founders consisted of Caucasian males and Polynesian females and led to an admixed present-day population. By examining a single large pedigree of 5742 individuals, spanning >200 years, we analyzed the influence of admixture and founder effect on various cardiovascular disease (CVD)-related traits. On account of the relative isolation of the population, on average one-third of the genomes of present-day islanders (single large pedigree individuals) is derived from 17 initial founders. The proportion of Polynesian ancestry in the present-day individuals was found to significantly influence total triglycerides, body mass index, systolic blood pressure and diastolic blood pressure. For various cholesterol traits, the influence of ancestry was less marked but overall the direction of effect for all CVD-related traits was consistent with Polynesian ancestry conferring greater CVD risk. Marker-derived homozygosity was computed and agreed with measures of inbreeding derived from pedigree information. Founder effect (inbreeding and marker-derived homozygosity) significantly influenced height. In conclusion, both founder effect and extreme admixture have substantially influenced the genetic architecture of a variety of CVD-related traits in this population.

An utter refutation of the "fundamental theorem of the HapMap"

The International HapMap Project was proposed in order to quantify linkage disequilibrium (LD) relationships among human DNA polymorphisms in an assortment of populations, in order to facilitate the process of selecting a minimal set of markers that could capture most of the signal from the untyped markers in a genome-wide association study. The central dogma can be summarized by the argument that if a marker is in tight LD with a polymorphism that directly impacts disease risk, as measured by the metric r(2), then one would be able to detect an association between the marker and disease with sample size that was increased by a factor of 1/r(2) over that needed to detect the effect of the functional variant directly. This "fundamental theorem" holds, however, only if one assumes that the LD between loci and the etiological effect of the functional variant are independent of each other, that they are statistically independent of all other etiological factors (in exposure and action), that sampling is prospective, and that the estimates of r(2) are accurate. None of these are standard operating assumptions, however. We describe the ramifications of these implicit assumptions, and provide simple examples in which the effects of a functional variant could be unequivocally detected if it were directly genotyped, even as markers in high LD with the functional variant would never show association with disease, even in infinite sample sizes. Both theoretical and empirical refutation of the central dogma of genome-wide association studies is thus presented.

Increased accuracy of artificial selection by using the realized relationship matrix

Dense marker genotypes allow the construction of the realized relationship matrix between individuals, with elements the realized proportion of the genome that is identical by descent (IBD) between pairs of individuals. In this paper, we demonstrate that by replacing the average relationship matrix derived from pedigree with the realized relationship matrix in best linear unbiased prediction (BLUP) of breeding values, the accuracy of the breeding values can be substantially increased, especially for individuals with no phenotype of their own. We further demonstrate that this method of predicting breeding values is exactly equivalent to the genomic selection methodology where the effects of quantitative trait loci (QTLs) contributing to variation in the trait are assumed to be normally distributed. The accuracy of breeding values predicted using the realized relationship matrix in the BLUP equations can be deterministically predicted for known family relationships, for example half sibs. The deterministic method uses the effective number of independently segregating loci controlling the phenotype that depends on the type of family relationship and the length of the genome. The accuracy of predicted breeding values depends on this number of effective loci, the family relationship and the number of phenotypic records. The deterministic prediction demonstrates that the accuracy of breeding values can approach unity if enough relatives are genotyped and phenotyped. For example, when 1000 full sibs per family were genotyped and phenotyped, and the heritability of the trait was 0.5, the reliability of predicted genomic breeding values (GEBVs) for individuals in the same full sib family without phenotypes was 0.82. These results were verified by simulation. A deterministic prediction was also derived for random mating populations, where the effective population size is the key parameter determining the effective number of independently segregating loci. If the effective population size is large, a very large number of individuals must be genotyped and phenotyped in order to accurately predict breeding values for unphenotyped individuals from the same population. If the heritability of the trait is 0.3, and N(e)=100, approximately 12474 individuals with genotypes and phenotypes are required in order to predict GEBVs of un-phenotyped individuals in the same population with an accuracy of 0.7 [corrected].

Linkage disequilibrium and demographic history of wild and domestic canids

Assessing the extent of linkage disequilibrium (LD) in natural populations of a nonmodel species has been difficult due to the lack of available genomic markers. However, with advances in genotyping and genome sequencing, genomic characterization of natural populations has become feasible. Using sequence data and SNP genotypes, we measured LD and modeled the demographic history of wild canid populations and domestic dog breeds. In 11 gray wolf populations and one coyote population, we find that the extent of LD as measured by the distance at which r2=0.2 extends <10 kb in outbred populations to >1.7 Mb in populations that have experienced significant founder events and bottlenecks. This large range in the extent of LD parallels that observed in 18 dog breeds where the r2 value varies from approximately 20 kb to >5 Mb. Furthermore, in modeling demographic history under a composite-likelihood framework, we find that two of five wild canid populations exhibit evidence of a historical population contraction. Five domestic dog breeds display evidence for a minor population contraction during domestication and a more severe contraction during breed formation. Only a 5% reduction in nucleotide diversity was observed as a result of domestication, whereas the loss of nucleotide diversity with breed formation averaged 35%.

Extent of linkage disequilibrium in wild and domestic chicken populations

Linkage disequilibrium (LD) analyses play a fundamental role in gene mapping, both as a tool for fine mapping of complex trait gene and in genome-wide association studies. The use of LD analyses in practice depends crucially on the understanding of the patterns of LD in the genome. In the present study, a total of 36 SNP were selected initially in a region (200 kb) of Contig.060226.1 on GGA1 based on the average physical distance. After verifying their level of polymorphism, 21 SNP were selected finally to genotype one wild and two domestic chicken populations, Red Jungle Fowl (RJF), Taihe Silkie chicken (TS) and White Recessive Rock chicken (WRR). Two distinct measures of linkage disequilibrium, D' and r(2), between marker pairs were used. The D'map of RJF is spurious. Many marker pairs showed complete LD. TS and WRR showed distinct characteristic of decreasing D' value over increasing physical distance. The r(2) showed much less inflation than did D' in RJF population, and also showed a characteristic decreasing value over increasing physical distance. In TS and WRR populations, although the two measures differed in scale, their decay profiles were similar. The data in the present study suggested that the extent of LD in this region is about 150 kb, corresponding to 0.4 cM. Our results imply that a very dense map of SNP markers will be required for LD mapping methods. Thus, association studies based on polymorphisms within all known genes, and candidate QTL mapping, may ultimately prove to be a more effective strategy.

Designing pharmacogenetic projects in industry: practical design perspectives from the Industry Pharmacogenomics Working Group

Pharmacogenetic association studies have the potential to identify variations in DNA sequence which impact drug response. Identifying these DNA variants can help to explain interindividual variability in drug response; this is the first step in personalizing dosing and treatment regimes to a patient's needs. There are many intricacies in the design and analysis of pharmacogenetic association studies, including having adequate power, selecting proper endpoints, detecting and correcting the effects of population stratification, modeling genetic and nongenetic covariates accurately, and validating the results. At this point there are no formal guidelines on the design and analysis of pharmacogenetic studies. The Industry Pharmacogenomics Working Group has initiated discussions regarding potential guidelines for pharmacogenetic study design and analyses (http://i-pwg.org) and the results from these discussions are presented in this paper.

Haplotype block partitioning as a tool for dimensionality reduction in SNP association studies

BACKGROUND

Identification of disease-related genes in association studies is challenged by the large number of SNPs typed. To address the dilution of power caused by high dimensionality, and to generate results that are biologically interpretable, it is critical to take into consideration spatial correlation of SNPs along the genome. With the goal of identifying true genetic associations, partitioning the genome according to spatial correlation can be a powerful and meaningful way to address this dimensionality problem.

RESULTS

We developed and validated an MCMC Algorithm To Identify blocks of Linkage DisEquilibrium (MATILDE) for clustering contiguous SNPs, and a statistical testing framework to detect association using partitions as units of analysis. We compared its ability to detect true SNP associations to that of the most commonly used algorithm for block partitioning, as implemented in the Haploview and HapBlock software. Simulations were based on artificially assigning phenotypes to individuals with SNPs corresponding to region 14q11 of the HapMap database. When block partitioning is performed using MATILDE, the ability to correctly identify a disease SNP is higher, especially for small effects, than it is with the alternatives considered. Advantages can be both in terms of true positive findings and limiting the number of false discoveries. Finer partitions provided by LD-based methods or by marker-by-marker analysis are efficient only for detecting big effects, or in presence of large sample sizes. The probabilistic approach we propose offers several additional advantages, including: a) adapting the estimation of blocks to the population, technology, and sample size of the study; b) probabilistic assessment of uncertainty about block boundaries and about whether any two SNPs are in the same block; c) user selection of the probability threshold for assigning SNPs to the same block.

CONCLUSION

We demonstrate that, in realistic scenarios, our adaptive, study-specific block partitioning approach is as or more efficient than currently available LD-based approaches in guiding the search for disease loci.

Extent of linkage disequilibrium in Holstein cattle in North America

The success of fine-scale mapping and genomic selection depends mainly on the strength of linkage disequilibrium (LD) between markers and causal mutations. With Lewontin's measure of LD (known as D'), high levels of LD that extend over several million base pairs have been reported in livestock. However, this measure of LD can be strongly biased upward by small samples and by low allele frequencies. The aim of this study was to characterize the level and extent of LD in Holstein cattle in North America (Canada and the United States for purposes of this study) by using the squared correlation of the alleles at 2 loci (r(2)). The Affymetrix MegAllele GeneChip Bovine Mapping 10K single nucleotide polymorphism (SNP) array was used to genotype 821 bulls, from which 497 were used in the analysis of the extent of LD. A total of 5,564 SNP were used after filtering out SNP with more than 5% of Mendelian inconsistencies, with more than 20% missing genotypes, or with a minor allele frequency of less than 10%. Analysis of syntenic pairs revealed that useful LD (measured as r(2) > 0.3) occurred at distances shorter than 100 kb. Linkage disequilibrium decayed very rapidly, within a few hundred kilobase pairs. In addition, no substantial LD between unlinked loci was found. Using a sliding window analysis, we observed an irregular pattern of LD across the genome. These findings suggest that to capture useful LD, which is required for whole-genome fine mapping and genomic selection, a denser SNP map would be needed.

Linkage disequilibrium structure of the 5q31-33 region in a Thai population

A number of loci related to the immune response are located on human chromosomal region 5q31-33, and polymorphisms in this region have been reported to be associated with autoimmune and infectious diseases. In Southeast Asian populations, no systematic survey with dense SNP markers has been performed for the 5q31-33 region. In this study, the LD and haplotype structures for a 472-kb region on 5q31 were investigated in a Thai population to provide useful information for association studies. In addition, the LD structure in Thais was compared with that of the CHB and JPT HapMap populations (CHB + JPT) to evaluate the transferability of tagging SNPs from CHB + JPT for Thais. We show that the minor allele frequency, pattern of LD block, and genetic structure in the 5q31-33 region were highly concordant between Thais and CHB + JPT. A high transferability of tagging SNPs from CHB + JPT for Thais was observed. Our results suggest that tagging SNPs from CHB + JPT (Northeast Asians) can efficiently capture common variants in Southeast Asians, and that the HapMap data are useful for association studies in Southeast Asian populations.

On transferability of genome-wide tagSNPs

The question of tagging single nucleotide polymorphism (tagSNP) transferability is an important one because many ongoing and upcoming Genome-Wide Association studies rely critically upon the validity, and practical feasibility of using a universal core set of tagSNPs. A series of recent studies analyzed performance of tagSNPs selected based on the HapMap. While these studies showed largely satisfactory transferability of the tagSNPs, they also reported that the level of transferability varies, substantively sometimes, especially when tagSNPs selected in one population were used in another distant population. We present a review of the literature about where and why tagSNP transferability may become a problem and suggest research directions that may help the resolution.

Characterization of LD structures and the utility of HapMap in genetic association studies

Observed distribution of and variation in linkage disequilibrium (LD) with respect to the evolution history and disease transmission in a population is the driving force behind the current wave of genome-wide association (GWA) studies of complex human diseases. An extensive literature covers topics from haplotype analysis that utilizes local LD structures in candidate genes and regions to genome-wide organization of LD blocks (neighborhood) that led to the development of International HapMap Project and panels of "tagSNPs" used by current GWA studies. In this chapter, we examine the scenarios where each of the major types of analysis methods may be applicable and where the current popular genotyping platforms for GWA might come short. We discuss current association analysis methods by emphasizing their reliance on the local LD structures or the global organization of the LD structures, and highlight the need to consider individual marker information content in large-scale association mapping.

Extent of linkage disequilibrium in chicken

Many of the economically important traits in chicken are multifactorial and governed by multiple genes located at different quantitative trait loci (QTLs). The optimal marker density to identify these QTLs in linkage and association studies is largely determined by the extent of linkage disequilibrium (LD) around them. In this study, we investigated the extent of LD on two chromosomes in a white layer and two broiler chicken breeds. Pairwise levels of LD were calculated for 33 and 36 markers on chromosomes 10 and 28, respectively. We found that useful LD (i.e. an r(2) value higher than 0.3) in Nutreco chicken breed E5 (inbred) can extend to around 1 cM on chromosomes 10 and 28, although in a second region on chromosome 28 it extends to about 2.5 cM. The extent in breed Nutreco E3 (outbred) was very short in chromosome 10 (15 kb) but very much larger on chromosome 28, particularly in one region of depressed heterozygosity. The layer breed E2 (inbred) showed an extent of useful LD up to 4 cM on chromosome 10; the extent on chromosome 28 could not be assessed due to an erratic pattern of LD on that chromosome, although in one region LD appears to be in the order of 0.8 cM. This indicates that there may be very large differences in patterns of LD between different chicken breeds and different genomic regions.

Admixture and patterns of linkage disequilibrium in a free-living vertebrate population

Linkage disequilibrium (LD), a measure of nonrandom association of alleles at different loci, is of great interest to evolutionary geneticists as it can be used to help identify loci that explain phenotypic variation. Surveys of the extent of LD across genomes have been carried out in a number of systems, most notably humans and model organisms. However, studies of natural populations of vertebrates have rarely been performed. Here, we describe an investigation of LD in a free-living island population of red deer Cervus elaphus. Relatively high levels of LD extended several tens of centimorgans, and significant LD was frequently detected between unlinked markers. The magnitude of LD varied depending on how the population was sampled. It also varied across different chromosomes, and was shown to be a function of sample size, intermarker distance and marker heterozygosity. A recent admixture event in the population led to an ephemeral increase in LD. Association mapping may be possible in this population, although a high 'baseline' level of LD could lead to false positive associations between marker loci and a trait of interest.

Bayesian estimates of linkage disequilibrium

BACKGROUND

The maximum likelihood estimator of D'--a standard measure of linkage disequilibrium--is biased toward disequilibrium, and the bias is particularly evident in small samples and rare haplotypes.

RESULTS

This paper proposes a Bayesian estimation of D' to address this problem. The reduction of the bias is achieved by using a prior distribution on the pair-wise associations between single nucleotide polymorphisms (SNP)s that increases the likelihood of equilibrium with increasing physical distances between pairs of SNPs. We show how to compute the Bayesian estimate using a stochastic estimation based on MCMC methods, and also propose a numerical approximation to the Bayesian estimates that can be used to estimate patterns of LD in large datasets of SNPs.

CONCLUSION

Our Bayesian estimator of D' corrects the bias toward disequilibrium that affects the maximum likelihood estimator. A consequence of this feature is a more objective view about the extent of linkage disequilibrium in the human genome, and a more realistic number of tagging SNPs to fully exploit the power of genome wide association studies.

ESTIMATION OF THE EXTENT OF LINKAGE DISEQUILIBRIUM IN SEVEN REGIONS OF THE PORCINE GENOME

Linkage disequilibrium (LD) refers to the correlation among neighboring alleles, reflecting non-random patterns of association between alleles at (nearby) loci. A better understanding of LD in the porcine genome is of direct relevance for identification of genes and mutations with a certain effect on the traits of interest. Here, 215 SNPs in seven genomic regions were genotyped in individuals of three breeds. Pairwise linkage disequilibrium was calculated for all marker pairs. To estimate the extent of LD, all pairwise LD values were plotted against the distance between the markers. Based on SNP markers in four genomic regions analyzed in three panels from populations of Large White, Dutch Landrace, and Meishan origin, useful LD is estimated to extend for approximately 40 to 60 kb in the porcine genome.

Association of the human kainate receptor GluR7 gene (GRIK3) with recurrent major depressive disorder

The etiology of mood disorders remains elusive, despite our increasing understanding of the neurotransmitter systems and brain regions that are involved. We performed a large family-based association study to test if the human kainate receptor GluR7 gene (GRIK3) is associated with bipolar disorder (BP) or recurrent major depressive disorder (R-MDD). One hundred fifty-three multiplex BP families from the National Institute of Mental Health (NIMH) Genetics Initiative on Bipolar Disorder were analyzed with the transmission disequilibrium test (TDT). We detected a significant linkage disequilibrium (LD) indicated by preferential maternal transmission of the GluR7 S310 allele to R-MDD patients (P = 0.012), but not to bipolar I disorder (BPI) patients (P = 1.00). We performed a second independent study by applying the TDT in 81 parent-offspring triads from families that inherit recurrent early-onset major depressive disorder (RE-MDD). The results from this second study showed only a suggestive maternal association (P = 0.068). Our findings imply that the GluR7 gene is a susceptibility factor in R-MDD and that the glutamatergic receptor system plays a critical role in the disease etiology.

Selection for heterozygosity gives hope to a wild population of inbred wolves

Recent analyses have questioned the usefulness of heterozygosity estimates as measures of the inbreeding coefficient (f), a finding that may have dramatic consequences for the management of endangered populations. We confirm that f and heterozygosity is poorly correlated in a wild and highly inbred wolf population. Yet, our data show that for each level of f, it was the most heterozygous wolves that established themselves as breeders, a selection process that seems to have decelerated the loss of heterozygosity in the population despite a steady increase of f. The markers contributing to the positive relationship between heterozygosity and breeding success were found to be located on different chromosomes, but there was a substantial amount of linkage disequilibrium in the population, indicating that the markers are reflecting heterozygosity over relatively wide genomic regions. Following our results we recommend that management programs of endangered populations include estimates of both f and heterozygosity, as they may contribute with complementary information about population viability.

Allele frequency matching between SNPs reveals an excess of linkage disequilibrium in genic regions of the human genome

Significant interest has emerged in mapping genetic susceptibility for complex traits through whole-genome association studies. These studies rely on the extent of association, i.e., linkage disequilibrium (LD), between single nucleotide polymorphisms (SNPs) across the human genome. LD describes the nonrandom association between SNP pairs and can be used as a metric when designing maximally informative panels of SNPs for association studies in human populations. Using data from the 1.58 million SNPs genotyped by Perlegen, we explored the allele frequency dependence of the LD statistic r² both empirically and theoretically. We show that average r² values between SNPs unmatched for allele frequency are always limited to much less than 1 (theoretical approximately 0.46 to 0.57 for this dataset). Frequency matching of SNP pairs provides a more sensitive measure for assessing the average decay of LD and generates average r² values across nearly the entire informative range (from 0 to 0.89 through 0.95). Additionally, we analyzed the extent of perfect LD (r² = 1.0) using frequency-matched SNPs and found significant differences in the extent of LD in genic regions versus intergenic regions. The SNP pairs exhibiting perfect LD showed a significant bias for derived, nonancestral alleles, providing evidence for positive natural selection in the human genome.

One of the primary goals for geneticists is isolating regions of the genome that convey increased risk of disease through the association of genetic polymorphisms with phenotypic traits. The recent availability of genome-wide polymorphism data (i.e., single nucleotide polymorphisms [SNPs]) has made association studies possible on an unprecedented scale, and the characterization and selection of these polymorphisms for these studies has been a topic of major interest. One method for choosing informative SNPs has been to compare the correlation between SNPs (a term called linkage disequilibrium), but this can create confounding problems when comparing SNPs of different frequencies. In this study, the authors show that if SNPs are compared to other SNPs of equal or near equal frequency, the correlation between them more accurately represents the true correlation. This also produces a more sensitive method for determining linkage disequilibrium. Using this method, SNPs were compared both within and outside of gene regions to examine the overall correlation between SNPs in each region. Matching SNPs according to their frequency greatly increased the maximum possible correlation and showed significantly higher correlations between SNPs within genes (intragenic) versus between genes (intergenic). Using the recently completed chimpanzee sequence, a larger fraction of high frequency human specific SNPs was found within the perfectly correlated SNP pairs in genic regions compared to intergenic regions. These observations suggest that regions of the genome around genes have been under selective pressure, leading to a greater correlation between SNPs. Genes found in regions with the highest correlations between SNPs will be of particular interest for future genotype-phenotype association studies.

Association of AKT1 haplotype with the risk of schizophrenia in Iranian population

AKT-glycogen synthase kinase 3beta (GSK3beta) signaling is a target of lithium and has been implicated in the pathogenesis of mood disorders and schizophrenia. AKT1 protein level is decreased in the peripheral lymphocytes and brains of schizophrenic patients. The SNP2/3/4 TCG haplotype of AKT1 was associated with schizophrenia in patients with Northern European origin. In the present study, we genotyped five single nucleotide polymorphisms (SNP1-5) of AKT1 gene according to the original study in Iranians comprising of 321 schizophrenic patients and 383 controls, all residing in Mashhad city, Northeastern Iran. Haplotype analysis showed that the frequency of a five-SNP haplotype (AGCAG) was significantly higher in schizophrenic patients (0.068) than that of controls (0.034) (P = 0.03 after Bonferroni correction, OR = 2.04, CI = 1.2-3.4). In stratified analysis by schizophrenia subtypes, the frequency of the same haplotype was significantly higher in disorganized subtype (n = 78, frequency of haplotype=0.081) when compared with normal controls (P = 0.04 after Bonferroni correction, OR = 2.59, CI = 1.3-5.2). Our findings did not confirm the association of AKT1 SNP2/3/4 TCG haplotype with the risk of schizophrenia as reported in the original study but showed the evidence of association with a different haplotype, AKT1 five-SNP AGCAG haplotype, with the risk of schizophrenia in Iranian population.