Genome-wide autozygosity is associated with lower general cognitive ability.

Inbreeding depression refers to lower fitness among offspring of genetic relatives. This reduced fitness is caused by the inheritance of two identical chromosomal segments (autozygosity) across the genome, which may expose the effects of (partially) recessive deleterious mutations. Even among outbred populations, autozygosity can occur to varying degrees due to cryptic relatedness between parents. Using dense genome-wide single-nucleotide polymorphism (SNP) data, we examined the degree to which autozygosity associated with measured cognitive ability in an unselected sample of 4854 participants of European ancestry. We used runs of homozygosity-multiple homozygous SNPs in a row-to estimate autozygous tracts across the genome. We found that increased levels of autozygosity predicted lower general cognitive ability, and estimate a drop of 0.6 s.d. among the offspring of first cousins (P=0.003-0.02 depending on the model). This effect came predominantly from long and rare autozygous tracts, which theory predicts as more likely to be deleterious than short and common tracts. Association mapping of autozygous tracts did not reveal any specific regions that were predictive beyond chance after correcting for multiple testing genome wide. The observed effect size is consistent with studies of cognitive decline among offspring of known consanguineous relationships. These findings suggest a role for multiple recessive or partially recessive alleles in general cognitive ability, and that alleles decreasing general cognitive ability have been selected against over evolutionary time.

Regional heritability advanced complex trait analysis for GPU and traditional parallel architectures.

MOTIVATION: Quantification of the contribution of genetic variation to phenotypic variation for complex traits becomes increasingly computationally demanding with increasing numbers of single-nucleotide polymorphisms and individuals. To meet the challenges in making feasible large-scale studies, we present the REgional heritability advanced complex trait analysis software. Adapted from advanced complex trait analysis (and, in turn, genome-wide complex trait analysis), it is tailored to exploit the parallelism present in modern traditional and graphics processing unit (GPU)-accelerated machines, from workstations to supercomputers. RESULTS: We adapt the genetic relationship matrix estimation algorithm to remove limitations on memory, allowing the analysis of large datasets. We build on this to develop a version of the code able to efficiently exploit GPU-accelerated systems for both the genetic relationship matrix and REstricted maximum likelihood (REML) parts of the analysis, offering substantial speedup over the traditional central processing unit version. We develop the ability to analyze multiple small regions of the genome across multiple compute nodes in parallel, following the 'regional heritability' approach. We demonstrate the new software using 1024 GPUs in parallel on one of the world's fastest supercomputers. AVAILABILITY: The code is freely available at http://www.epcc.ed.ac.uk/software-products CONTACT: a.gray@ed.ac.uk.

A genome-wide association study implicates the APOE locus in nonpathological cognitive ageing.

Cognitive decline is a feared aspect of growing old. It is a major contributor to lower quality of life and loss of independence in old age. We investigated the genetic contribution to individual differences in nonpathological cognitive ageing in five cohorts of older adults. We undertook a genome-wide association analysis using 549 692 single-nucleotide polymorphisms (SNPs) in 3511 unrelated adults in the Cognitive Ageing Genetics in England and Scotland (CAGES) project. These individuals have detailed longitudinal cognitive data from which phenotypes measuring each individual's cognitive changes were constructed. One SNP--rs2075650, located in TOMM40 (translocase of the outer mitochondrial membrane 40 homolog)--had a genome-wide significant association with cognitive ageing (P=2.5 × 10(-8)). This result was replicated in a meta-analysis of three independent Swedish cohorts (P=2.41 × 10(-6)). An Apolipoprotein E (APOE) haplotype (adjacent to TOMM40), previously associated with cognitive ageing, had a significant effect on cognitive ageing in the CAGES sample (P=2.18 × 10(-8); females, P=1.66 × 10(-11); males, P=0.01). Fine SNP mapping of the TOMM40/APOE region identified both APOE (rs429358; P=3.66 × 10(-11)) and TOMM40 (rs11556505; P=2.45 × 10(-8)) as loci that were associated with cognitive ageing. Imputation and conditional analyses in the discovery and replication cohorts strongly suggest that this effect is due to APOE (rs429358). Functional genomic analysis indicated that SNPs in the TOMM40/APOE region have a functional, regulatory non-protein-coding effect. The APOE region is significantly associated with nonpathological cognitive ageing. The identity and mechanism of one or multiple causal variants remain unclear.

Advanced complex trait analysis.

MOTIVATION: The Genome-wide Complex Trait Analysis (GCTA) software package can quantify the contribution of genetic variation to phenotypic variation for complex traits. However, as those datasets of interest continue to increase in size, GCTA becomes increasingly computationally prohibitive. We present an adapted version, Advanced Complex Trait Analysis (ACTA), demonstrating dramatically improved performance. RESULTS: We restructure the genetic relationship matrix (GRM) estimation phase of the code and introduce the highly optimized parallel Basic Linear Algebra Subprograms (BLAS) library combined with manual parallelization and optimization. We introduce the Linear Algebra PACKage (LAPACK) library into the restricted maximum likelihood (REML) analysis stage. For a test case with 8999 individuals and 279,435 single nucleotide polymorphisms (SNPs), we reduce the total runtime, using a compute node with two multi-core Intel Nehalem CPUs, from ∼17 h to ∼11 min. AVAILABILITY AND IMPLEMENTATION: The source code is fully available under the GNU Public License, along with Linux binaries. For more information see http://www.epcc.ed.ac.uk/software-products/acta. CONTACT: a.gray@ed.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Meta-analysis of genome-wide association studies for personality.

Personality can be thought of as a set of characteristics that influence people's thoughts, feelings and behavior across a variety of settings. Variation in personality is predictive of many outcomes in life, including mental health. Here we report on a meta-analysis of genome-wide association (GWA) data for personality in 10 discovery samples (17,375 adults) and five in silico replication samples (3294 adults). All participants were of European ancestry. Personality scores for Neuroticism, Extraversion, Openness to Experience, Agreeableness and Conscientiousness were based on the NEO Five-Factor Inventory. Genotype data of ≈ 2.4M single-nucleotide polymorphisms (SNPs; directly typed and imputed using HapMap data) were available. In the discovery samples, classical association analyses were performed under an additive model followed by meta-analysis using the weighted inverse variance method. Results showed genome-wide significance for Openness to Experience near the RASA1 gene on 5q14.3 (rs1477268 and rs2032794, P=2.8 × 10(-8) and 3.1 × 10(-8)) and for Conscientiousness in the brain-expressed KATNAL2 gene on 18q21.1 (rs2576037, P=4.9 × 10(-8)). We further conducted a gene-based test that confirmed the association of KATNAL2 to Conscientiousness. In silico replication did not, however, show significant associations of the top SNPs with Openness and Conscientiousness, although the direction of effect of the KATNAL2 SNP on Conscientiousness was consistent in all replication samples. Larger scale GWA studies and alternative approaches are required for confirmation of KATNAL2 as a novel gene affecting Conscientiousness.

TERC polymorphisms are associated both with susceptibility to colorectal cancer and with longer telomeres.

BACKGROUND AND AIMS: Shorter telomeres have been associated with increased risk of malignancy, including colorectal cancer (CRC). Telomere length is heritable and may be an intermediate phenotype linked to genetic susceptibility to CRC. METHODS: In a large sample, the study investigated whether candidate single nucleotide polymorphisms (SNP) in 'telomere biology' genes were associated with telomere length in leucocytes. SNP associated with an increased risk of CRC were searched for separately. RESULTS: Carriers of the common allele at SNP rs10936599, near the telomerase RNA component (TERC) locus, had significantly longer telomeres. It was independently found that the same rs10936599 allele was associated with increased risk of both CRC and colorectal adenomas. Neither telomere length nor CRC risk was associated with variation near telomerase reverse transcriptase or other telomere biology genes. In silico analysis showed that SNP rs2293607 was strongly correlated with rs10936599, mapped within TERC transcripts, had a predicted effect on messenger RNA folding and lay at a reported transcription factor binding site. TERC mRNA were expressed, differing only at the alleles of rs2293607, in CRC cell line HCT116. The long-telomere/CRC-risk allele was associated with higher levels of TERC mRNA and the formation of longer telomeres. CONCLUSIONS: Common genetic variation at TERC is associated with both longer telomeres and an increased risk of CRC, a potential mechanism being reduced levels of cell senescence or death. This finding is somewhat paradoxical, given retrospective studies reporting that CRC cases have shorter telomeres than controls. One possibility is that that association actually results from poorer survival in patients with longer telomeres.

SNP mistyping in genotyping arrays--an important cause of spurious association in case-control studies.

Using genome-wide association studies to identify genetic variants contributing to disease has been highly successful with many novel genetic predispositions identified and biological pathways revealed. Several pitfalls for spurious association or non-replication have been highlighted: from population structure, automated genotype scoring for cases and controls, to age-varying association. We describe an important yet unreported source of bias in case-control studies due to variations in chip technology between different commercial array releases. As cases are commonly genotyped with newer arrays and freely available control resources are frequently used for comparison, there exists an important potential for false associations which are robust to standard quality control and replication design.

Genome-wide association studies establish that human intelligence is highly heritable and polygenic.

General intelligence is an important human quantitative trait that accounts for much of the variation in diverse cognitive abilities. Individual differences in intelligence are strongly associated with many important life outcomes, including educational and occupational attainments, income, health and lifespan. Data from twin and family studies are consistent with a high heritability of intelligence, but this inference has been controversial. We conducted a genome-wide analysis of 3511 unrelated adults with data on 549,692 single nucleotide polymorphisms (SNPs) and detailed phenotypes on cognitive traits. We estimate that 40% of the variation in crystallized-type intelligence and 51% of the variation in fluid-type intelligence between individuals is accounted for by linkage disequilibrium between genotyped common SNP markers and unknown causal variants. These estimates provide lower bounds for the narrow-sense heritability of the traits. We partitioned genetic variation on individual chromosomes and found that, on average, longer chromosomes explain more variation. Finally, using just SNP data we predicted ∼1% of the variance of crystallized and fluid cognitive phenotypes in an independent sample (P=0.009 and 0.028, respectively). Our results unequivocally confirm that a substantial proportion of individual differences in human intelligence is due to genetic variation, and are consistent with many genes of small effects underlying the additive genetic influences on intelligence.

Association studies on 11 published colorectal cancer risk loci.

BACKGROUND: Recently, several genome-wide association studies (GWAS) have independently found numerous loci at which common single-nucleotide polymorphisms (SNPs) modestly influence the risk of developing colorectal cancer. The aim of this study was to test 11 loci, reported to be associated with an increased or decreased risk of colorectal cancer: 8q23.3 (rs16892766), 8q24.21 (rs6983267), 9p24 (rs719725), 10p14 (rs10795668), 11q23.1 (rs3802842), 14q22.2 (rs4444235), 15q13.3 (rs4779584), 16q22.1 (rs9929218), 18q21.1 (rs4939827), 19q13.1 (rs10411210) and 20p12.3 (rs961253), in a Swedish-based cohort. METHODS: The cohort was composed of 1786 cases and 1749 controls that were genotyped and analysed statistically. Genotype-phenotype analysis, for all 11 SNPs and sex, age of onset, family history of CRC and tumour location, was performed. RESULTS: Of eleven loci, 5 showed statistically significant odds ratios similar to previously published findings: 8q23.3, 8q24.21, 10p14, 15q13.3 and 18q21.1. The remaining loci 11q23.1, 16q22.1, 19q13.1 and 20p12.3 showed weak trends but somehow similar to what was previously published. The loci 9p24 and 14q22.2 could not be confirmed. We show a higher number of risk alleles in affected individuals compared to controls. Four statistically significant genotype-phenotype associations were found; the G allele of rs6983267 was associated to older age, the G allele of rs1075668 was associated with a younger age and sporadic cases, and the T allele of rs10411210 was associated with younger age. CONCLUSIONS: Our study, using a Swedish population, supports most genetic variants published in GWAS. More studies are needed to validate the genotype-phenotype correlations.

A large-scale meta-analysis to refine colorectal cancer risk estimates associated with MUTYH variants.

BACKGROUND: defective DNA repair has a causal role in hereditary colorectal cancer (CRC). Defects in the base excision repair gene MUTYH are responsible for MUTYH-associated polyposis and CRC predisposition as an autosomal recessive trait. Numerous reports have suggested MUTYH mono-allelic variants to be low penetrance risk alleles. We report a large collaborative meta-analysis to assess and refine CRC risk estimates associated with bi-allelic and mono-allelic MUTYH variants and investigate age and sex influence on risk. METHODS: MUTYH genotype data were included from 20 565 cases and 15 524 controls. Three logistic regression models were tested: a crude model; adjusted for age and sex; adjusted for age, sex and study. RESULTS: all three models produced very similar results. MUTYH bi-allelic carriers demonstrated a 28-fold increase in risk (95% confidence interval (CI): 6.95-115). Significant bi-allelic effects were also observed for G396D and Y179C/G396D compound heterozygotes and a marginal mono-allelic effect for variant Y179C (odds ratio (OR)=1.34; 95% CI: 1.00-1.80). A pooled meta-analysis of all published and unpublished datasets submitted showed bi-allelic effects for MUTYH, G396D and Y179C (OR=10.8, 95% CI: 5.02-23.2; OR=6.47, 95% CI: 2.33-18.0; OR=3.35, 95% CI: 1.14-9.89) and marginal mono-allelic effect for variants MUTYH (OR=1.16, 95% CI: 1.00-1.34) and Y179C alone (OR=1.34, 95% CI: 1.01-1.77). CONCLUSIONS: overall, this large study refines estimates of disease risk associated with mono-allelic and bi-allelic MUTYH carriers.

Using regulatory variants to detect gene-gene interactions identifies networks of genes linked to cell immortalisation.

The extent to which the impact of regulatory genetic variants may depend on other factors, such as the expression levels of upstream transcription factors, remains poorly understood. Here we report a framework in which regulatory variants are first aggregated into sets, and using these as estimates of the total cis-genetic effects on a gene we model their non-additive interactions with the expression of other genes in the genome. Using 1220 lymphoblastoid cell lines across platforms and independent datasets we identify 74 genes where the impact of their regulatory variant-set is linked to the expression levels of networks of distal genes. We show that these networks are predominantly associated with tumourigenesis pathways, through which immortalised cells are able to rapidly proliferate. We consequently present an approach to define gene interaction networks underlying important cellular pathways such as cell immortalisation.

Common genetic variants at the MC4R locus are associated with obesity, but not with dietary energy intake or colorectal cancer in the Scottish population.

BACKGROUND: Common single-nucleotide polymorphism (SNP) variants around the melanocortin 4 receptor (MC4R) gene have recently been associated with obesity risk and insulin resistance. Obesity is a known risk factor for colorectal cancer (CRC) and we hypothesized that there might be a common inherited genetic component. METHODS AND RESULTS: Four of the variants reported earlier were genotyped and tested for association with body mass index (BMI), waist circumference (WC), dietary energy intake (DEI) and CRC. Using a case-control genetic association study, we replicated the association with BMI (P=0.0001, additive genetic effect=0.37 kg/m(2)) and WC (P=0.005, additive genetic effect=0.70 cm) using over 3800 individuals. However, there was no association between these variants and CRC risk. Rare (highly penetrant) variants within the MC4R gene have been shown to influence eating behaviour and hyperphagia. We hypothesized that the newly identified common variants might also influence hyperphagia. Using DEI data recorded from a validated food frequency questionnaire, we found no significant genetic association between MC4R SNPs and DEI. CONCLUSIONS: As the MC4R locus explains only 0.28% of the BMI and 0.14% of the WC phenotypic variance in the Scottish population, most of the genetic contribution to obesity remains to be identified.

Estimation of linkage disequilibrium in a sample of the United Kingdom dairy cattle population using unphased genotypes.

The association between genetic marker alleles was estimated for two regions of the bovine genome from a random sample of 50 young dairy bulls born in the United Kingdom between 1988 and 1995. Microsatellite marker genotypes were obtained for six markers on chromosome 2 and seven markers on chromosome 6, spanning 38 and 20 cM, respectively. Two different methods, which do not require family information, were used to estimate population haplotype frequencies. Haplotype frequencies were estimated for pairs of loci using the expectation-maximization algorithm and for all linked loci using a Bayesian approach via a Markov chain-Monte Carlo algorithm. Significant (P = 0.0007) linkage disequilibrium was detected between pairs of loci in syntenic groups (that is, loci in the same linkage group), extending to about 10 cM. No significant linkage disequilibrium was detected between markers in nonsyntenic regions. Given the observed level of linkage disequilibrium, mapping methods based on population-wide association might provide a better resolution than traditional quantitative trait loci mapping methods in the U.K. dairy cattle population and may reduce the required sample sizes of the experiments.

GWAS-based pathway analysis differentiates between fluid and crystallized intelligence.

Cognitive abilities vary among people. About 40-50% of this variability is due to general intelligence (g), which reflects the positive correlation among individuals' scores on diverse cognitive ability tests. g is positively correlated with many life outcomes, such as education, occupational status and health, motivating the investigation of its underlying biology. In psychometric research, a distinction is made between general fluid intelligence (gF) - the ability to reason in novel situations - and general crystallized intelligence (gC) - the ability to apply acquired knowledge. This distinction is supported by developmental and cognitive neuroscience studies. Classical epidemiological studies and recent genome-wide association studies (GWASs) have established that these cognitive traits have a large genetic component. However, no robust genetic associations have been published thus far due largely to the known polygenic nature of these traits and insufficient sample sizes. Here, using two GWAS datasets, in which the polygenicity of gF and gC traits was previously confirmed, a gene- and pathway-based approach was undertaken with the aim of characterizing and differentiating their genetic architecture. Pathway analysis, using genes selected on the basis of relaxed criteria, revealed notable differences between these two traits. gF appeared to be characterized by genes affecting the quantity and quality of neurons and therefore neuronal efficiency, whereas long-term depression (LTD) seemed to underlie gC. Thus, this study supports the gF-gC distinction at the genetic level and identifies functional annotations and pathways worthy of further investigation.

The genetic association between personality and major depression or bipolar disorder. A polygenic score analysis using genome-wide association data.

The relationship between major depressive disorder (MDD) and bipolar disorder (BD) remains controversial. Previous research has reported differences and similarities in risk factors for MDD and BD, such as predisposing personality traits. For example, high neuroticism is related to both disorders, whereas openness to experience is specific for BD. This study examined the genetic association between personality and MDD and BD by applying polygenic scores for neuroticism, extraversion, openness to experience, agreeableness and conscientiousness to both disorders. Polygenic scores reflect the weighted sum of multiple single-nucleotide polymorphism alleles associated with the trait for an individual and were based on a meta-analysis of genome-wide association studies for personality traits including 13,835 subjects. Polygenic scores were tested for MDD in the combined Genetic Association Information Network (GAIN-MDD) and MDD2000+ samples (N=8921) and for BD in the combined Systematic Treatment Enhancement Program for Bipolar Disorder and Wellcome Trust Case-Control Consortium samples (N=6329) using logistic regression analyses. At the phenotypic level, personality dimensions were associated with MDD and BD. Polygenic neuroticism scores were significantly positively associated with MDD, whereas polygenic extraversion scores were significantly positively associated with BD. The explained variance of MDD and BD, ∼0.1%, was highly comparable to the variance explained by the polygenic personality scores in the corresponding personality traits themselves (between 0.1 and 0.4%). This indicates that the proportions of variance explained in mood disorders are at the upper limit of what could have been expected. This study suggests shared genetic risk factors for neuroticism and MDD on the one hand and for extraversion and BD on the other.

Association analysis of the chromosome 4p15-p16 candidate region for bipolar disorder and schizophrenia.

Several independent linkage studies have identified chromosome 4p15-p16 as a putative region of susceptibility for bipolar disorder (BP), schizophrenia (SCZ) and related phenotypes. Previously, we identified two subregions (B and D) of the 4p15-p16 region that are shared by three of four 4p-linked families examined. Here, we describe a large-scale association analysis of regions B and D (3.8 and 4.5 Mb, respectively). We selected 408 haplotype-tagging single nucleotide polymorphisms (SNPs) on a block-by-block basis from the International HapMap project and tested them in 368 BP, 386 SCZ and 458 control individuals. Nominal significance thresholds were determined using principal component analysis as implemented in the program SNPSpD. In region B, overlapping SNPs and haplotypes met the region-wide threshold (P

ABCB1/MDR1 gene determines susceptibility and phenotype in ulcerative colitis: discrimination of critical variants using a gene-wide haplotype tagging approach.

Several lines of evidence suggest a role for the multidrug resistance gene (ABCB1/MDR1) and its product, P-glycoprotein 170, in the pathogenesis of inflammatory bowel disease (IBD). In addition, P-glycoprotein activity determines bioavailability of many drugs used regularly in many medical specialties, and ABCB/MDR1 variation appears to be a critical pharmacogenetic determinant. We have utilized a gene-wide haplotype tagging approach to further define the identity of germ-line variations in the ABCB1/MDR1 gene contributing to IBD susceptibility. Six haplotype tagging single nucleotide polymorphisms (tSNPs) representing the haplotypic variations of the ABCB1/MDR1 gene were identified initially following the characterization of the haplotype structure of this gene in 24 Centre d'Etude du Polymorphisme Humain Caucasian trios. Genotyping was performed in 249 ulcerative colitis (UC) and 179 Crohn's disease (CD) patients and 260 healthy controls. Using log-likelihood analysis, we observed a highly significant association between the common haplotypes and UC (P=4.22 x 10(-7)) but not CD (P=0.22). This significant association was critically dependent on one tSNP, intronic variant rs3789243. All haplotypes with this variant retained a highly significant association (P=3.2 x 10(-7)-3.6 x 10(-12)), whereas significance was lost when rs3789243 was dropped in systematic haplotypic analysis. The effect of this tSNP was independent of C3435T SNP, previously suggested to be the critical variant in disease susceptibility and drug transport. The association with UC was shown to be strongest with the phenotype of extensive disease (P=1.7 x 10(-7)). This 'candidate gene' approach provides compelling evidence to support the contribution of the ABCB1/MDR1 gene in determining risk to UC but not to CD and provides new insights into the localization of the critical susceptibility determinants within the gene. In addition, these findings have potentially important implications in the application of pharmacogenetics across a range of common diseases, including HIV, epilepsy and colorectal cancer.

Association of MUTYH and colorectal cancer.

Mutations in the MUTYH gene have been reported to be associated with increased risk of developing colorectal cancer. In this study, we confirmed this association using original data on 928 colorectal cancer cases and 845 healthy controls from Scotland. We then conducted a meta-analysis from published data on the association between mutations at MUTYH and colorectal cancer risk. We show for the first time a small but significant mono-allelic effect with a genotype relative risk (GRR) of 1.27 (95% confidence interval (CI): 1.01-1.61), and confirm and give a more precise estimate of the strong bi-allelic effect with an estimated GRR of 117 (95% CI: 74-184). This study underscores the need for large sample sizes in order to identify small gene effects when the disease allele frequency is low.

Association analysis of the chromosome 4p-located G protein-coupled receptor 78 (GPR78) gene in bipolar affective disorder and schizophrenia.

The orphan G protein-coupled receptor 78 (GPR78) gene lies within a region of chromosome 4p where we have previously shown linkage to bipolar affective disorder (BPAD) in a large Scottish family. GPR78 was screened for single-nucleotide polymorphisms (SNPs) and a linkage disequilibrium map was constructed. Six tagging SNPs were selected and tested for association on a sample of 377 BPAD, 392 schizophrenia (SCZ) and 470 control individuals. Using standard chi(2) statistics and a backwards logistic regression approach to adjust for the effect of sex, SNP rs1282, located approximately 3 kb upstream of the coding region, was identified as a potentially important variant in SCZ (chi(2) P=0.044; LRT P=0.065). When the analysis was restricted to females, the strength of association increased to an uncorrected allele P-value of 0.015 (odds ratios (OR)=1.688, 95% confidence intervals (CI): 1.104-2.581) and uncorrected genotype P-value of 0.015 (OR=5.991, 95% CI: 1.545-23.232). Under the recessive model, the genotype P-value improved further to 0.005 (OR=5.618, 95% CI: 1.460-21.617) and remained significant after correcting for multiple testing (P=0.017). No single-marker association was detected in the SCZ males, in the BPAD individuals or with any other SNP. Haplotype analysis of the case-control samples revealed several global and individual haplotypes, with P-values <0.05, all but one of which contained SNP rs1282. After correcting for multiple testing, two haplotypes remained significant in both the female BPAD individuals (P=0.038 and 0.032) and in the full sample of affected female individuals (P=0.044 and 0.033). Our results provide preliminary evidence for the involvement of GPR78 in susceptibility to BPAD and SCZ in the Scottish population.

Power of linkage disequilibrium mapping to detect a quantitative trait locus (QTL) in selected samples of unrelated individuals.

We considered a strategy to map quantitative trait loci (QTLs) using linkage disequilibrium (LD) when the QTL and marker locus were multiallelic. The strategy involved phenotyping a large number of unrelated individuals and genotyping only selected individuals from the two tails of the trait distribution. Power to detect trait-marker association was assessed as a function of the number of QTL and marker alleles. Two patterns of LD were used to study their influence on power. When the frequency of the QTL allele with the largest effect and that of the marker allele linked in coupling were equal, power was maximum. In this case, increasing the number of QTL alleles reduced the power. The maximum difference in power between the two LD patterns studied was approximately 30%. For low QTL heritabilities (h2QTL<0.1) and single trait studies we recommend selecting around 5% of the upper and lower tails of the trait distribution.