Linkage disequilibrium measures for fine-scale mapping: a comparison

Genome-Wide Association Studies

Genetic association studies have made a major contribution to our understanding of the genetics of complex disorders over the last 10 years through genome-wide association studies (GWAS). In this chapter, we review the key concepts that underlie the GWAS approach. We will describe the "common disease, common variant" theory, and will review how we finally afforded to capture the common variance in genome to make GWAS possible. Finally, we will go over technical aspects of GWAS such as genotype imputation, epidemiologic designs, analysis methods, and considerations such as genomic inflation, multiple testing, and replication.

FGF-2 Gene Polymorphism in Osteoporosis among Guangxi's Zhuang Chinese

Osteoporosis is a complex multifactorial disorder of gradual bone loss and increased fracture risk. While previous studies have shown the importance of many genetic factors in determining peak bone mass and fragility fractures and in suggesting involvement of fibroblast growth factor-2 (FGF-2) in bone metabolism and bone mass, the relationship of FGF-2 genetic diversity with bone mass/osteoporosis has not yet been revealed. The current study investigated the potential relevance of FGF-2 gene polymorphism in osteoporosis among a Zhuang ethnic Chinese cohort of 623, including 237 normal bone mass controls, 227 osteopenia, and 159 osteoporosis of different ages. Bone density was examined by calcaneus ultrasound attenuation measurement, and single nucleotide polymorphisms (SNPs) and linkage disequilibrium analyses were performed on five SNP loci of FGF-2 gene. Significant differences were found in bone mass in males between the 45-year-old and ≥70-year-old groups (p < 0.01), and in females among 55, 60, 65 and 70-year-old groups (p < 0.05). Males had higher bone mass values than females in the same age (over 55-year-old) (p < 0.05). The proportions of individuals with normal bone mass decreased with age (65.2% to 40% in males, and 50% to 0% in females), whereas prevalence of osteoporosis increased with age (15.4% to 30% in men, and 7.7% to 82% in women). Out of five FGF-2 SNP loci, the TA genotype of rs308442 in the osteoporosis group (40.2%) was higher than in the control group (29.5%) (p < 0.05). The TA genotype was significantly correlated with the risk of osteoporosis (odds ratio OR = 1.653), 95% confidence interval (CI): 1.968-1.441). Strong linkage disequilibrium in FGF-2 gene was also detected between rs12644427 and rs3747676, between rs12644427 and rs3789138, and between rs3747676 and rs3789138 (D' > 0.8, and r² > 0.33). Thus, the rs308442 locus of FGF-2 gene is closely correlated to osteoporosis in this Zhuang ethnic Chinese cohort, and the TA may be the risk genotype of osteoporosis.

Conditional asymmetric linkage disequilibrium (ALD): extending the biallelic r2 measure

For multiallelic loci, standard measures of linkage disequilibrium provide an incomplete description of the correlation of variation at two loci, especially when there are different numbers of alleles at the two loci. We have developed a complementary pair of conditional asymmetric linkage disequilibrium (ALD) measures. Since these measures do not assume symmetry, they more accurately describe the correlation between two loci and can identify heterogeneity in genetic variation not captured by other symmetric measures. For biallelic loci the ALD are symmetric and equivalent to the correlation coefficient r. The ALD measures are particularly relevant for disease-association studies to identify cases in which an analysis can be stratified by one of more loci. A stratified analysis can aid in detecting primary disease-predisposing genes and additional disease genes in a genetic region. The ALD measures are also informative for detecting selection acting independently on loci in high linkage disequilibrium or on specific amino acids within genes. For SNP data, the ALD statistics provide a measure of linkage disequilibrium on the same scale for comparisons among SNPs, among SNPs and more polymorphic loci, among haplotype blocks of SNPs, and for fine mapping of disease genes. The ALD measures, combined with haplotype-specific homozygosity, will be increasingly useful as next-generation sequencing methods identify additional allelic variation throughout the genome.

Enhancing the power to detect low-frequency variants in genome-wide screens

In genetic association studies a conventional test statistic is proportional to the correlation coefficient between the trait and the variant, with the result that it lacks power to detect association for low-frequency variants. Considering the link between the conventional association test statistics and the linkage disequilibrium measure r(2), we propose a test statistic analogous to the standardized linkage disequilibrium D' to increase the power of detecting association for low-frequency variants. By both simulation and real data analysis we show that the proposed D' test is more powerful than the conventional methods for detecting association for low-frequency variants in a genome-wide setting. The optimal coding strategy for the D' test and its asymptotic properties are also investigated. In summary, we advocate using the D' test in a dominant model as a complementary approach to enhancing the power of detecting association for low-frequency variants with moderate to large effect sizes in case-control genome-wide association studies.

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.

On the uses and applications of the most commonly used measures of linkage disequilibrium from the comparative analysis of their statistical properties

BACKGROUND/OBJECTIVE

The analysis of linkage disequilibrium is relevant for the exploration of the structure and evolution of genomes and for the gene mapping of quantitative characters and human diseases. The strength of linkage disequilibrium between diallelic loci is commonly measured by the coefficients D' and r. Recent studies suggest that r is more useful than D' as a general measure of the strength of disequilibrium because it provides much more precise (lower sampling variance) and accurate (lower bias) estimates of disequilibrium. We compared for the first time the statistical properties of D' and r taking into account their differences in range.

METHODS

The sampling properties of D' and r were evaluated by simulation under a variety of realistic population conditions and varying sample sizes using standardised statistics that allow for comparisons of the precision, accuracy and efficiency of estimates with different ranges.

RESULTS

Simulations revealed that estimates of r do not tend to be significantly more precise, accurate or efficient than those of D' when compared by means of standardised statistics.

CONCLUSION

The supposed advantage of r over D' based on direct comparisons of their sampling distributions is more apparent than real. The obtained results are useful to assess the uses and applications of these widely used disequilibrium measures.

Genetic diversity, molecular phylogeny and selection evidence of the silkworm mitochondria implicated by complete resequencing of 41 genomes

Background

Mitochondria are a valuable resource for studying the evolutionary process and deducing phylogeny. A few mitochondria genomes have been sequenced, but a comprehensive picture of the domestication event for silkworm mitochondria remains to be established. In this study, we integrate the extant data, and perform a whole genome resequencing of Japanese wild silkworm to obtain breakthrough results in silkworm mitochondrial (mt) population, and finally use these to deduce a more comprehensive phylogeny of the Bombycidae.

Results

We identified 347 single nucleotide polymorphisms (SNPs) in the mt genome, but found no past recombination event to have occurred in the silkworm progenitor. A phylogeny inferred from these whole genome SNPs resulted in a well-classified tree, confirming that the domesticated silkworm, Bombyx mori, most recently diverged from the Chinese wild silkworm, rather than from the Japanese wild silkworm. We showed that the population sizes of the domesticated and Chinese wild silkworms both experience neither expansion nor contraction. We also discovered that one mt gene, named cytochrome b, shows a strong signal of positive selection in the domesticated clade. This gene is related to energy metabolism, and may have played an important role during silkworm domestication.

Conclusions

We present a comparative analysis on 41 mt genomes of B. mori and B. mandarina from China and Japan. With these, we obtain a much clearer picture of the evolution history of the silkworm. The data and analyses presented here aid our understanding of the silkworm in general, and provide a crucial insight into silkworm phylogeny.

Association methods in human genetics

Genetic association studies are increasingly used in the search for susceptibility variants for human traits. While many of the statistical tools available for such studies are well established, the field is advancing rapidly, as biological and technological developments allow investigators to generate vast amounts of detailed genetic data. This chapter gives an overview of the statistical evaluation of genetic data in both unrelated individuals and families. A brief introduction to fundamental population genetics concepts is followed by detailed examinations of measures of linkage disequilibrium and single-marker and haplotype association tests. Emphasis is given to the historical development of family-based tests to provide the context for more recent advancements. The chapter concludes with a discussion of design strategies for genetic association studies with dense genotyping of hundreds or thousands of markers, such as those planned for follow up of a linkage-candidate region or genome-wide association studies.

A population-based latent variable approach for association mapping of quantitative trait loci

A population-based latent variable approach is proposed for association mapping of quantitative trait loci (QTL), using multiple closely linked genetic markers within a small candidate region in the genome. By incorporating QTL as latent variables into a penetrance model, the QTL are flexible to characterize either alleles at putative trait loci or potential risk haplotypes/sub-haplotypes of the markers. Under a general likelihood framework, we develop an EM-based algorithm to estimate genetic effects of the QTL and haplotype frequencies of the QTL and markers jointly. Closed form solutions derived in the maximization step of the EM procedure for updating the joint haplotype frequencies of QTL and markers can effectively reduce the computational intensity. Various association measures between QTL and markers can then be derived from the haplotype frequencies of markers and used to infer QTL positions. The likelihood ratio statistic also provides a joint test for association between a quantitative trait and marker genotypes without requiring adjustment for the multiple testing. Extensive simulation studies are performed to evaluate the approach.

Haplotype homozygosity and derived alleles in the human genome

Haplotype-based techniques are being used to estimate the relative age of alleles--particularly in screening loci for signals of recent positive selection--but does this approach capture even coarse age differences? Using simulations and empirical data from the International HapMap Project, we show that a simple pairwise metric of haplotype homozygosity gives significantly higher mean values for human single-nucleotide-polymorphism alleles that appear to be derived than for those that appear to be ancestral, as determined by comparison with the chimpanzee genome. Our results support the use of haplotype-based techniques, such as extended haplotypic homozygosity, to assess the age of alleles.

Meprin beta metalloprotease gene polymorphisms associated with diabetic nephropathy in the Pima Indians

There is evidence that susceptibility to diabetic nephropathy has a significant genetic component. This investigation tested the hypothesis that variations in the structural or regulatory regions of the MEP1B gene are related to susceptibility to diabetic nephropathy in the Pima Indian population. The structure of the human MEP1B gene on chromosome 18 was determined by polymerase chain reaction (PCR) amplification. Samples from 154 diabetic individuals were analyzed for polymorphisms. These individuals belonged to 65 sibships with at least one sibling pair discordant for diabetic nephropathy. Approximately half of the individuals had diabetic nephropathy. Of the 154 samples, there were 91 discordant sibling pairs. Sequencing revealed 19 single nucleotide polymorphisms (SNPs) in the MEP1B gene. SNPs 1-5 were in the 5' region upstream of the start site for transcription; SNPs 6, 7, 9, 11-15, 17, and 19 were within introns; SNPs 8, 10, 16, and 18 were in exons 4, 9, 12, and 14. SNP 18 was the only one that results in an amino acid change (proline to leucine in the cytoplasmic tail). No overall associations were found for individual SNPs. Within-family association tests found significant results for SNPs 1, 3, 4, 5, 6, 9, 11, 18, and 19 such that the more common allele was more frequently observed in those with nephropathy than in their unaffected siblings. The present study demonstrates significant within-family association for SNPs in MEP1B gene with diabetic nephropathy. These results could be explained by functional effects of one or more of these SNPs or by linkage disequilibrium with a nearby functional locus.

Patterns of linkage disequilibrium and haplotype distribution in disease candidate genes

Background

The adequacy of association studies for complex diseases depends critically on the existence of linkage disequilibrium (LD) between functional alleles and surrounding SNP markers.

Results

We examined the patterns of LD and haplotype distribution in eight candidate genes for osteoporosis and/or obesity using 31 SNPs in 1,873 subjects. These eight genes are apolipoprotein E (APOE), type I collagen α1 (COL1A1), estrogen receptor-α (ER-α), leptin receptor (LEPR), parathyroid hormone (PTH)/PTH-related peptide receptor type 1 (PTHR1), transforming growth factor-β1 (TGF-β1), uncoupling protein 3 (UCP3), and vitamin D (1,25-dihydroxyvitamin D₃) receptor (VDR). Yin yang haplotypes, two high-frequency haplotypes composed of completely mismatching SNP alleles, were examined. To quantify LD patterns, two common measures of LD, D' and r², were calculated for the SNPs within the genes. The haplotype distribution varied in the different genes. Yin yang haplotypes were observed only in PTHR1 and UCP3. D' ranged from 0.020 to 1.000 with the average of 0.475, whereas the average r² was 0.158 (ranging from 0.000 to 0.883). A decay of LD was observed as the intermarker distance increased, however, there was a great difference in LD characteristics of different genes or even in different regions within gene.

Conclusion

The differences in haplotype distributions and LD patterns among the genes underscore the importance of characterizing genomic regions of interest prior to association studies.

Single nucleotide polymorphisms in innate immunity genes: abundant variation and potential role in complex human disease

Under selective pressure from infectious microorganisms, multicellular organisms have evolved immunological defense mechanisms, broadly categorized as innate or adaptive. Recent insights into the complex mechanisms of human innate immunity suggest that genetic variability in genes encoding its components may play a role in the development of asthma and related diseases. As part of a systematic assessment of genetic variability in innate immunity genes, we have thus far have examined 16 genes by resequencing 93 unrelated subjects from three ethnic samples (European American, African American and Hispanic American) and a sample of European American asthmatics. Approaches to discovering and understanding variation and the subsequent implementation of disease association studies are described and illustrated. Although highly conserved across a wide range of species, the innate immune genes we have sequenced demonstrate substantial interindividual variability predominantly in the form of single nucleotide polymorphisms (SNPs). Genetic variation in these genes may play a role in determining susceptibility to a range of common, chronic human diseases which have an inflammatory component. Differences in population history have produced distinctive patterns of SNP allele frequencies, linkage disequilibrium and haplotypes when ethnic groups are compared. These and other factors must be taken into account in the design and analysis of disease association studies.

Score tests for association between traits and haplotypes when linkage phase is ambiguous

A key step toward the discovery of a gene related to a trait is the finding of an association between the trait and one or more haplotypes. Haplotype analyses can also provide critical information regarding the function of a gene; however, when unrelated subjects are sampled, haplotypes are often ambiguous because of unknown linkage phase of the measured sites along a chromosome. A popular method of accounting for this ambiguity in case-control studies uses a likelihood that depends on haplotype frequencies, so that the haplotype frequencies can be compared between the cases and controls; however, this traditional method is limited to a binary trait (case vs. control), and it does not provide a method of testing the statistical significance of specific haplotypes. To address these limitations, we developed new methods of testing the statistical association between haplotypes and a wide variety of traits, including binary, ordinal, and quantitative traits. Our methods allow adjustment for nongenetic covariates, which may be critical when analyzing genetically complex traits. Furthermore, our methods provide several different global tests for association, as well as haplotype-specific tests, which give a meaningful advantage in attempts to understand the roles of many different haplotypes. The statistics can be computed rapidly, making it feasible to evaluate the associations between many haplotypes and a trait. To illustrate the use of our new methods, they are applied to a study of the association of haplotypes (composed of genes from the human-leukocyte-antigen complex) with humoral immune response to measles vaccination. Limited simulations are also presented to demonstrate the validity of our methods, as well as to provide guidelines on how our methods could be used.

Recombination in human mitochondrial DNA?

The possibility of recombination in human mitochondrial DNA (mtDNA) has been hotly debated over the last few years. In this study, a general model of recombination in circular molecules is developed and applied to a recently published African sample (n = 21) of complete mtDNA sequences. It is shown that the power of correlation measures to detect recombination in circular molecules can be vanishingly small and that the data are consistent with the given model and no recombination only if the overall heterogeneity in mutation rate is <0.09.

Association mapping: where we've been, where we're going

This paper provides a review of recent work in the area of marker-phenotype association studies, specifically as used for localizing--or mapping--genes affecting a trait of interest. We describe the basis of association mapping and discuss a number of the commonly used techniques. We have also included references to various papers that have evaluated the use of these methods.

A note on the evaluation of fluctuation experiments

Fluctuation analysis has emerged as a valuable tool for the measurement of mutation rates in single-cell populations. In this paper, we show how to make fuller use of the information supplied by the outcome of a fluctuation experiment. We shall extend Lea and Coulson's theory of the Luria-Delbrück distribution so that it accounts for residual mutation, reduced plating efficiency of mutants, and phenotypic lag, and establish a unifying method for the evaluation of fluctuation experiments in these cases and discuss its limitations. It will be proved that not all factors that might influence the distribution of mutant colonies in a fluctuation experiment can, in effect, be determined simultaneously. Nevertheless, it will be shown that the fluctuation-analytic approach to the measurement of mutation rates may retain its value in comparison with (or may even be superior to) alternative methods. Finally, we give some numerical examples to illustrate our results.

Genetics, environment and cognitive abilities: review and work in progress towards a genome scan for quantitative trait locus associations using DNA pooling

BACKGROUND

Multivariate genetic research indicates that genetic effects on diverse cognitive abilities are general rather than specific or modular. General cognitive ability (g), a key factor in learning and memory, is among the most heritable behavioural traits.

AIMS

To give a brief overview of quantitative genetic research on g and to describe initial results from a programme of research that aims to identify genes responsible for the substantial heritability of general cognitive ability.

METHOD

The research uses a new technique called DNA pooling, which combines DNA from individuals within a group and makes it feasible to screen thousands of DNA markers for a systematic scan of the genome for associations between DNA markers and g. Two independent samples of children with very high g scores and two control samples of children with average g scores were compared in a systematic scan of 147 markers on chromosome 4 and 66 markers on chromosome 22.

RESULTS

Three replicated associations on chromosome 4 were identified using DNA pooling and confirmed using individual genotyping.

CONCLUSIONS

These first results of the application of DNA pooling in systematic analysis of allelic association are encouraging.

The genetics of phenylthiocarbamide perception

The ability to taste the bitter compound phenylthiocarbamide (PTC) and related chemicals is bimodal, and all human populations tested to date contain some people who can and some people who cannot taste PTC. Why this trait has been maintained in the population is uncertain but this polymorphism may influence food selection, nutritional status or thyroid metabolism. The gene product that gives rise to this phenotype is unknown, and its characterization would provide insight into the mechanism of bitter taste perception. Although this trait is often considered a simple Mendelian trait, i.e. one gene two alleles, a recent linkage study found a major locus on chromosome 5p15 and evidence for an additional locus on chromosome 7. The development of methods to identify these genes will provide a good stepping-stone between single-gene disorders and polygenic traits.

A chronology of fine-scale gene mapping by linkage disequilibrium

The past decade produced several proposals for fine-scale gene mapping using linkage disequilibrium data. The suggested methods fall into two main groups, those that rely on pairwise statistics and those that rely on haplotypes. This paper reviews each strategy's development from a chronological perspective.

Analysis of European mtDNAs for recombination

The standard paradigm postulates that the human mitochondrial genome (mtDNA) is strictly maternally inherited and that, consequently, mtDNA lineages are clonal. As a result of mtDNA clonality, phylogenetic and population genetic analyses should therefore be free of the complexities imposed by biparental recombination. The use of mtDNA in analyses of human molecular evolution is contingent, in fact, on clonality, which is also a condition that is critical both for forensic studies and for understanding the transmission of pathogenic mtDNA mutations within families. This paradigm, however, has been challenged recently by Eyre-Walker and colleagues. Using two different tests, they have concluded that recombination has contributed to the distribution of mtDNA polymorphisms within the human population. We have assembled a database that comprises the complete sequences of 64 European and 2 African mtDNAs. When this set of sequences was analyzed using any of three measures of linkage disequilibrium, one of the tests of Eyre-Walker and colleagues, there was no evidence for mtDNA recombination. When their test for excess homoplasies was applied to our set of sequences, only a slight excess of homoplasies was observed. We discuss possible reasons that our results differ from those of Eyre-Walker and colleagues. When we take the various results together, our conclusion is that mtDNA recombination has not been sufficiently frequent during human evolution to overturn the standard paradigm.

Discovery of cancer susceptibility genes: study designs, analytic approaches, and trends in technology

Determining the genetic causes of cancers has immense public health benefits, ranging from prevention to earlier detection and treatment of disease. Although a number of cancer susceptibility genes have been successfully identified, design and analytic issues remain that challenge the current paradigm of gene discovery. Some examples are the definition and measurement of cancer phenotype, the use of intermediate end points, the choice of sample (e.g., affected relative pairs versus large extended pedigrees), the choice of analytic method [e.g., parametric logarithm of the odds (LOD) score method versus model-free methods], and the influence of gene-environment interaction on linkage analysis. Furthermore, association methods, based on either the traditional case-control study design or family-based controls, are popular choices to evaluate candidate genes or screen for linkage disequilibrium. Finally, the study design and analytic methods for gene discovery are determined to some extent by what genomic technology is feasible within the laboratory. Many of the main issues related to gene discovery, as well as trends in genomic technology that will impact on gene discovery, are discussed from the perspective of their strengths and weaknesses, pointing to areas in need of further work.

Significant evidence for linkage disequilibrium over a 5-cM region among Afrikaners

We explore the extent of deviations from Hardy-Weinberg equilibrium (HWE) at a marker locus and linkage disequilibrium (LD) between pairs of marker loci in the Afrikaner population of South Africa. DNA samples were used for genotyping of 23 loci on six chromosomes. The samples were collected from 91 healthy unrelated Afrikaner adults. Exact tests were used to determine evidence for deviations from HWE at a single marker locus or LD between pairs of marker loci. At the 0.05 level of significance, evidence was found for deviation from HWE at only one of the 23 loci. At the same level of significance, LD was found among 8 of the 34 intrachromosomal pairs of loci. On chromosome 21, there was evidence for LD (P = 0.02) between a pair of loci with a genetic distance of 5.51 cM. On chromosome 2, there was evidence for LD between a pair of loci with a genetic distance of 5.28 cM (P = 0.002) and a pair of loci with a genetic distance of 3.68 cM (P = 0.0004). Detailed analysis of LD for one locus pair indicated that only a few of all alleles participated in the LD and that strong LD was most often positive. Our findings indicate that Afrikaans-speaking Afrikaners represent one of those special populations deemed particularly suitable for disequilibrium mapping.

Linkage detection adaptive to linkage disequilibrium: the disequilibrium maximum-likelihood-binomial test for affected-sibship data

It has been demonstrated in the literature that the transmission/disequilibrium test (TDT) has higher power than the affected-sib-pair (ASP) mean test when linkage disequilibrium (LD) is strong but that the mean test has higher power when LD is weak. Thus, for ASP data, it seems clear that the TDT should be used when LD is strong but that the mean test or other linkage tests should be used when LD is weak or absent. However, in practice, it may be difficult to follow such a guideline, because the extent of LD is often unknown. Even with a highly dense genetic-marker map, in which some markers should be located near the disease-predisposing mutation, strong LD is not inevitable. Besides the genetic distance, LD is also affected by many factors, such as the allelic heterogeneity at the disease locus, the initial LD, the allelic frequencies at both disease locus and marker locus, and the age of the mutation. Therefore, it is of interest to develop methods that are adaptive to the extent of LD. In this report, we propose a disequilibrium maximum-binomial-likelihood (DMLB) test that incorporates LD in the maximum-binomial-likelihood (MLB) test. Examination of the corresponding score statistics shows that this method adaptively combines two sources of information: (a) the identity-by-descent (IBD) sharing score, which is informative for linkage regardless of the existence of LD, and (b) the contrast between allele-specific IBD sharing score, which is informative for linkage only in the presence of LD. For ASP data, the proposed test has higher power than either the TDT or the mean test when the extent of LD ranges from moderate to strong. Only when LD is very weak or absent is the DMLB slightly less powerful than the mean test; in such cases, the TDT has essentially no power to detect linkage. Therefore, the DMLB test is an interesting approach to linkage detection when the extent of LD is unknown.

DNA pooling and dense marker maps: a systematic search for genes for cognitive ability

Pooling DNA from subjects within a group and comparing the pooled DNA across groups for a dense map of DNA markers offers a solution to the conundrum that linkage is systematic but not powerful whereas allelic association is powerful but not systematic. We used DNA pooling to screen 66 markers on chromosome 22 in original and replication samples of children of high general cognitive ability (g) and controls of average g. Although none of these markers survived our three-stage screening design (original pooling, replication pooling, individual genotyping), the results of DNA pooling were largely confirmed by individual genotyping. We can therefore exclude associations of major effect size on chromosome 22 for g, a key variable for cognitive neuroscience research on learning and memory.

The integration of microarray information in the drug development process

In the past year, microarray technologies have moved beyond the proof-of-principle stage. Microarrays are now being used for genome-wide expression monitoring, large-scale polymorphism screening and mapping, and for the evaluation of drug candidates.

Mapping of complex traits by single-nucleotide polymorphisms

Molecular geneticists are developing the third-generation human genome map with single-nucleotide polymorphisms (SNPs), which can be assayed via chip-based microarrays. One use of these SNP markers is the ability to locate loci that may be responsible for complex traits, via linkage/linkage-disequilibrium analysis. In this communication, we describe a semiparametric method for combined linkage/linkage-disequilibrium analysis using SNP markers. Asymptotic results are obtained for the estimated parameters, and the finite-sample properties are evaluated via a simulation study. We also applied this technique to a simulated genome-scan experiment for mapping a complex trait with two major genes. This experiment shows that separate linkage and linkage-disequilibrium analyses correctly detected the signals of both major genes; but the rates of false-positive signals seem high. When linkage and linkage-disequilibrium signals were combined, the analysis yielded much stronger and clearer signals for the presence of two major genes than did two separate analyses.