Detection of linkage between a quantitative trait and a marker locus by the lod score method: sample size and sampling considerations

A simulation study is here conducted to measure the power of the lod score method to detect linkage between a quantitative trait and a marker locus in various situations. The number of families necessary to detect such linkage with 80% power is assessed for different sets of parameters at the trait locus and different values of the recombination fraction. The effects of varying the mode of sampling families and the sibship size are also evaluated.     

Linkage between marker loci and those affecting a quantitative trait

The power of a recently proposed method of detecting linkage between marker loci and those affecting quantitative traits is shown to be very low.     

A lod score method for detecting linkage on the X chromosome between a marker locus and a major gene locus for a quantitative character

A sequential lod-score method is proposed for detecting linkage on the X chromosome between a marker locus and the locus of a major gene influencing a quantitative trait. The method uses information from sons of doubly heterozygous mothers. The average number of families required to detect linkage is substantially less than that of the fixed sample-size method proposed by Hill.Work on this article was begun while the first author was Visiting Research Fellow, Department of Psychology and Galton laboratory, University College London, 1973–1974. Preparation of this article was supported in part by grants from the Foundations Fund for Research in Psychiatry and from the National Science Foundation.     

Multivariate multipoint linkage analysis of quantitative trait loci

Resolution of the genetic components of complex disorders may require simultaneous analysis of the contribution of individual quantitative trait loci (QTLs) to multiple variables. A likelihood approach is used to illustrate how the complexities of multivariate data may be resolved with multipoint linkage analysis. Sibling pair data were simulated from a model in which two QTLs and trait-specific polygenic effects explained all the sibling resemblance within and between five variables. Multipoint linkage analysis was used to obtain individual pair probabilities of having zero, one, or two alleles identical by descent, and these probabilities were applied in a weighted maximum-likelihood fit function. The results were compared with those obtained using conventional linear structural equation modeling to estimate the contribution of latent genetic factors to the genetic covariance in the multiple measures. Both analyses were conducted using the Mx package. Relatively poor agreement was found between genetic factors defined in purely statistical terms by varimax rotation of the first two factors of the genetic covariance matrix and the structure obtained by fitting a model jointly to the phenotypic and the multipoint linkage data.     

Pedigree linkage disequilibrium mapping of quantitative trait loci

In this paper, we propose to use pedigrees of any size and any types of relatives in joint high-resolution linkage disequilibrium (LD) and linkage mapping of quantitative trait loci (QTL) by variance component models. Two or multiple markers can be simultaneously used in modeling association with the trait locus, instead of using one marker a time in the analysis. The proposed method can provide a unified result by using two or multiple markers in the modeling. This may avoid the complications of different results obtained from the separate analysis of marker by marker. The models simultaneously incorporate both linkage and LD information. The measures of LD are modeled by mean coefficients, and linkage information is modeled by variance-covariance matrix. Using analytical formulas to calculate the regression coefficients, the genetic effects are shown to be decomposed into additive and dominance components. The noncentrality parameter approximations of test statistics of LD are provided to make power calculations. Power and type I error rates are explored to investigate the merit of the proposed method by both the analytical formulas and simulations. Comparing with the association between-family and association within-family ('AbAw') approach of Fulker and Abecasis et al, it is evident that the method proposed in this article is more powerful. The method is applied to investigate the relation between polymorphisms in the angiotensin 1-converting enzyme (ACE) genes and circulating ACE levels, with a better result than that of the 'AbAw' approach. Moreover, two markers I/D and 4656(CT)3/2 can fully interpret association with the trait locus at a 0.01 significance level, which provides a unique result for the ACE data.     

Combined high resolution linkage and association mapping of quantitative trait loci

In this paper, we investigate variance component models of both linkage analysis and high resolution linkage disequilibrium (LD) mapping for quantitative trait loci (QTL). The models are based on both family pedigree and population data. We consider likelihoods which utilize flanking marker information, and carry out an analysis of model building and parameter estimations. The likelihoods jointly include recombination fractions, LD coefficients, the average allele substitution effect and allele dominant effect as parameters. Hence, the model simultaneously takes care of the linkage, LD or association and the effects of the putative trait locus. The models clearly demonstrate that linkage analysis and LD mapping are complementary, not exclusive, methods for QTL mapping. By power calculations and comparisons, we show the advantages of the proposed method: (1) population data can provide information for LD mapping, and family pedigree data can provide information for both linkage analysis and LD mapping; (2) using family pedigree data and a sparse marker map, one may investigate the prior suggestive linkage between trait locus and markers to obtain low resolution of the trait loci, because linkage analysis can locate a broad candidate region; (3) with the prior knowledge of suggestive linkage from linkage analysis, both population and family pedigree data can be used simultaneously in high resolution LD mapping based on a dense marker map, since LD mapping can increase the resolution for candidate regions; (4) models of high resolution LD mappings using two flanking markers have higher power than that of models of using only one marker in the analysis; (5) excluding the dominant variance from the analysis when it does exist would lose power; (6) by performing linkage interval mappings, one may get higher power than by using only one marker in the analysis.     

A statistically robust variance-components approach for quantitative trait linkage analysis

Previously we showed (Wang, Guerra & Cohen 1998) that a statistically robust version of the Haseman & Elston (1972) sib-pair method greatly increased power to detect linkage in the presence of outliers. In this paper we report on M-estimation to accommodate outliers in the variance-components approach to linkage analysis developed by Amos (1994). Simulations show that in the presence of outliers the robust variance-components approach provides substantially greater power, more precise estimation of heritabilities, and better false–positive rates than the original Gaussian based approach. In the absence of outliers the performance of the robust variance-components approach is similar to that of the Gaussian based approach. For illustration we apply the method to two well characterized lipoprotein systems.     

High resolution mapping of quantitative trait loci by linkage disequilibrium analysis

Two methods, linkage analysis and linkage disequilibrium (LD) mapping or association study, are usually utilised for mapping quantitative trait loci (QTL). Linkage mapping is appropriate for low resolution mapping to localise trait loci to broad chromosome regions within a few cM (<10 cM), and is based on family data. Linkage disequilibrium mapping, on the other hand, is useful in high resolution or fine mapping, and is based on both population and family data. Using only one marker, one may carry out single-point linkage analysis and linkage disequilibrium mapping. Using two or more markers, it is possible to flank the QTL by multipoint analysis. The development and thus availability of dense marker maps, such as single nucleotide polymorphisms (SNP) in human genome, presents a tremendous opportunity for multipoint fine mapping. In this article, we propose a regression approach of mapping QTL by linkage disequilibrium mapping based on population data. Assuming that two marker loci flank one quantitative trait locus, a two-point linear regression is proposed to analyse population data. We derive analytical formulas of parameter estimations, and non-centrality parameters of appropriate tests of genetic effects and linkage disequilibrium coefficients. The merit of the method is shown by the power calculation and comparison. The two-point regression model can capture much more linkage and linkage disequilibrium information than that derived when only one marker is used. For a complex disease with heritability h(2)> or =0.15, a study with sample size of 250 can provide high power for QTL detection under moderate linkage disequilibria.     

Power of variance component linkage analysis to detect quantitative trait loci

Expressions are derived for the sample size required to achieve a given power in variance component linkage analysis of a quantitative trait in unascertained samples. For simplicity an additive model, comprising effects due to a single QTL, residual additive genetic factors, and individual-specific random environmental variation, is considered. Equations are given relating sample size to trait heritability for sibpairs, sib trios, nuclear families having two and three sibs, and arbitrary relative pairs. The effects of nonzero residual additive genetic variance and parental information are discussed, and a scale relationship for sample sizes with sibships and nuclear families is derived. For larger sampling structures such as extended pedigrees the inheritance space is randomly sampled and the relevant equations are solved numerically. Comparative power curves are presented for sibships of size 2–4 and for an extended pedigree of 48 individuals. Simulation results for sibpairs confirm the validity of the theoretical results.     

A quantitative trait locus influencing anxiety in the laboratory rat

A critical test for a gene that influences susceptibility to fear in animals is that it should have a consistent pattern of effects across a broad range of conditioned and unconditioned models of anxiety. Despite many years of research, definitive evidence that genetic effects operate in this way is lacking. The limited behavioral test regimes so far used in genetic mapping experiments and the lack of suitable multivariate methodologies have made it impossible to determine whether the quantitative trait loci (QTL) detected to date specifically influence fear-related traits. Here we report the first multivariate analysis to explore the genetic architecture of rodent behavior in a battery of animal models of anxiety. We have mapped QTLs in an F2 intercross of two rat strains, the Roman high and low avoidance rats, that have been selectively bred for differential response to fear. Multivariate analyses show that one locus, on rat chromosome 5, influences behavior in different models of anxiety. The QTL influences two-way active avoidance, conditioned fear, elevated plus maze, and open field activity but not acoustic startle response or defecation in a novel environment. The direction of effects of the QTL alleles and a coincidence between the behavioral profiles of anxiolytic drug and genetic action are consistent with the QTL containing at least one gene with a pleiotropic action on fear responses. As the neural basis of fear is conserved across species, we suggest that the QTL may have relevance to trait anxiety in humans.     

Possible causal relationships between cerebellar patterns of foliation and hindlimb coordination in laboratory mice: a quantitative trait locus analysis

The cerebellum is involved in a large set of integrative functions including memory, affect, and motricity. The cerebellar patterns of foliation and their causal relationships with motricity were investigated via a wide genome scan approach and quantitative trait locus (QTL) strategy. QTLs were mapped in an F₂ population derived from NZB/B1NJ and C57BL/6By inbred strains of mice for cerebellar fissures in the four vermal lobules (intraculminate, uvula, declival, and intracentral) and for hindpaw slips in a bar crossing test. No linkage was detected for uvula and intracentral fissures. We found five QTLs linked to declival fissure: Cpfd-1q and Cpfd-2q (chromosome 1), Cpfd-3q (chromosome 5), Cpfd-4q (chromosome 9), and Cpfd-5q (chromosome 13). Two QTLs were also mapped for intraculminate fissure Cpfi-1q (chromosome 4) and Cpfi-2q (chromosome 1). Most of the confidence intervals of these QTLs included genes that were previously identified for their implication in the physiological mechanisms underlying cerebellar patterns of foliation. Only one significant QTL was found for the measure of hindpaw coordination (Tne-1q). It was linked with Cpfd-1q and Cpfd-2q on the telomeric part of chromosome 1.     

Genome-wide scan identifies a quantitative trait locus at 4p15.3 for serum urate

Elevated serum urate levels lead to gout and are associated with hypertension, metabolic syndrome, type 2 diabetes and cardiovascular diseases. The purpose of this study was to identify evidence for genetic linkage with serum urate and to determine whether variation within positional candidate genes is associated with serum urate levels in a non-European population. Genetic linkage analysis and single nucleotide polymorphism (SNP) genotyping was performed in a large family pedigree cohort from Mauritius. We assessed associations between serum urate levels and 97 SNPs in a positional candidate gene, SLC2A9. A genome-wide scan identified a new region with evidence for linkage for serum urate at 4p15.3. SNP genotyping identified significant association between six SNP variants in SLC2A9 and serum urate levels. Allelic and gender-based effects were noted for several SNPs. Significant correlations were also observed between serum urate levels and individual components of metabolic syndrome. Our study results implicate genetic variation in SLC2A9 in influencing levels of serum urate over a broad range of values in a large Mauritian family cohort.     

The arthritis severity quantitative trait locus Cia7 regulates neutrophil migration into inflammatory sites

Neutrophils are required for the development of arthritis in rodents, and are the predominant cell in the synovial fluid of active rheumatoid arthritis. We hypothesized that neutrophil migration into the inflammed joint is genetically regulated. In addition, this genetic regulation would be accounted for by one of the arthritis loci that we have previously identified in an intercross between arthritis-susceptible DA and arthritis-resistant ACI rats studied for collagen-induced arthritis. We used the synovial-like air pouch model injected with carrageenan, and tested DA, ACI, and four congenic strains. ACI exudates had a significantly lower number of neutrophils compared with DA. Transfer of DA alleles at Cia7 into the ACI background, as in ACI.DA(Cia7) congenics, was enough to increase exudate neutrophil numbers to levels identical to DA, and this locus accounted for the difference between parental strains. None of the other congenic intervals explained the differences in exudate neutrophil counts. In conclusion, we have identified a novel function for Cia7, and determined that it regulates neutrophil migration into a synovial-like inflammatory site. Our data revealed no intrinsic defect in neutrophil responses to chemotactic agents, and suggest that Cia7 regulates an as yet unidentified factor central to neutrophil recruitment into inflammed tissues.     

定位人类复杂性状位点的连锁不平衡指数研究进展

随着遗传领域中快速增长的单核苷酸多态性(single nucleotide polymorphism,SNP)和详细的人类单体型数据的获得,群体水平上的连锁不平衡(linkage disequilibrium,LD)定位或关联研究被广泛用来精细定位人类复杂性状位点.一个简单的LD定位方法的关键是选取一个优良的指数来有效地度量性状基因与它紧密相连的遗传标记之间的连锁不平衡程度.本文就精细定位人类复杂性状位点的连锁不平衡指数作一综述.     

Lack of linkage between atopy and locus 11q13

Atopy as defined in terms of IgE responsiveness was reported to be controlled by a single gene in British families, and this concept was further supported by a significant linkage between atopy and restriction fragment length polymorphism (RFLP) detected by a DNA probe specific to chromosome 11q13. To confirm this observation in a Japanese population, segregation and linkage analyses were done in four large families. Although segregation patterns of atopy were in agreement with the pattern of autosomal dominant inheritance, there was no significant linkage between atopy and locus 11q13. Alterations in the definitions of atopy did not affect the results. These findings suggested the presence of heterogeneity in genetic elements of atopy, even though atopy may be determined mainly by a single dominant gene.     

家族性精神分裂症的定量性状与1号染色体的连锁分析

目的 探讨家族性精神分裂症的定量性状位点与1号染色体的分子遗传学关系。方法 在32个家族性精神分裂症家系中，选择以下量表对精神分裂症患者的性状进行定量，包括：阳性和阴性综合征量有、功能全面评定量表、病前分裂样和分裂型特质量表、病前社会适应量表，结合1号染色体上29个DNA多态标记位点的扫描数据，进行数量性状的遗传分析。结果 精神分裂症的阴性症状在147.64cM位置得到最大Trad H-E Lod值为1.73、最大EH H－E Lod值为1.65，此区域与质量性状连锁分析在1q21-23的峰值区域重叠。结论 提示精神分裂症阴性症状在1q21-23可能有独立的数量性状位点。