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PubMed2003

Mathematical multi-locus approaches to localizing complex human trait genes.

Statistical analysis methods for gene mapping originated in counting recombinant and non-recombinant offspring, but have now progressed to sophisticated approaches for the mapping of complex trait genes. Here, we outline new statistical methods that capture the simultaneous effects of multiple gene loci and thereby achieve a more global view of gene action and interaction than is possible by traditional gene-by-gene analysis. We aim to show that the work of statisticians goes far beyond the running of computer programs.

Biometry↗
PubMed1993

Two-trait-locus linkage analysis: a powerful strategy for mapping complex genetic traits.

Recent advances in molecular biology have provided geneticists with ever-increasing numbers of highly polymorphic genetic markers that have made possible linkage mapping of loci responsible for many human diseases. However, nearly all diseases mapped to date follow clear Mendelian, single-locus segregation patterns. In contrast, many common familial diseases such as diabetes, psoriasis, several forms of cancer, and schizophrenia are familial and appear to have a genetic component but do not exhibit simple Mendelian transmission. More complex models are required to explain the genetics of these important diseases. In this paper, we explore two-trait-locus, two-marker-locus linkage analysis in which two trait loci are mapped simultaneously to separate genetic markers. We compare the utility of this approach to standard one-trait-locus, one-marker-locus linkage analysis with and without allowance for heterogeneity. We also compare the utility of the two-trait-locus, two-marker-locus analysis to two-trait-locus, one-marker-locus linkage analysis. For common diseases, pedigrees are often bilineal, with disease genes entering via two or more unrelated pedigree members. Since such pedigrees often are avoided in linkage studies, we also investigate the relative information content of unilineal and bilineal pedigrees. For the dominant-or-recessive and threshold models that we consider, we find that two-trait-locus, two-marker-locus linkage analysis can provide substantially more linkage information, as measured by expected maximum lod score, than standard one-trait-locus, one-marker-locus methods, even allowing for heterogeneity, while, for a dominant-or-dominant generating model, one-locus models that allow for heterogeneity extract essentially as much information as the two-trait-locus methods. For these three models, we also find that bilineal pedigrees provide sufficient linkage information to warrant their inclusion in such studies. We also discuss strategies for assessing the significance of the two linkages assumed in two-trait-locus, two-marker-locus models.

Chromosome Mapping↗
PubMed2002

Genetics and social class.

OBJECTIVE: To assess claims that genes are a major determinant of social class. DESIGN: Using genetic epidemiological principles, five claims on the role of genes in determining social class are examined: (1) traits that run in families are usually inherited; (2) complex traits can be explained by alleles at a single gene locus; (3) complex traits are transmitted intact from one generation to the next; (4) natural selection explains social advantage. (5) Heritability estimates provide a valid estimate of the importance of genes in explaining complex human traits or behaviour. RESULTS: (1) Traits that run in families can result from environmental exposures that differ by social class. (2) The protein encoded by any single gene has too narrow a range of biological activity to explain traits as complex as social status. (3) Because alleles at different gene loci are transmitted independently, genetic inheritance cannot explain why offspring display the same complex traits as their parents. (4) The propagation of mutations that might result in a selective advantage takes much longer than the time for which any social class has achieved or maintained dominance. (5) Heritability measures are accurate only when environment is maintained constant. This is impossible in evaluating human traits. CONCLUSIONS: The roots of social class differences do not lie in our genes. Consequently, genetics cannot be used as a justification for maintaining a ruling class, limiting procreation among the poor, or minimising social support programmes.

Environment↗
PubMed2005

Integrating genotypic and expression data in a segregating mouse population to identify 5-lipoxygenase as a susceptibility gene for obesity and bone traits.

Forward genetic approaches to identify genes involved in complex traits such as common human diseases have met with limited success. Fine mapping of linkage regions and validation of positional candidates are time-consuming and not always successful. Here we detail a hybrid procedure to map loci involved in complex traits that leverages the strengths of forward and reverse genetic approaches. By integrating genotypic and expression data in a segregating mouse population, we show how clusters of expression quantitative trait loci linking to regions of the genome accurately reflect the underlying perturbation to the transcriptional network induced by DNA variations in genes that control the complex traits. By matching patterns of gene expression in a segregating population with expression responses induced by single-gene perturbation experiments, we show how genes controlling clusters of expression and clinical quantitative trait loci can be mapped directly. We demonstrate the utility of this approach by identifying 5-lipoxygenase as underlying previously identified quantitative trait loci in an F(2) cross between strains C57BL/6J and DBA/2J and showing that it has pleiotropic effects on body fat, lipid levels and bone density.

Animals↗
PubMed2025

Optimized phenotyping of complex morphological traits: enhancing discovery of common and rare genetic variants.

Genotype-phenotype (G-P) analyses for complex morphological traits typically utilize simple, predetermined anatomical measures or features derived via unsupervised dimension reduction techniques (e.g. principal component analysis (PCA) or eigen-shapes). Despite the popularity of these approaches, they do not necessarily reveal axes of phenotypic variation that are genetically relevant. Therefore, we introduce a framework to optimize phenotyping for G-P analyses, such as genome-wide association studies (GWAS) of common variants or rare variant association studies (RVAS) of rare variants. Our strategy is two-fold: (i) we construct a multidimensional feature space spanning a wide range of phenotypic variation, and (ii) within this feature space, we use an optimization algorithm to search for directions or feature combinations that are genetically enriched. To test our approach, we examine human facial shape in the context of GWAS and RVAS. In GWAS, we optimize for phenotypes exhibiting high heritability, estimated from either family data or genomic relatedness measured in unrelated individuals. In RVAS, we optimize for the skewness of phenotype distributions, aiming to detect commingled distributions that suggest single or few genomic loci with major effects. We compare our approach with eigen-shapes as baseline in GWAS involving 8246 individuals of European ancestry and in gene-based tests of rare variants with a subset of 1906 individuals. After applying linkage disequilibrium score regression to our GWAS results, heritability-enriched phenotypes yielded the highest SNP heritability, followed by eigen-shapes, while commingling-based traits displayed the lowest SNP heritability. Heritability-enriched phenotypes also exhibited higher discovery rates, identifying the same number of independent genomic loci as eigen-shapes with a smaller effective number of traits. For RVAS, commingling-based traits resulted in more genes passing the exome-wide significance threshold than eigen-shapes, while heritability-enriched phenotypes lead to only a few associations. Overall, our results demonstrate that optimized phenotyping allows for the extraction of genetically relevant traits that can specifically enhance discovery efforts of common and rare variants, as evidenced by their increased power in facial GWAS and RVAS.

Humans↗
PubMed1998

Telomeres, hidden mosaicism, loss of heterozygosity, and complex genetic traits.

Telomeres appear to function as an endogenous timing mechanism in human beings. Telomere attrition not only provides a satisfactory explanation for some aspects of aging, it might also resolve enigmatic features of complex genetic traits that are age-dependent. If, with the passage of time, telomere attrition in human beings leads to genomic instability and particularly the loss of chromosomes, then the age dependency of phenotypic expressions of complex genetic traits might result from the temporal loss of heterozygosity and the consequent expression of disease-causing genes. In this way, telomere attrition might play a role not only in aging, but also in the diverse expression of complex genetic traits, such as essential hypertension, non-insulin-dependent diabetes mellitus, atherosclerosis, and cancer.

Aging↗
PubMed2004

Regulatory polymorphisms underlying complex disease traits.

There is growing evidence that genetic variation plays an important role in the determination of individual susceptibility to complex disease traits. In contrast to coding sequence polymorphisms, where the consequences of non-synonymous variation may be resolved at the level of the protein phenotype, defining specific functional regulatory polymorphisms has proved problematic. This has arisen for a number of reasons, including difficulties with fine mapping due to linkage disequilibrium, together with a paucity of experimental tools to resolve the effects of non-coding sequence variation on gene expression. Recent studies have shown that variation in gene expression is heritable and can be mapped as a quantitative trait. Allele-specific effects on gene expression appear relatively common, typically of modest magnitude and context specific. The role of regulatory polymorphisms in determining susceptibility to a number of complex disease traits is discussed, including variation at the VNTR of INS, encoding insulin, in type 1 diabetes and polymorphism of CTLA4, encoding cytotoxic T lymphocyte antigen, in autoimmune disease. Examples where regulatory polymorphisms have been found to play a role in mongenic traits such as factor VII deficiency are discussed, and contrasted with those polymorphisms associated with ischaemic heart disease at the same gene locus. Molecular mechanisms operating in an allele-specific manner at the level of transcription are illustrated, with examples including the role of Duffy binding protein in malaria. The difficulty of resolving specific functional regulatory variants arising from linkage disequilibrium is demonstrated using a number of examples including polymorphism of CCR5, encoding CC chemokine receptor 5, and HIV-1 infection. The importance of understanding haplotypic structure to the design and interpretation of functional assays of putative regulatory variation is highlighted, together with discussion of the strategic use of experimental tools to resolve regulatory polymorphisms at a transcriptional level. A number of examples are discussed including work on the TNF locus which demonstrate biological and experimental context specificity. Regulatory variation may also operate at other levels of control of gene expression and the modulation of splicing at PTPRC, encoding protein tyrosine phosphatase receptor-type C, and of translational efficiency at F12, encoding factor XII, are discussed.

Autoimmune Diseases↗
PubMed2002

Segregation of experimental autoimmune glomerulonephritis as a complex genetic trait and exclusion of Col4a3 as a candidate gene.

Experimental autoimmune glomerulonephritis (EAG), an animal model of Goodpasture's disease, can be induced in Wistar-Kyoto (WKY) rats (RT1-l) by immunization with rat glomerular basement membrane (GBM) in adjuvant. The model in this rat strain is characterized by anti-GBM antibody production accompanied by focal necrotizing glomerulonephritis with crescent formation. The main autoantigen in humans and rats has been identified as the non-collagenous domain of the alpha3 chain of type IV collagen (alpha3(IV)NC1). By contrast, Lewis (LEW) rats with the same MHC background (RT1-l), immunized with the same antigen, develop similar levels of circulating anti-GBM antibodies, but no histological evidence of nephritis. In order to investigate the genetic basis of susceptibility to EAG, we examined the response of both F1 (WKY x LEW) and backcross (BC1; WKY x F1) rats to immunization with rat GBM. F1 animals were completely resistant to the development of EAG, while BC1 animals showed a range of responses from severe crescentic glomerulonephritis to no histological evidence of disease. The results indicate that EAG is inherited as a complex trait under the control of WKY genes unlinked to the MHC. cDNA sequence analysis of alpha3(IV)NC1 in the two parental strains was identical, indicating no predicted amino acid sequence variation in the alpha3(IV)NC1 domain between these strains. Radiation hybrid mapping, using two separate PCR amplicons from rat alpha3(IV)NC1, localized rat Col4a3 to a region of chromosome 9. Since Col4a3 (encoding the autoantigen) is a candidate for susceptibility to EAG, we screened the region of rat chromosome 9 where Col4a3 is localized, using polymorphic microsatellite markers in segregating BC1 progeny. No significant linkage was detected. These results exclude Col4a3 as a recessive susceptibility gene for EAG in the BC1 progeny.

Amino Acid Sequence↗
PubMed1996

Resistance to mycoplasmal lung disease in mice is a complex genetic trait.

Mouse strains differ markedly in resistance to Mycoplasma pulmonis infection, and investigation of these differences holds much promise for understanding the mechanisms of antimycoplasmal host defenses. To determine the potential genetic diversity of resistance to disease in murine respiratory mycoplasmosis (MRM) and to select disease-resistant and nonresistant mouse strains for further genetic analysis, we screened 17 inbred mouse strains of various Bcg and H-2 genotypes for resistance to M. pulmonis. Mice were inoculated intranasally with 10(4) CFU of M. pulmonis UAB CT and evaluated at 21 days postinfection for severities of the four histologic lung lesions characteristic of MRM: alveolar exudate, airway exudate, airway epithelial hyperplasia, and lymphoid infiltrate. On the basis of these assessments of MRM severity, one group of mouse strains was found to be extremely resistant to disease (C57BR/cdJ, C57BL/6NCr, C57BL/10ScNCr, and C57BL/6J). The remaining strains of mice (C57L/J, SJL/NCr, BALB/cAnNCr, A/JCr, C3H/HeJ, SWR/J, AKR/NCr, CBA/NCr, C58/J, DBA/2NCr, C3H/HeNCr, C3HeB/FeJ, and C3H/HeJCr) developed disease of widely varying severities. Furthermore, strains in the group with more disease varied in pattern of lesion severity. While the severities of all four lesions were correlated in most mouse strains, this was not always true. DBA/2NCr mice had one of the highest scores for alveolar exudate, only a moderate score for airway exudate, and significantly lower scores for both airway epithelial hyperplasia and lymphoid infiltrate than all other strains susceptible to lung disease. DBA/2NCr mice had one of the highest mortality rates. We concluded that resistance to MRM is a complex trait. The observed differences in lung disease severity could not be explained by known differences at the Bcg or H-2 locus in the strains of mice we studied.

Animals↗
PubMed2002

Genetics of Cd36 and the hypertension metabolic syndrome.

Although genetic mapping of quantitative trait loci (QTL) for complex traits related to hypertension is relatively straightforward, the identification of QTL at the molecular level has proven far more difficult. By combining techniques of gene mapping and gene expression profiling with studies in congenic and transgenic strains, a specific molecular defect in the Cd36 fatty acid transporter has been identified that contributes to the pathogenesis of 2 complex traits in the spontaneously hypertensive rat (SHR), namely, insulin resistance and disordered fatty acid metabolism. After mapping QTL linked to insulin resistance and dyslipidemia to the telomeric region of SHR chromosome 4, gene expression studies were used to identify candidate genes within the target chromosome segment that were differentially expressed in white adipose tissue between SHR congenic strains. This led to the identification of a major mutation in the SHR gene encoding Cd36, a fatty acid transporter involved in the transmembrane transport of long-chain fatty acids. The role for mutant Cd36 in the pathogenesis of insulin resistance and dyslipidemia was confirmed by rescuing the abnormal metabolic phenotypes through transgenic expression of wild-type Cd36 on the SHR background. These findings show that a primary defect in fatty acid transport can promote disordered carbohydrate metabolism in the SHR and show the power of advanced genome technologies for identifying QTL at the molecular level.

Animals↗
PubMed2006

A statistical framework for genome-wide scanning and testing of imprinted quantitative trait loci.

Non-equivalent expression of alleles at a locus results in genomic imprinting. In this article, a statistical framework for genome-wide scanning and testing of imprinted quantitative trait loci (iQTL) underlying complex traits is developed based on experimental crosses of inbred line species in backcross populations. The joint likelihood function is composed of four component likelihood functions with each of them derived from one of four backcross families. The proposed approach models genomic imprinting effect as a probability measure with which one can test the degree of imprinting. Simulation results show that the model is robust for identifying iQTL with various degree of imprinting ranging from no imprinting, partial imprinting to complete imprinting. Under various simulation scenarios, the proposed model shows consistent parameter estimation with reasonable precision and high power in testing iQTL. When a QTL shows Mendelian effect, the proposed model also outperforms traditional Mendelian model. Extension to incorporate maternal effect is also given. The developed model, built within the maximum likelihood framework and implemented with the EM algorithm, provides a quantitative framework for testing and estimating iQTL involved in the genetic control of complex traits.

Algorithms↗
PubMed2002

Gene finding strategies.

Both linkage and association methods have been used to localise and identify genes related to behaviour and other complex traits. The linkage approach (parametric or non-parametric) can be used for whole genome screens to localise genes of unknown function. The parametric linkage approach is very effective for locating single-gene disorders and is usually based on large family pedigrees. The non-parametric method is useful to detect quantitative trait loci (QTLs) for complex traits and was originally developed for sib pair analyses. Genetic association studies are most often used to test the association of alleles at a candidate gene with a disease or with levels of a quantitative trait. Allelic association between a trait and a marker can be studied in a case-control design, but because of possible problems due to population stratification, within-family designs have been proposed as the optimal test for association.

Alleles↗
PubMed1998

Genome-wide search for asthma susceptibility loci in a founder population. The Collaborative Study on the Genetics of Asthma.

Founder populations offer many advantages for mapping genetic traits, particularly complex traits that are likely to be genetically heterogeneous. To identify genes that influence asthma and asthma-associated phenotypes, we conducted a genome-wide screen in the Hutterites, a religious isolate of European ancestry. A primary sample of 361 individuals and a replication sample of 292 individuals were evaluated for asthma phenotypes according to a standardized protocol. A genome-wide screen has been completed using 292 autosomal and three X-Y pseudoautosomal markers. Using the semi-parametric likelihood ratio chi2 test and the transmission-disequilibrium test, we identified 12 markers in 10 regions that showed possible linkage to asthma or an associated phenotype (likelihood ratio P < 0.01). Markers in four regions (5q23-31, 12q15-24.1, 19q13 and 21q21) showed possible linkage in both the primary and replication samples and have also shown linkage to asthma phenotypes in other samples; two adjacent markers in one additional region (3p24.2-22) showing possible linkage is reported for the first time in the Hutterites. The results suggest that even in founder populations with a relatively small number of independent genomes, susceptibility alleles at many loci may influence asthma phenotypes and that these susceptibility alleles are likely to be common polymorphisms in the population.

Adolescent↗
PubMed2001

Genomewide linkage analysis of stature in multiple populations reveals several regions with evidence of linkage to adult height.

Genomewide linkage analysis has been extremely successful at identification of the genetic variation underlying single-gene disorders. However, linkage analysis has been less successful for common human diseases and other complex traits in which multiple genetic and environmental factors interact to influence disease risk. We hypothesized that a highly heritable complex trait, in which the contribution of environmental factors was relatively limited, might be more amenable to linkage analysis. We therefore chose to study stature (adult height), for which heritability is approximately 75%-90% (Phillips and Matheny 1990; Carmichael and McGue 1995; Preece 1996; Silventoinen et al. 2000). We reanalyzed genomewide scans from four populations for which genotype and height data were available, using a variance-components method implemented in GENEHUNTER 2.0 (Pratt et al. 2000). The populations consisted of 408 individuals in 58 families from the Botnia region of Finland, 753 individuals in 183 families from other parts of Finland, 746 individuals in 179 families from Southern Sweden, and 420 individuals in 63 families from the Saguenay-Lac-St.-Jean region of Quebec. Four regions showed evidence of linkage to stature: 6q24-25, multipoint LOD score 3.85 at marker D6S1007 in Botnia (genomewide P<.06), 7q31.3-36 (LOD 3.40 at marker D7S2195 in Sweden, P<.02), 12p11.2-q14 (LOD 3.35 at markers D12S10990-D12S398 in Finland, P<.05) and 13q32-33 (LOD 3.56 at markers D13S779-D13S797 in Finland, P<.05). In a companion article (Perola et al. 2001 [in this issue]), strong supporting evidence is obtained for linkage to the region on chromosome 7. These studies suggest that highly heritable complex traits such as stature may be genetically tractable and provide insight into the genetic architecture of complex traits.

Body Height↗
PubMed2003

Effects of covariates: a summary of Group 5 contributions.

This report summarizes the contributions of Genetic Analysis Workshop 13 (GAW13) related to the use of covariates in genetic analysis. Seven papers are summarized, five of which analyzed the Framingham Heart Study Data, and two the simulated data. Five papers examined the role of covariates in linkage analysis, using a variety of statistical approaches including affected sibling pair analysis, conditional logistic regression, and variance components methods. One paper examined the impact of covariates on family-based association analysis. In each of these papers, the detection of genetic effects could be influenced by the incorporation of covariates. The final paper examined the role of transmission ratio distortion in the analysis of complex traits and the role of covariates in the variability in transmission ratio distortion. While each paper takes a different approach to the genetic analysis of complex traits, a common thread running through each is that the inclusion of covariates can have a substantial impact on the results of the analysis. Care must be taken to understand how the covariates are being used in each analysis, what assumptions are being made, and how these assumptions might affect the results and their interpretation. Finally, the results of Group 5 studies show that inclusion of covariates can increase the power to detect genes for complex traits, and has the potential to advance an understanding of the role of genes in these complex traits.

Cardiovascular Diseases↗
PubMed2002

Modulation of multiple experimental arthritis models by collagen-induced arthritis quantitative trait loci isolated in congenic rat lines: different effects of non-major histocompatibility complex quantitative trait loci in males and females.

OBJECTIVE: Collagen-induced arthritis (CIA) is a model of inflammatory arthritis with many similarities to rheumatoid arthritis (RA). We previously mapped in F(2) offspring of CIA-susceptible DA and CIA-resistant F344 rats, 5 quantitative trait loci (QTLs) for which F344 alleles were associated with reduced CIA severity. In the present study, we sought to characterize the independent arthritis-modulating effects of these 5 QTLs. METHODS: CIA-regulatory regions were transferred from the F344 genome to the DA background or vice versa by repeated backcrossing. The arthritis-modulating effects of the transferred alleles were determined by comparing the severity of experimentally induced arthritis in congenic rats with that in DA rats. RESULTS: Congenic lines with either the F344 major histocompatibility complex (MHC) on the DA background or the DA MHC on the F344 background were resistant to CIA, confirming both MHC and non-MHC contributions to the genetic regulation of CIA. F344 alleles at the Cia3 and Cia5 regions of chromosomes 4 and 10 reduced CIA severity relative to that observed in DA rats. F344 Cia4 and Cia6 regions of chromosomes 7 and 8 failed to significantly alter CIA severity. Arthritis-modifying effects of Cia4 and Cia6 were, however, detected in pristane-induced and/or Freund's incomplete adjuvant oil-induced arthritis. The arthritis-modifying effects of the non-MHC CIA-regulatory loci differed in males and females. CONCLUSION: These congenic lines confirmed the existence and location of genes that regulate the severity of experimental arthritis in rats. Mechanisms responsible for the sex-specificity of individual arthritis-regulatory loci may explain some of the sex differences observed in RA and other autoimmune diseases in humans.

Animals↗
PubMedDate not supplied

Mapping behavioral traits by use of genome-tagged mice.

OBJECTIVE: Complex trait mapping has been widely used to analyze the genetics of behavior. However, the approach has some disadvantages, including poor gene localization and low replicability. Genome-tagged mice (GTMs) are sets of congenic mouse strains that span the entire mouse genome and are a promising reagent for localization of genes contributing to behavior. METHODS: In order to map behavioral loci of interest, a GTM was investigated in which the middle region of Chromosome 1 from DBA/2J was introgressed onto a C57BL/6J background. The GTM was analyzed for behaviors related to sensorimotor gating, anxiety, depression, pain sensitivity, and learning and memory. RESULTS: The GTM was found to harbor a locus contributing to learning and memory, replicating results from complex trait analysis. CONCLUSIONS: The GTMs should be a valuable resource for mapping and confirmation of loci contributing to complex behavioral traits in the mouse, with ultimate implications for human genomic-based research, as well.

Animals↗
PubMed2006

Advances in cereal genomics and applications in crop breeding.

Recent advances in cereal genomics have made it possible to analyse the architecture of cereal genomes and their expressed components, leading to an increase in our knowledge of the genes that are linked to key agronomically important traits. These studies have used molecular genetic mapping of quantitative trait loci (QTL) of several complex traits that are important in breeding. The identification and molecular cloning of genes underlying QTLs offers the possibility to examine the naturally occurring allelic variation for respective complex traits. Novel alleles, identified by functional genomics or haplotype analysis, can enrich the genetic basis of cultivated crops to improve productivity. Advances made in cereal genomics research in recent years thus offer the opportunities to enhance the prediction of phenotypes from genotypes for cereal breeding.

Alleles↗