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Complex Traits (complex + trait)
Selected AbstractsThird international meeting on the genetic epidemiology of complex traits, April 4,6, 2002, Cambridge, UKHUMAN MUTATION, Issue 3 2002Sally John Abstract The Third International Meeting on the Genetic Epidemiology of Complex Traits was held at Churchill College, Cambridge, UK on April 4,6, 2002. The event was organized by the Twin Research and Genetic Epidemiology Unit, St Thomas' Hospital, London and sponsored by Roche Genetics and Insightful. It provided an interactive forum for discussion of topical issues relating to the genetic analysis of complex diseases and traits. Topics discussed included linkage disequilibrium mapping and candidate gene analysis, as well as cutting edge advances in both technologies and statistical analysis methods. Details of the meeting can be found at http://www.twin-research.ac.uk/. Hum Mutat20:227,229, 2002. © 2002 Wiley-Liss, Inc. [source] Genomic Convergence of Genome-wide Investigations for Complex TraitsANNALS OF HUMAN GENETICS, Issue 5 2009Georgios D. Kitsios Summary Genome-wide investigations for identifying the genes for complex traits are considered to be agnostic in terms of prior assumptions for the responsible DNA alterations. The agreement of genome-wide association studies (GWAS) and genome-wide linkage scans (GWLS) has not been explored to date. In this study, a genomic convergence approach of GWAS and GWLS was implemented for the first time in order to identify genomic loci supported by both methods. A database with 376 GWLS and 102 GWAS for 19 complex traits was created. Data regarding the location and statistical significance for each genetic marker were extracted from articles or web-based databases. Convergence was quantified as the proportion of significant GWAS markers located within linked regions. Convergence was variable (0,73.3%) and was found to be significantly higher than expected by chance only for two of the 19 phenotypes. Seventy five loci of interest were identified, which being supported by independent lines of evidence, could merit prioritization in future investigations. Although convergence is supportive of genuine effects, lack of agreement between GWLS and GWAS is also indicative that these studies are designed to answer different questions and are not equally well suited for deciphering the genetics of complex traits. [source] A Combinatorial Searching Method for Detecting a Set of Interacting Loci Associated with Complex TraitsANNALS OF HUMAN GENETICS, Issue 5 2006Qiuying Sha Summary Complex diseases are presumed to be the results of the interaction of several genes and environmental factors, with each gene only having a small effect on the disease. Mapping complex disease genes therefore becomes one of the greatest challenges facing geneticists. Most current approaches of association studies essentially evaluate one marker or one gene (haplotype approach) at a time. These approaches ignore the possibility that effects of multilocus functional genetic units may play a larger role than a single-locus effect in determining trait variability. In this article, we propose a Combinatorial Searching Method (CSM) to detect a set of interacting loci (may be unlinked) that predicts the complex trait. In the application of the CSM, a simple filter is used to filter all the possible locus-sets and retain the candidate locus-sets, then a new objective function based on the cross-validation and partitions of the multi-locus genotypes is proposed to evaluate the retained locus-sets. The locus-set with the largest value of the objective function is the final locus-set and a permutation procedure is performed to evaluate the overall p-value of the test for association between the final locus-set and the trait. The performance of the method is evaluated by simulation studies as well as by being applied to a real data set. The simulation studies show that the CSM has reasonable power to detect high-order interactions. When the CSM is applied to a real data set to detect the locus-set (among the 13 loci in the ACE gene) that predicts systolic blood pressure (SBP) or diastolic blood pressure (DBP), we found that a four-locus gene-gene interaction model best predicts SBP with an overall p-value = 0.033, and similarly a two-locus gene-gene interaction model best predicts DBP with an overall p-value = 0.045. [source] Development of the cypriniform protrusible jaw complex in Danio rerio: Constructional insights for evolutionJOURNAL OF MORPHOLOGY, Issue 7 2010Katie Lynn Staab Abstract Studies on the evolution of complex biological systems are difficult because the construction of these traits cannot be observed during the course of evolution. Complex traits are defined as consisting of multiple elements, often of differing embryological origins, with multiple linkages integrated to form a single functional unit. An example of a complex system is the cypriniform oral jaw apparatus. Cypriniform fishes possess an upper jaw characterized by premaxillary protrusion during feeding. Cypriniforms effect protrusion via the kinethmoid, a synapomorphy for the order. The kinethmoid is a sesamoid ossification suspended by ligaments attaching to the premaxillae, maxillae, palatines, and neurocranium. Upon mouth opening, the kinethmoid rotates as the premaxillae move anteriorly. Along with bony and ligamentous elements, there are three divisions of the adductor mandibulae that render this system functional. It is unclear how cypriniform jaws evolved because although the evolution of sesamoid elements is common, the incorporation of the kinethmoid into the protrusible jaw results in a function that is atypical for sesamoids. Developmental studies can show how biological systems are assembled within individuals and offer clues about how traits might have been constructed during evolution. We investigated the development of the protrusible upper jaw in zebrafish to generate hypotheses regarding the evolution of this character. Early in development, the adductor mandibulae arises as a single unit. The muscle divides after ossification of the maxillae, on which the A1 division will ultimately insert. A cartilaginous kinethmoid first develops within the intermaxillary ligament; it later ossifies at points of ligamentous attachment. We combine our structural developmental data with published kinematic data at key developmental stages and discuss potential functional advantages in possessing even the earliest stages of a system for protrusion. J. Morphol. 2010. © 2010 Wiley-Liss, Inc. [source] Fetal programming: link between early nutrition, DNA methylation, and complex diseasesNUTRITION REVIEWS, Issue 2 2010Agata Chmurzynska Complex traits, including those involved in diet-related diseases, are determined by multiple genes and environmental influences. Factors influencing the development of complex traits should be expanded to include epigenetic factors, such as DNA methylation, which occurs in utero. Epigenetic factors regulate gene expression and thereby cell differentiation and organogenesis. The process of epigenotype establishment is sensitive to environmental conditions, with nutrition being one of the most important related factors. For example, DNA methylation depends on the availability of several nutrients including methionine and vitamins B6, B12, and folate. Epidemiological studies show that undernutrition during fetal life is associated with increased susceptibility to complex diseases. Numerous studies have been conducted on prenatal caloric and protein undernutrition. A reduction in the number of cells and changes in the structure and functioning of organs, as well as permanent changes in DNA methylation and gene expression, have been considered the molecular mechanisms responsible for metabolism programming. [source] Genes causing clefting syndromes as candidates for non-syndromic cleft lip with or without cleft palate: a family-based association studyEUROPEAN JOURNAL OF ORAL SCIENCES, Issue 6 2008Luca Scapoli Clefts of the orofacial region are among the most common congenital defects, caused by abnormal facial development during gestation. Non-syndromic cleft lip with or without cleft palate (NSCLP) is a complex trait most probably caused by multiple interacting loci, with possible additional environmental factors. As facial clefts form part of more than 300 syndromes, one strategy for identifying the genetic causes of NSCLP could be to study candidate genes responsible for clefting syndromes. Three genes were selected for this investigation: TP63, which codes for the tumour protein p63 and causes Ectrodactyly-Ectodermal dysplasia-orofacial Cleft syndrome; JAG2, a downstream gene of TP63; and MID1, which is responsible for Opitz syndrome. A linkage disequilibrium investigation was performed with intragenic single nucleotide polymorphisms on each of these genes in a sample study of 239 patients/parents trios. Evidence which suggests that JAG2 and MID1 may play a role in NSCLP was obtained. [source] INDEPENDENT EVOLUTION OF COMPLEX LIFE HISTORY ADAPTATIONS IN TWO FAMILIES OF FISHES, LIVE-BEARING HALFBEAKS (ZENARCHOPTERIDAE, BELONIFORMES) AND POECILIIDAE (CYPRINODONTIFORMES)EVOLUTION, Issue 11 2007David Reznick We have previously documented multiple, independent origins of placentas in the fish family Poeciliidae. Here we summarize similar analyses of fishes in the family Zenarchopteridae. This family includes three live-bearing genera. Earlier studies documented the presence of superfetation, or the ability to carry multiple litters of young in different stages of development in the same ovary, in some species in all three genera. There is also one earlier report of matrotrophy, or extensive postfertilization maternal provisioning, in two of these genera. We present detailed life-history data for approximately half of the species in all three genera and combine them with the best available phylogeny to make inferences about the pattern of life-history evolution within this family. Three species of Hemirhamphodon have superfetation but lack matrotrophy. Most species in Nomorhamphus and Dermogenys either lack superfetation and matrotrophy or have both superfetation and matrotrophy. Our phylogenetic analysis shows that matrotrophy may have evolved independently in each genus. In Dermogenys, matrotrophic species produce fewer, larger offspring than nonmatrotrophic species. In Nomorhamphus; matrotrophic species instead produce more and smaller offspring than lecithotrophic species. However, the matrotrophic species in both genera have significantly smaller masses of reproductive tissue relative to their body sizes. All aspects of these results are duplicated in the fish family Poeciliidae. We discuss the possible adaptive significance of matrotrophy in the light of these new results. The two families together present a remarkable opportunity to study the evolution of a complex trait because they contain multiple, independent origins of the trait that often include close relatives that vary in either the presence or absence of the matrotrophy or in the degree to which matrotrophy is developed. These are the raw materials that are required for either an analysis of the adaptive significance of the trait or for studies of the genetic mechanisms that underlie the evolution of the trait. [source] Upward bias in odds ratio estimates from genome-wide association studiesGENETIC EPIDEMIOLOGY, Issue 4 2007Chad Garner Abstract Genome-wide association studies are carried out to identify unknown genes for a complex trait. Polymorphisms showing the most statistically significant associations are reported and followed up in subsequent confirmatory studies. In addition to the test of association, the statistical analysis provides point estimates of the relationship between the genotype and phenotype at each polymorphism, typically an odds ratio in case-control association studies. The statistical significance of the test and the estimator of the odds ratio are completely correlated. Selecting the most extreme statistics is equivalent to selecting the most extreme odds ratios. The value of the estimator, given the value of the statistical significance depends on the standard error of the estimator and the power of the study. This report shows that when power is low, estimates of the odds ratio from a genome-wide association study, or any large-scale association study, will be upwardly biased. Genome-wide association studies are often underpowered given the low , levels required to declare statistical significance and the small individual genetic effects known to characterize complex traits. Factors such as low allele frequency, inadequate sample size and weak genetic effects contribute to large standard errors in the odds ratio estimates, low power and upwardly biased odds ratios. Studies that have high power to detect an association with the true odds ratio will have little or no bias, regardless of the statistical significance threshold. The results have implications for the interpretation of genome-wide association analysis and the planning of subsequent confirmatory stages. Genet Epidemiol. 2007. © 2007 Wiley-Liss, Inc. [source] Longitudinal data analysis in pedigree studiesGENETIC EPIDEMIOLOGY, Issue S1 2003W. James Gauderman Abstract Longitudinal family studies provide a valuable resource for investigating genetic and environmental factors that influence long-term averages and changes over time in a complex trait. This paper summarizes 13 contributions to Genetic Analysis Workshop 13, which include a wide range of methods for genetic analysis of longitudinal data in families. The methods can be grouped into two basic approaches: 1) two-step modeling, in which repeated observations are first reduced to one summary statistic per subject (e.g., a mean or slope), after which this statistic is used in a standard genetic analysis, or 2) joint modeling, in which genetic and longitudinal model parameters are estimated simultaneously in a single analysis. In applications to Framingham Heart Study data, contributors collectively reported evidence for genes that affected trait mean on chromosomes 1, 2, 3, 5, 8, 9, 10, 13, and 17, but most did not find genes affecting slope. Applications to simulated data suggested that even for a gene that only affected slope, use of a mean-type statistic could provide greater power than a slope-type statistic for detecting that gene. We report on the results of a small experiment that sheds some light on this apparently paradoxical finding, and indicate how one might form a more powerful test for finding a slope-affecting gene. Several areas for future research are discussed. Genet Epidemiol 25 (Suppl. 1):S18,S28, 2003. © 2003 Wiley-Liss, Inc. [source] Large-Scale Genome-Wide Linkage Analysis for Loci Linked to BMD at Different Skeletal Sites in Extreme Selected Sibships,JOURNAL OF BONE AND MINERAL RESEARCH, Issue 2 2007Yi-Hsiang Hsu Abstract Few genome-wide linkage studies of osteoporosis have been conducted in the Asian population. We performed a genome-wide scan involving 3093 adult siblings with at least one sib-pair extremely concordant or discordant for hip BMD. Our results indicated four genome-wide significant QTLs for BMD. In comparison with 12 previous reported linkage studies, we reveal novel linkage regions that have reaching global significance. Introduction: The genetic basis for osteoporosis has been firmly established, but efforts to identify genes associated with this complex trait have been incomplete, especially in Asian populations. The purpose of this study was to identify quantitative trait loci (QTLs) for BMD in a Chinese population. Materials and Methods: We performed a genome-wide scan involving 3093 siblings 25,64 years of age from 941 families, with at least one sib-pair extreme concordant or discordant for total hip BMD from a large community-based cohort (n = 23,327) in Anhui, China. Linkage analysis was performed on BMD residuals adjusted for age, height, weight, occupation, cigarette smoking, physical activity, and alcohol consumption using the revised Haseman-Elston regression-based linkage model. Results: Our results revealed significant QTLs on chromosome 7p21.2 for femoral neck BMD (LOD = 3.68) and on chromosome 2q24.3 for total hip BMD (LOD = 3.65). Suggestive linkage regions were found to overlap among different skeletal sites on chromosomes 2q, 7p, and 16q. Sex-specific linkage analysis further revealed a significant QTL for lumbar spine BMD on chromosome 13q21.1 (LOD = 3.62) in women only. When performing multivariate linkage analysis by combining BMDs at four skeletal sites (i.e., whole body, total hip, femoral neck, and lumbar spine BMD), an additional significant QTL was found at chromosome 5q21.2 (LOD = 4.56). None of these significant QTLs found in our study overlapped with major QTLs reported by other studies. Conclusions: This study reveals four novel QTLs in a Chinese population and suggests that BMD at different skeletal sites may also share common genetic determinants. [source] The genetic architecture of disease resistance in plants and the maintenance of recombination by parasitesMOLECULAR ECOLOGY, Issue 1 2001Paula X. Kover Abstract Parasites represent strong selection on host populations because they are ubiquitous and can drastically reduce host fitness. It has been hypothesized that parasite selection could explain the widespread occurrence of recombination because it is a coevolving force that favours new genetic combinations in the host. A review of deterministic models for the maintenance of recombination reveals that for recombination to be favoured, multiple genes that interact with each other must be under selection. To evaluate whether parasite selection can explain the maintenance of recombination, we review 85 studies that investigated the genetic architecture of plant disease resistance and discuss whether they conform to the requirements that emerge from theoretical models. General characteristics of disease resistance in plants and problems in evaluating resistance experimentally are also discussed. We found strong evidence that disease resistance in plants is determined by multiple loci. Furthermore, in most cases where loci were tested for interactions, epistasis between loci that affect resistance was found. However, we found weak support for the idea that specific allelic combinations determine resistance to different host genotypes and there was little data on whether epistasis between resistance genes is negative or positive. Thus, the current data indicate that it is possible that parasite selection can favour recombination, but more studies in natural populations that specifically address the nature of the interactions between resistance genes are necessary. The data summarized here suggest that disease resistance is a complex trait and that environmental effects and fitness trade-offs should be considered in future models of the coevolutionary dynamics of host and parasites. [source] Genetic mapping of quantitative trait loci for aseasonal reproduction in sheepANIMAL GENETICS, Issue 5 2010R. G. Mateescu Summary The productivity and economic prosperity of sheep farming could benefit greatly from more effective methods of selection for year-round lambing. Identification of QTL for aseasonal reproduction in sheep could lead to more accurate selection and faster genetic improvement. One hundred and twenty microsatellite markers were genotyped on 159 backcross ewes from a Dorset × East Friesian crossbred pedigree. Interval mapping was undertaken to map the QTL underlying several traits describing aseasonal reproduction including the number of oestrous cycles, maximum level of progesterone prior to breeding, pregnancy status determined by progesterone level, pregnancy status determined by ultrasound, lambing status and number of lambs born. Seven chromosomes (1, 3, 12, 17, 19, 20 and 24) were identified to harbour putative QTL for one or more component traits used to describe aseasonal reproduction. Ovine chromosomes 12, 17, 19 and 24 harbour QTL significant at the 5% chromosome-wide level, chromosomes 3 and 20 harbour QTL that exceeded the threshold at the 1% chromosome-wide level, while the QTL identified on chromosome 1 exceeded the 1% experiment-wide significance level. These results are a first step towards understanding the genetic mechanism of this complex trait and show that variation in aseasonal reproduction is associated with multiple chromosomal regions. [source] Genome-wide scan for bovine twinning rate QTL using linkage disequilibriumANIMAL GENETICS, Issue 3 2009E.-S. Kim Summary Twinning is a complex trait with negative impacts on health and reproduction, which cause economic loss in dairy production. Several twinning rate quantitative trait loci (QTL) have been detected in previous studies, but confidence intervals for QTL location are broad and many QTL are unreplicated. To identify genomic regions or genes associated with twinning rate, QTL analysis based on linkage combined with linkage disequilibrium (LLD) and individual marker associations was conducted across the genome using high-throughput single nucleotide polymorphism (SNP) genotypes. A total of 9919 SNP markers were genotyped with 200 sires and sons in 19 half-sib North American Holstein dairy cattle families. After SNPs were genotyped, informative markers were selected for genome-wide association tests and QTL searches. Evidence for twinning rate QTL was found throughout the genome. Thirteen markers significantly associated with twinning rate were detected on chromosomes 2, 5 and 14 (P < 2.3 × 10,5). Twenty-six regions on fourteen chromosomes were identified by LLD analysis at P < 0.0007. Seven previously reported ovulation or twinning rate QTL were supported by results of single marker association or LLD analyses. Single marker association analysis and LLD mapping were complementary tools for the identification of putative QTL in this genome scan. [source] HMGA2 Is Confirmed To Be Associated with Human Adult HeightANNALS OF HUMAN GENETICS, Issue 1 2010Tie-Lin Yang Summary Recent genome-wide association studies have identified a novel polymorphism, rs1042725, in the HMGA2 gene for human adult height, a highly heritable complex trait. Replications in independent populations are needed to evaluate a positive finding and determine its generality. Thus, we performed a replication study to examine the associations between polymorphisms in HMGA2 and adult height in two US Caucasian populations (an unrelated sample of 998 subjects and a family-based sample of 8385 subjects) and a Chinese population (1638 unrelated Han subjects). We confirmed the association between rs1042725 in HMGA2 and adult height both in the unrelated and family-based Caucasian populations (overall P= 4.25 × 10,9). Another two SNPs (rs7968902 and rs7968682), which were in high linkage disequilibrium with rs1042725, also achieved the significance level in both Caucasian populations (overall P= 6.34 × 10,7, and 2.72 × 10,9, respectively). Our results provide strong support to the initial finding. Moreover, SNP rs1042725 was firstly found to be associated with adult height (P= 0.008) in the Chinese population, and the effect is in the same direction as in the Caucasian populations, suggesting that it is a common variant across different populations. Our study further highlights the importance of the HMGA2 gene's involvement in normal growth. [source] A Combinatorial Searching Method for Detecting a Set of Interacting Loci Associated with Complex TraitsANNALS OF HUMAN GENETICS, Issue 5 2006Qiuying Sha Summary Complex diseases are presumed to be the results of the interaction of several genes and environmental factors, with each gene only having a small effect on the disease. Mapping complex disease genes therefore becomes one of the greatest challenges facing geneticists. Most current approaches of association studies essentially evaluate one marker or one gene (haplotype approach) at a time. These approaches ignore the possibility that effects of multilocus functional genetic units may play a larger role than a single-locus effect in determining trait variability. In this article, we propose a Combinatorial Searching Method (CSM) to detect a set of interacting loci (may be unlinked) that predicts the complex trait. In the application of the CSM, a simple filter is used to filter all the possible locus-sets and retain the candidate locus-sets, then a new objective function based on the cross-validation and partitions of the multi-locus genotypes is proposed to evaluate the retained locus-sets. The locus-set with the largest value of the objective function is the final locus-set and a permutation procedure is performed to evaluate the overall p-value of the test for association between the final locus-set and the trait. The performance of the method is evaluated by simulation studies as well as by being applied to a real data set. The simulation studies show that the CSM has reasonable power to detect high-order interactions. When the CSM is applied to a real data set to detect the locus-set (among the 13 loci in the ACE gene) that predicts systolic blood pressure (SBP) or diastolic blood pressure (DBP), we found that a four-locus gene-gene interaction model best predicts SBP with an overall p-value = 0.033, and similarly a two-locus gene-gene interaction model best predicts DBP with an overall p-value = 0.045. [source] A Partially Linear Tree-based Regression Model for Multivariate OutcomesBIOMETRICS, Issue 1 2010Kai Yu Summary In the genetic study of complex traits, especially behavior related ones, such as smoking and alcoholism, usually several phenotypic measurements are obtained for the description of the complex trait, but no single measurement can quantify fully the complicated characteristics of the symptom because of our lack of understanding of the underlying etiology. If those phenotypes share a common genetic mechanism, rather than studying each individual phenotype separately, it is more advantageous to analyze them jointly as a multivariate trait to enhance the power to identify associated genes. We propose a multilocus association test for the study of multivariate traits. The test is derived from a partially linear tree-based regression model for multiple outcomes. This novel tree-based model provides a formal statistical testing framework for the evaluation of the association between a multivariate outcome and a set of candidate predictors, such as markers within a gene or pathway, while accommodating adjustment for other covariates. Through simulation studies we show that the proposed method has an acceptable type I error rate and improved power over the univariate outcome analysis, which studies each component of the complex trait separately with multiple-comparison adjustment. A candidate gene association study of multiple smoking-related phenotypes is used to demonstrate the application and advantages of this new method. The proposed method is general enough to be used for the assessment of the joint effect of a set of multiple risk factors on a multivariate outcome in other biomedical research settings. [source] Personality: is it a viable endophenotype for genetic studies of bipolar affective disorder?BIPOLAR DISORDERS, Issue 4 2006Jonathan B Savitz Progress in identifying the genetic basis of bipolar affective disorder has been disappointing, most probably because of the genetic and phenotypic heterogeneity of the condition. These setbacks have led to the adoption of alternative strategies such as the use of endophenotypes or intermediate traits to identify those individuals at genetic risk for developing the disorder. Gottesman and Gould [Am J Psychiatry (2003), 160:636], in a review of the endophenotypic concept, have suggested five criteria that should be characteristic of a trait in order for it to qualify as an endophenotype. These five criteria are used in order to assess the viability of using personality traits as endophenotypes for genetic analyses of bipolar disorder. A review of the literature suggests that certain personality traits or temperaments are associated with the illness in a state independent manner, that personality is at least partly heritable, and that various temperaments aggregate in the non-affected relatives of bipolar probands. Nevertheless, it is unclear whether specific personality traits co-segregate with affectively ill individuals. We conclude that personality profiling of probands and their relatives may facilitate molecular genetic work, but given the fact that personality is itself a complex trait, its use as an endophenotype has certain limitations. [source] Beetle horns are regulated by the Hox gene, Sex combs reduced, in a species- and sex-specific mannerEVOLUTION AND DEVELOPMENT, Issue 4 2010Bethany R. Wasik SUMMARY Discovering the mechanisms that underlie the origin of novel features represents a major frontier in developmental and evolutionary biology. Here we begin to characterize the role of the Hox gene Sex combs reduced (Scr) during the development and evolution of a morphologically novel trait: beetle horns. Beetle horns develop as epidermal outgrowths from the prothorax and/or head, and size and location vary dramatically across species and between sexes. Using both comparative gene expression and larval RNA interference in two species of the horned beetle genus Onthophagus, we show that Scr functions in patterning adult labial mouthpart identity and suppressing wing development in the prothorax. At the same time, however, our results illustrate that Scr has acquired, within its ancestral domain of expression, additional new functions including the regulation of prepupal growth and pupal remodeling of pronotal horn primordia. Furthermore, comparative analyses of our results across both Onthophagus species, which differ in location of horn development (thoracic horns vs. thoracic and head horns) as well as patterns of sexual dimorphism (traditional vs. reversed sexual dimorphism), reveal surprising differences in exactly when, where, and to what degree Scr regulates horn formation in different sexes. These observations suggest that the interactions between Scr and its targets in the regulation of horn development can diversify quickly over remarkably short phylogenetic distances. More generally, our results suggest that the Hox complex can play an integral role in the development and evolution of novel complex traits while maintaining traditional patterning responsibilities. [source] Molecular analyses and identification of promising candidate genes for loci on mouse chromosome 1 affecting alcohol physical dependence and associated withdrawalGENES, BRAIN AND BEHAVIOR, Issue 5 2008D. L. Denmark We recently mapped quantitative trait loci (QTLs) with large effects on predisposition to physical dependence and associated withdrawal severity following chronic and acute alcohol exposure (Alcdp1/Alcw1) to a 1.1-Mb interval of mouse chromosome 1 syntenic with human chromosome 1q23.2-23.3. Here, we provide a detailed analysis of the genes within this interval and show that it contains 40 coding genes, 17 of which show validated genotype-dependent transcript expression and/or non-synonymous coding sequence variation that may underlie the influence of Alcdp1/Alcw1 on ethanol dependence and associated withdrawal. These high priority candidates are involved in diverse cellular functions including intracellular trafficking, oxidative homeostasis, mitochondrial respiration, and extracellular matrix dynamics, and indicate both established and novel aspects of the neurobiological response to ethanol. This work represents a substantial advancement toward identification of the gene(s) that underlies the phenotypic effects of Alcdp1/Alcw1. Additionally, a multitude of QTLs for a variety of complex traits, including diverse behavioral responses to ethanol, have been mapped in the vicinity of Alcdp1/Alcw1, and as many as four QTLs on human chromosome 1q have been implicated in human mapping studies for alcoholism and associated endophenotypes. Thus, our results will be primary to further efforts to identify genes involved in a wide variety of behavioral responses to alcohol and may directly facilitate progress in human alcoholism genetics. [source] Behavioural and physiological characterization of inbred mouse strains: prospects for elucidating the molecular mechanisms of mammalian learning and memoryGENES, BRAIN AND BEHAVIOR, Issue 2 2002P. V. Nguyen With the advent of recombinant DNA methodology, it has become possible to dissect the molecular mechanisms of complex traits, including brain function and behaviour. The increasing amount of available information on the genomes of mammalian organisms, including our own, has facilitated this research. The present review focuses on a somewhat neglected area of genetics, one that involves the study of inbred mouse strains. It is argued that the use of inbred mice is complementary to transgenic approaches in the analysis of molecular mechanisms of complex traits. Whereas transgenic technology allows one to manipulate a single gene and investigate the in vivo effects of highly specific, artificially induced mutations, the study of inbred mouse strains should shed light on the roles of naturally occurring allelic variants in brain function and behaviour. Systematic characterization of the behavioural, electrophysiological, neurochemical, and neuroanatomical properties of a large number of inbred strains is required to elucidate mechanisms of mammalian brain function and behaviour. In essence, a ,mouse phenome' project is needed, entailing the construction of databases to investigate possible causal relationships amongst the phenotypical characteristics. This review focuses on electrophysiological and behavioural characterization of mouse strains. Nevertheless, it is emphasized that the full potential of the analysis of inbred mouse strains may be attained if techniques of numerous disciplines, including gene expression profiling, biochemical analysis, and quantitative trait loci (QTL) mapping, to name but a few, are also included. [source] Summary of contributions to GAW Group 15: family-based samples are useful in identifying common polymorphisms associated with complex traitsGENETIC EPIDEMIOLOGY, Issue S1 2009Stacey Knight Abstract Traditionally, family-based samples have been used for genetic analyses of single-gene traits caused by rare but highly penetrant risk variants. The utility of family-based genetic data for analyzing common complex traits is unclear and contains numerous challenges. To assess the utility as well as to address these challenges, members of Genetic Analysis Workshop 16 Group 15 analyzed Framingham Heart Study data using family-based designs ranging from parent,offspring trios to large pedigrees. We investigated different methods including traditional linkage tests, family-based association tests, and population-based tests that correct for relatedness between subjects, and tests to detect parent-of-origin effects. The analyses presented an assortment of positive findings. One contribution found increased power to detect epistatic effects through linkage using ascertainment of sibships based on extreme quantitative values or presence of disease associated with the quantitative value. Another contribution found four single-nucleotide polymorphisms (SNPs) showing a maternal effect, two SNPs with an imprinting effect, and one SNP having both effects on a binary high blood pressure trait. Finally, three contributions illustrated the advantage of using population-based methods to detect association to complex binary or quantitative traits. Our findings highlight the contribution of family-based samples to the genetic dissection of complex traits. Genet. Epidemiol. 33 (Suppl. 1):S99,S104, 2009. © 2009 Wiley-Liss, Inc. [source] An optimal dose-effect mode trend test for SNP genotype tablesGENETIC EPIDEMIOLOGY, Issue 2 2009Ryo Yamada Abstract The genome-wide association studies have improved our understanding of the genetic basis of many complex traits. Two-by-three contingency tables are tested in these studies. The trend test for the additive mode is most often used, which is the test of 1 degree of freedom (df=1) and other tests, such as the genotype test (,2 (df=2)) and the ,2 (df=1) tests for the dominant and recessive modes are also used to increase the power for markers in the non-additive modes. However, any one of them or combination of them is not perfect. We describe the relations among the ,2 (df=2) test and ,2 (df=1) tests for the dominant and recessive modes and the trend test for the additive mode and propose a new statistic based on their relations that tests the hypothesis that the disease-susceptible allele has a dose-effect somewhere between the recessive and dominant modes, which corresponds to the optimal dose-effect for the observed data. Genet. Epidemiol. 2008. © 2008 Wiley-Liss, Inc. [source] Upward bias in odds ratio estimates from genome-wide association studiesGENETIC EPIDEMIOLOGY, Issue 4 2007Chad Garner Abstract Genome-wide association studies are carried out to identify unknown genes for a complex trait. Polymorphisms showing the most statistically significant associations are reported and followed up in subsequent confirmatory studies. In addition to the test of association, the statistical analysis provides point estimates of the relationship between the genotype and phenotype at each polymorphism, typically an odds ratio in case-control association studies. The statistical significance of the test and the estimator of the odds ratio are completely correlated. Selecting the most extreme statistics is equivalent to selecting the most extreme odds ratios. The value of the estimator, given the value of the statistical significance depends on the standard error of the estimator and the power of the study. This report shows that when power is low, estimates of the odds ratio from a genome-wide association study, or any large-scale association study, will be upwardly biased. Genome-wide association studies are often underpowered given the low , levels required to declare statistical significance and the small individual genetic effects known to characterize complex traits. Factors such as low allele frequency, inadequate sample size and weak genetic effects contribute to large standard errors in the odds ratio estimates, low power and upwardly biased odds ratios. Studies that have high power to detect an association with the true odds ratio will have little or no bias, regardless of the statistical significance threshold. The results have implications for the interpretation of genome-wide association analysis and the planning of subsequent confirmatory stages. Genet Epidemiol. 2007. © 2007 Wiley-Liss, Inc. [source] Tag SNPs chosen from HapMap perform well in several population isolatesGENETIC EPIDEMIOLOGY, Issue 3 2007Susan Service Abstract Population isolates may be particularly useful for association studies of complex traits. This utility, however, largely depends on the transferability of tag SNPs chosen from reference samples, such as HapMap, to samples from such populations. Factors that characterize population isolates, such as widespread genetic drift, could impede such transferability. In this report, we show that tag SNPs chosen from HapMap perform well in several population isolates; this is true even for populations that differ substantially from the HapMap sample either in levels of linkage disequilibrium or in SNP allele frequency distributions. Genet. Epidemiol. 2007. © 2007 Wiley-Liss, Inc. [source] MCMC-based linkage analysis for complex traits on general pedigrees: multipoint analysis with a two-locus model and a polygenic componentGENETIC EPIDEMIOLOGY, Issue 2 2007Yun Ju Sung Abstract We describe a new program lm_twoqtl, part of the MORGAN package, for parametric linkage analysis with a quantitative trait locus (QTL) model having one or two QTLs and a polygenic component, which models additional familial correlation from other unlinked QTLs. The program has no restriction on number of markers or complexity of pedigrees, facilitating use of more complex models with general pedigrees. This is the first available program that can handle a model with both two QTLs and a polygenic component. Competing programs use only simpler models: one QTL, one QTL plus a polygenic component, or variance components (VC). Use of simple models when they are incorrect, as for complex traits that are influenced by multiple genes, can bias estimates of QTL location or reduce power to detect linkage. We compute the likelihood with Markov Chain Monte Carlo (MCMC) realization of segregation indicators at the hypothesized QTL locations conditional on marker data, summation over phased multilocus genotypes of founders, and peeling of the polygenic component. Simulated examples, with various sized pedigrees, show that two-QTL analysis correctly identifies the location of both QTLs, even when they are closely linked, whereas other analyses, including the VC approach, fail to identify the location of QTLs with modest contribution. Our examples illustrate the advantage of parametric linkage analysis with two QTLs, which provides higher power for linkage detection and better localization than use of simpler models. Genet. Epidemiol. © 2006 Wiley-Liss, Inc. [source] Finding starting points for Markov chain Monte Carlo analysis of genetic data from large and complex pedigreesGENETIC EPIDEMIOLOGY, Issue 1 2003Yuqun Luo Abstract Genetic data from founder populations are advantageous for studies of complex traits that are often plagued by the problem of genetic heterogeneity. However, the desire to analyze large and complex pedigrees that often arise from such populations, coupled with the need to handle many linked and highly polymorphic loci simultaneously, poses challenges to current standard approaches. A viable alternative to solving such problems is via Markov chain Monte Carlo (MCMC) procedures, where a Markov chain, defined on the state space of a latent variable (e.g., genotypic configuration or inheritance vector), is constructed. However, finding starting points for the Markov chains is a difficult problem when the pedigree is not single-locus peelable; methods proposed in the literature have not yielded completely satisfactory solutions. We propose a generalization of the heated Gibbs sampler with relaxed penetrances (HGRP) of Lin et al., ([1993] IMA J. Math. Appl. Med. Biol. 10:1,17) to search for starting points. HGRP guarantees that a starting point will be found if there is no error in the data, but the chain usually needs to be run for a long time if the pedigree is extremely large and complex. By introducing a forcing step, the current algorithm substantially reduces the state space, and hence effectively speeds up the process of finding a starting point. Our algorithm also has a built-in preprocessing procedure for Mendelian error detection. The algorithm has been applied to both simulated and real data on two large and complex Hutterite pedigrees under many settings, and good results are obtained. The algorithm has been implemented in a user-friendly package called START. Genet Epidemiol 25:14,24, 2003. © 2003 Wiley-Liss, Inc. [source] A score for Bayesian genome screeningGENETIC EPIDEMIOLOGY, Issue 3 2003E. Warwick Daw Abstract Bayesian Monte Carlo Markov chain (MCMC) techniques have shown promise in dissecting complex genetic traits. The methods introduced by Heath ([1997], Am. J. Hum. Genet. 61:748,760), and implemented in the program Loki, have been able to localize genes for complex traits in both real and simulated data sets. Loki estimates the posterior probability of quantitative trait loci (QTL) at locations on a chromosome in an iterative MCMC process. Unfortunately, interpretation of the results and assessment of their significance have been difficult. Here, we introduce a score, the log of the posterior placement probability ratio (LOP), for assessing oligogenic QTL detection and localization. The LOP is the log of the posterior probability of linkage to the real chromosome divided by the posterior probability of linkage to an unlinked pseudochromosome, with marker informativeness similar to the marker data on the real chromosome. Since the LOP cannot be calculated exactly, we estimate it in simultaneous MCMC on both real and pseudochromosomes. We investigate empirically the distributional properties of the LOP in the presence and absence of trait genes. The LOP is not subject to trait model misspecification in the way a lod score may be, and we show that the LOP can detect linkage for loci of small effect when the lod score cannot. We show how, in the absence of linkage, an empirical distribution of the LOP may be estimated by simulation and used to provide an assessment of linkage detection significance. Genet Epidemiol 24:181,190, 2003. © 2003 Wiley-Liss, Inc. [source] Power and robustness of a score test for linkage analysis of quantitative traits using identity by descent data on sib pairsGENETIC EPIDEMIOLOGY, Issue 4 2001Darlene R. Goldstein Abstract Identification of genes involved in complex traits by traditional (lod score) linkage analysis is difficult due to many complicating factors. An unfortunate drawback of non-parametric procedures in general, though, is their low power to detect genetic effects. Recently, Dudoit and Speed [2000] proposed using a (likelihood-based) score test for detecting linkage with IBD data on sib pairs. This method uses the likelihood for ,, the recombination fraction between a trait locus and a marker locus, conditional on the phenotypes of the two sibs to test the null hypothesis of no linkage (, = ½). Although a genetic model must be specified, the approach offers several advantages. This paper presents results of simulation studies characterizing the power and robustness properties of this score test for linkage, and compares the power of the test to the Haseman-Elston and modified Haseman-Elston tests. The score test is seen to have impressively high power across a broad range of true and assumed models, particularly under multiple ascertainment. Assuming an additive model with a moderate allele frequency, in the range of p = 0.2 to 0.5, along with heritability H = 0.3 and a moderate residual correlation , = 0.2 resulted in a very good overall performance across a wide range of trait-generating models. Generally, our results indicate that this score test for linkage offers a high degree of protection against wrong assumptions due to its strong robustness when used with the recommended additive model. Genet. Epidemiol. 20:415,431, 2001. © 2001 Wiley-Liss, Inc. [source] Magnetic resonance imaging as a tool for in vivo and ex vivo anatomical phenotyping in experimental genetic modelsHUMAN BRAIN MAPPING, Issue 6 2007Alain Pitiot Abstract This article describes a suite of computational approaches suitable for deriving various quantitative phenotypes from structural magnetic resonance (MR) images obtained in rodents and used subsequently in genetic studies of complex traits. We begin by introducing the basic principles of genetic studies of complex traits in experimental models. We then illustrate the use of MR-based computational anatomy in vivo and ex vivo, and in combination with histology. This work was carried out in two inbred strains of rats, namely spontaneously hypertensive rats and Brown Norway rats; these are parental strains of the only existing panel of recombinant inbred strains of rats. The rats were scanned in vivo at two time points (at 8 and 12 weeks of age) and ex vivo (at 12 weeks of age). We describe between-strain differences and across-time changes in brain and kidney volumes, as well as regional variations in brain structure using surface- and deformation-based approaches. We conclude by discussing the power of the population-based computational analysis of MR images, and their fusion with histology, in studies of complex traits. Hum Brain Mapp, 2007. © 2007 Wiley-Liss, Inc. [source] Determination of haplotypes from single DNA molecules: a method for single-molecule barcoding,,HUMAN MUTATION, Issue 9 2007Ming Xiao Abstract Determining the haplotypes in a diploid individual is a major technical challenge in genetic studies of human complex traits. Here we report a method of molecular haplotyping by directly imaging multiple polymorphic sites on individual DNA molecules simultaneously. DNA fragments amplified by long-range PCR were labeled with fluorescent dyes at each polymorphic site using a modified gap-filled padlock probe ligation approach. The labeled DNA molecules were then stretched into linear form on a functionalized glass surface and imaged with multicolor total internal reflection fluorescence (TIRF) microscopy. By determining the colors and positions of the fluorescent labels with respect to the backbone at polymorphic sites, the haplotype can be inferred accurately, in a manner similar to reading a barcode, even when the DNA fragments are not fully labeled. The feasibility of this technology is demonstrated by the determination of the haplotype of a 9.3-kbp DNA fragment containing four SNPs. Hum Mutat 28(9), 913,921, 2007. Published 2007 Wiley-Liss, Inc. [source] | ||||||||||||||||||||||||||||||||||