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QTL
Kinds of QTL Terms modified by QTL Selected AbstractsMouse models for genetic dissection of polygenic gastrointestinal diseasesEUROPEAN JOURNAL OF CLINICAL INVESTIGATION, Issue 2 2003S. Hillebrandt Abstract Many diseases with a major public health impact are the result of complex interactions between environmental factors and multiple genes. In the past decade, methods for genome analysis, in particular quantitative trait locus (QTL) analysis in animal models, were developed to identify and localize the genes responsible for multifactorial (polygenic) diseases; QTL analysis is based on experimental crosses between inbred strains with high and low genetic susceptibility. Recently the genes underlying several QTLs could be cloned successfully. Here we describe the impact of these genomic approaches in mice on our understanding of the multifactorial genetics of three gastrointestinal diseases related to metabolism (cholesterol cholelithiasis), development (gastroschisis), and colorectal cancer. The examples demonstrate how mouse models continue to be an invaluable tool in unravelling complex pathomechanisms and unlocking our understanding of human diseases. [source] REVIEW: A comparison of selected quantitative trait loci associated with alcohol use phenotypes in humans and mouse modelsADDICTION BIOLOGY, Issue 2 2010Cindy L. Ehlers ABSTRACT Evidence for genetic linkage to alcohol and other substance dependence phenotypes in areas of the human and mouse genome have now been reported with some consistency across studies. However, the question remains as to whether the genes that underlie the alcohol-related behaviors seen in mice are the same as those that underlie the behaviors observed in human alcoholics. The aims of the current set of analyses were to identify a small set of alcohol-related phenotypes in human and in mouse by which to compare quantitative trait locus (QTL) data between the species using syntenic mapping. These analyses identified that QTLs for alcohol consumption and acute and chronic alcohol withdrawal on distal mouse chromosome 1 are syntenic to a region on human chromosome 1q where a number of studies have identified QTLs for alcohol-related phenotypes. Additionally, a QTL on human chromosome 15 for alcohol dependence severity/withdrawal identified in two human studies was found to be largely syntenic with a region on mouse chromosome 9, where two groups have found QTLs for alcohol preference. In both of these cases, while the QTLs were found to be syntenic, the exact phenotypes between humans and mice did not necessarily overlap. These studies demonstrate how this technique might be useful in the search for genes underlying alcohol-related phenotypes in multiple species. However, these findings also suggest that trying to match exact phenotypes in humans and mice may not be necessary or even optimal for determining whether similar genes influence a range of alcohol-related behaviors between the two species. [source] Implication of allelic polymorphism of osteopontin in the development of lupus nephritis in MRL/lpr miceEUROPEAN JOURNAL OF IMMUNOLOGY, Issue 5 2005Tatsuhiko Miyazaki Abstract Potentially, autoimmune diseases develop from a combination of multiple genes with allelic polymorphisms. An MRL/Mp-Faslpr/lpr (MRL/lpr) strain of mice develops autoimmune diseases, including lupus nephritis, but another lpr strain, C3H/HeJ-Faslpr/lpr (C3H/lpr) does not. This indicates that MRL polymorphic genes are involved in the development of the diseases. By quantitative trait loci (QTL) analysis using 527 of the (MRL/lpr × C3H/lpr)F2 mice, we identified a novel locus for susceptibility to lupus nephritis at map position D5Mit115 on chromosome 5, the same alias of the osteopontin (Opn) gene (LOD score =4.0), susceptible in the MRL allele. In functional analyses of the MRL and C3H Opn alleles using synthetic osteopontin (OPN) made with a new method "cell-free system" with wheat germ ribosomes, the MRL-OPN induced higher expression and production of immunoglobulins as well as cytokines including TNF-,, IL-1, and IFN-, in splenocytes and/or macrophages than that of the C3H allele. These findings suggest that allelic polymorphism of OPN causes the functional differences in antibody production and macrophage activation between MRL and C3H strains, possibly involved in the development of lupus nephritis. [source] RELATIVE CONTRIBUTION OF ADDITIVE, DOMINANCE, AND IMPRINTING EFFECTS TO PHENOTYPIC VARIATION IN BODY SIZE AND GROWTH BETWEEN DIVERGENT SELECTION LINES OF MICEEVOLUTION, Issue 5 2009Reinmar Hager Epigenetic effects attributed to genomic imprinting are increasingly recognized as an important source of variation in quantitative traits. However, little is known about their relative contribution to phenotypic variation compared to those of additive and dominance effects, and almost nothing about their role in phenotypic evolution. Here we address these questions by investigating the relative contribution of additive, dominance, and imprinting effects of quantitative trait loci (QTL) to variation in "early" and "late" body weight in an intercross of mice selected for divergent adult body weight. We identified 18 loci on 13 chromosomes; additive effects accounted for most of the phenotypic variation throughout development, and imprinting effects were always small. Genetic effects on early weight showed more dominance, less additive, and, surprisingly, less imprinting variation than that of late weight. The predominance of additivity of QTL effects on body weight follows the expectation that additive effects account for the evolutionary divergence between selection lines. We hypothesize that the appearance of more imprinting effects on late body weight may be a consequence of divergent selection on adult body weight, which may have indirectly selected for alleles showing partial imprinting effects due to their associated additive effects, highlighting a potential role of genomic imprinting in the response to selection. [source] A CENTENNIAL CELEBRATION FOR QUANTITATIVE GENETICSEVOLUTION, Issue 5 2007Derek A. Roff Quantitative genetics is at or is fast approaching its centennial. In this perspective I consider five current issues pertinent to the application of quantitative genetics to evolutionary theory. First, I discuss the utility of a quantitative genetic perspective in describing genetic variation at two very different levels of resolution, (1) in natural, free-ranging populations and (2) to describe variation at the level of DNA transcription. Whereas quantitative genetics can serve as a very useful descriptor of genetic variation, its greater usefulness is in predicting evolutionary change, particularly when used in the first instance (wild populations). Second, I review the contributions of Quantitative trait loci (QLT) analysis in determining the number of loci and distribution of their genetic effects, the possible importance of identifying specific genes, and the ability of the multivariate breeder's equation to predict the results of bivariate selection experiments. QLT analyses appear to indicate that genetic effects are skewed, that at least 20 loci are generally involved, with an unknown number of alleles, and that a few loci have major effects. However, epistatic effects are common, which means that such loci might not have population-wide major effects: this question waits upon (QTL) analyses conducted on more than a few inbred lines. Third, I examine the importance of research into the action of specific genes on traits. Although great progress has been made in identifying specific genes contributing to trait variation, the high level of gene interactions underlying quantitative traits makes it unlikely that in the near future we will have mechanistic models for such traits, or that these would have greater predictive power than quantitative genetic models. In the fourth section I present evidence that the results of bivariate selection experiments when selection is antagonistic to the genetic covariance are frequently not well predicted by the multivariate breeder's equation. Bivariate experiments that combine both selection and functional analyses are urgently needed. Finally, I discuss the importance of gaining more insight, both theoretical and empirical, on the evolution of the G and P matrices. [source] Single QTL mapping and nucleotide-level resolution of a physiologic trait in wine Saccharomyces cerevisiae strainsFEMS YEAST RESEARCH, Issue 6 2007Philippe Marullo Abstract Natural Saccharomyces cerevisiae yeast strains exhibit very large genotypic and phenotypic diversity. However, the link between phenotype variation and genetic determinism is still difficult to identify, especially in wild populations. Using genome hybridization on DNA microarrays, it is now possible to identify single-feature polymorphisms among divergent yeast strains. This tool offers the possibility of applying quantitative genetics to wild yeast strains. In this instance, we studied the genetic basis for variations in acetic acid production using progeny derived from two strains from grape must isolates. The trait was quantified during alcoholic fermentation of the two strains and 108 segregants derived from their crossing. A genetic map of 2212 markers was generated using oligonucleotide microarrays, and a major quantitative trait locus (QTL) was mapped with high significance. Further investigations showed that this QTL was due to a nonsynonymous single-nucleotide polymorphism that targeted the catalytic core of asparaginase type I (ASP1) and abolished its activity. This QTL was only effective when asparagine was used as a major nitrogen source. Our results link nitrogen assimilation and CO2 production rate to acetic acid production, as well as, on a broader scale, illustrating the specific problem of quantitative genetics when working with nonlaboratory microorganisms. [source] A genome-wide quantitative trait loci scan of neurocognitive performances in families with schizophreniaGENES, BRAIN AND BEHAVIOR, Issue 7 2010Y.-J. Lien Patients with schizophrenia frequently display neurocognitive dysfunction, and genetic studies suggest it to be an endophenotype for schizophrenia. Genetic studies of such traits may thus help elucidate the biological pathways underlying genetic susceptibility to schizophrenia. This study aimed to identify loci influencing neurocognitive performance in schizophrenia. The sample comprised of 1207 affected individuals and 1035 unaffected individuals of Han Chinese ethnicity from 557 sib-pair families co-affected with DSM-IV (Diagnostic and Statistical Manual, Fourth Edition) schizophrenia. Subjects completed a face-to-face semi-structured interview, the continuous performance test (CPT) and the Wisconsin card sorting test (WCST), and were genotyped with 386 microsatellite markers across the genome. A series of autosomal genome-wide multipoint nonparametric quantitative trait loci (QTL) linkage analysis were performed in affected individuals only. Determination of genome-wide empirical significance was performed using 1000 simulated genome scans. One linkage peak attaining genome-wide significance was identified: 12q24.32 for undegraded CPT hit rate [nonparametric linkage z (NPL-Z) scores = 3.32, genome-wide empirical P = 0.03]. This result was higher than the peak linkage signal obtained in the previous genome-wide scan using a dichotomous diagnosis of schizophrenia. The identification of 12q24.32 as a QTL has not been consistently implicated in previous linkage studies on schizophrenia, which suggests that the analysis of endophenotypes provides additional information from what is seen in analyses that rely on diagnoses. This region with linkage to a particular neurocognitive feature may inform functional hypotheses for further genetic studies for schizophrenia. [source] High-throughput behavioral phenotyping in the expanded panel of BXD recombinant inbred strainsGENES, BRAIN AND BEHAVIOR, Issue 2 2010V. M. Philip Genetic reference populations, particularly the BXD recombinant inbred (BXD RI) strains derived from C57BL/6J and DBA/2J mice, are a valuable resource for the discovery of the bio-molecular substrates and genetic drivers responsible for trait variation and covariation. This approach can be profitably applied in the analysis of susceptibility and mechanisms of drug and alcohol use disorders for which many predisposing behaviors may predict the occurrence and manifestation of increased preference for these substances. Many of these traits are modeled by common mouse behavioral assays, facilitating the detection of patterns and sources of genetic coregulation of predisposing phenotypes and substance consumption. Members of the Tennessee Mouse Genome Consortium (TMGC) have obtained phenotype data from over 250 measures related to multiple behavioral assays across several batteries: response to, and withdrawal from cocaine, 3,4-methylenedioxymethamphetamine; "ecstasy" (MDMA), morphine and alcohol; novelty seeking; behavioral despair and related neurological phenomena; pain sensitivity; stress sensitivity; anxiety; hyperactivity and sleep/wake cycles. All traits have been measured in both sexes in approximately 70 strains of the recently expanded panel of BXD RI strains. Sex differences and heritability estimates were obtained for each trait, and a comparison of early (N = 32) and recent (N = 37) BXD RI lines was performed. Primary data are publicly available for heritability, sex difference and genetic analyses using the MouseTrack database, and are also available in GeneNetwork.org for quantitative trait locus (QTL) detection and genetic analysis of gene expression. Together with the results of related studies, these data form a public resource for integrative systems genetic analysis of neurobehavioral traits. [source] Marker-assisted dissection of genetic influences on motor and neuroendocrine sensitization to cocaine in ratsGENES, BRAIN AND BEHAVIOR, Issue 3 2009L. F. Vendruscolo This study investigated genetic influences on behavioral and neuroendocrine responses to cocaine sensitization. We used male and female rats of the inbred strains Lewis (LEW) and spontaneously hypertensive rats (SHR), which display genetic differences in stress-related responses. The influence of two quantitative trait loci (QTL; Ofil1 and Ofil2 on chromosomes 4 and 7), which modulate stress reactivity in rats, on the effects of cocaine was also investigated through the use of recombinant lines (derived from a LEW × SHR intercross) selected by their genotype at Ofil1 and Ofil2. Animals were given repeated cocaine or saline injections and tested for locomotion (induction of sensitization). Two weeks later, all animals were challenged with cocaine, and locomotion and corticosterone levels were measured (expression of sensitization). Results indicated that male SHR rats showed more behavioral sensitization than LEW rats, whereas no strain differences in sensitization were seen among females. When challenged with cocaine, LEW and SHR rats of both sexes pretreated with cocaine showed behavioral sensitization compared with saline pretreated animals; however, only LEW rats displayed an increase in the corticosterone levels. Ofil1 was found to influence the induction of sensitization in males and Ofil2 modulated the locomotor effect of cocaine in females. This study provides evidence of a genotype-dependent relationship between the induction and expression of cocaine sensitization, and between the behavioral and neuroendocrine responses induced by cocaine. Moreover, the Ofil1 and Ofil2 loci may contain one or more genes that control the behavioral effects of cocaine in rats. [source] Variation in Galr1 expression determines susceptibility to excitotoxin-induced cell death in miceGENES, BRAIN AND BEHAVIOR, Issue 5 2008S. Kong Inbred strains of mice differ in their susceptibility to excitotoxin-induced cell death, but the genetic basis of individual variation in differential susceptibility is unknown. Previously, we identified a highly significant quantitative trait locus (QTL) on chromosome 18 that influenced susceptibility to kainic acid-induced cell death (Sicd1). Comparison of susceptibility to seizure-induced cell death between reciprocal congenic lines for Sicd1 and parental background mice indicates that genes influencing this trait were captured in both strains. Two positional gene candidates, Galr1 and Mbp, map to 55 cM, where the Sicd1 QTL had been previously mapped. Thus, this study was undertaken to determine if Galr1 and/or Mbp could be considered as candidate genes. Genomic sequence comparison of these two functional candidate genes from the C57BL/6J (resistant at Sicd1) and the FVB/NJ (susceptible at Sicd1) strains showed no single-nucleotide polymorphisms. However, expression studies confirmed that Galr1 shows significant differential expression in the congenic and parental inbred strains. Galr1 expression was downregulated in the hippocampus of C57BL/6J mice and FVB.B6- Sicd1 congenic mice when compared with FVB/NJ or B6.FVB- Sicd1 congenic mice. A survey of Galr1 expression among other inbred strains showed a significant effect such that ,susceptible' strains showed a reduction in Galr1 expression as compared with ,resistant' strains. In contrast, no differences in Mbp expression were observed. In summary, these results suggest that differential expression of Galr1 may contribute to the differences in susceptibility to seizure-induced cell death between cell death-resistant and cell death-susceptible strains. [source] Chromosomal loci that influence oral nicotine consumption in C57BL/6J × C3H/HeJ F2 intercross miceGENES, BRAIN AND BEHAVIOR, Issue 5 2007X. C. Li Several studies have demonstrated that there are genetic influences on free-choice oral nicotine consumption in mice. In order to establish the genetic architecture that underlies individual differences in free-choice nicotine consumption, quantitative trait loci (QTL) mapping was used to identify chromosomal regions that influence free-choice nicotine consumption in male and female F2 mice derived from a cross between C57BL/6J and C3H/HeJ mice. These two mouse strains were chosen not only because they differ significantly for oral nicotine consumption, but also because they are at or near phenotypic extremes for all measures of nicotine sensitivity that have been reported. A four-bottle choice paradigm was used to assess nicotine consumption over an 8-day period. The four bottles contained water or water supplemented with 25, 50 or 100 ,g/ml of nicotine base. Using micrograms of nicotine consumed per milliliter of total fluid consumed per day as the nicotine consumption phenotype, four significant QTL were identified. The QTL with the largest LOD score was located on distal chromosome 1 (peak LOD score = 15.7). Other chromosomes with significant QTL include central chromosome 4 (peak LOD score = 4.1), proximal chromosome 7 (peak LOD score = 6.1) and distal chromosome 15 (peak LOD score = 4.8). These four QTL appear to be responsible for up to 62% of the phenotypic variance in oral nicotine consumption. [source] Sensitivity to the locomotor-stimulant effects of ethanol and allopregnanolone: a quantitative trait locus study of common genetic influenceGENES, BRAIN AND BEHAVIOR, Issue 7 2006A. A. Palmer Previous studies have suggested that common genetic mechanisms influence sensitivity to the locomotor-stimulant effects of ethanol and allopregnanolone. We conducted two quantitative trait locus (QTL) studies to identify chromosomal regions that harbor genes that influence locomotor response to ethanol (2 g/kg) and allopregnanolone (17 mg/kg) using F2 crosses between C57BL/6J and DBA/2J mice. Because our previous data from the BXD recombinant inbred strains had indicated that chromosome 2 contained QTL for sensitivity to the locomotor-stimulant effects of both ethanol and allopregnanolone, we also tested reciprocal chromosome 2 congenic strains for sensitivity to the locomotor-stimulant effects of both drugs. The F2 analysis for ethanol sensitivity identified significant QTL on chromosomes 1 and 2 and suggestive QTL on chromosomes 5 and 9. The analysis of the allopregnanolone F2 study identified suggestive QTL on chromosomes 3, 5 and 12. Suggestive evidence for a female-specific QTL on chromosome 2 was also found. The studies of congenic mouse strains indicated that both the congenic strains captured one or more QTL for sensitivity to the locomotor-stimulant effects of both ethanol (2 g/kg) and allopregnanolone (17 mg/kg). When Fisher's method was used to combine the P values for the RI, F2 and congenic studies of the chromosome 2 QTL, cumulative probability scores of 9.6 × 10,15 for ethanol and 7.7 × 10,7 for allopregnanolone were obtained. These results confirm the presence of QTL for ethanol and allopregnanolone sensitivity in a common region of chromosome 2 and suggest possible pleiotropic genetic influence on sensitivity to these drugs. [source] Genetic basis for the psychostimulant effects of nicotine: a quantitative trait locus analysis in AcB/BcA recombinant congenic miceGENES, BRAIN AND BEHAVIOR, Issue 7 2005K. J. Gill Genetic differences in sensitivity to nicotine have been reported in both animals and humans. The present study utilized a novel methodology to map genes involved in regulating both the psychostimulant and depressant effects of nicotine in the AcB/BcA recombinant congenic strains (RCS) of mice. Locomotor activity was measured in a computerized open-field apparatus following subcutaneous administration of saline (days 1 and 2) or nicotine on day 3. The phenotypic measures obtained from this experimental design included total basal locomotor activity, as well as total nicotine activity, nicotine difference scores, nicotine percent change and nicotine regression residual scores. The results indicated that the C57BL/6J (B6) were insensitive to nicotine over the entire dose,response curve (0.1, 0.2, 0.4 and 0.8 mg/kg). However, the 0.8-mg/kg dose of nicotine produced a significant decrease in the locomotor activity in the A/J strain and a wide and continuous range of both locomotor excitation and depression among the AcB/BcA RCS. Single-locus association analysis in the AcB RCS identified quantitative trait loci (QTL) for the psychostimulant effects of nicotine on chromosomes 11, 12, 13, 14 and 17 and one QTL for nicotine-induced depression on chromosome 11. In the BcA RCS, nicotine-induced locomotor activation was associated with seven putative regions on chromosomes 2, 7, 8, 13, 14, 16 and 17. There were no overlapping QTL and no genetic correlations between saline- and nicotine-related phenotypes in the AcB/BcA RCS. A number of putative candidate genes were in proximity to regions identified with nicotine sensitivity, including the ,2 subunit of the nicotinic acetylcholine receptor and the dopamine D3 receptor. [source] Heritability, correlations and in silico mapping of locomotor behavior and neurochemistry in inbred strains of miceGENES, BRAIN AND BEHAVIOR, Issue 4 2005T. R. Mhyre The midbrain dopamine system mediates normal and pathologic behaviors related to motor activity, attention, motivation/reward and cognition. These are complex, quantitative traits whose variation among individuals is modulated by genetic, epigenetic and environmental factors. Conventional genetic methods have identified several genes important to this system, but the majority of factors contributing to the variation remain unknown. To understand these genetic and environmental factors, we initiated a study measuring 21 behavioral and neurochemical traits in 15 common inbred mouse strains. We report trait data, heritabilities and genetic and non-genetic correlations between pheno-types. In general, the behavioral traits were more heritable than neurochemical traits, and both genetic and non-genetic correlations within these trait sets were high. Surprisingly, there were few significant correlations between the behavioral and the individual neurochemical traits. However, striatal serotonin and one measure of dopamine turnover (DOPAC/DA) were highly correlated with most behavioral measures. The variable accounting for the most variation in behavior was mouse strain and not a specific neurochemical measure, suggesting that additional genetic factors remain to be determined to account for these behavioral differences. We also report the prospective use of the in silico method of quantitative trait loci (QTL) analysis and demonstrate difficulties in the use of this method, which failed to detect significant QTLs for the majority of these traits. These data serve as a framework for further studies of correlations between different midbrain dopamine traits and as a guide for experimental cross designs to identify QTLs and genes that contribute to these traits. [source] Potential pleiotropic effects of Mpdz on vulnerability to seizuresGENES, BRAIN AND BEHAVIOR, Issue 1 2004C. Fehr We previously mapped quantitative trait loci (QTL) responsible for approximately 26% of the genetic variance in acute alcohol and barbiturate (i.e., pentobarbital) withdrawal convulsion liability to a <,1 cM (1.8 Mb) interval of mouse chromosome 4. To date, Mpdz, which encodes the multiple PSD95/DLG/ZO-1 (PDZ) domain protein (MPDZ), is the only gene within the interval shown to have allelic variants that differ in coding sequence and/or expression, making it a strong candidate gene for the QTL. Previous work indicates that Mpdz haplotypes in standard mouse strains encode distinct protein variants (MPDZ1-3), and that MPDZ status is genetically correlated with severity of withdrawal from alcohol and pentobarbital. Here, we report that MPDZ status cosegregates with withdrawal convulsion severity in lines of mice selectively bred for phenotypic differences in severity of acute withdrawal from alcohol [i.e., High Alcohol Withdrawal (HAW) and Low Alcohol Withdrawal (LAW) lines] or pentobarbital [High Pentobarbital Withdrawal (HPW) and Low Pentobarbital Withdrawal (LPW) lines]. These analyses confirm that MPDZ status is associated with severity of alcohol and pentobarbital withdrawal convulsions. Using a panel of standard inbred strains of mice, we assessed the association between MPDZ status with seizures induced by nine chemiconvulsants. Our results show that MPDZ status is genetically correlated with seizure sensitivity to pentylenetetrazol, kainate and other chemiconvulsants. Our results provide evidence that Mpdz may have pleiotropic effects on multiple seizure phenotypes, including seizures associated with withdrawal from two classes of central nervous system (CNS) depressants and sensitivity to specific chemiconvulsants that affect glutaminergic and GABAergic neurotransmission. [source] Pleiotropic effect of a locus on chromosome 4 influencing alcohol drinking and emotional reactivity in ratsGENES, BRAIN AND BEHAVIOR, Issue 3 2003E. Terenina-Rigaldie A QTL search in a segregating F2 intercross between HEP (High-Ethanol Preferring line) and wistar-kyoto (WKY, a low-alcohol consuming strain) rats identified a locus on chromosome 4 linked to the consumption of a 5% alcohol solution offered as a free choice with water (Terenina-Rigaldie et al. submitted). In order to confirm and analyse the influence of this locus, F2 rats were selected according to their genotype at the markers flanking the QTL and bred in order to obtain two groups of rats homozygous HEP/HEP (,HIGH' line) or WKY/WKY (,LOW' line) at the QTL, the rest of the genome being randomly inherited from one or the other founder strain. These two groups of animals displayed large differences in emotional reactivity (open field, elevated-plus maze), sensitivity to taste reinforcers (saccharin, quinine) and alcohol consumption (either forced or as a free choice with water). These results confirm the influence of this locus on alcohol intake and emotional reactivity traits, and suggest a pleiotropic effect of the gene(s) involved. Current research aims at the identification of this (these) gene(s). [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] Bivariate combined linkage and association mapping of quantitative trait lociGENETIC EPIDEMIOLOGY, Issue 5 2008Jeesun Jung Abstract In this paper, bivariate/multivariate variance component models are proposed for high-resolution combined linkage and association mapping of quantitative trait loci (QTL), based on combinations of pedigree and population data. Suppose that a quantitative trait locus is located in a chromosome region that exerts pleiotropic effects on multiple quantitative traits. In the region, multiple markers such as single nucleotide polymorphisms are typed. Two regression models, "genotype effect model" and "additive effect model", are proposed to model the association between the markers and the trait locus. The linkage information, i.e., recombination fractions between the QTL and the markers, is modeled in the variance and covariance matrix. By analytical formulae, we show that the "genotype effect model" can be used to model the additive and dominant effects simultaneously; the "additive effect model" only takes care of additive effect. Based on the two models, F -test statistics are proposed to test association between the QTL and markers. By analytical power analysis, we show that bivariate models can be more powerful than univariate models. For moderate-sized samples, the proposed models lead to correct type I error rates; and so the models are reasonably robust. As a practical example, the method is applied to analyze the genetic inheritance of rheumatoid arthritis for the data of The North American Rheumatoid Arthritis Consortium, Problem 2, Genetic Analysis Workshop 15, which confirms the advantage of the proposed bivariate models. Genet. Epidemiol. 2008. © 2008 Wiley-Liss, Inc. [source] Interpreting analyses of continuous covariates in affected sibling pair linkage studiesGENETIC EPIDEMIOLOGY, Issue 6 2007Silke Schmidt Abstract Datasets collected for linkage analyses of complex human diseases often include a number of clinical or environmental covariates. In this study, we evaluated the performance of three linkage analysis methods when the relationship between continuous covariates and disease risk or linkage heterogeneity was modeled in three different ways: (1) The covariate distribution is determined by a quantitative trait locus (QTL), which contributes indirectly to the disease risk; (2) the covariate is not genetically determined, but influences the disease risk through statistical interaction with a disease susceptibility locus; (3) the covariate distribution differs in families linked or unlinked to a particular disease susceptibility locus. We analyzed simulated datasets with a regression-based QTL analysis, a nonparametric analysis of the binary affection status, and the ordered subset analysis (OSA). We found that a significant OSA result may be due to a gene that influences variability in the population distribution of a continuous disease risk factor. Conversely, a regression-based QTL analysis may detect the presence of gene-environment (G × E) interaction in a sample of primarily affected individuals. The contribution of unaffected siblings and the size of baseline lod scores may help distinguish between QTL and G × E models. As illustrated by a linkage study of multiplex families with age-related macular degeneration, our findings assist in the interpretation of analysis results in real datasets. They suggest that the side-by-side evaluation of OSA and QTL results may provide important information about the relationship of measured covariates with either disease risk or linkage heterogeneity. 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] Variance component models for X-linked QTLsGENETIC EPIDEMIOLOGY, Issue 5 2006Kenneth Lange Abstract This paper discusses the theory and implementation of a model for mapping X-linked quantitative trait loci (QTL). As a result of X inactivation, a female's body is subdivided into a number of patches. In each patch one of her two X chromosomes is randomly switched off. This smooths the allelic contributions in a heterozygote and implies that females should show less trait variation than males for an X-linked trait. The latest version of the genetic analysis program Mendel incorporates a simple variance component version of this model. An application to head circumference in autistic children illustrates Mendel in action. Genet. Epidemiol. 2006. © 2006 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] Limits of fine-mapping a quantitative traitGENETIC EPIDEMIOLOGY, Issue 2 2003Larry D. Atwood Abstract Once a significant linkage is found, an important goal is reducing the error in the estimated location of the linked locus. A common approach to reducing location error, called fine-mapping, is the genotyping of additional markers in the linked region to increase the genetic information. The utility of fine-mapping for quantitative trait linkage analysis is largely unknown. To explore this issue, we performed a fine-mapping simulation in which the region containing a significant linkage at a 10-centiMorgan (cM) resolution was fine-mapped at 2, 1, and 0.5 cM. We simulated six quantitative trait models in which the proportion of variation due to the quantitative trait locus (QTL) ranged from 0.20,0.90. We used four sampling designs that were all combinations of 100 and 200 families of sizes 5 and 7. Variance components linkage analysis (Genehunter) was performed until 1,000 replicates were found with a maximum lodscore greater than 3.0. For each of these 1,000 replications, we repeated the linkage analysis three times: once for each of the fine-map resolutions. For the most realistic model, reduction in the average location error ranged from 3,15% for 2-cM fine-mapping and from 3,18% for 1-cM fine-mapping, depending on the number of families and family size. Fine-mapping at 0.5 cM did not differ from the 1-cM results. Thus, if the QTL accounts for a small proportion of the variation, as is the case for realistic traits, fine-mapping has little value. Genet Epidemiol 24:99,106, 2003. © 2003 Wiley-Liss, Inc. [source] Unified sampling approach for multipoint linkage disequilibrium mapping of qualitative and quantitative traitsGENETIC EPIDEMIOLOGY, Issue 4 2002Fang-Chi Hsu Abstract Rapid development in biotechnology has enhanced the opportunity to deal with multipoint gene mapping for complex diseases, and association studies using quantitative traits have recently generated much attention. Unlike the conventional hypothesis-testing approach for fine mapping, we propose a unified multipoint method to localize a gene controlling a quantitative trait. We first calculate the sample size needed to detect linkage and linkage disequilibrium (LD) for a quantitative trait, categorized by decile, under three different modes of inheritance. Our results show that sampling trios of offspring and their parents from either extremely low (EL) or extremely high (EH) probands provides greater statistical power than sampling in the intermediate range. We next propose a unified sampling approach for multipoint LD mapping, where the goal is to estimate the map position (,) of a trait locus and to calculate a confidence interval along with its sampling uncertainty. Our method builds upon a model for an expected preferential transmission statistic at an arbitrary locus conditional on the sampling scheme, such as sampling from EL and EH probands. This approach is valid regardless of the underlying genetic model. The one major assumption for this model is that no more than one quantitative trait locus (QTL) is linked to the region being mapped. Finally we illustrate the proposed method using family data on total serum IgE levels collected in multiplex asthmatic families from Barbados. An unobserved QTL appears to be located at ,, = 41.93 cM with 95% confidence interval of (40.84, 43.02) through the 20-cM region framed by markers D12S1052 and D12S1064 on chromosome 12. The test statistic shows strong evidence of linkage and LD (chi-square statistic = 18.39 with 2 df, P -value = 0.0001). Genet. Epidemiol. 22:298,312, 2002. © 2002 Wiley-Liss, Inc. [source] Mouse chromosome 11 harbors genetic determinants of hippocampal strain-specific nicotinic receptor expressionHIPPOCAMPUS, Issue 8 2008Scott W. Rogers Abstract Differences between isogenic mouse strains in cellular expression of the neuronal nicotinic acetylcholine (ACh) receptor subunit alpha4 (nAChR,4) by the dorsal hippocampus are well known. To investigate further the genetic basis of these variations, expression of the nAChR,4 subunit was measured in congenic mouse lines derived from two strains exhibiting notable divergence in the expression of this subunit: C3H and C57BL/6. Congenic lines carrying reciprocally introgressed regions (quantitative trait loci; QTL) from chromosomes 4, 5, and 12 each retained the phenotype most closely associated with the parental strain. However, in congenic lines harboring the reciprocal transfer of a chromosome 11 QTL, a characteristic difference in the ratio of interneurons versus astrocytes expressing nAChR,4 in the CA1 region is reversed relative to the parental strain. These finding suggest that this chromosomal segment harbors genes that regulate strain distinct hippocampal morphology that is revealed by nAChR,4 expression. © 2008 Wiley-Liss, Inc. [source] Genetic analysis of collagen-induced arthritis in rats: a polygenic model for rheumatoid arthritis predicts a common framework of cross-species inflammatory/autoimmune disease lociIMMUNOLOGICAL REVIEWS, Issue 1 2001Marie M. Griffiths Summary: Collagen-induced arthritis (CIA) is a useful model for dissecting the genetic patterns underlying susceptibility to rheumatoid arthritis (RA) and related chronic/inflammatory autoimmune diseases. CIA exhibits three phenotypes characteristic of autoimmune disease pathogenesis: abnormal levels of immune reactivity to self antigens; chronic inflammation of target organs expressing that specific autoantigen; activation and direct participation of invading mononuclear cells and resident tissue fibroblasts in organ damage. Over 25 different quantitative trait loci (QTL) regulating arthritis severity and autoantibody in rats with CIA are mapped. QTL-congenic strains show that certain CIA,QTLs can modulate arthritis independently. These monogenic models are proving to be highly informative for fine mapping and function studies, revealing gender effects and evidence of gene clusters. Recent genome scans of RA populations identified RA-susceptibility loci in chromosome regions homologous to rat chromosomal segments housing CIA,QTLs. Also, CIA,QTLs frequently co-localize with susceptibility QTLs mapped in other rat arthritis models induced with non-immunogenic adjuvant oils and/or in rat autoimmune models of multiple sclerosis and diabetes. Common autoimmunity genes and inflammation genes important to several human diseases are likely being detected in the various rat disease models. Continued dissection of the genetic underpinnings of rat arthritis models should provide candidate genes for investigation in human patients and lead to a clearer understanding of the complex genetics of RA. [source] X-linked QTL for knockdown resistance to high temperature in Drosophila melanogasterINSECT MOLECULAR BIOLOGY, Issue 4 2007F. M. Norry Abstract Knockdown Resistance to High Temperature (KRHT) is an adaptive trait of thermotolerance in insects. An interval mapping was performed on chromosome X of Drosophila melanogaster to search for quantitative trait loci (QTL) affecting KRHT. A backcross population was obtained from two lines that dramatically differ for KRHT. Microsatellites were used as markers. Composite interval mapping identified a large-effect QTL in the region of band 10 where putative candidate genes map. To further test for this QTL a set of recombinant (but non-inbred) lines was obtained from backcrosses between the parental lines used for the interval mapping. Recombinant line analysis confirmed that one QTL is targeted by band 10. We identify and discuss candidate loci contained within our QTL region. [source] QTL for traits related to humoral immune response estimated from data of a porcine F2 resource populationINTERNATIONAL JOURNAL OF IMMUNOGENETICS, Issue 3 2009K. Wimmers Summary This study aimed to map quantitative trait loci (QTL) for traits related to humoral innate immune defence. Therefore, haemolytic complement activity in the alternative and the classical pathway, serum concentration of C3c and of haptoglobin (HP) were measured in blood samples obtained from F2 piglets (n = 457) of a porcine F2 resource population before and after Mycoplasma hyopneumoniae, Aujeszky's disease virus (Suid herpesvirus I, SuHVI) and porcine reproductive and respiratory syndrome virus (PRRSV) vaccination at 6, 14 and 16 weeks of age. Animals were genotyped at 88 autosomal markers. QTL analysis was performed under the line cross and the half sib. Phenotypic data were adjusted for systematic effects by mixed models with and without repeated measures statement. In total, 46 and 21 estimated QTL positions were detected with genome-wide significance at the 0.05 and 0.01 level, respectively. The proximal region of SSC2 (orthologous to HSA11 0,70 Mb), the distal region of SSC4 (HSA1 95,155 Mb), and the intermediate region of SSC16 (HSA5 0,73 Mb and 150,174 Mb) showed a clustering of estimated QTL positions for complement activity based on the different models. A common genetic background, i.e. a single true QTL, might underlie these QTL positions for related traits. In addition, QTL for antibody titres were detected on SSC1, 2, 6 and 7. With regard to number and magnitude of their impact, QTL for humoral innate immune traits behave like those for other quantitative traits. Discovery of such QTL facilitates the identification of candidate genes for disease resistance and immune competence that are applicable in selective breeding and further research towards improving therapeutic and prophylactic measures. [source] Fine mapping and detection of the causative mutation underlying Quantitative Trait LociJOURNAL OF ANIMAL BREEDING AND GENETICS, Issue 5 2010E. Uleberg Summary The effect on power and precision of including the causative SNP amongst the investigated markers in Quantitative Trait Loci (QTL) mapping experiments was investigated. Three fine mapping methods were tested to see which was most efficient in finding the causative mutation: combined linkage and linkage disequilibrium mapping (LLD); association mapping (MARK); a combination of LLD and association mapping (LLDMARK). Two simulated data sets were analysed: in one set, the causative SNP was included amongst the markers, while in the other set the causative SNP was masked between markers. Including the causative SNP amongst the markers increased both precision and power in the analyses. For the LLD method the number of correctly positioned QTL increased from 17 for the analysis without the causative SNP to 77 for the analysis including the causative SNP. The likelihood of the data analysis increased from 3.4 to 13.3 likelihood units for the MARK method when the causative SNP was included. When the causative SNP was masked between the analysed markers, the LLD method was most efficient in detecting the correct QTL position, while the MARK method was most efficient when the causative SNP was included as a marker in the analysis. The LLDMARK method, combining association mapping and LLD, assumes a QTL as the null hypothesis (using LLD method) and tests whether the ,putative causative SNP' explains significantly more variance than a QTL in the region. Thus, if the putative causative SNP does not only give an Identical-By-Descent (IBD) signal, but also an Alike-In-State (AIS) signal, LLDMARK gives a positive likelihood ratio. LLDMARK detected less than half as many causative SNPs as the other methods, and also had a relatively high false discovery rate when the QTL effect was large. LLDMARK may however be more robust against spurious associations, because the regional IBD is largely corrected for by fitting a QTL effect in the null hypothesis model. [source] The distribution of QTL additive and dominance effects in porcine F2 crossesJOURNAL OF ANIMAL BREEDING AND GENETICS, Issue 3 2010J. Bennewitz Summary The present study used published quantitative trait loci (QTL) mapping data from three F2 crosses in pigs for 34 meat quality and carcass traits to derive the distribution of additive QTL effects as well as dominance coefficients. Dominance coefficients were calculated as the observed QTL dominance deviation divided by the absolute value of the observed QTL additive effect. The error variance of this ratio was approximated using the delta method. Mixtures of normal distributions (mixtures of normals) were fitted to the dominance coefficient using a modified EM-algorithm that considered the heterogeneous error variances of the data points. The results suggested clearly to fit one component which means that the dominance coefficients are normally distributed with an estimated mean (standard deviation) of 0.193 (0.312). For the additive effects mixtures of normals and a truncated exponential distribution were fitted. Two components were fitted by the mixtures of normals. The mixtures of normals did not predict enough QTL with small effects compared to the exponential distribution and to literature reports. The estimated rate parameter of the exponential distribution was 5.81 resulting in a mean effect of 0.172. [source] | |||||||||||||||||||||||||||||||||||||