Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “complex trait”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 577 records · Page 32Linked to original sources
PubMed2003

Molecular variation of human HSP90alpha and HSP90beta genes in Caucasians.

Understanding DNA variation within the human genome is fundamental to the identification and interpretation of genetic components underlying complex traits and diseases. Despite their role in many crucial cellular pathways and their reported involvement in many complex diseases no data are available on the molecular variability of the genes coding for Heat Shock Proteins 90Kda (HSP90). Towards this purpose we have used DHPLC methodology to survey, a sample of Caucasians for genetic polymorphisms in the exons and exon-flanking regions of the expressed genes of human HSP90 gene families, HSP90alpha (HSPCAL4, 14q31.3) and HSP90beta (HSPCB, 6p12). A total of 18 and 11 variants were found in the HSP90-alpha and -beta genes respectively, providing an initial view of human genetic variation in these important genes. Only three of the observed mutations altered the genic product. Interestingly, one of the variations observed was a missense mutation leading to the impairment of the hsp90alpha protein.

DNA↗
PubMed2001

Linkage and association analysis of angiotensin I-converting enzyme (ACE)-gene polymorphisms with ACE concentration and blood pressure.

Considerable effort has been expended to determine whether the gene for angiotensin I-converting enzyme (ACE) confers susceptibility to cardiovascular disease. In this study, we genotyped 13 polymorphisms in the ACE gene in 1,343 Nigerians from 332 families. To localize the genetic effect, we first performed linkage and association analysis of all the markers with ACE concentration. In multipoint variance-component analysis, this region was strongly linked to ACE concentration (maximum LOD score 7.5). Likewise, most of the polymorphisms in the ACE gene were significantly associated with ACE (P<.0013). The two most highly associated polymorphisms, ACE4 and ACE8, accounted for 6% and 19% of the variance in ACE, respectively. A two-locus additive model with an additive x additive interaction of these polymorphisms explained most of the ACE variation associated with this region. We next analyzed the relationship between these two polymorphisms (ACE4 and ACE8) and blood pressure (BP). Although no evidence of linkage was detected, significant association was found for both systolic and diastolic BP when a two-locus additive model developed for ACE concentration was used. Further analyses demonstrated that an epistasis model provided the best fit to the BP variation. In conclusion, we found that the two polymorphisms explaining the greatest variation in ACE concentration are significantly associated with BP, through interaction, in this African population sample. Our study also demonstrates that greater statistical power can be anticipated with association analysis versus linkage, when markers in strong linkage disequilibrium with a trait locus have been identified. Furthermore, allelic interaction may play an important role in the dissection of complex traits such as BP.

Adult↗
PubMed2001

Genome-wide search for loci controlling serum IGF binding protein levels of mice.

A segregating F(2) pedigree based on two mouse lines (DU6i and DBA/2) with extremely different growth characteristics was generated to search for loci affecting serum levels of insulin-like growth factor (IGF) binding proteins (IGFBPs) and to estimate their effects on growth and body composition. DU6i is characterized by high body mass and obesity associated with hyperinsulinemia, hyperleptinemia, and elevated serum IGF-I concentrations. Furthermore, significantly elevated serum levels of IGFBP-2, IGFBP-3, and IGFBP-4 were found in DU6i vs. DBA/2 mice. Linkage analysis identified loci with major effects on the serum level of IGFBP-3 on Chromosome 5 at 58 cM (Igfbp3q1; F = 9.9) and on Chromosome 10 at 46 cM (Igfbp3q2; F = 33.8). A locus significantly influencing serum IGFBP-2 levels in males was found on Chromosome 7. Additional linkage was detected in males and females for IGFBP-2 on Chromosomes 8, 11, 14, 17, and X, and for IGFBP-4 on Chromosome 4. Additional loci affecting IGFBPs acted in a sex-specific manner. The identified loci coincide in part with chromosomal regions controlling growth and obesity. Thus, multiple genes or pleiotropic gene effects may be assumed for these chromosomal regions. The identification of quantitative trait loci for IGFBPs as subcomponents of growth regulation and differentiation will further improve the understanding of complex trait regulation.

Animals↗
PubMed2003

Genetic architecture of a selection response in Arabidopsis thaliana.

Quantitative trait locus (QTL) mapping has become an established and effective method for studying the genetic architecture of complex traits. In this report, we use a QTL mapping approach in combination with data from a large selection experiment in Arabidopsis thaliana to explore a response to selection of experimental populations with differentiated genetic backgrounds. Experimental populations with genetic backgrounds derived from ecotypes Landsberg and Niederzenz were exposed to multiple generations of fertility and viability selection. This selection resulted in phenotypic shifts in a number of life-history and fitness-related characters including early development time, flowering time, dry biomass, longevity, and fruit production. Quantitative trait loci were mapped for these traits and their positions were compared to previously characterized allele frequency changes in the experimental populations (Ungerer et al. 2003). Quantitative trait locus positions largely colocalized with genomic regions under strong and consistent selection in populations with differentiated genetic backgrounds, suggesting that alleles for these traits were selected similarly in differentiated genetic backgrounds. However, one QTL region exhibited a more variable response; being positively selected on one genetic background but apparently neutral in another. This study demonstrates how QTL mapping approaches can be combined with map-based population genetic data to study how selection acts on standing genetic variation in populations.

Analysis of Variance↗
PubMed2005

Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice.

Activation of the mesolimbic dopamine reward pathway by acute ethanol produces reinforcement and changes in gene expression that appear to be crucial to the molecular basis for adaptive behaviors and addiction. The inbred mouse strains DBA/2J and C57BL/6J exhibit contrasting acute behavioral responses to ethanol. We used oligonucleotide microarrays and bioinformatics methods to characterize patterns of gene expression in three brain regions of the mesolimbic reward pathway of these strains. Expression profiling included examination of both differences in gene expression 4 h after saline injection or acute ethanol (2 g/kg). Using a rigorous stepwise method for microarray analysis, we identified 788 genes differentially expressed in control DBA/2J versus C57BL/6J mice and 307 ethanol-regulated genes in the nucleus accumbens, prefrontal cortex, and ventral tegmental area. There were strikingly divergent patterns of ethanol-responsive gene expression in the two strains. Ethanol-responsive genes also showed clustering at discrete chromosomal regions, suggesting local chromatin effects in regulation. Ethanol-regulated genes were generally related to neuroplasticity, but regulation of discrete functional groups and pathways was brain region specific: glucocorticoid signaling, neurogenesis, and myelination in the prefrontal cortex; neuropeptide signaling and developmental genes, including factor Bdnf, in the nucleus accumbens; and retinoic acid signaling in the ventral tegmental area. Bioinformatics analysis identified several potential candidate genes for quantitative trait loci linked to ethanol behaviors, further supporting a role for expression profiling in identifying genes for complex traits. Brain region-specific changes in signaling and neuronal plasticity may be critical components in development of lasting ethanol behavioral phenotypes such as dependence, sensitization, and craving.

Animals↗
PubMed2003

Finding starting points for Markov chain Monte Carlo analysis of genetic data from large and complex pedigrees.

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.

Algorithms↗
PubMed2004

Adjusting for covariates in variance components QTL linkage analysis.

Variance components modeling has emerged as a powerful method for quantitative trait loci (QTL) linkage analysis. However, the power to detect a gene of minor effect is low. Many complex traits are affected by environmental as well as genetic factors, and one strategy to increase power is to reduce nongenetic phenotypic variance by adjusting for environmental covariates. In this paper, we investigate the power of three approaches to covariate adjustment in variance components linkage analysis: (i) incorporate covariates in the means model, (ii) incorporate covariates in the covariance matrix, and (iii) perform analysis on residual statistics. These approaches are compared to an analysis without adjustment. The results show that in the absence of correlation between the covariate and the QTL effect, adjusting for covariates indeed increases power to detect an underlying QTL. As this correlation increases, however, the power decreases. In the presence of a causal association between QTL and covariates, not adjusting for covariates appeared to be more powerful. The three approaches for adjusting for covariate: residual statistics, the means model, and the covariance model, had equal power to detect a QTL.

Analysis of Variance↗
PubMed2003

Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas fir. III. Quantitative trait loci-by-environment interactions.

Quantitative trait loci (QTL) were mapped in the woody perennial Douglas fir (Pseudotsuga menziesii var. menziesii [Mirb.] Franco) for complex traits controlling the timing of growth initiation and growth cessation. QTL were estimated under controlled environmental conditions to identify QTL interactions with photoperiod, moisture stress, winter chilling, and spring temperatures. A three-generation mapping population of 460 cloned progeny was used for genetic mapping and phenotypic evaluations. An all-marker interval mapping method was used for scanning the genome for the presence of QTL and single-factor ANOVA was used for estimating QTL-by-environment interactions. A modest number of QTL were detected per trait, with individual QTL explaining up to 9.5% of the phenotypic variation. Two QTL-by-treatment interactions were found for growth initiation, whereas several QTL-by-treatment interactions were detected among growth cessation traits. This is the first report of QTL interactions with specific environmental signals in forest trees and will assist in the identification of candidate genes controlling these important adaptive traits in perennial plants.

Genetic Linkage↗
PubMed2001

Procreative beneficence: why we should select the best children.

Eugenic selection of embryos is now possible by employing in vitro fertilization (IVF) and preimplantation genetic diagnosis (PGD). While PGD is currently being employed for the purposes of detecting chromosomal abnormalities or inherited genetic abnormalities, it could in principle be used to test any genetic trait such as hair colour or eye colour. Genetic research is rapidly progressing into the genetic basis of complex traits like intelligence and a gene has been identified for criminal behaviour in one family. Once the decision to have IVF is made, PGD has few 'costs' to couples, and people would be more inclined to use it to select less serious medical traits, such as a lower risk of developing Alzheimer Disease, or even for non-medical traits. PGD has already been used to select embryos of a desired gender in the absence of any history of sex-linked genetic disease. I will argue that: (1) some non-disease genes affect the likelihood of us leading the best life; (2) we have a reason to use information which is available about such genes in our reproductive decision-making; (3) couples should select embryos or fetuses which are most likely to have the best life, based on available genetic information, including information about non-disease genes. I will also argue that we should allow selection for non-disease genes even if this maintains or increases social inequality. I will focus on genes for intelligence and sex selection. I will defend a principle which I call Procreative Beneficence: couples (or single reproducers) should select the child, of the possible children they could have, who is expected to have the best life, or at least as good a life as the others, based on the relevant, available information.

Beneficence↗
PubMed2004

High factor VIII levels in venous thromboembolism show linkage to imprinted loci on chromosomes 5 and 11.

High factor VIII (FVIII) levels are known to be a risk factor for deep venous thrombosis, but the mechanisms responsible for high FVIII levels remain unclear. Here, a new phenotype "FVIII level residuum" (FVIII-R) was defined in order to eliminate the impact of common determinants on FVIII levels. We studied 13 families of patients with thrombosis and reproducibly high FVIII levels of unknown origin. Since familial clustering was evident, we looked for a possible genetic basis. A genome scan was performed with 402 evenly spaced microsatellite markers. A quantitative linkage analysis using variance component methods showed suggestive evidence for linkage of FVIII-R with a locus on chromosome 8 (logarithm of odds [LOD] = 2.1). In addition, we performed parametric exploratory linkage analysis of dichotomized FVIII-R, taking a parent-of-origin effect into account. Single-trait-locus MOD-score analysis showed suggestive evidence for linkage under an imprinting model at chromosomes 5 and 11. Furthermore, a 2-trait-locus analysis under a multiplicative model for the loci of chromosomes 5 and 11 yielded a remarkable LOD of 4.44. It confirmed the finding of paternal imprinting, obtained by single-trait-locus analysis, at both loci. Our results suggest that high FVIII levels in venous thromboembolism represent a complex trait caused by several genetic factors.

Chromosomes, Human, Pair 11↗
PubMed2005

Genetic dissections of partial resistances to leaf and neck blast in rice (Oryza sativa L.).

In a recombinant inbred line (RIL) population of indica rice, two subpopulations composed of susceptible lines were selected for mapping of partial resistance to leaf blast with two isolates of the pathogen. A third subpopulation composed of susceptible lines with similar heading time was used for mapping of partial resistance to neck blast with a third isolate. The traits measured for partial resistance included diseased leaf area (DLA), lesion size (LS) and lesion number (LN) for leaf blast and lesion length (LL) and conidium amount (CA) for neck blast. A linkage map consisting of 168 DNA markers was constructed by using the whole RIL population. Quantitative trait loci (QTLs) conditioning these traits were determined at one-locus and two-locus levels. Eleven main-effect QTLs and 28 digenic interactions were detected by QTLMapper 1.01 b. Only three QTLs showing main effects were also involved in digenic interactions for the same trait. General contributions of epistatic QTLs of each trait ranged from 16.0% to 51.7%, while those of main-effect QTLs of each trait ranged from 4.7% to 38.8%. The general contributions of main-effect QTLs of most traits were smaller than those of epistatic QTLs, confirming the importance of epistasis as the genetic basis for complex traits. The general contributions of the main and epistatic effects of all QTLs detected for the two traits LL and CA of the partial resistance to neck blast reached 70.6% and 82.6% respectively, which obviously represented a major part of the genetic basis controlling partial resistance to neck blast. The results indicated the necessity for partial resistance mapping to use susceptible subpopulations where the interference of major resistance genes is avoided.

Chromosome Mapping↗
PubMed2006

Trait components provide tools to dissect the genetic susceptibility of migraine.

The commonly used "end diagnosis" phenotype that is adopted in linkage and association studies of complex traits is likely to represent an oversimplified model of the genetic background of a disease. This is also likely to be the case for common types of migraine, for which no convincingly associated genetic variants have been reported. In headache disorders, most genetic studies have used end diagnoses of the International Headache Society (IHS) classification as phenotypes. Here, we introduce an alternative strategy; we use trait components--individual clinical symptoms of migraine--to determine affection status in genomewide linkage analyses of migraine-affected families. We identified linkage between several traits and markers on chromosome 4q24 (highest LOD score under locus heterogeneity [HLOD] 4.52), a locus we previously reported to be linked to the end diagnosis migraine with aura. The pulsation trait identified a novel locus on 17p13 (HLOD 4.65). Additionally, a trait combination phenotype (IHS full criteria) revealed a locus on 18q12 (HLOD 3.29), and the age at onset trait revealed a locus on 4q28 (HLOD 2.99). Furthermore, suggestive or nearly suggestive evidence of linkage to four additional loci was observed with the traits phonophobia (10q22) and aggravation by physical exercise (12q21, 15q14, and Xp21), and, interestingly, these loci have been linked to migraine in previous studies. Our findings suggest that the use of symptom components of migraine instead of the end diagnosis provides a useful tool in stratifying the sample for genetic studies.

Chromosome Mapping↗
PubMed2026

X chromosome-wide association studies for quantitative trait loci based on the mixture of general pedigrees and additional unrelated individuals.

Genome-wide association studies have successfully identified many genetic variants associated with complex traits. However, most existing methods target autosomes rather than X chromosome, and several existing X chromosome-wide association studies (XWAS) at quantitative trait loci (QTL) largely focus on unrelated individuals, with limited attention to general pedigrees or mixture of general pedigrees and additional unrelated individuals (called the mixed data for brevity). In this study, we propose nine novel methods for XWAS at QTL in the mixed data (${\mathrm{MQX}}_{\mathrm{cat}}$, ${\mathrm{MQZ}}_{\mathrm{max}}$, ${\mathrm{MT}}_{\mathrm{plinkw}}$, ${\mathrm{MT}}_{\mathrm{chenw}}$, $\mathrm{MwM}3\mathrm{VNA}$, ${\mathrm{MQMVX}}_{\mathrm{cat}}$, ${\mathrm{MQMVZ}}_{\mathrm{max}}$, $\mathrm{MpMV}$, and $\mathrm{McMV}$), also applicable to general pedigrees alone. The first four methods test for mean differences across genotypes; the latter four test for differences in both means and variances; $\mathrm{MwM}3\mathrm{VNA}$ tests for variance differences only. All mean-based and mean-variance-based methods incorporate X chromosome inactivation information, and all nine methods consider genetic relatedness in pedigrees. Simulation studies confirm well-controlled type I error rates, and inclusion of pedigrees significantly improves statistical power. Note that there has been no study focusing on X chromosome for the mixed data or general pedigrees from UK Biobank database, so we apply our proposed methods to this dataset, which identify five total cholesterol (TC)-associated and 13 low-density lipoprotein cholesterol (LDL-C)-associated single nucleotide polymorphisms (SNPs). Linkage disequilibrium (LD) analysis reveals that these SNPs fall into three distinct LD blocks. Functional annotation and gene ontology enrichment analysis reveal 16 and 28 enriched pathways for TC-associated and LDL-C-associated genes, respectively. These methods provide robust and powerful tools for XWAS at QTL in both mixed data and general pedigrees.

Quantitative Trait Loci↗
PubMed2005

Mapping quantitative trait loci for milk production and genetic polymorphisms of milk proteins in dairy sheep.

In this paper, we present recent advances in the molecular dissection of complex traits in dairy sheep and discuss their possible impact on breeding schemes. In the first step, we review the literature data on genetic polymorphisms and the effects of sheep alphas1-casein and beta-lactoglobulin loci. It is concluded that the results are rather inconsistent and cannot be used in dairy sheep selection. In a second step, we describe the strategy implemented in France, Italy and Spain taking advantage of the genetic maps for QTL detection. These studies were part of a European project, called "genesheepsafety", which investigated both milk production and functional traits. Preliminary QTL results are presented for production traits.

Animals↗
PubMed2005

Geography is a better determinant of human genetic differentiation than ethnicity.

Individuals differ genetically in their susceptibility to particular diseases and their response to drugs. However, personalized treatments are difficult to develop, because disease susceptibility and drug response generally have poorly characterized genetic architecture. It is thus tempting to use the ethnicity of patients to capture some of the variation in allele frequencies at the genes underlying a clinical trait. The success of such a strategy depends on whether human populations can be accurately classified into discrete genetic ethnic groups. Despite the heated discussions and controversies surrounding this issue, there has been essentially no attempt so far to quantify the relative power of ethnic groups and geography at predicting the proportion of shared alleles between human populations. Here, we present the first such quantification using a dataset of 51 populations typed at 377 autosomal microsatellite markers, and show that pair-wise geographic distances across landmasses constitute a far better predictor than ethnicity. Allele-sharing between human populations worldwide decays smoothly with increasing physical distance. We discuss the relevance of these patterns for the expected distribution of variants of medical interest. The distribution patterns of gene coding for simple traits are expected to be highly heterogeneous, as most such genes experienced strong natural selection. However, variants involved in complex traits are expected to behave essentially neutrally, and we expect them to fit closely our predictions based on microsatellites. We conclude that the use of ethnicity alone will often be inadequate as a basis for medical treatment.

Ethnicity↗
PubMed2000

Segregation distortion of mouse t haplotypes the molecular basis emerges.

The t haplotype is an ancestral version of proximal mouse chromosome 17 that has evolved mechanisms to persist as an intact genomic variant in mouse populations. t haplotypes contain mutations that affect embryonic development, male fertility and male transmission ratio distortion (TRD). Collectively, these mutations drive the evolutionary success of t haplotypes, a phenomenon that remains one of the longstanding mysteries of mouse genetics. Molecular genetic analysis of TRD has been confounded by inversions that arose to lock together the various elements of this complex trait. Our first molecular glimpse of the TRD mechanism has finally been revealed with the cloning of the t complex responder (Tcr) locus, a chimeric kinase with a genetically cis active effect. Whereas + sperm in a +/t male have impaired flagellar function caused by the deleterious action of trans-active, t-haplotype-encoded 'distorters,' the mutant activity of Tcr counterbalances the distorter effects, maintaining the motility and fertilizing ability of t sperm.

Animals↗
PubMed2003

Estimation and tests of haplotype-environment interaction when linkage phase is ambiguous.

In the study of complex traits, the utility of linkage analysis and single marker association tests can be limited for researchers attempting to elucidate the complex interplay between a gene and environmental covariates. For these purposes, tests of gene-environment interactions are needed. In addition, recent studies have indicated that haplotypes, which are specific combinations of nucleotides on the same chromosome, may be more suitable as the unit of analysis for statistical tests than single genetic markers. The difficulty with this approach is that, in standard laboratory genotyping, haplotypes are often not directly observable. Instead, unphased marker phenotypes are collected. In this article, we present a method for estimating and testing haplotype-environment interactions when linkage phase is potentially ambiguous. The method builds on the work of Schaid et al. [2002] and is applicable to any trait that can be placed in the generalized linear model framework. Simulations were run to illustrate the salient features of the method. In addition, the method was used to test for haplotype-smoking exposure interaction with data from the Childhood Asthma Management Program.

Algorithms↗
PubMed2006

Genetic characterization of a new set of recombinant inbred lines (LGXSM) formed from the inter-cross of SM/J and LG/J inbred mouse strains.

A new set of LGXSM recombinant inbred (RI) strains is presented. The RI strain panel consists of 18 remaining strains of the original 55 founding strains. Strain characterization is based on 506 polymorphic microsatellites and 4,289 single nucleotide polymorphisms (SNPs) distributed across the genome. Average microsatellite inter-marker distance is 4.80+/-4.84 Mb or 2.91+/-3.21 F(2) cM. SNPs are more densely spaced at 0.57+/-1.27 Mb. Ninety-five percent of all microsatellite inter-marker intervals are separated by less than 15.00 Mb or 8.50 F(2) cM, while 95% of the SNPs are less than 0.95 Mb apart. Strains show expected low levels of nonsyntenic association among loci and complete genomic independence. During inbreeding, the RI strains went through strong natural selection on the agouti locus on Chromosome 2, especially when the epistatically interacting tyrosinase locus on Chromosome 7 carried the wild-type allele. The LG/J and SM/J strains differ in a large number of biomedically important traits, and they and their inter-cross progeny have been used in multiple mapping studies. The LGxSM RI strain panel provides a powerful new resource for mapping the genetic bases of complex traits and should prove to be of great biomedical utility in modeling complex human diseases such as obesity and diabetes.

Animals↗