Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “genetic architecture”

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 19 recordsLinked to original sources
PubMed2005

The evolution of genetic architecture. I. Diversification of genetic backgrounds by genetic drift.

The genetic architecture of a phenotype plays a critical role in determining phenotypic evolution through its effects on patterns of genetic variation. Genetic architecture is often considered to be constant in evolutionary quantitative genetic models. However, genetic architecture may be variable and itself evolve when there are dominance and epistatic interactions among alleles at the same and different loci, respectively. The evolution of genetic architecture by genetic drift is examined here by testing the breeding value of four standard inbred mouse strains mated across a set of 26 related recombinant quasi-inbred (RqI) lines generated from the intercross of the Large (LG/J) and Small (SM/J) inbred mouse strains. Phenotypes of interest include age-specific body weights, growth, and adult body composition. If the genetic architecture of these traits has differentiated by genetic drift during the production of the RqI strains, we should observe interactions between tester strain and RqI strain. The breeding values of the tester strains will change relative to one another depending on which RqI strain they are crossed to. The study included an average of 15.1 offspring per cross, over a total of 100 different crosses. Multivariate and univariate analyses of variance indicate that there is strongly significant interaction for all traits. Interaction is more pronounced in males than in females and accounted for an average of about 40% of the explained variation in males and 30% in females. These results indicate that the genetic architecture of these traits has differentiated by genetic drift in the RqI strains since their isolation from a common founder population. Further analysis indicates that this differentiation results in changes in the order of tester strain effects so that common patterns of selection in these differentiated populations could result in the fixation of different alleles.

Animals↗
PubMed2000

Do the dimensions of the temperament and character inventory map a simple genetic architecture? Evidence from molecular genetics and factor analysis.

OBJECTIVE: It has been reported that the human temperament dimensions of novelty seeking and harm avoidance are associated with polymorphisms in the D(4) dopamine receptor gene (D4DR) and the serotonin-transporter-linked promoter region (5-HTTLPR), respectively. Although these findings are consistent with Cloninger's hypothesized psychobiological model of temperament and character, many studies failed to replicate these findings. In the present study the authors tested whether the psychobiological model taps the genetic architecture of personality by exploring associations between these candidate genes and the dimensions of the Temperament and Character Inventory and by examining its phenotypic structure. METHOD: Of the 946 male and female participants in the Baltimore Longitudinal Study of Aging to whom the Temperament and Character Inventory was administered, 587 were genotyped for a polymorphism with a 48-base-pair repeat in the D4DR gene and 425 were genotyped for a 44-base-pair insertion or deletion in the 5-HTTLPR polymorphism. RESULTS: There was no significant association between D4DR polymorphisms and novelty seeking. The authors also failed to find an association between 5-HTTLPR polymorphisms and harm avoidance. The factor structure of the Temperament and Character Inventory did not reveal the hypothesized phenotypic structure. CONCLUSIONS: This investigation produced no support for the temperament-character model at either the biological or psychological level.

Adult↗
PubMed2025

Leveraging local ancestry and cross-ancestry genetic architecture to improve genetic prediction of complex traits in admixed populations.

The broader application of polygenic risk score (PRS) is hindered by the limited transferability of PRS developed in Europeans to non-European populations. While many statistical methods have been developed to improve the performance of PRS in non-European populations, most of them focused on discrete genetic ancestry clusters and did not consider admixed individuals. Admixed individuals pose a unique challenge for PRS calculation due to the complexity of local ancestry and cross-ancestry effect sizes. Here, we present a statistical method called SDPR_admix for calculating PRS in admixed individuals. SDPR_admix characterizes the joint distribution of the effect sizes of a genetic variant with two ancestries to be both zero, ancestry enriched, or shared with correlation. SDPR_admix outperformed other methods in simulations and improved the prediction of real traits in European-African admixed individuals in UK Biobank when trained on the Population Architecture using Genomics and Epidemiology (PAGE) dataset (N = 13,000). Deployment of SDPR_admix on All of Us (N = 52,000) further increased the prediction accuracy by approximately 5-fold on average compared with training on PAGE. This enhancement was achieved with manageable computational time and cost, demonstrating the feasibility of training PRS models on large-scale All of Us data. We provided several examples demonstrating that both ancestral-enriched and shared effects, as included in the SDPR_admix prediction model, are helpful for improving polygenic prediction in admixed populations. We also applied SDPR_admix to construct PRS for admixed Americans with mixture of European and Amerindigenous ancestries and showed that SDPR_admix overall outperformed other methods.

Humans↗
PubMed2000

Quantitative genetic variation in Daphnia: temporal changes in genetic architecture.

Nonadditive genetic variation and genetic disequilibrium are two important factors that influence the evolutionary trajectory of natural populations. We assayed quantitative genetic variation in a temporary-pond-dwelling population of Daphnia pulex over a full season to examine the role of nonadditive genetic variation and genetic disequilibrium in determining the short-term evolutionary trajectory of a cyclic parthenogen. Quantitative traits were influenced by three factors: (1) clonal selection significantly changed the population mean phenotype during the course of the growing season; (2) sexual reproduction and recombination led to significant changes in life-history trait means and the levels of expressed genetic variation, implying the presence of substantial nonadditive genetic variation and genetic disequilibrium; and (3) Egg-bank effects were found to be an important component of the realized year-to-year change. Additionally, we examined the impact of genetic disequilibria induced by clonal selection on the genetic (co)variance structure with a common principal components model. Clonal selection caused significant changes in the (co)variance structure that were eliminated by a single bout of random mating, suggesting that a build-up of disequilibria was the primary source of changes in the (co)variance structure. The results of this study highlight the complexity of natural selection operating on populations that undergo alternating phases of sexual and asexual reproduction.

Animals↗
PubMed2025

Genomic structural equation modeling elucidates the shared genetic architecture of allergic disorders.

BACKGROUND: The intricate shared genetic architecture underlying allergic disorders-including allergic asthma, atopic dermatitis, contact dermatitis, allergic rhinitis, allergic conjunctivitis, allergic urticaria, anaphylaxis, and eosinophilic esophagitis-remains incompletely characterized. METHODS: Our study employed genomic structural equation modeling (Genomic SEM) to define the common factor representing the shared genetic architecture of allergic disorders. Coupled with diverse post-GWAS analytical methods, we aimed to discover susceptible loci and investigate genetic associations with external traits. Furthermore, we explored enriched genetic pathways, cellular layers, and genomic elements, and investigated putative plasma protein biomarkers. Polygenic risk score (PRS) analyses, leveraging our integrated GWAS data, were conducted to assess chromosomal-level risk associations for allergic disorders. RESULTS: A well-fitted genomic SEM integrated GWAS data, revealing the shared genetic architecture of allergic disorders. We identified a total of 2038 genome-wide significant SNP loci (p&#x2009;<&#x2009;5e-8), including 31 previously unreported loci. Fine-mapping of variants and gene sets pinpointed 2 causal variants and 31 candidate susceptible genes. Genetic correlation analyses further illuminated the shared genetic architecture underlying multiple traits, notably psychiatric disorders. Preliminary findings identified four putative causal plasma protein biomarkers. CONCLUSION: Notably, this study presents the first comprehensive genetic characterization of allergic disorders through a GWAS analysis of an unmeasured composite phenotype, providing novel insights into shared etiological pathways across these conditions.

Humans↗
PubMed2001

Genetic architecture of adaptive differentiation in evolving host races of the soapberry bug, Jadera haematoloma.

To explore genetic architecture and adaptive evolution, we conducted environmental and genetic experiments with two recently (ca. 100 generations) diverged, geographically adjacent races of the soapberry bug. One race occurs on a native host plant species, the other on an introduced host. We focused on three traits: length of the mouthparts, body size and development time. The first experiment was an environmental manipulation, comparing individuals of each population reared on one or the other host species ('cross-rearing') and estimating three evolutionary rates for each trait. The first rate, 'evolutionary path' compares ancestral-derived populations when both were reared on the introduced host. The second, 'current ecological contrast' compares populations with each reared on its natal host. The third, 'evolved tradeoff' compares the two races when reared on the native host. Differences among these rates are striking and informative. For example, development time, which appears to be relatively undifferentiated phenotypically, has actually evolved very rapidly via countergradient selection. The pattern differs for each trait, and clear developmental tradeoffs have evolved as quickly as adaptation to the new host in each. The second experiment was a two-generation 'line cross' study. With joint-scaling analyses, we compared purebred, hybrid and backcrossed individuals to describe genetic architecture. Additive genetic variance for mouthpart length was consistently large (ca. 60%), but the interaction of dominance, maternal effects and epistasis was important in the other traits. Rearing host strongly affected genetic architecture. There was no clear relationship between genetic architecture and rate of evolution. Selection has produced both additive and nonadditive differentiation between the host races with surprising speed, consistent with theoretical predictions about evolution in fitness-associated traits.

Adaptation, Biological↗
PubMed2026

Shared genetic architecture between major depression and intrinsic brain functional connectome organization.

BACKGROUND: Major depression (MD) is increasingly understood as a disorder characterized by widespread abnormalities in intrinsic brain functional network organization. Although both MD and brain functional connectome architecture are highly heritable, the genetic architecture underlying their relationship remains poorly characterized. METHODS: We integrated genome-wide association studies of MD with 191 ICA-based resting-state functional connectome traits to investigate their shared genetic architecture. These traits captured intrinsic connectome organization across amplitude, functional connectivity, and global connectivity domains. Cross-trait genetic analyses were used to assess pleiotropic overlap between traits. Locus-level and gene-based analyses integrating multi-omics evidence were performed to characterize the biological relevance of shared genetic signals. RESULTS: We identified significant genetic overlap between MD and 148 of 191 brain functional connectome traits. Cross-trait analyses revealed widespread shared genetic signals organized into 627 genomic loci across amplitude, functional connectivity, and global connectivity measures. Among these, 193 loci showed evidence consistent with shared causal variants based on colocalization analyses. Gene-level integration mapped these loci to 1459 protein-coding genes (390 unique genes). Multi-layer prioritization identified 17 high-confidence genes supported by convergent genomic, transcriptomic, and proteomic evidence, with enrichment in neurodevelopmental and lipid-related metabolism pathways. CONCLUSIONS: This study provides a multi-scale characterization of the shared genetic architecture between MD and intrinsic brain functional connectome organization, revealing that shared genetic signals between MD and brain functional systems are distributed across multiple functional levels and converge at the molecular level.

Connectome↗
PubMed1999

Estimating the genetic architecture of quantitative traits.

Understanding and estimating the structure and parameters associated with the genetic architecture of quantitative traits is a major research focus in quantitative genetics. With the availability of a well-saturated genetic map of molecular markers, it is possible to identify a major part of the structure of the genetic architecture of quantitative traits and to estimate the associated parameters. Multiple interval mapping, which was recently proposed for simultaneously mapping multiple quantitative trait loci (QTL), is well suited to the identification and estimation of the genetic architecture parameters, including the number, genomic positions, effects and interactions of significant QTL and their contribution to the genetic variance. With multiple traits and multiple environments involved in a QTL mapping experiment, pleiotropic effects and QTL by environment interactions can also be estimated. We review the method and discuss issues associated with multiple interval mapping, such as likelihood analysis, model selection, stopping rules and parameter estimation. The potential power and advantages of the method for mapping multiple QTL and estimating the genetic architecture are discussed. We also point out potential problems and difficulties in resolving the details of the genetic architecture as well as other areas that require further investigation. One application of the analysis is to improve genome-wide marker-assisted selection, particularly when the information about epistasis is used for selection with mating.

Algorithms↗
PubMed2006

Sexual reproduction reshapes the genetic architecture of digital organisms.

Modularity and epistasis, as well as other aspects of genetic architecture, have emerged as central themes in evolutionary biology. Theory suggests that modularity promotes evolvability, and that aggravating (synergistic) epistasis among deleterious mutations facilitates the evolution of sex. Here, by contrast, we investigate the evolution of different genetic architectures using digital organisms, which are computer programs that self-replicate, mutate, compete and evolve. Specifically, we investigate how genetic architecture is shaped by reproductive mode. We allowed 200 populations of digital organisms to evolve for over 10 000 generations while reproducing either asexually or sexually. For 10 randomly chosen organisms from each population, we constructed and analysed all possible single mutants as well as one million mutants at each mutational distance from 2 to 10. The genomes of sexual organisms were more modular than asexual ones; sites encoding different functional traits had less overlap and sites encoding a particular trait were more tightly clustered. Net directional epistasis was alleviating (antagonistic) in both groups, although the overall strength of this epistasis was weaker in sexual than in asexual organisms. Our results show that sexual reproduction profoundly influences the evolution of the genetic architecture.

Biological Evolution↗
PubMed2004

A general framework for analyzing the genetic architecture of developmental characteristics.

The genetic architecture of growth traits plays a central role in shaping the growth, development, and evolution of organisms. While a limited number of models have been devised to estimate genetic effects on complex phenotypes, no model has been available to examine how gene actions and interactions alter the ontogenetic development of an organism and transform the altered ontogeny into descendants. In this article, we present a novel statistical model for mapping quantitative trait loci (QTL) determining the developmental process of complex traits. Our model is constructed within the traditional maximum-likelihood framework implemented with the EM algorithm. We employ biologically meaningful growth curve equations to model time-specific expected genetic values and the AR(1) model to structure the residual variance-covariance matrix among different time points. Because of a reduced number of parameters being estimated and the incorporation of biological principles, the new model displays increased statistical power to detect QTL exerting an effect on the shape of ontogenetic growth and development. The model allows for the tests of a number of biological hypotheses regarding the role of epistasis in determining biological growth, form, and shape and for the resolution of developmental problems at the interface with evolution. Using our newly developed model, we have successfully detected significant additive x additive epistatic effects on stem height growth trajectories in a forest tree.

Algorithms↗
PubMed2006

The evolution of genetic architecture under frequency-dependent disruptive selection.

We propose a model to analyze a quantitative trait under frequency-dependent disruptive selection. Selection on the trait is a combination of stabilizing selection and intraspecific competition, where competition is maximal between individuals with equal phenotypes. In addition, there is a density-dependent component induced by population regulation. The trait is determined additively by a number of biallelic loci, which can have different effects on the trait value. In contrast to most previous models, we assume that the allelic effects at the loci can evolve due to epistatic interactions with the genetic background. Using a modifier approach, we derive analytical results under the assumption of weak selection and constant population size, and we investigate the full model by numerical simulations. We find that frequency-dependent disruptive selection favors the evolution of a highly asymmetric genetic architecture, where most of the genetic variation is concentrated on a small number of loci. We show that the evolution of genetic architecture can be understood in terms of the ecological niches created by competition. The phenotypic distribution of a population with an adapted genetic architecture closely matches this niche structure. Thus, evolution of the genetic architecture seems to be a plausible way for populations to adapt to regimes of frequency-dependent disruptive selection. As such, it should be seen as a potential evolutionary pathway to discrete polymorphisms and as a potential alternative to other evolutionary responses, such as the evolution of sexual dimorphism or assortative mating.

Alleles↗
PubMed2004

Allochronic differentiation among Daphnia species, hybrids and backcrosses: the importance of sexual reproduction for population dynamics and genetic architecture.

Seasonal dynamics of the abundance, sexual reproduction and genetic architecture in a Daphnia hyalina-galeata hybrid complex were studied in the large and deep Lake Constance. We found evidence for the occurrence of first and second order hybridization. Our study revealed strong differences between the parental species not only regarding their seasonal dynamics, genetic architecture and diversity, but also their sexual reproductive behaviour. The overwintering D. hyalina showed low genetic diversity, no genetic differentiation during the season, and reproduced sexually in autumn, whereas D. galeata reached higher levels of genetic diversity, reproduced sexually in early summer, and exhibited changes in genetic structure during the season, but was only present from spring to autumn. However, in both species sexual reproduction was a rare event, and daphnids, including hybrids, reproduced predominantly asexually. This allows long-term persistence of hybrids as well without continuing hybridization events. Within all variables studied, F1 and F2 hybrids showed an intermediate pattern, whereas proposed backcross hybrids were more similar to their respective parentals. These differences in phenotype as well as significant differences in pairwise Fst values between parentals suggest that gene flow seems to be relatively low in the Lake Constance hybrid system. We found evidence for unidirectional introgression by backcrossing from D. galeata to D. hyalina and found a decrease in at least one of the proposed introgressed alleles in the hyalina-backcross while the season progressed. Our findings suggest allochronic differentiation within this hybrid population and different microevolutionary trajectories of the parental species, which will be discussed in the light of the ongoing reoligotrophication process of Lake Constance.

Animals↗
PubMed1986

The genetic architecture of behavioural responses to novelty in mice.

The genetic architectures of 12 behavioural variables measured in adult male mice placed in a novel environment were analysed in a replicated 4 X 4 diallel cross. The results were combined with those obtained in a classical cross involving two of the four strains. Based on the hypothesis of an evolutionary history of stabilising selection for mouse exploratory behaviour, we expected additive genetic effects and ambidirectional dominance. Such genetic architectures were actually found for those exploratory behaviours where epistatic effects were of minor importance. Similar findings emerged for some non-exploratory phenotypes. All behaviours analysed appeared to be polygenically controlled.

Animals↗
PubMed2024

Multivariate genetic architecture reveals testosterone-driven sexual antagonism in contemporary humans.

Sex difference (SD) is ubiquitous in humans despite shared genetic architecture (SGA) between the sexes. A univariate approach, i.e., studying SD in single traits by estimating genetic correlation, does not provide a complete biological overview, because traits are not independent and are genetically correlated. The multivariate genetic architecture between the sexes can be summarized by estimating the additive genetic (co)variance across shared traits, which, apart from the cross-trait and cross-sex covariances, also includes the cross-sex-cross-trait covariances, e.g., between height in males and weight in females. Using such a multivariate approach, we investigated SD in the genetic architecture of 12 anthropometric, fat depositional, and sex-hormonal phenotypes. We uncovered sexual antagonism (SA) in the cross-sex-cross-trait covariances in humans, most prominently between testosterone and the anthropometric traits - a trend similar to phenotypic correlations. 27% of such cross-sex-cross-trait covariances were of opposite sign, contributing to asymmetry in the SGA. Intriguingly, using multivariate evolutionary simulations, we observed that the SGA acts as a genetic constraint to the evolution of SD in humans only when selection is sexually antagonistic and not concordant. Remarkably, we found that the lifetime reproductive success in both the sexes shows a positive genetic correlation with anthropometric traits, but not with testosterone. Moreover, we demonstrated that genetic variance is depleted along multivariate trait combinations in both the sexes but in different directions, suggesting absolute genetic constraint to evolution. Our results indicate that testosterone drives SA in contemporary humans and emphasize the necessity and significance of using a multivariate framework in studying SD.

Humans↗
PubMed2026

Pervasive context-dependent effects in the genetic architecture of complex and quantitative traits revealed by a powerful multiparent mapping population in yeast.

The genetic dissection of complex traits remains a major challenge in basic and biomedical research, but is essential for understanding the molecular pathways that shape phenotypic variation and for developing predictive models of trait and disease susceptibility. Here, we leverage a novel multiparent mapping population of budding yeast, CYClones, comprising 9,344 haploid strains derived from eight genetically diverse founders (~270,000 SNVs,&#x2009;~&#x2009;1 per 44 bp, capturing 56% of common variants and 32% of all variants with a minor allele frequency greater than 0.005 in the global population), to identify quantitative trait loci (QTL) and systematically investigate the genetic architecture of growth rates across ten environmental conditions. In total, we identified 349 QTL (ranging from 18 to 49 QTL per growth condition) that explained between 60% and 100% of narrow sense heritability across traits. The high power and resolution of CYClones revealed that growth traits exhibited distinct, condition-specific genetic architectures with extensive allelic heterogeneity, where a QTL was the result of multiple tightly linked causal variants. We also observed pleiotropy among QTL with complex, trait-dependent allele effects that are also consistent with allelic heterogeneity. Genetic complexity varied widely, with some traits showing nearly Mendelian architectures, while others were highly polygenic. Introgressed loci played a prominent role in the landscape of growth rate QTL, including a QTL localized to a 2.4 kb interval in the PCA1 cadmium transporter that explains 72% of variation in cadmium resistance and is largely driven by an introgression, and a non-additive interaction between the GAL3 regulator and introgressed GAL1/7/10 alleles, extending a previously described three-locus GAL-pathway incompatibility to a four-locus interaction. In both cadmium and galactose conditions, we show that allelic variation at a small number of loci stratifies the population into regulatory or physiological subgroups, each with distinct genetic architectures, a specific manifestation of epistasis we term allele-dependent stratification. Collectively, our results provide novel insights into the genetics of growth rates in budding yeast, the architectural features of genetic complexity, and demonstrate that CYClones is a powerful platform for revealing the molecular basis of complex trait variation.

Quantitative Trait Loci↗
PubMed2006

Genetic architecture of smoking behavior: a study of Finnish adult twins.

Both genetic and environmental factors affect smoking initiation and maintenance, but less is known about the genetic architecture of various other smoking-related behaviors. The aim of this study is to examine the genetic architecture of smoking behavior in a large twin cohort. Questionnaires with an extensive smoking history section were mailed to same-sex adult twins of the Finnish twin cohort. The final study population included 2923 monozygotic and 6018 dizygotic twin pairs aged 24 to 88 years. Two-stage bivariate genetic modeling of age at initiation with amount smoked (less than 20 cigarettes per day vs. 20 or more) and age at initiation with smoking cessation was done by using the Mx statistical package. For men the heritability estimate for age at initiation was .59 (95% confidence interval [CI] .49-.69), for amount smoked .54 (95% CI .45-.62) and for smoking cessation .58 (95% CI .50-.65). For women the heritability estimates were .36 (95% CI .28-.43), .61 (95% CI .46-.70) and .50 (95% CI .39-.60), respectively. The genetic correlations between age at initiation and amount smoked or smoking cessation were at most .22 in magnitude, indicating that genetic influences in age at initiation accounted for at most about 4% of the genetic factors in amount smoked or in cessation. Genetic factors are important in amount smoked and smoking cessation and they are largely independent of genetic influences on age at initiation. This has implications for defining phenotypes in searches for genes underlying smoking behaviors.

Age Factors↗