Sample records for multiple genetic interactions
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Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.
Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao
2016-04-01
To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.
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ERIC Educational Resources Information Center
Vendlinski, Matthew K.; Lemery-Chalfant, Kathryn; Essex, Marilyn J.; Goldsmith, H. Hill
2011-01-01
Background: Identifying how genetic risk interacts with experience to predict psychopathology is an important step toward understanding the etiology of mental health problems. Few studies have examined genetic risk by experience interaction (GxE) in the development of childhood psychopathology. Methods: We used both co-twin and parent mental…
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Etiology in psychiatry: embracing the reality of poly‐gene‐environmental causation of mental illness
Uher, Rudolf; Zwicker, Alyson
2017-01-01
Intriguing findings on genetic and environmental causation suggest a need to reframe the etiology of mental disorders. Molecular genetics shows that thousands of common and rare genetic variants contribute to mental illness. Epidemiological studies have identified dozens of environmental exposures that are associated with psychopathology. The effect of environment is likely conditional on genetic factors, resulting in gene‐environment interactions. The impact of environmental factors also depends on previous exposures, resulting in environment‐environment interactions. Most known genetic and environmental factors are shared across multiple mental disorders. Schizophrenia, bipolar disorder and major depressive disorder, in particular, are closely causally linked. Synthesis of findings from twin studies, molecular genetics and epidemiological research suggests that joint consideration of multiple genetic and environmental factors has much greater explanatory power than separate studies of genetic or environmental causation. Multi‐factorial gene‐environment interactions are likely to be a generic mechanism involved in the majority of cases of mental illness, which is only partially tapped by existing gene‐environment studies. Future research may cut across psychiatric disorders and address poly‐causation by considering multiple genetic and environmental measures across the life course with a specific focus on the first two decades of life. Integrative analyses of poly‐causation including gene‐environment and environment‐environment interactions can realize the potential for discovering causal types and mechanisms that are likely to generate new preventive and therapeutic tools. PMID:28498595
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Lekman, Magnus; Hössjer, Ola; Andrews, Peter; Källberg, Henrik; Uvehag, Daniel; Charney, Dennis; Manji, Husseini; Rush, John A; McMahon, Francis J; Moore, Jason H; Kockum, Ingrid
2014-01-01
Genetic contributions to major depressive disorder (MDD) are thought to result from multiple genes interacting with each other. Different procedures have been proposed to detect such interactions. Which approach is best for explaining the risk of developing disease is unclear. This study sought to elucidate the genetic interaction landscape in candidate genes for MDD by conducting a SNP-SNP interaction analysis using an exhaustive search through 3,704 SNP-markers in 1,732 cases and 1,783 controls provided from the GAIN MDD study. We used three different methods to detect interactions, two logistic regressions models (multiplicative and additive) and one data mining and machine learning (MDR) approach. Although none of the interaction survived correction for multiple comparisons, the results provide important information for future genetic interaction studies in complex disorders. Among the 0.5% most significant observations, none had been reported previously for risk to MDD. Within this group of interactions, less than 0.03% would have been detectable based on main effect approach or an a priori algorithm. We evaluated correlations among the three different models and conclude that all three algorithms detected the same interactions to a low degree. Although the top interactions had a surprisingly large effect size for MDD (e.g. additive dominant model Puncorrected = 9.10E-9 with attributable proportion (AP) value = 0.58 and multiplicative recessive model with Puncorrected = 6.95E-5 with odds ratio (OR estimated from β3) value = 4.99) the area under the curve (AUC) estimates were low (< 0.54). Moreover, the population attributable fraction (PAF) estimates were also low (< 0.15). We conclude that the top interactions on their own did not explain much of the genetic variance of MDD. The different statistical interaction methods we used in the present study did not identify the same pairs of interacting markers. Genetic interaction studies may uncover previously unsuspected effects that could provide novel insights into MDD risk, but much larger sample sizes are needed before this strategy can be powerfully applied.
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Chikkagoudar, Satish; Wang, Kai; Li, Mingyao
2011-05-26
Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs) have multiple cores, whereas Graphics Processing Units (GPUs) also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic interaction analysis for binary traits. Here we present a novel software package GENIE, which utilizes the power of multiple GPU or CPU processor cores to parallelize the interaction analysis. GENIE reads an entire genetic association study dataset into memory and partitions the dataset into fragments with non-overlapping sets of SNPs. For each fragment, GENIE analyzes: 1) the interaction of SNPs within it in parallel, and 2) the interaction between the SNPs of the current fragment and other fragments in parallel. We tested GENIE on a large-scale candidate gene study on high-density lipoprotein cholesterol. Using an NVIDIA Tesla C1060 graphics card, the GPU mode of GENIE achieves a speedup of 27 times over its single-core CPU mode run. GENIE is open-source, economical, user-friendly, and scalable. Since the computing power and memory capacity of graphics cards are increasing rapidly while their cost is going down, we anticipate that GENIE will achieve greater speedups with faster GPU cards. Documentation, source code, and precompiled binaries can be downloaded from http://www.cceb.upenn.edu/~mli/software/GENIE/.
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2011-01-01
Background Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs) have multiple cores, whereas Graphics Processing Units (GPUs) also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic interaction analysis for binary traits. Findings Here we present a novel software package GENIE, which utilizes the power of multiple GPU or CPU processor cores to parallelize the interaction analysis. GENIE reads an entire genetic association study dataset into memory and partitions the dataset into fragments with non-overlapping sets of SNPs. For each fragment, GENIE analyzes: 1) the interaction of SNPs within it in parallel, and 2) the interaction between the SNPs of the current fragment and other fragments in parallel. We tested GENIE on a large-scale candidate gene study on high-density lipoprotein cholesterol. Using an NVIDIA Tesla C1060 graphics card, the GPU mode of GENIE achieves a speedup of 27 times over its single-core CPU mode run. Conclusions GENIE is open-source, economical, user-friendly, and scalable. Since the computing power and memory capacity of graphics cards are increasing rapidly while their cost is going down, we anticipate that GENIE will achieve greater speedups with faster GPU cards. Documentation, source code, and precompiled binaries can be downloaded from http://www.cceb.upenn.edu/~mli/software/GENIE/. PMID:21615923
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Incorporating gene-environment interaction in testing for association with rare genetic variants.
Chen, Han; Meigs, James B; Dupuis, Josée
2014-01-01
The incorporation of gene-environment interactions could improve the ability to detect genetic associations with complex traits. For common genetic variants, single-marker interaction tests and joint tests of genetic main effects and gene-environment interaction have been well-established and used to identify novel association loci for complex diseases and continuous traits. For rare genetic variants, however, single-marker tests are severely underpowered due to the low minor allele frequency, and only a few gene-environment interaction tests have been developed. We aimed at developing powerful and computationally efficient tests for gene-environment interaction with rare variants. In this paper, we propose interaction and joint tests for testing gene-environment interaction of rare genetic variants. Our approach is a generalization of existing gene-environment interaction tests for multiple genetic variants under certain conditions. We show in our simulation studies that our interaction and joint tests have correct type I errors, and that the joint test is a powerful approach for testing genetic association, allowing for gene-environment interaction. We also illustrate our approach in a real data example from the Framingham Heart Study. Our approach can be applied to both binary and continuous traits, it is powerful and computationally efficient.
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A Novel Test for Gene-Ancestry Interactions in Genome-Wide Association Data
Dunlop, Malcolm G.; Houlston, Richard S.; Tomlinson, Ian P.; Holmes, Chris C.
2012-01-01
Genome-wide association study (GWAS) data on a disease are increasingly available from multiple related populations. In this scenario, meta-analyses can improve power to detect homogeneous genetic associations, but if there exist ancestry-specific effects, via interactions on genetic background or with a causal effect that co-varies with genetic background, then these will typically be obscured. To address this issue, we have developed a robust statistical method for detecting susceptibility gene-ancestry interactions in multi-cohort GWAS based on closely-related populations. We use the leading principal components of the empirical genotype matrix to cluster individuals into “ancestry groups” and then look for evidence of heterogeneous genetic associations with disease or other trait across these clusters. Robustness is improved when there are multiple cohorts, as the signal from true gene-ancestry interactions can then be distinguished from gene-collection artefacts by comparing the observed interaction effect sizes in collection groups relative to ancestry groups. When applied to colorectal cancer, we identified a missense polymorphism in iron-absorption gene CYBRD1 that associated with disease in individuals of English, but not Scottish, ancestry. The association replicated in two additional, independently-collected data sets. Our method can be used to detect associations between genetic variants and disease that have been obscured by population genetic heterogeneity. It can be readily extended to the identification of genetic interactions on other covariates such as measured environmental exposures. We envisage our methodology being of particular interest to researchers with existing GWAS data, as ancestry groups can be easily defined and thus tested for interactions. PMID:23236349
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Genome complexity, robustness and genetic interactions in digital organisms
NASA Astrophysics Data System (ADS)
Lenski, Richard E.; Ofria, Charles; Collier, Travis C.; Adami, Christoph
1999-08-01
Digital organisms are computer programs that self-replicate, mutate and adapt by natural selection. They offer an opportunity to test generalizations about living systems that may extend beyond the organic life that biologists usually study. Here we have generated two classes of digital organism: simple programs selected solely for rapid replication, and complex programs selected to perform mathematical operations that accelerate replication through a set of defined `metabolic' rewards. To examine the differences in their genetic architecture, we introduced millions of single and multiple mutations into each organism and measured the effects on the organism's fitness. The complex organisms are more robust than the simple ones with respect to the average effects of single mutations. Interactions among mutations are common and usually yield higher fitness than predicted from the component mutations assuming multiplicative effects; such interactions are especially important in the complex organisms. Frequent interactions among mutations have also been seen in bacteria, fungi and fruitflies. Our findings support the view that interactions are a general feature of genetic systems.
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Genome complexity, robustness and genetic interactions in digital organisms.
Lenski, R E; Ofria, C; Collier, T C; Adami, C
1999-08-12
Digital organisms are computer programs that self-replicate, mutate and adapt by natural selection. They offer an opportunity to test generalizations about living systems that may extend beyond the organic life that biologists usually study. Here we have generated two classes of digital organism: simple programs selected solely for rapid replication, and complex programs selected to perform mathematical operations that accelerate replication through a set of defined 'metabolic' rewards. To examine the differences in their genetic architecture, we introduced millions of single and multiple mutations into each organism and measured the effects on the organism's fitness. The complex organisms are more robust than the simple ones with respect to the average effects of single mutations. Interactions among mutations are common and usually yield higher fitness than predicted from the component mutations assuming multiplicative effects; such interactions are especially important in the complex organisms. Frequent interactions among mutations have also been seen in bacteria, fungi and fruitflies. Our findings support the view that interactions are a general feature of genetic systems.
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Host–parasite genotypic interactions in the honey bee: the dynamics of diversity
Evison, Sophie E F; Fazio, Geraldine; Chappell, Paula; Foley, Kirsten; Jensen, Annette B; Hughes, William O H
2013-01-01
Parasites are thought to be a major driving force shaping genetic variation in their host, and are suggested to be a significant reason for the maintenance of sexual reproduction. A leading hypothesis for the occurrence of multiple mating (polyandry) in social insects is that the genetic diversity generated within-colonies through this behavior promotes disease resistance. This benefit is likely to be particularly significant when colonies are exposed to multiple species and strains of parasites, but host–parasite genotypic interactions in social insects are little known. We investigated this using honey bees, which are naturally polyandrous and consequently produce genetically diverse colonies containing multiple genotypes (patrilines), and which are also known to host multiple strains of various parasite species. We found that host genotypes differed significantly in their resistance to different strains of the obligate fungal parasite that causes chalkbrood disease, while genotypic variation in resistance to the facultative fungal parasite that causes stonebrood disease was less pronounced. Our results show that genetic variation in disease resistance depends in part on the parasite genotype, as well as species, with the latter most likely relating to differences in parasite life history and host–parasite coevolution. Our results suggest that the selection pressure from genetically diverse parasites might be an important driving force in the evolution of polyandry, a mechanism that generates significant genetic diversity in social insects. PMID:23919163
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Host-parasite genotypic interactions in the honey bee: the dynamics of diversity.
Evison, Sophie E F; Fazio, Geraldine; Chappell, Paula; Foley, Kirsten; Jensen, Annette B; Hughes, William O H
2013-07-01
Parasites are thought to be a major driving force shaping genetic variation in their host, and are suggested to be a significant reason for the maintenance of sexual reproduction. A leading hypothesis for the occurrence of multiple mating (polyandry) in social insects is that the genetic diversity generated within-colonies through this behavior promotes disease resistance. This benefit is likely to be particularly significant when colonies are exposed to multiple species and strains of parasites, but host-parasite genotypic interactions in social insects are little known. We investigated this using honey bees, which are naturally polyandrous and consequently produce genetically diverse colonies containing multiple genotypes (patrilines), and which are also known to host multiple strains of various parasite species. We found that host genotypes differed significantly in their resistance to different strains of the obligate fungal parasite that causes chalkbrood disease, while genotypic variation in resistance to the facultative fungal parasite that causes stonebrood disease was less pronounced. Our results show that genetic variation in disease resistance depends in part on the parasite genotype, as well as species, with the latter most likely relating to differences in parasite life history and host-parasite coevolution. Our results suggest that the selection pressure from genetically diverse parasites might be an important driving force in the evolution of polyandry, a mechanism that generates significant genetic diversity in social insects.
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Wu, Yubao; Zhu, Xiaofeng; Chen, Jian; Zhang, Xiang
2013-11-01
Epistasis (gene-gene interaction) detection in large-scale genetic association studies has recently drawn extensive research interests as many complex traits are likely caused by the joint effect of multiple genetic factors. The large number of possible interactions poses both statistical and computational challenges. A variety of approaches have been developed to address the analytical challenges in epistatic interaction detection. These methods usually output the identified genetic interactions and store them in flat file formats. It is highly desirable to develop an effective visualization tool to further investigate the detected interactions and unravel hidden interaction patterns. We have developed EINVis, a novel visualization tool that is specifically designed to analyze and explore genetic interactions. EINVis displays interactions among genetic markers as a network. It utilizes a circular layout (specially, a tree ring view) to simultaneously visualize the hierarchical interactions between single nucleotide polymorphisms (SNPs), genes, and chromosomes, and the network structure formed by these interactions. Using EINVis, the user can distinguish marginal effects from interactions, track interactions involving more than two markers, visualize interactions at different levels, and detect proxy SNPs based on linkage disequilibrium. EINVis is an effective and user-friendly free visualization tool for analyzing and exploring genetic interactions. It is publicly available with detailed documentation and online tutorial on the web at http://filer.case.edu/yxw407/einvis/. © 2013 WILEY PERIODICALS, INC.
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USDA-ARS?s Scientific Manuscript database
Plant ash content is related to water use efficiency (WUE) (dry matter accumulation per unit of transpiration) and Delta 13C in a range of C3 species. In breeding programs, the genetic x environment interaction is measured with multiple locations and multiple years of evaluation but the genetic x e...
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Pathway-based discovery of genetic interactions in breast cancer
Xu, Zack Z.; Boone, Charles; Lange, Carol A.
2017-01-01
Breast cancer is the second largest cause of cancer death among U.S. women and the leading cause of cancer death among women worldwide. Genome-wide association studies (GWAS) have identified several genetic variants associated with susceptibility to breast cancer, but these still explain less than half of the estimated genetic contribution to the disease. Combinations of variants (i.e. genetic interactions) may play an important role in breast cancer susceptibility. However, due to a lack of statistical power, the current tests for genetic interactions from GWAS data mainly leverage prior knowledge to focus on small sets of genes or SNPs that are known to have an association with breast cancer. Thus, many genetic interactions, particularly among novel variants, remain understudied. Reverse-genetic interaction screens in model organisms have shown that genetic interactions frequently cluster into highly structured motifs, where members of the same pathway share similar patterns of genetic interactions. Based on this key observation, we recently developed a method called BridGE to search for such structured motifs in genetic networks derived from GWAS studies and identify pathway-level genetic interactions in human populations. We applied BridGE to six independent breast cancer cohorts and identified significant pathway-level interactions in five cohorts. Joint analysis across all five cohorts revealed a high confidence consensus set of genetic interactions with support in multiple cohorts. The discovered interactions implicated the glutathione conjugation, vitamin D receptor, purine metabolism, mitotic prometaphase, and steroid hormone biosynthesis pathways as major modifiers of breast cancer risk. Notably, while many of the pathways identified by BridGE show clear relevance to breast cancer, variants in these pathways had not been previously discovered by traditional single variant association tests, or single pathway enrichment analysis that does not consider SNP-SNP interactions. PMID:28957314
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Taylor, Mark A; Cooper, Martha D; Sellamuthu, Reena; Braun, Peter; Migneault, Andrew; Browning, Alyssa; Perry, Emily; Schmitt, Johanna
2017-10-01
Major alleles for seed dormancy and flowering time are well studied, and can interact to influence seasonal timing and fitness within generations. However, little is known about how this interaction controls phenology, life history, and population fitness across multiple generations in natural seasonal environments. To examine how seed dormancy and flowering time shape annual plant life cycles over multiple generations, we established naturally dispersing populations of recombinant inbred lines of Arabidopsis thaliana segregating early and late alleles for seed dormancy and flowering time in a field experiment. We recorded seasonal phenology and fitness of each genotype over 2 yr and several generations. Strong seed dormancy suppressed mid-summer germination in both early- and late-flowering genetic backgrounds. Strong dormancy and late-flowering genotypes were both necessary to confer a winter annual life history; other genotypes were rapid-cycling. Strong dormancy increased within-season fecundity in an early-flowering background, but decreased it in a late-flowering background. However, there were no detectable differences among genotypes in population growth rates. Seasonal phenology, life history, and cohort fitness over multiple generations depend strongly upon interacting genetic variation for dormancy and flowering. However, similar population growth rates across generations suggest that different life cycle genotypes can coexist in natural populations. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.
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USDA-ARS?s Scientific Manuscript database
Papayas are sweet, flavorful tropical fruit, rich in vitamin C and carotenoids. Multiple interactions among preharvest environmental conditions, genetics, and physiology determine papaya nutritional composition at harvest. Selecting a cultivar with the genetic potential for high nutrient content and...
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A perspective on interaction effects in genetic association studies
2016-01-01
ABSTRACT The identification of gene–gene and gene–environment interaction in human traits and diseases is an active area of research that generates high expectation, and most often lead to high disappointment. This is partly explained by a misunderstanding of the inherent characteristics of standard regression‐based interaction analyses. Here, I revisit and untangle major theoretical aspects of interaction tests in the special case of linear regression; in particular, I discuss variables coding scheme, interpretation of effect estimate, statistical power, and estimation of variance explained in regard of various hypothetical interaction patterns. Linking this components it appears first that the simplest biological interaction models—in which the magnitude of a genetic effect depends on a common exposure—are among the most difficult to identify. Second, I highlight the demerit of the current strategy to evaluate the contribution of interaction effects to the variance of quantitative outcomes and argue for the use of new approaches to overcome this issue. Finally, I explore the advantages and limitations of multivariate interaction models, when testing for interaction between multiple SNPs and/or multiple exposures, over univariate approaches. Together, these new insights can be leveraged for future method development and to improve our understanding of the genetic architecture of multifactorial traits. PMID:27390122
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ViSEN: methodology and software for visualization of statistical epistasis networks
Hu, Ting; Chen, Yuanzhu; Kiralis, Jeff W.; Moore, Jason H.
2013-01-01
The non-linear interaction effect among multiple genetic factors, i.e. epistasis, has been recognized as a key component in understanding the underlying genetic basis of complex human diseases and phenotypic traits. Due to the statistical and computational complexity, most epistasis studies are limited to interactions with an order of two. We developed ViSEN to analyze and visualize epistatic interactions of both two-way and three-way. ViSEN not only identifies strong interactions among pairs or trios of genetic attributes, but also provides a global interaction map that shows neighborhood and clustering structures. This visualized information could be very helpful to infer the underlying genetic architecture of complex diseases and to generate plausible hypotheses for further biological validations. ViSEN is implemented in Java and freely available at https://sourceforge.net/projects/visen/. PMID:23468157
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HU, TING; DARABOS, CHRISTIAN; CRICCO, MARIA E.; KONG, EMILY; MOORE, JASON H.
2014-01-01
The large volume of GWAS data poses great computational challenges for analyzing genetic interactions associated with common human diseases. We propose a computational framework for characterizing epistatic interactions among large sets of genetic attributes in GWAS data. We build the human phenotype network (HPN) and focus around a disease of interest. In this study, we use the GLAUGEN glaucoma GWAS dataset and apply the HPN as a biological knowledge-based filter to prioritize genetic variants. Then, we use the statistical epistasis network (SEN) to identify a significant connected network of pairwise epistatic interactions among the prioritized SNPs. These clearly highlight the complex genetic basis of glaucoma. Furthermore, we identify key SNPs by quantifying structural network characteristics. Through functional annotation of these key SNPs using Biofilter, a software accessing multiple publicly available human genetic data sources, we find supporting biomedical evidences linking glaucoma to an array of genetic diseases, proving our concept. We conclude by suggesting hypotheses for a better understanding of the disease. PMID:25592582
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USDA-ARS?s Scientific Manuscript database
Combining multiple genetic variants related to obesity into a genetic risk score (GRS) might improve identification of individuals at risk of developing obesity. Moreover, characterizing gene-diet interactions is a research challenge to establish dietary recommendations to individuals with higher pr...
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Abdullah, N; Abdul Murad, N A; Mohd Haniff, E A; Syafruddin, S E; Attia, J; Oldmeadow, C; Kamaruddin, M A; Abd Jalal, N; Ismail, N; Ishak, M; Jamal, R; Scott, R J; Holliday, E G
2017-08-01
Malaysia has a high and rising prevalence of type 2 diabetes (T2D). While environmental (non-genetic) risk factors for the disease are well established, the role of genetic variations and gene-environment interactions remain understudied in this population. This study aimed to estimate the relative contributions of environmental and genetic risk factors to T2D in Malaysia and also to assess evidence for gene-environment interactions that may explain additional risk variation. This was a case-control study including 1604 Malays, 1654 Chinese and 1728 Indians from the Malaysian Cohort Project. The proportion of T2D risk variance explained by known genetic and environmental factors was assessed by fitting multivariable logistic regression models and evaluating McFadden's pseudo R 2 and the area under the receiver-operating characteristic curve (AUC). Models with and without the genetic risk score (GRS) were compared using the log likelihood ratio Chi-squared test and AUCs. Multiplicative interaction between genetic and environmental risk factors was assessed via logistic regression within and across ancestral groups. Interactions were assessed for the GRS and its 62 constituent variants. The models including environmental risk factors only had pseudo R 2 values of 16.5-28.3% and AUC of 0.75-0.83. Incorporating a genetic score aggregating 62 T2D-associated risk variants significantly increased the model fit (likelihood ratio P-value of 2.50 × 10 -4 -4.83 × 10 -12 ) and increased the pseudo R 2 by about 1-2% and AUC by 1-3%. None of the gene-environment interactions reached significance after multiple testing adjustment, either for the GRS or individual variants. For individual variants, 33 out of 310 tested associations showed nominal statistical significance with 0.001 < P < 0.05. This study suggests that known genetic risk variants contribute a significant but small amount to overall T2D risk variation in Malaysian population groups. If gene-environment interactions involving common genetic variants exist, they are likely of small effect, requiring substantially larger samples for detection. Copyright © 2017 The Royal Society for Public Health. All rights reserved.
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J. G. Isebrands; G. E. Host; K. Lenz; G. Wu; H. W. Stech
2000-01-01
Process models are powerful research tools for assessing the effects of multiple environmental stresses on forest plantations. These models are driven by interacting environmental variables and often include genetic factors necessary for assessing forest plantation growth over a range of different site, climate, and silvicultural conditions. However, process models are...
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Kim, Jihye; Kraft, Peter; Hagan, Kaitlin A; Harrington, Laura B; Lindstroem, Sara; Kabrhel, Christopher
2018-06-01
Venous thromboembolism (VTE) is highly heritable. Physical activity, physical inactivity and body mass index (BMI) are also risk factors, but evidence of interaction between genetic and environmental risk factors is limited. Data on 2,134 VTE cases and 3,890 matched controls were obtained from the Nurses' Health Study (NHS), Nurses' Health Study II (NHS II), and Health Professionals Follow-up Study (HPFS). We calculated a weighted genetic risk score (wGRS) using 16 single nucleotide polymorphisms associated with VTE risk in published genome-wide association studies (GWAS). Data on three risk factors, physical activity (metabolic equivalent [MET] hours per week), physical inactivity (sitting hours per week) and BMI, were obtained from biennial questionnaires. VTE cases were incident since cohort inception; controls were matched to cases on age, cohort, and genotype array. Using conditional logistic regression, we assessed joint effects and interaction effects on both additive and multiplicative scales. We also ran models using continuous wGRS stratified by risk-factor categories. We observed a supra-additive interaction between wGRS and BMI. Having both high wGRS and high BMI was associated with a 3.4-fold greater risk of VTE (relative excess risk due to interaction = 0.69, p = 0.046). However, we did not find evidence for a multiplicative interaction with BMI. No interactions were observed for physical activity or inactivity. We found a synergetic effect between a genetic risk score and high BMI on the risk of VTE. Intervention efforts lowering BMI to decrease VTE risk may have particularly large beneficial effects among individuals with high genetic risk. © 2018 WILEY PERIODICALS, INC.
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Gene-Environment Interactions in Cardiovascular Disease
Flowers, Elena; Froelicher, Erika Sivarajan; Aouizerat, Bradley E.
2011-01-01
Background Historically, models to describe disease were exclusively nature-based or nurture-based. Current theoretical models for complex conditions such as cardiovascular disease acknowledge the importance of both biologic and non-biologic contributors to disease. A critical feature is the occurrence of interactions between numerous risk factors for disease. The interaction between genetic (i.e. biologic, nature) and environmental (i.e. non-biologic, nurture) causes of disease is an important mechanism for understanding both the etiology and public health impact of cardiovascular disease. Objectives The purpose of this paper is to describe theoretical underpinnings of gene-environment interactions, models of interaction, methods for studying gene-environment interactions, and the related concept of interactions between epigenetic mechanisms and the environment. Discussion Advances in methods for measurement of genetic predictors of disease have enabled an increasingly comprehensive understanding of the causes of disease. In order to fully describe the effects of genetic predictors of disease, it is necessary to place genetic predictors within the context of known environmental risk factors. The additive or multiplicative effect of the interaction between genetic and environmental risk factors is often greater than the contribution of either risk factor alone. PMID:21684212
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Haslam, Danielle E.; McKeown, Nicola M.; Herman, Mark A.; Lichtenstein, Alice H.; Dashti, Hassan S.
2018-01-01
The consumption of sugar-sweetened beverages (SSB), which includes soft drinks, fruit drinks, and other energy drinks, is associated with excess energy intake and increased risk for chronic metabolic disease among children and adults. Thus, reducing SSB consumption is an important strategy to prevent the onset of chronic diseases, and achieve and maintain a healthy body weight. The mechanisms by which excessive SSB consumption may contribute to complex chronic diseases may partially depend on an individual’s genetic predisposition. Gene–SSB interaction investigations, either limited to single genetic loci or including multiple genetic variants, aim to use genomic information to define mechanistic pathways linking added sugar consumption from SSBs to those complex diseases. The purpose of this review is to summarize the available gene-SSB interaction studies investigating the relationships between genetics, SSB consumption, and various health outcomes. Current evidence suggests there are genetic predispositions for an association between SSB intake and adiposity; evidence for a genetic predisposition between SSB and type 2 diabetes or cardiovascular disease is limited. PMID:29375475
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Gene–environment interaction in tobacco-related cancers
Taioli, Emanuela
2008-01-01
This review summarizes the carcinogenic effects of tobacco smoke and the basis for interaction between tobacco smoke and genetic factors. Examples of published papers on gene–tobacco interaction and cancer risk are presented. The assessment of gene–environment interaction in tobacco-related cancers has been more complex than originally expected for several reasons, including the multiplicity of genes involved in tobacco metabolism, the numerous substrates metabolized by the relevant genes and the interaction of smoking with other metabolic pathways. Future studies on gene–environment interaction and cancer risk should include biomarkers of smoking dose, along with markers of quantitative historical exposure to tobacco. Epigenetic studies should be added to classic genetic analyses, in order to better understand gene–environmental interaction and individual susceptibility. Other metabolic pathways in competition with tobacco genetic metabolism/repair should be incorporated in epidemiological studies to generate a more complete picture of individual cancer risk associated with environmental exposure to carcinogens. PMID:18550573
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Hadley, Dexter; Wu, Zhi-liang; Kao, Charlly; Kini, Akshata; Mohamed-Hadley, Alisha; Thomas, Kelly; Vazquez, Lyam; Qiu, Haijun; Mentch, Frank; Pellegrino, Renata; Kim, Cecilia; Connolly, John; Pinto, Dalila; Merikangas, Alison; Klei, Lambertus; Vorstman, Jacob A.S.; Thompson, Ann; Regan, Regina; Pagnamenta, Alistair T.; Oliveira, Bárbara; Magalhaes, Tiago R.; Gilbert, John; Duketis, Eftichia; De Jonge, Maretha V.; Cuccaro, Michael; Correia, Catarina T.; Conroy, Judith; Conceição, Inês C.; Chiocchetti, Andreas G.; Casey, Jillian P.; Bolshakova, Nadia; Bacchelli, Elena; Anney, Richard; Zwaigenbaum, Lonnie; Wittemeyer, Kerstin; Wallace, Simon; Engeland, Herman van; Soorya, Latha; Rogé, Bernadette; Roberts, Wendy; Poustka, Fritz; Mouga, Susana; Minshew, Nancy; McGrew, Susan G.; Lord, Catherine; Leboyer, Marion; Le Couteur, Ann S.; Kolevzon, Alexander; Jacob, Suma; Guter, Stephen; Green, Jonathan; Green, Andrew; Gillberg, Christopher; Fernandez, Bridget A.; Duque, Frederico; Delorme, Richard; Dawson, Geraldine; Café, Cátia; Brennan, Sean; Bourgeron, Thomas; Bolton, Patrick F.; Bölte, Sven; Bernier, Raphael; Baird, Gillian; Bailey, Anthony J.; Anagnostou, Evdokia; Almeida, Joana; Wijsman, Ellen M.; Vieland, Veronica J.; Vicente, Astrid M.; Schellenberg, Gerard D.; Pericak-Vance, Margaret; Paterson, Andrew D.; Parr, Jeremy R.; Oliveira, Guiomar; Almeida, Joana; Café, Cátia; Mouga, Susana; Correia, Catarina; Nurnberger, John I.; Monaco, Anthony P.; Maestrini, Elena; Klauck, Sabine M.; Hakonarson, Hakon; Haines, Jonathan L.; Geschwind, Daniel H.; Freitag, Christine M.; Folstein, Susan E.; Ennis, Sean; Coon, Hilary; Battaglia, Agatino; Szatmari, Peter; Sutcliffe, James S.; Hallmayer, Joachim; Gill, Michael; Cook, Edwin H.; Buxbaum, Joseph D.; Devlin, Bernie; Gallagher, Louise; Betancur, Catalina; Scherer, Stephen W.; Glessner, Joseph; Hakonarson, Hakon
2014-01-01
Although multiple reports show that defective genetic networks underlie the aetiology of autism, few have translated into pharmacotherapeutic opportunities. Since drugs compete with endogenous small molecules for protein binding, many successful drugs target large gene families with multiple drug binding sites. Here we search for defective gene family interaction networks (GFINs) in 6,742 patients with the ASDs relative to 12,544 neurologically normal controls, to find potentially druggable genetic targets. We find significant enrichment of structural defects (P≤2.40E−09, 1.8-fold enrichment) in the metabotropic glutamate receptor (GRM) GFIN, previously observed to impact attention deficit hyperactivity disorder (ADHD) and schizophrenia. Also, the MXD-MYC-MAX network of genes, previously implicated in cancer, is significantly enriched (P≤3.83E−23, 2.5-fold enrichment), as is the calmodulin 1 (CALM1) gene interaction network (P≤4.16E−04, 14.4-fold enrichment), which regulates voltage-independent calcium-activated action potentials at the neuronal synapse. We find that multiple defective gene family interactions underlie autism, presenting new translational opportunities to explore for therapeutic interventions. PMID:24927284
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Smith, Jennifer A; Zhao, Wei; Yasutake, Kalyn; August, Carmella; Ratliff, Scott M; Faul, Jessica D; Boerwinkle, Eric; Chakravarti, Aravinda; Diez Roux, Ana V; Gao, Yan; Griswold, Michael E; Heiss, Gerardo; Kardia, Sharon L R; Morrison, Alanna C; Musani, Solomon K; Mwasongwe, Stanford; North, Kari E; Rose, Kathryn M; Sims, Mario; Sun, Yan V; Weir, David R; Needham, Belinda L
2017-12-18
Inter-individual variability in blood pressure (BP) is influenced by both genetic and non-genetic factors including socioeconomic and psychosocial stressors. A deeper understanding of the gene-by-socioeconomic/psychosocial factor interactions on BP may help to identify individuals that are genetically susceptible to high BP in specific social contexts. In this study, we used a genomic region-based method for longitudinal analysis, Longitudinal Gene-Environment-Wide Interaction Studies (LGEWIS), to evaluate the effects of interactions between known socioeconomic/psychosocial and genetic risk factors on systolic and diastolic BP in four large epidemiologic cohorts of European and/or African ancestry. After correction for multiple testing, two interactions were significantly associated with diastolic BP. In European ancestry participants, outward/trait anger score had a significant interaction with the C10orf107 genomic region ( p = 0.0019). In African ancestry participants, depressive symptom score had a significant interaction with the HFE genomic region ( p = 0.0048). This study provides a foundation for using genomic region-based longitudinal analysis to identify subgroups of the population that may be at greater risk of elevated BP due to the combined influence of genetic and socioeconomic/psychosocial risk factors.
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Werren, John H.; Cohen, Lorna B.; Gadau, Juergen; Ponce, Rita; Baudry, Emmanuelle; Lynch, Jeremy A.
2016-01-01
The animal head is a complex structure where numerous sensory, structural and alimentary structures are concentrated and integrated, and its ontogeny requires precise and delicate interactions among genes, cells, and tissues. Thus, it is perhaps unsurprising that craniofacial abnormalities are among the most common birth defects in people, or that these defects have a complex genetic basis involving interactions among multiple loci. Developmental processes that depend on such epistatic interactions become exponentially more difficult to study in diploid organisms as the number of genes involved increases. Here, we present hybrid haploid males of the wasp species pair Nasonia vitripennis and Nasonia giraulti, which have distinct male head morphologies, as a genetic model of craniofacial development that possesses the genetic advantages of haploidy, along with many powerful genomic tools. Viable, fertile hybrids can be made between the species, and quantitative trail loci related to shape differences have been identified. In addition, a subset of hybrid males show head abnormalities, including clefting at the midline and asymmetries. Crucially, epistatic interactions among multiple loci underlie several developmental differences and defects observed in the F2 hybrid males. Furthermore, we demonstrate an introgression of a chromosomal region from N. giraulti into N. vitripennis that shows an abnormality in relative eye size, which maps to a region containing a major QTL for this trait. Therefore, the genetic sources of head morphology can, in principle, be identified by positional cloning. Thus, Nasonia is well positioned to be a uniquely powerful model invertebrate system with which to probe both development and complex genetics of craniofacial patterning and defects. PMID:26721604
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The BioGRID Interaction Database: 2011 update
Stark, Chris; Breitkreutz, Bobby-Joe; Chatr-aryamontri, Andrew; Boucher, Lorrie; Oughtred, Rose; Livstone, Michael S.; Nixon, Julie; Van Auken, Kimberly; Wang, Xiaodong; Shi, Xiaoqi; Reguly, Teresa; Rust, Jennifer M.; Winter, Andrew; Dolinski, Kara; Tyers, Mike
2011-01-01
The Biological General Repository for Interaction Datasets (BioGRID) is a public database that archives and disseminates genetic and protein interaction data from model organisms and humans (http://www.thebiogrid.org). BioGRID currently holds 347 966 interactions (170 162 genetic, 177 804 protein) curated from both high-throughput data sets and individual focused studies, as derived from over 23 000 publications in the primary literature. Complete coverage of the entire literature is maintained for budding yeast (Saccharomyces cerevisiae), fission yeast (Schizosaccharomyces pombe) and thale cress (Arabidopsis thaliana), and efforts to expand curation across multiple metazoan species are underway. The BioGRID houses 48 831 human protein interactions that have been curated from 10 247 publications. Current curation drives are focused on particular areas of biology to enable insights into conserved networks and pathways that are relevant to human health. The BioGRID 3.0 web interface contains new search and display features that enable rapid queries across multiple data types and sources. An automated Interaction Management System (IMS) is used to prioritize, coordinate and track curation across international sites and projects. BioGRID provides interaction data to several model organism databases, resources such as Entrez-Gene and other interaction meta-databases. The entire BioGRID 3.0 data collection may be downloaded in multiple file formats, including PSI MI XML. Source code for BioGRID 3.0 is freely available without any restrictions. PMID:21071413
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Casas-Agustench, Patricia; Arnett, Donna K.; Smith, Caren E.; Lai, Chao-Qiang; Parnell, Laurence D.; Borecki, Ingrid B.; Frazier-Wood, Alexis C.; Allison, Matthew; Chen, Yii-Der Ida; Taylor, Kent D.; Rich, Stephen S.; Rotter, Jerome I.; Lee, Yu-Chi; Ordovás, José M.
2014-01-01
Combining multiple genetic variants related to obesity into a genetic risk score (GRS) might improve identification of individuals at risk of developing obesity. Moreover, characterizing gene-diet interactions is a research challenge to establish dietary recommendations to individuals with higher predisposition to obesity. Our objective was to analyze the association between an obesity GRS and BMI in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) population, focusing on gene-diet interactions with total fat and saturated fatty acid (SFA) intake and to replicate findings in Multi-Ethnic Study of Atherosclerosis (MESA) population. Cross-sectional analyses included 783 US Caucasian participants from GOLDN and 2035 from MESA. Dietary intakes were estimated with validated food frequency questionnaires. Height and weight were measured. A weighted GRS was calculated on the basis of 63 obesity-associated variants. Multiple linear regression models adjusted by potential confounders were used to examine gene-diet interactions between dietary intake (total fat and SFA) and the obesity GRS in determining BMI. Significant interactions were found between total fat intake and the obesity GRS using these variables as continuous for BMI (P for interaction=0.010, 0.046, and 0.002 in GOLDN, MESA and meta-analysis, respectively). These association terms were stronger when assessing interactions between SFA intake and GRS for BMI (P for interaction=0.005, 0.018, and <0.001 in GOLDN, MESA and meta-analysis, respectively). SFA intake interacts with an obesity GRS in modulating BMI in two US populations. Although to determine the causal direction requires further investigation, these findings suggest that potential dietary recommendations to reduce BMI effectively in populations with high obesity GRS would be to reduce total fat intake mainly by limiting SFAs. PMID:24794412
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The genetic links between the big five personality traits and general interest domains.
Kandler, Christian; Bleidorn, Wiebke; Riemann, Rainer; Angleitner, Alois; Spinath, Frank M
2011-12-01
This is the first genetically informative study in which multiple informants were used to quantify the genetic and environmental sources of individual differences in general interests as well as the phenotypic and genetic links between general interests and Big Five personality traits. Self-reports and two peer ratings from 844 individuals, including 225 monozygotic and 113 dizygotic complete twin pairs, were collected. Multiple-rater scores (composites) revealed that the averaged levels of genetic and environmental effects on seven broad interest domains were similar to those on personality traits. Multivariate analyses showed that about 35% of the genetic and 9% of the environmental variance in interests were explained by personality domains, in particular by Openness. The findings suggest that interests cannot easily be considered as a byproduct of the interactions between personality genotypes and the environmental influences but rather as an internal regulation of behavior with an own genetic basis.
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Johnson, M T J; Agrawal, A A; Maron, J L; Salminen, J-P
2009-06-01
This study explored genetic variation and co-variation in multiple functional plant traits. Our goal was to characterize selection, heritabilities and genetic correlations among different types of traits to gain insight into the evolutionary ecology of plant populations and their interactions with insect herbivores. In a field experiment, we detected significant heritable variation for each of 24 traits of Oenothera biennis and extensive genetic covariance among traits. Traits with diverse functions formed several distinct groups that exhibited positive genetic covariation with each other. Genetic variation in life-history traits and secondary chemistry together explained a large proportion of variation in herbivory (r(2) = 0.73). At the same time, selection acted on lifetime biomass, life-history traits and two secondary compounds of O. biennis, explaining over 95% of the variation in relative fitness among genotypes. The combination of genetic covariances and directional selection acting on multiple traits suggests that adaptive evolution of particular traits is constrained, and that correlated evolution of groups of traits will occur, which is expected to drive the evolution of increased herbivore susceptibility. As a whole, our study indicates that an examination of genetic variation and covariation among many different types of traits can provide greater insight into the evolutionary ecology of plant populations and plant-herbivore interactions.
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Roetker, Nicholas S; Page, C David; Yonker, James A; Chang, Vicky; Roan, Carol L; Herd, Pamela; Hauser, Taissa S; Hauser, Robert M; Atwood, Craig S
2013-10-01
We examined depression within a multidimensional framework consisting of genetic, environmental, and sociobehavioral factors and, using machine learning algorithms, explored interactions among these factors that might better explain the etiology of depressive symptoms. We measured current depressive symptoms using the Center for Epidemiologic Studies Depression Scale (n = 6378 participants in the Wisconsin Longitudinal Study). Genetic factors were 78 single nucleotide polymorphisms (SNPs); environmental factors-13 stressful life events (SLEs), plus a composite proportion of SLEs index; and sociobehavioral factors-18 personality, intelligence, and other health or behavioral measures. We performed traditional SNP associations via logistic regression likelihood ratio testing and explored interactions with support vector machines and Bayesian networks. After correction for multiple testing, we found no significant single genotypic associations with depressive symptoms. Machine learning algorithms showed no evidence of interactions. Naïve Bayes produced the best models in both subsets and included only environmental and sociobehavioral factors. We found no single or interactive associations with genetic factors and depressive symptoms. Various environmental and sociobehavioral factors were more predictive of depressive symptoms, yet their impacts were independent of one another. A genome-wide analysis of genetic alterations using machine learning methodologies will provide a framework for identifying genetic-environmental-sociobehavioral interactions in depressive symptoms.
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Lindström, Sara; Yen, Yu-Chun; Spiegelman, Donna; Kraft, Peter
2009-01-01
The possibility of gene-environment interaction can be exploited to identify genetic variants associated with disease using a joint test of genetic main effect and gene-environment interaction. We consider how exposure misclassification and dependence between the true exposure E and the tested genetic variant G affect this joint test in absolute terms and relative to three other tests: the marginal test (G), the standard test for multiplicative gene-environment interaction (GE), and the case-only test for interaction (GE-CO). All tests can have inflated Type I error rate when E and G are correlated in the underlying population. For the GE and G-GE tests this inflation is only noticeable when the gene-environment dependence is unusually strong; the inflation can be large for the GE-CO test even for modest correlation. The joint G-GE test has greater power than the GE test generally, and greater power than the G test when there is no genetic main effect and the measurement error is small to moderate. The joint G-GE test is an attractive test for assessing genetic association when there is limited knowledge about casual mechanisms a priori, even in the presence of misclassification in environmental exposure measurement and correlation between exposure and genetic variants. PMID:19521099
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SZDB: A Database for Schizophrenia Genetic Research
Wu, Yong; Yao, Yong-Gang
2017-01-01
Abstract Schizophrenia (SZ) is a debilitating brain disorder with a complex genetic architecture. Genetic studies, especially recent genome-wide association studies (GWAS), have identified multiple variants (loci) conferring risk to SZ. However, how to efficiently extract meaningful biological information from bulk genetic findings of SZ remains a major challenge. There is a pressing need to integrate multiple layers of data from various sources, eg, genetic findings from GWAS, copy number variations (CNVs), association and linkage studies, gene expression, protein–protein interaction (PPI), co-expression, expression quantitative trait loci (eQTL), and Encyclopedia of DNA Elements (ENCODE) data, to provide a comprehensive resource to facilitate the translation of genetic findings into SZ molecular diagnosis and mechanism study. Here we developed the SZDB database (http://www.szdb.org/), a comprehensive resource for SZ research. SZ genetic data, gene expression data, network-based data, brain eQTL data, and SNP function annotation information were systematically extracted, curated and deposited in SZDB. In-depth analyses and systematic integration were performed to identify top prioritized SZ genes and enriched pathways. Multiple types of data from various layers of SZ research were systematically integrated and deposited in SZDB. In-depth data analyses and integration identified top prioritized SZ genes and enriched pathways. We further showed that genes implicated in SZ are highly co-expressed in human brain and proteins encoded by the prioritized SZ risk genes are significantly interacted. The user-friendly SZDB provides high-confidence candidate variants and genes for further functional characterization. More important, SZDB provides convenient online tools for data search and browse, data integration, and customized data analyses. PMID:27451428
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Is Hypovitaminosis D One of the Environmental Risk Factors for Multiple Sclerosis?
ERIC Educational Resources Information Center
Pierrot-Deseilligny, Charles; Souberbielle, Jean-Claude
2010-01-01
The role of hypovitaminosis D as a possible risk factor for multiple sclerosis is reviewed. First, it is emphasized that hypovitaminosis D could be only one of the risk factors for multiple sclerosis and that numerous other environmental and genetic risk factors appear to interact and combine to trigger the disease. Secondly, the classical…
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Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q
2016-05-01
Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.
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de Haas, Sanne; Delmar, Paul; Bansal, Aruna T; Moisse, Matthieu; Miles, David W; Leighl, Natasha; Escudier, Bernard; Van Cutsem, Eric; Carmeliet, Peter; Scherer, Stefan J; Pallaud, Celine; Lambrechts, Diether
2014-10-01
Despite extensive translational research, no validated biomarkers predictive of bevacizumab treatment outcome have been identified. We performed a meta-analysis of individual patient data from six randomized phase III trials in colorectal, pancreatic, lung, renal, breast, and gastric cancer to explore the potential relationships between 195 common genetic variants in the vascular endothelial growth factor (VEGF) pathway and bevacizumab treatment outcome. The analysis included 1,402 patients (716 bevacizumab-treated and 686 placebo-treated). Twenty variants were associated (P < 0.05) with progression-free survival (PFS) in bevacizumab-treated patients. Of these, 4 variants in EPAS1 survived correction for multiple testing (q < 0.05). Genotype-by-treatment interaction tests revealed that, across these 20 variants, 3 variants in VEGF-C (rs12510099), EPAS1 (rs4953344), and IL8RA (rs2234671) were potentially predictive (P < 0.05), but not resistant to multiple testing (q > 0.05). A weak genotype-by-treatment interaction effect was also observed for rs699946 in VEGF-A, whereas Bayesian genewise analysis revealed that genetic variability in VHL was associated with PFS in the bevacizumab arm (q < 0.05). Variants in VEGF-A, EPAS1, and VHL were located in expression quantitative loci derived from lymphoblastoid cell lines, indicating that they affect the expression levels of their respective gene. This large genetic analysis suggests that variants in VEGF-A, EPAS1, IL8RA, VHL, and VEGF-C have potential value in predicting bevacizumab treatment outcome across tumor types. Although these associations did not survive correction for multiple testing in a genotype-by-interaction analysis, they are among the strongest predictive effects reported to date for genetic variants and bevacizumab efficacy.
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Ge, Tian; Nichols, Thomas E.; Ghosh, Debashis; Mormino, Elizabeth C.
2015-01-01
Measurements derived from neuroimaging data can serve as markers of disease and/or healthy development, are largely heritable, and have been increasingly utilized as (intermediate) phenotypes in genetic association studies. To date, imaging genetic studies have mostly focused on discovering isolated genetic effects, typically ignoring potential interactions with non-genetic variables such as disease risk factors, environmental exposures, and epigenetic markers. However, identifying significant interaction effects is critical for revealing the true relationship between genetic and phenotypic variables, and shedding light on disease mechanisms. In this paper, we present a general kernel machine based method for detecting effects of interaction between multidimensional variable sets. This method can model the joint and epistatic effect of a collection of single nucleotide polymorphisms (SNPs), accommodate multiple factors that potentially moderate genetic influences, and test for nonlinear interactions between sets of variables in a flexible framework. As a demonstration of application, we applied the method to data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to detect the effects of the interactions between candidate Alzheimer's disease (AD) risk genes and a collection of cardiovascular disease (CVD) risk factors, on hippocampal volume measurements derived from structural brain magnetic resonance imaging (MRI) scans. Our method identified that two genes, CR1 and EPHA1, demonstrate significant interactions with CVD risk factors on hippocampal volume, suggesting that CR1 and EPHA1 may play a role in influencing AD-related neurodegeneration in the presence of CVD risks. PMID:25600633
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Hohman, Timothy J; Bush, William S; Jiang, Lan; Brown-Gentry, Kristin D; Torstenson, Eric S; Dudek, Scott M; Mukherjee, Shubhabrata; Naj, Adam; Kunkle, Brian W; Ritchie, Marylyn D; Martin, Eden R; Schellenberg, Gerard D; Mayeux, Richard; Farrer, Lindsay A; Pericak-Vance, Margaret A; Haines, Jonathan L; Thornton-Wells, Tricia A
2016-02-01
Late-onset Alzheimer disease (AD) has a complex genetic etiology, involving locus heterogeneity, polygenic inheritance, and gene-gene interactions; however, the investigation of interactions in recent genome-wide association studies has been limited. We used a biological knowledge-driven approach to evaluate gene-gene interactions for consistency across 13 data sets from the Alzheimer Disease Genetics Consortium. Fifteen single nucleotide polymorphism (SNP)-SNP pairs within 3 gene-gene combinations were identified: SIRT1 × ABCB1, PSAP × PEBP4, and GRIN2B × ADRA1A. In addition, we extend a previously identified interaction from an endophenotype analysis between RYR3 × CACNA1C. Finally, post hoc gene expression analyses of the implicated SNPs further implicate SIRT1 and ABCB1, and implicate CDH23 which was most recently identified as an AD risk locus in an epigenetic analysis of AD. The observed interactions in this article highlight ways in which genotypic variation related to disease may depend on the genetic context in which it occurs. Further, our results highlight the utility of evaluating genetic interactions to explain additional variance in AD risk and identify novel molecular mechanisms of AD pathogenesis. Copyright © 2016 Elsevier Inc. All rights reserved.
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Plasticity of genetic interactions in metabolic networks of yeast.
Harrison, Richard; Papp, Balázs; Pál, Csaba; Oliver, Stephen G; Delneri, Daniela
2007-02-13
Why are most genes dispensable? The impact of gene deletions may depend on the environment (plasticity), the presence of compensatory mechanisms (mutational robustness), or both. Here, we analyze the interaction between these two forces by exploring the condition-dependence of synthetic genetic interactions that define redundant functions and alternative pathways. We performed systems-level flux balance analysis of the yeast (Saccharomyces cerevisiae) metabolic network to identify genetic interactions and then tested the model's predictions with in vivo gene-deletion studies. We found that the majority of synthetic genetic interactions are restricted to certain environmental conditions, partly because of the lack of compensation under some (but not all) nutrient conditions. Moreover, the phylogenetic cooccurrence of synthetically interacting pairs is not significantly different from random expectation. These findings suggest that these gene pairs have at least partially independent functions, and, hence, compensation is only a byproduct of their evolutionary history. Experimental analyses that used multiple gene deletion strains not only confirmed predictions of the model but also showed that investigation of false predictions may both improve functional annotation within the model and also lead to the discovery of higher-order genetic interactions. Our work supports the view that functional redundancy may be more apparent than real, and it offers a unified framework for the evolution of environmental adaptation and mutational robustness.
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Motivational Aspects of Learning Genetics with Interactive Multimedia
ERIC Educational Resources Information Center
Tsui, Chi-Yan; Treagust, David F.
2004-01-01
A BioLogica trial in six U.S. schools using interpretive approach is conducted by the Concord Consortium that examined the student motivation of learning genetics. Multiple data sources like online tests, computer data log files and classroom observation are used that found the result in terms of interviewees' perception, class-wide online…
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Environmental Interactions and Epistasis Are Revealed in the Proteomic Responses to Complex Stimuli
Samir, Parimal; Rahul; Slaughter, James C.; Link, Andrew J.
2015-01-01
Ultimately, the genotype of a cell and its interaction with the environment determine the cell’s biochemical state. While the cell’s response to a single stimulus has been studied extensively, a conceptual framework to model the effect of multiple environmental stimuli applied concurrently is not as well developed. In this study, we developed the concepts of environmental interactions and epistasis to explain the responses of the S. cerevisiae proteome to simultaneous environmental stimuli. We hypothesize that, as an abstraction, environmental stimuli can be treated as analogous to genetic elements. This would allow modeling of the effects of multiple stimuli using the concepts and tools developed for studying gene interactions. Mirroring gene interactions, our results show that environmental interactions play a critical role in determining the state of the proteome. We show that individual and complex environmental stimuli behave similarly to genetic elements in regulating the cellular responses to stimuli, including the phenomena of dominance and suppression. Interestingly, we observed that the effect of a stimulus on a protein is dominant over other stimuli if the response to the stimulus involves the protein. Using publicly available transcriptomic data, we find that environmental interactions and epistasis regulate transcriptomic responses as well. PMID:26247773
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[Analysis of genetic models and gene effects on main agronomy characters in rapeseed].
Li, J; Qiu, J; Tang, Z; Shen, L
1992-01-01
According to four different genetic models, the genetic patterns of 8 agronomy traits were analysed by using the data of 24 generations which included positive and negative cross of 81008 x Tower, both of the varieties are of good quality. The results showed that none of 8 characters could fit in with additive-dominance models. Epistasis was found in all of these characters, and it has significant effect on generation means. Seed weight/plant and some other main yield characters are controlled by duplicate interaction genes. The interaction between triple genes or multiple genes needs to be utilized in yield heterosis.
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Gioutlakis, Aris; Klapa, Maria I.
2017-01-01
It has been acknowledged that source databases recording experimentally supported human protein-protein interactions (PPIs) exhibit limited overlap. Thus, the reconstruction of a comprehensive PPI network requires appropriate integration of multiple heterogeneous primary datasets, presenting the PPIs at various genetic reference levels. Existing PPI meta-databases perform integration via normalization; namely, PPIs are merged after converted to a certain target level. Hence, the node set of the integrated network depends each time on the number and type of the combined datasets. Moreover, the irreversible a priori normalization process hinders the identification of normalization artifacts in the integrated network, which originate from the nonlinearity characterizing the genetic information flow. PICKLE (Protein InteraCtion KnowLedgebasE) 2.0 implements a new architecture for this recently introduced human PPI meta-database. Its main novel feature over the existing meta-databases is its approach to primary PPI dataset integration via genetic information ontology. Building upon the PICKLE principles of using the reviewed human complete proteome (RHCP) of UniProtKB/Swiss-Prot as the reference protein interactor set, and filtering out protein interactions with low probability of being direct based on the available evidence, PICKLE 2.0 first assembles the RHCP genetic information ontology network by connecting the corresponding genes, nucleotide sequences (mRNAs) and proteins (UniProt entries) and then integrates PPI datasets by superimposing them on the ontology network without any a priori transformations. Importantly, this process allows the resulting heterogeneous integrated network to be reversibly normalized to any level of genetic reference without loss of the original information, the latter being used for identification of normalization biases, and enables the appraisal of potential false positive interactions through PPI source database cross-checking. The PICKLE web-based interface (www.pickle.gr) allows for the simultaneous query of multiple entities and provides integrated human PPI networks at either the protein (UniProt) or the gene level, at three PPI filtering modes. PMID:29023571
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Millette, Katie L; Keyghobadi, Nusha
2015-01-01
Despite strong interest in understanding how habitat spatial structure shapes the genetics of populations, the relative importance of habitat amount and configuration for patterns of genetic differentiation remains largely unexplored in empirical systems. In this study, we evaluate the relative influence of, and interactions among, the amount of habitat and aspects of its spatial configuration on genetic differentiation in the pitcher plant midge, Metriocnemus knabi. Larvae of this species are found exclusively within the water-filled leaves of pitcher plants (Sarracenia purpurea) in a system that is naturally patchy at multiple spatial scales (i.e., leaf, plant, cluster, peatland). Using generalized linear mixed models and multimodel inference, we estimated effects of the amount of habitat, patch size, interpatch distance, and patch isolation, measured at different spatial scales, on genetic differentiation (FST) among larval samples from leaves within plants, plants within clusters, and clusters within peatlands. Among leaves and plants, genetic differentiation appears to be driven by female oviposition behaviors and is influenced by habitat isolation at a broad (peatland) scale. Among clusters, gene flow is spatially restricted and aspects of both the amount of habitat and configuration at the focal scale are important, as is their interaction. Our results suggest that both habitat amount and configuration can be important determinants of genetic structure and that their relative influence is scale dependent. PMID:25628865
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Millette, Katie L; Keyghobadi, Nusha
2015-01-01
Despite strong interest in understanding how habitat spatial structure shapes the genetics of populations, the relative importance of habitat amount and configuration for patterns of genetic differentiation remains largely unexplored in empirical systems. In this study, we evaluate the relative influence of, and interactions among, the amount of habitat and aspects of its spatial configuration on genetic differentiation in the pitcher plant midge, Metriocnemus knabi. Larvae of this species are found exclusively within the water-filled leaves of pitcher plants (Sarracenia purpurea) in a system that is naturally patchy at multiple spatial scales (i.e., leaf, plant, cluster, peatland). Using generalized linear mixed models and multimodel inference, we estimated effects of the amount of habitat, patch size, interpatch distance, and patch isolation, measured at different spatial scales, on genetic differentiation (F ST) among larval samples from leaves within plants, plants within clusters, and clusters within peatlands. Among leaves and plants, genetic differentiation appears to be driven by female oviposition behaviors and is influenced by habitat isolation at a broad (peatland) scale. Among clusters, gene flow is spatially restricted and aspects of both the amount of habitat and configuration at the focal scale are important, as is their interaction. Our results suggest that both habitat amount and configuration can be important determinants of genetic structure and that their relative influence is scale dependent.
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Challenges and Opportunities in Genome-Wide Environmental Interaction (GWEI) studies
Aschard, Hugues; Lutz, Sharon; Maus, Bärbel; Duell, Eric J.; Fingerlin, Tasha; Chatterjee, Nilanjan; Kraft, Peter; Van Steen, Kristel
2012-01-01
The interest in performing gene-environment interaction studies has seen a significant increase with the increase of advanced molecular genetics techniques. Practically, it became possible to investigate the role of environmental factors in disease risk and hence to investigate their role as genetic effect modifiers. The understanding that genetics is important in the uptake and metabolism of toxic substances is an example of how genetic profiles can modify important environmental risk factors to disease. Several rationales exist to set up gene-environment interaction studies and the technical challenges related to these studies – when the number of environmental or genetic risk factors is relatively small – has been described before. In the post-genomic era, it is now possible to study thousands of genes and their interaction with the environment. This brings along a whole range of new challenges and opportunities. Despite a continuing effort in developing efficient methods and optimal bioinformatics infrastructures to deal with the available wealth of data, the challenge remains how to best present and analyze Genome-Wide Environmental Interaction (GWEI) studies involving multiple genetic and environmental factors. Since GWEIs are performed at the intersection of statistical genetics, bioinformatics and epidemiology, usually similar problems need to be dealt with as for Genome-Wide Association gene-gene Interaction (GWAI) studies. However, additional complexities need to be considered which are typical for large-scale epidemiological studies, but are also related to “joining” two heterogeneous types of data in explaining complex disease trait variation or for prediction purposes. PMID:22760307
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Ge, Tian; Nichols, Thomas E; Ghosh, Debashis; Mormino, Elizabeth C; Smoller, Jordan W; Sabuncu, Mert R
2015-04-01
Measurements derived from neuroimaging data can serve as markers of disease and/or healthy development, are largely heritable, and have been increasingly utilized as (intermediate) phenotypes in genetic association studies. To date, imaging genetic studies have mostly focused on discovering isolated genetic effects, typically ignoring potential interactions with non-genetic variables such as disease risk factors, environmental exposures, and epigenetic markers. However, identifying significant interaction effects is critical for revealing the true relationship between genetic and phenotypic variables, and shedding light on disease mechanisms. In this paper, we present a general kernel machine based method for detecting effects of the interaction between multidimensional variable sets. This method can model the joint and epistatic effect of a collection of single nucleotide polymorphisms (SNPs), accommodate multiple factors that potentially moderate genetic influences, and test for nonlinear interactions between sets of variables in a flexible framework. As a demonstration of application, we applied the method to the data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to detect the effects of the interactions between candidate Alzheimer's disease (AD) risk genes and a collection of cardiovascular disease (CVD) risk factors, on hippocampal volume measurements derived from structural brain magnetic resonance imaging (MRI) scans. Our method identified that two genes, CR1 and EPHA1, demonstrate significant interactions with CVD risk factors on hippocampal volume, suggesting that CR1 and EPHA1 may play a role in influencing AD-related neurodegeneration in the presence of CVD risks. Copyright © 2015 Elsevier Inc. All rights reserved.
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Genetic interaction of the fusiform rust fungus with resistance gene FR1 in loblolly pine
Thomas L. Kubisiak; Henry V. Amerson; C. Dana Nelson
2005-01-01
We propose a method for defining DNA markers linked to Cronartium quercuum f. sp. fusiforme avirulence (Avr) genes. However, before this method can be successfully employed, a spore competition study was needed to determine the genetic composition of single pycnial drops and multiple drops on single galls when using the standard...
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2014-01-01
In this study, we analyze the Genetic Analysis Workshop 18 (GAW18) data to identify regions of single-nucleotide polymorphisms (SNPs), which significantly influence hypertension status among individuals. We have studied the marginal impact of these regions on disease status in the past, but we extend the method to deal with environmental factors present in data collected over several exam periods. We consider the respective interactions between such traits as smoking status and age with the genetic information and hope to augment those genetic regions deemed influential marginally with those that contribute via an interactive effect. In particular, we focus only on rare variants and apply a procedure to combine signal among rare variants in a number of "fixed bins" along the chromosome. We extend the procedure in Agne et al [1] to incorporate environmental factors by dichotomizing subjects via traits such as smoking status and age, running the marginal procedure among each respective category (i.e., smokers or nonsmokers), and then combining their scores into a score for interaction. To avoid overlap of subjects, we examine each exam period individually. Out of a possible 629 fixed-bin regions in chromosome 3, we observe that 11 show up in multiple exam periods for gene-smoking score. Fifteen regions exhibit significance for multiple exam periods for gene-age score, with 4 regions deemed significant for all 3 exam periods. The procedure pinpoints SNPs in 8 "answer" genes, with 5 of these showing up as significant in multiple testing schemes (Gene-Smoking, Gene-Age for Exams 1, 2, and 3). PMID:25519400
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Casas-Agustench, Patricia; Arnett, Donna K; Smith, Caren E; Lai, Chao-Qiang; Parnell, Laurence D; Borecki, Ingrid B; Frazier-Wood, Alexis C; Allison, Matthew; Chen, Yii-Der Ida; Taylor, Kent D; Rich, Stephen S; Rotter, Jerome I; Lee, Yu-Chi; Ordovás, José M
2014-12-01
Combining multiple genetic variants related to obesity into a genetic risk score (GRS) might improve identification of individuals at risk of developing obesity. Moreover, characterizing gene-diet interactions is a research challenge to establish dietary recommendations to individuals with higher predisposition to obesity. Our objective was to analyze the association between an obesity GRS and body mass index (BMI) in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) population, focusing on gene-diet interactions with total fat and saturated fatty acid (SFA) intake, and to replicate findings in the Multi-Ethnic Study of Atherosclerosis (MESA) population. Cross-sectional analyses included 783 white US participants from GOLDN and 2,035 from MESA. Dietary intakes were estimated with validated food frequency questionnaires. Height and weight were measured. A weighted GRS was calculated on the basis of 63 obesity-associated variants. Multiple linear regression models adjusted by potential confounders were used to examine gene-diet interactions between dietary intake (total fat and SFA) and the obesity GRS in determining BMI. Significant interactions were found between total fat intake and the obesity GRS using these variables as continuous for BMI (P for interaction=0.010, 0.046, and 0.002 in GOLDN, MESA, and meta-analysis, respectively). These association terms were stronger when assessing interactions between SFA intake and GRS for BMI (P for interaction=0.005, 0.018, and <0.001 in GOLDN, MESA, and meta-analysis, respectively). SFA intake interacts with an obesity GRS in modulating BMI in two US populations. Although determining the causal direction requires further investigation, these findings suggest that potential dietary recommendations to reduce BMI effectively in populations with high obesity GRS would be to reduce total fat intake mainly by limiting SFAs. Copyright © 2014 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.
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Arya, Rector; Farook, Vidya S; Fowler, Sharon P; Puppala, Sobha; Chittoor, Geetha; Resendez, Roy G; Mummidi, Srinivas; Vanamala, Jairam; Almasy, Laura; Curran, Joanne E; Comuzzie, Anthony G; Lehman, Donna M; Jenkinson, Christopher P; Lynch, Jane L; DeFronzo, Ralph A; Blangero, John; Hale, Daniel E; Duggirala, Ravindranath; Diego, Vincent P
2018-06-01
Knowledge on genetic and environmental (G × E) interaction effects on cardiometabolic risk factors (CMRFs) in children is limited. The purpose of this study was to examine the impact of G × E interaction effects on CMRFs in Mexican American (MA) children (n = 617, ages 6-17 years). The environments examined were sedentary activity (SA), assessed by recalls from "yesterday" (SAy) and "usually" (SAu) and physical fitness (PF) assessed by Harvard PF scores (HPFS). CMRF data included body mass index (BMI), waist circumference (WC), fat mass (FM), fasting insulin (FI), homeostasis model of assessment-insulin resistance (HOMA-IR), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), systolic (SBP) and diastolic (DBP) blood pressure, and number of metabolic syndrome components (MSC). We examined potential G × E interaction in the phenotypic expression of CMRFs using variance component models and likelihood-based statistical inference. Significant G × SA interactions were identified for six CMRFs: BMI, WC, FI, HOMA-IR, MSC, and HDL, and significant G × HPFS interactions were observed for four CMRFs: BMI, WC, FM, and HOMA-IR. However, after correcting for multiple hypothesis testing, only WC × SAy, FM × SAy, and FI × SAu interactions became marginally significant. After correcting for multiple testing, most of CMRFs exhibited significant G × E interactions (Reduced G × E model vs. Constrained model). These findings provide evidence that genetic factors interact with SA and PF to influence variation in CMRFs, and underscore the need for better understanding of these relationships to develop strategies and interventions to effectively reduce or prevent cardiometabolic risk in children. © 2018 WILEY PERIODICALS, INC.
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Zeng, Ping; Mukherjee, Sayan; Zhou, Xiang
2017-01-01
Epistasis, commonly defined as the interaction between multiple genes, is an important genetic component underlying phenotypic variation. Many statistical methods have been developed to model and identify epistatic interactions between genetic variants. However, because of the large combinatorial search space of interactions, most epistasis mapping methods face enormous computational challenges and often suffer from low statistical power due to multiple test correction. Here, we present a novel, alternative strategy for mapping epistasis: instead of directly identifying individual pairwise or higher-order interactions, we focus on mapping variants that have non-zero marginal epistatic effects—the combined pairwise interaction effects between a given variant and all other variants. By testing marginal epistatic effects, we can identify candidate variants that are involved in epistasis without the need to identify the exact partners with which the variants interact, thus potentially alleviating much of the statistical and computational burden associated with standard epistatic mapping procedures. Our method is based on a variance component model, and relies on a recently developed variance component estimation method for efficient parameter inference and p-value computation. We refer to our method as the “MArginal ePIstasis Test”, or MAPIT. With simulations, we show how MAPIT can be used to estimate and test marginal epistatic effects, produce calibrated test statistics under the null, and facilitate the detection of pairwise epistatic interactions. We further illustrate the benefits of MAPIT in a QTL mapping study by analyzing the gene expression data of over 400 individuals from the GEUVADIS consortium. PMID:28746338
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Examination of association to autism of common genetic variationin genes related to dopamine.
Anderson, B M; Schnetz-Boutaud, N; Bartlett, J; Wright, H H; Abramson, R K; Cuccaro, M L; Gilbert, J R; Pericak-Vance, M A; Haines, J L
2008-12-01
Autism is a severe neurodevelopmental disorder characterized by a triad of complications. Autistic individuals display significant disturbances in language and reciprocal social interactions, combined with repetitive and stereotypic behaviors. Prevalence studies suggest that autism is more common than originally believed, with recent estimates citing a rate of one in 150. Although multiple genetic linkage and association studies have yielded multiple suggestive genes or chromosomal regions, a specific risk locus has yet to be identified and widely confirmed. Because many etiologies have been suggested for this complex syndrome, we hypothesize that one of the difficulties in identifying autism genes is that multiple genetic variants may be required to significantly increase the risk of developing autism. Thus, we took the alternative approach of examining 14 prominent dopamine pathway candidate genes for detailed study by genotyping 28 single nucleotide polymorphisms. Although we did observe a nominally significant association for rs2239535 (P=0.008) on chromosome 20, single-locus analysis did not reveal any results as significant after correction for multiple comparisons. No significant interaction was identified when Multifactor Dimensionality Reduction was employed to test specifically for multilocus effects. Although genome-wide linkage scans in autism have provided support for linkage to various loci along the dopamine pathway, our study does not provide strong evidence of linkage or association to any specific gene or combination of genes within the pathway. These results demonstrate that common genetic variation within the tested genes located within this pathway at most play a minor to moderate role in overall autism pathogenesis.
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A review of vulnerability and risks for schizophrenia: Beyond the two hit hypothesis
Davis, Justin; Eyre, Harris; Jacka, Felice N; Dodd, Seetal; Dean, Olivia; McEwen, Sarah; Debnath, Monojit; McGrath, John; Maes, Michael; Amminger, Paul; McGorry, Patrick D; Pantelis, Christos; Berk, Michael
2016-01-01
Schizophrenia risk has often been conceptualized using a model which requires two hits in order to generate the clinical phenotype—the first as an early priming in a genetically predisposed individual and the second a likely environmental insult. The aim of this paper was to review the literature and reformulate this binary risk-vulnerability model. We sourced the data for this narrative review from the electronic database PUBMED. Our search terms were not limited by language or date of publication. The development of schizophrenia may be driven by genetic vulnerability interacting with multiple vulnerability factors including lowered prenatal vitamin D exposure, viral infections, smoking intelligence quotient, social cognition cannabis use, social defeat, nutrition and childhood trauma. It is likely that these genetic risks, environmental risks and vulnerability factors are cumulative and interactive with each other and with critical periods of neurodevelopmental vulnerability. The development of schizophrenia is likely to be more complex and nuanced than the binary two hit model originally proposed nearly thirty years ago. Risk appears influenced by a more complex process involving genetic risk interfacing with multiple potentially interacting hits and vulnerability factors occurring at key periods of neurodevelopmental activity, which culminate in the expression of disease state. These risks are common across a number of neuropsychiatric and medical disorders, which might inform common preventive and intervention strategies across non-communicable disorders. PMID:27073049
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A "candidate-interactome" aggregate analysis of genome-wide association data in multiple sclerosis.
Mechelli, Rosella; Umeton, Renato; Policano, Claudia; Annibali, Viviana; Coarelli, Giulia; Ricigliano, Vito A G; Vittori, Danila; Fornasiero, Arianna; Buscarinu, Maria Chiara; Romano, Silvia; Salvetti, Marco; Ristori, Giovanni
2013-01-01
Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms.
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A “Candidate-Interactome” Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis
Policano, Claudia; Annibali, Viviana; Coarelli, Giulia; Ricigliano, Vito A. G.; Vittori, Danila; Fornasiero, Arianna; Buscarinu, Maria Chiara; Romano, Silvia; Salvetti, Marco; Ristori, Giovanni
2013-01-01
Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a “candidate interactome” (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms. PMID:23696811
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Pare, Guillaume; Mao, Shihong; Deng, Wei Q
2016-06-08
Despite considerable efforts, known genetic associations only explain a small fraction of predicted heritability. Regional associations combine information from multiple contiguous genetic variants and can improve variance explained at established association loci. However, regional associations are not easily amenable to estimation using summary association statistics because of sensitivity to linkage disequilibrium (LD). We now propose a novel method, LD Adjusted Regional Genetic Variance (LARGV), to estimate phenotypic variance explained by regional associations using summary statistics while accounting for LD. Our method is asymptotically equivalent to a multiple linear regression model when no interaction or haplotype effects are present. It has several applications, such as ranking of genetic regions according to variance explained or comparison of variance explained by two or more regions. Using height and BMI data from the Health Retirement Study (N = 7,776), we show that most genetic variance lies in a small proportion of the genome and that previously identified linkage peaks have higher than expected regional variance.
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Pare, Guillaume; Mao, Shihong; Deng, Wei Q.
2016-01-01
Despite considerable efforts, known genetic associations only explain a small fraction of predicted heritability. Regional associations combine information from multiple contiguous genetic variants and can improve variance explained at established association loci. However, regional associations are not easily amenable to estimation using summary association statistics because of sensitivity to linkage disequilibrium (LD). We now propose a novel method, LD Adjusted Regional Genetic Variance (LARGV), to estimate phenotypic variance explained by regional associations using summary statistics while accounting for LD. Our method is asymptotically equivalent to a multiple linear regression model when no interaction or haplotype effects are present. It has several applications, such as ranking of genetic regions according to variance explained or comparison of variance explained by two or more regions. Using height and BMI data from the Health Retirement Study (N = 7,776), we show that most genetic variance lies in a small proportion of the genome and that previously identified linkage peaks have higher than expected regional variance. PMID:27273519
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Air pollution is a worldwide contributor to cardiovascular disease mortality and morbidity. Traffic air pollution is a ubiquitous source of air pollution in developed nations, and is associated with multiple cardiovascular outcomes such as: coronary atherosclerosis, peripheral ar...
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Roetker, Nicholas S.; Yonker, James A.; Chang, Vicky; Roan, Carol L.; Herd, Pamela; Hauser, Taissa S.; Hauser, Robert M.
2013-01-01
Objectives. We examined depression within a multidimensional framework consisting of genetic, environmental, and sociobehavioral factors and, using machine learning algorithms, explored interactions among these factors that might better explain the etiology of depressive symptoms. Methods. We measured current depressive symptoms using the Center for Epidemiologic Studies Depression Scale (n = 6378 participants in the Wisconsin Longitudinal Study). Genetic factors were 78 single nucleotide polymorphisms (SNPs); environmental factors—13 stressful life events (SLEs), plus a composite proportion of SLEs index; and sociobehavioral factors—18 personality, intelligence, and other health or behavioral measures. We performed traditional SNP associations via logistic regression likelihood ratio testing and explored interactions with support vector machines and Bayesian networks. Results. After correction for multiple testing, we found no significant single genotypic associations with depressive symptoms. Machine learning algorithms showed no evidence of interactions. Naïve Bayes produced the best models in both subsets and included only environmental and sociobehavioral factors. Conclusions. We found no single or interactive associations with genetic factors and depressive symptoms. Various environmental and sociobehavioral factors were more predictive of depressive symptoms, yet their impacts were independent of one another. A genome-wide analysis of genetic alterations using machine learning methodologies will provide a framework for identifying genetic–environmental–sociobehavioral interactions in depressive symptoms. PMID:23927508
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Denis, Marie; Enquobahrie, Daniel A; Tadesse, Mahlet G; Gelaye, Bizu; Sanchez, Sixto E; Salazar, Manuel; Ananth, Cande V; Williams, Michelle A
2014-01-01
While available evidence supports the role of genetics in the pathogenesis of placental abruption (PA), PA-related placental genome variations and maternal-placental genetic interactions have not been investigated. Maternal blood and placental samples collected from participants in the Peruvian Abruptio Placentae Epidemiology study were genotyped using Illumina's Cardio-Metabochip platform. We examined 118,782 genome-wide SNPs and 333 SNPs in 32 candidate genes from mitochondrial biogenesis and oxidative phosphorylation pathways in placental DNA from 280 PA cases and 244 controls. We assessed maternal-placental interactions in the candidate gene SNPS and two imprinted regions (IGF2/H19 and C19MC). Univariate and penalized logistic regression models were fit to estimate odds ratios. We examined the combined effect of multiple SNPs on PA risk using weighted genetic risk scores (WGRS) with repeated ten-fold cross-validations. A multinomial model was used to investigate maternal-placental genetic interactions. In placental genome-wide and candidate gene analyses, no SNP was significant after false discovery rate correction. The top genome-wide association study (GWAS) hits were rs544201, rs1484464 (CTNNA2), rs4149570 (TNFRSF1A) and rs13055470 (ZNRF3) (p-values: 1.11e-05 to 3.54e-05). The top 200 SNPs of the GWAS overrepresented genes involved in cell cycle, growth and proliferation. The top candidate gene hits were rs16949118 (COX10) and rs7609948 (THRB) (p-values: 6.00e-03 and 8.19e-03). Participants in the highest quartile of WGRS based on cross-validations using SNPs selected from the GWAS and candidate gene analyses had a 8.40-fold (95% CI: 5.8-12.56) and a 4.46-fold (95% CI: 2.94-6.72) higher odds of PA compared to participants in the lowest quartile. We found maternal-placental genetic interactions on PA risk for two SNPs in PPARG (chr3:12313450 and chr3:12412978) and maternal imprinting effects for multiple SNPs in the C19MC and IGF2/H19 regions. Variations in the placental genome and interactions between maternal-placental genetic variations may contribute to PA risk. Larger studies may help advance our understanding of PA pathogenesis.
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Gene-environment interplay in the etiology of psychosis.
Zwicker, Alyson; Denovan-Wright, Eileen M; Uher, Rudolf
2018-01-15
Schizophrenia and other types of psychosis incur suffering, high health care costs and loss of human potential, due to the combination of early onset and poor response to treatment. Our ability to prevent or cure psychosis depends on knowledge of causal mechanisms. Molecular genetic studies show that thousands of common and rare variants contribute to the genetic risk for psychosis. Epidemiological studies have identified many environmental factors associated with increased risk of psychosis. However, no single genetic or environmental factor is sufficient to cause psychosis on its own. The risk of developing psychosis increases with the accumulation of many genetic risk variants and exposures to multiple adverse environmental factors. Additionally, the impact of environmental exposures likely depends on genetic factors, through gene-environment interactions. Only a few specific gene-environment combinations that lead to increased risk of psychosis have been identified to date. An example of replicable gene-environment interaction is a common polymorphism in the AKT1 gene that makes its carriers sensitive to developing psychosis with regular cannabis use. A synthesis of results from twin studies, molecular genetics, and epidemiological research outlines the many genetic and environmental factors contributing to psychosis. The interplay between these factors needs to be considered to draw a complete picture of etiology. To reach a more complete explanation of psychosis that can inform preventive strategies, future research should focus on longitudinal assessments of multiple environmental exposures within large, genotyped cohorts beginning early in life.
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Present status of understanding on the genetic etiology of polycystic ovary syndrome.
Dasgupta, S; Reddy, B Mohan
2008-01-01
Polycystic ovary syndrome (PCOS) is the most common endocrinopathy in women of reproductive age with a prevalence of approximately 7-10% worldwide. PCOS reflects multiple potential aetiologies and variable clinical manifestations. This syndrome is characterized by serious health implications such as diabetes, coronary heart diseases and cancer and also leads to infertility. PCOS can be viewed as a heterogeneous androgen excess disorder with varying degrees of reproductive and metabolic abnormalities determined by the interaction of multiple genetic and environmental factors. In this paper, we have attempted a comprehensive review of primarily molecular genetic studies done so far on PCOS. We have also covered the studies focusing on the environmental factors and impact of ethnicity on the presentation of this syndrome. A large number of studies have been attempted to understand the aetiological mechanisms behind PCOS both at the clinical and molecular genetic levels. In the Indian context, majority of the PCOS studies have been confined to the clinical dimensions. However, a concrete genetic mechanism behind the manifestation of PCOS is yet to be ascertained. Understanding of this complex disorder requires comprehensive studies incorporating relatively larger homogenous samples for genetic analysis and taking into account the ethnicity and the environmental conditions of the population/cohort under study. Research focused on these aspects may provide better understanding on the genetic etiology and the interaction between genes and environment, which may help develop new treatment methods and possible prevention of the syndrome.
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Serotonin transporter gene and childhood trauma--a G × E effect on anxiety sensitivity.
Klauke, Benedikt; Deckert, Jürgen; Reif, Andreas; Pauli, Paul; Zwanzger, Peter; Baumann, Christian; Arolt, Volker; Glöckner-Rist, Angelika; Domschke, Katharina
2011-12-21
Genetic factors and environmental factors are assumed to interactively influence the pathogenesis of anxiety disorders. Thus, a gene-environment interaction (G × E) study was conducted with respect to anxiety sensitivity (AS) as a promising intermediate phenotype of anxiety disorders. Healthy subjects (N = 363) were assessed for AS, childhood maltreatment (Childhood Trauma Questionnaire), and genotyped for functional serotonin transporter gene variants (5-HTTLPR/5-HTT rs25531). The influence of genetic and environmental variables on AS and its subdimensions was determined by a step-wise hierarchical regression and a multiple indicator multiple cause (MIMIC) model. A significant G × E effect of the more active 5-HTT genotypes and childhood maltreatment on AS was observed. Furthermore, genotype (LL)-childhood trauma interaction particularly influenced somatic AS subdimensions, whereas cognitive subdimensions were affected by childhood maltreatment only. Results indicate a G × E effect of the more active 5-HTT genotypes and childhood maltreatment on AS, with particular impact on its somatic subcomponent. © 2011 Wiley Periodicals, Inc.
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Genetics Home Reference: vitiligo
... PubMed or Free article on PubMed Central Smith AG, Sturm RA. Multiple genes and locus interactions in ... qualified healthcare professional . About Selection Criteria for Links Data Files & API Site Map Subscribe Customer Support USA. ...
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Li, Linlin; Gao, Kaiping; Zhao, Jingzhi; Feng, Tianping; Yin, Lei; Wang, Jinjin; Wang, Chongjian; Li, Chunyang; Wang, Yan; Wang, Qian; Zhai, Yujia; You, Haifei; Ren, Yongcheng; Wang, Bingyuan; Hu, Dongsheng
2014-01-25
Few genome-wide association studies have considered interactions between multiple genetic variants and environmental factors associated with disease. The interaction was examined between a glucagon gene (GCG) polymorphism and smoking, alcohol consumption and physical activity and the association with risk of type 2 diabetes mellitus (T2DM) in a case-control study of Chinese Han subjects. The rs12104705 polymorphism of GCG and interactions with environmental variables were analyzed for 9619 participants by binary multiple logistic regression. Smoking with the C-C haplotype of rs12104705 was associated with increased risk of T2DM (OR=1.174, 95% CI=1.013-1.361). Moderate and high physical activity with the C-C genotype was associated with decreased risk of T2DM as compared with low physical activity with the genotype (OR=0.251, 95% CI=0.206-0.306 and OR=0.190, 95% CI=0.164-0.220). However, the interaction of drinking and genotype was not associated with risk of T2DM. Genetic polymorphism in rs12104705 of GCG may interact with smoking and physical activity to modify the risk of T2DM. © 2013.
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Interaction of the GCKR and A1CF loci with alcohol consumption to influence the risk of gout.
Rasheed, Humaira; Stamp, Lisa K; Dalbeth, Nicola; Merriman, Tony R
2017-07-05
Some gout-associated loci interact with dietary exposures to influence outcome. The aim of this study was to systematically investigate interactions between alcohol exposure and urate-associated loci in gout. A total of 2792 New Zealand European and Polynesian (Māori or Pacific) people with or without gout were genotyped for 29 urate-associated genetic variants and tested for a departure from multiplicative interaction with alcohol exposure in the risk of gout. Publicly available data from 6892 European subjects were used to test for a departure from multiplicative interaction between specific loci and alcohol exposure for the risk of hyperuricemia (HU). Multivariate adjusted logistic and linear regression was done, including an interaction term. Interaction of any alcohol exposure with GCKR (rs780094) and A1CF (rs10821905) influenced the risk of gout in Europeans (interaction term 0.28, P = 1.5 × 10 -4 ; interaction term 0.29, P = 1.4 × 10 -4 , respectively). At A1CF, alcohol exposure suppressed the gout risk conferred by the A-positive genotype. At GCKR, alcohol exposure eliminated the genetic effect on gout. In the Polynesian sample set, there was no experiment-wide evidence for interaction with alcohol in the risk of gout (all P > 8.6 × 10 -4 ). However, at GCKR, there was nominal evidence for an interaction in a direction consistent the European observation (interaction term 0.62, P = 0.05). There was no evidence for an interaction of A1CF or GCKR with alcohol exposure in determining HU. These data support the hypothesis that alcohol influences the risk of gout via glucose and apolipoprotein metabolism. In the absence of alcohol exposure, genetic variants in the GCKR and A1CF genes have a stronger role in gout.
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Slattery, Martha L.; Lundgreen, Abbie; Herrick, Jennifer S.; Caan, Bette J.; Potter, John D.; Wolff, Roger K.
2012-01-01
There is considerable biologic plausibility to the hypothesis that genetic variability in pathways involved in insulin signaling and energy homeostasis may modulate dietary risk associated with colorectal cancer. We utilized data from 2 population-based case-control studies of colon (n = 1,574 cases, 1,970 controls) and rectal (n = 791 cases, 999 controls) cancer to evaluate genetic variation in candidate SNPs identified from 9 genes in a candidate pathway: PDK1, RP6KA1, RPS6KA2, RPS6KB1, RPS6KB2, PTEN, FRAP1 (mTOR), TSC1, TSC2, Akt1, PIK3CA, and PRKAG2 with dietary intake of total energy, carbohydrates, fat, and fiber. We employed SNP, haplotype, and multiple-gene analysis to evaluate associations. PDK1 interacted with dietary fat for both colon and rectal cancer and with dietary carbohydrates for colon cancer. Statistically significant interaction with dietary carbohydrates and rectal cancer was detected by haplotype analysis of PDK1. Evaluation of dietary interactions with multiple genes in this candidate pathway showed several interactions with pairs of genes: Akt1 and PDK1, PDK1 and PTEN, PDK1 and TSC1, and PRKAG2 and PTEN. Analyses show that genetic variation influences risk of colorectal cancer associated with diet and illustrate the importance of evaluating dietary interactions beyond the level of single SNPs or haplotypes when a biologically relevant candidate pathway is examined. PMID:21999454
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Turner, Leslie M; Harr, Bettina
2014-12-09
Mapping hybrid defects in contact zones between incipient species can identify genomic regions contributing to reproductive isolation and reveal genetic mechanisms of speciation. The house mouse features a rare combination of sophisticated genetic tools and natural hybrid zones between subspecies. Male hybrids often show reduced fertility, a common reproductive barrier between incipient species. Laboratory crosses have identified sterility loci, but each encompasses hundreds of genes. We map genetic determinants of testis weight and testis gene expression using offspring of mice captured in a hybrid zone between M. musculus musculus and M. m. domesticus. Many generations of admixture enables high-resolution mapping of loci contributing to these sterility-related phenotypes. We identify complex interactions among sterility loci, suggesting multiple, non-independent genetic incompatibilities contribute to barriers to gene flow in the hybrid zone.
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Interaction-based evolution: how natural selection and nonrandom mutation work together.
Livnat, Adi
2013-10-18
The modern evolutionary synthesis leaves unresolved some of the most fundamental, long-standing questions in evolutionary biology: What is the role of sex in evolution? How does complex adaptation evolve? How can selection operate effectively on genetic interactions? More recently, the molecular biology and genomics revolutions have raised a host of critical new questions, through empirical findings that the modern synthesis fails to explain: for example, the discovery of de novo genes; the immense constructive role of transposable elements in evolution; genetic variance and biochemical activity that go far beyond what traditional natural selection can maintain; perplexing cases of molecular parallelism; and more. Here I address these questions from a unified perspective, by means of a new mechanistic view of evolution that offers a novel connection between selection on the phenotype and genetic evolutionary change (while relying, like the traditional theory, on natural selection as the only source of feedback on the fit between an organism and its environment). I hypothesize that the mutation that is of relevance for the evolution of complex adaptation-while not Lamarckian, or "directed" to increase fitness-is not random, but is instead the outcome of a complex and continually evolving biological process that combines information from multiple loci into one. This allows selection on a fleeting combination of interacting alleles at different loci to have a hereditary effect according to the combination's fitness. This proposed mechanism addresses the problem of how beneficial genetic interactions can evolve under selection, and also offers an intuitive explanation for the role of sex in evolution, which focuses on sex as the generator of genetic combinations. Importantly, it also implies that genetic variation that has appeared neutral through the lens of traditional theory can actually experience selection on interactions and thus has a much greater adaptive potential than previously considered. Empirical evidence for the proposed mechanism from both molecular evolution and evolution at the organismal level is discussed, and multiple predictions are offered by which it may be tested. This article was reviewed by Nigel Goldenfeld (nominated by Eugene V. Koonin), Jürgen Brosius and W. Ford Doolittle.
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USDA-ARS?s Scientific Manuscript database
Genetic marker effects and interactions are estimated with poor precision when minor marker allele frequencies are low. An Angus population was subjected to marker assisted selection for multiple years to increase divergent haplotype and minor marker allele frequencies to 1) estimate effect size an...
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ERIC Educational Resources Information Center
Iarocci, Grace; Yager, Jodi; Elfers, Theo
2007-01-01
Social competence is a complex human behaviour that is likely to involve a system of genes that interacts with a myriad of environmental risk and protective factors. The search for its genetic and environmental origins and influences is equally complex and will require a multidimensional conceptualization and multiple methods and levels of…
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van Schaik, J; Dekeukeleire, D; Kerth, G
2015-05-01
Host-parasite interactions are ubiquitous in nature. However, how parasite population genetic structure is shaped by the interaction between host and parasite life history remains understudied. Studies comparing multiple parasites infecting a single host can be used to investigate how different parasite life history traits interplay with host behaviour and life history. In this study, we used 10 newly developed microsatellite loci to investigate the genetic structure of a parasitic bat fly (Basilia nana). Its host, the Bechstein's bat (Myotis bechsteinii), has a social system and roosting behaviour that restrict opportunities for parasite transmission. We compared fly genetic structure to that of the host and another parasite, the wing-mite, Spinturnix bechsteini. We found little spatial or temporal genetic structure in B. nana, suggesting a large, stable population with frequent genetic exchange between fly populations from different bat colonies. This contrasts sharply with the genetic structure of the wing-mite, which is highly substructured between the same bat colonies as well as temporally unstable. Our results suggest that although host and parasite life history interact to yield similar transmission patterns in both parasite species, the level of gene flow and eventual spatiotemporal genetic stability is differentially affected. This can be explained by the differences in generation time and winter survival between the flies and wing-mites. Our study thus exemplifies that the population genetic structure of parasites on a single host can vary strongly as a result of how their individual life history characteristics interact with host behaviour and life history traits. © 2015 John Wiley & Sons Ltd.
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Tang, Hongwei; Wei, Peng; Duell, Eric J; Risch, Harvey A; Olson, Sara H; Bueno-de-Mesquita, H Bas; Gallinger, Steven; Holly, Elizabeth A; Petersen, Gloria M; Bracci, Paige M; McWilliams, Robert R; Jenab, Mazda; Riboli, Elio; Tjønneland, Anne; Boutron-Ruault, Marie Christine; Kaaks, Rudolf; Trichopoulos, Dimitrios; Panico, Salvatore; Sund, Malin; Peeters, Petra H M; Khaw, Kay-Tee; Amos, Christopher I; Li, Donghui
2014-01-01
Obesity and diabetes are potentially alterable risk factors for pancreatic cancer. Genetic factors that modify the associations of obesity and diabetes with pancreatic cancer have previously not been examined at the genome-wide level. Using genome-wide association studies (GWAS) genotype and risk factor data from the Pancreatic Cancer Case Control Consortium, we conducted a discovery study of 2,028 cases and 2,109 controls to examine gene-obesity and gene-diabetes interactions in relation to pancreatic cancer risk by using the likelihood-ratio test nested in logistic regression models and Ingenuity Pathway Analysis (IPA). After adjusting for multiple comparisons, a significant interaction of the chemokine signaling pathway with obesity (P = 3.29 × 10(-6)) and a near significant interaction of calcium signaling pathway with diabetes (P = 1.57 × 10(-4)) in modifying the risk of pancreatic cancer were observed. These findings were supported by results from IPA analysis of the top genes with nominal interactions. The major contributing genes to the two top pathways include GNGT2, RELA, TIAM1, and GNAS. None of the individual genes or single-nucleotide polymorphism (SNP) except one SNP remained significant after adjusting for multiple testing. Notably, SNP rs10818684 of the PTGS1 gene showed an interaction with diabetes (P = 7.91 × 10(-7)) at a false discovery rate of 6%. Genetic variations in inflammatory response and insulin resistance may affect the risk of obesity- and diabetes-related pancreatic cancer. These observations should be replicated in additional large datasets. A gene-environment interaction analysis may provide new insights into the genetic susceptibility and molecular mechanisms of obesity- and diabetes-related pancreatic cancer.
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Genomic and Epigenomic Insights into Nutrition and Brain Disorders
Dauncey, Margaret Joy
2013-01-01
Considerable evidence links many neuropsychiatric, neurodevelopmental and neurodegenerative disorders with multiple complex interactions between genetics and environmental factors such as nutrition. Mental health problems, autism, eating disorders, Alzheimer’s disease, schizophrenia, Parkinson’s disease and brain tumours are related to individual variability in numerous protein-coding and non-coding regions of the genome. However, genotype does not necessarily determine neurological phenotype because the epigenome modulates gene expression in response to endogenous and exogenous regulators, throughout the life-cycle. Studies using both genome-wide analysis of multiple genes and comprehensive analysis of specific genes are providing new insights into genetic and epigenetic mechanisms underlying nutrition and neuroscience. This review provides a critical evaluation of the following related areas: (1) recent advances in genomic and epigenomic technologies, and their relevance to brain disorders; (2) the emerging role of non-coding RNAs as key regulators of transcription, epigenetic processes and gene silencing; (3) novel approaches to nutrition, epigenetics and neuroscience; (4) gene-environment interactions, especially in the serotonergic system, as a paradigm of the multiple signalling pathways affected in neuropsychiatric and neurological disorders. Current and future advances in these four areas should contribute significantly to the prevention, amelioration and treatment of multiple devastating brain disorders. PMID:23503168
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Fully automated analysis of multi-resolution four-channel micro-array genotyping data
NASA Astrophysics Data System (ADS)
Abbaspour, Mohsen; Abugharbieh, Rafeef; Podder, Mohua; Tebbutt, Scott J.
2006-03-01
We present a fully-automated and robust microarray image analysis system for handling multi-resolution images (down to 3-micron with sizes up to 80 MBs per channel). The system is developed to provide rapid and accurate data extraction for our recently developed microarray analysis and quality control tool (SNP Chart). Currently available commercial microarray image analysis applications are inefficient, due to the considerable user interaction typically required. Four-channel DNA microarray technology is a robust and accurate tool for determining genotypes of multiple genetic markers in individuals. It plays an important role in the state of the art trend where traditional medical treatments are to be replaced by personalized genetic medicine, i.e. individualized therapy based on the patient's genetic heritage. However, fast, robust, and precise image processing tools are required for the prospective practical use of microarray-based genetic testing for predicting disease susceptibilities and drug effects in clinical practice, which require a turn-around timeline compatible with clinical decision-making. In this paper we have developed a fully-automated image analysis platform for the rapid investigation of hundreds of genetic variations across multiple genes. Validation tests indicate very high accuracy levels for genotyping results. Our method achieves a significant reduction in analysis time, from several hours to just a few minutes, and is completely automated requiring no manual interaction or guidance.
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Kurbasic, Azra; Poveda, Alaitz; Chen, Yan; Ågren, Åsa; Engberg, Elisabeth; Hu, Frank B.; Johansson, Ingegerd; Barroso, Ines; Brändström, Anders; Hallmans, Göran; Renström, Frida; Franks, Paul W.
2014-01-01
Most complex diseases have well-established genetic and non-genetic risk factors. In some instances, these risk factors are likely to interact, whereby their joint effects convey a level of risk that is either significantly more or less than the sum of these risks. Characterizing these gene-environment interactions may help elucidate the biology of complex diseases, as well as to guide strategies for their targeted prevention. In most cases, the detection of gene-environment interactions will require sample sizes in excess of those needed to detect the marginal effects of the genetic and environmental risk factors. Although many consortia have been formed, comprising multiple diverse cohorts to detect gene-environment interactions, few robust examples of such interactions have been discovered. This may be because combining data across studies, usually through meta-analysis of summary data from the contributing cohorts, is often a statistically inefficient approach for the detection of gene-environment interactions. Ideally, single, very large and well-genotyped prospective cohorts, with validated measures of environmental risk factor and disease outcomes should be used to study interactions. The presence of strong founder effects within those cohorts might further strengthen the capacity to detect novel genetic effects and gene-environment interactions. Access to accurate genealogical data would also aid in studying the diploid nature of the human genome, such as genomic imprinting (parent-of-origin effects). Here we describe two studies from northern Sweden (the GLACIER and VIKING studies) that fulfill these characteristics. PMID:25396097
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Kurbasic, Azra; Poveda, Alaitz; Chen, Yan; Agren, Asa; Engberg, Elisabeth; Hu, Frank B; Johansson, Ingegerd; Barroso, Ines; Brändström, Anders; Hallmans, Göran; Renström, Frida; Franks, Paul W
2014-12-01
Most complex diseases have well-established genetic and non-genetic risk factors. In some instances, these risk factors are likely to interact, whereby their joint effects convey a level of risk that is either significantly more or less than the sum of these risks. Characterizing these gene-environment interactions may help elucidate the biology of complex diseases, as well as to guide strategies for their targeted prevention. In most cases, the detection of gene-environment interactions will require sample sizes in excess of those needed to detect the marginal effects of the genetic and environmental risk factors. Although many consortia have been formed, comprising multiple diverse cohorts to detect gene-environment interactions, few robust examples of such interactions have been discovered. This may be because combining data across studies, usually through meta-analysis of summary data from the contributing cohorts, is often a statistically inefficient approach for the detection of gene-environment interactions. Ideally, single, very large and well-genotyped prospective cohorts, with validated measures of environmental risk factor and disease outcomes should be used to study interactions. The presence of strong founder effects within those cohorts might further strengthen the capacity to detect novel genetic effects and gene-environment interactions. Access to accurate genealogical data would also aid in studying the diploid nature of the human genome, such as genomic imprinting (parent-of-origin effects). Here we describe two studies from northern Sweden (the GLACIER and VIKING studies) that fulfill these characteristics.
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Bush, W S; McCauley, J L; DeJager, P L; Dudek, S M; Hafler, D A; Gibson, R A; Matthews, P M; Kappos, L; Naegelin, Y; Polman, C H; Hauser, S L; Oksenberg, J; Haines, J L; Ritchie, M D
2011-07-01
Gene-gene interactions are proposed as an important component of the genetic architecture of complex diseases, and are just beginning to be evaluated in the context of genome-wide association studies (GWAS). In addition to detecting epistasis, a benefit to interaction analysis is that it also increases power to detect weak main effects. We conducted a knowledge-driven interaction analysis of a GWAS of 931 multiple sclerosis (MS) trios to discover gene-gene interactions within established biological contexts. We identify heterogeneous signals, including a gene-gene interaction between CHRM3 (muscarinic cholinergic receptor 3) and MYLK (myosin light-chain kinase) (joint P=0.0002), an interaction between two phospholipase C-β isoforms, PLCβ1 and PLCβ4 (joint P=0.0098), and a modest interaction between ACTN1 (actinin alpha 1) and MYH9 (myosin heavy chain 9) (joint P=0.0326), all localized to calcium-signaled cytoskeletal regulation. Furthermore, we discover a main effect (joint P=5.2E-5) previously unidentified by single-locus analysis within another related gene, SCIN (scinderin), a calcium-binding cytoskeleton regulatory protein. This work illustrates that knowledge-driven interaction analysis of GWAS data is a feasible approach to identify new genetic effects. The results of this study are among the first gene-gene interactions and non-immune susceptibility loci for MS. Further, the implicated genes cluster within inter-related biological mechanisms that suggest a neurodegenerative component to MS.
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Recent molecular genetic studies and methodological issues in suicide research.
Tsai, Shih-Jen; Hong, Chen-Jee; Liou, Ying-Jay
2011-06-01
Suicide behavior (SB) spans a spectrum ranging from suicidal ideation to suicide attempts and completed suicide. Strong evidence suggests a genetic susceptibility to SB, including familial heritability and common occurrence in twins. This review addresses recent molecular genetic studies in SB that include case-control association, genome gene-expression microarray, and genome-wide association (GWA). This work also reviews epigenetics in SB and pharmacogenetic studies of antidepressant-induced suicide. SB fulfills criteria for a complex genetic phenotype in which environmental factors interact with multiple genes to influence susceptibility. So far, case-control association approaches are still the mainstream in SB genetic studies, although whole genome gene-expression microarray and GWA studies have begun to emerge in recent years. Genetic association studies have suggested several genes (e.g., serotonin transporter, tryptophan hydroxylase 2, and brain-derived neurotrophic factor) related to SB, but not all reports support these findings. The case-control approach while useful is limited by present knowledge of disease pathophysiology. Genome-wide studies of gene expression and genetic variation are not constrained by our limited knowledge. However, the explanatory power and path to clinical translation of risk estimates for common variants reported in genome-wide association studies remain unclear because of the presence of rare and structural genetic variation. As whole genome sequencing becomes increasingly widespread, available genomic information will no longer be the limiting factor in applying genetics to clinical medicine. These approaches provide exciting new avenues to identify new candidate genes for SB genetic studies. The other limitation of genetic association is the lack of a consistent definition of the SB phenotype among studies, an inconsistency that hampers the comparability of the studies and data pooling. In summary, SB involves multiple genes interacting with non-genetic factors. A better understanding of the SB genes by combining whole genome approaches with case-control association studies, may potentially lead to developing effective screening, prevention, and management of SB. Copyright © 2010 Elsevier Inc. All rights reserved.
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Interactions within the MHC contribute to the genetic architecture of celiac disease.
Goudey, Benjamin; Abraham, Gad; Kikianty, Eder; Wang, Qiao; Rawlinson, Dave; Shi, Fan; Haviv, Izhak; Stern, Linda; Kowalczyk, Adam; Inouye, Michael
2017-01-01
Interaction analysis of GWAS can detect signal that would be ignored by single variant analysis, yet few robust interactions in humans have been detected. Recent work has highlighted interactions in the MHC region between known HLA risk haplotypes for various autoimmune diseases. To better understand the genetic interactions underlying celiac disease (CD), we have conducted exhaustive genome-wide scans for pairwise interactions in five independent CD case-control studies, using a rapid model-free approach to examine over 500 billion SNP pairs in total. We found 14 independent interaction signals within the MHC region that achieved stringent replication criteria across multiple studies and were independent of known CD risk HLA haplotypes. The strongest independent CD interaction signal corresponded to genes in the HLA class III region, in particular PRRC2A and GPANK1/C6orf47, which are known to contain variants for non-Hodgkin's lymphoma and early menopause, co-morbidities of celiac disease. Replicable evidence for statistical interaction outside the MHC was not observed. Both within and between European populations, we observed striking consistency of two-locus models and model distribution. Within the UK population, models of CD based on both interactions and additive single-SNP effects increased explained CD variance by approximately 1% over those of single SNPs. The interactions signal detected across the five cohorts indicates the presence of novel associations in the MHC region that cannot be detected using additive models. Our findings have implications for the determination of genetic architecture and, by extension, the use of human genetics for validation of therapeutic targets.
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Turner, Leslie M; Harr, Bettina
2014-01-01
Mapping hybrid defects in contact zones between incipient species can identify genomic regions contributing to reproductive isolation and reveal genetic mechanisms of speciation. The house mouse features a rare combination of sophisticated genetic tools and natural hybrid zones between subspecies. Male hybrids often show reduced fertility, a common reproductive barrier between incipient species. Laboratory crosses have identified sterility loci, but each encompasses hundreds of genes. We map genetic determinants of testis weight and testis gene expression using offspring of mice captured in a hybrid zone between M. musculus musculus and M. m. domesticus. Many generations of admixture enables high-resolution mapping of loci contributing to these sterility-related phenotypes. We identify complex interactions among sterility loci, suggesting multiple, non-independent genetic incompatibilities contribute to barriers to gene flow in the hybrid zone. DOI: http://dx.doi.org/10.7554/eLife.02504.001 PMID:25487987
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Genetics Home Reference: familial pityriasis rubra pilaris
... interacting proteins known as nuclear factor-kappa-B (NF-κB). NF-κB regulates the activity of multiple genes, including ... but it is particularly abundant in the skin. NF-κB signaling appears to play an important role ...
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Genetic Modification of the Relationship between Parental Rejection and Adolescent Alcohol Use.
Stogner, John M; Gibson, Chris L
2016-07-01
Parenting practices are associated with adolescents' alcohol consumption, however not all youth respond similarly to challenging family situations and harsh environments. This study examines the relationship between perceived parental rejection and adolescent alcohol use, and specifically evaluates whether youth who possess greater genetic sensitivity to their environment are more susceptible to negative parental relationships. Analyzing data from the National Longitudinal Study of Adolescent Health, we estimated a series of regression models predicting alcohol use during adolescence. A multiplicative interaction term between parental rejection and a genetic index was constructed to evaluate this potential gene-environment interaction. Results from logistic regression analyses show a statistically significant gene-environment interaction predicting alcohol use. The relationship between parental rejection and alcohol use was moderated by the genetic index, indicating that adolescents possessing more 'risk alleles' for five candidate genes were affected more by stressful parental relationships. Feelings of parental rejection appear to influence the alcohol use decisions of youth, but they do not do so equally for all. Higher scores on the constructed genetic sensitivity measure are related to increased susceptibility to negative parental relationships. © The Author 2016. Medical Council on Alcohol and Oxford University Press. All rights reserved.
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Akay, Alper; Craig, Ashley; Lehrbach, Nicolas; Larance, Mark; Pourkarimi, Ehsan; Wright, Jane E.; Lamond, Angus; Miska, Eric; Gartner, Anton
2013-01-01
Messenger RNA translation is regulated by RNA-binding proteins and small non-coding RNAs called microRNAs. Even though we know the majority of RNA-binding proteins and microRNAs that regulate messenger RNA expression, evidence of interactions between the two remain elusive. The role of the RNA-binding protein GLD-1 as a translational repressor is well studied during Caenorhabditis elegans germline development and maintenance. Possible functions of GLD-1 during somatic development and the mechanism of how GLD-1 acts as a translational repressor are not known. Its human homologue, quaking (QKI), is essential for embryonic development. Here, we report that the RNA-binding protein GLD-1 in C. elegans affects multiple microRNA pathways and interacts with proteins required for microRNA function. Using genome-wide RNAi screening, we found that nhl-2 and vig-1, two known modulators of miRNA function, genetically interact with GLD-1. gld-1 mutations enhance multiple phenotypes conferred by mir-35 and let-7 family mutants during somatic development. We used stable isotope labelling with amino acids in cell culture to globally analyse the changes in the proteome conferred by let-7 and gld-1 during animal development. We identified the histone mRNA-binding protein CDL-1 to be, in part, responsible for the phenotypes observed in let-7 and gld-1 mutants. The link between GLD-1 and miRNA-mediated gene regulation is further supported by its biochemical interaction with ALG-1, CGH-1 and PAB-1, proteins implicated in miRNA regulation. Overall, we have uncovered genetic and biochemical interactions between GLD-1 and miRNA pathways. PMID:24258276
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Demographic, genetic, and environmental factors that modify disease course.
Marrie, Ruth Ann
2011-05-01
As with susceptibility to disease, it is likely that multiple factors interact to influence the phenotype of multiple sclerosis and long-term disease outcomes. Such factors may include genetic factors, socioeconomic status, comorbid diseases, and health behaviors, as well as environmental exposures. An improved understanding of the influence of these factors on disease course may reap several benefits, such as improved prognostication, allowing us to tailor disease management with respect to intensity of disease-modifying therapies and changes in specific health behaviors, in the broad context of coexisting health issues. Such information can facilitate appropriately adjusted comparisons within and between populations. Elucidation of these factors will require careful study of well-characterized populations in which the roles of multiple factors are considered simultaneously. Copyright © 2011 Elsevier Inc. All rights reserved.
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Class II HLA interactions modulate genetic risk for multiple sclerosis
Dilthey, Alexander T; Xifara, Dionysia K; Ban, Maria; Shah, Tejas S; Patsopoulos, Nikolaos A; Alfredsson, Lars; Anderson, Carl A; Attfield, Katherine E; Baranzini, Sergio E; Barrett, Jeffrey; Binder, Thomas M C; Booth, David; Buck, Dorothea; Celius, Elisabeth G; Cotsapas, Chris; D’Alfonso, Sandra; Dendrou, Calliope A; Donnelly, Peter; Dubois, Bénédicte; Fontaine, Bertrand; Fugger, Lars; Goris, An; Gourraud, Pierre-Antoine; Graetz, Christiane; Hemmer, Bernhard; Hillert, Jan; Kockum, Ingrid; Leslie, Stephen; Lill, Christina M; Martinelli-Boneschi, Filippo; Oksenberg, Jorge R; Olsson, Tomas; Oturai, Annette; Saarela, Janna; Søndergaard, Helle Bach; Spurkland, Anne; Taylor, Bruce; Winkelmann, Juliane; Zipp, Frauke; Haines, Jonathan L; Pericak-Vance, Margaret A; Spencer, Chris C A; Stewart, Graeme; Hafler, David A; Ivinson, Adrian J; Harbo, Hanne F; Hauser, Stephen L; De Jager, Philip L; Compston, Alastair; McCauley, Jacob L; Sawcer, Stephen; McVean, Gil
2016-01-01
Association studies have greatly refined the understanding of how variation within the human leukocyte antigen (HLA) genes influences risk of multiple sclerosis. However, the extent to which major effects are modulated by interactions is poorly characterized. We analyzed high-density SNP data on 17,465 cases and 30,385 controls from 11 cohorts of European ancestry, in combination with imputation of classical HLA alleles, to build a high-resolution map of HLA genetic risk and assess the evidence for interactions involving classical HLA alleles. Among new and previously identified class II risk alleles (HLA-DRB1*15:01, HLA-DRB1*13:03, HLA-DRB1*03:01, HLA-DRB1*08:01 and HLA-DQB1*03:02) and class I protective alleles (HLA-A*02:01, HLA-B*44:02, HLA-B*38:01 and HLA-B*55:01), we find evidence for two interactions involving pairs of class II alleles: HLA-DQA1*01:01–HLA-DRB1*15:01 and HLA-DQB1*03:01–HLA-DQB1*03:02. We find no evidence for interactions between classical HLA alleles and non-HLA risk-associated variants and estimate a minimal effect of polygenic epistasis in modulating major risk alleles. PMID:26343388
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HaloTag Technology: A Versatile Platform for Biomedical Applications
2015-01-01
Exploration of protein function and interaction is critical for discovering links among genomics, proteomics, and disease state; yet, the immense complexity of proteomics found in biological systems currently limits our investigational capacity. Although affinity and autofluorescent tags are widely employed for protein analysis, these methods have been met with limited success because they lack specificity and require multiple fusion tags and genetic constructs. As an alternative approach, the innovative HaloTag protein fusion platform allows protein function and interaction to be comprehensively analyzed using a single genetic construct with multiple capabilities. This is accomplished using a simplified process, in which a variable HaloTag ligand binds rapidly to the HaloTag protein (usually linked to the protein of interest) with high affinity and specificity. In this review, we examine all current applications of the HaloTag technology platform for biomedical applications, such as the study of protein isolation and purification, protein function, protein–protein and protein–DNA interactions, biological assays, in vitro cellular imaging, and in vivo molecular imaging. In addition, novel uses of the HaloTag platform are briefly discussed along with potential future applications. PMID:25974629
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Individual Differences in Pain: Understanding the Mosaic that Makes Pain Personal
Fillingim, Roger B.
2016-01-01
The experience of pain is characterized by tremendous inter-individual variability. Multiple biological and psychosocial variables contribute to these individual differences in pain, including demographic variables, genetic factors, and psychosocial processes. For example, sex, age and ethnic group differences in the prevalence of chronic pain conditions have been widely reported. Moreover, these demographic factors have been associated with responses to experimentally-induced pain. Similarly, both genetic and psychosocial factors contribute to clinical and experimental pain responses. Importantly, these different biopsychosocial influences interact with each other in complex ways to sculpt the experience of pain. Some genetic associations with pain have been found to vary across sex and ethnic group. Moreover, genetic factors also interact with psychosocial factors, including stress and pain catastrophizing, to influence pain. The individual and combined influences of these biological and psychosocial variables results in a unique mosaic of factors that contributes pain in each individual. Understanding these mosaics is critically important in order to provide optimal pain treatment, and future research to further elucidate the nature of these biopsychosocial interactions is needed in order to provide more informed and personalized pain care. PMID:27902569
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Inherited genetic variants associated with occurrence of multiple primary melanoma.
Gibbs, David C; Orlow, Irene; Kanetsky, Peter A; Luo, Li; Kricker, Anne; Armstrong, Bruce K; Anton-Culver, Hoda; Gruber, Stephen B; Marrett, Loraine D; Gallagher, Richard P; Zanetti, Roberto; Rosso, Stefano; Dwyer, Terence; Sharma, Ajay; La Pilla, Emily; From, Lynn; Busam, Klaus J; Cust, Anne E; Ollila, David W; Begg, Colin B; Berwick, Marianne; Thomas, Nancy E
2015-06-01
Recent studies, including genome-wide association studies, have identified several putative low-penetrance susceptibility loci for melanoma. We sought to determine their generalizability to genetic predisposition for multiple primary melanoma in the international population-based Genes, Environment, and Melanoma (GEM) Study. GEM is a case-control study of 1,206 incident cases of multiple primary melanoma and 2,469 incident first primary melanoma participants as the control group. We investigated the odds of developing multiple primary melanoma for 47 SNPs from 21 distinct genetic regions previously reported to be associated with melanoma. ORs and 95% confidence intervals were determined using logistic regression models adjusted for baseline features (age, sex, age by sex interaction, and study center). We investigated univariable models and built multivariable models to assess independent effects of SNPs. Eleven SNPs in 6 gene neighborhoods (TERT/CLPTM1L, TYRP1, MTAP, TYR, NCOA6, and MX2) and a PARP1 haplotype were associated with multiple primary melanoma. In a multivariable model that included only the most statistically significant findings from univariable modeling and adjusted for pigmentary phenotype, back nevi, and baseline features, we found TERT/CLPTM1L rs401681 (P = 0.004), TYRP1 rs2733832 (P = 0.006), MTAP rs1335510 (P = 0.0005), TYR rs10830253 (P = 0.003), and MX2 rs45430 (P = 0.008) to be significantly associated with multiple primary melanoma, while NCOA6 rs4911442 approached significance (P = 0.06). The GEM Study provides additional evidence for the relevance of these genetic regions to melanoma risk and estimates the magnitude of the observed genetic effect on development of subsequent primary melanoma. ©2015 American Association for Cancer Research.
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Inherited genetic variants associated with occurrence of multiple primary melanoma
Gibbs, David C.; Orlow, Irene; Kanetsky, Peter A.; Luo, Li; Kricker, Anne; Armstrong, Bruce K.; Anton-Culver, Hoda; Gruber, Stephen B.; Marrett, Loraine D.; Gallagher, Richard P.; Zanetti, Roberto; Rosso, Stefano; Dwyer, Terence; Sharma, Ajay; La Pilla, Emily; From, Lynn; Busam, Klaus J.; Cust, Anne E.; Ollila, David W.; Begg, Colin B.; Berwick, Marianne; Thomas, Nancy E.
2015-01-01
Recent studies including genome-wide association studies have identified several putative low-penetrance susceptibility loci for melanoma. We sought to determine their generalizability to genetic predisposition for multiple primary melanoma in the international population-based Genes, Environment, and Melanoma (GEM) Study. GEM is a case-control study of 1,206 incident cases of multiple primary melanoma and 2,469 incident first primary melanoma participants as the control group. We investigated the odds of developing multiple primary melanoma for 47 single nucleotide polymorphisms (SNP) from 21 distinct genetic regions previously reported to be associated with melanoma. ORs and 95% CIs were determined using logistic regression models adjusted for baseline features (age, sex, age by sex interaction, and study center). We investigated univariable models and built multivariable models to assess independent effects of SNPs. Eleven SNPs in 6 gene neighborhoods (TERT/CLPTM1L, TYRP1, MTAP, TYR, NCOA6, and MX2) and a PARP1 haplotype were associated with multiple primary melanoma. In a multivariable model that included only the most statistically significant findings from univariable modeling and adjusted for pigmentary phenotype, back nevi, and baseline features, we found TERT/CLPTM1L rs401681 (P = 0.004), TYRP1 rs2733832 (P = 0.006), MTAP rs1335510 (P = 0.0005), TYR rs10830253 (P = 0.003), and MX2 rs45430 (P = 0.008) to be significantly associated with multiple primary melanoma while NCOA6 rs4911442 approached significance (P = 0.06). The GEM study provides additional evidence for the relevance of these genetic regions to melanoma risk and estimates the magnitude of the observed genetic effect on development of subsequent primary melanoma. PMID:25837821
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Tuni, Cristina; Goodacre, Sara; Bechsgaard, Jesper; Bilde, Trine
2012-01-01
Background Polyandry is widespread throughout the animal kingdom. In the absence of direct benefits of mating with different males, the underlying basis for polyandry is enigmatic because it can carry considerable costs such as elevated exposure to sexual diseases, physical injury or other direct fitness costs. Such costs may be balanced by indirect genetic benefits to the offspring of polyandrous females. We investigated polyandry and patterns of parentage in the spider Stegodyphus lineatus. This species experiences relatively high levels of inbreeding as a result of its spatial population structure, philopatry and limited male mating dispersal. Polyandry may provide an opportunity for post mating inbreeding avoidance that reduces the risk of genetic incompatibilities arising from incestuous matings. However, multiple mating carries direct fitness costs to females suggesting that genetic benefits must be substantial to counter direct costs. Methodology/Principal Findings Genetic parentage analyses in two populations from Israel and a Greek island, showed mixed-brood parentage in approximately 50% of the broods. The number of fathers ranged from 1–2 indicating low levels of multiple parentage and there was no evidence for paternity bias in mixed-broods from both populations. Microsatellite loci variation suggested limited genetic variation within populations, especially in the Greek island population. Relatedness estimates among females in the maternal generation and potentially interacting individuals were substantial indicating full-sib and half-sib relationships. Conclusions/Significance Three lines of evidence indicate limited potential to obtain substantial genetic benefits in the form of reduced inbreeding. The relatively low frequency of multiple parentage together with low genetic variation among potential mates and the elevated risk of mating among related individuals as corroborated by our genetic data suggest that there are limited actual outbreeding opportunities for polyandrous females. Polyandry in S. lineatus is thus unlikely to be maintained through adaptive female choice. PMID:22235316
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Genetic Advances in Autism: Heterogeneity and Convergence on Shared Pathways
Bill, Brent R.; Geschwind, Daniel H.
2009-01-01
The autism spectrum disorders (ASD) are a heterogeneous set of developmental disorders characterized at their core by deficits in social interaction and communication. Current psychiatric nosology groups this broad set of disorders with strong genetic liability and multiple etiologies into the same diagnostic category. This heterogeneity has challenged genetic analyses. But shared patient resources, genomic technologies, more refined phenotypes, and novel computational approaches have begun to yield dividends in defining the genetic mechanisms at work. Over the last five years, a large number of autism susceptibility loci have emerged, redefining our notion of autism’s etiologies, and reframing how we think about ASD. PMID:19477629
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Moonesinghe, Ramal; Ioannidis, John P A; Flanders, W Dana; Yang, Quanhe; Truman, Benedict I; Khoury, Muin J
2012-08-01
Genome-wide association studies have identified multiple genetic susceptibility variants to several complex human diseases. However, risk-genotype frequency at loci showing robust associations might differ substantially among different populations. In this paper, we present methods to assess the contribution of genetic variants to the difference in the incidence of disease between different population groups for different scenarios. We derive expressions for the contribution of a single genetic variant, multiple genetic variants, and the contribution of the joint effect of a genetic variant and an environmental factor to the difference in the incidence of disease. The contribution of genetic variants to the difference in incidence increases with increasing difference in risk-genotype frequency, but declines with increasing difference in incidence between the two populations. The contribution of genetic variants also increases with increasing relative risk and the contribution of joint effect of genetic and environmental factors increases with increasing relative risk of the gene-environmental interaction. The contribution of genetic variants to the difference in incidence between two populations can be expressed as a function of the population attributable risks of the genetic variants in the two populations. The contribution of a group of genetic variants to the disparity in incidence of disease could change considerably by adding one more genetic variant to the group. Any estimate of genetic contribution to the disparity in incidence of disease between two populations at this stage seems to be an elusive goal.
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Moonesinghe, Ramal; Ioannidis, John PA; Flanders, W Dana; Yang, Quanhe; Truman, Benedict I; Khoury, Muin J
2012-01-01
Genome-wide association studies have identified multiple genetic susceptibility variants to several complex human diseases. However, risk-genotype frequency at loci showing robust associations might differ substantially among different populations. In this paper, we present methods to assess the contribution of genetic variants to the difference in the incidence of disease between different population groups for different scenarios. We derive expressions for the contribution of a single genetic variant, multiple genetic variants, and the contribution of the joint effect of a genetic variant and an environmental factor to the difference in the incidence of disease. The contribution of genetic variants to the difference in incidence increases with increasing difference in risk-genotype frequency, but declines with increasing difference in incidence between the two populations. The contribution of genetic variants also increases with increasing relative risk and the contribution of joint effect of genetic and environmental factors increases with increasing relative risk of the gene–environmental interaction. The contribution of genetic variants to the difference in incidence between two populations can be expressed as a function of the population attributable risks of the genetic variants in the two populations. The contribution of a group of genetic variants to the disparity in incidence of disease could change considerably by adding one more genetic variant to the group. Any estimate of genetic contribution to the disparity in incidence of disease between two populations at this stage seems to be an elusive goal. PMID:22333905
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Pervasive sharing of genetic effects in autoimmune disease.
Cotsapas, Chris; Voight, Benjamin F; Rossin, Elizabeth; Lage, Kasper; Neale, Benjamin M; Wallace, Chris; Abecasis, Gonçalo R; Barrett, Jeffrey C; Behrens, Timothy; Cho, Judy; De Jager, Philip L; Elder, James T; Graham, Robert R; Gregersen, Peter; Klareskog, Lars; Siminovitch, Katherine A; van Heel, David A; Wijmenga, Cisca; Worthington, Jane; Todd, John A; Hafler, David A; Rich, Stephen S; Daly, Mark J
2011-08-01
Genome-wide association (GWA) studies have identified numerous, replicable, genetic associations between common single nucleotide polymorphisms (SNPs) and risk of common autoimmune and inflammatory (immune-mediated) diseases, some of which are shared between two diseases. Along with epidemiological and clinical evidence, this suggests that some genetic risk factors may be shared across diseases-as is the case with alleles in the Major Histocompatibility Locus. In this work we evaluate the extent of this sharing for 107 immune disease-risk SNPs in seven diseases: celiac disease, Crohn's disease, multiple sclerosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes. We have developed a novel statistic for Cross Phenotype Meta-Analysis (CPMA) which detects association of a SNP to multiple, but not necessarily all, phenotypes. With it, we find evidence that 47/107 (44%) immune-mediated disease risk SNPs are associated to multiple-but not all-immune-mediated diseases (SNP-wise P(CPMA)<0.01). We also show that distinct groups of interacting proteins are encoded near SNPs which predispose to the same subsets of diseases; we propose these as the mechanistic basis of shared disease risk. We are thus able to leverage genetic data across diseases to construct biological hypotheses about the underlying mechanism of pathogenesis.
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Molecular and genetic epidemiology of cancer in low- and medium-income countries.
Malhotra, Jyoti
2014-01-01
Genetic and molecular factors can play an important role in an individual's cancer susceptibility and response to carcinogen exposure. Cancer susceptibility and response to carcinogen exposure can be either through inheritance of high penetrance but rare germline mutations that constitute heritable cancer syndromes, or it can be inherited as common genetic variations or polymorphisms that are associated with low to moderate risk for development of cancer. These polymorphisms can interact with environmental exposures and can influence an individual's cancer risk through multiple pathways, including affecting the rate of metabolism of carcinogens or the immune response to these toxins. Thus, these genetic polymorphisms can account for some of the geographical differences seen in cancer prevalence between different populations. This review explores the role of molecular epidemiology in the field of cancer prevention and control in low- and medium-income countries. Using data from Human Genome Project and HapMap Project, genome-wide association studies have been able to identify multiple susceptibility loci for different cancers. The field of genetic and molecular epidemiology has been further revolutionized by the discovery of newer, faster, and more efficient DNA-sequencing technologies including next-generation sequencing. The new DNA-sequencing technologies can play an important role in planning and implementation of cancer prevention and screening strategies. More research is needed in this area, especially in investigating new biomarkers and measuring gene-environment interactions. Copyright © 2014 Icahn School of Medicine at Mount Sinai. Published by Elsevier Inc. All rights reserved.
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Interaction-based evolution: how natural selection and nonrandom mutation work together
2013-01-01
Background The modern evolutionary synthesis leaves unresolved some of the most fundamental, long-standing questions in evolutionary biology: What is the role of sex in evolution? How does complex adaptation evolve? How can selection operate effectively on genetic interactions? More recently, the molecular biology and genomics revolutions have raised a host of critical new questions, through empirical findings that the modern synthesis fails to explain: for example, the discovery of de novo genes; the immense constructive role of transposable elements in evolution; genetic variance and biochemical activity that go far beyond what traditional natural selection can maintain; perplexing cases of molecular parallelism; and more. Presentation of the hypothesis Here I address these questions from a unified perspective, by means of a new mechanistic view of evolution that offers a novel connection between selection on the phenotype and genetic evolutionary change (while relying, like the traditional theory, on natural selection as the only source of feedback on the fit between an organism and its environment). I hypothesize that the mutation that is of relevance for the evolution of complex adaptation—while not Lamarckian, or “directed” to increase fitness—is not random, but is instead the outcome of a complex and continually evolving biological process that combines information from multiple loci into one. This allows selection on a fleeting combination of interacting alleles at different loci to have a hereditary effect according to the combination’s fitness. Testing and implications of the hypothesis This proposed mechanism addresses the problem of how beneficial genetic interactions can evolve under selection, and also offers an intuitive explanation for the role of sex in evolution, which focuses on sex as the generator of genetic combinations. Importantly, it also implies that genetic variation that has appeared neutral through the lens of traditional theory can actually experience selection on interactions and thus has a much greater adaptive potential than previously considered. Empirical evidence for the proposed mechanism from both molecular evolution and evolution at the organismal level is discussed, and multiple predictions are offered by which it may be tested. Reviewers This article was reviewed by Nigel Goldenfeld (nominated by Eugene V. Koonin), Jürgen Brosius and W. Ford Doolittle. PMID:24139515
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Multivariate Methods for Meta-Analysis of Genetic Association Studies.
Dimou, Niki L; Pantavou, Katerina G; Braliou, Georgia G; Bagos, Pantelis G
2018-01-01
Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.
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Manier, Mollie K; Arnold, Stevan J
2006-12-07
Identifying ecological factors associated with population genetic differentiation is important for understanding microevolutionary processes and guiding the management of threatened populations. We identified ecological correlates of several population genetic parameters for three interacting species (two garter snakes and an anuran) that occupy a common landscape. Using multiple regression analysis, we found that species interactions were more important in explaining variation in population genetic parameters than habitat and nearest-neighbour characteristics. Effective population size was best explained by census size, while migration was associated with differences in species abundance. In contrast, genetic distance was poorly explained by the ecological correlates that we tested, but geographical distance was prominent in models for all species. We found substantially different population dynamics for the prey species relative to the two predators, characterized by larger effective sizes, lower gene flow and a state of migration-drift equilibrium. We also identified an escarpment formed by a series of block faults that serves as a barrier to dispersal for the predators. Our results suggest that successful landscape-level management should incorporate genetic and ecological data for all relevant species, because even closely associated species can exhibit very different population genetic dynamics on the same landscape.
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Suffering in silence: why a developmental psychopathology perspective on selective mutism is needed.
Cohan, Sharon L; Price, Joseph M; Stein, Murray B
2006-08-01
A developmental psychopathology perspective is offered in an effort to organize the existing literature regarding the etiology of selective mutism (SM), a relatively rare disorder in which a child consistently fails to speak in 1 or more social settings (e.g., school) despite speaking normally in other settings (e.g., home). Following a brief description of the history, prevalence, and course of the disorder, multiple pathways to the development of SM are discussed, with a focus on the various genetic, temperamental, psychological, and social/environmental systems that may be important in conceptualizing this unusual childhood disorder. The authors propose that SM develops due to a series of complex interactions among the various systems reviewed (e.g., a strong genetic loading for anxiety interacts with an existing communication disorder, resulting in heightened sensitivity to verbal interactions and mutism in some settings). Suggestions are provided for future longitudinal, twin/adoption, molecular genetic, and neuroimaging studies that would be particularly helpful in testing the pathways perspective on SM.
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Inferring genetic interactions via a nonlinear model and an optimization algorithm.
Chen, Chung-Ming; Lee, Chih; Chuang, Cheng-Long; Wang, Chia-Chang; Shieh, Grace S
2010-02-26
Biochemical pathways are gradually becoming recognized as central to complex human diseases and recently genetic/transcriptional interactions have been shown to be able to predict partial pathways. With the abundant information made available by microarray gene expression data (MGED), nonlinear modeling of these interactions is now feasible. Two of the latest advances in nonlinear modeling used sigmoid models to depict transcriptional interaction of a transcription factor (TF) for a target gene, but do not model cooperative or competitive interactions of several TFs for a target. An S-shape model and an optimization algorithm (GASA) were developed to infer genetic interactions/transcriptional regulation of several genes simultaneously using MGED. GASA consists of a genetic algorithm (GA) and a simulated annealing (SA) algorithm, which is enhanced by a steepest gradient descent algorithm to avoid being trapped in local minimum. Using simulated data with various degrees of noise, we studied how GASA with two model selection criteria and two search spaces performed. Furthermore, GASA was shown to outperform network component analysis, the time series network inference algorithm (TSNI), GA with regular GA (GAGA) and GA with regular SA. Two applications are demonstrated. First, GASA is applied to infer a subnetwork of human T-cell apoptosis. Several of the predicted interactions are supported by the literature. Second, GASA was applied to infer the transcriptional factors of 34 cell cycle regulated targets in S. cerevisiae, and GASA performed better than one of the latest advances in nonlinear modeling, GAGA and TSNI. Moreover, GASA is able to predict multiple transcription factors for certain targets, and these results coincide with experiments confirmed data in YEASTRACT. GASA is shown to infer both genetic interactions and transcriptional regulatory interactions well. In particular, GASA seems able to characterize the nonlinear mechanism of transcriptional regulatory interactions (TIs) in yeast, and may be applied to infer TIs in other organisms. The predicted genetic interactions of a subnetwork of human T-cell apoptosis coincide with existing partial pathways, suggesting the potential of GASA on inferring biochemical pathways.
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Harlid, Sophia; Butt, Salma; Ivarsson, Malin I L; Eyfjörd, Jorunn Erla; Lenner, Per; Manjer, Jonas; Dillner, Joakim; Carlson, Joyce
2012-06-22
Breast cancer today has many established risk factors, both genetic and environmental, but these risk factors by themselves explain only part of the total cancer incidence. We have investigated potential interactions between certain known genetic and phenotypic risk factors, specifically nine single nucleotide polymorphisms (SNPs) and height, body mass index (BMI) and hormone replacement therapy (HRT). We analyzed samples from three different study populations: two prospectively followed Swedish cohorts and one Icelandic case-control study. Totally 2884 invasive breast cancer cases and 4508 controls were analysed in the study. Genotypes were determined using Mass spectrometry-Maldi-TOF and phenotypic variables were derived from measurements and/or questionnaires. Odds Ratios and 95% confidence intervals were calculated using unconditional logistic regression with the inclusion of an interaction term in the logistic regression model. One SNP (rs851987 in ESR1) tended to interact with height, with an increasingly protective effect of the major allele in taller women (p = 0.007) and rs13281615 (on 8q24) tended to confer risk only in non users of HRT (p-for interaction = 0.03). There were no significant interactions after correction for multiple testing. We conclude that much larger sample sets would be necessary to demonstrate interactions between low-risk genetic polymorphisms and the phenotypic variables height, BMI and HRT on the risk for breast cancer. However the present hypothesis-generating study has identified tendencies that would be of interest to evaluate for gene-environment interactions in independent materials.
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Riveira-Munoz, Eva; He, Su-Min; Escaramís, Georgia; Stuart, Philip E; Hüffmeier, Ulrike; Lee, Catherine; Kirby, Brian; Oka, Akira; Giardina, Emiliano; Liao, Wilson; Bergboer, Judith; Kainu, Kati; de Cid, Rafael; Munkhbat, Batmunkh; Zeeuwen, Patrick L J M; Armour, John A L; Poon, Annie; Mabuchi, Tomotaka; Ozawa, Akira; Zawirska, Agnieszka; Burden, David A; Barker, Jonathan N; Capon, Francesca; Traupe, Heiko; Sun, Liang-Dan; Cui, Yong; Yin, Xian-Yong; Chen, Gang; Lim, Henry; Nair, Rajan; Voorhess, John; Tejasvi, Trilokraj; Pujol, Ramón; Munkhtuvshin, Namid; Fischer, Judith; Kere, Juha; Schalkwijk, Joost; Bowcock, Anne; Kwok, Pui-Yan; Novelli, Giuseppe; Inoko, Hidetoshi; Ryan, Anthony W; Trembath, Richard C; Reis, André; Zhang, Xue-Jun; Elder, James T; Estivill, Xavier
2012-01-01
A multicenter meta-analysis including data from 9389 psoriasis patients and 9477 control subjects was performed to investigate the contribution of the deletion of genes LCE3C and LCE3B, involved in skin barrier defense, to psoriasis susceptibility in different populations. The study confirms that the deletion of LCE3C and LCE3B is a common genetic factor for susceptibility to psoriasis in European populations [OROverall = 1.21 (1.15–1.27)], and for the first time directly demonstrated the deletion's association with psoriasis in [Chinese OR = 1.27 (1.16–1.34); Mongolian OR = 2.08 (1.44–2.99)] populations. The analysis of the HLA-Cw6 locus showed significant differences in the epistatic interaction with the LCE3C and LCE3B deletion in at least some European populations, indicating epistatic effects between these two major genetic contributors to psoriasis. The study highlights the value of examining genetic risk factors in multiple populations to identify genetic interactions, and indicates the need of further studies to understand the interaction of the skin barrier and the immune system in susceptibility to psoriasis. PMID:21107349
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Joint Associations of Diet, Lifestyle, and Genes with Age-Related Macular Degeneration.
Meyers, Kristin J; Liu, Zhe; Millen, Amy E; Iyengar, Sudha K; Blodi, Barbara A; Johnson, Elizabeth; Snodderly, D Max; Klein, Michael L; Gehrs, Karen M; Tinker, Lesley; Sarto, Gloria E; Robinson, Jennifer; Wallace, Robert B; Mares, Julie A
2015-11-01
Unhealthy lifestyles have been associated with increased odds for age-related macular degeneration (AMD). Whether this association is modified by genetic risk for AMD is unknown and was investigated. Interactions between healthy lifestyles AMD risk genotypes were studied in relation to the prevalence of AMD, assessed 6 years later. Women 50 to 79 years of age in the Carotenoids in Age-Related Eye Disease Study with exposure and AMD data (n=1663). Healthy lifestyle scores (0-6 points) were assigned based on Healthy Eating Index scores, physical activity (metabolic equivalent of task hours/week), and smoking pack years assessed in 1994 and 1998. Genetic risk was based on Y402H in complement factor H (CFH) and A69S in age-related maculopathy susceptibility locus 2 (ARMS2). Additive and multiplicative interactions in odds ratios were assessed using the synergy index and a multiplicative interaction term, respectively. AMD presence and severity were assessed from grading of stereoscopic fundus photographs taken in 2001-2004. AMD was present in 337 women, 91% of whom had early AMD. The odds of AMD were 3.3 times greater (95% confidence interval [CI], 1.8-6.1) in women with both low healthy lifestyle score (0-2) and high-risk CFH genotype (CC), relative to those who had low genetic risk (TT) and high healthy lifestyle scores (4-6). There were no significant additive (synergy index [SI], 1.08; 95% CI, 0.70-1.67) or multiplicative (Pinteraction=0.94) interactions in the full sample. However, when limiting the sample to women with stable diets before AMD assessment (n=728) the odds for AMD associated with low healthy lifestyle scores and high-risk CFH genotype were strengthened (odds ratio, 4.6; 95% CI, 1.8-11.6) and the synergy index was significant (SI, 1.34; 95% CI, 1.05-1.70). Adjusting for dietary lutein and zeaxanthin attenuated, and therefore partially explained, the joint association. There were no significant additive or multiplicative interactions for ARMS2 and lifestyle score. Having unhealthy lifestyles and 2 CFH risk alleles increased AMD risk (primarily in the early stages), in an or additive or greater (synergistic) manner. However, unhealthy lifestyles increased AMD risk regardless of AMD risk genotype. Copyright © 2015 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.
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Chatterjee, Nilanjan; Kalaylioglu, Zeynep; Moslehi, Roxana; Peters, Ulrike; Wacholder, Sholom
2006-12-01
In modern genetic epidemiology studies, the association between the disease and a genomic region, such as a candidate gene, is often investigated using multiple SNPs. We propose a multilocus test of genetic association that can account for genetic effects that might be modified by variants in other genes or by environmental factors. We consider use of the venerable and parsimonious Tukey's 1-degree-of-freedom model of interaction, which is natural when individual SNPs within a gene are associated with disease through a common biological mechanism; in contrast, many standard regression models are designed as if each SNP has unique functional significance. On the basis of Tukey's model, we propose a novel but computationally simple generalized test of association that can simultaneously capture both the main effects of the variants within a genomic region and their interactions with the variants in another region or with an environmental exposure. We compared performance of our method with that of two standard tests of association, one ignoring gene-gene/gene-environment interactions and the other based on a saturated model of interactions. We demonstrate major power advantages of our method both in analysis of data from a case-control study of the association between colorectal adenoma and DNA variants in the NAT2 genomic region, which are well known to be related to a common biological phenotype, and under different models of gene-gene interactions with use of simulated data.
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Urban, Mark C; De Meester, Luc; Vellend, Mark; Stoks, Robby; Vanoverbeke, Joost
2012-02-01
We need to understand joint ecological and evolutionary responses to climate change to predict future threats to biological diversity. The 'evolving metacommunity' framework emphasizes that interactions between ecological and evolutionary mechanisms at both local and regional scales will drive community dynamics during climate change. Theory suggests that ecological and evolutionary dynamics often interact to produce outcomes different from those predicted based on either mechanism alone. We highlight two of these dynamics: (i) species interactions prevent adaptation of nonresident species to new niches and (ii) resident species adapt to changing climates and thereby prevent colonization by nonresident species. The rate of environmental change, level of genetic variation, source-sink structure, and dispersal rates mediate between these potential outcomes. Future models should evaluate multiple species, species interactions other than competition, and multiple traits. Future experiments should manipulate factors such as genetic variation and dispersal to determine their joint effects on responses to climate change. Currently, we know much more about how climates will change across the globe than about how species will respond to these changes despite the profound effects these changes will have on global biological diversity. Integrating evolving metacommunity perspectives into climate change biology should produce more accurate predictions about future changes to species distributions and extinction threats.
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Urban, Mark C; De Meester, Luc; Vellend, Mark; Stoks, Robby; Vanoverbeke, Joost
2012-01-01
We need to understand joint ecological and evolutionary responses to climate change to predict future threats to biological diversity. The ‘evolving metacommunity’ framework emphasizes that interactions between ecological and evolutionary mechanisms at both local and regional scales will drive community dynamics during climate change. Theory suggests that ecological and evolutionary dynamics often interact to produce outcomes different from those predicted based on either mechanism alone. We highlight two of these dynamics: (i) species interactions prevent adaptation of nonresident species to new niches and (ii) resident species adapt to changing climates and thereby prevent colonization by nonresident species. The rate of environmental change, level of genetic variation, source-sink structure, and dispersal rates mediate between these potential outcomes. Future models should evaluate multiple species, species interactions other than competition, and multiple traits. Future experiments should manipulate factors such as genetic variation and dispersal to determine their joint effects on responses to climate change. Currently, we know much more about how climates will change across the globe than about how species will respond to these changes despite the profound effects these changes will have on global biological diversity. Integrating evolving metacommunity perspectives into climate change biology should produce more accurate predictions about future changes to species distributions and extinction threats. PMID:25568038
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Kent, Jack W
2016-02-03
New technologies for acquisition of genomic data, while offering unprecedented opportunities for genetic discovery, also impose severe burdens of interpretation and penalties for multiple testing. The Pathway-based Analyses Group of the Genetic Analysis Workshop 19 (GAW19) sought reduction of multiple-testing burden through various approaches to aggregation of highdimensional data in pathways informed by prior biological knowledge. Experimental methods testedincluded the use of "synthetic pathways" (random sets of genes) to estimate power and false-positive error rate of methods applied to simulated data; data reduction via independent components analysis, single-nucleotide polymorphism (SNP)-SNP interaction, and use of gene sets to estimate genetic similarity; and general assessment of the efficacy of prior biological knowledge to reduce the dimensionality of complex genomic data. The work of this group explored several promising approaches to managing high-dimensional data, with the caveat that these methods are necessarily constrained by the quality of external bioinformatic annotation.
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Network-based analysis of genotype-phenotype correlations between different inheritance modes.
Hao, Dapeng; Li, Chuanxing; Zhang, Shaojun; Lu, Jianping; Jiang, Yongshuai; Wang, Shiyuan; Zhou, Meng
2014-11-15
Recent studies on human disease have revealed that aberrant interaction between proteins probably underlies a substantial number of human genetic diseases. This suggests a need to investigate disease inheritance mode using interaction, and based on which to refresh our conceptual understanding of a series of properties regarding inheritance mode of human disease. We observed a strong correlation between the number of protein interactions and the likelihood of a gene causing any dominant diseases or multiple dominant diseases, whereas no correlation was observed between protein interaction and the likelihood of a gene causing recessive diseases. We found that dominant diseases are more likely to be associated with disruption of important interactions. These suggest inheritance mode should be understood using protein interaction. We therefore reviewed the previous studies and refined an interaction model of inheritance mode, and then confirmed that this model is largely reasonable using new evidences. With these findings, we found that the inheritance mode of human genetic diseases can be predicted using protein interaction. By integrating the systems biology perspectives with the classical disease genetics paradigm, our study provides some new insights into genotype-phenotype correlations. haodapeng@ems.hrbmu.edu.cn or biofomeng@hotmail.com Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Ozernov-Palchik, Ola; Yu, Xi; Wang, Yingying; Gaab, Nadine
2016-01-01
Dyslexia is a heritable reading disorder with an estimated prevalence of 5–17%. A multiple deficit model has been proposed that illustrates dyslexia as an outcome of multiple risks and protective factors interacting at the genetic, neural, cognitive, and environmental levels. Here we review the evidence on each of these levels and discuss possible underlying mechanisms and their reciprocal interactions along a developmental timeline. Current and potential implications of neuroscientific findings for contemporary challenges in the field of dyslexia, as well as for reading development and education in general, are then discussed. PMID:27766284
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Baker, Nicholas E.; Li, Ke; Quiquand, Manon; Ruggiero, Robert; Wang, Lan-Hsin
2014-01-01
The eye has been one of the most intensively studied organs in Drosophila. The wealth of knowledge about its development, as well as the reagents that have been developed, and the fact that the eye is dispensable for survival, also make the eye suitable for genetic interaction studies and genetic screens. This chapter provides a brief overview of the methods developed to image and probe eye development at multiple developmental stages, including live imaging, immunostaining of fixed tissues, in situ hybridizations, and scanning electron microscopy and color photography of adult eyes. Also summarized are genetic approaches that can be performed in the eye, including mosaic analysis and conditional mutation, gene misexpression and knockdown, and forward genetic and modifier screens. PMID:24784530
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Polygenic sex determination in the cichlid fish Astatotilapia burtoni.
Roberts, Natalie B; Juntti, Scott A; Coyle, Kaitlin P; Dumont, Bethany L; Stanley, M Kaitlyn; Ryan, Allyson Q; Fernald, Russell D; Roberts, Reade B
2016-10-26
The East African riverine cichlid species Astatotilapia burtoni serves as an important laboratory model for sexually dimorphic physiology and behavior, and also serves as an outgroup species for the explosive adaptive radiations of cichlid species in Lake Malawi and Lake Victoria. An astounding diversity of genetic sex determination systems have been revealed within the adaptive radiation of East African cichlids thus far, including polygenic sex determination systems involving the epistatic interaction of multiple, independently segregating sex determination alleles. However, sex determination has remained unmapped in A. burtoni. Here we present mapping results supporting the presence of multiple, novel sex determination alleles, and thus the presence of polygenic sex determination in A. burtoni. Using mapping in small families in conjunction with restriction-site associated DNA sequencing strategies, we identify associations with sex at loci on linkage group 13 and linkage group 5-14. Inheritance patterns support an XY sex determination system on linkage group 5-14 (a chromosome fusion relative to other cichlids studied), and an XYW system on linkage group 13, and these associations are replicated in multiple families. Additionally, combining our genetic data with comparative genomic analysis identifies another fusion that is unassociated with sex, with linkage group 8-24 and linkage group 16-21 fused in A. burtoni relative to other East African cichlid species. We identify genetic signals supporting the presence of three previously unidentified sex determination alleles at two loci in the species A. burtoni, strongly supporting the presence of polygenic sex determination system in the species. These results provide a foundation for future mapping of multiple sex determination genes and their interactions. A better understanding of sex determination in A. burtoni provides important context for their use in behavioral studies, as well as studies of the evolution of genetic sex determination and sexual conflicts in East African cichlids.
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Hein, R; Abbas, S; Seibold, P; Salazar, R; Flesch-Janys, D; Chang-Claude, J
2012-01-01
Menopausal hormone therapy (MHT) is associated with an increased breast cancer risk in postmenopausal women, with combined estrogen-progestagen therapy posing a greater risk than estrogen monotherapy. However, few studies focused on potential effect modification of MHT-associated breast cancer risk by genetic polymorphisms in the progesterone metabolism. We assessed effect modification of MHT use by five coding single nucleotide polymorphisms (SNPs) in the progesterone metabolizing enzymes AKR1C3 (rs7741), AKR1C4 (rs3829125, rs17134592), and SRD5A1 (rs248793, rs3736316) using a two-center population-based case-control study from Germany with 2,502 postmenopausal breast cancer patients and 4,833 matched controls. An empirical-Bayes procedure that tests for interaction using a weighted combination of the prospective and the retrospective case-control estimators as well as standard prospective logistic regression were applied to assess multiplicative statistical interaction between polymorphisms and duration of MHT use with regard to breast cancer risk assuming a log-additive mode of inheritance. No genetic marginal effects were observed. Breast cancer risk associated with duration of combined therapy was significantly modified by SRD5A1_rs3736316, showing a reduced risk elevation in carriers of the minor allele (p (interaction,empirical-Bayes) = 0.006 using the empirical-Bayes method, p (interaction,logistic regression) = 0.013 using logistic regression). The risk associated with duration of use of monotherapy was increased by AKR1C3_rs7741 in minor allele carriers (p (interaction,empirical-Bayes) = 0.083, p (interaction,logistic regression) = 0.029) and decreased in minor allele carriers of two SNPs in AKR1C4 (rs3829125: p (interaction,empirical-Bayes) = 0.07, p (interaction,logistic regression) = 0.021; rs17134592: p (interaction,empirical-Bayes) = 0.101, p (interaction,logistic regression) = 0.038). After Bonferroni correction for multiple testing only SRD5A1_rs3736316 assessed using the empirical-Bayes method remained significant. Postmenopausal breast cancer risk associated with combined therapy may be modified by genetic variation in SRD5A1. Further well-powered studies are, however, required to replicate our finding.
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Reed, Laura K; LaFlamme, Brooke A; Markow, Therese A
2008-08-27
The genetic basis of postzygotic isolation is a central puzzle in evolutionary biology. Evolutionary forces causing hybrid sterility or inviability act on the responsible genes while they still are polymorphic, thus we have to study these traits as they arise, before isolation is complete. Isofemale strains of D. mojavensis vary significantly in their production of sterile F(1) sons when females are crossed to D. arizonae males. We took advantage of the intraspecific polymorphism, in a novel design, to perform quantitative trait locus (QTL) mapping analyses directly on F(1) hybrid male sterility itself. We found that the genetic architecture of the polymorphism for hybrid male sterility (HMS) in the F(1) is complex, involving multiple QTL, epistasis, and cytoplasmic effects. The role of extensive intraspecific polymorphism, multiple QTL, and epistatic interactions in HMS in this young species pair shows that HMS is arising as a complex trait in this system. Directional selection alone would be unlikely to maintain polymorphism at multiple loci, thus we hypothesize that directional selection is unlikely to be the only evolutionary force influencing postzygotic isolation.
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Markov Logic Networks in the Analysis of Genetic Data
Sakhanenko, Nikita A.
2010-01-01
Abstract Complex, non-additive genetic interactions are common and can be critical in determining phenotypes. Genome-wide association studies (GWAS) and similar statistical studies of linkage data, however, assume additive models of gene interactions in looking for genotype-phenotype associations. These statistical methods view the compound effects of multiple genes on a phenotype as a sum of influences of each gene and often miss a substantial part of the heritable effect. Such methods do not use any biological knowledge about underlying mechanisms. Modeling approaches from the artificial intelligence (AI) field that incorporate deterministic knowledge into models to perform statistical analysis can be applied to include prior knowledge in genetic analysis. We chose to use the most general such approach, Markov Logic Networks (MLNs), for combining deterministic knowledge with statistical analysis. Using simple, logistic regression-type MLNs we can replicate the results of traditional statistical methods, but we also show that we are able to go beyond finding independent markers linked to a phenotype by using joint inference without an independence assumption. The method is applied to genetic data on yeast sporulation, a complex phenotype with gene interactions. In addition to detecting all of the previously identified loci associated with sporulation, our method identifies four loci with smaller effects. Since their effect on sporulation is small, these four loci were not detected with methods that do not account for dependence between markers due to gene interactions. We show how gene interactions can be detected using more complex models, which can be used as a general framework for incorporating systems biology with genetics. PMID:20958249
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Examination of Association to Autism of Common Genetic Variation in Genes Related to Dopamine
Anderson, B.M.; Schnetz-Boutaud, N.; Bartlett, J.; Wright, H.H.; Abramson, R.K.; Cuccaro, M.L.; Gilbert, J.R.; Pericak-Vance, M.A.; Haines, J.L.
2010-01-01
Autism is a severe neurodevelopmental disorder characterized by a triad of complications. Autistic individuals display significant disturbances in language and reciprocal social interactions, combined with repetitive and stereotypic behaviors. Prevalence studies suggest that autism is more common than originally believed, with recent estimates citing a rate of one in 150. Although this genomic approach has yielded multiple suggestive regions, a specific risk locus has yet to be identified and widely confirmed. Because many etiologies have been suggested for this complex syndrome, we hypothesize that one of the difficulties in identifying autism genes is that multiple genetic variants may be required to significantly increase the risk of developing autism. Thus we took the alternative approach of examining 14 prominent dopamine pathway candidate genes for detailed study by genotyping 28 SNPs. Although we did observe a nominally significant association for rs2239535 (p=.008) on chromosome 20, single locus analysis did not reveal any results as significant after correction for multiple comparisons. No significant interaction was identified when Multifactor Dimensionality Reduction (MDR) was employed to test specifically for multilocus effects. Although genome-wide linkage scans in autism have provided support for linkage to various loci along the dopamine pathway, our study does not provide strong evidence of linkage or association to any specific gene or combination of genes within the pathway. These results demonstrate that common genetic variation within the tested genes located within this pathway at most play a minor to moderate role in overall autism pathogenesis. PMID:19360691
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Complex clinical outcomes, such as adverse reaction to vaccination, arise from the concerted interactions among the myriad components of a biological system. Therefore, comprehensive etiological models can be developed only through the integrated study of multiple types of experi...
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Realized life history expression and productivity in aquatic species, and salmonid fishes in particular, is the result of multiple interacting factors including genetics, habitat, growth potential and condition, and the thermal regime individuals experience, both at critical stag...
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Gene-by-Socioeconomic Status Interaction on School Readiness
Rhemtulla, Mijke; Tucker-Drob, Elliot M.
2017-01-01
In previous work with a nationally representative sample of over 1,400 monozygotic and dizygotic twins born in the United States, Tucker-Drob, Rhemtulla, Harden, Turkheimer, and Fask (2011; Psychological Science, 22, 125–133) uncovered a gene × environment interaction on scores on the Bayley Short Form test of mental ability at 2 years of age—higher socioeconomic status (SES) was associated not only with higher mental ability, but also with larger genetic contributions to individual differences in mental ability. The current study examined gene × SES interactions in mathematics skill and reading skill at 4 years of age (preschool age) in the same sample of twins, and further examined whether interactions detected at 4 years could be attributed to the persistence of the interaction previously observed at 2 years. For early mathematics skill but not early reading skill, genetic influences were more pronounced at higher levels of SES. This interaction was not accounted for by the interaction observed at 2 years. These findings indicate that SES moderates the etiological influences on certain cognitive functions at multiple stages of child development. PMID:22350185
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Kljaic-Bukvic, Blazenka; Blekic, Mario; Aberle, Neda; Curtin, John A; Hankinson, Jenny; Semic-Jusufagic, Aida; Belgrave, Danielle; Simpson, Angela; Custovic, Adnan
2014-10-01
We investigated the interaction between genetic variants in endotoxin signalling pathway and domestic endotoxin exposure in relation to asthma presence, and amongst children with asthma, we explored the association of these genetic variants and endotoxin exposure with hospital admissions due to asthma exacerbations. In a case-control study, we analysed data from 824 children (417 asthmatics, 407 controls; age 5-18 yr). Amongst asthmatics, we extracted data on hospitalization for asthma exacerbation from medical records. Endotoxin exposure was measured in dust samples collected from homes. We included 26 single-nucleotide polymorphisms (SNPs) in the final analysis (5 CD14, 7LY96 and 14 TLR4). Two variants remained significantly associated with hospital admissions with asthma exacerbations after correction for multiple testing: for CD14 SNP rs5744455, carriers of T allele had decreased risk of repeated hospital admissions compared with homozygotes for C allele [OR (95% CI), 0.42 (0.25-0.88), p = 0.01, False Discovery Rate (FDR) p = 0.02]; for LY96 SNP rs17226566, C-allele carriers were at a lower risk of hospital admissions compared with T-allele homozygotes [0.59 (0.38-0.90), p = 0.01, FDR p = 0.04]. We observed two interactions between SNPs in CD14 and LY96 with environmental endotoxin exposure in relation to hospital admissions due to asthma exacerbation which remained significant after correction for multiple testing (CD14 SNPs rs2915863 and LY96 SNP rs17226566). Amongst children with asthma, genetic variants in CD14 and LY96 may increase the risk of hospital admissions with acute exacerbations. Polymorphisms in endotoxin pathway interact with domestic endotoxin exposure in further modification of the risk of hospitalization. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
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Ferguson, Jane F; Allayee, Hooman; Gerszten, Robert E; Ideraabdullah, Folami; Kris-Etherton, Penny M; Ordovás, José M; Rimm, Eric B; Wang, Thomas J; Bennett, Brian J
2016-06-01
Cardiometabolic diseases are the leading cause of death worldwide and are strongly linked to both genetic and nutritional factors. The field of nutrigenomics encompasses multiple approaches aimed at understanding the effects of diet on health or disease development, including nutrigenetic studies investigating the relationship between genetic variants and diet in modulating cardiometabolic risk, as well as the effects of dietary components on multiple "omic" measures, including transcriptomics, metabolomics, proteomics, lipidomics, epigenetic modifications, and the microbiome. Here, we describe the current state of the field of nutrigenomics with respect to cardiometabolic disease research and outline a direction for the integration of multiple omics techniques in future nutrigenomic studies aimed at understanding mechanisms and developing new therapeutic options for cardiometabolic disease treatment and prevention. © 2016 American Heart Association, Inc.
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Li, A; Meyre, D
2013-04-01
A robust replication of initial genetic association findings has proved to be difficult in human complex diseases and more specifically in the obesity field. An obvious cause of non-replication in genetic association studies is the initial report of a false positive result, which can be explained by a non-heritable phenotype, insufficient sample size, improper correction for multiple testing, population stratification, technical biases, insufficient quality control or inappropriate statistical analyses. Replication may, however, be challenging even when the original study describes a true positive association. The reasons include underpowered replication samples, gene × gene, gene × environment interactions, genetic and phenotypic heterogeneity and subjective interpretation of data. In this review, we address classic pitfalls in genetic association studies and provide guidelines for proper discovery and replication genetic association studies with a specific focus on obesity.
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Postdoctoral Fellow | Center for Cancer Research
The Khare lab in the Laboratory of Molecular Biology, NCI Center for Cancer Research, NIH, is looking to recruit highly motivated researchers interested in a postdoctoral fellowship to study the molecular and genetic basis of complex microbial behaviors. Our lab is focused on multiple research avenues including interspecies interactions, antibiotic persistence, and adaptation
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Designing Project-Based Instruction to Foster Generative and Mechanistic Understandings in Genetics
ERIC Educational Resources Information Center
Duncan, Ravit Golan; Tseng, Katie Ann
2011-01-01
The acquisition of scientific knowledge is fraught with difficulties and challenges for the learner. The very nature of some scientific domains contributes to the learning difficulties students' experience. Phenomena in these domains are composed of multiple organization levels featuring complicated interactions within and across these levels.…
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Oxidative balance and colon and rectal cancer: interaction of lifestyle factors and genes.
Slattery, Martha L; Lundgreen, Abbie; Welbourn, Bill; Wolff, Roger K; Corcoran, Christopher
2012-06-01
Pro-oxidant and anti-oxidant genetic and lifestyle factors can contribute to an individual's level of oxidative stress. We hypothesize that diet, lifestyle and genetic factors work together to influence colon and rectal cancer through an oxidative balance mechanism. We evaluated nine markers for eosinophil peroxidase (EPX), two for myeloperoxidase (MPO), four for hypoxia-inducible factor-1A (HIFIA), and 16 for inducible nitric oxide synthase (NOS2A) in conjunction with dietary antioxidants, aspirin/NSAID use, and cigarette smoking. We used data from population-based case-control studies (colon cancer n=1555 cases, 1956 controls; rectal cancer n=754 cases, 959 controls). Only NOS2A rs2297518 was associated with colon cancer (OR 0.86 95% CI 0.74, 0.99) and EPX rs2302313 and MPO rs2243828 were associated with rectal cancer (OR 0.75 95% CI 0.59, 0.96; OR 0.81 95% CI 0.67, 0.99 respectively) for main effects. However, after adjustment for multiple comparisons we observed the following significant interactions for colon cancer: NOS2A and lutein, EPX and aspirin/NSAID use, and NOS2A (4 SNPs) and cigarette smoking. For rectal cancer we observed the following interactions after adjustment for multiple comparisons: HIF1A and vitamin E, NOS2A (3SNPs) with calcium; MPO with lutein; HIF1A with lycopene; NOS2A with selenium; EPX and NOS2A with aspirin/NSAID use; HIF1A, MPO, and NOS2A (3 SNPs) with cigarette smoking. We observed significant interaction between a composite oxidative balance score and a polygenic model for both colon (p interaction 0.0008) and rectal cancer (p=0.0018). These results suggest the need to comprehensively evaluate interactions to assess the contribution of risk from both environmental and genetic factors. Copyright © 2012 Elsevier B.V. All rights reserved.
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Interaction between adolescent obesity and HLA risk genes in the etiology of multiple sclerosis
Lima Bomfim, Izaura; Barcellos, Lisa; Gianfrancesco, Milena; Schaefer, Catherine; Kockum, Ingrid; Olsson, Tomas; Alfredsson, Lars
2014-01-01
Objective: We investigated potential interactions between human leukocyte antigen (HLA) genotype and body mass index (BMI) status in relation to the risk of developing multiple sclerosis (MS). Methods: We used 2 case-control studies, one with incident cases (1,510 cases, 2,017 controls) and one with prevalent cases (937 cases, 609 controls). Subjects with different genotypes and BMI were compared with regard to incidence of MS by calculating odds ratios (ORs) with 95% confidence intervals (CIs) employing logistic regression. Potential interactions between genotypes and BMI were evaluated by calculating the attributable proportion due to interaction. Results: In both cohorts, a significant interaction was observed between HLA-DRB1*15 and obesity, regardless of HLA-A*02 status. Similarly, there was a significant interaction between absence of A*02 and obesity, regardless of DRB1*15 status. In the incident cohort, obese subjects with the most susceptible genotype (carriage of DRB1*15 and absence of A*02) had an OR of 16.2 (95% CI 7.5–35.2) compared to nonobese subjects without the genetic risk factors. The corresponding OR in the prevalent study was 13.8 (95% CI 4.1–46.8). Conclusions: We observed striking interactions between BMI status and HLA genotype with regard to MS risk. Hypothetically, a low-grade inflammatory response inherent to obesity synergizes with the adaptive, HLA molecule–restricted arm of the immune system, causing MS. Prevention of adolescent obesity may thus lower the risk of developing MS, predominantly among people with a genetic susceptibility to the disease. PMID:24500647
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Multiple levels of redundant processes inhibit Caenorhabditis elegans vulval cell fates.
Andersen, Erik C; Saffer, Adam M; Horvitz, H Robert
2008-08-01
Many mutations cause obvious abnormalities only when combined with other mutations. Such synthetic interactions can be the result of redundant gene functions. In Caenorhabditis elegans, the synthetic multivulva (synMuv) genes have been grouped into multiple classes that redundantly inhibit vulval cell fates. Animals with one or more mutations of the same class undergo wild-type vulval development, whereas animals with mutations of any two classes have a multivulva phenotype. By varying temperature and genetic background, we determined that mutations in most synMuv genes within a single synMuv class enhance each other. However, in a few cases no enhancement was observed. For example, mutations that affect an Mi2 homolog and a histone methyltransferase are of the same class and do not show enhancement. We suggest that such sets of genes function together in vivo and in at least some cases encode proteins that interact physically. The approach of genetic enhancement can be applied more broadly to identify potential protein complexes as well as redundant processes or pathways. Many synMuv genes are evolutionarily conserved, and the genetic relationships we have identified might define the functions not only of synMuv genes in C. elegans but also of their homologs in other organisms.
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Multiple Levels of Redundant Processes Inhibit Caenorhabditis elegans Vulval Cell Fates
Andersen, Erik C.; Saffer, Adam M.; Horvitz, H. Robert
2008-01-01
Many mutations cause obvious abnormalities only when combined with other mutations. Such synthetic interactions can be the result of redundant gene functions. In Caenorhabditis elegans, the synthetic multivulva (synMuv) genes have been grouped into multiple classes that redundantly inhibit vulval cell fates. Animals with one or more mutations of the same class undergo wild-type vulval development, whereas animals with mutations of any two classes have a multivulva phenotype. By varying temperature and genetic background, we determined that mutations in most synMuv genes within a single synMuv class enhance each other. However, in a few cases no enhancement was observed. For example, mutations that affect an Mi2 homolog and a histone methyltransferase are of the same class and do not show enhancement. We suggest that such sets of genes function together in vivo and in at least some cases encode proteins that interact physically. The approach of genetic enhancement can be applied more broadly to identify potential protein complexes as well as redundant processes or pathways. Many synMuv genes are evolutionarily conserved, and the genetic relationships we have identified might define the functions not only of synMuv genes in C. elegans but also of their homologs in other organisms. PMID:18689876
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Coleman, Jonathan R I; Krapohl, Eva; Eley, Thalia C; Breen, Gerome
2018-04-20
Juvenile obesity is associated with adverse health outcomes. Understanding genetic and environmental influences on body mass index (BMI) during adolescence could inform interventions. We investigated independent and interactive effects of parenting, socioeconomic status (SES) and polygenic risk on BMI pre-adolescence, and on the rate of change in BMI across adolescence. Genome-wide genotype data, BMI and child perceptions of parental warmth and punitive discipline were available at 11 years old, and parental SES was available from birth on 3,414 unrelated participants. Linear models were used to test the effects of social environment and polygenic risk on pre-adolescent BMI. Change in BMI across adolescence was assessed in a subset (N = 1943). Sex-specific effects were assessed. Higher genetic risk was associated with increased BMI pre-adolescence and across adolescence (p < 0.00417, corrected for multiple tests). Negative parenting was not significantly associated with either phenotype, but lower SES was associated with increased BMI pre-adolescence. No interactions passed correction for multiple testing. Polygenic risk scores from adult GWAS meta-analyses are associated with BMI in juveniles, suggesting a stable genetic component. Pre-adolescent BMI was associated with social environment, but parental style has, at most, a small effect.
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Autism genetics: Methodological issues and experimental design.
Sacco, Roberto; Lintas, Carla; Persico, Antonio M
2015-10-01
Autism is a complex neuropsychiatric disorder of developmental origin, where multiple genetic and environmental factors likely interact resulting in a clinical continuum between "affected" and "unaffected" individuals in the general population. During the last two decades, relevant progress has been made in identifying chromosomal regions and genes in linkage or association with autism, but no single gene has emerged as a major cause of disease in a large number of patients. The purpose of this paper is to discuss specific methodological issues and experimental strategies in autism genetic research, based on fourteen years of experience in patient recruitment and association studies of autism spectrum disorder in Italy.
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Genetic architecture, epigenetic influence and environment exposure in the pathogenesis of Autism.
Yu, Li; Wu, YiMing; Wu, Bai-Lin
2015-10-01
Autism spectrum disorder (ASD) is a spectral neurodevelopment disorder affecting approximately 1% of the population. ASD is characterized by impairments in reciprocal social interaction, communication deficits and restricted patterns of behavior. Multiple factors, including genetic/genomic, epigenetic/epigenomic and environmental, are thought to be necessary for autism development. Recent reviews have provided further insight into the genetic/genomic basis of ASD. It has long been suspected that epigenetic mechanisms, including DNA methylation, chromatin structures and long non-coding RNAs may play important roles in the pathology of ASD. In addition to genetic/genomic alterations and epigenetic/epigenomic influences, environmental exposures have been widely accepted as an important role in autism etiology, among which immune dysregulation and gastrointestinal microbiota are two prominent ones.
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Beauchaine, Theodore P; Constantino, John N
2017-09-11
In psychopathology research, endophenotypes are a subset of biomarkers that indicate genetic vulnerability independent of clinical state. To date, an explicit expectation is that endophenotypes be specific to single disorders. We evaluate this expectation considering recent advances in psychiatric genetics, recognition that transdiagnostic vulnerability traits are often more useful than clinical diagnoses in psychiatric genetics, and appreciation for etiological complexity across genetic, neural, hormonal and environmental levels of analysis. We suggest that the disorder-specificity requirement of endophenotypes be relaxed, that neural functions are preferable to behaviors as starting points in searches for endophenotypes, and that future research should focus on interactive effects of multiple endophenotypes on complex psychiatric disorders, some of which are 'phenocopies' with distinct etiologies.
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Genetic Differences Between Humans and Great Apes -- Implications for the Evolution of Humans
NASA Astrophysics Data System (ADS)
Varki, Ajit
2004-06-01
At the level of individual protein sequences, humans are 97-100% identical to the great apes, our closest evolutionary relatives. The evolution of humans (and of human intelligence) from a common ancestor with the chimpanzee and bonobo involved many steps, influenced by interactions amongst factors of genetic, developmental, ecological, microbial, climatic, behavioral, cultural and social origin. The genetic factors can be approached by direct comparisons of human and great ape genomes, genes and gene products, and by elucidating biochemical and biological consequences of any differences found. We have discovered multiple genetic and biochemical differences between humans and great apes, particularly with respect to a family of cell surface molecules called sialic acids, as well as in the metabolism of thyroid hormones. The hormone differences have potential consequences for human brain development. The differences in sialic acid biology have multiple implications for the human condition, ranging from susceptibility or resistance to microbial pathogens, effects on endogenous receptors in the immune system, and potential effects on placental signaling, expression of oncofetal antigens in cancers, consequences of dietary intake of animal foods, and development of the mammalian brain.
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Promiscuity resolves constraints on social mate choice imposed by population viscosity.
While, Geoffrey M; Uller, Tobias; Bordogna, Genevieve; Wapstra, Erik
2014-02-01
Population viscosity can have major consequences for adaptive evolution, in particular for phenotypes involved in social interactions. For example, population viscosity increases the probability of mating with close kin, resulting in selection for mechanisms that circumvent the potential negative consequences of inbreeding. Female promiscuity is often suggested to be one such mechanism. However, whether avoidance of genetically similar partners is a major selective force shaping patterns of promiscuity remains poorly supported by empirical data. Here, we show (i) that fine-scale genetic structure constrains social mate choice in a pair-bonding lizard, resulting in individuals pairing with genetically similar individuals, (ii) that these constraints are circumvented by multiple mating with less related individuals and (iii) that this results in increased heterozygosity of offspring. Despite this, we did not detect any significant effects of heterozygosity on offspring or adult fitness or a strong relationship between pair relatedness and female multiple mating. We discuss these results within the context of incorporating the genetic context dependence of mating strategies into a holistic understanding of mating system evolution. © 2013 John Wiley & Sons Ltd.
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Abbas, Farhat; Ke, Yanguo; Yu, Rangcai; Yue, Yuechong; Amanullah, Sikandar; Jahangir, Muhammad Muzammil; Fan, Yanping
2017-11-01
Terpenoids play several physiological and ecological functions in plant life through direct and indirect plant defenses and also in human society because of their enormous applications in the pharmaceutical, food and cosmetics industries. Through the aid of genetic engineering its role can by magnified to broad spectrum by improving genetic ability of crop plants, enhancing the aroma quality of fruits and flowers and the production of pharmaceutical terpenoids contents in medicinal plants. Terpenoids are structurally diverse and the most abundant plant secondary metabolites, playing an important role in plant life through direct and indirect plant defenses, by attracting pollinators and through different interactions between the plants and their environment. Terpenoids are also significant because of their enormous applications in the pharmaceutical, food and cosmetics industries. Due to their broad distribution and functional versatility, efforts are being made to decode the biosynthetic pathways and comprehend the regulatory mechanisms of terpenoids. This review summarizes the recent advances in biosynthetic pathways, including the spatiotemporal, transcriptional and post-transcriptional regulatory mechanisms. Moreover, we discuss the multiple functions of the terpene synthase genes (TPS), their interaction with the surrounding environment and the use of genetic engineering for terpenoid production in model plants. Here, we also provide an overview of the significance of terpenoid metabolic engineering in crop protection, plant reproduction and plant metabolic engineering approaches for pharmaceutical terpenoids production and future scenarios in agriculture, which call for sustainable production platforms by improving different plant traits.
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Genetic Mechanisms Leading to Sex Differences Across Common Diseases and Anthropometric Traits.
Traglia, Michela; Bseiso, Dina; Gusev, Alexander; Adviento, Brigid; Park, Daniel S; Mefford, Joel A; Zaitlen, Noah; Weiss, Lauren A
2017-02-01
Common diseases often show sex differences in prevalence, onset, symptomology, treatment, or prognosis. Although studies have been performed to evaluate sex differences at specific SNP associations, this work aims to comprehensively survey a number of complex heritable diseases and anthropometric traits. Potential genetically encoded sex differences we investigated include differential genetic liability thresholds or distributions, gene-sex interaction at autosomal loci, major contribution of the X-chromosome, or gene-environment interactions reflected in genes responsive to androgens or estrogens. Finally, we tested the overlap between sex-differential association with anthropometric traits and disease risk. We utilized complementary approaches of assessing GWAS association enrichment and SNP-based heritability estimation to explore explicit sex differences, as well as enrichment in sex-implicated functional categories. We do not find consistent increased genetic load in the lower-prevalence sex, or a disproportionate role for the X-chromosome in disease risk, despite sex-heterogeneity on the X for several traits. We find that all anthropometric traits show less than complete correlation between the genetic contribution to males and females, and find a convincing example of autosome-wide genome-sex interaction in multiple sclerosis (P = 1 × 10 -9 ). We also find some evidence for hormone-responsive gene enrichment, and striking evidence of the contribution of sex-differential anthropometric associations to common disease risk, implying that general mechanisms of sexual dimorphism determining secondary sex characteristics have shared effects on disease risk. Copyright © 2017 by the Genetics Society of America.
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Kim, Young Shin; Leventhal, Bennett L.
2014-01-01
Understanding the pathogenesis of Neurodevelopmental Disorders (NDDs) has proven to be challenging. Using Autism Spectrum Disorder (ASD) as a paradigmatic NDD, this paper reviews the existing literature on the etiologic substrates of ASD and explores how genetic epidemiology approaches including gene-environment interactions (GxE) can play roles in identifying factors associated with ASD etiology. New genetic and bioinformatics strategies have yielded important clues to ASD genetic substrates. Next steps for understanding ASD pathogenesis require significant effort to focus on how genes and environment interact with one another in typical development and its perturbations. Along with larger sample sizes, future study designs should include sample ascertainment that is epidemiologic and population-based to capture the entire ASD spectrum with both categorical and dimensional phenotypic characterization, environmental measurement with accuracy, validity and biomarkers, statistical methods to address population stratification, multiple comparisons and GxE of rare variants, animal models to test hypotheses and, new methods to broaden the capacity to search for GxE, including genome-wide and environment-wide association studies, precise estimation of heritability using dense genetic markers and consideration of GxE both as the disease cause and a disease course modifier. While examination of GxE appears to be a daunting task, tremendous recent progress in gene discovery opens new horizons for advancing our understanding the role of GxE in the pathogenesis of, and ultimately identifying the causes, treatments and even prevention for ASD and other NDDs. PMID:25483344
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The Interaction of Genotype and Environment Determines Variation in the Maize Kernel Ionome
Asaro, Alexandra; Ziegler, Gregory; Ziyomo, Cathrine; Hoekenga, Owen A.; Dilkes, Brian P.; Baxter, Ivan
2016-01-01
Plants obtain soil-resident elements that support growth and metabolism from the water-flow facilitated by transpiration and active transport processes. The availability of elements in the environment interacts with the genetic capacity of organisms to modulate element uptake through plastic adaptive responses, such as homeostasis. These interactions should cause the elemental contents of plants to vary such that the effects of genetic polymorphisms will be dramatically dependent on the environment in which the plant is grown. To investigate genotype by environment interactions underlying elemental accumulation, we analyzed levels of elements in maize kernels of the Intermated B73 × Mo17 (IBM) recombinant inbred population grown in 10 different environments, spanning a total of six locations and five different years. In analyses conducted separately for each environment, we identified a total of 79 quantitative trait loci (QTL) controlling seed elemental accumulation. While a set of these QTL was found in multiple environments, the majority were specific to a single environment, suggesting the presence of genetic by environment interactions. To specifically identify and quantify QTL by environment interactions (QEIs), we implemented two methods: linear modeling with environmental covariates, and QTL analysis on trait differences between growouts. With these approaches, we found several instances of QEI, indicating that elemental profiles are highly heritable, interrelated, and responsive to the environment. PMID:27770027
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The Interaction of Genotype and Environment Determines Variation in the Maize Kernel Ionome.
Asaro, Alexandra; Ziegler, Gregory; Ziyomo, Cathrine; Hoekenga, Owen A; Dilkes, Brian P; Baxter, Ivan
2016-12-07
Plants obtain soil-resident elements that support growth and metabolism from the water-flow facilitated by transpiration and active transport processes. The availability of elements in the environment interacts with the genetic capacity of organisms to modulate element uptake through plastic adaptive responses, such as homeostasis. These interactions should cause the elemental contents of plants to vary such that the effects of genetic polymorphisms will be dramatically dependent on the environment in which the plant is grown. To investigate genotype by environment interactions underlying elemental accumulation, we analyzed levels of elements in maize kernels of the Intermated B73 × Mo17 (IBM) recombinant inbred population grown in 10 different environments, spanning a total of six locations and five different years. In analyses conducted separately for each environment, we identified a total of 79 quantitative trait loci (QTL) controlling seed elemental accumulation. While a set of these QTL was found in multiple environments, the majority were specific to a single environment, suggesting the presence of genetic by environment interactions. To specifically identify and quantify QTL by environment interactions (QEIs), we implemented two methods: linear modeling with environmental covariates, and QTL analysis on trait differences between growouts. With these approaches, we found several instances of QEI, indicating that elemental profiles are highly heritable, interrelated, and responsive to the environment. Copyright © 2016 Asaro et al.
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Host genetic variation impacts microbiome composition across human body sites.
Blekhman, Ran; Goodrich, Julia K; Huang, Katherine; Sun, Qi; Bukowski, Robert; Bell, Jordana T; Spector, Timothy D; Keinan, Alon; Ley, Ruth E; Gevers, Dirk; Clark, Andrew G
2015-09-15
The composition of bacteria in and on the human body varies widely across human individuals, and has been associated with multiple health conditions. While microbial communities are influenced by environmental factors, some degree of genetic influence of the host on the microbiome is also expected. This study is part of an expanding effort to comprehensively profile the interactions between human genetic variation and the composition of this microbial ecosystem on a genome- and microbiome-wide scale. Here, we jointly analyze the composition of the human microbiome and host genetic variation. By mining the shotgun metagenomic data from the Human Microbiome Project for host DNA reads, we gathered information on host genetic variation for 93 individuals for whom bacterial abundance data are also available. Using this dataset, we identify significant associations between host genetic variation and microbiome composition in 10 of the 15 body sites tested. These associations are driven by host genetic variation in immunity-related pathways, and are especially enriched in host genes that have been previously associated with microbiome-related complex diseases, such as inflammatory bowel disease and obesity-related disorders. Lastly, we show that host genomic regions associated with the microbiome have high levels of genetic differentiation among human populations, possibly indicating host genomic adaptation to environment-specific microbiomes. Our results highlight the role of host genetic variation in shaping the composition of the human microbiome, and provide a starting point toward understanding the complex interaction between human genetics and the microbiome in the context of human evolution and disease.
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References for Haplotype Imputation in the Big Data Era
Li, Wenzhi; Xu, Wei; Li, Qiling; Ma, Li; Song, Qing
2016-01-01
Imputation is a powerful in silico approach to fill in those missing values in the big datasets. This process requires a reference panel, which is a collection of big data from which the missing information can be extracted and imputed. Haplotype imputation requires ethnicity-matched references; a mismatched reference panel will significantly reduce the quality of imputation. However, currently existing big datasets cover only a small number of ethnicities, there is a lack of ethnicity-matched references for many ethnic populations in the world, which has hampered the data imputation of haplotypes and its downstream applications. To solve this issue, several approaches have been proposed and explored, including the mixed reference panel, the internal reference panel and genotype-converted reference panel. This review article provides the information and comparison between these approaches. Increasing evidence showed that not just one or two genetic elements dictate the gene activity and functions; instead, cis-interactions of multiple elements dictate gene activity. Cis-interactions require the interacting elements to be on the same chromosome molecule, therefore, haplotype analysis is essential for the investigation of cis-interactions among multiple genetic variants at different loci, and appears to be especially important for studying the common diseases. It will be valuable in a wide spectrum of applications from academic research, to clinical diagnosis, prevention, treatment, and pharmaceutical industry. PMID:27274952
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Humblet, Olivier; Korrick, Susan A; Williams, Paige L; Sergeyev, Oleg; Emond, Claude; Birnbaum, Linda S; Burns, Jane S; Altshul, Larisa M; Patterson, Donald G; Turner, Wayman E; Lee, Mary M; Revich, Boris; Hauser, Russ
2013-01-01
Exposure to dioxins has been associated with delayed pubertal onset in both epidemiologic and animal studies. Whether genetic polymorphisms may modify this association is currently unknown. Identifying such genes could provide insight into mechanistic pathways. This is one of the first studies to assess genetic susceptibility to dioxins. We evaluated whether common polymorphisms in genes affecting either molecular responses to dioxin exposure or pubertal onset influence the association between peripubertal serum dioxin concentration and male pubertal onset. In this prospective cohort of Russian adolescent boys (n = 392), we assessed gene-environment interactions for 337 tagging single-nucleotide polymorphisms (SNPs) from 46 candidate genes and two intergenic regions. Dioxins were measured in the boys' serum at age 8-9 years. Pubertal onset was based on testicular volume and on genitalia staging. Statistical approaches for controlling for multiple testing were used, both with and without prescreening for marginal genetic associations. After accounting for multiple testing, two tag SNPs in the glucocorticoid receptor (GR/NR3C1) gene and one in the estrogen receptor-α (ESR1) gene were significant (q < 0.2) modifiers of the association between peripubertal serum dioxin concentration and male pubertal onset defined by genitalia staging, although not by testicular volume. The results were sensitive to whether multiple comparison adjustment was applied to all gene-environment tests or only to those with marginal genetic associations. Common genetic polymorphisms in the glucocorticoid receptor and estrogen receptor-α genes may modify the association between peripubertal serum dioxin concentration and pubertal onset. Further studies are warranted to confirm these findings.
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Disruptions in Energy Balance: Does Nature overcome Nurture?
Fernández, José R.; Casazza, Krista; Divers, Jasmin; López-Alarcón, Mardya
2008-01-01
Fat accumulation, in general, is the result of a breakdown in the homeostatic regulation of energy balance. Although, the specific factors influencing the disruption of energy balance and why these factors affect individuals differently are not completely understood, numerous studies have identified multiple contributors. Environmental components influence food acquisition, eating, and lifestyle habits. However, the variability in obesity-related outcomes observed among individuals placed in similar controlled environments support the notion that genetic components also wield some control. Multiple genetic regions have been associated with measures related to energy balance; however, the replication of these genetic contributors to energy intake and energy expenditure in humans is relatively small perhaps because of the heterogeneity of human populations. Genetic tools such as genetic admixture account for individual’s genetic background in gene association studies, reducing the confounding effect of population stratification, and promise to be a relevant tool on the identification of genetic contributions to energy balance, particularly among individuals of diverse racial/ethnic backgrounds. Although it has been recognized that genes are expressed according to environmental influences, the search toward the understanding of nature and nurture in obesity will require the detailed study of the effect of genes under diverse physiologic and behavioral environments. It is evident that more research is needed to elucidate the methodological and statistical issues that underlie the interactions between genes and environments in obesity and its related comorbidities. PMID:18096193
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Rapid contemporary evolution and clonal food web dynamics
Jones, Laura E.; Becks, Lutz; Ellner, Stephen P.; Hairston, Nelson G.; Yoshida, Takehito; Fussmann, Gregor F.
2009-01-01
Character evolution that affects ecological community interactions often occurs contemporaneously with temporal changes in population size, potentially altering the very nature of those dynamics. Such eco-evolutionary processes may be most readily explored in systems with short generations and simple genetics. Asexual and cyclically parthenogenetic organisms such as microalgae, cladocerans and rotifers, which frequently dominate freshwater plankton communities, meet these requirements. Multiple clonal lines can coexist within each species over extended periods, until either fixation occurs or a sexual phase reshuffles the genetic material. When clones differ in traits affecting interspecific interactions, within-species clonal dynamics can have major effects on the population dynamics. We first consider a simple predator–prey system with two prey genotypes, parametrized with data from a well-studied experimental system, and explore how the extent of differences in defence against predation within the prey population determine dynamic stability versus instability of the system. We then explore how increased potential for evolution affects the community dynamics in a more general community model with multiple predator and multiple prey genotypes. These examples illustrate how microevolutionary ‘details’ that enhance or limit the potential for heritable phenotypic change can have significant effects on contemporaneous community-level dynamics and the persistence and coexistence of species. PMID:19414472
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Multiple sclerosis among Afghan immigrants in Isfahan, Iran.
Etemadifar, Masoud; Sadeghpour, Niyousha; Nekouie, Kimia; Jahansouz, Mohammadmostafa; Salari, Mehri; Fereidan-Esfahani, Mahboobeh
2017-04-01
Multiple sclerosis is a central nervous system demyelinating disease with unknown etiology. However, it is believed to be a multifactorial disease resulting from an interaction of genetic and environmental factors. Immigrant studies have been performed to provide a better view of the pattern of this interaction. We aimed to report the prevalence of MS Afghan immigrants of Isfahan, a population who share the same environment as Isfahan residents but with different genetic backgrounds. Medical documents of 4536 patients registered by Isfahan Multiple Sclerosis Society (IMSS), the only MS registry in the province of Isfahan, were reviewed for Afghan patients and the demographic and clinical characteristics. The information on the current population of Afghans residing in the province was gathered through Bureau for Aliens and Foreign Immigrants Affairs (BAFIA). Six Afghan cases were identified among 4536 patients registered by IMSS. Current population of Afghans in the province was 123,578 people (65,041 male and 58,537 female). One of the cases was male and the other five were females with a female/male ratio of 5:1. Sex-adjusted prevalence for males and females was 1.53 and 8.54 per 100,000, respectively. The overall crude prevalence for Afghan population of Isfahan is 4.85 per 100,000. This study shows a lower prevalence of MS among Afghan residents of Isfahan compared to the overall prevalence of the province. Our result could be implying a stronger bond between genetic factors and developing MS, rather than the environmental factors. Copyright © 2017 Elsevier B.V. All rights reserved.
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Dlugosch, Katrina M; Anderson, Samantha R; Braasch, Joseph; Cang, F Alice; Gillette, Heather D
2015-05-01
The influence of genetic variation on invasion success has captivated researchers since the start of the field of invasion genetics 50 years ago. We review the history of work on this question and conclude that genetic variation-as surveyed with molecular markers-appears to shape invasion rarely. Instead, there is a significant disconnect between marker assays and ecologically relevant genetic variation in introductions. We argue that the potential for adaptation to facilitate invasion will be shaped by the details of genotypes affecting phenotypes, and we highlight three areas in which we see opportunities to make powerful new insights. (i) The genetic architecture of adaptive variation. Traits shaped by large-effect alleles may be strongly impacted by founder events yet more likely to respond to selection when genetic drift is strong. Large-effect loci may be especially relevant for traits involved in biotic interactions. (ii) Cryptic genetic variation exposed during invasion. Introductions have strong potential to uncover masked variation due to alterations in genetic and ecological environments. (iii) Genetic interactions during admixture of multiple source populations. As divergence among sources increases, positive followed by increasingly negative effects of admixture should be expected. Although generally hypothesized to be beneficial during invasion, admixture is most often reported among sources of intermediate divergence, supporting the possibility that incompatibilities among divergent source populations might be limiting their introgression. Finally, we note that these details of invasion genetics can be coupled with comparative demographic analyses to link genetic changes to the evolution of invasiveness itself. © 2015 John Wiley & Sons Ltd.
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Bioinformatic prediction and in vivo validation of residue-residue interactions in human proteins
NASA Astrophysics Data System (ADS)
Jordan, Daniel; Davis, Erica; Katsanis, Nicholas; Sunyaev, Shamil
2014-03-01
Identifying residue-residue interactions in protein molecules is important for understanding both protein structure and function in the context of evolutionary dynamics and medical genetics. Such interactions can be difficult to predict using existing empirical or physical potentials, especially when residues are far from each other in sequence space. Using a multiple sequence alignment of 46 diverse vertebrate species we explore the space of allowed sequences for orthologous protein families. Amino acid changes that are known to damage protein function allow us to identify specific changes that are likely to have interacting partners. We fit the parameters of the continuous-time Markov process used in the alignment to conclude that these interactions are primarily pairwise, rather than higher order. Candidates for sites under pairwise epistasis are predicted, which can then be tested by experiment. We report the results of an initial round of in vivo experiments in a zebrafish model that verify the presence of multiple pairwise interactions predicted by our model. These experimentally validated interactions are novel, distant in sequence, and are not readily explained by known biochemical or biophysical features.
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Interactions between genetic variation and cellular environment in skeletal muscle gene expression.
Taylor, D Leland; Knowles, David A; Scott, Laura J; Ramirez, Andrea H; Casale, Francesco Paolo; Wolford, Brooke N; Guan, Li; Varshney, Arushi; Albanus, Ricardo D'Oliveira; Parker, Stephen C J; Narisu, Narisu; Chines, Peter S; Erdos, Michael R; Welch, Ryan P; Kinnunen, Leena; Saramies, Jouko; Sundvall, Jouko; Lakka, Timo A; Laakso, Markku; Tuomilehto, Jaakko; Koistinen, Heikki A; Stegle, Oliver; Boehnke, Michael; Birney, Ewan; Collins, Francis S
2018-01-01
From whole organisms to individual cells, responses to environmental conditions are influenced by genetic makeup, where the effect of genetic variation on a trait depends on the environmental context. RNA-sequencing quantifies gene expression as a molecular trait, and is capable of capturing both genetic and environmental effects. In this study, we explore opportunities of using allele-specific expression (ASE) to discover cis-acting genotype-environment interactions (GxE)-genetic effects on gene expression that depend on an environmental condition. Treating 17 common, clinical traits as approximations of the cellular environment of 267 skeletal muscle biopsies, we identify 10 candidate environmental response expression quantitative trait loci (reQTLs) across 6 traits (12 unique gene-environment trait pairs; 10% FDR per trait) including sex, systolic blood pressure, and low-density lipoprotein cholesterol. Although using ASE is in principle a promising approach to detect GxE effects, replication of such signals can be challenging as validation requires harmonization of environmental traits across cohorts and a sufficient sampling of heterozygotes for a transcribed SNP. Comprehensive discovery and replication will require large human transcriptome datasets, or the integration of multiple transcribed SNPs, coupled with standardized clinical phenotyping.
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Sadee, Wolfgang
2013-09-01
Pharmacogenetic biomarker tests include mostly specific single gene-drug pairs, capable of accounting for a portion of interindividual variability in drug response and toxicity. However, multiple genes are likely to contribute, either acting independently or epistatically, with the CYP2C9-VKORC1-warfarin test panel, an example of a clinically used gene-gene-dug interaction. I discuss here further instances of gene-gene-drug interactions, including a proposed dynamic effect on statin therapy by genetic variants in both a transporter (SLCO1B1) and a metabolizing enzyme (CYP3A4) in liver cells, the main target site where statins block cholesterol synthesis. These examples set a conceptual framework for developing diagnostic panels involving multiple gene-drug combinations. Copyright © 2013 Wiley Periodicals, Inc.
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Lemery-Chalfant, Kathryn; Kao, Karen; Swann, Gregory; Goldsmith, H Hill
2013-02-01
Biological parents pass on genotypes to their children, as well as provide home environments that correlate with their genotypes; thus, the association between the home environment and children's temperament can be genetically (i.e., passive gene-environment correlation) or environmentally mediated. Furthermore, family environments may suppress or facilitate the heritability of children's temperament (i.e., gene-environment interaction). The sample comprised 807 twin pairs (mean age = 7.93 years) from the longitudinal Wisconsin Twin Project. Important passive gene-environment correlations emerged, such that home environments were less chaotic for children with high effortful control, and this association was genetically mediated. Children with high extraversion/surgency experienced more chaotic home environments, and this correlation was also genetically mediated. In addition, heritability of children's temperament was moderated by home environments, such that effortful control and extraversion/surgency were more heritable in chaotic homes, and negative affectivity was more heritable under crowded or unsafe home conditions. Modeling multiple types of gene-environment interplay uncovered the complex role of genetic factors and the hidden importance of the family environment for children's temperament and development more generally.
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Reed, Laura K.; LaFlamme, Brooke A.; Markow, Therese A.
2008-01-01
Background The genetic basis of postzygotic isolation is a central puzzle in evolutionary biology. Evolutionary forces causing hybrid sterility or inviability act on the responsible genes while they still are polymorphic, thus we have to study these traits as they arise, before isolation is complete. Methodology/Principal Findings Isofemale strains of D. mojavensis vary significantly in their production of sterile F1 sons when females are crossed to D. arizonae males. We took advantage of the intraspecific polymorphism, in a novel design, to perform quantitative trait locus (QTL) mapping analyses directly on F1 hybrid male sterility itself. We found that the genetic architecture of the polymorphism for hybrid male sterility (HMS) in the F1 is complex, involving multiple QTL, epistasis, and cytoplasmic effects. Conclusions/Significance The role of extensive intraspecific polymorphism, multiple QTL, and epistatic interactions in HMS in this young species pair shows that HMS is arising as a complex trait in this system. Directional selection alone would be unlikely to maintain polymorphism at multiple loci, thus we hypothesize that directional selection is unlikely to be the only evolutionary force influencing postzygotic isolation. PMID:18728782
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Bhardwaj, Deepak; Lakhanpaul, Suman; Tuteja, Narendra
2012-09-01
Climate change is a major concern especially in view of the increasing global population and food security. Plant scientists need to look for genetic tools whose appropriate usage can contribute to sustainable food availability. G-proteins have been identified as some of the potential genetic tools that could be useful for protecting plants from various stresses. Heterotrimeric G-proteins consisting of three subunits Gα, Gβ and Gγ are important components of a number of signalling pathways. Their structure and functions are already well studied in animals but their potential in plants is now gaining attention for their role in stress tolerance. Earlier we have reported that over expressing pea Gβ conferred heat tolerance in tobacco plants. Here we report the interacting partners (proteins) of Gβ subunit of Pisum sativum and their putative role in stress and development. Out of 90 transformants isolated from the yeast-two-hybrid (Y2H) screening, seven were chosen for further investigation due to their recurrence in multiple experiments. These interacting partners were confirmed using β-galactosidase colony filter lift and ONPG (O-nitrophenyl-β-D-galactopyranoside) assays. These partners include thioredoxin H, histidine-containing phosphotransfer protein 5-like, pathogenesis-related protein, glucan endo-beta-1, 3-glucosidase (acidic isoform), glycine rich RNA binding protein, cold and drought-regulated protein (corA gene) and soluble inorganic pyrophosphatase 1. This study suggests the role of pea Gβ subunit in stress signal transduction and development pathways owing to its capability to interact with a wide range of proteins of multiple functions. Copyright © 2012 Elsevier Masson SAS. All rights reserved.
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Zhang, Wenchao; Dai, Xinbin; Wang, Qishan; Xu, Shizhong; Zhao, Patrick X
2016-05-01
The term epistasis refers to interactions between multiple genetic loci. Genetic epistasis is important in regulating biological function and is considered to explain part of the 'missing heritability,' which involves marginal genetic effects that cannot be accounted for in genome-wide association studies. Thus, the study of epistasis is of great interest to geneticists. However, estimating epistatic effects for quantitative traits is challenging due to the large number of interaction effects that must be estimated, thus significantly increasing computing demands. Here, we present a new web server-based tool, the Pipeline for estimating EPIStatic genetic effects (PEPIS), for analyzing polygenic epistatic effects. The PEPIS software package is based on a new linear mixed model that has been used to predict the performance of hybrid rice. The PEPIS includes two main sub-pipelines: the first for kinship matrix calculation, and the second for polygenic component analyses and genome scanning for main and epistatic effects. To accommodate the demand for high-performance computation, the PEPIS utilizes C/C++ for mathematical matrix computing. In addition, the modules for kinship matrix calculations and main and epistatic-effect genome scanning employ parallel computing technology that effectively utilizes multiple computer nodes across our networked cluster, thus significantly improving the computational speed. For example, when analyzing the same immortalized F2 rice population genotypic data examined in a previous study, the PEPIS returned identical results at each analysis step with the original prototype R code, but the computational time was reduced from more than one month to about five minutes. These advances will help overcome the bottleneck frequently encountered in genome wide epistatic genetic effect analysis and enable accommodation of the high computational demand. The PEPIS is publically available at http://bioinfo.noble.org/PolyGenic_QTL/.
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An integrative model of evolutionary covariance: a symposium on body shape in fishes.
Walker, Jeffrey A
2010-12-01
A major direction of current and future biological research is to understand how multiple, interacting functional systems coordinate in producing a body that works. This understanding is complicated by the fact that organisms need to work well in multiple environments, with both predictable and unpredictable environmental perturbations. Furthermore, organismal design reflects a history of past environments and not a plan for future environments. How complex, interacting functional systems evolve, then, is a truly grand challenge. In accepting the challenge, an integrative model of evolutionary covariance is developed. The model combines quantitative genetics, functional morphology/physiology, and functional ecology. The model is used to convene scientists ranging from geneticists, to physiologists, to ecologists, to engineers to facilitate the emergence of body shape in fishes as a model system for understanding how complex, interacting functional systems develop and evolve. Body shape of fish is a complex morphology that (1) results from many developmental paths and (2) functions in many different behaviors. Understanding the coordination and evolution of the many paths from genes to body shape, body shape to function, and function to a working fish body in a dynamic environment is now possible given new technologies from genetics to engineering and new theoretical models that integrate the different levels of biological organization (from genes to ecology).
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Modification of Occupational Exposures on Bladder Cancer Risk by Common Genetic Polymorphisms.
Figueroa, Jonine D; Koutros, Stella; Colt, Joanne S; Kogevinas, Manolis; Garcia-Closas, Montserrat; Real, Francisco X; Friesen, Melissa C; Baris, Dalsu; Stewart, Patricia; Schwenn, Molly; Johnson, Alison; Karagas, Margaret R; Armenti, Karla R; Moore, Lee E; Schned, Alan; Lenz, Petra; Prokunina-Olsson, Ludmila; Banday, A Rouf; Paquin, Ashley; Ylaya, Kris; Chung, Joon-Yong; Hewitt, Stephen M; Nickerson, Michael L; Tardón, Adonina; Serra, Consol; Carrato, Alfredo; García-Closas, Reina; Lloreta, Josep; Malats, Núria; Fraumeni, Joseph F; Chanock, Stephen J; Chatterjee, Nilanjan; Rothman, Nathaniel; Silverman, Debra T
2015-11-01
Few studies have demonstrated gene/environment interactions in cancer research. Using data on high-risk occupations for 2258 case patients and 2410 control patients from two bladder cancer studies, we observed that three of 16 known or candidate bladder cancer susceptibility variants displayed statistically significant and consistent evidence of additive interactions; specifically, the GSTM1 deletion polymorphism (P interaction ≤ .001), rs11892031 (UGT1A, P interaction = .01), and rs798766 (TMEM129-TACC3-FGFR3, P interaction = .03). There was limited evidence for multiplicative interactions. When we examined detailed data on a prevalent occupational exposure associated with increased bladder cancer risk, straight metalworking fluids, we also observed statistically significant additive interaction for rs798766 (TMEM129-TACC3-FGFR3, P interaction = .02), with the interaction more apparent in patients with tumors positive for FGFR3 expression. All statistical tests were two-sided. The interaction we observed for rs798766 (TMEM129-TACC3-FGFR3) with specific exposure to straight metalworking fluids illustrates the value of integrating germline genetic variation, environmental exposures, and tumor marker data to provide insight into the mechanisms of bladder carcinogenesis. Published by Oxford University Press 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.
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A versatile modular vector system for rapid combinatorial mammalian genetics.
Albers, Joachim; Danzer, Claudia; Rechsteiner, Markus; Lehmann, Holger; Brandt, Laura P; Hejhal, Tomas; Catalano, Antonella; Busenhart, Philipp; Gonçalves, Ana Filipa; Brandt, Simone; Bode, Peter K; Bode-Lesniewska, Beata; Wild, Peter J; Frew, Ian J
2015-04-01
Here, we describe the multiple lentiviral expression (MuLE) system that allows multiple genetic alterations to be introduced simultaneously into mammalian cells. We created a toolbox of MuLE vectors that constitute a flexible, modular system for the rapid engineering of complex polycistronic lentiviruses, allowing combinatorial gene overexpression, gene knockdown, Cre-mediated gene deletion, or CRISPR/Cas9-mediated (where CRISPR indicates clustered regularly interspaced short palindromic repeats) gene mutation, together with expression of fluorescent or enzymatic reporters for cellular assays and animal imaging. Examples of tumor engineering were used to illustrate the speed and versatility of performing combinatorial genetics using the MuLE system. By transducing cultured primary mouse cells with single MuLE lentiviruses, we engineered tumors containing up to 5 different genetic alterations, identified genetic dependencies of molecularly defined tumors, conducted genetic interaction screens, and induced the simultaneous CRISPR/Cas9-mediated knockout of 3 tumor-suppressor genes. Intramuscular injection of MuLE viruses expressing oncogenic H-RasG12V together with combinations of knockdowns of the tumor suppressors cyclin-dependent kinase inhibitor 2A (Cdkn2a), transformation-related protein 53 (Trp53), and phosphatase and tensin homolog (Pten) allowed the generation of 3 murine sarcoma models, demonstrating that genetically defined autochthonous tumors can be rapidly generated and quantitatively monitored via direct injection of polycistronic MuLE lentiviruses into mouse tissues. Together, our results demonstrate that the MuLE system provides genetic power for the systematic investigation of the molecular mechanisms that underlie human diseases.
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Causes and Consequences of Genetic Background Effects Illuminated by Integrative Genomic Analysis
Chandler, Christopher H.; Chari, Sudarshan; Dworkin, Ian
2014-01-01
The phenotypic consequences of individual mutations are modulated by the wild-type genetic background in which they occur. Although such background dependence is widely observed, we do not know whether general patterns across species and traits exist or about the mechanisms underlying it. We also lack knowledge on how mutations interact with genetic background to influence gene expression and how this in turn mediates mutant phenotypes. Furthermore, how genetic background influences patterns of epistasis remains unclear. To investigate the genetic basis and genomic consequences of genetic background dependence of the scallopedE3 allele on the Drosophila melanogaster wing, we generated multiple novel genome-level datasets from a mapping-by-introgression experiment and a tagged RNA gene expression dataset. In addition we used whole genome resequencing of the parental lines—two commonly used laboratory strains—to predict polymorphic transcription factor binding sites for SD. We integrated these data with previously published genomic datasets from expression microarrays and a modifier mutation screen. By searching for genes showing a congruent signal across multiple datasets, we were able to identify a robust set of candidate loci contributing to the background-dependent effects of mutations in sd. We also show that the majority of background-dependent modifiers previously reported are caused by higher-order epistasis, not quantitative noncomplementation. These findings provide a useful foundation for more detailed investigations of genetic background dependence in this system, and this approach is likely to prove useful in exploring the genetic basis of other traits as well. PMID:24504186
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Guo, Xiuqing; Franceschini, Nora; Cheng, Ching-Yu; Sim, Xueling; Vojinovic, Dina; Marten, Jonathan; Musani, Solomon K.; Li, Changwei; Schwander, Karen; Richard, Melissa A.; Noordam, Raymond; Aschard, Hugues; Bartz, Traci M.; Bielak, Lawrence F.; Dorajoo, Rajkumar; Fisher, Virginia; Hartwig, Fernando P.; Horimoto, Andrea R. V. R.; Lohman, Kurt K.; Manning, Alisa K.; Rankinen, Tuomo; Smith, Albert V.; Wojczynski, Mary K.; Alver, Maris; Boissel, Mathilde; Cai, Qiuyin; Divers, Jasmin; Gao, Chuan; Goel, Anuj; Harris, Sarah E.; He, Meian; Hsu, Fang-Chi; Jackson, Anne U.; Kähönen, Mika; Kasturiratne, Anuradhani; Komulainen, Pirjo; Kühnel, Brigitte; Laguzzi, Federica; Luan, Jian'an; Nolte, Ilja M.; Padmanabhan, Sandosh; Robino, Antonietta; Scott, Robert A.; Sofer, Tamar; Stančáková, Alena; Takeuchi, Fumihiko; Tayo, Bamidele O.; Varga, Tibor V.; Vitart, Veronique; Wang, Yajuan; Warren, Helen R.; Wen, Wanqing; Yanek, Lisa R.; Zhang, Weihua; Zhao, Jing Hua; Afaq, Saima; Amin, Najaf; Arking, Dan E.; Aung, Tin; Boerwinkle, Eric; Borecki, Ingrid; Broeckel, Ulrich; Brown, Morris; Brumat, Marco; Burke, Gregory L.; Chakravarti, Aravinda; Charumathi, Sabanayagam; Ida Chen, Yii-Der; Connell, John M.; Correa, Adolfo; de las Fuentes, Lisa; de Mutsert, Renée; de Silva, H. Janaka; Deng, Xuan; Ding, Jingzhong; Duan, Qing; Eaton, Charles B.; Ehret, Georg; Eppinga, Ruben N.; Faul, Jessica D.; Felix, Stephan B.; Forouhi, Nita G.; Forrester, Terrence; Franco, Oscar H.; Friedlander, Yechiel; Gandin, Ilaria; Gao, He; Ghanbari, Mohsen; Gigante, Bruna; Gu, C. Charles; Gu, Dongfeng; Hagenaars, Saskia P.; Hallmans, Göran; Harris, Tamara B.; He, Jiang; Heng, Chew-Kiat; Hirata, Makoto; Howard, Barbara V.; Ikram, M. Arfan; John, Ulrich; Katsuya, Tomohiro; Khor, Chiea Chuen; Kilpeläinen, Tuomas O.; Koh, Woon-Puay; Krieger, José E.; Kritchevsky, Stephen B.; Kubo, Michiaki; Kuusisto, Johanna; Lakka, Timo A.; Langefeld, Carl D.; Langenberg, Claudia; Launer, Lenore J.; Lehne, Benjamin; Lewis, Cora E.; Li, Yize; Lin, Shiow; Liu, Jianjun; Liu, Jingmin; Loh, Marie; Louie, Tin; Mägi, Reedik; McKenzie, Colin A.; Meitinger, Thomas; Milaneschi, Yuri; Milani, Lili; Mohlke, Karen L.; Momozawa, Yukihide; Nalls, Mike A.; Nelson, Christopher P.; Sotoodehnia, Nona; Norris, Jill M.; O'Connell, Jeff R.; Palmer, Nicholette D.; Perls, Thomas; Pedersen, Nancy L.; Peters, Annette; Peyser, Patricia A.; Poulter, Neil; Raffel, Leslie J.; Raitakari, Olli T.; Roll, Kathryn; Rose, Lynda M.; Rosendaal, Frits R.; Rotter, Jerome I.; Schmidt, Carsten O.; Schreiner, Pamela J.; Schupf, Nicole; Scott, William R.; Shi, Yuan; Sidney, Stephen; Sims, Mario; Sitlani, Colleen M.; Smith, Jennifer A.; Snieder, Harold; Starr, John M.; Strauch, Konstantin; Stringham, Heather M.; Tan, Nicholas Y. Q.; Tang, Hua; Taylor, Kent D.; Teo, Yik Ying; Tham, Yih Chung; Turner, Stephen T.; Uitterlinden, André G.; Vollenweider, Peter; Waldenberger, Melanie; Wang, Lihua; Wang, Ya Xing; Wei, Wen Bin; Williams, Christine; Yao, Jie; Yu, Caizheng; Yuan, Jian-Min; Zhao, Wei; Zonderman, Alan B.; Becker, Diane M.; Boehnke, Michael; Bowden, Donald W.; Chambers, John C.; Deary, Ian J.; Esko, Tõnu; Farrall, Martin; Franks, Paul W.; Freedman, Barry I.; Froguel, Philippe; Gasparini, Paolo; Gieger, Christian; Kamatani, Yoichiro; Kato, Norihiro; Kooner, Jaspal S.; Kutalik, Zoltán; Laakso, Markku; Laurie, Cathy C.; Leander, Karin; Lehtimäki, Terho; Study, Lifelines Cohort; Magnusson, Patrik K. E.; Oldehinkel, Albertine J.; Penninx, Brenda W. J. H.; Polasek, Ozren; Porteous, David J.; Rauramaa, Rainer; Samani, Nilesh J.; Scott, James; Shu, Xiao-Ou; van der Harst, Pim; Wagenknecht, Lynne E.; Watkins, Hugh; Weir, David R.; Wickremasinghe, Ananda R.; Wu, Tangchun; Zheng, Wei; Bouchard, Claude; Christensen, Kaare; Evans, Michele K.; Gudnason, Vilmundur; Horta, Bernardo L.; Kardia, Sharon L. R.; Liu, Yongmei; Pereira, Alexandre C.; Psaty, Bruce M.; Ridker, Paul M.; van Dam, Rob M.; Gauderman, W. James; Zhu, Xiaofeng; Mook-Kanamori, Dennis O.; Fornage, Myriam; Rotimi, Charles N.; Cupples, L. Adrienne; Kelly, Tanika N.; Fox, Ervin R.; Hayward, Caroline; van Duijn, Cornelia M.; Tai, E Shyong; Wong, Tien Yin; Kooperberg, Charles; Palmas, Walter; Morrison, Alanna C.; Caulfield, Mark J.; Munroe, Patricia B.; Rao, Dabeeru C.; Province, Michael A.; Levy, Daniel
2018-01-01
Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10−5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10−8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10−8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension. PMID:29912962
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Feitosa, Mary F; Kraja, Aldi T; Chasman, Daniel I; Sung, Yun J; Winkler, Thomas W; Ntalla, Ioanna; Guo, Xiuqing; Franceschini, Nora; Cheng, Ching-Yu; Sim, Xueling; Vojinovic, Dina; Marten, Jonathan; Musani, Solomon K; Li, Changwei; Bentley, Amy R; Brown, Michael R; Schwander, Karen; Richard, Melissa A; Noordam, Raymond; Aschard, Hugues; Bartz, Traci M; Bielak, Lawrence F; Dorajoo, Rajkumar; Fisher, Virginia; Hartwig, Fernando P; Horimoto, Andrea R V R; Lohman, Kurt K; Manning, Alisa K; Rankinen, Tuomo; Smith, Albert V; Tajuddin, Salman M; Wojczynski, Mary K; Alver, Maris; Boissel, Mathilde; Cai, Qiuyin; Campbell, Archie; Chai, Jin Fang; Chen, Xu; Divers, Jasmin; Gao, Chuan; Goel, Anuj; Hagemeijer, Yanick; Harris, Sarah E; He, Meian; Hsu, Fang-Chi; Jackson, Anne U; Kähönen, Mika; Kasturiratne, Anuradhani; Komulainen, Pirjo; Kühnel, Brigitte; Laguzzi, Federica; Luan, Jian'an; Matoba, Nana; Nolte, Ilja M; Padmanabhan, Sandosh; Riaz, Muhammad; Rueedi, Rico; Robino, Antonietta; Said, M Abdullah; Scott, Robert A; Sofer, Tamar; Stančáková, Alena; Takeuchi, Fumihiko; Tayo, Bamidele O; van der Most, Peter J; Varga, Tibor V; Vitart, Veronique; Wang, Yajuan; Ware, Erin B; Warren, Helen R; Weiss, Stefan; Wen, Wanqing; Yanek, Lisa R; Zhang, Weihua; Zhao, Jing Hua; Afaq, Saima; Amin, Najaf; Amini, Marzyeh; Arking, Dan E; Aung, Tin; Boerwinkle, Eric; Borecki, Ingrid; Broeckel, Ulrich; Brown, Morris; Brumat, Marco; Burke, Gregory L; Canouil, Mickaël; Chakravarti, Aravinda; Charumathi, Sabanayagam; Ida Chen, Yii-Der; Connell, John M; Correa, Adolfo; de Las Fuentes, Lisa; de Mutsert, Renée; de Silva, H Janaka; Deng, Xuan; Ding, Jingzhong; Duan, Qing; Eaton, Charles B; Ehret, Georg; Eppinga, Ruben N; Evangelou, Evangelos; Faul, Jessica D; Felix, Stephan B; Forouhi, Nita G; Forrester, Terrence; Franco, Oscar H; Friedlander, Yechiel; Gandin, Ilaria; Gao, He; Ghanbari, Mohsen; Gigante, Bruna; Gu, C Charles; Gu, Dongfeng; Hagenaars, Saskia P; Hallmans, Göran; Harris, Tamara B; He, Jiang; Heikkinen, Sami; Heng, Chew-Kiat; Hirata, Makoto; Howard, Barbara V; Ikram, M Arfan; John, Ulrich; Katsuya, Tomohiro; Khor, Chiea Chuen; Kilpeläinen, Tuomas O; Koh, Woon-Puay; Krieger, José E; Kritchevsky, Stephen B; Kubo, Michiaki; Kuusisto, Johanna; Lakka, Timo A; Langefeld, Carl D; Langenberg, Claudia; Launer, Lenore J; Lehne, Benjamin; Lewis, Cora E; Li, Yize; Lin, Shiow; Liu, Jianjun; Liu, Jingmin; Loh, Marie; Louie, Tin; Mägi, Reedik; McKenzie, Colin A; Meitinger, Thomas; Metspalu, Andres; Milaneschi, Yuri; Milani, Lili; Mohlke, Karen L; Momozawa, Yukihide; Nalls, Mike A; Nelson, Christopher P; Sotoodehnia, Nona; Norris, Jill M; O'Connell, Jeff R; Palmer, Nicholette D; Perls, Thomas; Pedersen, Nancy L; Peters, Annette; Peyser, Patricia A; Poulter, Neil; Raffel, Leslie J; Raitakari, Olli T; Roll, Kathryn; Rose, Lynda M; Rosendaal, Frits R; Rotter, Jerome I; Schmidt, Carsten O; Schreiner, Pamela J; Schupf, Nicole; Scott, William R; Sever, Peter S; Shi, Yuan; Sidney, Stephen; Sims, Mario; Sitlani, Colleen M; Smith, Jennifer A; Snieder, Harold; Starr, John M; Strauch, Konstantin; Stringham, Heather M; Tan, Nicholas Y Q; Tang, Hua; Taylor, Kent D; Teo, Yik Ying; Tham, Yih Chung; Turner, Stephen T; Uitterlinden, André G; Vollenweider, Peter; Waldenberger, Melanie; Wang, Lihua; Wang, Ya Xing; Wei, Wen Bin; Williams, Christine; Yao, Jie; Yu, Caizheng; Yuan, Jian-Min; Zhao, Wei; Zonderman, Alan B; Becker, Diane M; Boehnke, Michael; Bowden, Donald W; Chambers, John C; Deary, Ian J; Esko, Tõnu; Farrall, Martin; Franks, Paul W; Freedman, Barry I; Froguel, Philippe; Gasparini, Paolo; Gieger, Christian; Jonas, Jost Bruno; Kamatani, Yoichiro; Kato, Norihiro; Kooner, Jaspal S; Kutalik, Zoltán; Laakso, Markku; Laurie, Cathy C; Leander, Karin; Lehtimäki, Terho; Study, Lifelines Cohort; Magnusson, Patrik K E; Oldehinkel, Albertine J; Penninx, Brenda W J H; Polasek, Ozren; Porteous, David J; Rauramaa, Rainer; Samani, Nilesh J; Scott, James; Shu, Xiao-Ou; van der Harst, Pim; Wagenknecht, Lynne E; Wareham, Nicholas J; Watkins, Hugh; Weir, David R; Wickremasinghe, Ananda R; Wu, Tangchun; Zheng, Wei; Bouchard, Claude; Christensen, Kaare; Evans, Michele K; Gudnason, Vilmundur; Horta, Bernardo L; Kardia, Sharon L R; Liu, Yongmei; Pereira, Alexandre C; Psaty, Bruce M; Ridker, Paul M; van Dam, Rob M; Gauderman, W James; Zhu, Xiaofeng; Mook-Kanamori, Dennis O; Fornage, Myriam; Rotimi, Charles N; Cupples, L Adrienne; Kelly, Tanika N; Fox, Ervin R; Hayward, Caroline; van Duijn, Cornelia M; Tai, E Shyong; Wong, Tien Yin; Kooperberg, Charles; Palmas, Walter; Rice, Kenneth; Morrison, Alanna C; Elliott, Paul; Caulfield, Mark J; Munroe, Patricia B; Rao, Dabeeru C; Province, Michael A; Levy, Daniel
2018-01-01
Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.
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2010-01-01
Introduction Several common breast cancer genetic susceptibility variants have recently been identified. We aimed to determine how these variants combine with a subset of other known risk factors to influence breast cancer risk in white women of European ancestry using case-control studies participating in the Breast Cancer Association Consortium. Methods We evaluated two-way interactions between each of age at menarche, ever having had a live birth, number of live births, age at first birth and body mass index (BMI) and each of 12 single nucleotide polymorphisms (SNPs) (10q26-rs2981582 (FGFR2), 8q24-rs13281615, 11p15-rs3817198 (LSP1), 5q11-rs889312 (MAP3K1), 16q12-rs3803662 (TOX3), 2q35-rs13387042, 5p12-rs10941679 (MRPS30), 17q23-rs6504950 (COX11), 3p24-rs4973768 (SLC4A7), CASP8-rs17468277, TGFB1-rs1982073 and ESR1-rs3020314). Interactions were tested for by fitting logistic regression models including per-allele and linear trend main effects for SNPs and risk factors, respectively, and single-parameter interaction terms for linear departure from independent multiplicative effects. Results These analyses were applied to data for up to 26,349 invasive breast cancer cases and up to 32,208 controls from 21 case-control studies. No statistical evidence of interaction was observed beyond that expected by chance. Analyses were repeated using data from 11 population-based studies, and results were very similar. Conclusions The relative risks for breast cancer associated with the common susceptibility variants identified to date do not appear to vary across women with different reproductive histories or body mass index (BMI). The assumption of multiplicative combined effects for these established genetic and other risk factors in risk prediction models appears justified. PMID:21194473
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Fields, Peter D.; Bourgeois, Yann; Du Pasquier, Louis; Ebert, Dieter
2017-01-01
Negative frequency-dependent selection (NFDS) is an evolutionary mechanism suggested to govern host-parasite coevolution and the maintenance of genetic diversity at host resistance loci, such as the vertebrate MHC and R-genes in plants. Matching-allele interactions of hosts and parasites that prevent the emergence of host and parasite genotypes that are universally resistant and infective are a genetic mechanism predicted to underpin NFDS. The underlying genetics of matching-allele interactions are unknown even in host-parasite systems with empirical support for coevolution by NFDS, as is the case for the planktonic crustacean Daphnia magna and the bacterial pathogen Pasteuria ramosa. We fine-map one locus associated with D. magna resistance to P. ramosa and genetically characterize two haplotypes of the Pasteuria resistance (PR-) locus using de novo genome and transcriptome sequencing. Sequence comparison of PR-locus haplotypes finds dramatic structural polymorphisms between PR-locus haplotypes including a large portion of each haplotype being composed of non-homologous sequences resulting in haplotypes differing in size by 66 kb. The high divergence of PR-locus haplotypes suggest a history of multiple, diverse and repeated instances of structural mutation events and restricted recombination. Annotation of the haplotypes reveals striking differences in gene content. In particular, a group of glycosyltransferase genes that is present in the susceptible but absent in the resistant haplotype. Moreover, in natural populations, we find that the PR-locus polymorphism is associated with variation in resistance to different P. ramosa genotypes, pointing to the PR-locus polymorphism as being responsible for the matching-allele interactions that have been previously described for this system. Our results conclusively identify a genetic basis for the matching-allele interaction observed in a coevolving host-parasite system and provide a first insight into its molecular basis. PMID:28222092
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Bento, Gilberto; Routtu, Jarkko; Fields, Peter D; Bourgeois, Yann; Du Pasquier, Louis; Ebert, Dieter
2017-02-01
Negative frequency-dependent selection (NFDS) is an evolutionary mechanism suggested to govern host-parasite coevolution and the maintenance of genetic diversity at host resistance loci, such as the vertebrate MHC and R-genes in plants. Matching-allele interactions of hosts and parasites that prevent the emergence of host and parasite genotypes that are universally resistant and infective are a genetic mechanism predicted to underpin NFDS. The underlying genetics of matching-allele interactions are unknown even in host-parasite systems with empirical support for coevolution by NFDS, as is the case for the planktonic crustacean Daphnia magna and the bacterial pathogen Pasteuria ramosa. We fine-map one locus associated with D. magna resistance to P. ramosa and genetically characterize two haplotypes of the Pasteuria resistance (PR-) locus using de novo genome and transcriptome sequencing. Sequence comparison of PR-locus haplotypes finds dramatic structural polymorphisms between PR-locus haplotypes including a large portion of each haplotype being composed of non-homologous sequences resulting in haplotypes differing in size by 66 kb. The high divergence of PR-locus haplotypes suggest a history of multiple, diverse and repeated instances of structural mutation events and restricted recombination. Annotation of the haplotypes reveals striking differences in gene content. In particular, a group of glycosyltransferase genes that is present in the susceptible but absent in the resistant haplotype. Moreover, in natural populations, we find that the PR-locus polymorphism is associated with variation in resistance to different P. ramosa genotypes, pointing to the PR-locus polymorphism as being responsible for the matching-allele interactions that have been previously described for this system. Our results conclusively identify a genetic basis for the matching-allele interaction observed in a coevolving host-parasite system and provide a first insight into its molecular basis.
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Kitchen, James L.; Allaby, Robin G.
2013-01-01
Selection and adaptation of individuals to their underlying environments are highly dynamical processes, encompassing interactions between the individual and its seasonally changing environment, synergistic or antagonistic interactions between individuals and interactions amongst the regulatory genes within the individual. Plants are useful organisms to study within systems modeling because their sedentary nature simplifies interactions between individuals and the environment, and many important plant processes such as germination or flowering are dependent on annual cycles which can be disrupted by climate behavior. Sedentism makes plants relevant candidates for spatially explicit modeling that is tied in with dynamical environments. We propose that in order to fully understand the complexities behind plant adaptation, a system that couples aspects from systems biology with population and landscape genetics is required. A suitable system could be represented by spatially explicit individual-based models where the virtual individuals are located within time-variable heterogeneous environments and contain mutable regulatory gene networks. These networks could directly interact with the environment, and should provide a useful approach to studying plant adaptation. PMID:27137364
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Nettleton, Jennifer A; McKeown, Nicola M; Kanoni, Stavroula; Lemaitre, Rozenn N; Hivert, Marie-France; Ngwa, Julius; van Rooij, Frank J A; Sonestedt, Emily; Wojczynski, Mary K; Ye, Zheng; Tanaka, Tosh; Garcia, Melissa; Anderson, Jennifer S; Follis, Jack L; Djousse, Luc; Mukamal, Kenneth; Papoutsakis, Constantina; Mozaffarian, Dariush; Zillikens, M Carola; Bandinelli, Stefania; Bennett, Amanda J; Borecki, Ingrid B; Feitosa, Mary F; Ferrucci, Luigi; Forouhi, Nita G; Groves, Christopher J; Hallmans, Goran; Harris, Tamara; Hofman, Albert; Houston, Denise K; Hu, Frank B; Johansson, Ingegerd; Kritchevsky, Stephen B; Langenberg, Claudia; Launer, Lenore; Liu, Yongmei; Loos, Ruth J; Nalls, Michael; Orho-Melander, Marju; Renstrom, Frida; Rice, Kenneth; Riserus, Ulf; Rolandsson, Olov; Rotter, Jerome I; Saylor, Georgia; Sijbrands, Eric J G; Sjogren, Per; Smith, Albert; Steingrímsdóttir, Laufey; Uitterlinden, André G; Wareham, Nicholas J; Prokopenko, Inga; Pankow, James S; van Duijn, Cornelia M; Florez, Jose C; Witteman, Jacqueline C M; Dupuis, Josée; Dedoussis, George V; Ordovas, Jose M; Ingelsson, Erik; Cupples, L Adrienne; Siscovick, David S; Franks, Paul W; Meigs, James B
2010-12-01
Whole-grain foods are touted for multiple health benefits, including enhancing insulin sensitivity and reducing type 2 diabetes risk. Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with fasting glucose and insulin concentrations in individuals free of diabetes. We tested the hypothesis that whole-grain food intake and genetic variation interact to influence concentrations of fasting glucose and insulin. Via meta-analysis of data from 14 cohorts comprising ∼ 48,000 participants of European descent, we studied interactions of whole-grain intake with loci previously associated in GWAS with fasting glucose (16 loci) and/or insulin (2 loci) concentrations. For tests of interaction, we considered a P value <0.0028 (0.05 of 18 tests) as statistically significant. Greater whole-grain food intake was associated with lower fasting glucose and insulin concentrations independent of demographics, other dietary and lifestyle factors, and BMI (β [95% CI] per 1-serving-greater whole-grain intake: -0.009 mmol/l glucose [-0.013 to -0.005], P < 0.0001 and -0.011 pmol/l [ln] insulin [-0.015 to -0.007], P = 0.0003). No interactions met our multiple testing-adjusted statistical significance threshold. The strongest SNP interaction with whole-grain intake was rs780094 (GCKR) for fasting insulin (P = 0.006), where greater whole-grain intake was associated with a smaller reduction in fasting insulin concentrations in those with the insulin-raising allele. Our results support the favorable association of whole-grain intake with fasting glucose and insulin and suggest a potential interaction between variation in GCKR and whole-grain intake in influencing fasting insulin concentrations.
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Stillwell, R Craig; Wallin, William G; Hitchcock, Lisa J; Fox, Charles W
2007-08-01
Most studies of phenotypic plasticity investigate the effects of an individual environmental factor on organism phenotypes. However, organisms exist in an ecologically complex world where multiple environmental factors can interact to affect growth, development and life histories. Here, using a multifactorial experimental design, we examine the separate and interactive effects of two environmental factors, rearing host species (Vigna radiata, Vigna angularis and Vigna unguiculata) and temperature (20, 25, 30 and 35 degrees C), on growth and life history traits in two populations [Burkina Faso (BF) and South India (SI)] of the seed beetle, Callosobruchus maculatus. The two study populations of beetles responded differently to both rearing host and temperature. We also found a significant interaction between rearing host and temperature for body size, growth rate and female lifetime fecundity but not larval development time or larval survivorship. The interaction was most apparent for growth rate; the variance in growth rate among hosts increased with increasing temperature. However, the details of host differences differed between our two study populations; the degree to which V. unguiculata was a better host than V. angularis or V. radiata increased at higher temperatures for BF beetles, whereas the degree to which V. unguiculata was the worst host increased at higher temperatures for SI beetles. We also found that the heritabilities of body mass, growth rate and fecundity were similar among rearing hosts and temperatures, and that the cross-temperature genetic correlation was not affected by rearing host, suggesting that genetic architecture is generally stable across rearing conditions. The most important finding of our study is that multiple environmental factors can interact to affect organism growth, but the degree of interaction, and thus the degree of complexity of phenotypic plasticity, varies among traits and between populations.
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Genetic Basis of Atherosclerosis: Insights from Mice and Humans
Stylianou, Ioannis M.; Bauer, Robert C.; Reilly, Muredach P.; Rader, Daniel J.
2012-01-01
Atherosclerosis is a complex and heritable disease involving multiple cell types and the interactions of many different molecular pathways. The genetic and molecular mechanisms of atherosclerosis have in part been elucidated by mouse models; at least 100 different genes have been shown to influence atherosclerosis in mice. Importantly, unbiased genome-wide association studies have recently identified a number of novel loci robustly associated with atherosclerotic coronary artery disease (CAD). Here we review the genetic data elucidated from mouse models of atherosclerosis, as well as significant associations for human CAD. Furthermore, we discuss in greater detail some of these novel human CAD loci. The combination of mouse and human genetics has the potential to identify and validate novel genes that influence atherosclerosis, some of which may be candidates for new therapeutic approaches. PMID:22267839
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Adrian, Molly; Kiff, Cara; Glazner, Chris; Kohen, Ruth; Tracy, Julia Helen; Zhou, Chuan; McCauley, Elizabeth; Stoep, Ann Vander
2015-01-01
Objective The objective of this study was to apply a Bayesian statistical analytic approach that minimizes multiple testing problems to explore the combined effects of chronic low familial support and variants in 12 candidate genes on risk for a common and debilitating childhood mental health condition. Method Bayesian mixture modeling was used to examine gene by environment interactions among genetic variants and environmental factors (family support) associated in previous studies with the occurrence of comorbid depression and disruptive behavior disorders youth, using a sample of 255 children. Results One main effects, variants in the oxytocin receptor (OXTR, rs53576) was associated with increased risk for comorbid disorders. Two significant gene x environment and one signification gene x gene interaction emerged. Variants in the nicotinic acetylcholine receptor α5 subunit (CHRNA5, rs16969968) and in the glucocorticoid receptor chaperone protein FK506 binding protein 5 (FKBP5, rs4713902) interacted with chronic low family support in association with child mental health status. One gene x gene interaction, 5-HTTLPR variant of the serotonin transporter (SERT/SLC6A4) in combination with μ opioid receptor (OPRM1, rs1799971) was associated with comorbid depression and conduct problems. Conclusions Results indicate that Bayesian modeling is a feasible strategy for conducting behavioral genetics research. This approach, combined with an optimized genetic selection strategy (Vrieze, Iacono, & McGue, 2012), revealed genetic variants involved in stress regulation ( FKBP5, SERTxOPMR), social bonding (OXTR), and nicotine responsivity (CHRNA5) in predicting comorbid status. PMID:26228411
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Kitzlerová, Eva; Lelková, Petra; Jirák, Roman; Zvěřová, Martina; Hroudová, Jana; Manukyan, Ada; Martásek, Pavel; Raboch, Jiří
2018-01-01
Background Several genetic susceptibility loci for major depressive disorder (MDD) or Alzheimer’s disease (AD) have been described. Interactions among polymorphisms are thought to explain the differences between low- and high-risk groups. We tested for the contribution of interactions between multiple functional polymorphisms in the risk of MDD or AD. Material/Methods A genetic association case-control study was performed in 68 MDD cases, 84 AD cases (35 of them with comorbid depression), and 90 controls. The contribution of 7 polymorphisms from 5 genes (APOE, HSPA1A, SLC6A4, HTR2A, and BDNF) related to risk of MDD or AD development was analyzed. Results Significant associations were found between MDD and interactions among polymorphisms in HSPA1A, SLC6A4, and BDNF or HSPA1A, BDNF, and APOE genes. For polymorphisms in the APOE gene in AD, significant differences were confirmed on the distributions of alleles and genotype rates compared to the control or MDD. Increased probability of comorbid depression was found in patients with AD who do not carry the ɛ4 allele of APOE. Conclusions Assessment of the interactions among polymorphisms of susceptibility loci in both MDD and AD confirmed a synergistic effect of genetic factors influencing inflammatory, serotonergic, and neurotrophic pathways at these heterogenous complex diseases. The effect of interactions was greater in MDD than in AD. A presence of the ɛ4 allele was confirmed as a genetic susceptibility factor in AD. Our findings indicate a role of APOE genotype in onset of comorbid depression in a subgroup of patients with AD who are not carriers of the APOE ɛ4 allele. PMID:29703883
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Genome organization and long-range regulation of gene expression by enhancers
Smallwood, Andrea; Ren, Bing
2014-01-01
It is now well accepted that cell-type specific gene regulation is under the purview of enhancers. Great strides have been made recently to characterize and identify enhancers both genetically and epigenetically for multiple cell types and species, but efforts have just begun to link enhancers to their target promoters. Mapping these interactions and understanding how the 3D landscape of the genome constrains such interactions is fundamental to our understanding of mammalian gene regulation. Here, we review recent progress in mapping long-range regulatory interactions in mammalian genomes, focusing on transcriptional enhancers and chromatin organization principles. PMID:23465541
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Pike, Andrew; Dimopoulos, George
2018-01-01
Mosquitoes that have been genetically engineered for resistance to human pathogens are a potential new tool for controlling vector-borne disease. However, genetic modification may have unintended off-target effects that could affect the mosquitoes' utility for disease control. We measured the resistance of five genetically modified Plasmodium-suppressing Anopheles stephensi lines to o'nyong'nyong virus, four classes of insecticides, and diverse Plasmodium falciparum field isolates and characterized the interactions between our genetic modifications and infection with the bacterium Wolbachia. The genetic modifications did not alter the mosquitoes' resistance to either o'nyong'nyong virus or insecticides, and the mosquitoes were equally resistant to all tested P. falciparum strains, regardless of Wolbachia infection status. These results indicate that mosquitoes can be genetically modified for resistance to malaria parasite infection and remain compatible with other vector-control measures without becoming better vectors for other pathogens.
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Characterizing Male–Female Interactions Using Natural Genetic Variation in Drosophila melanogaster
Reinhart, Michael; Carney, Tara; Clark, Andrew G.
2015-01-01
Drosophila melanogaster females commonly mate with multiple males establishing the opportunity for pre- and postcopulatory sexual selection. Traits impacting sexual selection can be affected by a complex interplay of the genotypes of the competing males, the genotype of the female, and compatibilities between the males and females. We scored males from 96 2nd and 94 3rd chromosome substitution lines for traits affecting reproductive success when mated with females from 3 different genetic backgrounds. The traits included male-induced female refractoriness, male remating ability, the proportion of offspring sired under competitive conditions and male-induced female fecundity. We observed significant effects of male line, female genetic background, and strong male by female interactions. Some males appeared to be “generalists” and performed consistently across the different females; other males appeared to be “specialists” and performed very well with a particular female and poorly with others. “Specialist” males did not, however, prefer to court those females with whom they had the highest reproductive fitness. Using 143 polymorphisms in male reproductive genes, we mapped several genes that had consistent effects across the different females including a derived, high fitness allele in Acp26Aa that may be the target of adaptive evolution. We also identified a polymorphism upstream of PebII that may interact with the female genetic background to affect male-induced refractoriness to remating. These results suggest that natural variation in PebII might contribute to the observed male–female interactions. PMID:25425680
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Dobson, Adam J.; Chaston, John M.; Newell, Peter D.; Donahue, Leanne; Hermann, Sara L.; Sannino, David R.; Westmiller, Stephanie; Wong, Adam C.-N.; Clark, Andrew G.; Lazzaro, Brian P.; Douglas, Angela E.
2015-01-01
Animals bear communities of gut microorganisms with substantial effects on animal nutrition, but the host genetic basis of these effects is unknown. Here, we use Drosophila to demonstrate substantial among-genotype variation in the effects of eliminating the gut microbiota on five host nutritional indices (weight, and protein, lipid, glucose and glycogen contents); this includes variation in both the magnitude and direction of microbiota-dependent effects. Genome-wide associations to identify the genetic basis of the microbiota-dependent variation reveal polymorphisms in largely non-overlapping sets of genes associated with variation in the nutritional traits, including strong representation of conserved genes functioning in signaling. Key genes identified by the GWA study are validated by loss-of-function mutations that altered microbiota-dependent nutritional effects. We conclude that the microbiota interacts with the animal at multiple points in the signaling and regulatory networks that determine animal nutrition. These interactions with the microbiota are likely conserved across animals, including humans. PMID:25692519
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Gut Microbiome and Infant Health: Brain-Gut-Microbiota Axis and Host Genetic Factors.
Cong, Xiaomei; Xu, Wanli; Romisher, Rachael; Poveda, Samantha; Forte, Shaina; Starkweather, Angela; Henderson, Wendy A
2016-09-01
The development of the neonatal gut microbiome is influenced by multiple factors, such as delivery mode, feeding, medication use, hospital environment, early life stress, and genetics. The dysbiosis of gut microbiota persists during infancy, especially in high-risk preterm infants who experience lengthy stays in the Neonatal intensive care unit (NICU). Infant microbiome evolutionary trajectory is essentially parallel with the host (infant) neurodevelopmental process and growth. The role of the gut microbiome, the brain-gut signaling system, and its interaction with the host genetics have been shown to be related to both short and long term infant health and bio-behavioral development. The investigation of potential dysbiosis patterns in early childhood is still lacking and few studies have addressed this host-microbiome co-developmental process. Further research spanning a variety of fields of study is needed to focus on the mechanisms of brain-gut-microbiota signaling system and the dynamic host-microbial interaction in the regulation of health, stress and development in human newborns.
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Kubo, Takahiko; Yoshimura, Atsushi; Kurata, Nori
2016-05-03
Pollen killer genes disable noncarrier pollens, and are responsible for male sterility and segregation distortion in hybrid populations of distantly related plant species. The genetic networks and the molecular mechanisms underlying the pollen killer system remain largely unknown. Two pollen killer genes, S24 and S35, have been found in an intersubspecific cross of Oryza sativa ssp. indica and japonica The effect of S24 is counteracted by an unlinked locus EFS Additionally, S35 has been proposed to interact with S24 to induce pollen sterility. These genetic interactions are suggestive of a single S24-centric genetic pathway (EFS-S24-S35) for the pollen killer system. To examine this hypothetical genetic pathway, the S35 and the S24 regions were further characterized and genetically dissected in this study. Our results indicated that S35 causes pollen sterility independently of both the EFS and S24 genes, but is dependent on a novel gene close to the S24 locus, named incentive for killing pollen (INK). We confirmed the phenotypic effect of the INK gene separately from the S24 gene, and identified the INK locus within an interval of less than 0.6 Mb on rice chromosome 5. This study characterized the genetic effect of the two independent genetic pathways of INK-S35 and EFS-S24 in indica-japonica hybrid progeny. Our results provide clear evidence that hybrid male sterility in rice is caused by several pollen killer networks with multiple factors positively and negatively regulating pollen killer genes. Copyright © 2016 Kubo et al.
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Kubo, Takahiko; Yoshimura, Atsushi; Kurata, Nori
2016-01-01
Pollen killer genes disable noncarrier pollens, and are responsible for male sterility and segregation distortion in hybrid populations of distantly related plant species. The genetic networks and the molecular mechanisms underlying the pollen killer system remain largely unknown. Two pollen killer genes, S24 and S35, have been found in an intersubspecific cross of Oryza sativa ssp. indica and japonica. The effect of S24 is counteracted by an unlinked locus EFS. Additionally, S35 has been proposed to interact with S24 to induce pollen sterility. These genetic interactions are suggestive of a single S24-centric genetic pathway (EFS–S24–S35) for the pollen killer system. To examine this hypothetical genetic pathway, the S35 and the S24 regions were further characterized and genetically dissected in this study. Our results indicated that S35 causes pollen sterility independently of both the EFS and S24 genes, but is dependent on a novel gene close to the S24 locus, named incentive for killing pollen (INK). We confirmed the phenotypic effect of the INK gene separately from the S24 gene, and identified the INK locus within an interval of less than 0.6 Mb on rice chromosome 5. This study characterized the genetic effect of the two independent genetic pathways of INK–S35 and EFS–S24 in indica–japonica hybrid progeny. Our results provide clear evidence that hybrid male sterility in rice is caused by several pollen killer networks with multiple factors positively and negatively regulating pollen killer genes. PMID:27172610
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Adaptive genetic variation mediates bottom-up and top-down control in an aquatic ecosystem
Rudman, Seth M.; Rodriguez-Cabal, Mariano A.; Stier, Adrian; Sato, Takuya; Heavyside, Julian; El-Sabaawi, Rana W.; Crutsinger, Gregory M.
2015-01-01
Research in eco-evolutionary dynamics and community genetics has demonstrated that variation within a species can have strong impacts on associated communities and ecosystem processes. Yet, these studies have centred around individual focal species and at single trophic levels, ignoring the role of phenotypic variation in multiple taxa within an ecosystem. Given the ubiquitous nature of local adaptation, and thus intraspecific variation, we sought to understand how combinations of intraspecific variation in multiple species within an ecosystem impacts its ecology. Using two species that co-occur and demonstrate adaptation to their natal environments, black cottonwood (Populus trichocarpa) and three-spined stickleback (Gasterosteus aculeatus), we investigated the effects of intraspecific phenotypic variation on both top-down and bottom-up forces using a large-scale aquatic mesocosm experiment. Black cottonwood genotypes exhibit genetic variation in their productivity and consequently their leaf litter subsidies to the aquatic system, which mediates the strength of top-down effects from stickleback on prey abundances. Abundances of four common invertebrate prey species and available phosphorous, the most critically limiting nutrient in freshwater systems, are dictated by the interaction between genetic variation in cottonwood productivity and stickleback morphology. These interactive effects fit with ecological theory on the relationship between productivity and top-down control and are comparable in strength to the effects of predator addition. Our results illustrate that intraspecific variation, which can evolve rapidly, is an under-appreciated driver of community structure and ecosystem function, demonstrating that a multi-trophic perspective is essential to understanding the role of evolution in structuring ecological patterns. PMID:26203004
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Adaptive genetic variation mediates bottom-up and top-down control in an aquatic ecosystem.
Rudman, Seth M; Rodriguez-Cabal, Mariano A; Stier, Adrian; Sato, Takuya; Heavyside, Julian; El-Sabaawi, Rana W; Crutsinger, Gregory M
2015-08-07
Research in eco-evolutionary dynamics and community genetics has demonstrated that variation within a species can have strong impacts on associated communities and ecosystem processes. Yet, these studies have centred around individual focal species and at single trophic levels, ignoring the role of phenotypic variation in multiple taxa within an ecosystem. Given the ubiquitous nature of local adaptation, and thus intraspecific variation, we sought to understand how combinations of intraspecific variation in multiple species within an ecosystem impacts its ecology. Using two species that co-occur and demonstrate adaptation to their natal environments, black cottonwood (Populus trichocarpa) and three-spined stickleback (Gasterosteus aculeatus), we investigated the effects of intraspecific phenotypic variation on both top-down and bottom-up forces using a large-scale aquatic mesocosm experiment. Black cottonwood genotypes exhibit genetic variation in their productivity and consequently their leaf litter subsidies to the aquatic system, which mediates the strength of top-down effects from stickleback on prey abundances. Abundances of four common invertebrate prey species and available phosphorous, the most critically limiting nutrient in freshwater systems, are dictated by the interaction between genetic variation in cottonwood productivity and stickleback morphology. These interactive effects fit with ecological theory on the relationship between productivity and top-down control and are comparable in strength to the effects of predator addition. Our results illustrate that intraspecific variation, which can evolve rapidly, is an under-appreciated driver of community structure and ecosystem function, demonstrating that a multi-trophic perspective is essential to understanding the role of evolution in structuring ecological patterns. © 2015 The Author(s).
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Improving drug safety: From adverse drug reaction knowledge discovery to clinical implementation.
Tan, Yuxiang; Hu, Yong; Liu, Xiaoxiao; Yin, Zhinan; Chen, Xue-Wen; Liu, Mei
2016-11-01
Adverse drug reactions (ADRs) are a major public health concern, causing over 100,000 fatalities in the United States every year with an annual cost of $136 billion. Early detection and accurate prediction of ADRs is thus vital for drug development and patient safety. Multiple scientific disciplines, namely pharmacology, pharmacovigilance, and pharmacoinformatics, have been addressing the ADR problem from different perspectives. With the same goal of improving drug safety, this article summarizes and links the research efforts in the multiple disciplines into a single framework from comprehensive understanding of the interactions between drugs and biological system and the identification of genetic and phenotypic predispositions of patients susceptible to higher ADR risks and finally to the current state of implementation of medication-related decision support systems. We start by describing available computational resources for building drug-target interaction networks with biological annotations, which provides a fundamental knowledge for ADR prediction. Databases are classified by functions to help users in selection. Post-marketing surveillance is then introduced where data-driven approach can not only enhance the prediction accuracy of ADRs but also enables the discovery of genetic and phenotypic risk factors of ADRs. Understanding genetic risk factors for ADR requires well organized patient genetics information and analysis by pharmacogenomic approaches. Finally, current state of clinical decision support systems is presented and described how clinicians can be assisted with the integrated knowledgebase to minimize the risk of ADR. This review ends with a discussion of existing challenges in each of disciplines with potential solutions and future directions. Copyright © 2016 Elsevier Inc. All rights reserved.
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Tang, Xinyu; Cleves, Mario A; Nick, Todd G; Li, Ming; MacLeod, Stewart L; Erickson, Stephen W; Li, Jingyun; Shaw, Gary M; Mosley, Bridget S; Hobbs, Charlotte A
2015-06-01
Right-sided and left-sided obstructive heart defects (OHDs) are subtypes of congenital heart defects, in which the heart valves, arteries, or veins are abnormally narrow or blocked. Previous studies have suggested that the development of OHDs involved a complex interplay between genetic variants and maternal factors. Using the data from 569 OHD case families and 1,644 control families enrolled in the National Birth Defects Prevention Study (NBDPS) between 1997 and 2008, we conducted an analysis to investigate the genetic effects of 877 single nucleotide polymorphisms (SNPs) in 60 candidate genes for association with the risk of OHDs, and their interactions with maternal use of folic acid supplements, and pre-pregnancy obesity. Applying log-linear models based on the hybrid design, we identified a SNP in methylenetetrahydrofolate reductase (MTHFR) gene (C677T polymorphism) with a main genetic effect on the occurrence of OHDs. In addition, multiple SNPs in betaine-homocysteine methyltransferase (BHMT and BHMT2) were also identified to be associated with the occurrence of OHDs through significant main infant genetic effects and interaction effects with maternal use of folic acid supplements. We also identified multiple SNPs in glutamate-cysteine ligase, catalytic subunit (GCLC) and DNA (cytosine-5-)-methyltransferase 3 beta (DNMT3B) that were associated with elevated risk of OHDs among obese women. Our findings suggested that the risk of OHDs was closely related to a combined effect of variations in genes in the folate, homocysteine, or glutathione/transsulfuration pathways, maternal use of folic acid supplements and pre-pregnancy obesity. © 2015 Wiley Periodicals, Inc.
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Genetic studies of human neuropathic pain conditions: a review
Zorina-Lichtenwalter, Katerina; Parisien, Marc; Diatchenko, Luda
2018-01-01
Abstract Numerous studies have shown associations between genetic variants and neuropathic pain disorders. Rare monogenic disorders are caused by mutations of substantial effect size in a single gene, whereas common disorders are likely to have a contribution from multiple genetic variants of mild effect size, representing different biological pathways. In this review, we survey the reported genetic contributors to neuropathic pain and submit them for validation in a 150,000-participant sample of the U.K. Biobank cohort. Successfully replicated association with a neuropathic pain construct for 2 variants in IL10 underscores the importance of neuroimmune interactions, whereas genome-wide significant association with low back pain (P = 1.3e-8) and false discovery rate 5% significant associations with hip, knee, and neck pain for variant rs7734804 upstream of the MAT2B gene provide evidence of shared contributing mechanisms to overlapping pain conditions at the molecular genetic level. PMID:29240606
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Genetic and environmental variance in content dimensions of the MMPI.
Rose, R J
1988-08-01
To evaluate genetic and environmental variance in the Minnesota Multiphasic Personality Inventory (MMPI), I studied nine factor scales identified in the first item factor analysis of normal adult MMPIs in a sample of 820 adolescent and young adult co-twins. Conventional twin comparisons documented heritable variance in six of the nine MMPI factors (Neuroticism, Psychoticism, Extraversion, Somatic Complaints, Inadequacy, and Cynicism), whereas significant influence from shared environmental experience was found for four factors (Masculinity versus Femininity, Extraversion, Religious Orthodoxy, and Intellectual Interests). Genetic variance in the nine factors was more evident in results from twin sisters than those of twin brothers, and a developmental-genetic analysis, using hierarchical multiple regressions of double-entry matrixes of the twins' raw data, revealed that in four MMPI factor scales, genetic effects were significantly modulated by age or gender or their interaction during the developmental period from early adolescence to early adulthood.
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The Impact of Familial Autism Diagnoses on Autism Symptomatology in Infants and Toddlers
ERIC Educational Resources Information Center
Kozlowski, Alison M.; Matson, Johnny L.; Worley, Julie A.
2012-01-01
Debate regarding the etiology of Autism Spectrum Disorders (ASD) is on the rise with numerous theories being put forth. Currently, the theory with the most empirical support is the interaction of multiple genes. Many studies have provided evidence that as the incidence of ASD increases so do genetic similarities. However, very little research has…
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USDA-ARS?s Scientific Manuscript database
Cardiometabolic diseases are the leading cause of death worldwide and are strongly linked to both genetic and nutritional factors. The field of nutrigenomics encompasses multiple approaches aimed at understanding the effects of diet on health or disease development, including nutrigenetic studies in...
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Yamamoto, Satoshi; Ooshima, Yuki; Nakata, Mitsugu; Yano, Takashi; Matsuoka, Kunio; Watanabe, Sayuri; Maeda, Ryouta; Takahashi, Hideki; Takeyama, Michiyasu; Matsumoto, Yoshio; Hashimoto, Tadatoshi
2013-06-01
Gene-targeting technology using mouse embryonic stem (ES) cells has become the "gold standard" for analyzing gene functions and producing disease models. Recently, genetically modified mice with multiple mutations have increasingly been produced to study the interaction between proteins and polygenic diseases. However, introduction of an additional mutation into mice already harboring several mutations by conventional natural crossbreeding is an extremely time- and labor-intensive process. Moreover, to do so in mice with a complex genetic background, several years may be required if the genetic background is to be retained. Establishing ES cells from multiple-mutant mice, or disease-model mice with a complex genetic background, would offer a possible solution. Here, we report the establishment and characterization of novel ES cell lines from a mouse model of Alzheimer's disease (3xTg-AD mouse, Oddo et al. in Neuron 39:409-421, 2003) harboring 3 mutated genes (APPswe, TauP301L, and PS1M146V) and a complex genetic background. Thirty blastocysts were cultured and 15 stable ES cell lines (male: 11; female: 4) obtained. By injecting these ES cells into diploid or tetraploid blastocysts, we generated germline-competent chimeras. Subsequently, we confirmed that F1 mice derived from these animals showed similar biochemical and behavioral characteristics to the original 3xTg-AD mice. Furthermore, we introduced a gene-targeting vector into the ES cells and successfully obtained gene-targeted ES cells, which were then used to generate knockout mice for the targeted gene. These results suggest that the present methodology is effective for introducing an additional mutation into mice already harboring multiple mutated genes and/or a complex genetic background.
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Genetic Mechanisms Leading to Sex Differences Across Common Diseases and Anthropometric Traits
Traglia, Michela; Bseiso, Dina; Gusev, Alexander; Adviento, Brigid; Park, Daniel S.; Mefford, Joel A.; Zaitlen, Noah; Weiss, Lauren A.
2017-01-01
Common diseases often show sex differences in prevalence, onset, symptomology, treatment, or prognosis. Although studies have been performed to evaluate sex differences at specific SNP associations, this work aims to comprehensively survey a number of complex heritable diseases and anthropometric traits. Potential genetically encoded sex differences we investigated include differential genetic liability thresholds or distributions, gene–sex interaction at autosomal loci, major contribution of the X-chromosome, or gene–environment interactions reflected in genes responsive to androgens or estrogens. Finally, we tested the overlap between sex-differential association with anthropometric traits and disease risk. We utilized complementary approaches of assessing GWAS association enrichment and SNP-based heritability estimation to explore explicit sex differences, as well as enrichment in sex-implicated functional categories. We do not find consistent increased genetic load in the lower-prevalence sex, or a disproportionate role for the X-chromosome in disease risk, despite sex-heterogeneity on the X for several traits. We find that all anthropometric traits show less than complete correlation between the genetic contribution to males and females, and find a convincing example of autosome-wide genome-sex interaction in multiple sclerosis (P = 1 × 10−9). We also find some evidence for hormone-responsive gene enrichment, and striking evidence of the contribution of sex-differential anthropometric associations to common disease risk, implying that general mechanisms of sexual dimorphism determining secondary sex characteristics have shared effects on disease risk. PMID:27974502
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Genetic architecture of resistance in Daphnia hosts against two species of host-specific parasites.
Routtu, J; Ebert, D
2015-02-01
Understanding the genetic architecture of host resistance is key for understanding the evolution of host-parasite interactions. Evolutionary models often assume simple genetics based on few loci and strong epistasis. It is unknown, however, whether these assumptions apply to natural populations. Using a quantitative trait loci (QTL) approach, we explore the genetic architecture of resistance in the crustacean Daphnia magna to two of its natural parasites: the horizontally transmitted bacterium Pasteuria ramosa and the horizontally and vertically transmitted microsporidium Hamiltosporidium tvaerminnensis. These two systems have become models for studies on the evolution of host-parasite interactions. In the QTL panel used here, Daphnia's resistance to P. ramosa is controlled by a single major QTL (which explains 50% of the observed variation). Resistance to H. tvaerminnensis horizontal infections shows a signature of a quantitative trait based in multiple loci with weak epistatic interactions (together explaining 38% variation). Resistance to H. tvaerminnensis vertical infections, however, shows only one QTL (explaining 13.5% variance) that colocalizes with one of the QTLs for horizontal infections. QTLs for resistance to Pasteuria and Hamiltosporidium do not colocalize. We conclude that the genetics of resistance in D. magna are drastically different for these two parasites. Furthermore, we infer that based on these and earlier results, the mechanisms of coevolution differ strongly for the two host-parasite systems. Only the Pasteuria-Daphnia system is expected to follow the negative frequency-dependent selection (Red Queen) model. How coevolution works in the Hamiltosporidium-Daphnia system remains unclear.
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Genetic architecture of resistance in Daphnia hosts against two species of host-specific parasites
Routtu, J; Ebert, D
2015-01-01
Understanding the genetic architecture of host resistance is key for understanding the evolution of host–parasite interactions. Evolutionary models often assume simple genetics based on few loci and strong epistasis. It is unknown, however, whether these assumptions apply to natural populations. Using a quantitative trait loci (QTL) approach, we explore the genetic architecture of resistance in the crustacean Daphnia magna to two of its natural parasites: the horizontally transmitted bacterium Pasteuria ramosa and the horizontally and vertically transmitted microsporidium Hamiltosporidium tvaerminnensis. These two systems have become models for studies on the evolution of host–parasite interactions. In the QTL panel used here, Daphnia's resistance to P. ramosa is controlled by a single major QTL (which explains 50% of the observed variation). Resistance to H. tvaerminnensis horizontal infections shows a signature of a quantitative trait based in multiple loci with weak epistatic interactions (together explaining 38% variation). Resistance to H. tvaerminnensis vertical infections, however, shows only one QTL (explaining 13.5% variance) that colocalizes with one of the QTLs for horizontal infections. QTLs for resistance to Pasteuria and Hamiltosporidium do not colocalize. We conclude that the genetics of resistance in D. magna are drastically different for these two parasites. Furthermore, we infer that based on these and earlier results, the mechanisms of coevolution differ strongly for the two host–parasite systems. Only the Pasteuria–Daphnia system is expected to follow the negative frequency-dependent selection (Red Queen) model. How coevolution works in the Hamiltosporidium–Daphnia system remains unclear. PMID:25335558
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Zhang, Qingrun; Long, Quan; Ott, Jurg
2014-06-01
Identifying gene-gene interaction is a hot topic in genome wide association studies. Two fundamental challenges are: (1) how to smartly identify combinations of variants that may be associated with the trait from astronomical number of all possible combinations; and (2) how to test epistatic interaction when all potential combinations are available. We developed AprioriGWAS, which brings two innovations. (1) Based on Apriori, a successful method in field of Frequent Itemset Mining (FIM) in which a pattern growth strategy is leveraged to effectively and accurately reduce search space, AprioriGWAS can efficiently identify genetically associated genotype patterns. (2) To test the hypotheses of epistasis, we adopt a new conditional permutation procedure to obtain reliable statistical inference of Pearson's chi-square test for the [Formula: see text] contingency table generated by associated variants. By applying AprioriGWAS to age-related macular degeneration (AMD) data, we found that: (1) angiopoietin 1 (ANGPT1) and four retinal genes interact with Complement Factor H (CFH). (2) GO term "glycosaminoglycan biosynthetic process" was enriched in AMD interacting genes. The epistatic interactions newly found by AprioriGWAS on AMD data are likely true interactions, since genes interacting with CFH are retinal genes, and GO term enrichment also verified that interaction between glycosaminoglycans (GAGs) and CFH plays an important role in disease pathology of AMD. By applying AprioriGWAS on Bipolar disorder in WTCCC data, we found variants without marginal effect show significant interactions. For example, multiple-SNP genotype patterns inside gene GABRB2 and GRIA1 (AMPA subunit 1 receptor gene). AMPARs are found in many parts of the brain and are the most commonly found receptor in the nervous system. The GABRB2 mediates the fastest inhibitory synaptic transmission in the central nervous system. GRIA1 and GABRB2 are relevant to mental disorders supported by multiple evidences.
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Health-related disparities: influence of environmental factors.
Olden, Kenneth; White, Sandra L
2005-07-01
Racial disparities in health cannot be explained solely on the basis of poverty, access to health care, behavior, or environmental factors. Their complex etiology is dependent on interactions between all these factors plus genetics. Scientists have been slow to consider genetics as a risk factor because genetic polymorphisms tend to be more variable within a race than between races. Now that studies are demonstrating the existence of racial differences in allelic frequencies for multiple genes affecting a single biologic mechanism, the present argument for a significant genetic role in contributing to health disparities is gaining support. Individuals vary, often significantly, in their response to environmental agents. This variability provides a high "background noise" when scientists examine human populations to identify environmental links to disease. This variability often masks important environmental contributors to disease risk and is a major impediment to efforts to investigate the causes of diseases.Fortunately, investments in the various genome projects have led to the development of tools and databases that can be used to help identify the genetic variations in environmental response genes that can lead to such wide differences in disease susceptibility. NIEHS developed the environ-mental genome project to catalog these genetic variants (polymorphisms)and to identify the ones that play a major role in human susceptibility to environmental agents. This information is being used in epidemiologic studies to pinpoint environmental contributors to disease better. The research summarized in this article is critically important for tying genetics and the environment to health disparities, and for the development of a rational approach to gauge environmental threats. Common variants in genes play pivotal roles in determining if or when illness or death result from exposure to drugs or environmental xenobiotics. Most common variants exist in all human populations, but their frequency can vary substantially,rendering individuals or groups more or less susceptible to particular environmental exposures. Such findings are consistent with the highly publicized analogy, "genetics loads the gun, but the environment pulls the trigger." That is, one can inherit the genetic predisposition to develop a disease but will do so only if or when exposed to the environmental trigger. Poor people have approximately the same genetic makeup as everyone else,but they have the unfortunate experience of living and working in environments containing multiple and high levels of carcinogens or other toxicants capable of interacting with susceptibility genes to cause disease.Furthermore, certain disadvantaged ethnic groups may have a higher incidence of certain susceptible genes that render them more vulnerable to adverse effects of the environments they inhabit. For both of these reasons,much of the nation's disease burden could likely be reduced through better environmental protection practices, especially in low-income and minority communities. Of the many implications of polymorphisms and frequency variations for public health and the practice of medicine, however, none is more urgent than the choice of drugs in therapy. Using such knowledge,randomized trials have identified race-specific drug response differences between blacks and whites [42].To date, most knowledge of the health effects of environmental factors is derived from studies of single agents. The reality, though, is that environmental contributions to health disparities are mostly from multiple agents. These simultaneous exposures to multiple risk factors, which may accumulate or interact synergistically, remain to be fully explained and defined.Finally, health disparity is a significant public health problem that cannot be solved using "business as usual" approaches for funding and priority setting. The current emphasis on basic and clinical research at the exclusion of public health and the social sciences does not provide the interdisciplinary research teams necessary to address such a complex problem as health disparities. Although the poor will always be with us, their health could be greatly improved if social, environmental, and genetic scientists could find ways to collaborate and develop more insightful and relevant ways to address the health of disadvantaged communities.
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Xavier, Alencar; Jarquin, Diego; Howard, Reka; Ramasubramanian, Vishnu; Specht, James E; Graef, George L; Beavis, William D; Diers, Brian W; Song, Qijian; Cregan, Perry B; Nelson, Randall; Mian, Rouf; Shannon, J Grover; McHale, Leah; Wang, Dechun; Schapaugh, William; Lorenz, Aaron J; Xu, Shizhong; Muir, William M; Rainey, Katy M
2018-02-02
Genetic improvement toward optimized and stable agronomic performance of soybean genotypes is desirable for food security. Understanding how genotypes perform in different environmental conditions helps breeders develop sustainable cultivars adapted to target regions. Complex traits of importance are known to be controlled by a large number of genomic regions with small effects whose magnitude and direction are modulated by environmental factors. Knowledge of the constraints and undesirable effects resulting from genotype by environmental interactions is a key objective in improving selection procedures in soybean breeding programs. In this study, the genetic basis of soybean grain yield responsiveness to environmental factors was examined in a large soybean nested association population. For this, a genome-wide association to performance stability estimates generated from a Finlay-Wilkinson analysis and the inclusion of the interaction between marker genotypes and environmental factors was implemented. Genomic footprints were investigated by analysis and meta-analysis using a recently published multiparent model. Results indicated that specific soybean genomic regions were associated with stability, and that multiplicative interactions were present between environments and genetic background. Seven genomic regions in six chromosomes were identified as being associated with genotype-by-environment interactions. This study provides insight into genomic assisted breeding aimed at achieving a more stable agronomic performance of soybean, and documented opportunities to exploit genomic regions that were specifically associated with interactions involving environments and subpopulations. Copyright © 2018 Xavier et al.
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Chen, Chunhui; Chen, Chuansheng; Moyzis, Robert; Stern, Hal; He, Qinghua; Li, He; Li, Jin; Zhu, Bi; Dong, Qi
2011-01-01
Traditional behavioral genetic studies (e.g., twin, adoption studies) have shown that human personality has moderate to high heritability, but recent molecular behavioral genetic studies have failed to identify quantitative trait loci (QTL) with consistent effects. The current study adopted a multi-step approach (ANOVA followed by multiple regression and permutation) to assess the cumulative effects of multiple QTLs. Using a system-level (dopamine system) genetic approach, we investigated a personality trait deeply rooted in the nervous system (the Highly Sensitive Personality, HSP). 480 healthy Chinese college students were given the HSP scale and genotyped for 98 representative polymorphisms in all major dopamine neurotransmitter genes. In addition, two environment factors (stressful life events and parental warmth) that have been implicated for their contributions to personality development were included to investigate their relative contributions as compared to genetic factors. In Step 1, using ANOVA, we identified 10 polymorphisms that made statistically significant contributions to HSP. In Step 2, these polymorphism's main effects and interactions were assessed using multiple regression. This model accounted for 15% of the variance of HSP (p<0.001). Recent stressful life events accounted for an additional 2% of the variance. Finally, permutation analyses ascertained the probability of obtaining these findings by chance to be very low, p ranging from 0.001 to 0.006. Dividing these loci by the subsystems of dopamine synthesis, degradation/transport, receptor and modulation, we found that the modulation and receptor subsystems made the most significant contribution to HSP. The results of this study demonstrate the utility of a multi-step neuronal system-level approach in assessing genetic contributions to individual differences in human behavior. It can potentially bridge the gap between the high heritability estimates based on traditional behavioral genetics and the lack of reproducible genetic effects observed currently from molecular genetic studies.
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Chen, Chunhui; Chen, Chuansheng; Moyzis, Robert; Stern, Hal; He, Qinghua; Li, He; Li, Jin; Zhu, Bi; Dong, Qi
2011-01-01
Traditional behavioral genetic studies (e.g., twin, adoption studies) have shown that human personality has moderate to high heritability, but recent molecular behavioral genetic studies have failed to identify quantitative trait loci (QTL) with consistent effects. The current study adopted a multi-step approach (ANOVA followed by multiple regression and permutation) to assess the cumulative effects of multiple QTLs. Using a system-level (dopamine system) genetic approach, we investigated a personality trait deeply rooted in the nervous system (the Highly Sensitive Personality, HSP). 480 healthy Chinese college students were given the HSP scale and genotyped for 98 representative polymorphisms in all major dopamine neurotransmitter genes. In addition, two environment factors (stressful life events and parental warmth) that have been implicated for their contributions to personality development were included to investigate their relative contributions as compared to genetic factors. In Step 1, using ANOVA, we identified 10 polymorphisms that made statistically significant contributions to HSP. In Step 2, these polymorphism's main effects and interactions were assessed using multiple regression. This model accounted for 15% of the variance of HSP (p<0.001). Recent stressful life events accounted for an additional 2% of the variance. Finally, permutation analyses ascertained the probability of obtaining these findings by chance to be very low, p ranging from 0.001 to 0.006. Dividing these loci by the subsystems of dopamine synthesis, degradation/transport, receptor and modulation, we found that the modulation and receptor subsystems made the most significant contribution to HSP. The results of this study demonstrate the utility of a multi-step neuronal system-level approach in assessing genetic contributions to individual differences in human behavior. It can potentially bridge the gap between the high heritability estimates based on traditional behavioral genetics and the lack of reproducible genetic effects observed currently from molecular genetic studies. PMID:21765900
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Rin4 Causes Hybrid Necrosis and Race-Specific Resistance in an Interspecific Lettuce Hybrid[W
Jeuken, Marieke J.W.; Zhang, Ningwen W.; McHale, Leah K.; Pelgrom, Koen; den Boer, Erik; Lindhout, Pim; Michelmore, Richard W.; Visser, Richard G.F.; Niks, Rients E.
2009-01-01
Some inter- and intraspecific crosses may result in reduced viability or sterility in the offspring, often due to genetic incompatibilities resulting from interactions between two or more loci. Hybrid necrosis is a postzygotic genetic incompatibility that is phenotypically manifested as necrotic lesions on the plant. We observed hybrid necrosis in interspecific lettuce (Lactuca sativa and Lactuca saligna) hybrids that correlated with resistance to downy mildew. Segregation analysis revealed a specific allelic combination at two interacting loci to be responsible. The allelic interaction had two consequences: (1) a quantitative temperature-dependent autoimmunity reaction leading to necrotic lesions, lethality, and quantitative resistance to an otherwise virulent race of Bremia lactucae; and (2) a qualitative temperature-independent race-specific resistance to an avirulent race of B. lactucae. We demonstrated by transient expression and silencing experiments that one of the two interacting genes was Rin4. In Arabidopsis thaliana, RIN4 is known to interact with multiple R gene products, and their interactions result in hypersensitive resistance to Pseudomonas syringae. Site-directed mutation studies on the necrosis-eliciting allele of Rin4 in lettuce showed that three residues were critical for hybrid necrosis. PMID:19855048
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Rin4 causes hybrid necrosis and race-specific resistance in an interspecific lettuce hybrid.
Jeuken, Marieke J W; Zhang, Ningwen W; McHale, Leah K; Pelgrom, Koen; den Boer, Erik; Lindhout, Pim; Michelmore, Richard W; Visser, Richard G F; Niks, Rients E
2009-10-01
Some inter- and intraspecific crosses may result in reduced viability or sterility in the offspring, often due to genetic incompatibilities resulting from interactions between two or more loci. Hybrid necrosis is a postzygotic genetic incompatibility that is phenotypically manifested as necrotic lesions on the plant. We observed hybrid necrosis in interspecific lettuce (Lactuca sativa and Lactuca saligna) hybrids that correlated with resistance to downy mildew. Segregation analysis revealed a specific allelic combination at two interacting loci to be responsible. The allelic interaction had two consequences: (1) a quantitative temperature-dependent autoimmunity reaction leading to necrotic lesions, lethality, and quantitative resistance to an otherwise virulent race of Bremia lactucae; and (2) a qualitative temperature-independent race-specific resistance to an avirulent race of B. lactucae. We demonstrated by transient expression and silencing experiments that one of the two interacting genes was Rin4. In Arabidopsis thaliana, RIN4 is known to interact with multiple R gene products, and their interactions result in hypersensitive resistance to Pseudomonas syringae. Site-directed mutation studies on the necrosis-eliciting allele of Rin4 in lettuce showed that three residues were critical for hybrid necrosis.
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THE PEAKS AND GEOMETRY OF FITNESS LANDSCAPES
CRONA, KRISTINA; GREENE, DEVIN; BARLOW, MIRIAM
2012-01-01
Fitness landscapes are central in the theory of adaptation. Recent work compares global and local properties of fitness landscapes. It has been shown that multi-peaked fitness landscapes have a local property called reciprocal sign epistasis interactions. The converse is not true. We show that no condition phrased in terms of reciprocal sign epistasis interactions only, implies multiple peaks. We give a sufficient condition for multiple peaks phrased in terms of two-way interactions. This result is surprising since it has been claimed that no sufficient local condition for multiple peaks exist. We show that our result cannot be generalized to sufficient conditions for three or more peaks. Our proof depends on fitness graphs, where nodes represent genotypes and where arrows point toward more fit genotypes. We also use fitness graphs in order to give a new brief proof of the equivalent characterizations of fitness landscapes lacking genetic constraints on accessible mutational trajectories. We compare a recent geometric classification of fitness landscape based on triangulations of polytopes with qualitative aspects of gene interactions. One observation is that fitness graphs provide information not contained in the geometric classification. We argue that a qualitative perspective may help relating theory of fitness landscapes and empirical observations. PMID:23036916
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Dutech, C; Fabreguettes, O; Capdevielle, X; Robin, C
2010-08-01
The occurrence of multiple introductions may be a crucial factor in the successful establishment of invasive species, but few studies focus on the introduction of fungal pathogens, despite their significant effect on invaded habitats. Although Cryphonectria parasitica, the chestnut blight fungus introduced in North America and Europe from Asia during the 20th century, caused dramatic changes in its new range, the history of its introduction is not well retraced in Europe. Using 10 microsatellite loci, we investigated the genetic diversity of 583 isolates in France, where several introductions have been hypothesized. Our analyses showed that the seven most frequent multilocus genotypes belonged to three genetic lineages, which had a different and geographically limited distribution. These results suggest that different introduction events occurred in France. Genetic recombination was low among these lineages, despite the presence of the two mating types in each chestnut stand analysed. The spatial distribution of lineages suggests that the history of introductions in France associated with the slow expansion of the disease has contributed to the low observed rate of recombination among the divergent lineages. However, we discuss the possibility that environmental conditions or viral interactions could locally reduce recombination among genotypes.
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McDaniel, Stuart F; Willis, John H; Shaw, A Jonathan
2008-07-01
Divergent populations are intrinsically reproductively isolated when hybrids between them either fail to develop properly or do not produce viable offspring. Intrinsic isolation may result from Dobzhansky-Muller (DM) incompatibilities, in which deleterious interactions among genes or gene products lead to developmental problems or underdominant chromosome structure differences between the parents. These mechanisms can be tested by studying marker segregation patterns in a hybrid mapping population. Here we examine the genetic basis of abnormal development in hybrids between two geographically distant populations of the moss Ceratodon purpureus. Approximately half of the hybrid progeny exhibited a severely reduced growth rate in early gametophyte development. We identified four unlinked quantitative trait loci (QTL) that interacted asymmetrically to cause the abnormal development phenotype. This pattern is consistent with DM interactions. We also found an excess of recombination between three marker pairs in the abnormally developing progeny, relative to that estimated in the normal progeny. This suggests that structural differences in these regions contribute to hybrid breakdown. Two QTL coincided with inferred structural differences, consistent with recent theory suggesting that rearrangements may harbor population divergence alleles. These observations suggest that multiple complex genetic factors contribute to divergence among populations of C. purpureus.
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He, Liang; Zhbannikov, Ilya; Arbeev, Konstantin G; Yashin, Anatoliy I; Kulminski, Alexander M
2017-11-01
Unraveling the underlying biological mechanisms or pathways behind the effects of genetic variations on complex diseases remains one of the major challenges in the post-GWAS (where GWAS is genome-wide association study) era. To further explore the relationship between genetic variations, biomarkers, and diseases for elucidating underlying pathological mechanism, a huge effort has been placed on examining pleiotropic and gene-environmental interaction effects. We propose a novel genetic stochastic process model (GSPM) that can be applied to GWAS and jointly investigate the genetic effects on longitudinally measured biomarkers and risks of diseases. This model is characterized by more profound biological interpretation and takes into account the dynamics of biomarkers during follow-up when investigating the hazards of a disease. We illustrate the rationale and evaluate the performance of the proposed model through two GWAS. One is to detect single nucleotide polymorphisms (SNPs) having interaction effects on type 2 diabetes (T2D) with body mass index (BMI) and the other is to detect SNPs affecting the optimal BMI level for protecting from T2D. We identified multiple SNPs that showed interaction effects with BMI on T2D, including a novel SNP rs11757677 in the CDKAL1 gene (P = 5.77 × 10 -7 ). We also found a SNP rs1551133 located on 2q14.2 that reversed the effect of BMI on T2D (P = 6.70 × 10 -7 ). In conclusion, the proposed GSPM provides a promising and useful tool in GWAS of longitudinal data for interrogating pleiotropic and interaction effects to gain more insights into the relationship between genes, quantitative biomarkers, and risks of complex diseases. © 2017 WILEY PERIODICALS, INC.
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Nature plus nurture: the triggering of multiple sclerosis.
Wekerle, Hartmut
2015-01-01
Recent clinical and experimental studies indicate that multiple sclerosis develops as consequence of a failed interplay between genetic ("nature") and environmental ("nurture") factors. A large number of risk genes favour an autoimmune response against the body's own brain matter. New experimental data indicate that the actual trigger of this attack is however provided by an interaction of brain-specific immune cells with components of the regular commensal gut flora, the intestinal microbiota. This concept opens the way for new therapeutic approaches involving modulation of the microbiota by dietary or antibiotic regimens.
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Tchetgen Tchetgen, Eric
2011-03-01
This article considers the detection and evaluation of genetic effects incorporating gene-environment interaction and independence. Whereas ordinary logistic regression cannot exploit the assumption of gene-environment independence, the proposed approach makes explicit use of the independence assumption to improve estimation efficiency. This method, which uses both cases and controls, fits a constrained retrospective regression in which the genetic variant plays the role of the response variable, and the disease indicator and the environmental exposure are the independent variables. The regression model constrains the association of the environmental exposure with the genetic variant among the controls to be null, thus explicitly encoding the gene-environment independence assumption, which yields substantial gain in accuracy in the evaluation of genetic effects. The proposed retrospective regression approach has several advantages. It is easy to implement with standard software, and it readily accounts for multiple environmental exposures of a polytomous or of a continuous nature, while easily incorporating extraneous covariates. Unlike the profile likelihood approach of Chatterjee and Carroll (Biometrika. 2005;92:399-418), the proposed method does not require a model for the association of a polytomous or continuous exposure with the disease outcome, and, therefore, it is agnostic to the functional form of such a model and completely robust to its possible misspecification.
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Griffiths, Sarah M; Harrison, Xavier A; Weldon, Ché; Wood, Michael D; Pretorius, Abigail; Hopkins, Kevin; Fox, Graeme; Preziosi, Richard F; Antwis, Rachael E
2018-06-25
Amphibian populations worldwide are at risk of extinction from infectious diseases, including chytridiomycosis caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd). Amphibian cutaneous microbiomes interact with Bd and can confer protective benefits to the host. The composition of the microbiome itself is influenced by many environment- and host-related factors. However, little is known about the interacting effects of host population structure, genetic variation and developmental stage on microbiome composition and Bd prevalence across multiple sites. Here we explore these questions in Amietia hymenopus, a disease-affected frog in southern Africa. We use microsatellite genotyping and 16S amplicon sequencing to show that the microbiome associated with tadpole mouthparts is structured spatially, and is influenced by host genotype and developmental stage. We observed strong genetic structure in host populations based on rivers and geographic distances, but this did not correspond to spatial patterns in microbiome composition. These results indicate that demographic and host genetic factors affect microbiome composition within sites, but different factors are responsible for host population structure and microbiome structure at the between-site level. Our results help to elucidate complex within- and among- population drivers of microbiome structure in amphibian populations. That there is a genetic basis to microbiome composition in amphibians could help to inform amphibian conservation efforts against infectious diseases.
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Tzeng, Jung-Ying; Zhang, Daowen; Pongpanich, Monnat; Smith, Chris; McCarthy, Mark I.; Sale, Michèle M.; Worrall, Bradford B.; Hsu, Fang-Chi; Thomas, Duncan C.; Sullivan, Patrick F.
2011-01-01
Genomic association analyses of complex traits demand statistical tools that are capable of detecting small effects of common and rare variants and modeling complex interaction effects and yet are computationally feasible. In this work, we introduce a similarity-based regression method for assessing the main genetic and interaction effects of a group of markers on quantitative traits. The method uses genetic similarity to aggregate information from multiple polymorphic sites and integrates adaptive weights that depend on allele frequencies to accomodate common and uncommon variants. Collapsing information at the similarity level instead of the genotype level avoids canceling signals that have the opposite etiological effects and is applicable to any class of genetic variants without the need for dichotomizing the allele types. To assess gene-trait associations, we regress trait similarities for pairs of unrelated individuals on their genetic similarities and assess association by using a score test whose limiting distribution is derived in this work. The proposed regression framework allows for covariates, has the capacity to model both main and interaction effects, can be applied to a mixture of different polymorphism types, and is computationally efficient. These features make it an ideal tool for evaluating associations between phenotype and marker sets defined by linkage disequilibrium (LD) blocks, genes, or pathways in whole-genome analysis. PMID:21835306
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Trenkwalder, T; Kessler, T; Schunkert, H
2017-08-01
Genetic testing plays an increasing role in cardiovascular medicine. Advances in technology and the development of novel and more affordable (high throughput) methods have led to the identification of genetic risk factors in research and clinical practice. Also, this progress has simplified the screening of patients and individuals at risk. In case of rare monogenic diseases, diagnostics, risk stratification, and, in some cases, treatment decisions have become easier. For common, polygenic cardiovascular diseases, the situation is more complex due to interaction of modifiable external risk factors and nonmodifiable factors like genetic predisposition. Over the last few years, it has been shown that multiple genes are involved in the pathophysiology of these cardiovascular diseases rather than one single gene. In the following article, we give an overview of the genetic risk factors in polygenic cardiovascular diseases as atrial fibrillation, arterial hypertension and coronary artery disease. Furthermore, we aim to illustrate in which cases genetic testing is recommended in these diseases.
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[Genetic and neuroendocrine aspects in autism spectrum disorder].
Oviedo, Norma; Manuel-Apolinar, Leticia; de la Chesnaye, Elsa; Guerra-Araiza, Christian
The autism spectrum disorder (ASD) was described in 1943 and is defined as a developmental disorder that affects social interaction and communication. It is usually identified in early stages of development from 18 months of age. Currently, autism is considered a neurological disorder with a spectrum covering cases of different degrees, which is associated with genetic factors, not genetic and environmental. Among the genetic factors, various syndromes have been described that are associated with this disorder. Also, the neurobiology of autism has been studied at the genetic, neurophysiological, neurochemical and neuropathological levels. Neuroimaging techniques have shown multiple structural abnormalities in these patients. There have also been changes in the serotonergic, GABAergic, catecholaminergic and cholinergic systems related to this disorder. This paper presents an update of the information presented in the genetic and neuroendocrine aspects of autism spectrum disorder. Copyright © 2014 Hospital Infantil de México Federico Gómez. Publicado por Masson Doyma México S.A. All rights reserved.
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Hu, Jian; Zhou, Yi-ren; Ding, Jia-lin; Wang, Zhi-yuan; Liu, Ling; Wang, Ye-kai; Lou, Hui-ling; Qiao, Shou-yi; Wu, Yan-hua
2017-05-20
The ABO blood type is one of the most common and widely used genetic traits in humans. Three glycosyltransferase-encoding gene alleles, I A , I B and i, produce three red blood cell surface antigens, by which the ABO blood type is classified. By using the ABO blood type experiment as an ideal case for genetics teaching, we can easily introduce to the students several genetic concepts, including multiple alleles, gene interaction, single nucleotide polymorphism (SNP) and gene evolution. Herein we have innovated and integrated our ABO blood type genetics experiments. First, in the section of Molecular Genetics, a new method of ABO blood genotyping was established: specific primers based on SNP sites were designed to distinguish three alleles through quantitative real-time PCR. Next, the experimental teaching method of Gene Evolution was innovated in the Population Genetics section: a gene-evolution software was developed to simulate the evolutionary tendency of the ABO genotype encoding alleles under diverse conditions. Our reform aims to extend the contents of genetics experiments, to provide additional teaching approaches, and to improve the learning efficiency of our students eventually.
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Chemical genetics and regeneration.
Sengupta, Sumitra; Zhang, Liyun; Mumm, Jeff S
2015-01-01
Regeneration involves interactions between multiple signaling pathways acting in a spatially and temporally complex manner. As signaling pathways are highly conserved, understanding how regeneration is controlled in animal models exhibiting robust regenerative capacities should aid efforts to stimulate repair in humans. One way to discover molecular regulators of regeneration is to alter gene/protein function and quantify effect(s) on the regenerative process: dedifferentiation/reprograming, stem/progenitor proliferation, migration/remodeling, progenitor cell differentiation and resolution. A powerful approach for applying this strategy to regenerative biology is chemical genetics, the use of small-molecule modulators of specific targets or signaling pathways. Here, we review advances that have been made using chemical genetics for hypothesis-focused and discovery-driven studies aimed at furthering understanding of how regeneration is controlled.
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Foo, Shawna A; Dworjanyn, Symon A; Poore, Alistair G B; Byrne, Maria
2012-01-01
Predicting effects of rapid climate change on populations depends on measuring the effects of climate stressors on performance, and potential for adaptation. Adaptation to stressful climatic conditions requires heritable genetic variance for stress tolerance present in populations. We quantified genetic variation in tolerance of early development of the ecologically important sea urchin Centrostephanus rodgersii to near-future (2100) ocean conditions projected for the southeast Australian global change hot spot. Multiple dam-sire crosses were used to quantify the interactive effects of warming (+2-4 °C) and acidification (-0.3-0.5 pH units) across twenty-seven family lines. Acidification, but not temperature, decreased the percentage of cleavage stage embryos. In contrast, temperature, but not acidification decreased the percentage of gastrulation. Cleavage success in response to both stressors was strongly affected by sire identity. Sire and dam identity significantly affected gastrulation and both interacted with temperature to determine developmental success. Positive genetic correlations for gastrulation indicated that genotypes that did well at lower pH also did well in higher temperatures. Significant genotype (sire) by environment interactions for both stressors at gastrulation indicated the presence of heritable variation in thermal tolerance and the ability of embryos to respond to changing environments. The significant influence of dam may be due to maternal provisioning (maternal genotype or environment) and/or offspring genotype. It appears that early development in this ecologically important sea urchin is not constrained in adapting to the multiple stressors of ocean warming and acidification. The presence of tolerant genotypes indicates the potential to adapt to concurrent warming and acidification, contributing to the resilience of C. rodgersii in a changing ocean.
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Foo, Shawna A.; Dworjanyn, Symon A.; Poore, Alistair G. B.; Byrne, Maria
2012-01-01
Background Predicting effects of rapid climate change on populations depends on measuring the effects of climate stressors on performance, and potential for adaptation. Adaptation to stressful climatic conditions requires heritable genetic variance for stress tolerance present in populations. Methodology/Principal Findings We quantified genetic variation in tolerance of early development of the ecologically important sea urchin Centrostephanus rodgersii to near-future (2100) ocean conditions projected for the southeast Australian global change hot spot. Multiple dam-sire crosses were used to quantify the interactive effects of warming (+2–4°C) and acidification (−0.3−0.5 pH units) across twenty-seven family lines. Acidification, but not temperature, decreased the percentage of cleavage stage embryos. In contrast, temperature, but not acidification decreased the percentage of gastrulation. Cleavage success in response to both stressors was strongly affected by sire identity. Sire and dam identity significantly affected gastrulation and both interacted with temperature to determine developmental success. Positive genetic correlations for gastrulation indicated that genotypes that did well at lower pH also did well in higher temperatures. Conclusions/Significance Significant genotype (sire) by environment interactions for both stressors at gastrulation indicated the presence of heritable variation in thermal tolerance and the ability of embryos to respond to changing environments. The significant influence of dam may be due to maternal provisioning (maternal genotype or environment) and/or offspring genotype. It appears that early development in this ecologically important sea urchin is not constrained in adapting to the multiple stressors of ocean warming and acidification. The presence of tolerant genotypes indicates the potential to adapt to concurrent warming and acidification, contributing to the resilience of C. rodgersii in a changing ocean. PMID:22880005
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van der Meer, D; Hoekstra, P J; van Donkelaar, M; Bralten, J; Oosterlaan, J; Heslenfeld, D; Faraone, S V; Franke, B; Buitelaar, J K; Hartman, C A
2017-01-01
Identifying genetic variants contributing to attention-deficit/hyperactivity disorder (ADHD) is complicated by the involvement of numerous common genetic variants with small effects, interacting with each other as well as with environmental factors, such as stress exposure. Random forest regression is well suited to explore this complexity, as it allows for the analysis of many predictors simultaneously, taking into account any higher-order interactions among them. Using random forest regression, we predicted ADHD severity, measured by Conners’ Parent Rating Scales, from 686 adolescents and young adults (of which 281 were diagnosed with ADHD). The analysis included 17 374 single-nucleotide polymorphisms (SNPs) across 29 genes previously linked to hypothalamic–pituitary–adrenal (HPA) axis activity, together with information on exposure to 24 individual long-term difficulties or stressful life events. The model explained 12.5% of variance in ADHD severity. The most important SNP, which also showed the strongest interaction with stress exposure, was located in a region regulating the expression of telomerase reverse transcriptase (TERT). Other high-ranking SNPs were found in or near NPSR1, ESR1, GABRA6, PER3, NR3C2 and DRD4. Chronic stressors were more influential than single, severe, life events. Top hits were partly shared with conduct problems. We conclude that random forest regression may be used to investigate how multiple genetic and environmental factors jointly contribute to ADHD. It is able to implicate novel SNPs of interest, interacting with stress exposure, and may explain inconsistent findings in ADHD genetics. This exploratory approach may be best combined with more hypothesis-driven research; top predictors and their interactions with one another should be replicated in independent samples. PMID:28585928
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Plasticity as Phenotype: G x E Interaction in a Freshwater Snail
NASA Astrophysics Data System (ADS)
Brunkow, P. E.; Calloway, S. A.
2005-05-01
Plasticity in morphological development allows species to accommodate environmental variation experienced during growth; however, genetic variation for phenotypic plasticity per se has been relatively under-studied. We utilized the well-documented plastic response of shell development to predator cues in a freshwater snail to quantify genetic variation for plasticity in growth rate and shell shape. Field-caught pairs of snails reproduced in the laboratory to create families of full siblings, which were then divided and allowed to grow in control and predator cue treatments. Predator (crayfish) cues had significant effects on both size-corrected growth rate and shell shape; family identity also significantly affected both final shell shape and growth rate. The interaction between predator treatment and family identity significantly affected snail growth rate but not final shell shape, suggesting genetic variation in the plastic response to predator cues for a physiological variable (growth rate) but not for a variable known to mechanically reduce the risk of predation (shell shape), at least in this population of snails. The possibility that risk of multiple modes of predation (i.e., both fish and crayfish) in some populations might maintain genetic variation in morphological plasticity is discussed.
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Lemery-Chalfant, Kathryn; Kao, Karen; Swann, Gregory; Goldsmith, H. Hill
2013-01-01
Biological parents pass on genotypes to their children, as well as provide home environments that correlate with their genotypes; thus, the association between the home environment and children's temperament can be genetically (i.e. passive gene-environment correlation) or environmentally mediated. Furthermore, family environments may suppress or facilitate the heritability of children's temperament (i.e. gene-environment interaction). The sample comprised 807 twin pairs (M age = 7.93 years) from the longitudinal Wisconsin Twin Project. Important passive gene-environment correlations emerged, such that home environments were less chaotic for children with high Effortful Control, and this association was genetically mediated. Children with high Extraversion/Surgency experienced more chaotic home environments, and this correlation was also genetically mediated. In addition, heritability of children's temperament was moderated by home environments, such that Effortful Control and Extraversion/Surgency were more heritable in chaotic homes, and Negative Affectivity was more heritable under crowded or unsafe home conditions. Modeling multiple types of gene-environment interplay uncovered the complex role of genetic factors and the hidden importance of the family environment for children's temperament and development more generally. PMID:23398752
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Li, Tongchao; Giagtzoglou, Nikolaos; Eberl, Daniel F; Jaiswal, Sonal Nagarkar; Cai, Tiantian; Godt, Dorothea; Groves, Andrew K; Bellen, Hugo J
2016-06-22
Myosins play essential roles in the development and function of auditory organs and multiple myosin genes are associated with hereditary forms of deafness. Using a forward genetic screen in Drosophila, we identified an E3 ligase, Ubr3, as an essential gene for auditory organ development. Ubr3 negatively regulates the mono-ubiquitination of non-muscle Myosin II, a protein associated with hearing loss in humans. The mono-ubiquitination of Myosin II promotes its physical interaction with Myosin VIIa, a protein responsible for Usher syndrome type IB. We show that ubr3 mutants phenocopy pathogenic variants of Myosin II and that Ubr3 interacts genetically and physically with three Usher syndrome proteins. The interactions between Myosin VIIa and Myosin IIa are conserved in the mammalian cochlea and in human retinal pigment epithelium cells. Our work reveals a novel mechanism that regulates protein complexes affected in two forms of syndromic deafness and suggests a molecular function for Myosin IIa in auditory organs.
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Zheng, Yong-Sheng; Lu, Yu-Qing; Meng, Ying-Ying; Zhang, Rong-Zhi; Zhang, Han; Sun, Jia-Mei; Wang, Mu-Mu; Li, Li-Hui; Li, Ru-Yu
2017-05-01
WD-40 repeat-containing protein MSI4 (FVE)/MSI4 plays important roles in determining flowering time in Arabidopsis. However, its function is unexplored in wheat. In the present study, coimmunoprecipitation and nanoscale liquid chromatography coupled to MS/MS were used to identify FVE in wheat (TaFVE)-interacting or associated proteins. Altogether 89 differentially expressed proteins showed the same downregulated expression trends as TaFVE in wheat line 5660M. Among them, 62 proteins were further predicted to be involved in the interaction network of TaFVE and 11 proteins have been shown to be potential TaFVE interactors based on curated databases and experimentally determined in other species by the STRING. Both yeast two-hybrid assay and bimolecular fluorescence complementation assay showed that histone deacetylase 6 and histone deacetylase 15 directly interacted with TaFVE. Multiple chromatin-remodelling proteins and polycomb group proteins were also identified and predicted to interact with TaFVE. These results showed that TaFVE directly interacted with multiple proteins to form multiple complexes to regulate spike developmental process, e.g. histone deacetylate, chromatin-remodelling and polycomb repressive complex 2 complexes. In addition, multiple flower development regulation factors (e.g. flowering locus K homology domain, flowering time control protein FPA, FY, flowering time control protein FCA, APETALA 1) involved in floral transition were also identified in the present study. Taken together, these results further elucidate the regulatory functions of TaFVE and help reveal the genetic mechanisms underlying wheat spike differentiation. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Generating Enhanced Natural Environments and Terrain for Interactive Combat Simulations (GENETICS)
2005-09-01
split to avoid T-junctions ........................................................................52 Figure 2-23 Longest edge bisection...database. This feature allows trainers the flexibility to use the same terrain repeatedly or use a new one each time, forcing trainees to avoid ...model are favored to create a good surface approximation. Cracks are avoided by projecting primitives and their respective textures onto multiple
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Multiple myeloma: a clinical overview.
Anderson, Kenneth C
2011-11-15
Multiple myeloma (MM) is the second most common hematologic malignancy in the United States, affecting slightly more men than women and twice as many African Americans as Caucasians. Older age is the primary risk factor for MM, but obesity also increases risk. MM is incurable, but treatment advances in the past decade have more than doubled the duration of survival. MM is a progressive plasma cell tumor in which an initially stable clone becomes malignant via a multistep process. Causative factors implicated in this process include radiation, environmental toxins, chronic antigen stimulation, and genetics. The malignant plasma cells interact with other hematopoietic and stromal cells within the bone marrow microenvironment to disrupt homeostasis among cells and within the extracellular matrix. These tumor-host interactions lead to MM cell proliferation and migration, angiogenesis, osteolysis, immunodeficiency, and anemia. As a result, patients often present with osteolytic bone lesions, recurrent infections, renal insufficiency, and fatigue. The Durie-Salmon and International Staging Systems are used to stage MM, with the latter providing prognostic information based on readily available laboratory data. However, a number of cytogenetic markers are emerging as prognostic indicators, introducing the possibility of more refined disease staging systems and tailored treatment strategies based on genetic profiles.
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Johansson, A; Bergman, H; Corander, J; Waldman, I D; Karrani, N; Salo, B; Jern, P; Algars, M; Sandnabba, K; Santtila, P; Westberg, L
2012-03-01
We explored if the disposition to react with aggression while alcohol intoxicated was moderated by polymorphic variants of the oxytocin receptor gene (OXTR). Twelve OXTR polymorphisms were genotyped in 116 Finnish men [aged 18-30, M = 22.7, standard deviation (SD) = 2.4] who were randomly assigned to an alcohol condition in which they received an alcohol dose of 0.7 g pure ethanol/kg body weight or a placebo condition. Aggressive behavior was measured using a laboratory paradigm in which it was operationalized as the level of aversive noise administered to a fictive opponent. No main effects of the polymorphisms on aggressive behavior were found after controlling for multiple testing. The interactive effects between alcohol and two of the OXTR polymorphisms (rs4564970 and rs1488467) on aggressive behavior were nominally significant and remained significant for the rs4564970 when controlled for multiple tests. To the best of our knowledge, this is the first experimental study suggesting interactive effects of specific genetic variants and alcohol on aggressive behavior in humans. © 2011 The Authors. Genes, Brain and Behavior © 2011 Blackwell Publishing Ltd and International Behavioural and Neural Genetics Society.
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Tregenza, Tom; Wedell, Nina; Hosken, David J; Ward, Paul I
2003-02-01
Direct costs and benefits to females of multiple mating have been shown to have large effects on female fecundity and longevity in several species. However, with the exception of studies examining genetic benefits of polyandry, little attention has been paid to the possible effects on offspring of multiple mating by females. We propose that nongenetic effects of maternal matings on offspring fitness are best viewed in the same context as other maternal phenotype effects on offspring that are well known even in species lacking parental care. Hence, matings can exert effects on offspring in the same way as other maternal environment variables, and are likely to interact with such effects. We have conducted a study using yellow dung flies (Scathophaga stercoraria), in which we independently manipulated female mating rate, number of mates and maternal thermal environment and measured subsequent fecundity, hatching success, and offspring life-history traits. To distinguish between direct effects of matings and potential genetic benefits of polyandry we split broods and reared offspring at three different temperature regimes. This allowed us to demonstrate that although we could not detect any simple benefits or costs to matings, there are effects of maternal environment on offspring and these effects interact with female mating regime affecting offspring fitness. Such interactions between female phenotype and the costs and benefits of matings have potentially broad implications for understanding female behavior.
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Contribution of genome-environment interaction to pre-eclampsia in a Havana Maternity Hospital.
Lardoeyt, Roberto; Vargas, Gerardo; Lumpuy, Jairo; García, Ramón; Torres, Yuselis
2013-07-01
Pre-eclampsia is a major cause of morbidity and mortality during pregnancy worldwide and is among the leading causes of maternal mortality in Cuba. It is a complex, multifactoral disease, in which interaction of genetic and environmental factors should not be overlooked if the goal is proper risk assessment to support personalized preventive genetic counseling and more effective prenatal care to prevent pregnancy complications. Determine the contribution to pre-eclampsia of interaction between a predisposing genome and adverse environmental factors in pregnant women in a Havana maternity hospital. This was the exploratory phase of a hospital-based case-control study, using January 2007-December 2009 patient records from the Eusebio Hernández University Hospital, a provincial maternity hospital in Havana. Eighty pregnant women diagnosed with pre-eclampsia and 160 controls were studied. The main variables were age, parity, nutritional status (measured by BMI), alcohol use, tobacco use, and history of pre-eclampsia in relatives of the pregnant woman (proband) or of her partner. Pearson chi square and Fisher exact test were used to assess statistical significance of associations between variables and odds ratio as a measure of association strength. Familial aggregation was studied and a case-control design used to assess gene-environment interaction, using multiplicative and additive models. Among the environmental risk factors studied, alcohol showed the strongest effect on pre-eclampsia risk (OR 3.87, 95% CI 1.64-9.13). Familial pre-eclampsia clustering was observed; risk was increased for both first-degree (OR 2.43, 95% CI 1.62-3.73) and second-degree (OR 1.89, 95% CI 1.34-2.68) relatives as well as for husband's relatives (OR 2.32, 95% CI 1.40-3.86). There was evidence of interaction between alcohol consumption and family history. Familial aggregation of the disorder was demonstrated, the first Cuban epidemiological evidence of genetic and enviromental contributions to pre-eclampsia risk. Familial clustering among the husband's relatives demonstrates the fetal genome's importance in genesis of pre-eclampsia. The interaction of environmental risk factors with genetic ones produces increased pre-eclampsia risk, compared to expectations based on independent action of these variables. KEYWORDS Pre-eclampsia, toxemia of pregnancy, pregnancy outcome, environment, genetics, genome-environment interaction, genetic epidemiology, Cuba.
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Genome organization and long-range regulation of gene expression by enhancers.
Smallwood, Andrea; Ren, Bing
2013-06-01
It is now well accepted that cell-type specific gene regulation is under the purview of enhancers. Great strides have been made recently to characterize and identify enhancers both genetically and epigenetically for multiple cell types and species, but efforts have just begun to link enhancers to their target promoters. Mapping these interactions and understanding how the 3D landscape of the genome constrains such interactions is fundamental to our understanding of mammalian gene regulation. Here, we review recent progress in mapping long-range regulatory interactions in mammalian genomes, focusing on transcriptional enhancers and chromatin organization principles. Copyright © 2013. Published by Elsevier Ltd.
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Chemical interaction: enhancement and inhibition of clastogenicity.
Anwar, W A
1993-01-01
Most environmental exposures involve concurrent or sequential exposure to multiple chemicals in air, water, and food. Interactive effects in carcinogenesis have been described for certain combinations of agents. They are described in terms of enhancement or inhibition of carcinogenesis. Enhancement effects have been documented for cigarette smoking in combination with exposure to asbestos, radon, alcohol, or other exposures. A variety of inhibitors of carcinogenesis have also been described. They are classified into agents preventing formation of carcinogens; blocking agents; and suppressing agents. Assessment of risk from exposure to multiple agents can be derived either from epidemiological studies in relation to actual exposure or from laboratory studies after controlled exposure to different agents. Prediction of how toxic components of mixtures will interact should be based on an understanding of the mechanisms of such interactions. Compounds may interact chemically, yielding new toxic components or causing a change in the biological availability of the existing components or metabolites. In humans, great individual variability in response is to be expected because of genetic heterogeneity or acquired host susceptibility factors. Interaction is thus a key component in the risk assessment process. In this paper, the definition of interaction and the theoretical basis for different types of interaction in cancer causation are reviewed. Epidemiological and experimental studies showing interactive effects of two chemical carcinogens are also presented. PMID:8143617
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Quantitative trait loci that control the oil content variation of rapeseed (Brassica napus L.).
Jiang, Congcong; Shi, Jiaqin; Li, Ruiyuan; Long, Yan; Wang, Hao; Li, Dianrong; Zhao, Jianyi; Meng, Jinling
2014-04-01
This report describes an integrative analysis of seed-oil-content quantitative trait loci (QTL) in Brassica napus , using a high-density genetic map to align QTL among different populations. Rapeseed (Brassica napus) is an important source of edible oil and sustainable energy. Given the challenge involved in using only a few genes to substantially increase the oil content of rapeseed without affecting the fatty acid composition, exploitation of a greater number of genetic loci that regulate the oil content variation among rapeseed germplasm is of fundamental importance. In this study, we investigated variation in the seed-oil content among two related genetic populations of Brassica napus, the TN double-haploid population and its derivative reconstructed-F2 population. Each population was grown in multiple experiments under different environmental conditions. Mapping of quantitative trait loci (QTL) identified 41 QTL in the TN populations. Furthermore, of the 20 pairs of epistatic interaction loci detected, approximately one-third were located within the QTL intervals. The use of common markers on different genetic maps and the TN genetic map as a reference enabled us to project QTL from an additional three genetic populations onto the TN genetic map. In summary, we used the TN genetic map of the B. napus genome to identify 46 distinct QTL regions that control seed-oil content on 16 of the 19 linkage groups of B. napus. Of these, 18 were each detected in multiple populations. The present results are of value for ongoing efforts to breed rapeseed with high oil content, and alignment of the QTL makes an important contribution to the development of an integrative system for genetic studies of rapeseed.
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Kennedy, Richard B.; Ovsyannikova, Inna G.; Pankratz, V. Shane; Haralambieva, Iana H.; Vierkant, Robert A.; Poland, Gregory A.
2014-01-01
The role that genetics plays in response to infection or disease is becoming increasingly clear as we learn more about immunogenetics and host-pathogen interactions. Here we report a genome-wide analysis of the effects of host genetic variation on cytokine responses to vaccinia virus stimulation in smallpox vaccine recipients. Our data show that vaccinia stimulation of immune individuals results in secretion of inflammatory and Th1 cytokines. We identified multiple SNPs significantly associated with variations in cytokine secretion. These SNPs are found in genes with known immune function, as well as in genes encoding for proteins involved in signal transduction, cytoskeleton, membrane channels and ion transport, as well as others with no previously identified connection to immune responses. The large number of significant SNP associations implies that cytokine secretion in response to vaccinia virus is a complex process controlled by multiple genes and gene families. Follow-up studies to replicate these findings and then pursue mechanistic studies will provide a greater understanding of how genetic variation influences vaccine responses. PMID:22610502
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Function of the CRISPR-Cas System of the Human Pathogen Clostridium difficile
Boudry, Pierre; Semenova, Ekaterina; Monot, Marc; Datsenko, Kirill A.; Lopatina, Anna; Sekulovic, Ognjen; Ospina-Bedoya, Maicol; Fortier, Louis-Charles; Severinov, Konstantin; Dupuy, Bruno
2015-01-01
ABSTRACT Clostridium difficile is the cause of most frequently occurring nosocomial diarrhea worldwide. As an enteropathogen, C. difficile must be exposed to multiple exogenous genetic elements in bacteriophage-rich gut communities. CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated) systems allow bacteria to adapt to foreign genetic invaders. Our recent data revealed active expression and processing of CRISPR RNAs from multiple type I-B CRISPR arrays in C. difficile reference strain 630. Here, we demonstrate active expression of CRISPR arrays in strain R20291, an epidemic C. difficile strain. Through genome sequencing and host range analysis of several new C. difficile phages and plasmid conjugation experiments, we provide evidence of defensive function of the CRISPR-Cas system in both C. difficile strains. We further demonstrate that C. difficile Cas proteins are capable of interference in a heterologous host, Escherichia coli. These data set the stage for mechanistic and physiological analyses of CRISPR-Cas-mediated interactions of important global human pathogen with its genetic parasites. PMID:26330515
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Family conflict interacts with genetic liability in predicting childhood and adolescent depression.
Rice, Frances; Harold, Gordon T; Shelton, Katherine H; Thapar, Anita
2006-07-01
To test for gene-environment interaction with depressive symptoms and family conflict. Specifically, to first examine whether the influence of family conflict in predicting depressive symptoms is increased in individuals at genetic risk of depression. Second, to test whether the genetic component of variance in depressive symptoms increases as levels of family conflict increase. A longitudinal twin design was used. Children ages 5 to 16 were reassessed approximately 3 years later to test whether the influence of family conflict in predicting depressive symptoms varied according to genetic liability. The conflict subscale of the Family Environment Scale was used to assess family conflict and the Mood and Feelings Questionnaire was used to assess depressive symptoms. The response rate to the questionnaire at time 1 was 73% and 65% at time 2. Controlling for initial symptoms levels (i.e., internalizing at time 1), primary analyses were conducted using ordinary least-squares multiple regression. Structural equation models, using raw score maximum likelihood estimation, were also fit to the data for the purpose of model fit comparison. Results suggested significant gene-environment interaction specifically with depressive symptoms and family conflict. Genetic factors were of greater importance in the etiology of depressive symptoms where levels of family conflict were high. The effects of family conflict on depressive symptoms were greater in children and adolescents at genetic risk of depression. The present results suggest that children with a family history of depression may be at an increased risk of developing depressive symptoms in response to family conflict. Intervention programs that incorporate one or more family systems may be of benefit in alleviating the adverse effect of negative family factors on children.
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Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.
Kang, Eun Yong; Han, Buhm; Furlotte, Nicholas; Joo, Jong Wha J; Shih, Diana; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar
2014-01-01
Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study.
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Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice
Joo, Jong Wha J.; Shih, Diana; Davis, Richard C.; Lusis, Aldons J.; Eskin, Eleazar
2014-01-01
Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study. PMID:24415945
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Bookman, Ebony B.; McAllister, Kimberly; Gillanders, Elizabeth; Wanke, Kay; Balshaw, David; Rutter, Joni; Reedy, Jill; Shaughnessy, Daniel; Agurs-Collins, Tanya; Paltoo, Dina; Atienza, Audie; Bierut, Laura; Kraft, Peter; Fallin, M. Daniele; Perera, Frederica; Turkheimer, Eric; Boardman, Jason; Marazita, Mary L.; Rappaport, Stephen M.; Boerwinkle, Eric; Suomi, Stephen J.; Caporaso, Neil E.; Hertz-Picciotto, Irva; Jacobson, Kristen C.; Lowe, William L.; Goldman, Lynn R.; Duggal, Priya; Gunnar, Megan R.; Manolio, Teri A.; Green, Eric D.; Olster, Deborah H.; Birnbaum, Linda S.
2011-01-01
Although it is recognized that many common complex diseases are a result of multiple genetic and environmental risk factors, studies of gene-environment interaction remain a challenge and have had limited success to date. Given the current state-of-the-science, NIH sought input on ways to accelerate investigations of gene-environment interplay in health and disease by inviting experts from a variety of disciplines to give advice about the future direction of gene-environment interaction studies. Participants of the NIH Gene-Environment Interplay Workshop agreed that there is a need for continued emphasis on studies of the interplay between genetic and environmental factors in disease and that studies need to be designed around a multifaceted approach to reflect differences in diseases, exposure attributes, and pertinent stages of human development. The participants indicated that both targeted and agnostic approaches have strengths and weaknesses for evaluating main effects of genetic and environmental factors and their interactions. The unique perspectives represented at the workshop allowed the exploration of diverse study designs and analytical strategies, and conveyed the need for an interdisciplinary approach including data sharing, and data harmonization to fully explore gene-environment interactions. Further, participants also emphasized the continued need for high-quality measures of environmental exposures and new genomic technologies in ongoing and new studies. PMID:21308768
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Mitochondrial Recombination Reveals Mito-Mito Epistasis in Yeast.
Wolters, John F; Charron, Guillaume; Gaspary, Alec; Landry, Christian R; Fiumera, Anthony C; Fiumera, Heather L
2018-05-01
Genetic variation in mitochondrial DNA (mtDNA) provides adaptive potential although the underlying genetic architecture of fitness components within mtDNAs is not known. To dissect functional variation within mtDNAs, we first identified naturally occurring mtDNAs that conferred high or low fitness in Saccharomyces cerevisiae by comparing growth in strains containing identical nuclear genotypes but different mtDNAs. During respiratory growth under temperature and oxidative stress conditions, mitotype effects were largely independent of nuclear genotypes even in the presence of mito-nuclear interactions. Recombinant mtDNAs were generated to determine fitness components within high- and low-fitness mtDNAs. Based on phenotypic distributions of isogenic strains containing recombinant mtDNAs, we found that multiple loci contributed to mitotype fitness differences. These mitochondrial loci interacted in epistatic, nonadditive ways in certain environmental conditions. Mito-mito epistasis ( i.e. , nonadditive interactions between mitochondrial loci) influenced fitness in progeny from four different crosses, suggesting that mito-mito epistasis is a widespread phenomenon in yeast and other systems with recombining mtDNAs. Furthermore, we found that interruption of coadapted mito-mito interactions produced recombinant mtDNAs with lower fitness. Our results demonstrate that mito-mito epistasis results in functional variation through mitochondrial recombination in fungi, providing modes for adaptive evolution and the generation of mito-mito incompatibilities. Copyright © 2018 by the Genetics Society of America.
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Boosting for detection of gene-environment interactions.
Pashova, H; LeBlanc, M; Kooperberg, C
2013-01-30
In genetic association studies, it is typically thought that genetic variants and environmental variables jointly will explain more of the inheritance of a phenotype than either of these two components separately. Traditional methods to identify gene-environment interactions typically consider only one measured environmental variable at a time. However, in practice, multiple environmental factors may each be imprecise surrogates for the underlying physiological process that actually interacts with the genetic factors. In this paper, we develop a variant of L(2) boosting that is specifically designed to identify combinations of environmental variables that jointly modify the effect of a gene on a phenotype. Because the effect modifiers might have a small signal compared with the main effects, working in a space that is orthogonal to the main predictors allows us to focus on the interaction space. In a simulation study that investigates some plausible underlying model assumptions, our method outperforms the least absolute shrinkage and selection and Akaike Information Criterion and Bayesian Information Criterion model selection procedures as having the lowest test error. In an example for the Women's Health Initiative-Population Architecture using Genomics and Epidemiology study, the dedicated boosting method was able to pick out two single-nucleotide polymorphisms for which effect modification appears present. The performance was evaluated on an independent test set, and the results are promising. Copyright © 2012 John Wiley & Sons, Ltd.
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Beauchaine, Theodore P.; Gatzke-Kopp, Lisa M.
2014-01-01
During the last quarter century, developmental psychopathology has become increasingly inclusive and now spans disciplines ranging from psychiatric genetics to primary prevention. As a result, developmental psychopathologists have extended traditional diathesis–stress and transactional models to include causal processes at and across all relevant levels of analysis. Such research is embodied in what is known as the multiple levels of analysis perspective. We describe how multiple levels of analysis research has informed our current thinking about antisocial and borderline personality development among trait impulsive and therefore vulnerable individuals. Our approach extends the multiple levels of analysis perspective beyond simple Biology × Environment interactions by evaluating impulsivity across physiological systems (genetic, autonomic, hormonal, neural), psychological constructs (social, affective, motivational), developmental epochs (preschool, middle childhood, adolescence, adulthood), sexes (male, female), and methods of inquiry (self-report, informant report, treatment outcome, cardiovascular, electrophysiological, neuroimaging). By conducting our research using any and all available methods across these levels of analysis, we have arrived at a developmental model of trait impulsivity that we believe confers a greater understanding of this highly heritable trait and captures at least some heterogeneity in key behavioral outcomes, including delinquency and suicide. PMID:22781868
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Binder, Elisabeth B.; Bradley, Rebekah G.; Liu, Wei; Epstein, Michael P.; Deveau, Todd C.; Mercer, Kristina B.; Tang, Yilang; Gillespie, Charles F.; Heim, Christine M.; Nemeroff, Charles B.; Schwartz, Ann C.; Cubells, Joseph F.; Ressler, Kerry J.
2008-01-01
Context In addition to trauma exposure, other factors contribute to risk for development of posttraumatic stress disorder (PTSD) in adulthood. Both genetic and environmental factors are contributory, with child abuse providing significant risk liability. Objective To increase understanding of genetic and environmental risk factors as well as their interaction in the development of PTSD by gene × environment interactions of child abuse, level of non–child abuse trauma exposure, and genetic polymorphisms at the stress-related gene FKBP5. Design, Setting, and Participants A cross-sectional study examining genetic and psychological risk factors in 900 non psychiatric clinic patients (762 included for all genotype studies) with significant levels of childhood abuse as well as non–child abuse trauma using a verbally presented survey combined with single-nucleotide polymorphism (SNP) genotyping. Participants were primarily urban, low-income, black (>95%) men and women seeking care in the general medical care and obstetrics-gynecology clinics of an urban public hospital in Atlanta, Georgia, between 2005 and 2007. Main Outcome Measures Severity of adult PTSD symptomatology, measured with the modified PTSD Symptom Scale, non–child abuse (primarily adult) trauma exposure and child abuse measured using the traumatic events inventory and 8 SNPs spanning the FKBP5 locus. Results Level of child abuse and non–child abuse trauma each separately predicted level of adult PTSD symptomatology (mean [SD], PTSD Symptom Scale for no child abuse, 8.03 [10.48] vs ≥2 types of abuse, 20.93 [14.32]; and for no non–child abuse trauma, 3.58 [6.27] vs ≥4 types, 16.74 [12.90]; P<.001). Although FKBP5 SNPs did not directly predict PTSD symptom outcome or interact with level of non–child abuse trauma to predict PTSD symptom severity, 4 SNPs in the FKBP5 locus significantly interacted (rs9296158, rs3800373, rs1360780, and rs9470080; minimum P=.0004) with the severity of child abuse to predict level of adult PTSD symptoms after correcting for multiple testing. This gene × environment interaction remained significant when controlling for depression severity scores, age, sex, levels of non–child abuse trauma exposure, and genetic ancestry. This genetic interaction was also paralleled by FKBP5 genotype-dependent and PTSD-dependent effects on glucocorticoid receptor sensitivity, measured by the dexamethasone suppression test. Conclusions Four SNPs of the FKBP5 gene interacted with severity of child abuse as a predictor of adult PTSD symptoms. There were no main effects of the SNPs on PTSD symptoms and no significant genetic interactions with level of non–child abuse trauma as predictor of adult PTSD symptoms, suggesting a potential gene-childhood environment interaction for adult PTSD. PMID:18349090
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Bahar, Muh Akbar; Setiawan, Didik; Hak, Eelko; Wilffert, Bob
2017-05-01
Currently, most guidelines on drug-drug interaction (DDI) neither consider the potential effect of genetic polymorphism in the strength of the interaction nor do they account for the complex interaction caused by the combination of DDI and drug-gene interaction (DGI) where there are multiple biotransformation pathways, which is referred to as drug-drug-gene interaction (DDGI). In this systematic review, we report the impact of pharmacogenetics on DDI and DDGI in which three major drug-metabolizing enzymes - CYP2C9, CYP2C19 and CYP2D6 - are central. We observed that several DDI and DDGI are highly gene-dependent, leading to a different magnitude of interaction. Precision drug therapy should take pharmacogenetics into account when drug interactions in clinical practice are expected.
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Slutske, Wendy S; Deutsch, Arielle R; Statham, Dixie J; Martin, Nicholas G
2015-08-01
Previous research has demonstrated that local area characteristics (such as disadvantage and gambling outlet density) and genetic risk factors are associated with gambling involvement and disordered gambling. These 2 lines of research were brought together in the present study by examining the extent to which genetic contributions to individual differences in gambling involvement and disorder contributed to being exposed to, and were also accentuated by, local area disadvantage. Participants were members of the national community-based Australian Twin Registry who completed a telephone interview in which the past-year frequency of gambling and symptoms of disordered gambling were assessed. Indicators of local area disadvantage were based on census data matched to the participants' postal codes. Univariate biometric model-fitting revealed that exposure to area disadvantage was partially explained by genetic factors. Bivariate biometric model-fitting was conducted to examine the evidence for gene-environment interaction while accounting for gene-environment correlation. These analyses demonstrated that: (a) a small portion of the genetic propensity to gamble was explained by moving to or remaining in a disadvantaged area, and (b) the remaining genetic and unique environmental variation in the frequency of participating in electronic machine gambling (among men and women) and symptoms of disordered gambling (among women) was greater in more disadvantaged localities. As the gambling industry continues to grow, it will be important to take into account the multiple contexts in which problematic gambling behavior can emerge-from genes to geography-as well as the ways in which such contexts may interact with each other. (c) 2015 APA, all rights reserved).
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Slutske, Wendy S.; Deutsch, Arielle R.; Statham, Dixie B.; Martin, Nicholas G.
2015-01-01
Previous research has demonstrated that local area characteristics (such as disadvantage and gambling outlet density) and genetic risk factors are associated with gambling involvement and disordered gambling. These two lines of research were brought together in the present study by examining the extent to which genetic contributions to individual differences in gambling involvement and disorder contributed to being exposed to, and were also accentuated by, local area disadvantage. Participants were members of the national community-based Australian Twin Registry who completed a telephone interview in which the past-year frequency of gambling and symptoms of disordered gambling were assessed. Indicators of local area disadvantage were based on census data matched to the participants' postal codes. Univariate biometric model-fitting revealed that exposure to area disadvantage was partially explained by genetic factors. Bivariate biometric model-fitting was conducted to examine the evidence for gene-environment interaction while accounting for gene-environment correlation. These analyses demonstrated that: (a) a small portion of the genetic propensity to gamble was explained by moving to or remaining in a disadvantaged area, and (b) the remaining genetic and unique environmental variation in the frequency of participating in electronic machine gambling (among men and women) and symptoms of disordered gambling (among women) was greater in more disadvantaged localities. As the gambling industry continues to grow, it will be important to take into account the multiple contexts in which problematic gambling behavior can emerge -- from genes to geography -- as well as the ways in which such contexts may interact with each other. PMID:26147321
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Selection of higher order regression models in the analysis of multi-factorial transcription data.
Prazeres da Costa, Olivia; Hoffman, Arthur; Rey, Johannes W; Mansmann, Ulrich; Buch, Thorsten; Tresch, Achim
2014-01-01
Many studies examine gene expression data that has been obtained under the influence of multiple factors, such as genetic background, environmental conditions, or exposure to diseases. The interplay of multiple factors may lead to effect modification and confounding. Higher order linear regression models can account for these effects. We present a new methodology for linear model selection and apply it to microarray data of bone marrow-derived macrophages. This experiment investigates the influence of three variable factors: the genetic background of the mice from which the macrophages were obtained, Yersinia enterocolitica infection (two strains, and a mock control), and treatment/non-treatment with interferon-γ. We set up four different linear regression models in a hierarchical order. We introduce the eruption plot as a new practical tool for model selection complementary to global testing. It visually compares the size and significance of effect estimates between two nested models. Using this methodology we were able to select the most appropriate model by keeping only relevant factors showing additional explanatory power. Application to experimental data allowed us to qualify the interaction of factors as either neutral (no interaction), alleviating (co-occurring effects are weaker than expected from the single effects), or aggravating (stronger than expected). We find a biologically meaningful gene cluster of putative C2TA target genes that appear to be co-regulated with MHC class II genes. We introduced the eruption plot as a tool for visual model comparison to identify relevant higher order interactions in the analysis of expression data obtained under the influence of multiple factors. We conclude that model selection in higher order linear regression models should generally be performed for the analysis of multi-factorial microarray data.
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NASA Astrophysics Data System (ADS)
Piemonti, Adriana Debora; Babbar-Sebens, Meghna; Mukhopadhyay, Snehasis; Kleinberg, Austin
2017-05-01
Interactive Genetic Algorithms (IGA) are advanced human-in-the-loop optimization methods that enable humans to give feedback, based on their subjective and unquantified preferences and knowledge, during the algorithm's search process. While these methods are gaining popularity in multiple fields, there is a critical lack of data and analyses on (a) the nature of interactions of different humans with interfaces of decision support systems (DSS) that employ IGA in water resources planning problems and on (b) the effect of human feedback on the algorithm's ability to search for design alternatives desirable to end-users. In this paper, we present results and analyses of observational experiments in which different human participants (surrogates and stakeholders) interacted with an IGA-based, watershed DSS called WRESTORE to identify plans of conservation practices in a watershed. The main goal of this paper is to evaluate how the IGA adapts its search process in the objective space to a user's feedback, and identify whether any similarities exist in the objective space of plans found by different participants. Some participants focused on the entire watershed, while others focused only on specific local subbasins. Additionally, two different hydrology models were used to identify any potential differences in interactive search outcomes that could arise from differences in the numerical values of benefits displayed to participants. Results indicate that stakeholders, in comparison to their surrogates, were more likely to use multiple features of the DSS interface to collect information before giving feedback, and dissimilarities existed among participants in the objective space of design alternatives.
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Research advances on microbial genetics in China in 2015.
Xie, Jian-ping; Han, Yu-bo; Liu, Gang; Bai, Lin-quan
2016-09-01
In 2015, there are significant progresses in many aspects of the microbial genetics in China. To showcase the contribution of Chinese scientists in microbial genetics, this review surveys several notable progresses in microbial genetics made largely by Chinese scientists, and some key findings are highlighted. For the basic microbial genetics, the components, structures and functions of many macromolecule complexes involved in gene expression regulation have been elucidated. Moreover, the molecular basis underlying the recognition of foreign nucleic acids by microbial immune systems was unveiled. We also illustrated the biosynthetic pathways and regulators of multiple microbial compounds, novel enzyme reactions, and new mechanisms regulating microbial gene expression. And new findings were obtained in the microbial development, evolution and population genetics. For the industrial microbiology, more understanding on the molecular basis of the microbial factory has been gained. For the pathogenic microbiology, the genetic circuits of several pathogens were depicted, and significant progresses were achieved for understanding the pathogen-host interaction and revealing the genetic mechanisms underlying antimicrobial resistance, emerging pathogens and environmental microorganisms at the genomic level. In future, the genetic diversity of microbes can be used to obtain specific products, while gut microbiome is gathering momentum.
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Baynam, Gareth; Pachter, Nicholas; McKenzie, Fiona; Townshend, Sharon; Slee, Jennie; Kiraly-Borri, Cathy; Vasudevan, Anand; Hawkins, Anne; Broley, Stephanie; Schofield, Lyn; Verhoef, Hedwig; Walker, Caroline E; Molster, Caron; Blackwell, Jenefer M; Jamieson, Sarra; Tang, Dave; Lassmann, Timo; Mina, Kym; Beilby, John; Davis, Mark; Laing, Nigel; Murphy, Lesley; Weeramanthri, Tarun; Dawkins, Hugh; Goldblatt, Jack
2016-06-11
The Rare and Undiagnosed Diseases Diagnostic Service (RUDDS) refers to a genomic diagnostic platform operating within the Western Australian Government clinical services delivered through Genetic Services of Western Australia (GSWA). GSWA has provided a state-wide service for clinical genetic care for 28 years and it serves a population of 2.5 million people across a geographical area of 2.5milion Km(2). Within this context, GSWA has established a clinically integrated genomic diagnostic platform in partnership with other public health system managers and service providers, including but not limited to the Office of Population Health Genomics, Diagnostic Genomics (PathWest Laboratories) and with executive level support from the Department of Health. Herein we describe report presents the components of this service that are most relevant to the heterogeneity of paediatric clinical genetic care. Briefly the platform : i) offers multiple options including non-genetic testing; monogenic and genomic (targeted in silico filtered and whole exome) analysis; and matchmaking; ii) is delivered in a patient-centric manner that is resonant with the patient journey, it has multiple points for entry, exit and re-entry to allow people access to information they can use, when they want to receive it; iii) is synchronous with precision phenotyping methods; iv) captures new knowledge, including multiple expert review; v) is integrated with current translational genomic research activities and best practice; and vi) is designed for flexibility for interactive generation of, and integration with, clinical research for diagnostics, community engagement, policy and models of care. The RUDDS has been established as part of routine clinical genetic services and is thus sustainable, equitably managed and seeks to translate new knowledge into efficient diagnostics and improved health for the whole community.
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Liu, Shiwei; Liu, Yihui; Zhao, Jiawei; Cai, Shitao; Qian, Hongmei; Zuo, Kaijing; Zhao, Lingxia; Zhang, Lida
2017-04-01
Rice (Oryza sativa) is one of the most important staple foods for more than half of the global population. Many rice traits are quantitative, complex and controlled by multiple interacting genes. Thus, a full understanding of genetic relationships will be critical to systematically identify genes controlling agronomic traits. We developed a genome-wide rice protein-protein interaction network (RicePPINet, http://netbio.sjtu.edu.cn/riceppinet) using machine learning with structural relationship and functional information. RicePPINet contained 708 819 predicted interactions for 16 895 non-transposable element related proteins. The power of the network for discovering novel protein interactions was demonstrated through comparison with other publicly available protein-protein interaction (PPI) prediction methods, and by experimentally determined PPI data sets. Furthermore, global analysis of domain-mediated interactions revealed RicePPINet accurately reflects PPIs at the domain level. Our studies showed the efficiency of the RicePPINet-based method in prioritizing candidate genes involved in complex agronomic traits, such as disease resistance and drought tolerance, was approximately 2-11 times better than random prediction. RicePPINet provides an expanded landscape of computational interactome for the genetic dissection of agronomically important traits in rice. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.
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Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease
Hartman, John L.; Stisher, Chandler; Outlaw, Darryl A.; Guo, Jingyu; Shah, Najaf A.; Tian, Dehua; Santos, Sean M.; Rodgers, John W.; White, Richard A.
2015-01-01
The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease. PMID:25668739
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Genetic control of floral zygomorphy in pea (Pisum sativum L.).
Wang, Zheng; Luo, Yonghai; Li, Xin; Wang, Liping; Xu, Shilei; Yang, Jun; Weng, Lin; Sato, Shusei; Tabata, Satoshi; Ambrose, Mike; Rameau, Catherine; Feng, Xianzhong; Hu, Xiaohe; Luo, Da
2008-07-29
Floral zygomorphy (flowers with bilateral symmetry) has multiple origins and typically manifests two kinds of asymmetries, dorsoventral (DV) and organ internal (IN) asymmetries in floral and organ planes, respectively, revealing the underlying key regulators in plant genomes that generate and superimpose various mechanisms to build up complexity and different floral forms during plant development. In this study, we investigate the loci affecting these asymmetries during the development of floral zygomorphy in pea (Pisum sativum L.). Two genes, LOBED STANDARD 1 (LST1) and KEELED WINGS (K), were cloned that encode TCP transcription factors and have divergent functions to constitute the DV asymmetry. A previously undescribed regulator, SYMMETRIC PETALS 1 (SYP1), has been isolated as controlling IN asymmetry. Genetic analysis demonstrates that DV and IN asymmetries could be controlled independently by the two kinds of regulators in pea, and their interactions help to specify the type of zygomorphy. Based on the genetic analysis in pea, we suggest that variation in both the functions and interactions of these regulators could give rise to the wide spectrum of floral symmetries among legume species and other flowering plants.
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Fitness consequences of parental compatibility in the frog Crinia georgiana.
Dziminski, Martin A; Roberts, J Dale; Simmons, Leigh W
2008-04-01
Theory suggests that multiple mating by females can evolve as a mechanism for acquiring compatible genes that promote offspring fitness. Genetic compatibility models predict that differences in fitness among offspring arise from interactions between male and female haplotypes. Using a cross-classified breeding design and in vitro fertilization, we raised families of maternal and paternal half-siblings of the frog Crinia georgiana, a species with a polyandrous breeding system and external fertilization. After controlling for variation in maternal provisioning, we found significant effects of interacting parental haplotypes on fertilization success, and nonadditive genetic effects on measures of offspring fitness such as embryo survival, and survival to, size at, and time to metamorphosis. Additive genetic variation due to males and females was negligible, and not statistically significant for any of the fitness traits measured. Combinations of parental haplotypes that resulted in high rates of fertilization produced offspring with higher embryo survival and rapid juvenile development. We suggest that a gamete recognition mechanism for selective fertilization by compatible sperm may promote offspring fitness in this system.
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Uncovering Local Trends in Genetic Effects of Multiple Phenotypes via Functional Linear Models.
Vsevolozhskaya, Olga A; Zaykin, Dmitri V; Barondess, David A; Tong, Xiaoren; Jadhav, Sneha; Lu, Qing
2016-04-01
Recent technological advances equipped researchers with capabilities that go beyond traditional genotyping of loci known to be polymorphic in a general population. Genetic sequences of study participants can now be assessed directly. This capability removed technology-driven bias toward scoring predominantly common polymorphisms and let researchers reveal a wealth of rare and sample-specific variants. Although the relative contributions of rare and common polymorphisms to trait variation are being debated, researchers are faced with the need for new statistical tools for simultaneous evaluation of all variants within a region. Several research groups demonstrated flexibility and good statistical power of the functional linear model approach. In this work we extend previous developments to allow inclusion of multiple traits and adjustment for additional covariates. Our functional approach is unique in that it provides a nuanced depiction of effects and interactions for the variables in the model by representing them as curves varying over a genetic region. We demonstrate flexibility and competitive power of our approach by contrasting its performance with commonly used statistical tools and illustrate its potential for discovery and characterization of genetic architecture of complex traits using sequencing data from the Dallas Heart Study. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.
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Sorrentino, F S; Gallenga, C E; Bonifazzi, C; Perri, P
2016-01-01
Retinitis pigmentosa (RP) is a group of inherited retinal disorders characterized by a complex association between tremendous genotypic multiplicity and great phenotypic heterogeneity. The severity of the clinical manifestation depends on penetrance and expressivity of the disease-gene. Also, various interactions between gene expression and environmental factors have been hypothesized. More than 250 genes with ~4500 causative mutations have been reported to be involved in different RP-related mechanisms. Nowadays, not more than the 50% of RPs are attributable to identified genes, whereas the rest of molecular defects are still undetectable, especially in populations where few genetic screenings have been performed. Therefore, new genetic strategies can be a remarkably useful tool to aid clinical diagnosis, potentially modifying treatment options, and family counseling. Genome-wide analytical techniques (array comparative genomic hybridization and single-nucleotide polymorphism genotyping) and DNA sequencing strategies (arrayed primer extension, Sanger sequencing, and ultra high-throughput sequencing) are successfully used to early make molecular diagnosis detecting single or multiple mutations in the huge heterogeneity of RPs. To date, further research needs to be carried out to better investigate the genotype/phenotype correlation, putting together genetic and clinical findings to provide detailed information concerning the risk of RP development and novel effective treatments. PMID:27564722
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Gene–environment interactions: key to unraveling the mystery of Parkinson’s disease
Gao, Hui-Ming; Hong, Jau-shyong
2011-01-01
Parkinson’s disease (PD) is the second most common neurodegenerative disease. The gradual, irreversible loss of dopamine neurons in the substantia nigra isthe signature lesion of PD. Clinical symptoms of PD become apparent when 50–60% of nigral dopamine neurons are lost. PD progresses insidiously for 5–7 years (preclinical period) and then continues to worsen even under the symptomatic treatment. To determine what triggers the disease onset and what drives the chronic, self-propelling neurodegenerative process becomes critical and urgent, since lack of such knowledge impedes the discovery of effective treatments to retard PD progression. At present, available therapeutics only temporarily relieve PD symptoms. While the identification of causative gene defects in familial PD uncovers important genetic influences in this disease, the majority of PD cases are sporadic and idiopathic. The current consensus suggests that PD develops from multiple risk factors including aging, genetic predisposition, and environmental exposure. Here, we briefly review research on the genetic and environmental causes of PD. We also summarize very recent genome-wide association studies on risk gene polymorphisms in the emergence of PD. We highlight the new converging evidence on gene-environment interplay in the development of PD with an emphasis on newly developed multiple-hit PD models involving both genetic lesions and environmental triggers. PMID:21439347
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Wound Healing in Mac-1 Deficient Mice
2017-05-01
36. Rosenkranz AR, Coxon A, Maurer M, Gurish MF, Austen KF, Friend DS, Galli SJ, Mayadas TN. Impaired mast cell development and innate immunity in Mac...genetically deficient mice. 3 INTRODUCTION Wound healing is a complex yet well-regulated process in which multiple resident cells ...recruited inflammatory cells , and stem cells interact to create an environment that supports the healing process. An optimal inflammatory response is a
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Bone marrow micro-environment is a crucial player for myelomagenesis and disease progression
Mondello, Patrizia; Cuzzocrea, Salvatore; Navarra, Michele; Mian, Michael
2017-01-01
Despite the advent of many therapeutic agents, such as bortezomib and lenalidomide that have significantly improved the overall survival, multiple myeloma remains an incurable disease. Failure to cure is multifactorial and can be attributed to the underlying genetic heterogeneity of the cancer and to the surrounding micro-environment. Understanding the mutual interaction between myeloma cells and micro-environment may lead to the development of novel treatment strategies able to eradicate this disease. In this review we discuss the principal molecules involved in the micro-environment network in multiple myeloma and the currently available therapies targeting them. PMID:28099912
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The genetic basis of female multiple mating in a polyandrous livebearing fish
Evans, Jonathan P; Gasparini, Clelia
2013-01-01
The widespread occurrence of female multiple mating (FMM) demands evolutionary explanation, particularly in the light of the costs of mating. One explanation encapsulated by “good sperm” and “sexy-sperm” (GS-SS) theoretical models is that FMM facilitates sperm competition, thus ensuring paternity by males that pass on genes for elevated sperm competitiveness to their male offspring. While support for this component of GS-SS theory is accumulating, a second but poorly tested assumption of these models is that there should be corresponding heritable genetic variation in FMM – the proposed mechanism of postcopulatory preferences underlying GS-SS models. Here, we conduct quantitative genetic analyses on paternal half-siblings to test this component of GS-SS theory in the guppy (Poecilia reticulata), a freshwater fish with some of the highest known rates of FMM in vertebrates. As with most previous quantitative genetic analyses of FMM in other species, our results reveal high levels of phenotypic variation in this trait and a correspondingly low narrow-sense heritability (h2 = 0.11). Furthermore, although our analysis of additive genetic variance in FMM was not statistically significant (probably owing to limited statistical power), the ensuing estimate of mean-standardized additive genetic variance (IA = 0.7) was nevertheless relatively low compared with estimates published for life-history traits across a broad range of taxa. Our results therefore add to a growing body of evidence that FMM is characterized by relatively low additive genetic variation, thus apparently contradicting GS-SS theory. However, we qualify this conclusion by drawing attention to potential deficiencies in most designs (including ours) that have tested for genetic variation in FMM, particularly those that fail to account for intersexual interactions that underlie FMM in many systems. PMID:23403856
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Farzan, Shohreh F.; Department of Population Health, New York University School of Medicine, New York, NY; Karagas, Margaret R.
Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide and mounting evidence indicates that toxicant exposures can profoundly impact on CVD risk. Epidemiologic studies have suggested that arsenic (As) exposure is positively related to increases in blood pressure (BP), a primary CVD risk factor. However, evidence of whether genetic susceptibility can modify the association between As and BP is lacking. In this study, we used mixed effect models adjusted for potential confounders to examine the interaction between As exposure from well water and potential genetic modifiers on longitudinal change in BP over approximately 7 years of follow-upmore » in 1137 subjects selected from the Health Effects of Arsenic Longitudinal Study (HEALS) cohort in Bangladesh. Genotyping was conducted for 235 SNPs in 18 genes related to As metabolism, oxidative stress and endothelial function. We observed interactions between 44 SNPs with well water As for one or more BP outcome measures (systolic, diastolic, or pulse pressure (PP)) over the course of follow-up. The interaction between CYBA rs3794624 and well water As on annual PP remained statistically significant after correction for multiple comparisons (FDR-adjusted p for interaction = 0.05). Among individuals with the rs3794624 variant genotype, well water As was associated with a 2.23 mm Hg (95% CI: 1.14–3.32) greater annual increase in PP, while among those with the wild type, well water As was associated with a 0.13 mm Hg (95% CI: 0.02–0.23) greater annual increase in PP. Our results suggest that genetic variability may contribute to As-associated increases in BP over time. - Highlights: • Arsenic (As) exposure has been associated with blood pressure increases over time. • Genetic polymorphisms may modify the association between As and blood pressure. • An interaction between CYBA rs3794624 and well As increased annual pulse pressure. • Genetic variants may contribute to As-related blood pressure increases over time.« less
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Engineering genetic circuit interactions within and between synthetic minimal cells
NASA Astrophysics Data System (ADS)
Adamala, Katarzyna P.; Martin-Alarcon, Daniel A.; Guthrie-Honea, Katriona R.; Boyden, Edward S.
2017-05-01
Genetic circuits and reaction cascades are of great importance for synthetic biology, biochemistry and bioengineering. An open question is how to maximize the modularity of their design to enable the integration of different reaction networks and to optimize their scalability and flexibility. One option is encapsulation within liposomes, which enables chemical reactions to proceed in well-isolated environments. Here we adapt liposome encapsulation to enable the modular, controlled compartmentalization of genetic circuits and cascades. We demonstrate that it is possible to engineer genetic circuit-containing synthetic minimal cells (synells) to contain multiple-part genetic cascades, and that these cascades can be controlled by external signals as well as inter-liposomal communication without crosstalk. We also show that liposomes that contain different cascades can be fused in a controlled way so that the products of incompatible reactions can be brought together. Synells thus enable a more modular creation of synthetic biology cascades, an essential step towards their ultimate programmability.
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Genetic architectures of seropositive and seronegative rheumatic diseases.
Kirino, Yohei; Remmers, Elaine F
2015-07-01
Rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis and some other rheumatic diseases are genetically complex, with evidence of familial clustering, but not of Mendelian inheritance. These diseases are thought to result from contributions and interactions of multiple genetic and nongenetic risk factors, which have small effects individually. Genome-wide association studies (GWAS) of large collections of data from cases and controls have revealed many genetic factors that contribute to non-Mendelian rheumatic diseases, thus providing insights into associated molecular mechanisms. This Review summarizes methods for the identification of gene variants that influence genetically complex diseases and focuses on what we have learned about the rheumatic diseases for which GWAS have been reported. Our review of the disease-associated loci identified to date reveals greater sharing of risk loci among the groups of seropositive (diseases in which specific autoantibodies are often present) or seronegative diseases than between these two groups. The nature of the shared and discordant loci suggests important similarities and differences among these diseases.
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Entropy Based Genetic Association Tests and Gene-Gene Interaction Tests
de Andrade, Mariza; Wang, Xin
2011-01-01
In the past few years, several entropy-based tests have been proposed for testing either single SNP association or gene-gene interaction. These tests are mainly based on Shannon entropy and have higher statistical power when compared to standard χ2 tests. In this paper, we extend some of these tests using a more generalized entropy definition, Rényi entropy, where Shannon entropy is a special case of order 1. The order λ (>0) of Rényi entropy weights the events (genotype/haplotype) according to their probabilities (frequencies). Higher λ places more emphasis on higher probability events while smaller λ (close to 0) tends to assign weights more equally. Thus, by properly choosing the λ, one can potentially increase the power of the tests or the p-value level of significance. We conducted simulation as well as real data analyses to assess the impact of the order λ and the performance of these generalized tests. The results showed that for dominant model the order 2 test was more powerful and for multiplicative model the order 1 or 2 had similar power. The analyses indicate that the choice of λ depends on the underlying genetic model and Shannon entropy is not necessarily the most powerful entropy measure for constructing genetic association or interaction tests. PMID:23089811
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2013-01-01
Background Wolbachia pipientis, a diverse group of α-proteobacteria, can alter arthropod host reproduction and confer a reproductive advantage to Wolbachia-infected females (cytoplasmic incompatibility (CI)). This advantage can alter host population genetics because Wolbachia-infected females produce more offspring with their own mitochondrial DNA (mtDNA) haplotypes than uninfected females. Thus, these host haplotypes become common or fixed (selective sweep). Although simulations suggest that for a CI-mediated sweep to occur, there must be a transient phase with repeated initial infections of multiple individual hosts by different Wolbachia strains, this has not been observed empirically. Wolbachia has been found in the tsetse fly, Glossina fuscipes fuscipes, but it is not limited to a single host haplotype, suggesting that CI did not impact its population structure. However, host population genetic differentiation could have been generated if multiple Wolbachia strains interacted in some populations. Here, we investigated Wolbachia genetic variation in G. f. fuscipes populations of known host genetic composition in Uganda. We tested for the presence of multiple Wolbachia strains using Multi-Locus Sequence Typing (MLST) and for an association between geographic region and host mtDNA haplotype using Wolbachia DNA sequence from a variable locus, groEL (heat shock protein 60). Results MLST demonstrated that some G. f. fuscipes carry Wolbachia strains from two lineages. GroEL revealed high levels of sequence diversity within and between individuals (Haplotype diversity = 0.945). We found Wolbachia associated with 26 host mtDNA haplotypes, an unprecedented result. We observed a geographical association of one Wolbachia lineage with southern host mtDNA haplotypes, but it was non-significant (p = 0.16). Though most Wolbachia-infected host haplotypes were those found in the contact region between host mtDNA groups, this association was non-significant (p = 0.17). Conclusions High Wolbachia sequence diversity and the association of Wolbachia with multiple host haplotypes suggest that different Wolbachia strains infected G. f. fuscipes multiple times independently. We suggest that these observations reflect a transient phase in Wolbachia evolution that is influenced by the long gestation and low reproductive output of tsetse. Although G. f. fuscipes is superinfected with Wolbachia, our data does not support that bidirectional CI has influenced host genetic diversity in Uganda. PMID:23384159
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Gender Differences in Genetic Risk Profiles for Cardiovascular Disease
Silander, Kaisa; Saarela, Olli; Ripatti, Samuli; Auro, Kirsi; Karvanen, Juha; Kulathinal, Sangita; Niemelä, Matti; Ellonen, Pekka; Vartiainen, Erkki; Jousilahti, Pekka; Saarela, Janna; Kuulasmaa, Kari; Evans, Alun; Perola, Markus; Salomaa, Veikko; Peltonen, Leena
2008-01-01
Background Cardiovascular disease (CVD) incidence, complications and burden differ markedly between women and men. Although there is variation in the distribution of lifestyle factors between the genders, they do not fully explain the differences in CVD incidence and suggest the existence of gender-specific genetic risk factors. We aimed to estimate whether the genetic risk profiles of coronary heart disease (CHD), ischemic stroke and the composite end-point of CVD differ between the genders. Methodology/Principal Findings We studied in two Finnish population cohorts, using the case-cohort design the association between common variation in 46 candidate genes and CHD, ischemic stroke, CVD, and CVD-related quantitative risk factors. We analyzed men and women jointly and also conducted genotype-gender interaction analysis. Several allelic variants conferred disease risk for men and women jointly, including rs1801020 in coagulation factor XII (HR = 1.31 (1.08–1.60) for CVD, uncorrected p = 0.006 multiplicative model). Variant rs11673407 in the fucosyltransferase 3 gene was strongly associated with waist/hip ratio (uncorrected p = 0.00005) in joint analysis. In interaction analysis we found statistical evidence of variant-gender interaction conferring risk of CHD and CVD: rs3742264 in the carboxypeptidase B2 gene, p(interaction) = 0.009 for CHD, and rs2774279 in the upstream stimulatory factor 1 gene, p(interaction) = 0.007 for CHD and CVD, showed strong association in women but not in men, while rs2069840 in interleukin 6 gene, p(interaction) = 0.004 for CVD, showed strong association in men but not in women (uncorrected p-values). Also, two variants in the selenoprotein S gene conferred risk for ischemic stroke in women, p(interaction) = 0.003 and 0.007. Importantly, we identified a larger number of gender-specific effects for women than for men. Conclusions/Significance A false discovery rate analysis suggests that we may expect half of the reported findings for combined gender analysis to be true positives, while at least third of the reported genotype-gender interaction results are true positives. The asymmetry in positive findings between the genders could imply that genetic risk loci for CVD are more readily detectable in women, while for men they are more confounded by environmental/lifestyle risk factors. The possible differences in genetic risk profiles between the genders should be addressed in more detail in genetic studies of CVD, and more focus on female CVD risk is also warranted in genome-wide association studies. PMID:18974842
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Hill, Kristine; Porco, Silvana; Lobet, Guillaume; Zappala, Susan; Mooney, Sacha; Draye, Xavier; Bennett, Malcolm J.
2013-01-01
Genetic and genomic approaches in model organisms have advanced our understanding of root biology over the last decade. Recently, however, systems biology and modeling have emerged as important approaches, as our understanding of root regulatory pathways has become more complex and interpreting pathway outputs has become less intuitive. To relate root genotype to phenotype, we must move beyond the examination of interactions at the genetic network scale and employ multiscale modeling approaches to predict emergent properties at the tissue, organ, organism, and rhizosphere scales. Understanding the underlying biological mechanisms and the complex interplay between systems at these different scales requires an integrative approach. Here, we describe examples of such approaches and discuss the merits of developing models to span multiple scales, from network to population levels, and to address dynamic interactions between plants and their environment. PMID:24143806
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Levine, Andrew J; Reynolds, Sandra; Cox, Christopher; Miller, Eric N; Sinsheimer, Janet S; Becker, James T; Martin, Eileen; Sacktor, Ned
2014-06-01
Both human immunodeficiency virus (HIV)-1 infection and illicit stimulant use can adversely impact neurocognitive functioning, and these effects can be additive. However, significant variability exists such that as-of-yet unidentified exogenous and endogenous factors affect one's risk for neurocognitive impairment. Literature on both HIV and stimulant use indicates that host genetic variants in immunologic and dopamine-related genes are one such factor. In this study, the individual and interactive effects of HIV status, stimulant use, and genotype upon neurocognitive functioning were examined longitudinally over a 10-year period. Nine hundred fifty-two Caucasian HIV+ and HIV- cases from the Multicenter AIDS Cohort Study were included. All cases had at least two comprehensive neurocognitive evaluations between 1985 and 1995. Pre-highly active antiretroviral therapy (HAART) data were examined in order to avoid the confounding effect of variable drug regimens. Linear mixed models were used, with neurocognitive domain scores as the outcome variables. No four-way interactions were found, indicating that HIV and stimulant use do not interact over time to affect neurocognitive functioning as a function of genotype. Multiple three-way interactions were found that involved genotype and HIV status. All immunologically related genes found to interact with HIV status affected neurocognitive functioning in the expected direction; however, only C-C chemokine ligand 2 (CCL2) and CCL3 affected HIV+ individuals specifically. Dopamine-related genetic variants generally affected HIV-negative individuals only. Neurocognitive functioning among HIV+ individuals who also used stimulants was not significantly different from those who did not use stimulants. The findings support the role of immunologically related genetic differences in CCL2 and CCL3 in neurocognitive functioning among HIV+ individuals; however, their impact is minor. Being consistent with findings from another cohort, dopamine (DA)-related genetic differences do not appear to impact the longitudinal neurocognitive functioning of HIV+ individuals.
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Using Movies to Analyse Gene Circuit Dynamics in Single Cells
Locke, James CW; Elowitz, Michael B
2010-01-01
Preface Many bacterial systems rely on dynamic genetic circuits to control critical processes. A major goal of systems biology is to understand these behaviours in terms of individual genes and their interactions. However, traditional techniques based on population averages wash out critical dynamics that are either unsynchronized between cells or driven by fluctuations, or ‘noise,’ in cellular components. Recently, the combination of time-lapse microscopy, quantitative image analysis, and fluorescent protein reporters has enabled direct observation of multiple cellular components over time in individual cells. In conjunction with mathematical modelling, these techniques are now providing powerful insights into genetic circuit behaviour in diverse microbial systems. PMID:19369953
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Wu, Zheyang; Zhao, Hongyu
2012-01-01
For more fruitful discoveries of genetic variants associated with diseases in genome-wide association studies, it is important to know whether joint analysis of multiple markers is more powerful than the commonly used single-marker analysis, especially in the presence of gene-gene interactions. This article provides a statistical framework to rigorously address this question through analytical power calculations for common model search strategies to detect binary trait loci: marginal search, exhaustive search, forward search, and two-stage screening search. Our approach incorporates linkage disequilibrium, random genotypes, and correlations among score test statistics of logistic regressions. We derive analytical results under two power definitions: the power of finding all the associated markers and the power of finding at least one associated marker. We also consider two types of error controls: the discovery number control and the Bonferroni type I error rate control. After demonstrating the accuracy of our analytical results by simulations, we apply them to consider a broad genetic model space to investigate the relative performances of different model search strategies. Our analytical study provides rapid computation as well as insights into the statistical mechanism of capturing genetic signals under different genetic models including gene-gene interactions. Even though we focus on genetic association analysis, our results on the power of model selection procedures are clearly very general and applicable to other studies.
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Genetic architecture for susceptibility to gout in the KARE cohort study.
Shin, Jimin; Kim, Younyoung; Kong, Minyoung; Lee, Chaeyoung
2012-06-01
This study aimed to identify functional associations of cis-regulatory regions with gout susceptibility using data resulted from a genome-wide association study (GWAS), and to show a genetic architecture for gout with interaction effects among genes within each of the identified functions. The GWAS was conducted with 8314 control subjects and 520 patients with gout in the Korea Association REsource cohort. However, genetic associations with any individual nucleotide variants were not discovered by Bonferroni multiple testing in the GWAS (P>1.42 × 10(-7)). Genomic regions enrichment analysis was employed to identify functional associations of cis-regulatory regions. This analysis revealed several biological processes associated with gout susceptibility, and they were quite different from those with serum uric acid level. Epistasis for susceptibility to gout was estimated using entropy decomposition with selected genes within each biological process identified by the genomic regions enrichment analysis. Some epistases among nucleotide sequence variants for gout susceptibility were found to be larger than their individual effects. This study provided the first evidence that genetic factors for gout susceptibility greatly differed from those for serum uric acid level, which may suggest that research endeavors for identifying genetic factors for gout susceptibility should not be heavily dependent on pathogenesis of uric acid. Interaction effects between genes should be examined to explain a large portion of phenotypic variability for gout susceptibility.
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Wu, Zheyang; Zhao, Hongyu
2013-01-01
For more fruitful discoveries of genetic variants associated with diseases in genome-wide association studies, it is important to know whether joint analysis of multiple markers is more powerful than the commonly used single-marker analysis, especially in the presence of gene-gene interactions. This article provides a statistical framework to rigorously address this question through analytical power calculations for common model search strategies to detect binary trait loci: marginal search, exhaustive search, forward search, and two-stage screening search. Our approach incorporates linkage disequilibrium, random genotypes, and correlations among score test statistics of logistic regressions. We derive analytical results under two power definitions: the power of finding all the associated markers and the power of finding at least one associated marker. We also consider two types of error controls: the discovery number control and the Bonferroni type I error rate control. After demonstrating the accuracy of our analytical results by simulations, we apply them to consider a broad genetic model space to investigate the relative performances of different model search strategies. Our analytical study provides rapid computation as well as insights into the statistical mechanism of capturing genetic signals under different genetic models including gene-gene interactions. Even though we focus on genetic association analysis, our results on the power of model selection procedures are clearly very general and applicable to other studies. PMID:23956610
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Ye, Ping; Peyser, Brian D; Spencer, Forrest A; Bader, Joel S
2005-01-01
Background In a genetic interaction, the phenotype of a double mutant differs from the combined phenotypes of the underlying single mutants. When the single mutants have no growth defect, but the double mutant is lethal or exhibits slow growth, the interaction is termed synthetic lethality or synthetic fitness. These genetic interactions reveal gene redundancy and compensating pathways. Recently available large-scale data sets of genetic interactions and protein interactions in Saccharomyces cerevisiae provide a unique opportunity to elucidate the topological structure of biological pathways and how genes function in these pathways. Results We have defined congruent genes as pairs of genes with similar sets of genetic interaction partners and constructed a genetic congruence network by linking congruent genes. By comparing path lengths in three types of networks (genetic interaction, genetic congruence, and protein interaction), we discovered that high genetic congruence not only exhibits correlation with direct protein interaction linkage but also exhibits commensurate distance with the protein interaction network. However, consistent distances were not observed between genetic and protein interaction networks. We also demonstrated that congruence and protein networks are enriched with motifs that indicate network transitivity, while the genetic network has both transitive (triangle) and intransitive (square) types of motifs. These results suggest that robustness of yeast cells to gene deletions is due in part to two complementary pathways (square motif) or three complementary pathways, any two of which are required for viability (triangle motif). Conclusion Genetic congruence is superior to genetic interaction in prediction of protein interactions and function associations. Genetically interacting pairs usually belong to parallel compensatory pathways, which can generate transitive motifs (any two of three pathways needed) or intransitive motifs (either of two pathways needed). PMID:16283923
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Posttranslational Modifications and Plant-Environment Interaction.
Hashiguchi, A; Komatsu, S
2017-01-01
Posttranslational modifications (PTMs) of proteins such as phosphorylation and ubiquitination are crucial for controlling protein stability, localization, and conformation. Genetic information encoded in DNA is transcribed, translated, and increases its complexity by multiple PTMs. Conformational change introduced by PTMs affects interacting partners of each proteins and their downstream signaling; therefore, PTMs are the major level of modulations of total outcome of living cells. Plants are living in harsh environment that requires unremitting physiological modulation to survive, and the plant response to various environment stresses is regulated by PTMs of proteins. This review deals with the novel knowledge of PTM-focused proteomic studies on various life conditions. PTMs are focused that mediate plant-environment interaction such as stress perception, protein homeostasis, control of energy shift, and defense by immune system. Integration of diverse signals on a protein via multiple PTMs is discussed as well, considering current situation where signal integration became an emerging area approached by systems biology into account. © 2017 Elsevier Inc. All rights reserved.
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Feltus, F Alex
2014-06-01
Understanding the control of any trait optimally requires the detection of causal genes, gene interaction, and mechanism of action to discover and model the biochemical pathways underlying the expressed phenotype. Functional genomics techniques, including RNA expression profiling via microarray and high-throughput DNA sequencing, allow for the precise genome localization of biological information. Powerful genetic approaches, including quantitative trait locus (QTL) and genome-wide association study mapping, link phenotype with genome positions, yet genetics is less precise in localizing the relevant mechanistic information encoded in DNA. The coupling of salient functional genomic signals with genetically mapped positions is an appealing approach to discover meaningful gene-phenotype relationships. Techniques used to define this genetic-genomic convergence comprise the field of systems genetics. This short review will address an application of systems genetics where RNA profiles are associated with genetically mapped genome positions of individual genes (eQTL mapping) or as gene sets (co-expression network modules). Both approaches can be applied for knowledge independent selection of candidate genes (and possible control mechanisms) underlying complex traits where multiple, likely unlinked, genomic regions might control specific complex traits. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
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The heritable basis of gene-environment interactions in cardiometabolic traits.
Poveda, Alaitz; Chen, Yan; Brändström, Anders; Engberg, Elisabeth; Hallmans, Göran; Johansson, Ingegerd; Renström, Frida; Kurbasic, Azra; Franks, Paul W
2017-03-01
Little is known about the heritable basis of gene-environment interactions in humans. We therefore screened multiple cardiometabolic traits to assess the probability that they are influenced by genotype-environment interactions. Fourteen established environmental risk exposures and 11 cardiometabolic traits were analysed in the VIKING study, a cohort of 16,430 Swedish adults from 1682 extended pedigrees with available detailed genealogical, phenotypic and demographic information, using a maximum likelihood variance decomposition method in Sequential Oligogenic Linkage Analysis Routines software. All cardiometabolic traits had statistically significant heritability estimates, with narrow-sense heritabilities (h 2 ) ranging from 24% to 47%. Genotype-environment interactions were detected for age and sex (for the majority of traits), physical activity (for triacylglycerols, 2 h glucose and diastolic BP), smoking (for weight), alcohol intake (for weight, BMI and 2 h glucose) and diet pattern (for weight, BMI, glycaemic traits and systolic BP). Genotype-age interactions for weight and systolic BP, genotype-sex interactions for BMI and triacylglycerols and genotype-alcohol intake interactions for weight remained significant after multiple test correction. Age, sex and alcohol intake are likely to be major modifiers of genetic effects for a range of cardiometabolic traits. This information may prove valuable for studies that seek to identify specific loci that modify the effects of lifestyle in cardiometabolic disease.
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The influence of the microenvironment on the malignant phenotype
NASA Technical Reports Server (NTRS)
Park, C. C.; Bissell, M. J.; Barcellos-Hoff, M. H.
2000-01-01
Normal tissue homeostasis is maintained by dynamic interactions between epithelial cells and their microenvironment. As tissue becomes cancerous, there are reciprocal interactions between neoplastic cells, adjacent normal cells such as stroma and endothelium, and their microenvironments. The current dominant paradigm wherein multiple genetic lesions provide both the impetus for, and the Achilles heel of, cancer might be inadequate to understand cancer as a disease process. In the following brief review, we will use selected examples to illustrate the influence of the microenvironment in the evolution of the malignant phenotype. We will also discuss recent studies that suggest novel therapeutic interventions might be derived from focusing on microenvironment and tumor cells interactions.
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Group selection for adaptation to multiple-hen cages: humoral immune response.
Hester, P Y; Muir, W M; Craig, J V
1996-11-01
A selected line of White Leghorns, which has shown improved survivability and reduced feather loss in large multiple-hen cages, was evaluated for humoral immune response to SRBC under both stressed and unstressed conditions. Three lines of chickens (selected, control, and commercial) were housed in either single- (1 hen) or multiple-hen cages (12 hens, social competition) and subjected to a cold ambient temperature (0 C) at 33 wk of age and to two heating episodes (38 C) at 44 wk of age. Each hen was challenged intravenously with 1 mL of a 7% saline suspension of SRBC at the time that cold exposure was initiated. Hens subjected to high ambient temperatures had been exposed previously to a cold temperature, but were not challenged with SRBC until 16 to 18 h following the end of the second heating episode. Exposure to cold caused immunosuppression in single-caged hens, but not in hens in colony cages. Single- vs colony-caged hens of the control environment challenged with SRBC at 33 wk of age had similar primary hemagglutinin responses to SRBC. Hens subjected to heat experienced immunosuppression at 9 and 12 d following challenge to SRBC when compared to the controls. Hens of multiple-bird cages challenged with antigen at 44 wk of age had a significantly lower hemagglutinin response to SRBC than those reared in single-bird cages. The three lines of genetic stock had similar primary hemagglutinin responses to SRBC; the interactions of genetic stock with cage size or environmental temperature were not significant. It was concluded that genetically selecting hens for survival in multiple-hen cages did not affect their humoral immune response to SRBC.
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Inflammatory Genes and Psychological Factors Predict Induced Shoulder Pain Phenotype
George, Steven Z.; Parr, Jeffrey J.; Wallace, Margaret R.; Wu, Samuel S.; Borsa, Paul A.; Dai, Yunfeng; Fillingim, Roger B.
2014-01-01
Purpose The pain experience has multiple influences but little is known about how specific biological and psychological factors interact to influence pain responses. The current study investigated the combined influences of genetic (pro-inflammatory) and psychological factors on several pre-clinical shoulder pain phenotypes. Methods An exercise-induced shoulder injury model was used, and a priori selected genetic (IL1B, TNF/LTA region, IL6 single nucleotide polymorphisms, SNPs) and psychological (anxiety, depressive symptoms, pain catastrophizing, fear of pain, kinesiophobia) factors were included as the predictors of interest. The phenotypes were pain intensity (5-day average and peak reported on numerical rating scale), upper-extremity disability (5-day average and peak reported on the QuickDASH instrument), and duration of shoulder pain (in days). Results After controlling for age, sex, and race, the genetic and psychological predictors were entered separately as main effects and interaction terms in regression models for each pain phenotype. Results from the recruited cohort (n = 190) indicated strong statistical evidence for the interactions between 1) TNF/LTA SNP rs2229094 and depressive symptoms for average pain intensity and duration and 2) IL1B two-SNP diplotype and kinesiophobia for average shoulder pain intensity. Moderate statistical evidence for prediction of additional shoulder pain phenotypes included interactions of kinesiophobia, fear of pain, or depressive symptoms with TNF/LTA rs2229094 and IL1B. Conclusion These findings support the combined predictive ability of specific genetic and psychological factors for shoulder pain phenotypes by revealing novel combinations that may merit further investigation in clinical cohorts, to determine their involvement in the transition from acute to chronic pain conditions. PMID:24598699
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Hsueh, Yi-Ping
2012-03-26
Both Neurofibromatosis type I (NF1) and inclusion body myopathy with Paget's disease of bone and frontotemporal dementia (IBMPFD) are autosomal dominant genetic disorders. These two diseases are fully penetrant but with high heterogeneity in phenotypes, suggesting the involvement of genetic modifiers in modulating patients' phenotypes. Although NF1 is recognized as a developmental disorder and IBMPFD is associated with degeneration of multiple tissues, a recent study discovered the direct protein interaction between neurofibromin, the protein product of the NF1 gene, and VCP/p97, encoded by the causative gene of IBMPFD. Both NF1 and VCP/p97 are critical for dendritic spine formation, which provides the cellular mechanism explaining the cognitive deficits and dementia found in patients. Moreover, disruption of the interaction between neurofibromin and VCP impairs dendritic spinogenesis. Neurofibromin likely influences multiple downstream pathways to control dendritic spinogenesis. One is to activate the protein kinase A pathway to initiate dendritic spine formation; another is to regulate the synaptic distribution of VCP and control the activity of VCP in dendritic spinogenesis. Since neurofibromin and VCP/p97 also regulate cell growth and bone metabolism, the understanding of neurofibromin and VCP/p97 in neurons may be applied to study of cancer and bone. Statin treatment rescues the spine defects caused by VCP deficiency, suggesting the potential role of statin in clinical treatment for these two diseases.
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Taylor, E B; McPhail, J D
2000-01-01
Historical contingency and determinism are often cast as opposing paradigms under which evolutionary diversification operates. It may be, however, that both factors act together to promote evolutionary divergence, although there are few examples of such interaction in nature. We tested phylogenetic predictions of an explicit historical model of divergence (double invasions of freshwater by marine ancestors) in sympatric species of three-spined sticklebacks (Gasterosteus aculeatus) where determinism has been implicated as an important factor driving evolutionary novelty. Microsatellite DNA variation at six loci revealed relatively low genetic variation in freshwater populations, supporting the hypothesis that they were derived by colonization of freshwater by more diverse marine ancestors. Phylogenetic and genetic distance analyses suggested that pairs of sympatric species have evolved multiple times, further implicating determinism as a factor in speciation. Our data also supported predictions based on the hypothesis that the evolution of sympatric species was contingent upon 'double invasions' of postglacial lakes by ancestral marine sticklebacks. Sympatric sticklebacks, therefore, provide an example of adaptive radiation by determinism contingent upon historical conditions promoting unique ecological interactions, and illustrate how contingency and determinism may interact to generate geographical variation in species diversity PMID:11133026
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Arsenic exposure assists ccm3 genetic polymorphism in elevating blood pressure
Liu, Xinxia; Xing, Xiumei; Zhang, Huimin; Yun, Jianpei; Ou, Xiaoyan; Su, Xiaolin; Lu, Yao; Sun, Yi; Yang, Yarui; Jiang, Jun; Cui, Dong; Zhuang, Zhixiong; He, Yun
2018-01-01
Epidemiologic study has suggested that arsenic exposure is positively related to increased blood pressure. However, the underlying mechanism concerning interaction between genetic polymorphisms and arsenic exposure remains unclear. In present study, within 395 Chinese, the effects of interaction between arsenic exposure and CCM3 gene polymorphisms on elevation of blood pressure were probed by multiple Logistic regression models after adjusting for confounding factors. Firstly, we found that serum arsenic was positively associated with blood pressure, cholesterol, glucose and C-reactive protein. Then, adjusted for confounding factors of age, gender, smoking, alcohol consumption, BMI and degree of education, arsenic exposure incurred the hazard of increased systolic pressure and diastolic pressure, with odds ratios (ORs) being 1.725 and 1.425, respectively. Distinctly, we found that interactions between rs3804610* rs9818496, rs6784267*rs9818496, and rs3804610* rs6784267 variant genotype can increase significantly risks of SBP. Additionally, interactions between rs9818496, rs3804610 and rs6784267 genotypic variantions and arsenic exposure boosted the hazard of increased systolic pressure, with ORs being 1.496, 1.496 and 1.312. In conclusion, our fingdings suggest that As exposure of population can assist CCM3 polymorphism in elevating SBP. PMID:29435151
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Type 2 diabetes susceptibility genes on chromosome 1q21-24.
Hasstedt, S J; Chu, W S; Das, S K; Wang, H; Elbein, S C
2008-03-01
Type 2 diabetes (T2D) has been linked to chromosome 1q21-24 in multiple samples, including a Utah family sample. Variants in 13 of the numerous candidate genes in the 1q region were tested for association with T2D in a Utah case-control sample. The most promising, 19 variants in 6 candidates, were genotyped on the Utah family sample. Herein, we tested the 19 variants individually and in pairs for an effect on T2D risk in family members using a logistic regression model that accounted for gender, age, and BMI and attributed residual genetic effects to a polygenic component. Seven variants increased risk significantly through 5 pairs of interactions. The significant variant pairs were apolipoprotein A-II (APOA2) rs6413453 interacting with calsequestrin 1 (CASQ1) rs617698, dual specificity phosphatase 12 (DUSP12) rs1503814, and retinoid X receptor gamma (RXRG) rs10918169, a poly-T insertion-deletion polymorphism in liver pyruvate kinase (PKLR) interacting with APOA2 rs12143180, and DUSP12 rs1027702 interacting with RXRG rs10918169. Genotypes of these 5 variant pairs accounted for 25.8% of the genetic variance in T2D in these pedigrees.
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Janzen, F. J.
1992-01-01
The magnitude of quantitative genetic variation for primary sex ratio was measured in families extracted from a natural population of the common snapping turtle (Chelydra serpentina), which possesses temperature-dependent sex determination (TSD). Eggs were incubated at three temperatures that produced mixed sex ratios. This experimental design provided estimates of the heritability of sex ratio in multiple environments and a test of the hypothesis that genotype X environment (G X E) interactions may be maintaining genetic variation for sex ratio in this population of C. serpentina. Substantial quantitative genetic variation for primary sex ratio was detected in all experimental treatments. These results in conjunction with the occurrence of TSD in this species provide support for three critical assumptions of Fisher's theory for the microevolution of sex ratio. There were statistically significant effects of family and incubation temperature on sex ratio, but no significant interaction was observed. Estimates of the genetic correlations of sex ratio across environments were highly positive and essentially indistinguishable from +1. These latter two findings suggest that G X E interaction is not the mechanism maintaining genetic variation for sex ratio in this system. Finally, although substantial heritable variation exists for primary sex ratio of C. serpentina under constant temperatures, estimates of the effective heritability of primary sex ratio in nature are approximately an order of magnitude smaller. Small effective heritability and a long generation time in C. serpentina imply that evolution of sex ratios would be slow even in response to strong selection by, among other potential agents, any rapid and/or substantial shifts in local temperatures, including those produced by changes in the global climate. PMID:1592234
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Awareness of Cancer Susceptibility Genetic Testing
Mai, Phuong L.; Vadaparampil, Susan Thomas; Breen, Nancy; McNeel, Timothy S.; Wideroff, Louise; Graubard, Barry I.
2014-01-01
Background Genetic testing for several cancer susceptibility syndromes is clinically available; however, existing data suggest limited population awareness of such tests. Purpose To examine awareness regarding cancer genetic testing in the U.S. population aged ≥25 years in the 2000, 2005, and 2010 National Health Interview Surveys. Methods The weighted percentages of respondents aware of cancer genetic tests, and percent changes from 2000–2005 and 2005–2010, overall and by demographic, family history, and healthcare factors were calculated. Interactions were used to evaluate the patterns of change in awareness between 2005 and 2010 among subgroups within each factor. To evaluate associations with awareness in 2005 and 2010, percentages were adjusted for covariates using multiple logistic regression. The analysis was performed in 2012. Results Awareness decreased from 44.4% to 41.5% (p<0.001) between 2000 and 2005, and increased to 47.0% (p<0.001) in 2010. Awareness increased between 2005 and 2010 in most subgroups, particularly among individuals in the South (p-interaction=0.03) or with a usual place of care (p-interaction=0.01). In 2005 and 2010, awareness was positively associated with personal or family cancer history and high perceived cancer risk, and inversely associated with racial/ethnic minorities, age 25–39 or ≥60 years, male gender, lower education and income levels, public or no health insurance, and no provider contact in 12 months. Conclusions Despite improvement from 2005 to 2010, ≤50% of the U.S. adult population was aware of cancer genetic testing in 2010. Notably, disparities persist for racial/ethnic minorities and individuals with limited health care access or income. PMID:24745633
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2011-01-01
Background Somatotropinoma, a pituitary adenoma characterised by excessive production of growth hormone (GH), is extremely rare in childhood. A genetic defect is evident in some cases; known genetic changes include: multiple endocrine neoplasia type 1 (MEN1); Carney complex; McCune-Albright syndrome; and, more recently identified, aryl hydrocarbon receptor-interacting protein (AIP). We describe seven children with somatotropinoma with a special focus on the differences between genetic and sporadic forms. Methods Seven children who presented in our regional network between 1992 and 2008 were included in this retrospective analysis. First-type therapy was somatostatin (SMS) analogues or transsphenoidal surgery. Control was defined as when insulin-like growth factor-1 (IGF-1) levels were within the normal range for the patient's age at 6 months after therapy, associated with decreasing tumour volume. Results Patients were aged 5-17 years and the majority (n = 6) were male. Four patients had an identified genetic mutation (McCune-Albright syndrome: n = 1; MEN1: n = 1; AIP: n = 2); the remaining three cases were sporadic. Accelerated growth rate was reported as the first clinical sign in four patients. Five patients presented with macroadenoma; invasion was noted in four of them (sporadic: n = 1; genetic: n = 3). Six patients were treated with SMS analogues; normalisation of IGF-1 occurred in one patient who had a sporadic intrasellar macroadenoma. Multiple types of therapy were necessary in all patients with an identified genetic mutation (4 types: n = 1; 3 types: n = 2; 2 types: n = 1), whereas two of the three patients with sporadic somatotropinoma required only one type of therapy. Conclusions This is the first series that analyzes the therapeutic response of somatotropinoma in paediatric patients with identified genetic defects. We found that, in children, genetic somatotropinomas are more invasive than sporadic somatotropinomas. Furthermore, SMS analogues appear to be less effective for treating genetic somatotropinoma than sporadic somatotropinoma. PMID:22024364
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Hughes, Travis; Adler, Adam; Kelly, Jennifer A; Kaufman, Kenneth M; Williams, Adrienne H; Langefeld, Carl D; Brown, Elizabeth E; Alarcón, Graciela S; Kimberly, Robert P; Edberg, Jeffrey C; Ramsey-Goldman, Rosalind; Petri, Michelle; Boackle, Susan A; Stevens, Anne M; Reveille, John D; Sanchez, Elena; Martín, Javier; Niewold, Timothy B; Vilá, Luis M; Scofield, R Hal; Gilkeson, Gary S; Gaffney, Patrick M; Criswell, Lindsey A; Moser, Kathy L; Merrill, Joan T; Jacob, Chaim O; Tsao, Betty P; James, Judith A; Vyse, Timothy J; Alarcón-Riquelme, Marta E; Harley, John B; Richardson, Bruce C; Sawalha, Amr H
2012-02-01
Several confirmed genetic susceptibility loci for lupus have been described. To date, no clear evidence for genetic epistasis in lupus has been established. The aim of this study was to test for gene-gene interactions in a number of known lupus susceptibility loci. Eighteen single-nucleotide polymorphisms tagging independent and confirmed lupus susceptibility loci were genotyped in a set of 4,248 patients with lupus and 3,818 normal healthy control subjects of European descent. Epistasis was tested by a 2-step approach using both parametric and nonparametric methods. The false discovery rate (FDR) method was used to correct for multiple testing. We detected and confirmed gene-gene interactions between the HLA region and CTLA4, IRF5, and ITGAM and between PDCD1 and IL21 in patients with lupus. The most significant interaction detected by parametric analysis was between rs3131379 in the HLA region and rs231775 in CTLA4 (interaction odds ratio 1.19, Z = 3.95, P = 7.8 × 10(-5) [FDR ≤0.05], P for multifactor dimensionality reduction = 5.9 × 10(-45)). Importantly, our data suggest that in patients with lupus, the presence of the HLA lupus risk alleles in rs1270942 and rs3131379 increases the odds of also carrying the lupus risk allele in IRF5 (rs2070197) by 17% and 16%, respectively (P = 0.0028 and P = 0.0047, respectively). We provide evidence for gene-gene epistasis in systemic lupus erythematosus. These findings support a role for genetic interaction contributing to the complexity of lupus heritability. Copyright © 2012 by the American College of Rheumatology.
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Levallois, Patrick; Giguère, Yves; Nguile-Makao, Molière; Rodriguez, Manuel; Campagna, Céline; Tardif, Robert; Bureau, Alexandre
2016-01-01
Exposure to disinfection by-products (DBPs) during pregnancy was associated with reduced foetal growth. Genetic susceptibility might play a role, especially for genes encoding for the Cytochrome P450 (CYP2E1) and Glutathione S-Transferase (GST) enzymes, involved in metabolism and activation of DBPs. Few epidemiological studies evaluated these gene-environment interactions and their results were never replicated. This study aims to examine interactions between trihalomethanes (THM) or haloacetic acids (HAA) exposure and genetic polymorphisms on small for gestational age (SGA) neonates by investigating single nucleotide polymorphisms (SNPs) in CYP2E1 gene and GSTM1 and GSTT1 deletions in mothers-children pairs. A population-based case-control study of 1549 mothers and 1455 children was conducted on SGA and THM/HAA exposure. DNA was extracted from blood or saliva cells. Targeted SNPs and deletions were genotyped. Statistical interaction between SNPs/deletions and THMs or HAAs in utero exposure with regard to SGA occurrence was evaluated by unconditional logistic regression with control of potential confounders. Previously reported positive modification of the effect of THM uterine exposure by mothers or newborns CYP2E1 rs3813867 C allele or GSTM1 deletion was not replicated. However interactions with CYP2E1 rs117618383 and rs2515641 were observed but were not statistically significant after correction for multiple testing. Previous positive interactions between THMs exposure and CYP2E1 and GSTM1 were not replicated but interactions with other CYP2E1 polymorphisms are reported. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Levallois, Patrick; Giguère, Yves; Nguile-Makao, Molière; Rodriguez, Manuel; Campagna, Céline; Tardif, Robert; Bureau, Alexandre
2016-01-01
Background Exposure to disinfection by-products (DBPs) during pregnancy was associated with reduced fetal growth. Genetic susceptibility might play a role, especially for genes encoding for the Cytochrome P450 (CYP2E1) and Glutathione S-Transferase (GST) enzymes, involved in metabolism and activation of DBPs. Few epidemiological studies evaluated these gene-environment interactions and their results were never replicated. Objective This study aims to examine interactions between trihalomethanes (THM) or haloacetic acids (HAA) exposure and genetic polymorphisms on small for gestational age (SGA) neonates by investigating single nucleotide polymorphisms (SNPs) in CYP2E1 gene and GSTM1 and GSTT1 deletions in mothers-children pairs. Methods A population-based case-control study of 1549 mothers and 1455 children was conducted on SGA and THM/HAA exposure. DNA was extracted from blood or saliva cells. Targeted SNPs and deletions were genotyped. Statistical interaction between SNPs/deletions and THMs or HAAs in utero exposure with regard to SGA occurrence was evaluated by unconditional logistic regression with control of potential confounders. Results Previously reported positive modification of the effect of THM uterine exposure by mothers or newborns CYP2E1 rs3813867 C allele or GSTM1 deletion was not replicated. However interactions with CYP2E1 rs117618383 and rs2515641 were observed but were not statistically significant after correction for multiple testing. Conclusions Previous positive interactions between THMs exposure and CYP2E1 and GSTM1 were not replicated but interactions with other CYP2E1 polymorphisms are reported. PMID:27107227
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ERIC Educational Resources Information Center
Buckley, Barbara C.; Gobert, Janice D.; Kindfield, Ann C. H.; Horwitz, Paul; Tinker, Robert F.; Gerlits, Bobbi; Wilensky, Uri; Dede, Chris; Willett, John
2004-01-01
This paper describes part of a project called Modeling Across the Curriculum which is a large-scale research study in 15 schools across the United States. The specific data presented and discussed here in this paper is based on BioLogica, a hypermodel, interactive environment for learning genetics, which was implemented in multiple classes in…
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Li, Tongchao; Giagtzoglou, Nikolaos; Eberl, Daniel F; Jaiswal, Sonal Nagarkar; Cai, Tiantian; Godt, Dorothea; Groves, Andrew K; Bellen, Hugo J
2016-01-01
Myosins play essential roles in the development and function of auditory organs and multiple myosin genes are associated with hereditary forms of deafness. Using a forward genetic screen in Drosophila, we identified an E3 ligase, Ubr3, as an essential gene for auditory organ development. Ubr3 negatively regulates the mono-ubiquitination of non-muscle Myosin II, a protein associated with hearing loss in humans. The mono-ubiquitination of Myosin II promotes its physical interaction with Myosin VIIa, a protein responsible for Usher syndrome type IB. We show that ubr3 mutants phenocopy pathogenic variants of Myosin II and that Ubr3 interacts genetically and physically with three Usher syndrome proteins. The interactions between Myosin VIIa and Myosin IIa are conserved in the mammalian cochlea and in human retinal pigment epithelium cells. Our work reveals a novel mechanism that regulates protein complexes affected in two forms of syndromic deafness and suggests a molecular function for Myosin IIa in auditory organs. DOI: http://dx.doi.org/10.7554/eLife.15258.001 PMID:27331610
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Population Genetics of Plasmodium vivax in Four Rural Communities in Central Vietnam
Hong, Nguyen Van; Delgado-Ratto, Christopher; Thanh, Pham Vinh; Van den Eede, Peter; Guetens, Pieter; Binh, Nguyen Thi Huong; Phuc, Bui Quang; Duong, Tran Thanh; Van Geertruyden, Jean Pierre; D’Alessandro, Umberto; Erhart, Annette; Rosanas-Urgell, Anna
2016-01-01
Background The burden of malaria in Vietnam has drastically reduced, prompting the National Malaria Control Program to officially engage in elimination efforts. Plasmodium vivax is becoming increasingly prevalent, remaining a major problem in the country's central and southern provinces. A better understanding of P. vivax genetic diversity and structure of local parasite populations will provide baseline data for the evaluation and improvement of current efforts for control and elimination. The aim of this study was to examine the population genetics and structure of P. vivax isolates from four communities in Tra Leng commune, Nam Tra My district in Quang Nam, Central Vietnam. Methodology/Principal Findings P. vivax mono infections collected from 234 individuals between April 2009 and December 2010 were successfully analyzed using a panel of 14 microsatellite markers. Isolates displayed moderate genetic diversity (He = 0.68), with no significant differences between study communities. Polyclonal infections were frequent (71.4%) with a mean multiplicity of infection of 1.91 isolates/person. Low but significant genetic differentiation (FST value from -0.05 to 0.18) was observed between the community across the river and the other communities. Strong linkage disequilibrium (IAS = 0.113, p < 0.001) was detected across all communities, suggesting gene flow within and among them. Using multiple approaches, 101 haplotypes were grouped into two genetic clusters, while 60.4% of haplotypes were admixed. Conclusions/Significance In this area of Central Vietnam, where malaria transmission has decreased significantly over the past decade, there was moderate genetic diversity and high occurrence of polyclonal infections. Local human populations have frequent social and economic interactions that facilitate gene flow and inbreeding among parasite populations, while decreasing population structure. Findings provide important information on parasites populations circulating in the study area and are relevant to current malaria elimination efforts. PMID:26872387
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Decoding the non-coding genome: elucidating genetic risk outside the coding genome.
Barr, C L; Misener, V L
2016-01-01
Current evidence emerging from genome-wide association studies indicates that the genetic underpinnings of complex traits are likely attributable to genetic variation that changes gene expression, rather than (or in combination with) variation that changes protein-coding sequences. This is particularly compelling with respect to psychiatric disorders, as genetic changes in regulatory regions may result in differential transcriptional responses to developmental cues and environmental/psychosocial stressors. Until recently, however, the link between transcriptional regulation and psychiatric genetic risk has been understudied. Multiple obstacles have contributed to the paucity of research in this area, including challenges in identifying the positions of remote (distal from the promoter) regulatory elements (e.g. enhancers) and their target genes and the underrepresentation of neural cell types and brain tissues in epigenome projects - the availability of high-quality brain tissues for epigenetic and transcriptome profiling, particularly for the adolescent and developing brain, has been limited. Further challenges have arisen in the prediction and testing of the functional impact of DNA variation with respect to multiple aspects of transcriptional control, including regulatory-element interaction (e.g. between enhancers and promoters), transcription factor binding and DNA methylation. Further, the brain has uncommon DNA-methylation marks with unique genomic distributions not found in other tissues - current evidence suggests the involvement of non-CG methylation and 5-hydroxymethylation in neurodevelopmental processes but much remains unknown. We review here knowledge gaps as well as both technological and resource obstacles that will need to be overcome in order to elucidate the involvement of brain-relevant gene-regulatory variants in genetic risk for psychiatric disorders. © 2015 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.
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Schinasi, Leah H; Brown, Elizabeth E; Camp, Nicola J; Wang, Sophia S; Hofmann, Jonathan N; Chiu, Brian C; Miligi, Lucia; Beane Freeman, Laura E; de Sanjose, Silvia; Bernstein, Leslie; Monnereau, Alain; Clavel, Jacqueline; Tricot, Guido J; Atanackovic, Djordje; Cocco, Pierluigi; Orsi, Laurent; Dosman, James A; McLaughlin, John R; Purdue, Mark P; Cozen, Wendy; Spinelli, John J; de Roos, Anneclaire J
2016-10-01
Family clusters of multiple myeloma (MM) suggest disease heritability. Nevertheless, patterns of inheritance and the importance of genetic versus environmental risk factors in MM aetiology remain unclear. We pooled data from eleven case-control studies from the International Multiple Myeloma Consortium to characterize the association of MM risk with having a first-degree relative with a history of a lympho-haematapoietic cancer. Unconditional logistic regression models, adjusted for study, sex, age and education level, were used to estimate associations between MM risk and having a first-degree relative with a history of non-Hodgkin lymphoma, Hodgkin lymphoma, leukaemia or MM. Sex, African American race/ethnicity and age were explored as effect modifiers. A total of 2843 cases and 11 470 controls were included. MM risk was elevated in association with having a first-degree relative with any lympho-haematapoietic cancer (Odds Ratio (OR) = 1·29, 95% Confidence Interval (CI): 1·08-1·55). The association was particularly strong for having a first-degree relative with MM (OR = 1·90, 95% CI: 1·26-2·87), especially among men (OR = 4·13, 95% CI: 2·17-7·85) and African Americans (OR = 5·52, 95% CI: 1·87-16·27).These results support the hypothesis that genetic inheritance plays a role in MM aetiology. Future studies are warranted to characterize interactions of genetic markers with environmental exposures. © 2016 John Wiley & Sons Ltd.
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Clarke, John D; Cherrington, Nathan J
2012-03-01
Organic anion transporting polypeptide (OATP) uptake transporters are important for the disposition of many drugs and perturbed OATP activity can contribute to adverse drug reactions (ADRs). It is well documented that both genetic and environmental factors can alter OATP expression and activity. Genetic factors include single nucleotide polymorphisms (SNPs) that change OATP activity and epigenetic regulation that modify OATP expression levels. SNPs in OATPs contribute to ADRs. Environmental factors include the pharmacological context of drug-drug interactions and the physiological context of liver diseases. Liver diseases such as non-alcoholic fatty liver disease, cholestasis and hepatocellular carcinoma change the expression of multiple OATP isoforms. The role of liver diseases in the occurrence of ADRs is unknown. This article covers the roles OATPs play in ADRs when considered in the context of genetic or environmental factors. The reader will gain a greater appreciation for the current evidence regarding the salience and importance of each factor in OATP-mediated ADRs. A SNP in a single OATP transporter can cause changes in drug pharmacokinetics and contribute to ADRs but, because of overlap in substrate specificities, there is potential for compensatory transport by other OATP isoforms. By contrast, the expression of multiple OATP isoforms is decreased in liver diseases, reducing compensatory transport and thereby increasing the probability of ADRs. To date, most research has focused on the genetic factors in OATP-mediated ADRs while the impact of environmental factors has largely been ignored.
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Genomic Selection in Multi-environment Crop Trials.
Oakey, Helena; Cullis, Brian; Thompson, Robin; Comadran, Jordi; Halpin, Claire; Waugh, Robbie
2016-05-03
Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and nonmarker residual genetic variation (i.e., additive and nonadditive effects). This results in a more precise estimate of marker genetic effects. Using barley height data from trials, in 2 different years, of up to 477 cultivars, we demonstrate that our new genomic selection model improves predictions compared to current models. Analyzing single trials revealed improvements in predictive ability of up to 5.7%. For the multiple environment trial (MET) model, combining both year trials improved predictive ability up to 11.4% compared to a single environment analysis. Benefits were significant even when fewer markers were used. Compared to a single-year standard model run with 3490 markers, our partitioned MET model achieved the same predictive ability using between 500 and 1000 markers depending on the trial. Our approach can be used to increase accuracy and confidence in the selection of the best lines for breeding and/or, to reduce costs by using fewer markers. Copyright © 2016 Oakey et al.
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Communicating Genetic Risk Information for Common Disorders in the Era of Genomic Medicine
Lautenbach, Denise M.; Christensen, Kurt D.; Sparks, Jeffrey A.; Green, Robert C.
2013-01-01
Communicating genetic risk information in ways that maximize understanding and promote health is increasingly important given the rapidly expanding availability and capabilities of genomic technologies. A well-developed literature on risk communication in general provides guidance for best practices, including presentation of information in multiple formats, attention to framing effects, use of graphics, sensitivity to the way numbers are presented, parsimony of information, attentiveness to emotions, and interactivity as part of the communication process. Challenges to communicating genetic risk information include deciding how best to tailor it, streamlining the process, deciding what information to disclose, accepting that communications may have limited influence, and understanding the impact of context. Meeting these challenges has great potential for empowering individuals to adopt healthier lifestyles and improve public health, but will require multidisciplinary approaches and collaboration. PMID:24003856
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Recombination Promoted by DNA Viruses: Phage λ to Herpes Simplex Virus
Weller, Sandra K.; Sawitzke, James A.
2015-01-01
The purpose of this review is to explore recombination strategies in DNA viruses. Homologous recombination is a universal genetic process that plays multiple roles in the biology of all organisms, including viruses. Recombination and DNA replication are interconnected, with recombination being essential for repairing DNA damage and supporting replication of the viral genome. Recombination also creates genetic diversity, and viral recombination mechanisms have important implications for understanding viral origins as well as the dynamic nature of viral-host interactions. Both bacteriophage λ and herpes simplex virus (HSV) display high rates of recombination, both utilizing their own proteins and commandeering cellular proteins to promote recombination reactions. We focus primarily on λ and HSV, as they have proven amenable to both genetic and biochemical analysis and have recently been shown to exhibit some surprising similarities that will guide future studies. PMID:25002096
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de la Fuente, José; Antunes, Sandra; Bonnet, Sarah; Cabezas-Cruz, Alejandro; Domingos, Ana G.; Estrada-Peña, Agustín; Johnson, Nicholas; Kocan, Katherine M.; Mansfield, Karen L.; Nijhof, Ard M.; Papa, Anna; Rudenko, Nataliia; Villar, Margarita; Alberdi, Pilar; Torina, Alessandra; Ayllón, Nieves; Vancova, Marie; Golovchenko, Maryna; Grubhoffer, Libor; Caracappa, Santo; Fooks, Anthony R.; Gortazar, Christian; Rego, Ryan O. M.
2017-01-01
Ticks and the pathogens they transmit constitute a growing burden for human and animal health worldwide. Vector competence is a component of vectorial capacity and depends on genetic determinants affecting the ability of a vector to transmit a pathogen. These determinants affect traits such as tick-host-pathogen and susceptibility to pathogen infection. Therefore, the elucidation of the mechanisms involved in tick-pathogen interactions that affect vector competence is essential for the identification of molecular drivers for tick-borne diseases. In this review, we provide a comprehensive overview of tick-pathogen molecular interactions for bacteria, viruses, and protozoa affecting human and animal health. Additionally, the impact of tick microbiome on these interactions was considered. Results show that different pathogens evolved similar strategies such as manipulation of the immune response to infect vectors and facilitate multiplication and transmission. Furthermore, some of these strategies may be used by pathogens to infect both tick and mammalian hosts. Identification of interactions that promote tick survival, spread, and pathogen transmission provides the opportunity to disrupt these interactions and lead to a reduction in tick burden and the prevalence of tick-borne diseases. Targeting some of the similar mechanisms used by the pathogens for infection and transmission by ticks may assist in development of preventative strategies against multiple tick-borne diseases. PMID:28439499
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McBride, Colleen M; Alford, Sharon Hensley; Reid, Robert J; Larson, Eric B; Baxevanis, Andreas D; Brody, Lawrence C
2009-08-01
To evaluate what psychological and behavioral factors predict who is likely to seek SNP-based genetic tests for multiple common health conditions where feedback can be used to motivate primary prevention. Adults aged 25-40 years who were enrolled in a large managed care organization were surveyed. Those eligible could log on to a secure study Web site to review information about the risks and benefits of a SNP-based genetic test and request free testing. Two primary outcomes are addressed: accessing the Web (yes or no) and deciding to be tested (completed a blood draw at the clinic) Those considering genetic susceptibility testing did not hold genetically deterministic beliefs (0.42 on scale of 0 [behavior] to 1 [genetic]) but believed genetic information to be valuable and were confident they could understand such information. Individuals who believed it important to learn about genetics (odds ratio = 1.28), were confident they could understand genetics (odds ratio = 1.26), and reported the most health habits to change (odds ratio = 1.39) were most likely to get tested. Individuals who present to health care providers with online genetics information may be among the most motivated to take steps toward healthier lifestyles. These motives might be leveraged by health care providers to promote positive health outcomes.
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Contribution of vitamin D insufficiency to the pathogenesis of multiple sclerosis
Souberbielle, Jean-Claude
2013-01-01
The contribution of vitamin D insufficiency to the pathogenesis of multiple sclerosis (MS) is reviewed. Among the multiple recently discovered actions of vitamin D, an immunomodulatory role has been documented in experimental autoimmune encephalomyelitis and in humans. This action in the peripheral immune system is currently the main known mechanism through which vitamin D might influence MS, but other types of actions could be involved within the central nervous system. Furthermore, vitamin D insufficiency is widespread in temperate countries and in patients with MS at the earliest stages of the disease, suggesting that the deleterious effects related to vitamin D insufficiency may be exerted in these patients. In fact, many genetic and environmental risk factors appear to interact and contribute to MS. In genetics, several human leukocyte antigen (HLA) alleles (more particularly HLA-DRB1*1501) could favour the disease whereas some others could be protective. Some of the genes involved in vitamin D metabolism (e.g. CYP27B1) also play a significant role. Furthermore, three environmental risk factors have been identified: past Epstein–Barr virus infection, vitamin D insufficiency and cigarette smoking. Interactions between genetic and environmental risk or protective factors may occur during the mother’s pregnancy and could continue during childhood and adolescence and until the disease is triggered in adulthood, therefore possibly modulating the MS risk throughout the first decades of life. Furthermore, some clinical findings already strongly suggest that vitamin D status influences the relapse rate and radiological lesions in patients with MS, although the results of adequately powered randomized clinical trials using vitamin D supplementation have not yet been reported. While awaiting these incontrovertible results, which might be long in coming, patients with MS who are currently in vitamin D insufficiency should be supplemented, at least for their general health status, using moderate doses of the vitamin. PMID:23483715
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Mikuls, Ted R.; LeVan, Tricia; Gould, Karen A.; Yu, Fang; Thiele, Geoffrey M.; Bynote, Kimberly K.; Conn, Doyt; Jonas, Beth L.; Callahan, Leigh F.; Smith, Edwin; Brasington, Richard; Moreland, Larry W.; Reynolds, Richard; Gaffo, Angelo; Bridges, S. Louis
2011-01-01
Objective To examine whether polymorphisms in genes coding for drug metabolizing enzymes (DMEs) impact rheumatoid arthritis (RA) risk due to cigarette smoking in African Americans. Methods Smoking status was evaluated in African American RA cases and non-RA controls categorized as heavy (≥ 10 pack-years) vs. other. Individuals were genotyped for a homozygous deletion polymorphism in glutathione S-transferase Mu-1 (GSTM1-null) in addition to tagging single nucleotide polymorphisms (SNPs) in N-acetyltransferase (NAT)1, NAT2, and epoxide hydrolase (EPXH1). Associations of genotypes with RA were examined using logistic regression and gene-smoking interactions were assessed. Results There were no significant associations of any DME genotype with RA. After adjustment for multiple comparisons, there were significant additive interactions between heavy smoking and NAT2 SNPs rs9987109 (Padd = 0.000003) and rs1208 (Padd = 0.00001); attributable proportions (APs) due to interaction ranged from 0.61 to 0.67. None of the multiplicative gene-smoking interactions examined remained significant after adjustment for multiple testing in overall disease risk. There was no evidence of significant gene-smoking interactions in analyses of GSTM1-null, NAT1, or EPXH1. DME gene-smoking interactions were similar when cases were limited to anti-citrullinated protein antibody (ACPA) positive individuals. Conclusion Among African Americans, RA risk imposed by heavy smoking appears to be mediated in part by genetic variation in NAT2. While further studies are needed to elucidate mechanisms underpinning these interactions, these SNPs appear to identify African American smokers at a much higher risk for RA with relative risks that are at least two-fold higher compared to non-smokers lacking these risk alleles. PMID:21989592
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Luo, Xingguang; Zuo, Lingjun; Kranzler, Henry; Zhang, Huiping; Wang, Shuang; Gelernter, Joel
2011-01-01
Background Personality traits are among the most complex quantitative traits. Certain personality traits are associated with substance dependence (SD); genetic factors may influence both. Associations between opioid receptor (OPR) genes and SD have been reported. This study investigated the relationship between OPR genes and personality traits in a case-control sample. Methods We assessed dimensions of the five-factor model of personality in 556 subjects: 250 with SD [181 European-Americans (EAs) and 69 African-Americans (AAs)] and 306 healthy subjects (266 EAs and 40 AAs). We genotyped 20 OPRM1 markers, 8 OPRD1 markers, and 7 OPRK1 markers, and 38 unlinked ancestry-informative markers in these subjects. The relationships between OPR genes and personality traits were examined using MANCOVA, controlling for gene-gene interaction effects and potential confounders. Associations were decomposed by Roy-Bargmann Stepdown ANCOVA. Results Personality traits were associated as main or interaction effects with the haplotypes, diplotypes, alleles and genotypes at the three OPR genes (0.002
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Olsson, Anders H.; Volkov, Petr; Bacos, Karl; Dayeh, Tasnim; Hall, Elin; Nilsson, Emma A.; Ladenvall, Claes; Rönn, Tina; Ling, Charlotte
2014-01-01
Genetic and epigenetic mechanisms may interact and together affect biological processes and disease development. However, most previous studies have investigated genetic and epigenetic mechanisms independently, and studies examining their interactions throughout the human genome are lacking. To identify genetic loci that interact with the epigenome, we performed the first genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human pancreatic islets. We related 574,553 single nucleotide polymorphisms (SNPs) with genome-wide DNA methylation data of 468,787 CpG sites targeting 99% of RefSeq genes in islets from 89 donors. We identified 67,438 SNP-CpG pairs in cis, corresponding to 36,783 SNPs (6.4% of tested SNPs) and 11,735 CpG sites (2.5% of tested CpGs), and 2,562 significant SNP-CpG pairs in trans, corresponding to 1,465 SNPs (0.3% of tested SNPs) and 383 CpG sites (0.08% of tested CpGs), showing significant associations after correction for multiple testing. These include reported diabetes loci, e.g. ADCY5, KCNJ11, HLA-DQA1, INS, PDX1 and GRB10. CpGs of significant cis-mQTLs were overrepresented in the gene body and outside of CpG islands. Follow-up analyses further identified mQTLs associated with gene expression and insulin secretion in human islets. Causal inference test (CIT) identified SNP-CpG pairs where DNA methylation in human islets is the potential mediator of the genetic association with gene expression or insulin secretion. Functional analyses further demonstrated that identified candidate genes (GPX7, GSTT1 and SNX19) directly affect key biological processes such as proliferation and apoptosis in pancreatic β-cells. Finally, we found direct correlations between DNA methylation of 22,773 (4.9%) CpGs with mRNA expression of 4,876 genes, where 90% of the correlations were negative when CpGs were located in the region surrounding transcription start site. Our study demonstrates for the first time how genome-wide genetic and epigenetic variation interacts to influence gene expression, islet function and potential diabetes risk in humans. PMID:25375650
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Khramtsova, Ekaterina A; Stranger, Barbara E
2017-02-01
Over the last decade, genome-wide association studies (GWAS) have generated vast amounts of analysis results, requiring development of novel tools for data visualization. Quantile–quantile (QQ) plots and Manhattan plots are classical tools which have been utilized to visually summarize GWAS results and identify genetic variants significantly associated with traits of interest. However, static visualizations are limiting in the information that can be shown. Here, we present Assocplots, a Python package for viewing and exploring GWAS results not only using classic static Manhattan and QQ plots, but also through a dynamic extension which allows to interactively visualize the relationships between GWAS results from multiple cohorts or studies. The Assocplots package is open source and distributed under the MIT license via GitHub (https://github.com/khramts/assocplots) along with examples, documentation and installation instructions. ekhramts@medicine.bsd.uchicago.edu or bstranger@medicine.bsd.uchicago.edu
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Kling, Teresia; Johansson, Patrik; Sanchez, José; Marinescu, Voichita D.; Jörnsten, Rebecka; Nelander, Sven
2015-01-01
Statistical network modeling techniques are increasingly important tools to analyze cancer genomics data. However, current tools and resources are not designed to work across multiple diagnoses and technical platforms, thus limiting their applicability to comprehensive pan-cancer datasets such as The Cancer Genome Atlas (TCGA). To address this, we describe a new data driven modeling method, based on generalized Sparse Inverse Covariance Selection (SICS). The method integrates genetic, epigenetic and transcriptional data from multiple cancers, to define links that are present in multiple cancers, a subset of cancers, or a single cancer. It is shown to be statistically robust and effective at detecting direct pathway links in data from TCGA. To facilitate interpretation of the results, we introduce a publicly accessible tool (cancerlandscapes.org), in which the derived networks are explored as interactive web content, linked to several pathway and pharmacological databases. To evaluate the performance of the method, we constructed a model for eight TCGA cancers, using data from 3900 patients. The model rediscovered known mechanisms and contained interesting predictions. Possible applications include prediction of regulatory relationships, comparison of network modules across multiple forms of cancer and identification of drug targets. PMID:25953855
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Xu, Rong; Wang, QuanQiu; Li, Li
2015-01-01
Dietary intakes of red meat and fat are established risk factors for both colorectal cancer (CRC) and cardiovascular disease (CVDs). Recent studies have shown a mechanistic link between TMAO, an intestinal microbial metabolite of red meat and fat, and risk of CVDs. Data linking TMAO directly to CRC is, however, lacking. Here, we present an unbiased data-driven network-based systems approach to uncover a potential genetic relationship between TMAO and CRC. We constructed two different epigenetic interaction networks (EINs) using chemical-gene, disease-gene and protein-protein interaction data from multiple large-scale data resources. We developed a network-based ranking algorithm to ascertain TMAO-related diseases from EINs. We systematically analyzed disease categories among TMAO-related diseases at different ranking cutoffs. We then determined which genetic pathways were associated with both TMAO and CRC. We show that CVDs and their major risk factors were ranked highly among TMAO-related diseases, confirming the newly discovered mechanistic link between CVDs and TMAO, and thus validating our algorithms. CRC was ranked highly among TMAO-related disease retrieved from both EINs (top 0.02%, #1 out of 4,372 diseases retrieved based on Mendelian genetics and top 10.9% among 882 diseases based on genome-wide association genetics), providing strong supporting evidence for our hypothesis that TMAO is genetically related to CRC. We have also identified putative genetic pathways that may link TMAO to CRC, which warrants further investigation. Through systematic disease enrichment analysis, we also demonstrated that TMAO is related to metabolic syndromes and cancers in general. Our genome-wide analysis demonstrates that systems approaches to studying the epigenetic interactions among diet, microbiome metabolisms, and disease genetics hold promise for understanding disease pathogenesis. Our results show that TMAO is genetically associated with CRC. This study suggests that TMAO may be an important intermediate marker linking dietary meat and fat and gut microbiota metabolism to risk of CRC, underscoring opportunities for the development of new gut microbiome-dependent diagnostic tests and therapeutics for CRC.
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Multiple Query Evaluation Based on an Enhanced Genetic Algorithm.
ERIC Educational Resources Information Center
Tamine, Lynda; Chrisment, Claude; Boughanem, Mohand
2003-01-01
Explains the use of genetic algorithms to combine results from multiple query evaluations to improve relevance in information retrieval. Discusses niching techniques, relevance feedback techniques, and evolution heuristics, and compares retrieval results obtained by both genetic multiple query evaluation and classical single query evaluation…
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Chang, Hongjuan; Yan, Qiuge; Tang, Lina; Huang, Juan; Ma, Yuqiao; Ye, Xiaozhou; Wu, Chunxia; Wu, Linguo; Yu, Yizhen
2018-01-01
Genetic predisposition is an important factor leading to aggressive behavior. However, the relationship between genetic polymorphisms and aggressive behavior has not been elucidated. We identified candidate genes located in the dopaminergic and serotonin system (DRD3, DRD4, and FEV) that had been previously reported to be associated with aggressive behavior. We investigated 14 tag single-nucleotide polymorphisms (SNPs) using a multi-analytic strategy combining logistic regression (LR) and classification and regression tree (CART) to explore higher-order interactions between these SNPs and aggressive behavior in 318 patients and 558 controls. Both LR and CART analyses suggested that the rs16859448 polymorphism is the strongest individual factor associated with aggressive behavior risk. In CART analysis, individuals carrying the combined genotypes of rs16859448TT/GT-rs11246228CT/TT-rs3773679TT had the highest risk, while rs16859448GG-rs2134655CT had the lowest risk (OR = 5.25, 95% CI: 2.53-10.86). This study adds to the growing evidence on the association of single- and multiple-risk variants in DRD3, DRD4, and FEV with aggressive behavior in Chinese adolescents. However, the aggressive behavior scale used to diagnose aggression in this study did not account for comorbid conditions; therefore, further studies are needed to confirm our observations. Copyright © 2017 Elsevier B.V. All rights reserved.
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Wise, Michael J; Rausher, Mark D
2013-06-01
Although plants are generally attacked by a community of several species of herbivores, relatively little is known about the strength of natural selection for resistance in multiple-herbivore communities-particularly how the strength of selection differs among herbivores that feed on different plant organs or how strongly genetic correlations in resistance affect the evolutionary responses of the plant. Here, we report on a field study measuring natural selection for resistance in a diverse community of herbivores of Solanum carolinense. Using linear phenotypic-selection analyses, we found that directional selection acted to increase resistance to seven species. Selection was strongest to increase resistance to fruit feeders, followed by flower feeders, then leaf feeders. Selection favored a decrease in resistance to a stem borer. Bootstrapping analyses showed that the plant population contained significant genetic variation for each of 14 measured resistance traits and significant covariances in one-third of the pairwise combinations of resistance traits. These genetic covariances reduced the plant's overall predicted evolutionary response for resistance against the herbivore community by about 60%. Diffuse (co)evolution was widespread in this community, and the diffuse interactions had an overwhelmingly constraining (rather than facilitative) effect on the plant's evolution of resistance. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.
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Distinct genetic profiles in colorectal tumors with or without the CpG island methylator phenotype
Toyota, Minoru; Ohe-Toyota, Mutsumi; Ahuja, Nita; Issa, Jean-Pierre J.
2000-01-01
Colorectal cancers (CRCs) are characterized by multiple genetic (mutations) and epigenetic (CpG island methylation) alterations, but it is not known whether these evolve independently through stochastic processes. We have recently described a novel pathway termed CpG island methylator phenotype (CIMP) in CRC, which is characterized by the simultaneous methylation of multiple CpG islands, including several known genes, such as p16, hMLH1, and THBS1. We have now studied mutations in K-RAS, p53, DPC4, and TGFβRII in a panel of colorectal tumors with or without CIMP. We find that CIMP defines two groups of tumors with significantly different genetic lesions: frequent K-RAS mutations were found in CIMP+ CRCs (28/41, 68%) compared with CIMP− cases (14/47, 30%, P = 0.0005). By contrast, p53 mutations were found in 24% (10/41) of CIMP+ CRCs vs. 60% (30/46) of CIMP− cases (P = 0.002). Both of these differences were independent of microsatellite instability. These interactions between CIMP, K-RAS mutations, and p53 mutations were preserved in colorectal adenomas, suggesting that they occur early in carcinogenesis. The distinct combinations of epigenetic and genetic alterations in each group suggest that activation of oncogenes and inactivation of tumor suppressor genes is related to the underlying mechanism of generating molecular diversity in cancer, rather than simply accumulate stochastically during cancer development. PMID:10639144
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Selection for avian immune response: a commercial breeding company challenge.
Fulton, J E
2004-04-01
Selection for immune function in the commercial breeding environment is a challenging proposition for commercial breeding companies. Immune response is only one of many traits that are under intensive selection, thus selection pressure needs to be carefully balanced across multiple traits. The selection environment (single bird cages, biosecure facilities, controlled environment) is a very different environment than the commercial production facilities (multiple bird cages, potential disease exposure, variable environment) in which birds are to produce. The testing of individual birds is difficult, time consuming, and expensive. It is essential that the results of any tests be relevant to actual disease or environmental challenge in the commercial environment. The use of genetic markers as indicators of immune function is being explored by breeding companies. Use of genetic markers would eliminate many of the limitations in enhancing immune function currently encountered by commercial breeding companies. Information on genetic markers would allow selection to proceed without subjecting breeding stock to disease conditions and could be done before production traits are measured. These markers could be candidate genes with known interaction or involvement with disease pathology or DNA markers that are closely linked to genetic regions that influence the immune response. The current major limitation to this approach is the paucity of mapped chicken immune response genes and the limited number of DNA markers mapped on the chicken genome. These limitations should be eliminated once the chicken genome is sequenced.
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Castro-Santos, Patricia; Díaz-Peña, Roberto
2017-09-01
Most rheumatic diseases are complex or multifactorial entities with pathogeneses that interact with both multiple genetic factors and a high number of diverse environmental factors. Knowledge of the human genome sequence and its diversity among populations has provided a crucial step forward in our understanding of genetic diseases, identifying many genetic loci or genes associated with diverse phenotypes. In general, susceptibility to autoimmunity is associated with multiple risk factors, but the mechanism of the environmental component influence is poorly understood. Studies in twins have demonstrated that genetics do not explain the totality of the pathogenesis of rheumatic diseases. One method of modulating gene expression through environmental effects is via epigenetic modifications. These techniques open a new field for identifying useful new biomarkers and therapeutic targets. In this context, the development of "-omics" techniques is an opportunity to progress in our knowledge of complex diseases, impacting the discovery of new potential biomarkers suitable for their introduction into clinical practice. In this review, we focus on the recent advances in the fields of genomics and epigenomics in rheumatic diseases and their potential to be useful for the diagnosis, follow-up, and treatment of these diseases. The ultimate aim of genomic studies in any human disease is to understand its pathogenesis, thereby enabling the prediction of the evolution of the disease to establish new treatments and address the development of personalized therapies.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Khodayari, Ali; Maranas, Costas D.
Kinetic models of metabolism at a genome scale that faithfully recapitulate the effect of multiple genetic interventions would be transformative in our ability to reliably design novel overproducing microbial strains. Here, we introduce k-ecoli457, a genome-scale kinetic model of Escherichia coli metabolism that satisfies fluxomic data for wild-type and 25 mutant strains under different substrates and growth conditions. The k-ecoli457 model contains 457 model reactions, 337 metabolites and 295 substrate-level regulatory interactions. Parameterization is carried out using a genetic algorithm by simultaneously imposing all available fluxomic data (about 30 measured fluxes per mutant). Furthermore, the Pearson correlation coefficient between experimentalmore » data and predicted product yields for 320 engineered strains spanning 24 product metabolites is 0.84. This is substantially higher than that using flux balance analysis, minimization of metabolic adjustment or maximization of product yield exhibiting systematic errors with correlation coefficients of, respectively, 0.18, 0.37 and 0.47.« less
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Natural allelic variation of the AZI1 gene controls root growth under zinc-limiting condition
Bouain, Nadia; Saenchai, Chorpet
2018-01-01
Zinc is an essential micronutrient for all living organisms and is involved in a plethora of processes including growth and development, and immunity. However, it is unknown if there is a common genetic and molecular basis underlying multiple facets of zinc function. Here we used natural variation in Arabidopsis thaliana to study the role of zinc in regulating growth. We identify allelic variation of the systemic immunity gene AZI1 as a key for determining root growth responses to low zinc conditions. We further demonstrate that this gene is important for modulating primary root length depending on the zinc and defence status. Finally, we show that the interaction of the immunity signal azelaic acid and zinc level to regulate root growth is conserved in rice. This work demonstrates that there is a common genetic and molecular basis for multiple zinc dependent processes and that nutrient cues can determine the balance of growth and immune responses in plants. PMID:29608565
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Khodayari, Ali; Maranas, Costas D.
2016-12-20
Kinetic models of metabolism at a genome scale that faithfully recapitulate the effect of multiple genetic interventions would be transformative in our ability to reliably design novel overproducing microbial strains. Here, we introduce k-ecoli457, a genome-scale kinetic model of Escherichia coli metabolism that satisfies fluxomic data for wild-type and 25 mutant strains under different substrates and growth conditions. The k-ecoli457 model contains 457 model reactions, 337 metabolites and 295 substrate-level regulatory interactions. Parameterization is carried out using a genetic algorithm by simultaneously imposing all available fluxomic data (about 30 measured fluxes per mutant). Furthermore, the Pearson correlation coefficient between experimentalmore » data and predicted product yields for 320 engineered strains spanning 24 product metabolites is 0.84. This is substantially higher than that using flux balance analysis, minimization of metabolic adjustment or maximization of product yield exhibiting systematic errors with correlation coefficients of, respectively, 0.18, 0.37 and 0.47.« less
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Telonis-Scott, Marina; Sgrò, Carla M.; Hoffmann, Ary A.; Griffin, Philippa C.
2016-01-01
Repeated attempts to map the genomic basis of complex traits often yield different outcomes because of the influence of genetic background, gene-by-environment interactions, and/or statistical limitations. However, where repeatability is low at the level of individual genes, overlap often occurs in gene ontology categories, genetic pathways, and interaction networks. Here we report on the genomic overlap for natural desiccation resistance from a Pool-genome-wide association study experiment and a selection experiment in flies collected from the same region in southeastern Australia in different years. We identified over 600 single nucleotide polymorphisms associated with desiccation resistance in flies derived from almost 1,000 wild-caught genotypes, a similar number of loci to that observed in our previous genomic study of selected lines, demonstrating the genetic complexity of this ecologically important trait. By harnessing the power of cross-study comparison, we narrowed the candidates from almost 400 genes in each study to a core set of 45 genes, enriched for stimulus, stress, and defense responses. In addition to gene-level overlap, there was higher order congruence at the network and functional levels, suggesting genetic redundancy in key stress sensing, stress response, immunity, signaling, and gene expression pathways. We also identified variants linked to different molecular aspects of desiccation physiology previously verified from functional experiments. Our approach provides insight into the genomic basis of a complex and ecologically important trait and predicts candidate genetic pathways to explore in multiple genetic backgrounds and related species within a functional framework. PMID:26733490
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Vinson, Amanda; Prongay, Kamm; Ferguson, Betsy
2013-01-01
Complex diseases (e.g., cardiovascular disease and type 2 diabetes, among many others) pose the biggest threat to human health worldwide and are among the most challenging to investigate. Susceptibility to complex disease may be caused by multiple genetic variants (GVs) and their interaction, by environmental factors, and by interaction between GVs and environment, and large study cohorts with substantial analytical power are typically required to elucidate these individual contributions. Here, we discuss the advantages of both power and feasibility afforded by the use of extended pedigrees of rhesus macaques (Macaca mulatta) for genetic studies of complex human disease based on next-generation sequence data. We present these advantages in the context of previous research conducted in rhesus macaques for several representative complex diseases. We also describe a single, multigeneration pedigree of Indian-origin rhesus macaques and a sample biobank we have developed for genetic analysis of complex disease, including power of this pedigree to detect causal GVs using either genetic linkage or association methods in a variance decomposition approach. Finally, we summarize findings of significant heritability for a number of quantitative traits that demonstrate that genetic contributions to risk factors for complex disease can be detected and measured in this pedigree. We conclude that the development and application of an extended pedigree to analysis of complex disease traits in the rhesus macaque have shown promising early success and that genome-wide genetic and higher order -omics studies in this pedigree are likely to yield useful insights into the architecture of complex human disease. PMID:24174435
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[Analytic methods for seed models with genotype x environment interactions].
Zhu, J
1996-01-01
Genetic models with genotype effect (G) and genotype x environment interaction effect (GE) are proposed for analyzing generation means of seed quantitative traits in crops. The total genetic effect (G) is partitioned into seed direct genetic effect (G0), cytoplasm genetic of effect (C), and maternal plant genetic effect (Gm). Seed direct genetic effect (G0) can be further partitioned into direct additive (A) and direct dominance (D) genetic components. Maternal genetic effect (Gm) can also be partitioned into maternal additive (Am) and maternal dominance (Dm) genetic components. The total genotype x environment interaction effect (GE) can also be partitioned into direct genetic by environment interaction effect (G0E), cytoplasm genetic by environment interaction effect (CE), and maternal genetic by environment interaction effect (GmE). G0E can be partitioned into direct additive by environment interaction (AE) and direct dominance by environment interaction (DE) genetic components. GmE can also be partitioned into maternal additive by environment interaction (AmE) and maternal dominance by environment interaction (DmE) genetic components. Partitions of genetic components are listed for parent, F1, F2 and backcrosses. A set of parents, their reciprocal F1 and F2 seeds is applicable for efficient analysis of seed quantitative traits. MINQUE(0/1) method can be used for estimating variance and covariance components. Unbiased estimation for covariance components between two traits can also be obtained by the MINQUE(0/1) method. Random genetic effects in seed models are predictable by the Adjusted Unbiased Prediction (AUP) approach with MINQUE(0/1) method. The jackknife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects, which can be further used in a t-test for parameter. Unbiasedness and efficiency for estimating variance components and predicting genetic effects are tested by Monte Carlo simulations.
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Malosetti, Marcos; Ribaut, Jean-Marcel; van Eeuwijk, Fred A.
2013-01-01
Genotype-by-environment interaction (GEI) is an important phenomenon in plant breeding. This paper presents a series of models for describing, exploring, understanding, and predicting GEI. All models depart from a two-way table of genotype by environment means. First, a series of descriptive and explorative models/approaches are presented: Finlay–Wilkinson model, AMMI model, GGE biplot. All of these approaches have in common that they merely try to group genotypes and environments and do not use other information than the two-way table of means. Next, factorial regression is introduced as an approach to explicitly introduce genotypic and environmental covariates for describing and explaining GEI. Finally, QTL modeling is presented as a natural extension of factorial regression, where marker information is translated into genetic predictors. Tests for regression coefficients corresponding to these genetic predictors are tests for main effect QTL expression and QTL by environment interaction (QEI). QTL models for which QEI depends on environmental covariables form an interesting model class for predicting GEI for new genotypes and new environments. For realistic modeling of genotypic differences across multiple environments, sophisticated mixed models are necessary to allow for heterogeneity of genetic variances and correlations across environments. The use and interpretation of all models is illustrated by an example data set from the CIMMYT maize breeding program, containing environments differing in drought and nitrogen stress. To help readers to carry out the statistical analyses, GenStat® programs, 15th Edition and Discovery® version, are presented as “Appendix.” PMID:23487515
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Effects of enamel matrix genes on dental caries are moderated by fluoride exposures
Shaffer, John R.; Carlson, Jenna C.; Stanley, Brooklyn O. C.; Feingold, Eleanor; Cooper, Margaret; Vanyukov, Michael M.; Maher, Brion S.; Slayton, Rebecca L.; Willing, Marcia C.; Reis, Steven E.; McNeil, Daniel W.; Crout, Richard J.; Weyant, Robert J.; Levy, Steven M.; Vieira, Alexandre R.; Marazita, Mary L.
2014-01-01
Dental caries (tooth decay) is the most common chronic disease, worldwide, affecting most children and adults. Though dental caries is highly heritable, few caries-related genes have been discovered. We investigated whether 18 genetic variants in the group of nonamelogenin enamel matrix genes (AMBN, ENAM, TUFT1, and TFIP11) were associated with dental caries experience in 13 age- and race-stratified samples from six parent studies (N=3,600). Linear regression was used to model genetic associations and test gene-byfluoride interaction effects for two sources of fluoride: daily tooth brushing and home water fluoride concentration. Meta-analysis was used to combine results across five child and eight adult samples. We observed the statistically significant association of rs2337359 upstream of TUFT1 with dental caries experience via meta-analysis across adult samples (p<0.002) and the suggestive association for multiple variants in TFIP11 across child samples (p<0.05). Moreover, we discovered two genetic variants (rs2337359 upstream of TUFT1 and missense rs7439186 in AMBN) involved in gene-by-fluoride interactions. For each interaction, participants with the risk allele/genotype exhibited greater dental caries experience only if they were not exposed to the source of fluoride. Altogether, these results confirm that variation in enamel matrix genes contributes to individual differences in dental caries liability, and demonstrate that the effects of these genes may be moderated by protective fluoride exposures. In short, genes may exert greater influence on dental caries in unprotected environments, or equivalently, the protective effects of fluoride may obviate the effects of genetic risk alleles. PMID:25373699
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Han, Xuesong; Zheng, Tongzhang; Lan, Qing; Zhang, Yaqun; Kilfoy, Briseis A.; Qin, Qin; Rothman, Nathaniel; Zahm, Shelia H.; Holford, Theodore R.; Leaderer, Brian; Zhang, Yawei
2010-01-01
Oxidative damage caused by reactive oxygen species (ROS) and other free radicals is involved in carcinogenesis. It has been suggested that high vegetable and fruit intake may reduce the risk of non-Hodgkin lymphoma (NHL) as vegetables and fruit are rich in antioxidants. The aim of this study is to evaluate the interaction of vegetable and fruit intake with genetic polymorphisms in oxidative stress pathway genes and NHL risk. This hypothesis was investigated in a population-based case-control study of NHL and NHL histological subtype in Connecticut women including 513 histologically confirmed incident cases and 591 randomly selected controls. Gene-vegetable/fruit joint effects were estimated using unconditional logistic regression model. The false discovery rate method was applied to adjust for multiple comparisons. Significant interactions with vegetable and fruit intake were mainly found for genetic polymorphisms on nitric oxide synthase (NOS) genes among those with diffuse large B-cell lymphoma (DLBCL) and Follicular lymphoma (FL). Two single nucleotide polymorphisms (SNPs) in the NOS1 gene were found to significantly modify the association between total vegetable and fruit intake and risk of NHL overall, as well as the risk of follicular lymphoma (FL). When vegetables, bean vegetables, cruciferous vegetables, green leafy vegetables, red vegetables, yellow/orange vegetables, fruit, and citrus fruit were examined separately, strong interaction effects were narrowed to vegetable intake among DLBCL patients. Our results suggest that genetic polymorphisms in oxidative stress pathway genes, especially in the nitric oxide synthase genes, modify the association between vegetable and fruit intake and risk of NHL. PMID:19423521
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Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks.
Deeter, Anthony; Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui
2017-01-01
The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.
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Windhorst, Dafna A; Mileva-Seitz, Viara R; Rippe, Ralph C A; Tiemeier, Henning; Jaddoe, Vincent W V; Verhulst, Frank C; van IJzendoorn, Marinus H; Bakermans-Kranenburg, Marian J
2016-08-01
In a longitudinal cohort study, we investigated the interplay of harsh parenting and genetic variation across a set of functionally related dopamine genes, in association with children's externalizing behavior. This is one of the first studies to employ gene-based and gene-set approaches in tests of Gene by Environment (G × E) effects on complex behavior. This approach can offer an important alternative or complement to candidate gene and genome-wide environmental interaction (GWEI) studies in the search for genetic variation underlying individual differences in behavior. Genetic variants in 12 autosomal dopaminergic genes were available in an ethnically homogenous part of a population-based cohort. Harsh parenting was assessed with maternal (n = 1881) and paternal (n = 1710) reports at age 3. Externalizing behavior was assessed with the Child Behavior Checklist (CBCL) at age 5 (71 ± 3.7 months). We conducted gene-set analyses of the association between variation in dopaminergic genes and externalizing behavior, stratified for harsh parenting. The association was statistically significant or approached significance for children without harsh parenting experiences, but was absent in the group with harsh parenting. Similarly, significant associations between single genes and externalizing behavior were only found in the group without harsh parenting. Effect sizes in the groups with and without harsh parenting did not differ significantly. Gene-environment interaction tests were conducted for individual genetic variants, resulting in two significant interaction effects (rs1497023 and rs4922132) after correction for multiple testing. Our findings are suggestive of G × E interplay, with associations between dopamine genes and externalizing behavior present in children without harsh parenting, but not in children with harsh parenting experiences. Harsh parenting may overrule the role of genetic factors in externalizing behavior. Gene-based and gene-set analyses offer promising new alternatives to analyses focusing on single candidate polymorphisms when examining the interplay between genetic and environmental factors.
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Multiple Independent Genetic Factors at NOS1AP Modulate the QT Interval in a Multi-Ethnic Population
Arking, Dan E.; Khera, Amit; Xing, Chao; Kao, W. H. Linda; Post, Wendy; Boerwinkle, Eric; Chakravarti, Aravinda
2009-01-01
Extremes of electrocardiographic QT interval are associated with increased risk for sudden cardiac death (SCD); thus, identification and characterization of genetic variants that modulate QT interval may elucidate the underlying etiology of SCD. Previous studies have revealed an association between a common genetic variant in NOS1AP and QT interval in populations of European ancestry, but this finding has not been extended to other ethnic populations. We sought to characterize the effects of NOS1AP genetic variants on QT interval in the multi-ethnic population-based Dallas Heart Study (DHS, n = 3,072). The SNP most strongly associated with QT interval in previous samples of European ancestry, rs16847548, was the most strongly associated in White (P = 0.005) and Black (P = 3.6×10−5) participants, with the same direction of effect in Hispanics (P = 0.17), and further showed a significant SNP × sex-interaction (P = 0.03). A second SNP, rs16856785, uncorrelated with rs16847548, was also associated with QT interval in Blacks (P = 0.01), with qualitatively similar results in Whites and Hispanics. In a previously genotyped cohort of 14,107 White individuals drawn from the combined Atherosclerotic Risk in Communities (ARIC) and Cardiovascular Health Study (CHS) cohorts, we validated both the second locus at rs16856785 (P = 7.63×10−8), as well as the sex-interaction with rs16847548 (P = 8.68×10−6). These data extend the association of genetic variants in NOS1AP with QT interval to a Black population, with similar trends, though not statistically significant at P<0.05, in Hispanics. In addition, we identify a strong sex-interaction and the presence of a second independent site within NOS1AP associated with the QT interval. These results highlight the consistent and complex role of NOS1AP genetic variants in modulating QT interval. PMID:19180230
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Identification of SNPs associated with variola virus virulence.
Hoen, Anne Gatewood; Gardner, Shea N; Moore, Jason H
2013-02-14
Decades after the eradication of smallpox, its etiological agent, variola virus (VARV), remains a threat as a potential bioweapon. Outbreaks of smallpox around the time of the global eradication effort exhibited variable case fatality rates (CFRs), likely attributable in part to complex viral genetic determinants of smallpox virulence. We aimed to identify genome-wide single nucleotide polymorphisms associated with CFR. We evaluated unadjusted and outbreak geographic location-adjusted models of single SNPs and two- and three-way interactions between SNPs. Using the data mining approach multifactor dimensionality reduction (MDR), we identified five VARV SNPs in models significantly associated with CFR. The top performing unadjusted model and adjusted models both revealed the same two-way gene-gene interaction. We discuss the biological plausibility of the influence of the SNPs identified these and other significant models on the strain-specific virulence of VARV. We have identified genetic loci in the VARV genome that are statistically associated with VARV virulence as measured by CFR. While our ability to infer a causal relationship between the specific SNPs identified in our analysis and VARV virulence is limited, our results suggest that smallpox severity is in part associated with VARV strain variation and that VARV virulence may be determined by multiple genetic loci. This study represents the first application of MDR to the identification of pathogen gene-gene interactions for predicting infectious disease outbreak severity.
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Dechaine, Jennifer M; Brock, Marcus T; Iniguez-Luy, Federico L; Weinig, Cynthia
2014-01-01
Growth in plants occurs via the addition of repeating modules, suggesting that the genetic architecture of similar subunits may vary between earlier- and later-developing modules. These complex environment × ontogeny interactions are not well elucidated, as studies examining quantitative trait loci (QTLs) expression over ontogeny have not included multiple environments. Here, we characterized the genetic architecture of vegetative traits and onset of reproduction over ontogeny in recombinant inbred lines of Brassica rapa in the field and glasshouse. The magnitude of genetic variation in plasticity of seedling internodes was greater than in those produced later in ontogeny. We correspondingly detected that QTLs for seedling internode length were environment-specific, whereas later in ontogeny the majority of QTLs affected internode lengths in all treatments. The relationship between internode traits and onset of reproduction varied with environment and ontogenetic stage. This relationship was observed only in the glasshouse environment and was largely attributable to one environment-specific QTL. Our results provide the first evidence of a QTL × environment × ontogeny interaction, and provide QTL resolution for differences between early- and later-stage plasticity for stem elongation. These results also suggest potential constraints on morphological evolution in early vs later modules as a result of associations with reproductive timing. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.
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Identification of SNPs associated with variola virus virulence
2013-01-01
Background Decades after the eradication of smallpox, its etiological agent, variola virus (VARV), remains a threat as a potential bioweapon. Outbreaks of smallpox around the time of the global eradication effort exhibited variable case fatality rates (CFRs), likely attributable in part to complex viral genetic determinants of smallpox virulence. We aimed to identify genome-wide single nucleotide polymorphisms associated with CFR. We evaluated unadjusted and outbreak geographic location-adjusted models of single SNPs and two- and three-way interactions between SNPs. Findings Using the data mining approach multifactor dimensionality reduction (MDR), we identified five VARV SNPs in models significantly associated with CFR. The top performing unadjusted model and adjusted models both revealed the same two-way gene-gene interaction. We discuss the biological plausibility of the influence of the SNPs identified these and other significant models on the strain-specific virulence of VARV. Conclusions We have identified genetic loci in the VARV genome that are statistically associated with VARV virulence as measured by CFR. While our ability to infer a causal relationship between the specific SNPs identified in our analysis and VARV virulence is limited, our results suggest that smallpox severity is in part associated with VARV strain variation and that VARV virulence may be determined by multiple genetic loci. This study represents the first application of MDR to the identification of pathogen gene-gene interactions for predicting infectious disease outbreak severity. PMID:23410064
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Diet, microbes, and host genetics: the perfect storm in inflammatory bowel diseases.
Leone, Vanessa; Chang, Eugene B; Devkota, Suzanne
2013-03-01
The incidence of inflammatory bowel diseases (IBD), as well as other inflammatory conditions, has dramatically increased over the past half century. While many studies have shown that IBD exhibits a genetic component via genome-wide association studies, genetic drift alone cannot account for this increase, and other factors, such as those found in the environment must play a role, suggesting a "multiple hit" phenomenon that precipitates disease. One major environmental factor, dietary intake, has shifted to a high fat, high carbohydrate Western-type diet in developing nations, nearly in direct correlation with the increasing incidence of IBD. Recent evidence suggests that specific changes in dietary intake have led to a shift in the composite human gut microbiota, resulting in the emergence of pathobionts that can thrive under specific conditions. In the genetically susceptible host, the emerging pathobionts can lead to increasing incidence and severity of IBD and other inflammatory disorders. Since the gut microbiota is plastic and responds to dietary modulations, the use of probiotics, prebiotics, and/or dietary alterations are all intriguing complementary therapeutic approaches to alleviate IBD symptoms. However, the interactions are complex and it is unlikely that a one-size-fits all approach can be utilized across all populations affected by IBD. Exploration into and thoroughly understanding the interactions between host and microbes, primarily in the genetically susceptible host, will help define strategies that can be tailored to an individual as we move towards an era of personalized medicine to treat IBD.
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Cerón-Muñoz, M F; Tonhati, H; Costa, C N; Rojas-Sarmiento, D; Echeverri Echeverri, D M
2004-08-01
Descriptive herd variables (DVHE) were used to explain genotype by environment interactions (G x E) for milk yield (MY) in Brazilian and Colombian production environments and to develop a herd-cluster model to estimate covariance components and genetic parameters for each herd environment group. Data consisted of 180,522 lactation records of 94,558 Holstein cows from 937 Brazilian and 400 Colombian herds. Herds in both countries were jointly grouped in thirds according to 8 DVHE: production level, phenotypic variability, age at first calving, calving interval, percentage of imported semen, lactation length, and herd size. For each DVHE, REML bivariate animal model analyses were used to estimate genetic correlations for MY between upper and lower thirds of the data. Based on estimates of genetic correlations, weights were assigned to each DVHE to group herds in a cluster analysis using the FASTCLUS procedure in SAS. Three clusters were defined, and genetic and residual variance components were heterogeneous among herd clusters. Estimates of heritability in clusters 1 and 3 were 0.28 and 0.29, respectively, but the estimate was larger (0.39) in Cluster 2. The genetic correlations of MY from different clusters ranged from 0.89 to 0.97. The herd-cluster model based on DVHE properly takes into account G x E by grouping similar environments accordingly and seems to be an alternative to simply considering country borders to distinguish between environments.
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Surgical correction of urethral dilatation in an intersex goat.
Karras, S; Modransky, P; Welker, B
1992-11-15
Multiple congenital urethral abnormalities were successfully corrected in a polled goat kid. Anatomic genito-urinary abnormalities identified were paired testes with associated epididymis, ductus deferens, and active endometrial tissue. Blood karyotyping revealed the female state--XX sex chromosomes. This case exemplifies the complex interactions in addition to Y dominant Mendelian genetics that determine reproductive tract development in goats. The resultant intersex state is clinically recognized with greater frequency in polled progeny.
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On the nature of species: insights from Paramecium and other ciliates
Hall, Meaghan S.; Katz, Laura A.
2011-01-01
The multiple species concepts currently in use by the scientific community (e.g. Morphological, Biological, Phylogenetic) are united in that they all aim to capture the process of divergence between populations. For example, the Biological Species Concept (BSC) defines a species as a natural group of organisms that is reproductively isolated from other such groups. Here we synthesize nearly a century of research on the ciliate genus Paramecium that highlights the shortcomings of our prevailing notions on the nature of species. In this lineage, there is discordance between morphology, mating behavior, and genetics, features assumed to be correlated, at least after sufficient time has passed, under all species concepts. Intriguingly, epigenetic phenomena are well documented in ciliates where they influence features such as germline/soma differentiation and mating type determination. Consequently, we hypothesize that divergence within ciliate populations is due to a dynamic interaction between genetic and epigenetic factors. The growing list of examples of epigenetic phenomena that potentially impact speciation (i.e. by influencing the dynamics of sex chromosomes, fate of hybrids, zygotic drive and genomic conflicts) suggests that interactions between genetics and epigenetics may also drive divergence in other eukaryotic lineages. PMID:21505762
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Mobile DNA and evolution in the 21st century
2010-01-01
Scientific history has had a profound effect on the theories of evolution. At the beginning of the 21st century, molecular cell biology has revealed a dense structure of information-processing networks that use the genome as an interactive read-write (RW) memory system rather than an organism blueprint. Genome sequencing has documented the importance of mobile DNA activities and major genome restructuring events at key junctures in evolution: exon shuffling, changes in cis-regulatory sites, horizontal transfer, cell fusions and whole genome doublings (WGDs). The natural genetic engineering functions that mediate genome restructuring are activated by multiple stimuli, in particular by events similar to those found in the DNA record: microbial infection and interspecific hybridization leading to the formation of allotetraploids. These molecular genetic discoveries, plus a consideration of how mobile DNA rearrangements increase the efficiency of generating functional genomic novelties, make it possible to formulate a 21st century view of interactive evolutionary processes. This view integrates contemporary knowledge of the molecular basis of genetic change, major genome events in evolution, and stimuli that activate DNA restructuring with classical cytogenetic understanding about the role of hybridization in species diversification. PMID:20226073
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Tian, Xiaolin; Zhu, Mingwei; Li, Long; Wu, Chunlai
2013-01-01
Genetic screens conducted using Drosophila melanogaster (fruit fly) have made numerous milestone discoveries in the advance of biological sciences. However, the use of biochemical screens aimed at extending the knowledge gained from genetic analysis was explored only recently. Here we describe a method to purify the protein complex that associates with any protein of interest from adult fly heads. This method takes advantage of the Drosophila GAL4/UAS system to express a bait protein fused with a Tandem Affinity Purification (TAP) tag in fly neurons in vivo, and then implements two rounds of purification using a TAP procedure similar to the one originally established in yeast1 to purify the interacting protein complex. At the end of this procedure, a mixture of multiple protein complexes is obtained whose molecular identities can be determined by mass spectrometry. Validation of the candidate proteins will benefit from the resource and ease of performing loss-of-function studies in flies. Similar approaches can be applied to other fly tissues. We believe that the combination of genetic manipulations and this proteomic approach in the fly model system holds tremendous potential for tackling fundamental problems in the field of neurobiology and beyond. PMID:24335807
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Hoffer, Laurent; Chira, Camelia; Marcou, Gilles; Varnek, Alexandre; Horvath, Dragos
2015-05-19
This paper describes the development of the unified conformational sampling and docking tool called Sampler for Multiple Protein-Ligand Entities (S4MPLE). The main novelty in S4MPLE is the unified dealing with intra- and intermolecular degrees of freedom (DoF). While classically programs are either designed for folding or docking, S4MPLE transcends this artificial specialization. It supports folding, docking of a flexible ligand into a flexible site and simultaneous docking of several ligands. The trick behind it is the formal assimilation of inter-molecular to intra-molecular DoF associated to putative inter-molecular contact axes. This is implemented within the genetic operators powering a Lamarckian Genetic Algorithm (GA). Further novelty includes differentiable interaction fingerprints to control population diversity, and fitting a simple continuum solvent model and favorable contact bonus terms to the AMBER/GAFF force field. Novel applications-docking of fragment-like compounds, simultaneous docking of multiple ligands, including free crystallographic waters-were published elsewhere. This paper discusses: (a) methodology, (b) set-up of the force field energy functions and (c) their validation in classical redocking tests. More than 80% success in redocking was achieved (RMSD of top-ranked pose < 2.0 Å).
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Imani, Saber; Cheng, Jingliang; Shasaltaneh, Marzieh Dehghan; Wei, Chunli; Yang, Lisha; Fu, Shangyi; Zou, Hui; Khan, Md. Asaduzzaman; Zhang, Xianqin; Chen, Hanchun; Zhang, Dianzheng; Duan, Chengxia; Lv, Hongbin; Li, Yumei; Chen, Rui; Fu, Junjiang
2018-01-01
Stargardt disease-4 (STGD4) is an autosomal dominant complex, genetically heterogeneous macular degeneration/dystrophy (MD) disorder. In this paper, we used targeted next generation sequencing and multiple molecular dynamics analyses to identify and characterize a disease-causing genetic variant in four generations of a Chinese family with STGD4-like MD. We found a novel heterozygous missense mutation, c.734T>C (p.L245P) in the PROM1 gene. Structurally, this mutation most likely impairs PROM1 protein stability, flexibility, and amino acid interaction network after changing the amino acid residue Leucine into Proline in the basic helix-loop-helix leucine zipper domain. Molecular dynamic simulation and principal component analysis provide compelling evidence that this PROM1 mutation contributes to disease causativeness or susceptibility variants in patients with STGD4-like MD. Thus, this finding defines new approaches in genetic characterization, accurate diagnosis, and prevention of STGD4-like MD. PMID:29416601
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Odour dialects among wild mammals.
Kean, Eleanor Freya; Bruford, Michael William; Russo, Isa-Rita M; Müller, Carsten Theodor; Chadwick, Elizabeth Anna
2017-10-19
Across multiple taxa, population structure and dynamics depend on effective signalling between individuals. Among mammals, chemical communication is arguably the most important sense, underpinning mate choice, parental care, territoriality and even disease transmission. There is a growing body of evidence that odours signal genetic information that may confer considerable benefits including inbreeding avoidance and nepotism. To date, however, there has been no clear evidence that odours encode population-level information in wild mammals. Here we demonstrate for the first time the existence of 'odour dialects' in genetically distinct mammalian subpopulations across a large geographical scale. We found that otters, Lutra lutra, from across the United Kingdom possess sex and biogeography-specific odours. Subpopulations with the most distinctive odour profiles are also the most genetically diverse but not the most genetically differentiated. Furthermore, geographic distance between individuals does not explain regional odour differences, refuting other potential explanations such as group odour sharing behaviour. Differences in the language of odours between subpopulations have the potential to affect individual interactions, which could impact reproduction and gene-flow.
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Farzan, Shohreh F; Karagas, Margaret R.; Jiang, Jieying; Wu, Fen; Liu, Mengling; Newman, Jonathan D.; Jasmine, Farzana; Kibriya, Muhammad G; Paul-Brutus, Rachelle; Parvez, Faruque; Argos, Maria; Bryan, Molly Scannell; Eunus, Mahbub; Ahmed, Alauddin; Islam, Tariqul; Rakibuz-Zaman, Muhammad; Hasan, Rabiul; Sarwar, Golam; Slavkovich, Vesna; Graziano, Joseph; Ahsan, Habibul; Chen, Yu
2015-01-01
Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide and mounting evidence indicates that toxicant exposures can profoundly impact on CVD risk. Epidemiologic studies have suggested that arsenic (As) exposure is positively related to increases in blood pressure (BP), a primary CVD risk factor. However, evidence of whether genetic susceptibility can modify the association between As and BP are lacking. In this study, we used mixed effects models adjusted for potential confounders to examine the interaction between As exposure from well water and potential genetic modifiers on longitudinal change in BP over approximately 7 years of follow-up in 1137 subjects selected from the Health Effects of Arsenic Longitudinal Study (HEALS) cohort in Bangladesh. Genotyping was conducted for 235 SNPs in 18 genes related to As metabolism, oxidative stress and endothelial function. We observed interactions between 44 SNPs with well water As for one or more BP outcome measures (systolic, diastolic, or pulse pressure (PP)) over the course of follow-up. The interaction between CYBA rs3794624 and well water As on annual PP remained statistically significant after correction for multiple comparisons (FDR-adjusted p for interaction = 0.05). Among individuals with the rs3794624 variant genotype, well water As was associated with a 2.23 mmHg (95% CI: 1.14-3.32) greater annual increase in PP, while among those with the wild type, well water As was associated with a 0.13 mmHg (95% CI: 0.02-0.23) greater annual increase in PP. Our results suggest that genetic variability may contribute to As-associated increases in BP over time. PMID:26220686
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Fu, Jiaqi; Nogueira, Sarah V; Drongelen, Vincent van; Coit, Patrick; Ling, Song; Rosloniec, Edward F; Sawalha, Amr H; Holoshitz, Joseph
2018-05-01
The susceptibility to autoimmune diseases is affected by genetic and environmental factors. In rheumatoid arthritis (RA), the shared epitope (SE), a five-amino acid sequence motif encoded by RA-associated HLA-DRB1 alleles, is the single most significant genetic risk factor. The risk conferred by the SE is increased in a multiplicative way by exposure to various environmental pollutants, such as cigarette smoke. The mechanism of this synergistic interaction is unknown. It is worth noting that the SE has recently been found to act as a signal transduction ligand that facilitates differentiation of Th17 cells and osteoclasts in vitro and in vivo. Intriguingly, the aryl hydrocarbon receptor (AhR), a transcription factor that mediates the xenobiotic effects of many pollutants, including tobacco combustion products, has been found to activate similar biologic effects. Prompted by these similarities, we sought to determine whether the SE and AhR signaling pathways interact in autoimmune arthritis. Here we uncovered a nuclear factor kappa B-mediated synergistic interaction between the SE and AhR pathways that leads to markedly enhanced osteoclast differentiation and Th17 polarization in vitro. Administration of AhR pathway agonists to transgenic mice carrying human SE-coding alleles resulted in a robust increase in arthritis severity, bone destruction, overabundance of osteoclasts, and IL17-expressing cells in the inflamed joints and draining lymph nodes of arthritic mice. Thus, this study identifies a previously unrecognized mechanism of gene-environment interaction that could provide insights into the well-described but poorly understood amplification of the genetic risk for RA upon exposure to environmental pollutants. Copyright © 2018 the Author(s). Published by PNAS.
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Lifestyle may modify the glucose-raising effect of genetic loci. A study in the Greek population.
Marouli, E; Kanoni, S; Dimitriou, M; Kolovou, G; Deloukas, P; Dedoussis, G
2016-03-01
Lifestyle habits including dietary intake and physical activity are closely associated with multiple body processes including glucose metabolism and are known to affect human health. Recent genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) associated with glucose levels. The hypothesis tested here is whether a healthy lifestyle assessed via a score is associated with glycaemic traits and whether there is an interaction between the lifestyle and known glucose-raising genetic variants in association with glycaemic traits. Participants of Greek descent from the THISEAS study were included in this analysis. We developed a glucose preventive score (GPS) including dietary and physical activity characteristics. We also modelled a weighted genetic risk score (wGRS), based on 20 known glucose-raising loci, in order to investigate the impact of lifestyle-gene interaction on glucose levels. The GPS was observed to be significantly associated with lower glucose concentrations (β ± SE: -0.083 ± 0.021 mmol/L, P = 1.6 × 10(-04)) and the wGRS, as expected, with increased glucose levels (β ± SE: 0.020 ± 0.007 mmol/L, P = 8.4 × 10(-3)). The association of the wGRS with glucose levels was attenuated after interaction with the GPS. A higher GPS indicated decreasing glucose levels in the presence of an increasing wGRS (β interaction ± SE: -0.019 ± 0.007 mmol/L, P = 0.014). Our results indicate that lower glucose levels underlie a healthier lifestyle and also support an interaction between the wGRS for known glycaemic loci and GPS associated with lower glucose levels. These scores could be useful tools for monitoring glucose metabolism. Copyright © 2016. Published by Elsevier B.V.
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FKBP5 and emotional neglect interact to predict individual differences in amygdala reactivity.
White, M G; Bogdan, R; Fisher, P M; Muñoz, K E; Williamson, D E; Hariri, A R
2012-10-01
Individual variation in physiological responsiveness to stress mediates risk for mental illness and is influenced by both experiential and genetic factors. Common polymorphisms in the human gene for FK506 binding protein 5 (FKBP5), which is involved in transcriptional regulation of the hypothalamic-pituitary-adrenal (HPA) axis, have been shown to interact with childhood abuse and trauma to predict stress-related psychopathology. In the current study, we examined if such gene-environment interaction effects may be related to variability in the threat-related reactivity of the amygdala, which plays a critical role in mediating physiological and behavioral adaptations to stress including modulation of the HPA axis. To this end, 139 healthy Caucasian youth completed a blood oxygen level-dependent functional magnetic resonance imaging probe of amygdala reactivity and self-report assessments of emotional neglect (EN) and other forms of maltreatment. These individuals were genotyped for 6 FKBP5 polymorphisms (rs7748266, rs1360780, rs9296158, rs3800373, rs9470080 and rs9394309) previously associated with psychopathology and/or HPA axis function. Interactions between each SNP and EN emerged such that risk alleles predicted relatively increased dorsal amygdala reactivity in the context of higher EN, even after correcting for multiple testing. Two different haplotype analyses confirmed this relationship as haplotypes with risk alleles also exhibited increased amygdala reactivity in the context of higher EN. Our results suggest that increased threat-related amygdala reactivity may represent a mechanism linking psychopathology to interactions between common genetic variants affecting HPA axis function and childhood trauma. © 2012 The Authors. Genes, Brain and Behavior © 2012 Blackwell Publishing Ltd and International Behavioural and Neural Genetics Society.
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Knepper, Caleb; Day, Brad
2010-01-01
More than 60 years ago, H.H. Flor proposed the "Gene-for-Gene" hypothesis, which described the genetic relationship between host plants and pathogens. In the decades that followed Flor's seminal work, our understanding of the plant-pathogen interaction has evolved into a sophisticated model, detailing the molecular genetic and biochemical processes that control host-range, disease resistance signaling and susceptibility. The interaction between plants and microbes is an intimate exchange of signals that has evolved for millennia, resulting in the modification and adaptation of pathogen virulence strategies and host recognition elements. In total, plants have evolved mechanisms to combat the ever-changing landscape of biotic interactions bombarding their environment, while in parallel, plant pathogens have co-evolved mechanisms to sense and adapt to these changes. On average, the typical plant is susceptible to attack by dozens of microbial pathogens, yet in most cases, remains resistant to many of these challenges. The sum of research in our field has revealed that these interactions are regulated by multiple layers of intimately linked signaling networks. As an evolved model of Flor's initial observations, the current paradigm in host-pathogen interactions is that pathogen effector molecules, in large part, drive the recognition, activation and subsequent physiological responses in plants that give rise to resistance and susceptibility. In this Chapter, we will discuss our current understanding of the association between plants and microbial pathogens, detailing the pressures placed on both host and microbe to either maintain disease resistance, or induce susceptibility and disease. From recognition to transcriptional reprogramming, we will review current data and literature that has advanced the classical model of the Gene-for-Gene hypothesis to our current understanding of basal and effector triggered immunity.
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Van Mai, Tan; Fujita, Daisuke; Matsumura, Masaya; Yoshimura, Atsushi; Yasui, Hideshi
2015-01-01
The rice cultivar ASD7 (Oryza sativa L. ssp. indica) is resistant to the brown planthopper (BPH; Nilaparvata lugens Stål) and the green leafhopper (Nephotettix virescens Distant). Here, we analyzed multiple genetic resistance to BPH and the green rice leafhopper (GRH; Nephotettix cincticeps Uhler). Using two independent F2 populations derived from a cross between ASD7 and Taichung 65 (Oryza sativa ssp. japonica), we detected two QTLs (qBPH6 and qBPH12) for resistance to BPH and one QTL (qGRH5) for resistance to GRH. Linkage analysis in BC2F3 populations revealed that qBPH12 controlled resistance to BPH and co-segregated with SSR markers RM28466 and RM7376 in plants homozygous for the ASD7 allele at qBPH6. Plants homozygous for the ASD7 alleles at both QTLs showed a much faster antibiosis response to BPH than plants homozygous at only one of these QTLs. It revealed that epistatic interaction between qBPH6 and qBPH12 is the basis of resistance to BPH in ASD7. In addition, qGRH5 controlled resistance to GRH and co-segregated with SSR markers RM6082 and RM3381. qGRH5 is identical to GRH1. Thus, we clarified the genetic basis of multiple resistance of ASD7 to BPH and GRH. PMID:26719745
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Pan, Wen-Chi; Kile, Molly L.; Seow, Wei Jie; Lin, Xihong; Quamruzzaman, Quazi; Rahman, Mahmuder; Mahiuddin, Golam; Mostofa, Golam; Lu, Quan; Christiani, David C.
2013-01-01
Background Chronic exposure to arsenic in drinking water is associated with increased risk of type 2 diabetes mellitus (T2DM) but the underlying molecular mechanism remains unclear. Objectives This study evaluated the interaction between single nucleotide polymorphisms (SNPs) in genes associated with diabetes and arsenic exposure in drinking water on the risk of developing T2DM. Methods In 2009–2011, we conducted a follow up study of 957 Bangladeshi adults who participated in a case-control study of arsenic-induced skin lesions in 2001–2003. Logistic regression models were used to evaluate the association between 38 SNPs in 18 genes and risk of T2DM measured at follow up. T2DM was defined as having a blood hemoglobin A1C level greater than or equal to 6.5% at follow-up. Arsenic exposure was characterized by drinking water samples collected from participants' tubewells. False discovery rates were applied in the analysis to control for multiple comparisons. Results Median arsenic levels in 2001–2003 were higher among diabetic participants compared with non-diabetic ones (71.6 µg/L vs. 12.5 µg/L, p-value <0.001). Three SNPs in ADAMTS9 were nominally associated with increased risk of T2DM (rs17070905, Odds Ratio (OR) = 2.30, 95% confidence interval (CI) 1.17–4.50; rs17070967, OR = 2.02, 95%CI 1.00–4.06; rs6766801, OR = 2.33, 95%CI 1.18–4.60), but these associations did not reach the statistical significance after adjusting for multiple comparisons. A significant interaction between arsenic and NOTCH2 (rs699780) was observed which significantly increased the risk of T2DM (p for interaction = 0.003; q-value = 0.021). Further restricted analysis among participants exposed to water arsenic of less than 148 µg/L showed consistent results for interaction between the NOTCH2 variant and arsenic exposure on T2DM (p for interaction = 0.048; q-value = 0.004). Conclusions These findings suggest that genetic variation in NOTCH2 increased susceptibility to T2DM among people exposed to inorganic arsenic. Additionally, genetic variants in ADAMTS9 may increase the risk of T2DM. PMID:23967108
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[Genetic factors in myocardial infarction].
Hara, Masahiko; Sakata, Yasuhiko; Sato, Hiroshi
2013-02-01
One of the main mechanisms of acute myocardial infarction (AMI) is plaque rupture or erosion followed by intraluminal thrombus formation and occlusion of the coronary arteries. Thus far, many underlying conditions or environmental factors, such as hypertension, diabetes, dyslipidemia, smoking or obesity, as well as a family history of coronary artery diseases have been identified as risks for the onset of AMI. These risks suggest that AMI occurs due to interactions between underlying conditions and multiple genetic susceptibilities. For this reason, many target gene-disease association studies have been performed with the recent introduction of genome-wide association studies (GWAS) that have further revealed new genetic susceptibilities for AMI. GWAS is a way to examine many common genetic variants in different individuals to see if any variant is associated with a trait in a case-control fashion, and typically focuses on associations between single-nucleotide polymorphisms (SNP) and traits. SNP on chromosome 9p21 is one of the robust susceptibility variants for AMI which has been identified by many GWAS. In this review, we overview the methodology of GWAS, introduce genetic variants identified by GWAS as those with susceptibility for AMI, and describe the foresight of using GWAS to investigate genetic susceptibility to AMI.
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Savage, Jeanne E; Jansen, Philip R; Stringer, Sven; Watanabe, Kyoko; Bryois, Julien; de Leeuw, Christiaan A; Nagel, Mats; Awasthi, Swapnil; Barr, Peter B; Coleman, Jonathan R I; Grasby, Katrina L; Hammerschlag, Anke R; Kaminski, Jakob A; Karlsson, Robert; Krapohl, Eva; Lam, Max; Nygaard, Marianne; Reynolds, Chandra A; Trampush, Joey W; Young, Hannah; Zabaneh, Delilah; Hägg, Sara; Hansell, Narelle K; Karlsson, Ida K; Linnarsson, Sten; Montgomery, Grant W; Muñoz-Manchado, Ana B; Quinlan, Erin B; Schumann, Gunter; Skene, Nathan G; Webb, Bradley T; White, Tonya; Arking, Dan E; Avramopoulos, Dimitrios; Bilder, Robert M; Bitsios, Panos; Burdick, Katherine E; Cannon, Tyrone D; Chiba-Falek, Ornit; Christoforou, Andrea; Cirulli, Elizabeth T; Congdon, Eliza; Corvin, Aiden; Davies, Gail; Deary, Ian J; DeRosse, Pamela; Dickinson, Dwight; Djurovic, Srdjan; Donohoe, Gary; Conley, Emily Drabant; Eriksson, Johan G; Espeseth, Thomas; Freimer, Nelson A; Giakoumaki, Stella; Giegling, Ina; Gill, Michael; Glahn, David C; Hariri, Ahmad R; Hatzimanolis, Alex; Keller, Matthew C; Knowles, Emma; Koltai, Deborah; Konte, Bettina; Lahti, Jari; Le Hellard, Stephanie; Lencz, Todd; Liewald, David C; London, Edythe; Lundervold, Astri J; Malhotra, Anil K; Melle, Ingrid; Morris, Derek; Need, Anna C; Ollier, William; Palotie, Aarno; Payton, Antony; Pendleton, Neil; Poldrack, Russell A; Räikkönen, Katri; Reinvang, Ivar; Roussos, Panos; Rujescu, Dan; Sabb, Fred W; Scult, Matthew A; Smeland, Olav B; Smyrnis, Nikolaos; Starr, John M; Steen, Vidar M; Stefanis, Nikos C; Straub, Richard E; Sundet, Kjetil; Tiemeier, Henning; Voineskos, Aristotle N; Weinberger, Daniel R; Widen, Elisabeth; Yu, Jin; Abecasis, Goncalo; Andreassen, Ole A; Breen, Gerome; Christiansen, Lene; Debrabant, Birgit; Dick, Danielle M; Heinz, Andreas; Hjerling-Leffler, Jens; Ikram, M Arfan; Kendler, Kenneth S; Martin, Nicholas G; Medland, Sarah E; Pedersen, Nancy L; Plomin, Robert; Polderman, Tinca J C; Ripke, Stephan; van der Sluis, Sophie; Sullivan, Patrick F; Vrieze, Scott I; Wright, Margaret J; Posthuma, Danielle
2018-06-25
Intelligence is highly heritable 1 and a major determinant of human health and well-being 2 . Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence 3-7 , but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.
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Genetic architecture of adiposity and organ weight using combined generation QTL analysis.
Fawcett, Gloria L; Roseman, Charles C; Jarvis, Joseph P; Wang, Bing; Wolf, Jason B; Cheverud, James M
2008-08-01
We present here a detailed study of the genetic contributions to adult body size and adiposity in the LG,SM advanced intercross line (AIL), an obesity model. This study represents a first step in fine-mapping obesity quantitative trait loci (QTLs) in an AIL. QTLs for adiposity in this model were previously isolated to chromosomes 1, 6, 7, 8, 9, 12, 13, and 18. This study focuses on heritable contributions and the genetic architecture of fatpad and organ weights. We analyzed both the F(2) and F(3) generations of the LG,SM AIL population single-nucleotide polymorphism (SNP) genotyped with a marker density of approximately 4 cM. We replicate 88% of the previously identified obesity QTLs and identify 13 new obesity QTLs. Nearly half of the single-trait QTLs were sex-specific. Several broad QTL regions were resolved into multiple, narrower peaks. The 113 single-trait QTLs for organs and body weight clustered into 27 pleiotropic loci. A large number of epistatic interactions are described which begin to elucidate potential interacting molecular networks. We present a relatively rapid means to obtain fine-mapping details from AILs using dense marker maps and consecutive generations. Analysis of the complex genetic architecture underlying fatpad and organ weights in this model may eventually help to elucidate not only heritable contributions to obesity but also common gene sets for obesity and its comorbidities.
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Genetic and environmental factors affecting cryptic variations in gene regulatory networks
2013-01-01
Background Cryptic genetic variation (CGV) is considered to facilitate phenotypic evolution by producing visible variations in response to changes in the internal and/or external environment. Several mechanisms enabling the accumulation and release of CGVs have been proposed. In this study, we focused on gene regulatory networks (GRNs) as an important mechanism for producing CGVs, and examined how interactions between GRNs and the environment influence the number of CGVs by using individual-based simulations. Results Populations of GRNs were allowed to evolve under various stabilizing selections, and we then measured the number of genetic and phenotypic variations that had arisen. Our results showed that CGVs were not depleted irrespective of the strength of the stabilizing selection for each phenotype, whereas the visible fraction of genetic variation in a population decreased with increasing strength of selection. On the other hand, increasing the number of different environments that individuals encountered within their lifetime (i.e., entailing plastic responses to multiple environments) suppressed the accumulation of CGVs, whereas the GRNs with more genes and interactions were favored in such heterogeneous environments. Conclusions Given the findings that the number of CGVs in a population was largely determined by the size (order) of GRNs, we propose that expansion of GRNs and adaptation to novel environments are mutually facilitating and sustainable sources of evolvability and hence the origins of biological diversity and complexity. PMID:23622056
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Genetic and environmental factors affecting cryptic variations in gene regulatory networks.
Iwasaki, Watal M; Tsuda, Masaki E; Kawata, Masakado
2013-04-26
Cryptic genetic variation (CGV) is considered to facilitate phenotypic evolution by producing visible variations in response to changes in the internal and/or external environment. Several mechanisms enabling the accumulation and release of CGVs have been proposed. In this study, we focused on gene regulatory networks (GRNs) as an important mechanism for producing CGVs, and examined how interactions between GRNs and the environment influence the number of CGVs by using individual-based simulations. Populations of GRNs were allowed to evolve under various stabilizing selections, and we then measured the number of genetic and phenotypic variations that had arisen. Our results showed that CGVs were not depleted irrespective of the strength of the stabilizing selection for each phenotype, whereas the visible fraction of genetic variation in a population decreased with increasing strength of selection. On the other hand, increasing the number of different environments that individuals encountered within their lifetime (i.e., entailing plastic responses to multiple environments) suppressed the accumulation of CGVs, whereas the GRNs with more genes and interactions were favored in such heterogeneous environments. Given the findings that the number of CGVs in a population was largely determined by the size (order) of GRNs, we propose that expansion of GRNs and adaptation to novel environments are mutually facilitating and sustainable sources of evolvability and hence the origins of biological diversity and complexity.
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Knüppel, Sven; Meidtner, Karina; Arregui, Maria; Holzhütter, Hermann-Georg; Boeing, Heiner
2015-07-01
Analyzing multiple single nucleotide polymorphisms (SNPs) is a promising approach to finding genetic effects beyond single-locus associations. We proposed the use of multilocus stepwise regression (MSR) to screen for allele combinations as a method to model joint effects, and compared the results with the often used genetic risk score (GRS), conventional stepwise selection, and the shrinkage method LASSO. In contrast to MSR, the GRS, conventional stepwise selection, and LASSO model each genotype by the risk allele doses. We reanalyzed 20 unlinked SNPs related to type 2 diabetes (T2D) in the EPIC-Potsdam case-cohort study (760 cases, 2193 noncases). No SNP-SNP interactions and no nonlinear effects were found. Two SNP combinations selected by MSR (Nagelkerke's R² = 0.050 and 0.048) included eight SNPs with mean allele combination frequency of 2%. GRS and stepwise selection selected nearly the same SNP combinations consisting of 12 and 13 SNPs (Nagelkerke's R² ranged from 0.020 to 0.029). LASSO showed similar results. The MSR method showed the best model fit measured by Nagelkerke's R² suggesting that further improvement may render this method a useful tool in genetic research. However, our comparison suggests that the GRS is a simple way to model genetic effects since it does not consider linkage, SNP-SNP interactions, and no non-linear effects. © 2015 John Wiley & Sons Ltd/University College London.
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Genetic and epigenetic effects in sex determination.
Gunes, Sezgin Ozgur; Metin Mahmutoglu, Asli; Agarwal, Ashok
2016-12-01
Sex determination is a complex and dynamic process with multiple genetic and environmental causes, in which germ and somatic cells receive various sex-specific features. During the fifth week of fetal life, the bipotential embryonic gonad starts to develop in humans. In the bipotential gonadal tissue, certain cell groups start to differentiate to form the ovaries or testes. Despite considerable efforts and advances in identifying the mechanisms playing a role in sex determination and differentiation, the underlying mechanisms of the exact functions of many genes, gene-gene interactions, and epigenetic modifications that are involved in different stages of this cascade are not completely understood. This review aims at discussing current data on the genetic effects via genes and epigenetic mechanisms that affect the regulation of sex determination. Birth Defects Research (Part C) 108:321-336, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
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Shadows of complexity: what biological networks reveal about epistasis and pleiotropy
Tyler, Anna L.; Asselbergs, Folkert W.; Williams, Scott M.; Moore, Jason H.
2011-01-01
Pleiotropy, in which one mutation causes multiple phenotypes, has traditionally been seen as a deviation from the conventional observation in which one gene affects one phenotype. Epistasis, or gene-gene interaction, has also been treated as an exception to the Mendelian one gene-one phenotype paradigm. This simplified perspective belies the pervasive complexity of biology and hinders progress toward a deeper understanding of biological systems. We assert that epistasis and pleiotropy are not isolated occurrences, but ubiquitous and inherent properties of biomolecular networks. These phenomena should not be treated as exceptions, but rather as fundamental components of genetic analyses. A systems level understanding of epistasis and pleiotropy is, therefore, critical to furthering our understanding of human genetics and its contribution to common human disease. Finally, graph theory offers an intuitive and powerful set of tools with which to study the network bases of these important genetic phenomena. PMID:19204994
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Tops, Sanne; Habel, Ute; Radke, Sina
2018-03-12
Oxytocin and the oxytocin receptor (OXTR) play an important role in a large variety of social behaviors. The oxytocinergic system interacts with environmental cues and is highly dependent on interindividual factors. Deficits in this system have been linked to mental disorders associated with social impairments, such as autism spectrum disorder (ASD). This review focuses on the modulation of social behavior by alterations in two domains of the oxytocinergic system. We discuss genetic and epigenetic regulatory mechanisms and alterations in these mechanisms that were found to have clinical implications for ASD. We propose possible explanations how these alterations affect the biological pathways underlying the aberrant social behavior and point out avenues for future research. We advocate the need for integration studies that combine multiple measures covering a broad range of social behaviors and link these to genetic and epigenetic profiles. Copyright © 2018. Published by Elsevier Inc.
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Personalized Approaches to Clopidogrel Therapy: Are We There Yet?
Anderson, Christopher D.; Biffi, Alessandro; Greenberg, Steven M.; Rosand, Jonathan
2010-01-01
Clopidogrel is one of the most commonly prescribed medications world-wide. Recent advisories from the US Food and Drug Administration (FDA) have drawn attention to the possibility of personalized decision-making for individuals who are candidates for clopidogrel. As is the case with antihypertensives, statins and warfarin, common genetic sequence variants can influence clopidogrel metabolism and its effect on platelet activity. These genetic variants have, in multiple studies, been associated with adverse clinical outcomes. Concurrent medication use also influences the body's handling of clopidogrel. Proton pump inhibitors, widely prescribed in conjunction with clopidogrel, may blunt its effectiveness. We address implications for bedside decision-making in light of accumulated data and current FDA advisories, and conclude that genetic testing for CYP2C19 genotype and limitation of PPI interactions do not yet appear to offer an opportunity to optimize treatment given the current state of knowledge. PMID:21030701
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Bmp signaling mediates endoderm pouch morphogenesis by regulating Fgf signaling in zebrafish.
Lovely, C Ben; Swartz, Mary E; McCarthy, Neil; Norrie, Jacqueline L; Eberhart, Johann K
2016-06-01
The endodermal pouches are a series of reiterated structures that segment the pharyngeal arches and help pattern the vertebrate face. Multiple pathways regulate the complex process of endodermal development, including the Bone morphogenetic protein (Bmp) pathway. However, the role of Bmp signaling in pouch morphogenesis is poorly understood. Using genetic and chemical inhibitor approaches, we show that pouch morphogenesis requires Bmp signaling from 10-18 h post-fertilization, immediately following gastrulation. Blocking Bmp signaling during this window results in morphological defects to the pouches and craniofacial skeleton. Using genetic chimeras we show that Bmp signals directly to the endoderm for proper morphogenesis. Time-lapse imaging and analysis of reporter transgenics show that Bmp signaling is necessary for pouch outpocketing via the Fibroblast growth factor (Fgf) pathway. Double loss-of-function analyses demonstrate that Bmp and Fgf signaling interact synergistically in craniofacial development. Collectively, our analyses shed light on the tissue and signaling interactions that regulate development of the vertebrate face. © 2016. Published by The Company of Biologists Ltd.
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Discovering Hematopoietic Mechanisms Through Genome-Wide Analysis of GATA Factor Chromatin Occupancy
Fujiwara, Tohru; O'Geen, Henriette; Keles, Sunduz; Blahnik, Kimberly; Linnemann, Amelia K.; Kang, Yoon-A; Choi, Kyunghee; Farnham, Peggy J.; Bresnick, Emery H.
2009-01-01
SUMMARY GATA factors interact with simple DNA motifs (WGATAR) to regulate critical processes, including hematopoiesis, but very few WGATAR motifs are occupied in genomes. Given the rudimentary knowledge of mechanisms underlying this restriction, and how GATA factors establish genetic networks, we used ChIP-seq to define GATA-1 and GATA-2 occupancy genome-wide in erythroid cells. Coupled with genetic complementation analysis and transcriptional profiling, these studies revealed a rich collection of targets containing a characteristic binding motif of greater complexity than WGATAR. GATA factors occupied loci encoding multiple components of the Scl/TAL1 complex, a master regulator of hematopoiesis and leukemogenic target. Mechanistic analyses provided evidence for cross-regulatory and autoregulatory interactions among components of this complex, including GATA-2 induction of the hematopoietic corepressor ETO-2 and an ETO-2 negative autoregulatory loop. These results establish fundamental principles underlying GATA factor mechanisms in chromatin and illustrate a complex network of considerable importance for the control of hematopoiesis. PMID:19941826
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Bmp signaling mediates endoderm pouch morphogenesis by regulating Fgf signaling in zebrafish
Swartz, Mary E.; McCarthy, Neil; Norrie, Jacqueline L.; Eberhart, Johann K.
2016-01-01
The endodermal pouches are a series of reiterated structures that segment the pharyngeal arches and help pattern the vertebrate face. Multiple pathways regulate the complex process of endodermal development, including the Bone morphogenetic protein (Bmp) pathway. However, the role of Bmp signaling in pouch morphogenesis is poorly understood. Using genetic and chemical inhibitor approaches, we show that pouch morphogenesis requires Bmp signaling from 10-18 h post-fertilization, immediately following gastrulation. Blocking Bmp signaling during this window results in morphological defects to the pouches and craniofacial skeleton. Using genetic chimeras we show that Bmp signals directly to the endoderm for proper morphogenesis. Time-lapse imaging and analysis of reporter transgenics show that Bmp signaling is necessary for pouch outpocketing via the Fibroblast growth factor (Fgf) pathway. Double loss-of-function analyses demonstrate that Bmp and Fgf signaling interact synergistically in craniofacial development. Collectively, our analyses shed light on the tissue and signaling interactions that regulate development of the vertebrate face. PMID:27122171
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Genetic and environmental influences on the development of alcoholism: resilience vs. risk.
Enoch, Mary-Anne
2006-12-01
The physiological changes of adolescence may promote risk-taking behaviors, including binge drinking. Approximately 40% of alcoholics were already drinking heavily in late adolescence. Most cases of alcoholism are established by the age of 30 years with the peak prevalence at 18-23 years of age. Therefore the key time frame for the development, and prevention, of alcoholism lies in adolescence and young adulthood. Severe childhood stressors have been associated with increased vulnerability to addiction, however, not all stress-exposed children go on to develop alcoholism. Origins of resilience can be both genetic (variation in alcohol-metabolizing genes, increased susceptibility to alcohol's sedative effects) and environmental (lack of alcohol availability, positive peer and parental support). Genetic vulnerability is likely to be conferred by multiple genes of small to modest effects, possibly only apparent in gene-environment interactions. For example, it has been shown that childhood maltreatment interacts with a monoamine oxidase A (MAOA) gene variant to predict antisocial behavior that is often associated with alcoholism, and an interaction between early life stress and a serotonin transporter promoter variant predicts alcohol abuse in nonhuman primates and depression in humans. In addition, a common Met158 variant in the catechol-O-methyltransferase (COMT) gene can confer both risk and resilience to alcoholism in different drinking environments. It is likely that a complex mix of gene(s)-environment(s) interactions underlie addiction vulnerability and development. Risk-resilience factors can best be determined in longitudinal studies, preferably starting during pregnancy. This kind of research is important for planning future measures to prevent harmful drinking in adolescence.
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Song, Nan; Shin, Aesun; Oh, Jae Hwan; Kim, Jeongseon
2018-01-01
Background Genome-wide association studies (GWAS) have identified approximately 40 common genetic loci associated with colorectal cancer risk. To investigate possible gene-environment interactions (GEIs) between GWAS-identified single-nucleotide polymorphisms (SNPs) and alcohol consumption with respect to colorectal cancer, a hospital-based case-control study was conducted. Results Higher levels of alcohol consumption as calculated based on a standardized definition of a drink (1 drink=12.5g of ethanol) were associated with increased risk of colorectal cancer (OR=2.47, 95% CI=1.62-3.76 for heavy drinkers [>50g/day] compared to never drinkers; ptrend<0.01). SNP rs6687758 near the DUSP10 gene at 1q41 had a statistically significant interaction with alcohol consumption in analyses of standardized drinks (p=4.6×10-3), although this did not surpass the corrected threshold for multiple testing. When stratified by alcohol consumption levels, in an additive model the risk of colorectal cancer associated with the G allele of rs6687758 tended to increase among individuals in the heavier alcohol consumption strata. A statistically significant association between rs6687758 and colorectal cancer risk was observed among moderate alcohol drinkers who consumed between >12.5 and ≤50g of alcohol per day (OR=1.46, 95% CI=1.01-2.11). Methods A total of 2,109 subjects (703 colorectal cancer patients and 1,406 healthy controls) were recruited from the Korean National Cancer Center. For genotyping, 30 GWAS-identified SNPs were selected. A logistic regression model was used to evaluate associations of SNPs and alcohol consumption with colorectal cancer risk. We also tested GEIs between SNPs and alcohol consumption using a logistic model with multiplicative interaction terms. Conclusions Our results suggest that SNP rs6687758 at 1q41 may interact with alcohol consumption in the etiology of colorectal cancer. PMID:29464080
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Song, Nan; Shin, Aesun; Oh, Jae Hwan; Kim, Jeongseon
2018-01-19
Genome-wide association studies (GWAS) have identified approximately 40 common genetic loci associated with colorectal cancer risk. To investigate possible gene-environment interactions (GEIs) between GWAS-identified single-nucleotide polymorphisms (SNPs) and alcohol consumption with respect to colorectal cancer, a hospital-based case-control study was conducted. Higher levels of alcohol consumption as calculated based on a standardized definition of a drink (1 drink=12.5g of ethanol) were associated with increased risk of colorectal cancer (OR=2.47, 95% CI=1.62-3.76 for heavy drinkers [>50g/day] compared to never drinkers; p trend <0.01). SNP rs6687758 near the DUSP10 gene at 1q41 had a statistically significant interaction with alcohol consumption in analyses of standardized drinks ( p =4.6×10 -3 ), although this did not surpass the corrected threshold for multiple testing. When stratified by alcohol consumption levels, in an additive model the risk of colorectal cancer associated with the G allele of rs6687758 tended to increase among individuals in the heavier alcohol consumption strata. A statistically significant association between rs6687758 and colorectal cancer risk was observed among moderate alcohol drinkers who consumed between >12.5 and ≤50g of alcohol per day (OR=1.46, 95% CI=1.01-2.11). A total of 2,109 subjects (703 colorectal cancer patients and 1,406 healthy controls) were recruited from the Korean National Cancer Center. For genotyping, 30 GWAS-identified SNPs were selected. A logistic regression model was used to evaluate associations of SNPs and alcohol consumption with colorectal cancer risk. We also tested GEIs between SNPs and alcohol consumption using a logistic model with multiplicative interaction terms. Our results suggest that SNP rs6687758 at 1q41 may interact with alcohol consumption in the etiology of colorectal cancer.
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Larsen, Lesli H; Angquist, Lars; Vimaleswaran, Karani S; Hager, Jörg; Viguerie, Nathalie; Loos, Ruth J F; Handjieva-Darlenska, Teodora; Jebb, Susan A; Kunesova, Marie; Larsen, Thomas M; Martinez, J Alfredo; Papadaki, Angeliki; Pfeiffer, Andreas F H; van Baak, Marleen A; Sørensen, Thorkild Ia; Holst, Claus; Langin, Dominique; Astrup, Arne; Saris, Wim H M
2012-05-01
Differences in the interindividual response to dietary intervention could be modified by genetic variation in nutrient-sensitive genes. This study examined single nucleotide polymorphisms (SNPs) in presumed nutrient-sensitive candidate genes for obesity and obesity-related diseases for main and dietary interaction effects on weight, waist circumference, and fat mass regain over 6 mo. In total, 742 participants who had lost ≥ 8% of their initial body weight were randomly assigned to follow 1 of 5 different ad libitum diets with different glycemic indexes and contents of dietary protein. The SNP main and SNP-diet interaction effects were analyzed by using linear regression models, corrected for multiple testing by using Bonferroni correction and evaluated by using quantile-quantile (Q-Q) plots. After correction for multiple testing, none of the SNPs were significantly associated with weight, waist circumference, or fat mass regain. Q-Q plots showed that ALOX5AP rs4769873 showed a higher observed than predicted P value for the association with less waist circumference regain over 6 mo (-3.1 cm/allele; 95% CI: -4.6, -1.6; P/Bonferroni-corrected P = 0.000039/0.076), independently of diet. Additional associations were identified by using Q-Q plots for SNPs in ALOX5AP, TNF, and KCNJ11 for main effects; in LPL and TUB for glycemic index interaction effects on waist circumference regain; in GHRL, CCK, MLXIPL, and LEPR on weight; in PPARC1A, PCK2, ALOX5AP, PYY, and ADRB3 on waist circumference; and in PPARD, FABP1, PLAUR, and LPIN1 on fat mass regain for dietary protein interaction. The observed effects of SNP-diet interactions on weight, waist, and fat mass regain suggest that genetic variation in nutrient-sensitive genes can modify the response to diet. This trial was registered at clinicaltrials.gov as NCT00390637.
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Sun Exposure, Vitamin D Receptor Polymorphisms FokI and BsmI and Risk of Multiple Primary Melanoma
Mandelcorn-Monson, Rochelle; Marrett, Loraine; Kricker, Anne; Armstrong, Bruce K.; Orlow, Irene; Goumas, Chris; Paine, Susan; Rosso, Stefano; Thomas, Nancy; Millikan, Robert C.; Pole, Jason D.; Cotignola, Javier; Rosen, Cheryl; Kanetsky, Peter A.; Lee-Taylor, Julia; Begg, Colin B.; Berwick, Marianne
2011-01-01
Sunlight exposure increases risk of melanoma. Sunlight also potentiates cutaneous synthesis of vitamin D, which can inhibit melanoma cell growth and promote apoptosis. Vitamin D effects are mediated through the vitamin D receptor (VDR). We hypothesized that genetic variation in VDR affects the relationship of sun exposure to risk of a further melanoma in people who have already had one. We investigated the interaction between VDR polymorphisms and sun exposure in a population-based multinational study comparing 1138 patients with a multiple (second or subsequent) primary melanoma (cases) to 2151 patients with a first primary melanoma (controls); essentially a case-control study of melanoma in a population of melanoma survivors. Sun exposure was assessed using a questionnaire and interview, and was shown to be associated with multiple primary melanoma. VDR was genotyped at the FokI and BsmI loci and the main effects of variants at these loci and their interactions with sun exposure were analyzed. Only the BsmI variant was associated with multiple primary melanoma (OR = 1.27, 95% CI 0.99-1.62 for the homozygous variant genotype). Joint effects analyses showed highest ORs in the high exposure, homozygous variant BsmI genotype category for each sun exposure variable. Stratified analyses showed somewhat higher ORs for the homozygous BsmI variant genotype in people with high sun exposure than with low sun exposure. P values for interaction, however, were high. These results suggest that risk of multiple primary melanoma is increased in people who have the BsmI variant of VDR. PMID:21612999
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Sánchez, Brisa N; Kang, Shan; Mukherjee, Bhramar
2012-06-01
Many existing cohort studies initially designed to investigate disease risk as a function of environmental exposures have collected genomic data in recent years with the objective of testing for gene-environment interaction (G × E) effects. In environmental epidemiology, interest in G × E arises primarily after a significant effect of the environmental exposure has been documented. Cohort studies often collect rich exposure data; as a result, assessing G × E effects in the presence of multiple exposure markers further increases the burden of multiple testing, an issue already present in both genetic and environment health studies. Latent variable (LV) models have been used in environmental epidemiology to reduce dimensionality of the exposure data, gain power by reducing multiplicity issues via condensing exposure data, and avoid collinearity problems due to presence of multiple correlated exposures. We extend the LV framework to characterize gene-environment interaction in presence of multiple correlated exposures and genotype categories. Further, similar to what has been done in case-control G × E studies, we use the assumption of gene-environment (G-E) independence to boost the power of tests for interaction. The consequences of making this assumption, or the issue of how to explicitly model G-E association has not been previously investigated in LV models. We postulate a hierarchy of assumptions about the LV model regarding the different forms of G-E dependence and show that making such assumptions may influence inferential results on the G, E, and G × E parameters. We implement a class of shrinkage estimators to data adaptively trade-off between the most restrictive to most flexible form of G-E dependence assumption and note that such class of compromise estimators can serve as a benchmark of model adequacy in LV models. We demonstrate the methods with an example from the Early Life Exposures in Mexico City to Neuro-Toxicants Study of lead exposure, iron metabolism genes, and birth weight. © 2011, The International Biometric Society.
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Lindén, Rolf O; Eronen, Ville-Pekka; Aittokallio, Tero
2011-03-24
High-throughput genetic screening approaches have enabled systematic means to study how interactions among gene mutations contribute to quantitative fitness phenotypes, with the aim of providing insights into the functional wiring diagrams of genetic interaction networks on a global scale. However, it is poorly known how well these quantitative interaction measurements agree across the screening approaches, which hinders their integrated use toward improving the coverage and quality of the genetic interaction maps in yeast and other organisms. Using large-scale data matrices from epistatic miniarray profiling (E-MAP), genetic interaction mapping (GIM), and synthetic genetic array (SGA) approaches, we carried out here a systematic comparative evaluation among these quantitative maps of genetic interactions in yeast. The relatively low association between the original interaction measurements or their customized scores could be improved using a matrix-based modelling framework, which enables the use of single- and double-mutant fitness estimates and measurements, respectively, when scoring genetic interactions. Toward an integrative analysis, we show how the detections from the different screening approaches can be combined to suggest novel positive and negative interactions which are complementary to those obtained using any single screening approach alone. The matrix approximation procedure has been made available to support the design and analysis of the future screening studies. We have shown here that even if the correlation between the currently available quantitative genetic interaction maps in yeast is relatively low, their comparability can be improved by means of our computational matrix approximation procedure, which will enable integrative analysis and detection of a wider spectrum of genetic interactions using data from the complementary screening approaches.
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Wille, Lukas; Messmer, Monika M; Studer, Bruno; Hohmann, Pierre
2018-04-12
Root and foot diseases severely impede grain legume cultivation worldwide. Breeding lines with resistance against individual pathogens exist, but these resistances are often overcome by the interaction of multiple pathogens in field situations. Novel tools allow to decipher plant-microbiome interactions in unprecedented detail and provide insights into resistance mechanisms that consider both simultaneous attacks of various pathogens and the interplay with beneficial microbes. Although it has become clear that plant-associated microbes play a key role in plant health, a systematic picture of how and to what extend plants can shape their own detrimental or beneficial microbiome remains to be drawn. There is increasing evidence for the existence of genetic variation in the regulation of plant-microbe interactions that can be exploited by plant breeders. We propose to consider the entire plant holobiont in resistance breeding strategies in order to unravel hidden parts of complex defence mechanisms. This review summarises (i) the current knowledge of resistance against soil-borne pathogens in grain legumes, (ii) evidence for genetic variation for rhizosphere-related traits, (iii) the role of root exudation in microbe-mediated disease resistance and elaborates (iv) how these traits can be incorporated in resistance breeding programmes. This article is protected by copyright. All rights reserved.
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Bezemer, N; Krauss, S L; Phillips, R D; Roberts, D G; Hopper, S D
2016-12-01
Optimal foraging behaviour by nectavores is expected to result in a leptokurtic pollen dispersal distribution and predominantly near-neighbour mating. However, complex social interactions among nectarivorous birds may result in different mating patterns to those typically observed in insect-pollinated plants. Mating system, realised pollen dispersal and spatial genetic structure were examined in the bird-pollinated Eucalyptus caesia, a species characterised by small, geographically disjunct populations. Nine microsatellite markers were used to genotype an entire adult stand and 181 seeds from 28 capsules collected from 6 trees. Mating system analysis using MLTR revealed moderate to high outcrossing (t m =0.479-0.806) and low estimates of correlated paternity (r p =0.136±s.e. 0.048). Paternity analysis revealed high outcrossing rates (mean=0.72) and high multiple paternity, with 64 different sires identified for 181 seeds. There was a significant negative relationship between the frequency of outcross mating and distance between mating pairs. Realised mating events were more frequent than expected with random mating for plants <40 m apart. The overall distribution of pollen dispersal distances was platykurtic. Despite extensive pollen dispersal within the stand, three genetic clusters were detected by STRUCTURE analysis. These genetic clusters were strongly differentiated yet geographically interspersed, hypothesised to be a consequence of rare recruitment events coupled with extreme longevity. We suggest that extensive polyandry and pollen dispersal is a consequence of pollination by highly mobile honeyeaters and may buffer E. caesia against the loss of genetic diversity predicted for small and genetically isolated populations.
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Bezemer, N; Krauss, S L; Phillips, R D; Roberts, D G; Hopper, S D
2016-01-01
Optimal foraging behaviour by nectavores is expected to result in a leptokurtic pollen dispersal distribution and predominantly near-neighbour mating. However, complex social interactions among nectarivorous birds may result in different mating patterns to those typically observed in insect-pollinated plants. Mating system, realised pollen dispersal and spatial genetic structure were examined in the bird-pollinated Eucalyptus caesia, a species characterised by small, geographically disjunct populations. Nine microsatellite markers were used to genotype an entire adult stand and 181 seeds from 28 capsules collected from 6 trees. Mating system analysis using MLTR revealed moderate to high outcrossing (tm=0.479–0.806) and low estimates of correlated paternity (rp=0.136±s.e. 0.048). Paternity analysis revealed high outcrossing rates (mean=0.72) and high multiple paternity, with 64 different sires identified for 181 seeds. There was a significant negative relationship between the frequency of outcross mating and distance between mating pairs. Realised mating events were more frequent than expected with random mating for plants <40 m apart. The overall distribution of pollen dispersal distances was platykurtic. Despite extensive pollen dispersal within the stand, three genetic clusters were detected by STRUCTURE analysis. These genetic clusters were strongly differentiated yet geographically interspersed, hypothesised to be a consequence of rare recruitment events coupled with extreme longevity. We suggest that extensive polyandry and pollen dispersal is a consequence of pollination by highly mobile honeyeaters and may buffer E. caesia against the loss of genetic diversity predicted for small and genetically isolated populations. PMID:27530908
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Scaling laws and universality for the strength of genetic interactions in yeast
NASA Astrophysics Data System (ADS)
Velenich, Andrea; Dai, Mingjie; Gore, Jeff
2012-02-01
Genetic interactions provide a window to the organization of the thousands of biochemical reactions in living cells. If two mutations affect unrelated cellular functions, the fitness effects of their combination can be easily predicted from the two separate fitness effects. However, because of interactions, for some pairs of mutations their combined fitness effect deviates from the naive prediction. We study genetic interactions in yeast cells by analyzing a publicly available database containing experimental growth rates of 5 million double mutants. We show that the characteristic strength of genetic interactions has a simple power law dependence on the fitness effects of the two interacting mutations and that the probability distribution of genetic interactions is a universal function. We further argue that the strength of genetic interactions depends only on the fitness effects of the interacting mutations and not on their biological origin in terms of single point mutations, entire gene knockouts or even more complicated physiological perturbations. Finally, we discuss the implications of the power law scaling of genetic interactions on the ruggedness of fitness landscapes and the consequent evolutionary dynamics.
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Global Mapping of the Yeast Genetic Interaction Network
NASA Astrophysics Data System (ADS)
Tong, Amy Hin Yan; Lesage, Guillaume; Bader, Gary D.; Ding, Huiming; Xu, Hong; Xin, Xiaofeng; Young, James; Berriz, Gabriel F.; Brost, Renee L.; Chang, Michael; Chen, YiQun; Cheng, Xin; Chua, Gordon; Friesen, Helena; Goldberg, Debra S.; Haynes, Jennifer; Humphries, Christine; He, Grace; Hussein, Shamiza; Ke, Lizhu; Krogan, Nevan; Li, Zhijian; Levinson, Joshua N.; Lu, Hong; Ménard, Patrice; Munyana, Christella; Parsons, Ainslie B.; Ryan, Owen; Tonikian, Raffi; Roberts, Tania; Sdicu, Anne-Marie; Shapiro, Jesse; Sheikh, Bilal; Suter, Bernhard; Wong, Sharyl L.; Zhang, Lan V.; Zhu, Hongwei; Burd, Christopher G.; Munro, Sean; Sander, Chris; Rine, Jasper; Greenblatt, Jack; Peter, Matthias; Bretscher, Anthony; Bell, Graham; Roth, Frederick P.; Brown, Grant W.; Andrews, Brenda; Bussey, Howard; Boone, Charles
2004-02-01
A genetic interaction network containing ~1000 genes and ~4000 interactions was mapped by crossing mutations in 132 different query genes into a set of ~4700 viable gene yeast deletion mutants and scoring the double mutant progeny for fitness defects. Network connectivity was predictive of function because interactions often occurred among functionally related genes, and similar patterns of interactions tended to identify components of the same pathway. The genetic network exhibited dense local neighborhoods; therefore, the position of a gene on a partially mapped network is predictive of other genetic interactions. Because digenic interactions are common in yeast, similar networks may underlie the complex genetics associated with inherited phenotypes in other organisms.
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White, Marquitta J.; Tacconelli, Alessandra; Chen, Jane S.; Wejse, Christian; Hill, Philip C.; Gomez, Victor F; Velez-Edwards, Digna R.; Østergaard, Lars J.; Hu, Ting; Moore, Jason H.; Novelli, Giuseppe; Scott, William K.; Williams, Scott M.; Sirugo, Giorgio
2017-01-01
We analyzed two West African samples (Guinea-Bissau: n = 289 cases, 322 controls; The Gambia: n = 240 cases, 248 controls) to evaluate single nucleotide polymorphisms (SNPs) in Epiregulin (EREG) and V-ATPase (T cell immune regulator 1, TCIRG1) using single and multi-locus analyses to determine whether previously described associations with pulmonary tuberculosis (PTB) in Vietnamese and Italians would replicate in African populations. We did not detect any significant single locus or haplotype associations in either sample. We also performed exploratory pairwise interaction analyses using Visualization of Statistical Epistasis Networks (ViSEN), a novel method to detect only interactions among multiple variables, to elucidate possible interaction effects between SNPs and demographic factors. Although we found no strong evidence of marginal effects, there were several significant pairwise interactions that were identified in either the Guinea-Bissau or The Gambia samples, two of which replicated across populations. Our results indicate that the effects of EREG and TCIRG1 variants on PTB susceptibility, to the extent that they exist, are dependent on gene-gene interactions in West African populations as detected with ViSEN. In addition, epistatic effects are likely to be influenced by inter- and intra-population differences in genetic or environmental context and/or the mycobacterial lineages causing disease. PMID:24898387
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NASA Astrophysics Data System (ADS)
Babbar-Sebens, M.; Minsker, B. S.
2006-12-01
In the water resources management field, decision making encompasses many kinds of engineering, social, and economic constraints and objectives. Representing all of these problem dependant criteria through models (analytical or numerical) and various formulations (e.g., objectives, constraints, etc.) within an optimization- simulation system can be a very non-trivial issue. Most models and formulations utilized for discerning desirable traits in a solution can only approximate the decision maker's (DM) true preference criteria, and they often fail to consider important qualitative and incomputable phenomena related to the management problem. In our research, we have proposed novel decision support frameworks that allow DMs to actively participate in the optimization process. The DMs explicitly indicate their true preferences based on their subjective criteria and the results of various simulation models and formulations. The feedback from the DMs is then used to guide the search process towards solutions that are "all-rounders" from the perspective of the DM. The two main research questions explored in this work are: a) Does interaction between the optimization algorithm and a DM assist the system in searching for groundwater monitoring designs that are robust from the DM's perspective?, and b) How can an interactive search process be made more effective when human factors, such as human fatigue and cognitive learning processes, affect the performance of the algorithm? The application of these frameworks on a real-world groundwater long-term monitoring (LTM) case study in Michigan highlighted the following salient advantages: a) in contrast to the non-interactive optimization methodology, the proposed interactive frameworks were able to identify low cost monitoring designs whose interpolation maps respected the expected spatial distribution of the contaminants, b) for many same-cost designs, the interactive methodologies were able to propose multiple alternatives that met the DM's preference criteria, therefore allowing the expert to select among several strong candidate designs depending on her/his LTM budget, c) two of the methodologies - Case-Based Micro Interactive Genetic Algorithm (CBMIGA) and Interactive Genetic Algorithm with Mixed Initiative Interaction (IGAMII) - were also able to assist in controlling human fatigue and adapt to the DM's learning process.
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Leblond, Claire S; Heinrich, Jutta; Delorme, Richard; Proepper, Christian; Betancur, Catalina; Huguet, Guillaume; Konyukh, Marina; Chaste, Pauline; Ey, Elodie; Rastam, Maria; Anckarsäter, Henrik; Nygren, Gudrun; Gillberg, I Carina; Melke, Jonas; Toro, Roberto; Regnault, Beatrice; Fauchereau, Fabien; Mercati, Oriane; Lemière, Nathalie; Skuse, David; Poot, Martin; Holt, Richard; Monaco, Anthony P; Järvelä, Irma; Kantojärvi, Katri; Vanhala, Raija; Curran, Sarah; Collier, David A; Bolton, Patrick; Chiocchetti, Andreas; Klauck, Sabine M; Poustka, Fritz; Freitag, Christine M; Waltes, Regina; Kopp, Marnie; Duketis, Eftichia; Bacchelli, Elena; Minopoli, Fiorella; Ruta, Liliana; Battaglia, Agatino; Mazzone, Luigi; Maestrini, Elena; Sequeira, Ana F; Oliveira, Barbara; Vicente, Astrid; Oliveira, Guiomar; Pinto, Dalila; Scherer, Stephen W; Zelenika, Diana; Delepine, Marc; Lathrop, Mark; Bonneau, Dominique; Guinchat, Vincent; Devillard, Françoise; Assouline, Brigitte; Mouren, Marie-Christine; Leboyer, Marion; Gillberg, Christopher; Boeckers, Tobias M; Bourgeron, Thomas
2012-02-01
Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental disorders with a complex inheritance pattern. While many rare variants in synaptic proteins have been identified in patients with ASD, little is known about their effects at the synapse and their interactions with other genetic variations. Here, following the discovery of two de novo SHANK2 deletions by the Autism Genome Project, we identified a novel 421 kb de novo SHANK2 deletion in a patient with autism. We then sequenced SHANK2 in 455 patients with ASD and 431 controls and integrated these results with those reported by Berkel et al. 2010 (n = 396 patients and n = 659 controls). We observed a significant enrichment of variants affecting conserved amino acids in 29 of 851 (3.4%) patients and in 16 of 1,090 (1.5%) controls (P = 0.004, OR = 2.37, 95% CI = 1.23-4.70). In neuronal cell cultures, the variants identified in patients were associated with a reduced synaptic density at dendrites compared to the variants only detected in controls (P = 0.0013). Interestingly, the three patients with de novo SHANK2 deletions also carried inherited CNVs at 15q11-q13 previously associated with neuropsychiatric disorders. In two cases, the nicotinic receptor CHRNA7 was duplicated and in one case the synaptic translation repressor CYFIP1 was deleted. These results strengthen the role of synaptic gene dysfunction in ASD but also highlight the presence of putative modifier genes, which is in keeping with the "multiple hit model" for ASD. A better knowledge of these genetic interactions will be necessary to understand the complex inheritance pattern of ASD.
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Leblond, Claire S.; Heinrich, Jutta; Delorme, Richard; Proepper, Christian; Betancur, Catalina; Huguet, Guillaume; Konyukh, Marina; Chaste, Pauline; Ey, Elodie; Rastam, Maria; Anckarsäter, Henrik; Nygren, Gudrun; Gillberg, I. Carina; Melke, Jonas; Toro, Roberto; Regnault, Beatrice; Fauchereau, Fabien; Mercati, Oriane; Lemière, Nathalie; Skuse, David; Poot, Martin; Holt, Richard; Monaco, Anthony P.; Järvelä, Irma; Kantojärvi, Katri; Vanhala, Raija; Curran, Sarah; Collier, David A.; Bolton, Patrick; Chiocchetti, Andreas; Klauck, Sabine M.; Poustka, Fritz; Freitag, Christine M.; Waltes, Regina; Kopp, Marnie; Duketis, Eftichia; Bacchelli, Elena; Minopoli, Fiorella; Ruta, Liliana; Battaglia, Agatino; Mazzone, Luigi; Maestrini, Elena; Sequeira, Ana F.; Oliveira, Barbara; Vicente, Astrid; Oliveira, Guiomar; Pinto, Dalila; Scherer, Stephen W.; Zelenika, Diana; Delepine, Marc; Lathrop, Mark; Bonneau, Dominique; Guinchat, Vincent; Devillard, Françoise; Assouline, Brigitte; Mouren, Marie-Christine; Leboyer, Marion; Gillberg, Christopher; Boeckers, Tobias M.; Bourgeron, Thomas
2012-01-01
Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental disorders with a complex inheritance pattern. While many rare variants in synaptic proteins have been identified in patients with ASD, little is known about their effects at the synapse and their interactions with other genetic variations. Here, following the discovery of two de novo SHANK2 deletions by the Autism Genome Project, we identified a novel 421 kb de novo SHANK2 deletion in a patient with autism. We then sequenced SHANK2 in 455 patients with ASD and 431 controls and integrated these results with those reported by Berkel et al. 2010 (n = 396 patients and n = 659 controls). We observed a significant enrichment of variants affecting conserved amino acids in 29 of 851 (3.4%) patients and in 16 of 1,090 (1.5%) controls (P = 0.004, OR = 2.37, 95% CI = 1.23–4.70). In neuronal cell cultures, the variants identified in patients were associated with a reduced synaptic density at dendrites compared to the variants only detected in controls (P = 0.0013). Interestingly, the three patients with de novo SHANK2 deletions also carried inherited CNVs at 15q11–q13 previously associated with neuropsychiatric disorders. In two cases, the nicotinic receptor CHRNA7 was duplicated and in one case the synaptic translation repressor CYFIP1 was deleted. These results strengthen the role of synaptic gene dysfunction in ASD but also highlight the presence of putative modifier genes, which is in keeping with the “multiple hit model” for ASD. A better knowledge of these genetic interactions will be necessary to understand the complex inheritance pattern of ASD. PMID:22346768
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Wu, Fen; Jasmine, Farzana; Kibriya, Muhammad G; Liu, Mengling; Cheng, Xin; Parvez, Faruque; Islam, Tariqul; Ahmed, Alauddin; Rakibuz-Zaman, Muhammad; Jiang, Jieying; Roy, Shantanu; Paul-Brutus, Rachelle; Slavkovich, Vesna; Islam, Tariqul; Levy, Diane; VanderWeele, Tyler J; Pierce, Brandon L; Graziano, Joseph H; Ahsan, Habibul; Chen, Yu
2015-05-01
Epidemiologic data on genetic susceptibility to cardiovascular effects of arsenic exposure from drinking water are limited. We investigated whether the association between well-water arsenic and cardiovascular disease (CVD) differed by 170 single nucleotide polymorphisms (SNPs) in 17 genes related to arsenic metabolism, oxidative stress, inflammation, and endothelial dysfunction. We conducted a prospective case-cohort study nested in the Health Effects of Arsenic Longitudinal Study, with a random subcohort of 1,375 subjects and 447 incident fatal and nonfatal cases of CVD. Well-water arsenic was measured in 2000 at baseline. The CVD cases, 56 of which occurred in the subcohort, included 238 coronary heart disease cases, 165 stroke cases, and 44 deaths due to other CVD identified during follow-up from 2000 to 2012. Of the 170 SNPs tested, multiplicative interactions between well-water arsenic and two SNPs, rs281432 in ICAM1 (padj = 0.0002) and rs3176867 in VCAM1 (padj = 0.035), were significant for CVD after adjustment for multiple testing. Compared with those with GC or CC genotype in rs281432 and lower well-water arsenic, the adjusted hazard ratio (aHR) for CVD was 1.82 (95% CI: 1.31, 2.54) for a 1-SD increase in well-water arsenic combined with the GG genotype, which was greater than expected given aHRs of 1.08 and 0.96 for separate effects of arsenic and the genotype alone, respectively. Similarly, the joint aHR for arsenic and the rs3176867 CC genotype was 1.34 (95% CI: 0.95, 1.87), greater than expected given aHRs for their separate effects of 1.02 and 0.84, respectively. Associations between CVD and arsenic exposure may be modified by genetic variants related to endothelial dysfunction.
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Díaz-Mejía, J Javier; Celaj, Albi; Mellor, Joseph C; Coté, Atina; Balint, Attila; Ho, Brandon; Bansal, Pritpal; Shaeri, Fatemeh; Gebbia, Marinella; Weile, Jochen; Verby, Marta; Karkhanina, Anna; Zhang, YiFan; Wong, Cassandra; Rich, Justin; Prendergast, D'Arcy; Gupta, Gaurav; Öztürk, Sedide; Durocher, Daniel; Brown, Grant W; Roth, Frederick P
2018-05-28
Condition-dependent genetic interactions can reveal functional relationships between genes that are not evident under standard culture conditions. State-of-the-art yeast genetic interaction mapping, which relies on robotic manipulation of arrays of double-mutant strains, does not scale readily to multi-condition studies. Here, we describe barcode fusion genetics to map genetic interactions (BFG-GI), by which double-mutant strains generated via en masse "party" mating can also be monitored en masse for growth to detect genetic interactions. By using site-specific recombination to fuse two DNA barcodes, each representing a specific gene deletion, BFG-GI enables multiplexed quantitative tracking of double mutants via next-generation sequencing. We applied BFG-GI to a matrix of DNA repair genes under nine different conditions, including methyl methanesulfonate (MMS), 4-nitroquinoline 1-oxide (4NQO), bleomycin, zeocin, and three other DNA-damaging environments. BFG-GI recapitulated known genetic interactions and yielded new condition-dependent genetic interactions. We validated and further explored a subnetwork of condition-dependent genetic interactions involving MAG1 , SLX4, and genes encoding the Shu complex, and inferred that loss of the Shu complex leads to an increase in the activation of the checkpoint protein kinase Rad53. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.
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Common genetic variation within miR-146a predicts disease onset and relapse in multiple sclerosis.
Zhou, Yuan; Chen, Ming; Simpson, Steve; Lucas, Robyn M; Charlesworth, Jac C; Blackburn, Nicholas; van der Mei, Ingrid; Ponsonby, Anne-Louise; Taylor, Bruce V
2018-02-01
Despite extensive studies focusing on the changes in expression of microRNAs (miRNAs) in multiple sclerosis (MS) compared to healthy controls, few studies have evaluated the association of genetic variants of miRNAs with MS clinical course. We investigated whether a functional polymorphism in the MS associated miR-146a gene predicted clinical course (hazard of conversion to MS and of relapse, and annualized change in disability), using a longitudinal cohort study of persons with a first demyelinating event followed up to their 5-year review. We found the genotype (GC+CC) of rs2910164 predicted relapse compared with the GG genotype (HR=2.09 (95% CI 1.42, 3.06), p=0.0001), as well as a near-significant (p=0.07) association with MS conversion risk. Moreover, we found a significant additive interaction between rs2910164 and baseline anti-EBNA-1 IgG titers predicting risk of conversion to MS (relative excess risk due to interaction [RERI] 2.39, p=0.00002) and of relapse (RERI 1.20, p=0.006). Supporting these results, similar results were seen for the other EBV-correlated variables: anti-EBNA-2 IgG titers and past history of infectious mononucleosis. There was no association of rs2910164 genotype for disability progression. Our findings provide evidence for miR-146a and EBV infection in modulating MS clinical course.
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Mahjani, Behrang; Toor, Salman; Nettelblad, Carl; Holmgren, Sverker
2017-01-01
In quantitative trait locus (QTL) mapping significance of putative QTL is often determined using permutation testing. The computational needs to calculate the significance level are immense, 10 4 up to 10 8 or even more permutations can be needed. We have previously introduced the PruneDIRECT algorithm for multiple QTL scan with epistatic interactions. This algorithm has specific strengths for permutation testing. Here, we present a flexible, parallel computing framework for identifying multiple interacting QTL using the PruneDIRECT algorithm which uses the map-reduce model as implemented in Hadoop. The framework is implemented in R, a widely used software tool among geneticists. This enables users to rearrange algorithmic steps to adapt genetic models, search algorithms, and parallelization steps to their needs in a flexible way. Our work underlines the maturity of accessing distributed parallel computing for computationally demanding bioinformatics applications through building workflows within existing scientific environments. We investigate the PruneDIRECT algorithm, comparing its performance to exhaustive search and DIRECT algorithm using our framework on a public cloud resource. We find that PruneDIRECT is vastly superior for permutation testing, and perform 2 ×10 5 permutations for a 2D QTL problem in 15 hours, using 100 cloud processes. We show that our framework scales out almost linearly for a 3D QTL search.
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Kappen, Claudia
2016-01-01
The process of patterning along the anterior-posterior axis in vertebrates is highly conserved. The function of Hox genes in the axis patterning process is particularly well documented for bone development in the vertebral column and the limbs. We here show that Hoxb6, in skeletal elements at the cervico-thoracic junction, controls multiple independent aspects of skeletal pattern, implicating discrete developmental pathways as substrates for this transcription factor. In addition, we demonstrate that Hoxb6 function is subject to modulation by genetic factors. These results establish Hox-controlled skeletal pattern as a quantitative trait modulated by gene-gene interactions, and provide evidence that distinct modifiers influence the function of conserved developmental genes in fundamental patterning processes. PMID:26800342
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Variation of types of alcoholism: review and subtypes identified in Han Chinese.
Lee, Sheng-Yu; Chen, Shiou-Lan; Chang, Yun-Hsuan; Lu, Ru-Band
2014-01-03
Alcoholism, as it has been hypothesized, is caused by a highly heterogeneous genetic load. Since 1960, many reports have used the bio-psycho-social approach to subtype alcoholism; however, no subtypes have been genetically validated. We reviewed and compared the major single-gene, multiple-gene, and gene-to-gene interaction studies on alcoholism published during the past quarter-century, including many recent studies that have made contributions to the subtyping of alcoholism. Four subtypes of alcoholism have been reported: [1] pure alcoholism, [2] anxiety/depression alcoholism, [3] antisocial alcoholism, and [4] mixed alcoholism. Most of the important studies focused on three genes: DRD2, MAOA, and ALDH2. Therefore, our review focuses on these three genes. © 2013.
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Carvalho, Claudia M B; Vasanth, Shivakumar; Shinawi, Marwan; Russell, Chad; Ramocki, Melissa B; Brown, Chester W; Graakjaer, Jesper; Skytte, Anne-Bine; Vianna-Morgante, Angela M; Krepischi, Ana C V; Patel, Gayle S; Immken, LaDonna; Aleck, Kyrieckos; Lim, Cynthia; Cheung, Sau Wai; Rosenberg, Carla; Katsanis, Nicholas; Lupski, James R
2014-11-06
The 17p13.1 microdeletion syndrome is a recently described genomic disorder with a core clinical phenotype of intellectual disability, poor to absent speech, dysmorphic features, and a constellation of more variable clinical features, most prominently microcephaly. We identified five subjects with copy-number variants (CNVs) on 17p13.1 for whom we performed detailed clinical and molecular studies. Breakpoint mapping and retrospective analysis of published cases refined the smallest region of overlap (SRO) for microcephaly to a genomic interval containing nine genes. Dissection of this phenotype in zebrafish embryos revealed a complex genetic architecture: dosage perturbation of four genes (ASGR1, ACADVL, DVL2, and GABARAP) impeded neurodevelopment and decreased dosage of the same loci caused a reduced mitotic index in vitro. Moreover, epistatic analyses in vivo showed that dosage perturbations of discrete gene pairings induce microcephaly. Taken together, these studies support a model in which concomitant dosage perturbation of multiple genes within the CNV drive the microcephaly and possibly other neurodevelopmental phenotypes associated with rearrangements in the 17p13.1 SRO. Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
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Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies
Manitz, Juliane; Burger, Patricia; Amos, Christopher I.; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike
2017-01-01
The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility. PMID:28785300
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Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies.
Friedrichs, Stefanie; Manitz, Juliane; Burger, Patricia; Amos, Christopher I; Risch, Angela; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike; Hofner, Benjamin
2017-01-01
The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility.
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Gärtner, Matti; Grimm, Simone; Aust, Sabine; Fan, Yan; von Scheve, Christian; Bajbouj, Malek
2017-07-07
Converging evidence suggests that well-being plays an important role in promoting and maintaining mental health across the life span. It has been shown that well-being has a considerable heritable component, but little is known about the specific genes involved. In this study, we investigated a healthy sample (N = 298) that was genotyped for the serotonin transporter-linked polymorphic region (5-HTTLPR). We hypothesized that 5-HTTLPR gene variation would influence well-being, and additionally investigated interaction effects with age and the environmental influence of early life stress (ELS). Using multiple regression, our results showed a significant three-way interaction between genotype, ELS, and age. Exploration of this interaction showed that young subjects had decreased levels of well-being if they were exposed to ELS and homozygous for the short variant of 5-HTTLPR. This relationship was reversed in old age: subjects that were exposed to ELS and carried the long variant of 5-HTTLPR had decreased levels of well-being. Our results indicate that genetic and environmental factors have joint effects on well-being that are susceptible to profound changes across the life span.
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Mahoney, J. Matthew; Taroni, Jaclyn; Martyanov, Viktor; Wood, Tammara A.; Greene, Casey S.; Pioli, Patricia A.; Hinchcliff, Monique E.; Whitfield, Michael L.
2015-01-01
Systemic sclerosis (SSc) is a rare systemic autoimmune disease characterized by skin and organ fibrosis. The pathogenesis of SSc and its progression are poorly understood. The SSc intrinsic gene expression subsets (inflammatory, fibroproliferative, normal-like, and limited) are observed in multiple clinical cohorts of patients with SSc. Analysis of longitudinal skin biopsies suggests that a patient's subset assignment is stable over 6–12 months. Genetically, SSc is multi-factorial with many genetic risk loci for SSc generally and for specific clinical manifestations. Here we identify the genes consistently associated with the intrinsic subsets across three independent cohorts, show the relationship between these genes using a gene-gene interaction network, and place the genetic risk loci in the context of the intrinsic subsets. To identify gene expression modules common to three independent datasets from three different clinical centers, we developed a consensus clustering procedure based on mutual information of partitions, an information theory concept, and performed a meta-analysis of these genome-wide gene expression datasets. We created a gene-gene interaction network of the conserved molecular features across the intrinsic subsets and analyzed their connections with SSc-associated genetic polymorphisms. The network is composed of distinct, but interconnected, components related to interferon activation, M2 macrophages, adaptive immunity, extracellular matrix remodeling, and cell proliferation. The network shows extensive connections between the inflammatory- and fibroproliferative-specific genes. The network also shows connections between these subset-specific genes and 30 SSc-associated polymorphic genes including STAT4, BLK, IRF7, NOTCH4, PLAUR, CSK, IRAK1, and several human leukocyte antigen (HLA) genes. Our analyses suggest that the gene expression changes underlying the SSc subsets may be long-lived, but mechanistically interconnected and related to a patients underlying genetic risk. PMID:25569146
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The Complex Contributions of Genetics and Nutrition to Immunity in Drosophila melanogaster
Unckless, Robert L.; Rottschaefer, Susan M.; Lazzaro, Brian P.
2015-01-01
Both malnutrition and undernutrition can lead to compromised immune defense in a diversity of animals, and “nutritional immunology” has been suggested as a means of understanding immunity and determining strategies for fighting infection. The genetic basis for the effects of diet on immunity, however, has been largely unknown. In the present study, we have conducted genome-wide association mapping in Drosophila melanogaster to identify the genetic basis for individual variation in resistance, and for variation in immunological sensitivity to diet (genotype-by-environment interaction, or GxE). D. melanogaster were reared for several generations on either high-glucose or low-glucose diets and then infected with Providencia rettgeri, a natural bacterial pathogen of D. melanogaster. Systemic pathogen load was measured at the peak of infection intensity, and several indicators of nutritional status were taken from uninfected flies reared on each diet. We find that dietary glucose level significantly alters the quality of immune defense, with elevated dietary glucose resulting in higher pathogen loads. The quality of immune defense is genetically variable within the sampled population, and we find genetic variation for immunological sensitivity to dietary glucose (genotype-by-diet interaction). Immune defense was genetically correlated with indicators of metabolic status in flies reared on the high-glucose diet, and we identified multiple genes that explain variation in immune defense, including several that have not been previously implicated in immune response but which are confirmed to alter pathogen load after RNAi knockdown. Our findings emphasize the importance of dietary composition to immune defense and reveal genes outside the conventional “immune system” that can be important in determining susceptibility to infection. Functional variation in these genes is segregating in a natural population, providing the substrate for evolutionary response to pathogen pressure in the context of nutritional environment. PMID:25764027
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The complex contributions of genetics and nutrition to immunity in Drosophila melanogaster.
Unckless, Robert L; Rottschaefer, Susan M; Lazzaro, Brian P
2015-03-01
Both malnutrition and undernutrition can lead to compromised immune defense in a diversity of animals, and "nutritional immunology" has been suggested as a means of understanding immunity and determining strategies for fighting infection. The genetic basis for the effects of diet on immunity, however, has been largely unknown. In the present study, we have conducted genome-wide association mapping in Drosophila melanogaster to identify the genetic basis for individual variation in resistance, and for variation in immunological sensitivity to diet (genotype-by-environment interaction, or GxE). D. melanogaster were reared for several generations on either high-glucose or low-glucose diets and then infected with Providencia rettgeri, a natural bacterial pathogen of D. melanogaster. Systemic pathogen load was measured at the peak of infection intensity, and several indicators of nutritional status were taken from uninfected flies reared on each diet. We find that dietary glucose level significantly alters the quality of immune defense, with elevated dietary glucose resulting in higher pathogen loads. The quality of immune defense is genetically variable within the sampled population, and we find genetic variation for immunological sensitivity to dietary glucose (genotype-by-diet interaction). Immune defense was genetically correlated with indicators of metabolic status in flies reared on the high-glucose diet, and we identified multiple genes that explain variation in immune defense, including several that have not been previously implicated in immune response but which are confirmed to alter pathogen load after RNAi knockdown. Our findings emphasize the importance of dietary composition to immune defense and reveal genes outside the conventional "immune system" that can be important in determining susceptibility to infection. Functional variation in these genes is segregating in a natural population, providing the substrate for evolutionary response to pathogen pressure in the context of nutritional environment.
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Gene-environment interaction involving recently identified colorectal cancer susceptibility loci
Kantor, Elizabeth D.; Hutter, Carolyn M.; Minnier, Jessica; Berndt, Sonja I.; Brenner, Hermann; Caan, Bette J.; Campbell, Peter T.; Carlson, Christopher S.; Casey, Graham; Chan, Andrew T.; Chang-Claude, Jenny; Chanock, Stephen J.; Cotterchio, Michelle; Du, Mengmeng; Duggan, David; Fuchs, Charles S.; Giovannucci, Edward L.; Gong, Jian; Harrison, Tabitha A.; Hayes, Richard B.; Henderson, Brian E.; Hoffmeister, Michael; Hopper, John L.; Jenkins, Mark A.; Jiao, Shuo; Kolonel, Laurence N.; Le Marchand, Loic; Lemire, Mathieu; Ma, Jing; Newcomb, Polly A.; Ochs-Balcom, Heather M.; Pflugeisen, Bethann M.; Potter, John D.; Rudolph, Anja; Schoen, Robert E.; Seminara, Daniela; Slattery, Martha L.; Stelling, Deanna L.; Thomas, Fridtjof; Thornquist, Mark; Ulrich, Cornelia M.; Warnick, Greg S.; Zanke, Brent W.; Peters, Ulrike; Hsu, Li; White, Emily
2014-01-01
BACKGROUND Genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) that are associated with risk of colorectal cancer (CRC). Prior research has evaluated the presence of gene-environment interaction involving the first 10 identified susceptibility loci, but little work has been conducted on interaction involving SNPs at recently identified susceptibility loci, including: rs10911251, rs6691170, rs6687758, rs11903757, rs10936599, rs647161, rs1321311, rs719725, rs1665650, rs3824999, rs7136702, rs11169552, rs59336, rs3217810, rs4925386, and rs2423279. METHODS Data on 9160 cases and 9280 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and Colon Cancer Family Registry (CCFR) were used to evaluate the presence of interaction involving the above-listed SNPs and sex, body mass index (BMI), alcohol consumption, smoking, aspirin use, post-menopausal hormone (PMH) use, as well as intake of dietary calcium, dietary fiber, dietary folate, red meat, processed meat, fruit, and vegetables. Interaction was evaluated using a fixed-effects meta-analysis of an efficient Empirical Bayes estimator, and permutation was used to account for multiple comparisons. RESULTS None of the permutation-adjusted p-values reached statistical significance. CONCLUSIONS The associations between recently identified genetic susceptibility loci and CRC are not strongly modified by sex, BMI, alcohol, smoking, aspirin, PMH use, and various dietary factors. IMPACT Results suggest no evidence of strong gene-environment interactions involving the recently identified 16 susceptibility loci for CRC taken one at a time. PMID:24994789
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Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks
Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui
2017-01-01
The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways. PMID:29049295
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De Coninck, Dieter I M; De Schamphelaere, Karel A C; Jansen, Mieke; De Meester, Luc; Janssen, Colin R
2013-04-15
Natural and chemical stressors occur simultaneously in the aquatic environment. Their combined effects on biota are usually difficult to predict from their individual effects due to interactions between the different stressors. Several recent studies have suggested that synergistic effects of multiple stressors on organisms may be more common at high compared to low overall levels of stress. In this study, we used a three-way full factorial design to investigate whether interactive effects between a natural stressor, the bacterial parasite Pasteuria ramosa, and a chemical stressor, the insecticide carbaryl, were different between two genetically distinct clones of Daphnia magna that strongly differ in their sensitivity to carbaryl. Interactive effects on various life-history and physiological endpoints were assessed as significant deviations from the reference Independent Action (IA) model, which was implemented by testing the significance of the two-way carbaryl×parasite interaction term in two-way ANOVA's on log-transformed observational data for each clone separately. Interactive effects (and thus significant deviations from IA) were detected in both the carbaryl-sensitive clone (on survival, early reproduction and growth) and in the non-sensitive clone (on growth, electron transport activity and prophenoloxidase activity). No interactions were found for maturation rate, filtration rate, and energy reserve fractions (carbohydrate, protein, lipid). Furthermore, only antagonistic interactions were detected in the non-sensitive clone, while only synergistic interactions were observed in the carbaryl sensitive clone. Our data clearly show that there are genetically determined differences in the interactive effects following combined exposure to carbaryl and Pasteuria in D. magna. Copyright © 2013 Elsevier B.V. All rights reserved.
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A global interaction network maps a wiring diagram of cellular function
Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N.; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D.; Pelechano, Vicent; Styles, Erin B.; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S.; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F.; Li, Sheena C.; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; Luis, Bryan-Joseph San; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W.; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G.; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M.; Moore, Claire L.; Rosebrock, Adam P.; Caudy, Amy A.; Myers, Chad L.; Andrews, Brenda; Boone, Charles
2017-01-01
We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing over 23 million double mutants, identifying ~550,000 negative and ~350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. PMID:27708008
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The genetic landscape of a physical interaction
Diss, Guillaume
2018-01-01
A key question in human genetics and evolutionary biology is how mutations in different genes combine to alter phenotypes. Efforts to systematically map genetic interactions have mostly made use of gene deletions. However, most genetic variation consists of point mutations of diverse and difficult to predict effects. Here, by developing a new sequencing-based protein interaction assay – deepPCA – we quantified the effects of >120,000 pairs of point mutations on the formation of the AP-1 transcription factor complex between the products of the FOS and JUN proto-oncogenes. Genetic interactions are abundant both in cis (within one protein) and trans (between the two molecules) and consist of two classes – interactions driven by thermodynamics that can be predicted using a three-parameter global model, and structural interactions between proximally located residues. These results reveal how physical interactions generate quantitatively predictable genetic interactions. PMID:29638215
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Genetic associations with micronutrient levels identified in immune and gastrointestinal networks.
Morine, Melissa J; Monteiro, Jacqueline Pontes; Wise, Carolyn; Teitel, Candee; Pence, Lisa; Williams, Anna; Ning, Baitang; McCabe-Sellers, Beverly; Champagne, Catherine; Turner, Jerome; Shelby, Beatrice; Bogle, Margaret; Beger, Richard D; Priami, Corrado; Kaput, Jim
2014-07-01
The discovery of vitamins and clarification of their role in preventing frank essential nutrient deficiencies occurred in the early 1900s. Much vitamin research has understandably focused on public health and the effects of single nutrients to alleviate acute conditions. The physiological processes for maintaining health, however, are complex systems that depend upon interactions between multiple nutrients, environmental factors, and genetic makeup. To analyze the relationship between these factors and nutritional health, data were obtained from an observational, community-based participatory research program of children and teens (age 6-14) enrolled in a summer day camp in the Delta region of Arkansas. Assessments of erythrocyte S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH), plasma homocysteine (Hcy) and 6 organic micronutrients (retinol, 25-hydroxy vitamin D3, pyridoxal, thiamin, riboflavin, and vitamin E), and 1,129 plasma proteins were performed at 3 time points in each of 2 years. Genetic makeup was analyzed with 1 M SNP genotyping arrays, and nutrient status was assessed with 24-h dietary intake questionnaires. A pattern of metabolites (met_PC1) that included the ratio of erythrocyte SAM/SAH, Hcy, and 5 vitamins were identified by principal component analysis. Met_PC1 levels were significantly associated with (1) single-nucleotide polymorphisms, (2) levels of plasma proteins, and (3) multilocus genotypes coding for gastrointestinal and immune functions, as identified in a global network of metabolic/protein-protein interactions. Subsequent mining of data from curated pathway, network, and genome-wide association studies identified genetic and functional relationships that may be explained by gene-nutrient interactions. The systems nutrition strategy described here has thus associated a multivariate metabolite pattern in blood with genes involved in immune and gastrointestinal functions.
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Zhang, Guicheng; Khoo, Siew-Kim; Mäkelä, Mika J; Candelaria, Pierre; Hayden, Catherine M; von Hertzen, Leena; Laatikainen, Tiina; Vartiainen, Erkki; Goldblatt, Jack; Haahtela, Tari; LeSouëf, Peter N
2014-07-01
We investigated maternal genetic effects of four IL-4/IL-13 pathway genes as well as their interactions with the "Western or Eastern lifestyles/environments" on IgE in Karelian children. This study included 609 children and their mothers. Total IgE levels in children and mothers were measured and 10 single nucleotide polymorphisms (SNPs) in IL-4, IL-4Ra, IL-13, and STAT6 were genotyped in mothers and their children. The maternal G allele of IL-13 130 (rs20541) was significantly (P=0.001) associated with decreased IgE in children in the Karelian population (Pooling Finnish and Russian children), as well as in Finnish (P=0.030) and Russian children (P=0.018). The IgE levels were significantly (P=0.001) higher in Russian children whose mothers were homozygous for the G allele of the IL-4Ra 50 (rs1805010) SNP than that in Russian children of mothers who were AG heterozygotes or AA homozygotes. After accounting for children's genotypes, we observed interactive effects on children's IgE for maternal IL-13 130 genotypes (P=0.014) and maternal IL-4Ra 50 genotypes (P=0.0003) with "Western or Eastern" lifestyles/environments. With the adjustment for multiple comparisons using a false discovery rate (FDR) of 0.05, the interactive effect of the maternal IL-4Ra50 SNP was significant. Maternal genetic variants in IL-4/IL-13 pathway genes, such as IL-13 130 and IL-4Ra50, influenced IgE levels in school children that were independent of the children's genetic effects. These effects differ in "Western or Eastern" environments.
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Trotta, Antonella; Iyegbe, Conrad; Yiend, Jenny; Dazzan, Paola; David, Anthony S; Pariante, Carmine; Mondelli, Valeria; Colizzi, Marco; Murray, Robin M; Di Forti, Marta; Fisher, Helen L
2018-04-10
There is consistent evidence of a cumulative relationship between childhood adversity and psychosis, with number of adversities experienced increasing the probability of psychosis onset. It is possible that genetic factors moderate the association between childhood adversity and psychosis, potentially by influencing how an individual reacts biologically and/or psychologically following exposure to adversity, in such a way as to set them off on the path to psychosis. However, identifying the specific genetic variants involved and how they interact with childhood adversity remains challenging. We examined whether the association between cumulative exposure to childhood adversity and development of psychotic disorder was moderated by the COMT Val 158 Met, AKT1 rs2494732 or DRD2 rs1076560 polymorphisms, known to affect dopamine levels. Participants were 285 first-presentation psychosis cases and 256 geographically-matched controls drawn from the Genetics and Psychosis (GAP) study. Childhood adversity was assessed using the Childhood Experience of Care and Abuse Questionnaire (CECA.Q) and blood- and cheek-derived genotype data were collected. Our findings revealed no main effect of COMT Val 158 Met, AKT1 rs2494732 and DRD2 rs1076560 polymorphisms on psychosis case status or reports of childhood adversity. Individuals reporting a history of multiple adversities were more likely to be psychosis patients than controls, regardless of their genetic risk. There was no evidence of candidate genotype by childhood adversity interactions in relation to psychosis onset. These findings did not provide evidence of a possible role of COMT Val 158 Met, AKT1 rs2494732 or DRD2 rs1076560 genotypes in modifying the association between childhood adversity and onset of psychosis. Copyright © 2018 Elsevier B.V. All rights reserved.
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Buescher, Elizabeth M.; Moon, Jihyun; Runkel, Anne; Hake, Sarah; Dilkes, Brian P.
2014-01-01
Leaf architecture determines plant structural integrity, light harvesting, and economic considerations such as plant density. Ligules, junctions at the leaf sheath and blade in grasses, protect stalks from environmental stresses and, in conjunction with auricles, controls leaf angle. Previous studies in mutants have recessive liguleless mutants (lg1 and lg2) and dominant mutations in knotted1-like homeobox genes (Lg3-O, Lg4, and Kn1) involved in ligule development. Recently, a new semidominant liguleless mutant, Liguleless narrow (Lgn-R), has been characterized in maize that affects ligule and auricle development and results in a narrow leaf phenotype. We show that quantitative genetic variation affects penetrance of Lgn-R. To examine the genetic architecture underlying Lgn-R expressivity, crosses between Lgn-R/+ mutants in a B73 background and intermated B73 x Mo17 recombinant inbred lines were evaluated in multiple years and locations. A single main-effect quantitative trait locus (QTL) on chromosome 1 (sympathy for the ligule; sol) was discovered with a Mo17-contributed allele that suppressed Lgn-R mutant phenotypes. This QTL has a genetic-interaction with a locus on chromosome 7 (lucifer; lcf) for which the B73-contributed allele increases the ability of the solMo17 allele to suppress Lgn-R. Neither of the genetic intervals likely to contain sol or lcf overlap with any current liguleless genes nor with previously identified genome-wide association QTL connected to leaf architecture. Analysis of phenotypes across environments further identified a genotype by enviroment interaction determining the strength of the sol x lcf interaction. PMID:25344411
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Feldman, R; Vengrober, A; Ebstein, R P
2014-03-11
Research indicates that risk for post-traumatic stress disorder (PTSD) is shaped by the interaction between genetic vulnerability and early caregiving experiences; yet, caregiving has typically been assessed by adult retrospective accounts. Here, we employed a prospective longitudinal design with real-time observations of early caregiving combined with assessment of genetic liability along the axis of vasopressin-oxytocin (OT) gene pathways to test G × E contributions to PTSD. Participants were 232 young Israeli children (1.5-5 years) and their parents, including 148 living in zones of continuous war and 84 controls. A cumulative genetic risk factor was computed for each family member by summing five risk alleles across three genes (OXTR, CD38 and AVPR1a) previously associated with psychopathology, sociality and caregiving. Child PTSD was diagnosed and mother-child interactions were observed in multiple contexts. In middle childhood (7-8 years), child psychopathology was re-evaluated. War exposure increased propensity to develop Axis-I disorder by threefold: 60% of exposed children displayed a psychiatric disorder by middle childhood and 62% of those showed several comorbid disorders. On the other hand, maternal sensitive support reduced risk for psychopathology. G × E effect was found for child genetic risk: in the context of war exposure, greater genetic risk on the vasopressin-OT pathway increased propensity for psychopathology. Among exposed children, chronicity of PTSD from early to middle childhood was related to higher child, maternal and paternal genetic risk, low maternal support and greater initial avoidance symptoms. Child avoidance was predicted by low maternal support and reduced mother-child reciprocity. These findings underscore the saliency of both genetic and behavioral facets of the human affiliation system in shaping vulnerability to PTSD as well as providing an underlying mechanism of post-traumatic resilience.
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Feldman, R; Vengrober, A; Ebstein, R P
2014-01-01
Research indicates that risk for post-traumatic stress disorder (PTSD) is shaped by the interaction between genetic vulnerability and early caregiving experiences; yet, caregiving has typically been assessed by adult retrospective accounts. Here, we employed a prospective longitudinal design with real-time observations of early caregiving combined with assessment of genetic liability along the axis of vasopressin–oxytocin (OT) gene pathways to test G × E contributions to PTSD. Participants were 232 young Israeli children (1.5–5 years) and their parents, including 148 living in zones of continuous war and 84 controls. A cumulative genetic risk factor was computed for each family member by summing five risk alleles across three genes (OXTR, CD38 and AVPR1a) previously associated with psychopathology, sociality and caregiving. Child PTSD was diagnosed and mother–child interactions were observed in multiple contexts. In middle childhood (7–8 years), child psychopathology was re-evaluated. War exposure increased propensity to develop Axis-I disorder by threefold: 60% of exposed children displayed a psychiatric disorder by middle childhood and 62% of those showed several comorbid disorders. On the other hand, maternal sensitive support reduced risk for psychopathology. G × E effect was found for child genetic risk: in the context of war exposure, greater genetic risk on the vasopressin–OT pathway increased propensity for psychopathology. Among exposed children, chronicity of PTSD from early to middle childhood was related to higher child, maternal and paternal genetic risk, low maternal support and greater initial avoidance symptoms. Child avoidance was predicted by low maternal support and reduced mother–child reciprocity. These findings underscore the saliency of both genetic and behavioral facets of the human affiliation system in shaping vulnerability to PTSD as well as providing an underlying mechanism of post-traumatic resilience. PMID:24618689
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Lachowiec, Jennifer; Shen, Xia; Queitsch, Christine; Carlborg, Örjan
2015-01-01
Efforts to identify loci underlying complex traits generally assume that most genetic variance is additive. Here, we examined the genetics of Arabidopsis thaliana root length and found that the genomic narrow-sense heritability for this trait in the examined population was statistically zero. The low amount of additive genetic variance that could be captured by the genome-wide genotypes likely explains why no associations to root length could be found using standard additive-model-based genome-wide association (GWA) approaches. However, as the broad-sense heritability for root length was significantly larger, and primarily due to epistasis, we also performed an epistatic GWA analysis to map loci contributing to the epistatic genetic variance. Four interacting pairs of loci were revealed, involving seven chromosomal loci that passed a standard multiple-testing corrected significance threshold. The genotype-phenotype maps for these pairs revealed epistasis that cancelled out the additive genetic variance, explaining why these loci were not detected in the additive GWA analysis. Small population sizes, such as in our experiment, increase the risk of identifying false epistatic interactions due to testing for associations with very large numbers of multi-marker genotypes in few phenotyped individuals. Therefore, we estimated the false-positive risk using a new statistical approach that suggested half of the associated pairs to be true positive associations. Our experimental evaluation of candidate genes within the seven associated loci suggests that this estimate is conservative; we identified functional candidate genes that affected root development in four loci that were part of three of the pairs. The statistical epistatic analyses were thus indispensable for confirming known, and identifying new, candidate genes for root length in this population of wild-collected A. thaliana accessions. We also illustrate how epistatic cancellation of the additive genetic variance explains the insignificant narrow-sense and significant broad-sense heritability by using a combination of careful statistical epistatic analyses and functional genetic experiments.
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Gu, Xing-You; Kianian, Shahryar F; Foley, Michael E
2004-01-01
Weedy rice has much stronger seed dormancy than cultivated rice. A wild-like weedy strain SS18-2 was selected to investigate the genetic architecture underlying seed dormancy, a critical adaptive trait in plants. A framework genetic map covering the rice genome was constructed on the basis of 156 BC(1) [EM93-1 (nondormant breeding line)//EM93-1/SS18-2] individuals. The mapping population was replicated using a split-tiller technique to control and better estimate the environmental variation. Dormancy was determined by germination of seeds after 1, 11, and 21 days of after-ripening (DAR). Six dormancy QTL, designated as qSD(S)-4, -6, -7-1, -7-2, -8, and -12, were identified. The locus qSD(S)-7-1 was tightly linked to the red pericarp color gene Rc. A QTL x DAR interaction was detected for qSD(S)-12, the locus with the largest main effect at 1, 11, and 21 DAR (R(2) = 0.14, 0.24, and 0.20, respectively). Two, three, and four orders of epistases were detected with four, six, and six QTL, respectively. The higher-order epistases strongly suggest the presence of genetically complex networks in the regulation of variation for seed dormancy in natural populations and make it critical to select for a favorable combination of alleles at multiple loci in positional cloning of a target dormancy gene. PMID:15082564
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Simple F Test Reveals Gene-Gene Interactions in Case-Control Studies
Chen, Guanjie; Yuan, Ao; Zhou, Jie; Bentley, Amy R.; Adeyemo, Adebowale; Rotimi, Charles N.
2012-01-01
Missing heritability is still a challenge for Genome Wide Association Studies (GWAS). Gene-gene interactions may partially explain this residual genetic influence and contribute broadly to complex disease. To analyze the gene-gene interactions in case-control studies of complex disease, we propose a simple, non-parametric method that utilizes the F-statistic. This approach consists of three steps. First, we examine the joint distribution of a pair of SNPs in cases and controls separately. Second, an F-test is used to evaluate the ratio of dependence in cases to that of controls. Finally, results are adjusted for multiple tests. This method was used to evaluate gene-gene interactions that are associated with risk of Type 2 Diabetes among African Americans in the Howard University Family Study. We identified 18 gene-gene interactions (P < 0.0001). Compared with the commonly-used logistical regression method, we demonstrate that the F-ratio test is an efficient approach to measuring gene-gene interactions, especially for studies with limited sample size. PMID:22837643
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Musci, Rashelle J; Fairman, Brian; Masyn, Katherine E; Uhl, George; Maher, Brion; Sisto, Danielle Y; Kellam, Sheppard G; Ialongo, Nicholas S
2018-01-01
The present study examines the interaction between a polygenic score and an elementary school-based universal preventive intervention trial and its effects on a discrete-time survival analysis of time to first smoking marijuana. Research has suggested that initiation of substances is both genetically and environmentally driven (Rhee et al., Archives of general psychiatry 60:1256-1264, 2003; Verweij et al., Addiction 105:417-430, 2010). A previous work has found a significant interaction between the polygenic score and the same elementary school-based intervention with tobacco smoking (Musci et al., in press). The polygenic score reflects the contribution of multiple genes and has been shown in prior research to be predictive of smoking cessation, tobacco use, and marijuana use (Uhl et al., Molecular Psychiatry 19:50-54, 2014). Using data from a longitudinal preventive intervention study (N = 678), we examined age of first marijuana use from sixth grade to age 18. Genetic data were collected during emerging adulthood and were genotyped using the Affymetrix 6.0 microarray (N = 545). The polygenic score was computed using these data. Discrete-time survival analysis was employed to test for intervention main and interaction effects with the polygenic score. We found main effect of the polygenic score approaching significance, with the participants with higher polygenic scores reporting their first smoking marijuana at an age significantly later than controls (p = .050). We also found a significant intervention × polygenic score interaction effect at p = .003, with participants at the higher end of the polygenic score benefiting the most from the intervention in terms of delayed age of first use. These results suggest that genetics may play an important role in the age of first use of marijuana and that differences in genetics may account for the differential effectiveness of classroom-based interventions in delaying substance use experimentation.
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Aggressive behavior, related conduct problems, and variation in genes affecting dopamine turnover.
Grigorenko, Elena L; De Young, Colin G; Eastman, Maria; Getchell, Marya; Haeffel, Gerald J; Klinteberg, Britt af; Koposov, Roman A; Oreland, Lars; Pakstis, Andrew J; Ponomarev, Oleg A; Ruchkin, Vladislav V; Singh, Jay P; Yrigollen, Carolyn M
2010-01-01
A number of dopamine-related genes have been implicated in the etiology of violent behavior and conduct problems. Of these genes, the ones that code for the enzymes that influence the turnover of dopamine (DA) have received the most attention. In this study, we investigated 12 genetic polymorphisms in four genes involved with DA functioning (COMT, MAOA and MAOB, and DbetaH) in 179 incarcerated male Russian adolescents and two groups of matched controls: boys without criminal records referred to by their teachers as (a) "troubled-behavior-free" boys, n=182; and (b) "troubled-behavior" boys, n=60. The participants were classified as (1) being incarcerated or not, (2) having the DSM-IV diagnosis of conduct disorder (CD) or not, and (3) having committed violent or nonviolent crimes (for the incarcerated individuals only). The findings indicate that, although no single genetic variant in any of the four genes differentiated individuals in the investigated groups, various linear combinations (i.e., haplotypes) and nonlinear combinations (i.e., interactions between variants within and across genes) of genetic variants resulted in informative and robust classifications for two of the three groupings. These combinations of genetic variants differentiated individuals in incarceration vs. nonincarcerated and CD vs. no-CD groups; no informative combinations were established consistently for the grouping by crime within the incarcerated individuals. This study underscores the importance of considering multiple rather than single markers within candidate genes and their additive and interactive combinations, both with themselves and with nongenetic indicators, while attempting to understand the genetic background of such complex behaviors as serious conduct problems. (c) 2010 Wiley-Liss, Inc.
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Striatal Circuits as a Common Node for Autism Pathophysiology
Fuccillo, Marc V.
2016-01-01
Autism spectrum disorders (ASD) are characterized by two seemingly unrelated symptom domains—deficits in social interactions and restrictive, repetitive patterns of behavioral output. Whether the diverse nature of ASD symptomatology represents distributed dysfunction of brain networks or abnormalities within specific neural circuits is unclear. Striatal dysfunction is postulated to underlie the repetitive motor behaviors seen in ASD, and neurological and brain-imaging studies have supported this assumption. However, as our appreciation of striatal function expands to include regulation of behavioral flexibility, motivational state, goal-directed learning, and attention, we consider whether alterations in striatal physiology are a central node mediating a range of autism-associated behaviors, including social and cognitive deficits that are hallmarks of the disease. This review investigates multiple genetic mouse models of ASD to explore whether abnormalities in striatal circuits constitute a common pathophysiological mechanism in the development of autism-related behaviors. Despite the heterogeneity of genetic insult investigated, numerous genetic ASD models display alterations in the structure and function of striatal circuits, as well as abnormal behaviors including repetitive grooming, stereotypic motor routines, deficits in social interaction and decision-making. Comparative analysis in rodents provides a unique opportunity to leverage growing genetic association data to reveal canonical neural circuits whose dysfunction directly contributes to discrete aspects of ASD symptomatology. The description of such circuits could provide both organizing principles for understanding the complex genetic etiology of ASD as well as novel treatment routes. Furthermore, this focus on striatal mechanisms of behavioral regulation may also prove useful for exploring the pathogenesis of other neuropsychiatric diseases, which display overlapping behavioral deficits with ASD. PMID:26903795
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Hauser, Kurt F; Knapp, Pamela E
2014-01-01
Considerable insight has been gained into the comorbid, interactive effects of HIV and drug abuse in the brain using experimental models. This review, which considers opiates, methamphetamine, and cocaine, emphasizes the importance of host genetics and glial plasticity in driving the pathogenic neuron remodeling underlying neuro-acquired immunodeficiency syndrome and drug abuse comorbidity. Clinical findings are less concordant than experimental work, and the response of individuals to HIV and to drug abuse can vary tremendously. Host-genetic variability is important in determining viral tropism, neuropathogenesis, drug responses, and addictive behavior. However, genetic differences alone cannot account for individual variability in the brain "connectome." Environment and experience are critical determinants in the evolution of synaptic circuitry throughout life. Neurons and glia both exercise control over determinants of synaptic plasticity that are disrupted by HIV and drug abuse. Perivascular macrophages, microglia, and to a lesser extent astroglia can harbor the infection. Uninfected bystanders, especially astroglia, propagate and amplify inflammatory signals. Drug abuse by itself derails neuronal and glial function, and the outcome of chronic exposure is maladaptive plasticity. The negative consequences of coexposure to HIV and drug abuse are determined by numerous factors including genetics, sex, age, and multidrug exposure. Glia and some neurons are generated throughout life, and their progenitors appear to be targets of HIV and opiates/psychostimulants. The chronic nature of HIV and drug abuse appears to result in sustained alterations in the maturation and fate of neural progenitors, which may affect the balance of glial populations within multiple brain regions. © 2014 Elsevier Inc. All rights reserved.
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Hauser, Kurt F.; Knapp, Pamela E.
2015-01-01
Considerable insight has been gained into the comorbid, interactive effects of HIV and drug abuse in the brain using experimental models. This review, which considers opiates, methamphetamine, and cocaine, emphasizes the importance of host genetics and glial plasticity in driving the pathogenic neuron remodeling underlying neuro-acquired immunodeficiency syndrome (neuroAIDS) and drug abuse comorbidity. Clinical findings are less concordant than experimental work, and the response of individuals to HIV and to drug abuse can vary tremendously. Host-genetic variability is important in determining viral tropism, neuropathogenesis, drug responses, and addictive behavior. However, genetic differences alone cannot account for individual variability in the brain “connectome”. Environment and experience are critical determinants in the evolution of synaptic circuitry throughout life. Neurons and glia both exercise control over determinants of synaptic plasticity that are disrupted by HIV and drug abuse. Perivascular macrophages, microglia, and to a lesser extent astroglia can harbor the infection. Uninfected bystanders, especially astroglia, propagate and amplify inflammatory signals. Drug abuse by itself derails neuronal and glial function, and the outcome of chronic exposure is maladaptive plasticity. The negative consequences of coexposure to HIV and drug abuse are determined by numerous factors including genetics, sex, age, and multidrug exposure. Glia and some neurons are generated throughout life and their progenitors appear to be targets of HIV and opiates/psychostimulants. The chronic nature of HIV and drug abuse appears to result in sustained alterations in the maturation and fate of neural progenitors, which may affect the balance of glial populations within multiple brain regions. PMID:25175867
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Debunking Occam's razor: Diagnosing multiple genetic diseases in families by whole-exome sequencing.
Balci, T B; Hartley, T; Xi, Y; Dyment, D A; Beaulieu, C L; Bernier, F P; Dupuis, L; Horvath, G A; Mendoza-Londono, R; Prasad, C; Richer, J; Yang, X-R; Armour, C M; Bareke, E; Fernandez, B A; McMillan, H J; Lamont, R E; Majewski, J; Parboosingh, J S; Prasad, A N; Rupar, C A; Schwartzentruber, J; Smith, A C; Tétreault, M; Innes, A M; Boycott, K M
2017-09-01
Recent clinical whole exome sequencing (WES) cohorts have identified unanticipated multiple genetic diagnoses in single patients. However, the frequency of multiple genetic diagnoses in families is largely unknown. We set out to identify the rate of multiple genetic diagnoses in probands and their families referred for analysis in two national research programs in Canada. We retrospectively analyzed WES results for 802 undiagnosed probands referred over the past 5 years in either the FORGE or Care4Rare Canada WES initiatives. Of the 802 probands, 226 (28.2%) were diagnosed based on mutations in known disease genes. Eight (3.5%) had two or more genetic diagnoses explaining their clinical phenotype, a rate in keeping with the large published studies (average 4.3%; 1.4 - 7.2%). Seven of the 8 probands had family members with one or more of the molecularly diagnosed diseases. Consanguinity and multisystem disease appeared to increase the likelihood of multiple genetic diagnoses in a family. Our findings highlight the importance of comprehensive clinical phenotyping of family members to ultimately provide accurate genetic counseling. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
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Wu, Fen; Jasmine, Farzana; Kibriya, Muhammad G.; Liu, Mengling; Cheng, Xin; Parvez, Faruque; Islam, Tariqul; Ahmed, Alauddin; Rakibuz-Zaman, Muhammad; Jiang, Jieying; Roy, Shantanu; Paul-Brutus, Rachelle; Slavkovich, Vesna; Islam, Tariqul; Levy, Diane; VanderWeele, Tyler J.; Pierce, Brandon L.; Graziano, Joseph H.; Ahsan, Habibul
2015-01-01
Background: Epidemiologic data on genetic susceptibility to cardiovascular effects of arsenic exposure from drinking water are limited. Objective: We investigated whether the association between well-water arsenic and cardiovascular disease (CVD) differed by 170 single nucleotide polymorphisms (SNPs) in 17 genes related to arsenic metabolism, oxidative stress, inflammation, and endothelial dysfunction. Method: We conducted a prospective case-cohort study nested in the Health Effects of Arsenic Longitudinal Study, with a random subcohort of 1,375 subjects and 447 incident fatal and nonfatal cases of CVD. Well-water arsenic was measured in 2000 at baseline. The CVD cases, 56 of which occurred in the subcohort, included 238 coronary heart disease cases, 165 stroke cases, and 44 deaths due to other CVD identified during follow-up from 2000 to 2012. Results: Of the 170 SNPs tested, multiplicative interactions between well-water arsenic and two SNPs, rs281432 in ICAM1 (padj = 0.0002) and rs3176867 in VCAM1 (padj = 0.035), were significant for CVD after adjustment for multiple testing. Compared with those with GC or CC genotype in rs281432 and lower well-water arsenic, the adjusted hazard ratio (aHR) for CVD was 1.82 (95% CI: 1.31, 2.54) for a 1-SD increase in well-water arsenic combined with the GG genotype, which was greater than expected given aHRs of 1.08 and 0.96 for separate effects of arsenic and the genotype alone, respectively. Similarly, the joint aHR for arsenic and the rs3176867 CC genotype was 1.34 (95% CI: 0.95, 1.87), greater than expected given aHRs for their separate effects of 1.02 and 0.84, respectively. Conclusions: Associations between CVD and arsenic exposure may be modified by genetic variants related to endothelial dysfunction. Citation: Wu F, Jasmine F, Kibriya MG, Liu M, Cheng X, Parvez F, Islam T, Ahmed A, Rakibuz-Zaman M, Jiang J, Roy S, Paul-Brutus R, Slavkovich V, Islam T, Levy D, VanderWeele TJ, Pierce BL, Graziano JH, Ahsan H, Chen Y. 2015. Interaction between arsenic exposure from drinking water and genetic polymorphisms on cardiovascular disease in Bangladesh: a prospective case-cohort study. Environ Health Perspect 123:451–457; http://dx.doi.org/10.1289/ehp.1307883 PMID:25575156
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Genetic background effects in quantitative genetics: gene-by-system interactions.
Sardi, Maria; Gasch, Audrey P
2018-04-11
Proper cell function depends on networks of proteins that interact physically and functionally to carry out physiological processes. Thus, it seems logical that the impact of sequence variation in one protein could be significantly influenced by genetic variants at other loci in a genome. Nonetheless, the importance of such genetic interactions, known as epistasis, in explaining phenotypic variation remains a matter of debate in genetics. Recent work from our lab revealed that genes implicated from an association study of toxin tolerance in Saccharomyces cerevisiae show extensive interactions with the genetic background: most implicated genes, regardless of allele, are important for toxin tolerance in only one of two tested strains. The prevalence of background effects in our study adds to other reports of widespread genetic-background interactions in model organisms. We suggest that these effects represent many-way interactions with myriad features of the cellular system that vary across classes of individuals. Such gene-by-system interactions may influence diverse traits and require new modeling approaches to accurately represent genotype-phenotype relationships across individuals.
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Fejerman, Laura
2013-01-01
Hispanic women in the USA have lower breast cancer incidence than non-Hispanic white (NHW) women. Genetic factors may contribute to this difference. Breast cancer genome-wide association studies (GWAS) conducted in women of European or Asian descent have identified multiple risk variants. We tested the association between 10 previously reported single nucleotide polymorphisms (SNPs) and risk of breast cancer in a sample of 4697 Hispanic and 3077 NHW women recruited as part of three population-based case–control studies of breast cancer. We used stratified logistic regression analyses to compare the associations with different genetic variants in NHWs and Hispanics classified by their proportion of Indigenous American (IA) ancestry. Five of 10 SNPs were statistically significantly associated with breast cancer risk. Three of the five significant variants (rs17157903-RELN, rs7696175-TLR1 and rs13387042-2q35) were associated with risk among Hispanics but not in NHWs. The odds ratio (OR) for the heterozygous at 2q35 was 0.75 [95% confidence interval (CI) = 0.50–1.15] for low IA ancestry and 1.38 (95% CI = 1.04–1.82) for high IA ancestry (P interaction 0.02). The ORs for association at RELN were 0.87 (95% CI = 0.59–1.29) and 1.69 (95% CI = 1.04–2.73), respectively (P interaction 0.03). At the TLR1 locus, the ORs for women homozygous for the rare allele were 0.74 (95% CI = 0.42–1.31) and 1.73 (95% CI = 1.19–2.52) (P interaction 0.03). Our results suggest that the proportion of IA ancestry modifies the magnitude and direction of the association of 3 of the 10 previously reported variants. Genetic ancestry should be considered when assessing risk in women of mixed descent and in studies designed to discover causal mutations. PMID:23563089
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Kendrick, Agnieszka A.; Schafer, Johnathon; Dzieciatkowska, Monika; Nemkov, Travis; D'Alessandro, Angelo; Neelakantan, Deepika; Ford, Heide L.; Pearson, Chad G.; Weekes, Colin D.; Hansen, Kirk C.; Eisenmesser, Elan Z.
2017-01-01
Increased expression of CD147 in pancreatic cancer has been proposed to play a critical role in cancer progression via CD147 chaperone function for lactate monocarboxylate transporters (MCTs). Here, we show for the first time that CD147 interacts with membrane transporters beyond MCTs and exhibits a protective role for several of its interacting partners. CD147 prevents its interacting partner's proteasome-dependent degradation and incorrect plasma membrane localization through the CD147 transmembrane (TM) region. The interactions with transmembrane small molecule and ion transporters identified here indicate a central role of CD147 in pancreatic cancer metabolic reprogramming, particularly with respect to amino acid anabolism and calcium signaling. Importantly, CD147 genetic ablation prevents pancreatic cancer cell proliferation and tumor growth in vitro and in vivo in conjunction with metabolic rewiring towards amino acid anabolism, thus paving the way for future combined pharmacological treatments. PMID:28039486
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Kendrick, Agnieszka A; Schafer, Johnathon; Dzieciatkowska, Monika; Nemkov, Travis; D'Alessandro, Angelo; Neelakantan, Deepika; Ford, Heide L; Pearson, Chad G; Weekes, Colin D; Hansen, Kirk C; Eisenmesser, Elan Z
2017-01-24
Increased expression of CD147 in pancreatic cancer has been proposed to play a critical role in cancer progression via CD147 chaperone function for lactate monocarboxylate transporters (MCTs). Here, we show for the first time that CD147 interacts with membrane transporters beyond MCTs and exhibits a protective role for several of its interacting partners. CD147 prevents its interacting partner's proteasome-dependent degradation and incorrect plasma membrane localization through the CD147 transmembrane (TM) region. The interactions with transmembrane small molecule and ion transporters identified here indicate a central role of CD147 in pancreatic cancer metabolic reprogramming, particularly with respect to amino acid anabolism and calcium signaling. Importantly, CD147 genetic ablation prevents pancreatic cancer cell proliferation and tumor growth in vitro and in vivo in conjunction with metabolic rewiring towards amino acid anabolism, thus paving the way for future combined pharmacological treatments.
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Identification of five novel modifier loci of ApcMin harbored in the BXH14 recombinant inbred strain
Siracusa, Linda D.
2012-01-01
Every year thousands of people in the USA are diagnosed with small intestine and colorectal cancers (CRC). Although environmental factors affect disease etiology, uncovering underlying genetic factors is imperative for risk assessment and developing preventative therapies. Familial adenomatous polyposis is a heritable genetic disorder in which individuals carry germ-line mutations in the adenomatous polyposis coli (APC) gene that predisposes them to CRC. The Apc Min mouse model carries a point mutation in the Apc gene and develops polyps along the intestinal tract. Inbred strain background influences polyp phenotypes in Apc Min mice. Several Modifier of Min (Mom) loci that alter tumor phenotypes associated with the Apc Min mutation have been identified to date. We screened BXH recombinant inbred (RI) strains by crossing BXH RI females with C57BL/6J (B6) Apc Min males and quantitating tumor phenotypes in backcross progeny. We found that the BXH14 RI strain harbors five modifier loci that decrease polyp multiplicity. Furthermore, we show that resistance is determined by varying combinations of these modifier loci. Gene interaction network analysis shows that there are multiple networks with proven gene–gene interactions, which contain genes from all five modifier loci. We discuss the implications of this result for studies that define susceptibility loci, namely that multiple networks may be acting concurrently to alter tumor phenotypes. Thus, the significance of this work resides not only with the modifier loci we identified but also with the combinations of loci needed to get maximal protection against polyposis and the impact of this finding on human disease studies. Abbreviations:APCadenomatous polyposis coliGWASgenome-wide association studiesQTLquantitative trait lociSNPsingle-nucleotide polymorphism. PMID:22637734
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Dong, Chuanhui; Della-Morte, David; Beecham, Ashley; Wang, Liyong; Cabral, Digna; Blanton, Susan H; Sacco, Ralph L; Rundek, Tatjana
2015-06-01
There is an established sex-difference in carotid artery intima-media thickness (cIMT), a recognized marker of subclinical atherosclerosis. However, the genetic underpinnings of sex-differences in gene-IMT associations are largely unknown. With a multistage design using 731,037 single nucleotide polymorphisms (SNP), a genome wide interaction study was performed in a discovery sample of 931 unrelated Hispanics, followed by replication in 153 non-Hispanic whites and 257 non-Hispanic blacks. Assuming an additive genetic model, we tested for sex-SNP interactions on cIMT using regression analysis. We did not identify any genome-wide significant SNPs but identified 14 loci with suggestive significance. Specifically, SNP-by-sex interaction was found for rs7616559 within LEKR1 gene (P = 3.5E-06 in Hispanic discovery sample, P = 0.018 in White, and P = 1.3E-06 in combined analysis) and for rs2081015 located within GALNT10 gene (P = 4.5E-06 in Hispanic discovery sample, P = 0.042 in Blacks, and P = 5.3E-07 in combined analysis). For rs7616559 within LEKR1, men had greater cIMT than women in G allele carriers (beta ± SE: 0.044 ± 0.007, P = 4.2E-09 in AG carriers; beta ± SE: 0.064 ± 0.007, P = 6.2E-05 in GG carriers). For rs2081015 within GALNT10, men had greater cIMT than women in C allele carriers (beta ± SE: 0.022 ± 0.007, P = 0.002 in CT carriers; beta ± SE: 0.051 ± 0.008, P = 3.1E-10 in CC carriers). Our genome-wide interaction analysis reveals multiple loci that may modulate sex difference in cIMT. Of them, genetic variants on LEKR1 and GALNT10 genes have been associated with control of adiposity and weight. Given the consistent findings across different-ethnic groups, further studies are warranted to perform investigations of functional genetic variants in these regions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
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Multiple testing and power calculations in genetic association studies.
So, Hon-Cheong; Sham, Pak C
2011-01-01
Modern genetic association studies typically involve multiple single-nucleotide polymorphisms (SNPs) and/or multiple genes. With the development of high-throughput genotyping technologies and the reduction in genotyping cost, investigators can now assay up to a million SNPs for direct or indirect association with disease phenotypes. In addition, some studies involve multiple disease or related phenotypes and use multiple methods of statistical analysis. The combination of multiple genetic loci, multiple phenotypes, and multiple methods of evaluating associations between genotype and phenotype means that modern genetic studies often involve the testing of an enormous number of hypotheses. When multiple hypothesis tests are performed in a study, there is a risk of inflation of the type I error rate (i.e., the chance of falsely claiming an association when there is none). Several methods for multiple-testing correction are in popular use, and they all have strengths and weaknesses. Because no single method is universally adopted or always appropriate, it is important to understand the principles, strengths, and weaknesses of the methods so that they can be applied appropriately in practice. In this article, we review the three principle methods for multiple-testing correction and provide guidance for calculating statistical power.
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An Overview of Mongenic and Syndromic Obesities in Humans
Chung, Wendy K.
2011-01-01
Obesity is increasing in prevalence in the United States with over 65% of adults considered overweight and 16% of children with BMI > 95 percentile. The heritability of obesity is estimated between 40 and 70%, but the genetics of obesity for most individuals are complex and involve the interaction of multiple genes and environment. There are however several syndromic and non-syndromic forms of obesity that are monogenic and oligogenic that provide insight into the underlying molecular control of food intake and the neural networks that control ingestive behavior and satiety to regulate body weight and which may interact with treatment exposures to produce or exacerbate obesity in childhood cancer survivors. PMID:21994130
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Vortman, Yoni; Safran, Rebecca J; Reiner Brodetzki, Tali; Dor, Roi; Lotem, Arnon
2015-01-01
The level of expression of sexually selected traits is generally determined by genes, environment and their interaction. In species that use multiple sexual signals which may be costly to produce, investing in the expression of one sexual signal may limit the expression of the other, favoring the evolution of a strategy for resource allocation among signals. As a result, even when the expression of sexual signals is condition dependent, the relative level of expression of each signal may be heritable. We tested this hypothesis in the East-Mediterranean barn swallow (Hirundo rustica transitiva), in which males have been shown to express two uncorrelated sexual signals: red-brown ventral coloration, and long tail streamers. We show that variation in both signals may partially be explained by age, as well as by paternal origin (genetic father-son regressions), but that the strongest similarity between fathers and sons is the relative allocation towards one trait or the other (relative expression index), rather than the expression of the traits themselves. These results suggest that the expression of one signal is not independent of the other, and that genetic strategies for resource allocation among sexual signals may be selected for during the evolution of multiple sexual signals.
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Vortman, Yoni; Safran, Rebecca J.; Reiner Brodetzki, Tali; Dor, Roi; Lotem, Arnon
2015-01-01
The level of expression of sexually selected traits is generally determined by genes, environment and their interaction. In species that use multiple sexual signals which may be costly to produce, investing in the expression of one sexual signal may limit the expression of the other, favoring the evolution of a strategy for resource allocation among signals. As a result, even when the expression of sexual signals is condition dependent, the relative level of expression of each signal may be heritable. We tested this hypothesis in the East-Mediterranean barn swallow (Hirundo rustica transitiva), in which males have been shown to express two uncorrelated sexual signals: red-brown ventral coloration, and long tail streamers. We show that variation in both signals may partially be explained by age, as well as by paternal origin (genetic father-son regressions), but that the strongest similarity between fathers and sons is the relative allocation towards one trait or the other (relative expression index), rather than the expression of the traits themselves. These results suggest that the expression of one signal is not independent of the other, and that genetic strategies for resource allocation among sexual signals may be selected for during the evolution of multiple sexual signals. PMID:25679206
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Chung, Wendy K.; Patki, Amit; Matsuoka, Naoki; Boyer, Bert B.; Liu, Nianjun; Musani, Solomon K.; Goropashnaya, Anna V.; Tan, Perciliz L.; Katsanis, Nicholas; Johnson, Stephen B.; Gregersen, Peter K.; Allison, David B.; Leibel, Rudolph L.; Tiwari, Hemant K.
2009-01-01
Objective Human adiposity is highly heritable, but few of the genes that predispose to obesity in most humans are known. We tested candidate genes in pathways related to food intake and energy expenditure for association with measures of adiposity. Methods We studied 355 genetic variants in 30 candidate genes in 7 molecular pathways related to obesity in two groups of adult subjects: 1,982 unrelated European Americans living in the New York metropolitan area drawn from the extremes of their body mass index (BMI) distribution and 593 related Yup'ik Eskimos living in rural Alaska characterized for BMI, body composition, waist circumference, and skin fold thicknesses. Data were analyzed by using a mixed model in conjunction with a false discovery rate (FDR) procedure to correct for multiple testing. Results After correcting for multiple testing, two single nucleotide polymorphisms (SNPs) in Ghrelin (GHRL) (rs35682 and rs35683) were associated with BMI in the New York European Americans. This association was not replicated in the Yup'ik participants. There was no evidence for gene × gene interactions among genes within the same molecular pathway after adjusting for multiple testing via FDR control procedure. Conclusion Genetic variation in GHRL may have a modest impact on BMI in European Americans. PMID:19077438
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Chung, Wendy K; Patki, Amit; Matsuoka, Naoki; Boyer, Bert B; Liu, Nianjun; Musani, Solomon K; Goropashnaya, Anna V; Tan, Perciliz L; Katsanis, Nicholas; Johnson, Stephen B; Gregersen, Peter K; Allison, David B; Leibel, Rudolph L; Tiwari, Hemant K
2009-01-01
Human adiposity is highly heritable, but few of the genes that predispose to obesity in most humans are known. We tested candidate genes in pathways related to food intake and energy expenditure for association with measures of adiposity. We studied 355 genetic variants in 30 candidate genes in 7 molecular pathways related to obesity in two groups of adult subjects: 1,982 unrelated European Americans living in the New York metropolitan area drawn from the extremes of their body mass index (BMI) distribution and 593 related Yup'ik Eskimos living in rural Alaska characterized for BMI, body composition, waist circumference, and skin fold thicknesses. Data were analyzed by using a mixed model in conjunction with a false discovery rate (FDR) procedure to correct for multiple testing. After correcting for multiple testing, two single nucleotide polymorphisms (SNPs) in Ghrelin (GHRL) (rs35682 and rs35683) were associated with BMI in the New York European Americans. This association was not replicated in the Yup'ik participants. There was no evidence for gene x gene interactions among genes within the same molecular pathway after adjusting for multiple testing via FDR control procedure. Genetic variation in GHRL may have a modest impact on BMI in European Americans.
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Genetic architecture and balancing selection: the life and death of differentiated variants.
Llaurens, Violaine; Whibley, Annabel; Joron, Mathieu
2017-05-01
Balancing selection describes any form of natural selection, which results in the persistence of multiple variants of a trait at intermediate frequencies within populations. By offering up a snapshot of multiple co-occurring functional variants and their interactions, systems under balancing selection can reveal the evolutionary mechanisms favouring the emergence and persistence of adaptive variation in natural populations. We here focus on the mechanisms by which several functional variants for a given trait can arise, a process typically requiring multiple epistatic mutations. We highlight how balancing selection can favour specific features in the genetic architecture and review the evolutionary and molecular mechanisms shaping this architecture. First, balancing selection affects the number of loci underlying differentiated traits and their respective effects. Control by one or few loci favours the persistence of differentiated functional variants by limiting intergenic recombination, or its impact, and may sometimes lead to the evolution of supergenes. Chromosomal rearrangements, particularly inversions, preventing adaptive combinations from being dissociated are increasingly being noted as features of such systems. Similarly, due to the frequency of heterozygotes maintained by balancing selection, dominance may be a key property of adaptive variants. High heterozygosity and limited recombination also influence associated genetic load, as linked recessive deleterious mutations may be sheltered. The capture of deleterious elements in a locus under balancing selection may reinforce polymorphism by further promoting heterozygotes. Finally, according to recent genomewide scans, balanced polymorphism might be more pervasive than generally thought. We stress the need for both functional and ecological studies to characterize the evolutionary mechanisms operating in these systems. © 2017 John Wiley & Sons Ltd.
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Ravits, John; Appel, Stanley; Baloh, Robert H; Barohn, Richard; Brooks, Benjamin Rix; Elman, Lauren; Floeter, Mary Kay; Henderson, Christopher; Lomen-Hoerth, Catherine; Macklis, Jeffrey D; McCluskey, Leo; Mitsumoto, Hiroshi; Przedborski, Serge; Rothstein, Jeffrey; Trojanowski, John Q; van den Berg, Leonard H; Ringel, Steven
2013-05-01
Amyotrophic lateral sclerosis (ALS) is characterized phenotypically by progressive weakness and neuropathologically by loss of motor neurons. Phenotypically, there is marked heterogeneity. Typical ALS has mixed upper motor neuron (UMN) and lower motor neuron (LMN) involvement. Primary lateral sclerosis has predominant UMN involvement. Progressive muscular atrophy has predominant LMN involvement. Bulbar and limb ALS have predominant regional involvement. Frontotemporal dementia has significant cognitive and behavioral involvement. These phenotypes can be so distinctive that they would seem to have differing biology. However, they cannot be distinguished, at least neuropathologically or genetically. In sporadic ALS (SALS), they are mostly characterized by ubiquitinated cytoplasmic inclusions of TDP-43. In familial ALS (FALS), where phenotypes are indistinguishable from SALS and similarly heterogeneous, each mutated gene has its own genetic and molecular signature. Overall, since the same phenotypes can have multiple causes including different gene mutations, there must be multiple molecular mechanisms causing ALS - and ALS is a syndrome. Since, however, multiple phenotypes can be caused by one single gene mutation, a single molecular mechanism can cause heterogeneity. What the mechanisms are remain unknown, but active propagation of the pathology neuroanatomically seems to be a principal component. Leading candidate mechanisms include RNA processing, cell-cell interactions between neurons and non-neuronal neighbors, focal seeding from a misfolded protein that has prion-like propagation, and fatal errors introduced during neurodevelopment of the motor system. If fundamental mechanisms could be identified and understood, ALS therapy could rationally target progression and stop the disease - a goal that seems increasingly achievable.
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Sequential divergence and the multiplicative origin of community diversity
Hood, Glen R.; Forbes, Andrew A.; Powell, Thomas H. Q.; Egan, Scott P.; Hamerlinck, Gabriela; Smith, James J.; Feder, Jeffrey L.
2015-01-01
Phenotypic and genetic variation in one species can influence the composition of interacting organisms within communities and across ecosystems. As a result, the divergence of one species may not be an isolated process, as the origin of one taxon could create new niche opportunities for other species to exploit, leading to the genesis of many new taxa in a process termed “sequential divergence.” Here, we test for such a multiplicative effect of sequential divergence in a community of host-specific parasitoid wasps, Diachasma alloeum, Utetes canaliculatus, and Diachasmimorpha mellea (Hymenoptera: Braconidae), that attack Rhagoletis pomonella fruit flies (Diptera: Tephritidae). Flies in the R. pomonella species complex radiated by sympatrically shifting and ecologically adapting to new host plants, the most recent example being the apple-infesting host race of R. pomonella formed via a host plant shift from hawthorn-infesting flies within the last 160 y. Using population genetics, field-based behavioral observations, host fruit odor discrimination assays, and analyses of life history timing, we show that the same host-related ecological selection pressures that differentially adapt and reproductively isolate Rhagoletis to their respective host plants (host-associated differences in the timing of adult eclosion, host fruit odor preference and avoidance behaviors, and mating site fidelity) cascade through the ecosystem and induce host-associated genetic divergence for each of the three members of the parasitoid community. Thus, divergent selection at lower trophic levels can potentially multiplicatively and rapidly amplify biodiversity at higher levels on an ecological time scale, which may sequentially contribute to the rich diversity of life. PMID:26499247
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Genetic modifiers of CHEK2*1100delC-associated breast cancer risk.
Muranen, Taru A; Greco, Dario; Blomqvist, Carl; Aittomäki, Kristiina; Khan, Sofia; Hogervorst, Frans; Verhoef, Senno; Pharoah, Paul D P; Dunning, Alison M; Shah, Mitul; Luben, Robert; Bojesen, Stig E; Nordestgaard, Børge G; Schoemaker, Minouk; Swerdlow, Anthony; García-Closas, Montserrat; Figueroa, Jonine; Dörk, Thilo; Bogdanova, Natalia V; Hall, Per; Li, Jingmei; Khusnutdinova, Elza; Bermisheva, Marina; Kristensen, Vessela; Borresen-Dale, Anne-Lise; Investigators, Nbcs; Peto, Julian; Dos Santos Silva, Isabel; Couch, Fergus J; Olson, Janet E; Hillemans, Peter; Park-Simon, Tjoung-Won; Brauch, Hiltrud; Hamann, Ute; Burwinkel, Barbara; Marme, Frederik; Meindl, Alfons; Schmutzler, Rita K; Cox, Angela; Cross, Simon S; Sawyer, Elinor J; Tomlinson, Ian; Lambrechts, Diether; Moisse, Matthieu; Lindblom, Annika; Margolin, Sara; Hollestelle, Antoinette; Martens, John W M; Fasching, Peter A; Beckmann, Matthias W; Andrulis, Irene L; Knight, Julia A; Investigators, kConFab/Aocs; Anton-Culver, Hoda; Ziogas, Argyrios; Giles, Graham G; Milne, Roger L; Brenner, Hermann; Arndt, Volker; Mannermaa, Arto; Kosma, Veli-Matti; Chang-Claude, Jenny; Rudolph, Anja; Devilee, Peter; Seynaeve, Caroline; Hopper, John L; Southey, Melissa C; John, Esther M; Whittemore, Alice S; Bolla, Manjeet K; Wang, Qin; Michailidou, Kyriaki; Dennis, Joe; Easton, Douglas F; Schmidt, Marjanka K; Nevanlinna, Heli
2017-05-01
CHEK2*1100delC is a founder variant in European populations that confers a two- to threefold increased risk of breast cancer (BC). Epidemiologic and family studies have suggested that the risk associated with CHEK2*1100delC is modified by other genetic factors in a multiplicative fashion. We have investigated this empirically using data from the Breast Cancer Association Consortium (BCAC). Using genotype data from 39,139 (624 1100delC carriers) BC patients and 40,063 (224) healthy controls from 32 BCAC studies, we analyzed the combined risk effects of CHEK2*1100delC and 77 common variants in terms of a polygenic risk score (PRS) and pairwise interaction. The PRS conferred odds ratios (OR) of 1.59 (95% CI: 1.21-2.09) per standard deviation for BC for CHEK2*1100delC carriers and 1.58 (1.55-1.62) for noncarriers. No evidence of deviation from the multiplicative model was found. The OR for the highest quintile of the PRS was 2.03 (0.86-4.78) for CHEK2*1100delC carriers, placing them in the high risk category according to UK NICE guidelines. The OR for the lowest quintile was 0.52 (0.16-1.74), indicating a lifetime risk close to the population average. Our results confirm the multiplicative nature of risk effects conferred by CHEK2*1100delC and the common susceptibility variants. Furthermore, the PRS could identify carriers at a high lifetime risk for clinical actions.Genet Med advance online publication 06 October 2016.
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Kandler, Christian; Riemann, Rainer
2013-07-01
In the current study, we examined the genetic and environmental sources of the links between individual religiousness and individual personality traits, perceived parental religiousness, and perceived peer religiousness. Data from 870 individuals (incl. 394 twin pairs) were analyzed. Variance in individual religiousness was significantly influenced by genetic effects, environmental influences shared by twins reared together, and individual-specific environmental influences. Individual religiousness showed significant associations with age, sex, specific personality traits (e.g., agreeableness, openness to values), and perceived religiousness of important social interaction partners, such as parents, best friends, and spouses. The links to personality traits were relatively small and primarily genetically mediated. The associations between individual religiousness and parental religiousness were substantial and mediated by shared environmental effects. These links significantly decreased across age accompanying a significant decrease of shared environmental influences on individual religiousness. The correlations between individual religiousness and perceived religiousness of spouses and best friends were relatively moderate but increased with age. These associations were mediated by genetic as well as nonshared environmental sources accompanying an increase of nonshared environmental influences on individual religiousness with age. The results suggest that inter-individual differences in religiousness are due to multiple sources.
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Genetic Differences Between Great Apes and Humans: Implications for Human Evolution
DOE Office of Scientific and Technical Information (OSTI.GOV)
Varki, Ajit
2004-03-17
When considering protein sequences, humans are 99-100% identical to chimpanzees and bonobos, our closest evolutionary relatives. The evolution of humans (and the unique features of our species) from a common ancestor with these great apes involved many steps, influenced by interactions amongst factors of genetic, developmental, ecological, microbial, climatic, behavioral, cultural and social origin. The genetic factors can be approached by direct comparisons of human and great ape genomes, genes and gene products, and by elucidating biochemical and biological consequences of the differences. We have discovered multiple genetic and biochemical differences between humans and great apes, particularly in relationship tomore » a family of cell surface molecules called sialic acids. These differences have implications for the human condition, ranging from susceptibility or resistance to microbial pathogens; effects on endogenous receptors in the immune system; potential effects on placental signaling; the expression of oncofetal antigens in cancers; consequences of dietary intake of animal foods; and the development of the mammalian brain. This talk will provide an overview of these and other genetic differences between humans and great apes, with attention to differences potentially relevant to the evolution of humans.« less
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Monir, Md. Mamun; Zhu, Jun
2017-01-01
Most of the genome-wide association studies (GWASs) for human complex diseases have ignored dominance, epistasis and ethnic interactions. We conducted comparative GWASs for total cholesterol using full model and additive models, which illustrate the impacts of the ignoring genetic variants on analysis results and demonstrate how genetic effects of multiple loci could differ across different ethnic groups. There were 15 quantitative trait loci with 13 individual loci and 3 pairs of epistasis loci identified by full model, whereas only 14 loci (9 common loci and 5 different loci) identified by multi-loci additive model. Again, 4 full model detected loci were not detected using multi-loci additive model. PLINK-analysis identified two loci and GCTA-analysis detected only one locus with genome-wide significance. Full model identified three previously reported genes as well as several new genes. Bioinformatics analysis showed some new genes are related with cholesterol related chemicals and/or diseases. Analyses of cholesterol data and simulation studies revealed that the full model performs were better than the additive-model performs in terms of detecting power and unbiased estimations of genetic variants of complex traits. PMID:28079101
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Chang, Audrey S; Bennett, Sarah M; Noor, Mohamed A F
2010-10-27
The Bateson-Dobzhansky-Muller model posits that hybrid incompatibilities result from genetic changes that accumulate during population divergence. Indeed, much effort in recent years has been devoted to identifying genes associated with hybrid incompatibilities, often with limited success, suggesting that hybrid sterility and inviability are frequently caused by complex interactions between multiple loci and not by single or a small number of gene pairs. Our previous study showed that the nature of epistasis between sterility-conferring QTL in the Drosophila persimilis-D. pseudoobscura bogotana species pair is highly specific. Here, we further dissect one of the three QTL underlying hybrid male sterility between these species and provide evidence for multiple factors within this QTL. This result indicates that the number of loci thought to contribute to hybrid dysfunction may have been underestimated, and we discuss how linkage and complex epistasis may be characteristic of the genetics of hybrid incompatibilities. We further pinpoint the location of one locus that confers hybrid male sterility when homozygous, dubbed "mule-like", to roughly 250 kilobases.
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Chang, Audrey S.; Bennett, Sarah M.; Noor, Mohamed A. F.
2010-01-01
The Bateson-Dobzhansky-Muller model posits that hybrid incompatibilities result from genetic changes that accumulate during population divergence. Indeed, much effort in recent years has been devoted to identifying genes associated with hybrid incompatibilities, often with limited success, suggesting that hybrid sterility and inviability are frequently caused by complex interactions between multiple loci and not by single or a small number of gene pairs. Our previous study showed that the nature of epistasis between sterility-conferring QTL in the Drosophila persimilis-D. pseudoobscura bogotana species pair is highly specific. Here, we further dissect one of the three QTL underlying hybrid male sterility between these species and provide evidence for multiple factors within this QTL. This result indicates that the number of loci thought to contribute to hybrid dysfunction may have been underestimated, and we discuss how linkage and complex epistasis may be characteristic of the genetics of hybrid incompatibilities. We further pinpoint the location of one locus that confers hybrid male sterility when homozygous, dubbed “mule-like”, to roughly 250 kilobases. PMID:21060872
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The differential view of genotype–phenotype relationships
Orgogozo, Virginie; Morizot, Baptiste; Martin, Arnaud
2015-01-01
An integrative view of diversity and singularity in the living world requires a better understanding of the intricate link between genotypes and phenotypes. Here we re-emphasize the old standpoint that the genotype–phenotype (GP) relationship is best viewed as a connection between two differences, one at the genetic level and one at the phenotypic level. As of today, predominant thinking in biology research is that multiple genes interact with multiple environmental variables (such as abiotic factors, culture, or symbionts) to produce the phenotype. Often, the problem of linking genotypes and phenotypes is framed in terms of genotype and phenotype maps, and such graphical representations implicitly bring us away from the differential view of GP relationships. Here we show that the differential view of GP relationships is a useful explanatory framework in the context of pervasive pleiotropy, epistasis, and environmental effects. In such cases, it is relevant to view GP relationships as differences embedded into differences. Thinking in terms of differences clarifies the comparison between environmental and genetic effects on phenotypes and helps to further understand the connection between genotypes and phenotypes. PMID:26042146
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Developmental mechanisms underlying variation in craniofacial disease and evolution.
Fish, Jennifer L
2016-07-15
Craniofacial disease phenotypes exhibit significant variation in penetrance and severity. Although many genetic contributions to phenotypic variation have been identified, genotype-phenotype correlations remain imprecise. Recent work in evolutionary developmental biology has exposed intriguing developmental mechanisms that potentially explain incongruities in genotype-phenotype relationships. This review focuses on two observations from work in comparative and experimental animal model systems that highlight how development structures variation. First, multiple genetic inputs converge on relatively few developmental processes. Investigation of when and how variation in developmental processes occurs may therefore help predict potential genetic interactions and phenotypic outcomes. Second, genetic mutation is typically associated with an increase in phenotypic variance. Several models outlining developmental mechanisms underlying mutational increases in phenotypic variance are discussed using Satb2-mediated variation in jaw size as an example. These data highlight development as a critical mediator of genotype-phenotype correlations. Future research in evolutionary developmental biology focusing on tissue-level processes may help elucidate the "black box" between genotype and phenotype, potentially leading to novel treatment, earlier diagnoses, and better clinical consultations for individuals affected by craniofacial anomalies. Copyright © 2015 Elsevier Inc. All rights reserved.
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Sun exposure, vitamin D receptor polymorphisms FokI and BsmI and risk of multiple primary melanoma.
Mandelcorn-Monson, Rochelle; Marrett, Loraine; Kricker, Anne; Armstrong, Bruce K; Orlow, Irene; Goumas, Chris; Paine, Susan; Rosso, Stefano; Thomas, Nancy; Millikan, Robert C; Pole, Jason D; Cotignola, Javier; Rosen, Cheryl; Kanetsky, Peter A; Lee-Taylor, Julia; Begg, Colin B; Berwick, Marianne
2011-12-01
Sunlight exposure increases risk of melanoma. Sunlight also potentiates cutaneous synthesis of vitamin D, which can inhibit melanoma cell growth and promote apoptosis. Vitamin D effects are mediated through the vitamin D receptor (VDR). We hypothesized that genetic variation in VDR affects the relationship of sun exposure to risk of a further melanoma in people who have already had one. We investigated the interaction between VDR polymorphisms and sun exposure in a population-based multinational study comparing 1138 patients with a multiple (second or subsequent) primary melanoma (cases) to 2151 patients with a first primary melanoma (controls); essentially a case-control study of melanoma in a population of melanoma survivors. Sun exposure was assessed using a questionnaire and interview, and was shown to be associated with multiple primary melanoma. VDR was genotyped at the FokI and BsmI loci and the main effects of variants at these loci and their interactions with sun exposure were analyzed. Only the BsmI variant was associated with multiple primary melanoma (OR=1.27, 95% CI 0.99-1.62 for the homozygous variant genotype). Joint effects analyses showed highest ORs in the high exposure, homozygous variant BsmI genotype category for each sun exposure variable. Stratified analyses showed somewhat higher ORs for the homozygous BsmI variant genotype in people with high sun exposure than with low sun exposure. P values for interaction, however, were high. These results suggest that risk of multiple primary melanoma is increased in people who have the BsmI variant of VDR. Copyright © 2011 Elsevier Ltd. All rights reserved.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Mohr, Georg; Del Campo, Mark; Turner, Kathryn G.
The Saccharomyces cerevisiae DEAD-box protein Mss116p is a general RNA chaperone that functions in splicing mitochondrial group I and group II introns. Recent X-ray crystal structures of Mss116p in complex with ATP analogs and single-stranded RNA show that the helicase core induces a bend in the bound RNA, as in other DEAD-box proteins, while a C-terminal extension (CTE) induces a second bend, resulting in RNA crimping. Here, we illuminate these structures by using high-throughput genetic selections, unigenic evolution, and analyses of in vivo splicing activity to comprehensively identify functionally important regions and permissible amino acid substitutions throughout Mss116p. The functionallymore » important regions include those containing conserved sequence motifs involved in ATP and RNA binding or interdomain interactions, as well as previously unidentified regions, including surface loops that may function in protein-protein interactions. The genetic selections recapitulate major features of the conserved helicase motifs seen in other DEAD-box proteins but also show surprising variations, including multiple novel variants of motif III (SAT). Patterns of amino acid substitutions indicate that the RNA bend induced by the helicase core depends on ionic and hydrogen-bonding interactions with the bound RNA; identify a subset of critically interacting residues; and indicate that the bend induced by the CTE results primarily from a steric block. Finally, we identified two conserved regions - one the previously noted post II region in the helicase core and the other in the CTE - that may help displace or sequester the opposite RNA strand during RNA unwinding.« less
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The genetic basis of local adaptation for pathogenic fungi in agricultural ecosystems.
Croll, Daniel; McDonald, Bruce A
2017-04-01
Local adaptation plays a key role in the evolutionary trajectory of host-pathogen interactions. However, the genetic architecture of local adaptation in host-pathogen systems is poorly understood. Fungal plant pathogens in agricultural ecosystems provide highly tractable models to quantify phenotypes and map traits to corresponding genomic loci. The outcome of crop-pathogen interactions is thought to be governed largely by gene-for-gene interactions. However, recent studies showed that virulence can be governed by quantitative trait loci and that many abiotic factors contribute to the outcome of the interaction. After introducing concepts of local adaptation and presenting examples from wild plant pathosystems, we focus this review on a major pathogen of wheat, Zymoseptoria tritici, to show how a multitude of traits can affect local adaptation. Zymoseptoria tritici adapted to different thermal environments across its distribution range, indicating that thermal adaptation may limit effective dispersal to different climates. The application of fungicides led to the rapid evolution of multiple, independent resistant populations. The degree of colony melanization showed strong pleiotropic effects with other traits, including trade-offs with colony growth rates and fungicide sensitivity. The success of the pathogen on its host can be assessed quantitatively by counting pathogen reproductive structures and measuring host damage based on necrotic lesions. Interestingly, these two traits can be weakly correlated and depend both on host and pathogen genotypes. Quantitative trait mapping studies showed that the genetic architecture of locally adapted traits varies from single loci with large effects to many loci with small individual effects. We discuss how local adaptation could hinder or accelerate the development of epidemics in agricultural ecosystems. © 2016 John Wiley & Sons Ltd.
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Human genetics of infectious diseases: a unified theory
Casanova, Jean-Laurent; Abel, Laurent
2007-01-01
Since the early 1950s, the dominant paradigm in the human genetics of infectious diseases postulates that rare monogenic immunodeficiencies confer vulnerability to multiple infectious diseases (one gene, multiple infections), whereas common infections are associated with the polygenic inheritance of multiple susceptibility genes (one infection, multiple genes). Recent studies, since 1996 in particular, have challenged this view. A newly recognised group of primary immunodeficiencies predisposing the individual to a principal or single type of infection is emerging. In parallel, several common infections have been shown to reflect the inheritance of one major susceptibility gene, at least in some populations. This novel causal relationship (one gene, one infection) blurs the distinction between patient-based Mendelian genetics and population-based complex genetics, and provides a unified conceptual frame for exploring the molecular genetic basis of infectious diseases in humans. PMID:17255931
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McKay, Gareth J; Loane, Edward; Nolan, John M; Patterson, Christopher C; Meyers, Kristin J; Mares, Julie A; Yonova-Doing, Ekaterina; Hammond, Christopher J; Beatty, Stephen; Silvestri, Giuliana
2013-01-01
Objective To investigate association of scavenger receptor class B, member 1 (SCARB1) genetic variants with serum carotenoid levels of lutein (L) and zeaxanthin (Z) and macular pigment optical density (MPOD). Design A cross-sectional study of healthy adults aged 20-70. Participants 302 participants recruited following local advertisement. Methods MPOD was measured by customized heterochromatic flicker photometry. Fasting blood samples were taken for serum L and Z measurement by HPLC and lipoprotein analysis by spectrophotometric assay. Forty-seven single nucleotide polymorphisms (SNPs) across SCARB1 were genotyped using Sequenom technology. Association analyses were performed using PLINK to compare allele and haplotype means, with adjustment for potential confounding and correction for multiple comparisons by permutation testing. Replication analysis was performed in the TwinsUK and CAREDS cohorts. Main outcome measures Odds ratios (ORs) for macular pigment optical density area, serum lutein and zeaxanthin concentrations associated with genetic variations in SCARB1 and interactions between SCARB1 and sex. Results Following multiple regression analysis with adjustment for age, body mass index, sex, high-density lipoprotein cholesterol (HDLc), low-density lipoprotein cholesterol (LDLc), triglycerides, smoking, dietary L and Z levels, 5 SNPs were significantly associated with serum L concentration and 1 SNP with MPOD (P<0.01). Only the association between rs11057841 and serum L withstood correction for multiple comparisons by permutation testing (P<0.01) and replicated in the TwinsUK cohort (P=0.014). Independent replication was also observed in the CAREDS cohort with rs10846744 (P=2×10−4), a SNP in high linkage disequilibrium with rs11057841 (r2=0.93). No significant interactions by sex were found. Haplotype analysis revealed no stronger association than obtained with single SNP analyses. Conclusions Our study has identified association between rs11057841 and serum L concentration (24% increase per T allele) in healthy subjects, independent of potential confounding factors. Our data supports further evaluation of the role for SCARB1 in the transport of macular pigment and the possible modulation of AMD risk through combating the effects of oxidative stress within the retina. PMID:23562302
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An integrated, structure- and energy-based view of the genetic code.
Grosjean, Henri; Westhof, Eric
2016-09-30
The principles of mRNA decoding are conserved among all extant life forms. We present an integrative view of all the interaction networks between mRNA, tRNA and rRNA: the intrinsic stability of codon-anticodon duplex, the conformation of the anticodon hairpin, the presence of modified nucleotides, the occurrence of non-Watson-Crick pairs in the codon-anticodon helix and the interactions with bases of rRNA at the A-site decoding site. We derive a more information-rich, alternative representation of the genetic code, that is circular with an unsymmetrical distribution of codons leading to a clear segregation between GC-rich 4-codon boxes and AU-rich 2:2-codon and 3:1-codon boxes. All tRNA sequence variations can be visualized, within an internal structural and energy framework, for each organism, and each anticodon of the sense codons. The multiplicity and complexity of nucleotide modifications at positions 34 and 37 of the anticodon loop segregate meaningfully, and correlate well with the necessity to stabilize AU-rich codon-anticodon pairs and to avoid miscoding in split codon boxes. The evolution and expansion of the genetic code is viewed as being originally based on GC content with progressive introduction of A/U together with tRNA modifications. The representation we present should help the engineering of the genetic code to include non-natural amino acids. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
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Kinnunen, Tarja K.
2014-01-01
Heparan sulfate proteoglycans (HSPGs) play critical roles in the development and adult physiology of all metazoan organisms. Most of the known molecular interactions of HSPGs are attributed to the structurally highly complex heparan sulfate (HS) glycans. However, whether a specific HSPG (such as syndecan) contains HS modifications that differ from another HSPG (such as glypican) has remained largely unresolved. Here, a neural model in C. elegans is used to demonstrate for the first time the relationship between specific HSPGs and HS modifications in a defined biological process in vivo. HSPGs are critical for the migration of hermaphrodite specific neurons (HSNs) as genetic elimination of multiple HSPGs leads to 80% defect of HSN migration. The effects of genetic elimination of HSPGs are additive, suggesting that multiple HSPGs, present in the migrating neuron and in the matrix, act in parallel to support neuron migration. Genetic analyses suggest that syndecan/sdn-1 and HS 6-O-sulfotransferase, hst-6, function in a linear signaling pathway and glypican/lon-2 and HS 2-O-sulfotransferase, hst-2, function together in a pathway that is parallel to sdn-1 and hst-6. These results suggest core protein specific HS modifications that are critical for HSN migration. In C. elegans, the core protein specificity of distinct HS modifications may be in part regulated at the level of tissue specific expression of genes encoding for HSPGs and HS modifying enzymes. Genetic analysis reveals that there is a delicate balance of HS modifications and eliminating one HS modifying enzyme in a compromised genetic background leads to significant changes in the overall phenotype. These findings are of importance with the view of HS as a critical regulator of cell signaling in normal development and disease. PMID:25054285
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Lapp, Hannah E; Ahmed, Sarah; Moore, Celia L; Hunter, Richard G
2018-02-21
Histories of early life stress (ELS) or social discrimination can reach levels of severity characterized as toxic to mental and physical health. Such toxic social stress during development has been linked to altered acute hypothalamic-pituitary-adrenal (HPA) response to social stress in adulthood. However, there are important individual differences in the size and direction of these effects. We explored developmental, genetic, epigenetic, and contextual sources of individual differences in the relationship between ELS, discrimination, and adult responses to acute social stress in a standard laboratory test. Additional measures included perceived status, social support, background activity of HPA axis, and genetic variants in aspects of the stress response system. Participants (n = 90) answered questions about historical and ongoing stress, provided a DNA sample to examine genetic polymorphisms and epigenetic marks, and underwent the Trier Social Stress Test (TSST) during which three saliva samples were collected to assess HPA function. Individuals who reported high levels of childhood adversity had a blunted salivary cortisol response to the TSST. Childhood adversity, discrimination experiences, and FKBP5 genotype were found to predict pretest cortisol levels. Following up on recent observations that the glucocorticoid receptor directly interacts with the mitochondrial genome, particularly the NADH dehydrogenase 6 (MT-ND6) gene, individuals who reported high childhood adversity were also found to have higher percent methylation across six CpG sites upstream of MT-ND6. These findings suggest multiple contributions across psychological, genetic, epigenetic, and social domains to vulnerability and resilience in hypothalamic-pituitary-adrenal axis regulation. Further study to examine how these multiple contributors affect developmental endpoints through integrated or independent pathways will be of use. Copyright © 2018 Elsevier Inc. All rights reserved.
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Genetic and epigenetic mechanisms of epilepsy: a review
Chen, Tian; Giri, Mohan; Xia, Zhenyi; Subedi, Yadu Nanda; Li, Yan
2017-01-01
Epilepsy is a common episodic neurological disorder or condition characterized by recurrent epileptic seizures, and genetics seems to play a key role in its etiology. Early linkage studies have localized multiple loci that may harbor susceptibility genes to epilepsy, and mutational analyses have detected a number of mutations involved in both ion channel and nonion channel genes in patients with idiopathic epilepsy. Genome-wide studies of epilepsy have found copy number variants at 2q24.2-q24.3, 7q11.22, 15q11.2-q13.3, and 16p13.11-p13.2, some of which disrupt multiple genes, such as NRXN1, AUTS2, NLGN1, CNTNAP2, GRIN2A, PRRT2, NIPA2, and BMP5, implicated for neurodevelopmental disorders, including intellectual disability and autism. Unfortunately, only a few common genetic variants have been associated with epilepsy. Recent exome-sequencing studies have found some genetic mutations, most of which are located in nonion channel genes such as the LGI1, PRRT2, EFHC1, PRICKLE, RBFOX1, and DEPDC5 and in probands with rare forms of familial epilepsy, and some of these genes are involved with the neurodevelopment. Since epigenetics plays a role in neuronal function from embryogenesis and early brain development to tissue-specific gene expression, epigenetic regulation may contribute to the genetic mechanism of neurodevelopment through which a gene and the environment interacting with each other affect the development of epilepsy. This review focused on the analytic tools used to identify epilepsy and then provided a summary of recent linkage and association findings, indicating the existence of novel genes on several chromosomes for further understanding of the biology of epilepsy. PMID:28761347
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Efficient inference for genetic association studies with multiple outcomes.
Ruffieux, Helene; Davison, Anthony C; Hager, Jorg; Irincheeva, Irina
2017-10-01
Combined inference for heterogeneous high-dimensional data is critical in modern biology, where clinical and various kinds of molecular data may be available from a single study. Classical genetic association studies regress a single clinical outcome on many genetic variants one by one, but there is an increasing demand for joint analysis of many molecular outcomes and genetic variants in order to unravel functional interactions. Unfortunately, most existing approaches to joint modeling are either too simplistic to be powerful or are impracticable for computational reasons. Inspired by Richardson and others (2010, Bayesian Statistics 9), we consider a sparse multivariate regression model that allows simultaneous selection of predictors and associated responses. As Markov chain Monte Carlo (MCMC) inference on such models can be prohibitively slow when the number of genetic variants exceeds a few thousand, we propose a variational inference approach which produces posterior information very close to that of MCMC inference, at a much reduced computational cost. Extensive numerical experiments show that our approach outperforms popular variable selection methods and tailored Bayesian procedures, dealing within hours with problems involving hundreds of thousands of genetic variants and tens to hundreds of clinical or molecular outcomes. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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Genetic testing in congenital heart disease: A clinical approach
Chaix, Marie A; Andelfinger, Gregor; Khairy, Paul
2016-01-01
Congenital heart disease (CHD) is the most common type of birth defect. Traditionally, a polygenic model defined by the interaction of multiple genes and environmental factors was hypothesized to account for different forms of CHD. It is now understood that the contribution of genetics to CHD extends beyond a single unified paradigm. For example, monogenic models and chromosomal abnormalities have been associated with various syndromic and non-syndromic forms of CHD. In such instances, genetic investigation and testing may potentially play an important role in clinical care. A family tree with a detailed phenotypic description serves as the initial screening tool to identify potentially inherited defects and to guide further genetic investigation. The selection of a genetic test is contingent upon the particular diagnostic hypothesis generated by clinical examination. Genetic investigation in CHD may carry the potential to improve prognosis by yielding valuable information with regards to personalized medical care, confidence in the clinical diagnosis, and/or targeted patient follow-up. Moreover, genetic assessment may serve as a tool to predict recurrence risk, define the pattern of inheritance within a family, and evaluate the need for further family screening. In some circumstances, prenatal or preimplantation genetic screening could identify fetuses or embryos at high risk for CHD. Although genetics may appear to constitute a highly specialized sector of cardiology, basic knowledge regarding inheritance patterns, recurrence risks, and available screening and diagnostic tools, including their strengths and limitations, could assist the treating physician in providing sound counsel. PMID:26981213
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Neas, Lucas M.; Blach, Colette; Haynes, Carol S.; LaRocque-Abramson, Karen; Grass, Elizabeth; Dowdy, Z. Elaine; Devlin, Robert B.; Diaz-Sanchez, David; Cascio, Wayne E.; Miranda, Marie Lynn; Gregory, Simon G.; Shah, Svati H.; Kraus, William E.; Hauser, Elizabeth R.
2017-01-01
Air pollution is a worldwide contributor to cardiovascular disease mortality and morbidity. Traffic-related air pollution is a widespread environmental exposure and is associated with multiple cardiovascular outcomes such as coronary atherosclerosis, peripheral arterial disease, and myocardial infarction. Despite the recognition of the importance of both genetic and environmental exposures to the pathogenesis of cardiovascular disease, studies of how these two contributors operate jointly are rare. We performed a genome-wide interaction study (GWIS) to examine gene-traffic exposure interactions associated with coronary atherosclerosis. Using race-stratified cohorts of 538 African-Americans (AA) and 1562 European-Americans (EA) from a cardiac catheterization cohort (CATHGEN), we identify gene-by-traffic exposure interactions associated with the number of significantly diseased coronary vessels as a measure of chronic atherosclerosis. We found five suggestive (P<1x10-5) interactions in the AA GWIS, of which two (rs1856746 and rs2791713) replicated in the EA cohort (P < 0.05). Both SNPs are in the PIGR-FCAMR locus and are eQTLs in lymphocytes. The protein products of both PIGR and FCAMR are implicated in inflammatory processes. In the EA GWIS, there were three suggestive interactions; none of these replicated in the AA GWIS. All three were intergenic; the most significant interaction was in a regulatory region associated with SAMSN1, a gene previously associated with atherosclerosis and B cell activation. In conclusion, we have uncovered several novel genes associated with coronary atherosclerosis in individuals chronically exposed to increased ambient concentrations of traffic air pollution. These genes point towards inflammatory pathways that may modify the effects of air pollution on cardiovascular disease risk. PMID:28355232
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Genetic interactions underlying otic placode induction and formation.
Solomon, Keely S; Kwak, Su-Jin; Fritz, Andreas
2004-07-01
The formation of the otic placode is a complex process requiring multiple inductive signals. In zebrafish, fgf3 and fgf8, dlx3b and dlx4b, and foxi1 have been identified as the earliest-acting genes in this process. fgf3 and fgf8 are required as inductive signals, whereas dlx3b, dlx4b, and foxi1 appear to act directly within otic primordia. We have investigated potential interactions among these genes. Depletion of either dlx3b and dlx4b or foxi1 leads to a delay of pax2a expression in the otic primordia and reduction of the otic vesicle. Depletion of both foxi1 and dlx3b results in a complete ablation of otic placode formation. A strong synergistic interaction is also observed among foxi1, fgf3, and fgf8, and a weaker interaction among dlx3b, fgf3, and fgf8. Misexpression of foxi1 can induce expression of pax8, an early marker for the otic primordia, in embryos treated with an inhibitor of fibroblast growth factor (FGF) signaling. Conversely, morpholino knockdown of foxi1 blocks ectopic pax8 expression and otic vesicle formation induced by misexpression of fgf3 and/or fgf8. The observed genetic interactions suggest a model in which foxi1 and dlx3b/dlx4b act in independent pathways together with distinct phases of FGF signaling to promote otic placode induction and development. Copyright 2004 Wiley-Liss, Inc.
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Cultural Neuroscience: Progress and Promise
Chiao, Joan Y.; Cheon, Bobby K.; Pornpattanangkul, Narun; Mrazek, Alissa J.; Blizinsky, Katherine D.
2013-01-01
The nature and origin of human diversity has been a source of intellectual curiosity since the beginning of human history. Contemporary advances in cultural and biological sciences provide unique opportunities for the emerging field of cultural neuroscience. Research in cultural neuroscience examines how cultural and genetic diversity shape the human mind, brain and behavior across multiple time scales: situation, ontogeny and phylogeny. Recent progress in cultural neuroscience provides novel theoretical frameworks for understanding the complex interaction of environmental, cultural and genetic factors in the production of adaptive human behavior. Here, we provide a brief history of cultural neuroscience, theoretical and methodological advances, as well as empirical evidence of the promise of and progress in the field. Implications of this research for population health disparities and public policy are discussed. PMID:23914126
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The FLIGHT Drosophila RNAi database
Bursteinas, Borisas; Jain, Ekta; Gao, Qiong; Baum, Buzz; Zvelebil, Marketa
2010-01-01
FLIGHT (http://flight.icr.ac.uk/) is an online resource compiling data from high-throughput Drosophila in vivo and in vitro RNAi screens. FLIGHT includes details of RNAi reagents and their predicted off-target effects, alongside RNAi screen hits, scores and phenotypes, including images from high-content screens. The latest release of FLIGHT is designed to enable users to upload, analyze, integrate and share their own RNAi screens. Users can perform multiple normalizations, view quality control plots, detect and assign screen hits and compare hits from multiple screens using a variety of methods including hierarchical clustering. FLIGHT integrates RNAi screen data with microarray gene expression as well as genomic annotations and genetic/physical interaction datasets to provide a single interface for RNAi screen analysis and datamining in Drosophila. PMID:20855970
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Ochoa-Martínez, Ángeles C; Ruíz-Vera, Tania; Almendarez-Reyna, Claudia I; Orta-García, Sandra T; Pérez-Maldonado, Iván N
2017-11-01
It has been demonstrated that Cardiovascular Diseases (CVD) are a consequence of the combination of genetic and environmental factors and/or the interaction between them. Therefore, the aim of this study was to evaluate the impact of polycyclic aromatic hydrocarbon (PAHs) exposure and PON1 Q192R polymorphism (genetic susceptibility) on serum asymmetric dimethylarginine (ADMA) levels in Mexican women (n = 206). Urinary 1-hydroxypyrene concentrations (1-OHP; exposure biomarker for PAHs) were quantified using a high-performance liquid chromatography technique, PON1 Q192R polymorphism was genotyped using TaqMan probes and serum ADMA concentrations were evaluated using a commercially available ELISA kit. Urinary 1-OHP levels detected in this study ranged from 0.07 to 9.37 μmol/mol of creatinine (0.13-18.0 μg/g of creatinine). Regarding allele frequency (PON1 Q192R polymorphism), the 192Q-allele frequency was 0.43 and for the 192R-allele it was 0.57. In relation to serum ADMA levels, the levels ranged from 0.06 to 1.46 μmol/L. Moreover, multiple linear regression analysis was performed and associations between urinary 1-OHP levels (β = 0.05, p = 0.002), PON1 Q192R polymorphism (β = 0.04, p = 0.003) and serum ADMA concentrations were found. Besides, an interaction (gene-environment interaction) of both independent variables (1-OHP and PON1 polymorphism) on serum ADMA levels was found (β = 0.04, p = 0.02) in the constructed multiple linear model. Therefore, according to the significance of this research, it is necessary to execute health programs to reduce cardiovascular risk in the assessed population. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Environmental and gene-environment interactions and risk of rheumatoid arthritis
Karlson, Elizabeth W.; Deane, Kevin
2012-01-01
Multiple environmental factors including hormones, dietary factors, infections and exposure to tobacco smoke as well as gene-environment interactions have been associated with increased risk for rheumatoid arthritis (RA). Importantly, the growing understanding of the prolonged period prior to the first onset of symptoms of RA suggests that these environmental and genetic factors are likely acting to drive the development of RA-related autoimmunity long before the appearance of the first joint symptoms and clinical findings that are characteristic of RA. Herein we will review these factors and interactions, especially those that have been investigated in a prospective fashion prior to the symptomatic onset of RA. We will also discuss how these factors may be explored in future study to further the understanding of the pathogenesis of RA, and ultimately perhaps develop preventive measures for this disease. PMID:22819092
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McKinney, Cushla; Stamp, Lisa K; Dalbeth, Nicola; Topless, Ruth K; Day, Richard O; Kannangara, Diluk Rw; Williams, Kenneth M; Janssen, Matthijs; Jansen, Timothy L; Joosten, Leo A; Radstake, Timothy R; Riches, Philip L; Tausche, Anne-Kathrin; Lioté, Frederic; So, Alexander; Merriman, Tony R
2015-10-13
The acute gout flare results from a localised self-limiting innate immune response to monosodium urate (MSU) crystals deposited in joints in hyperuricaemic individuals. Activation of the caspase recruitment domain-containing protein 8 (CARD8) NOD-like receptor pyrin-containing 3 (NLRP3) inflammasome by MSU crystals and production of mature interleukin-1β (IL-1β) is central to acute gouty arthritis. However very little is known about genetic control of the innate immune response involved in acute gouty arthritis. Therefore our aim was to test functional single nucleotide polymorphism (SNP) variants in the toll-like receptor (TLR)-inflammasome-IL-1β axis for association with gout. 1,494 gout cases of European and 863 gout cases of New Zealand (NZ) Polynesian (Māori and Pacific Island) ancestry were included. Gout was diagnosed by the 1977 ARA gout classification criteria. There were 1,030 Polynesian controls and 10,942 European controls including from the publicly-available Atherosclerosis Risk in Communities (ARIC) and Framingham Heart (FHS) studies. The ten SNPs were either genotyped by Sequenom MassArray or by Affymetrix SNP array or imputed in the ARIC and FHS datasets. Allelic association was done by logistic regression adjusting by age and sex with European and Polynesian data combined by meta-analysis. Sample sets were pooled for multiplicative interaction analysis, which was also adjusted by sample set. Eleven SNPs were tested in the TLR2, CD14, IL1B, CARD8, NLRP3, MYD88, P2RX7, DAPK1 and TNXIP genes. Nominally significant (P < 0.05) associations with gout were detected at CARD8 rs2043211 (OR = 1.12, P = 0.007), IL1B rs1143623 (OR = 1.10, P = 0.020) and CD14 rs2569190 (OR = 1.08; P = 0.036). There was significant multiplicative interaction between CARD8 and IL1B (P = 0.005), with the IL1B risk genotype amplifying the risk effect of CARD8. There is evidence for association of gout with functional variants in CARD8, IL1B and CD14. The gout-associated allele of IL1B increases expression of IL-1β - the multiplicative interaction with CARD8 would be consistent with a synergy of greater inflammasome activity (resulting from reduced CARD8) combined with higher levels of pre-IL-1β expression leading to increased production of mature IL-1β in gout.
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Liscum, E; Stowe-Evans, E L
2000-09-01
Phototropism is the process by which plants reorient growth of various organs, most notably stems, in response to lateral differences in light quantity and/or quality. The ubiquitous nature of the phototropic response in the plant kingdom implies that it provides some adaptive evolutionary advantage. Upon visual inspection it is tempting to surmise that phototropic curvatures result from a relatively simple growth response to a directional stimulus. However, detailed photophysiological, and more recently genetic and molecular, studies have demonstrated that phototropism is in fact regulated by complex interactions among several photosensory systems. At least two receptors, phototropin and a presently unidentified receptor, appear to mediate the primary photoreception of directional blue light cues in dark-grown plants. PhyB may also function as a primary receptor to detect lateral increases in far-red light in neighbor-avoidance responses of light-grown plants. Phytochromes (phyA and phyB at a minimum) also appear to function as secondary receptors to regulate adaptation processes that ultimately modulate the magnitude of curvature induced by primary photoperception. As a result of the interactions of these multiple photosensory systems plants are able to maximize the adaptive advantage of the phototropic response in ever changing light environments.
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Multiparametric Imaging of Organ System Interfaces
Vandoorne, Katrien; Nahrendorf, Matthias
2017-01-01
Cardiovascular diseases are a consequence of genetic and environmental risk factors that together generate arterial wall and cardiac pathologies. Blood vessels connect multiple systems throughout the entire body and allow organs to interact via circulating messengers. These same interactions facilitate nervous and metabolic system influence on cardiovascular health. Multiparametric imaging offers the opportunity to study these interfacing systems’ distinct processes, to quantify their interactions and to explore how these contribute to cardiovascular disease. Noninvasive multiparametric imaging techniques are emerging tools that can further our understanding of this complex and dynamic interplay. PET/MRI and multichannel optical imaging are particularly promising because they can simultaneously sample multiple biomarkers. Preclinical multiparametric diagnostics could help discover clinically relevant biomarker combinations pivotal for understanding cardiovascular disease. Interfacing systems important to cardiovascular disease include the immune, nervous and hematopoietic systems. These systems connect with ‘classical’ cardiovascular organs, like the heart and vasculature, and with the brain. The dynamic interplay between these systems and organs enables processes such as hemostasis, inflammation, angiogenesis, matrix remodeling, metabolism and fibrosis. As the opportunities provided by imaging expand, mapping interconnected systems will help us decipher the complexity of cardiovascular disease and monitor novel therapeutic strategies. PMID:28360260
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Proceedings of the 2017 annual meeting of the Fetal Alcohol Spectrum Disorders study group.
Wozniak, Jeffrey R; Klintsova, Anna Y; Hamilton, Derek A; Mooney, Sandra M
2018-06-01
The 2017 Fetal Alcohol Spectrum Disorders Study Group (FASDSG) meeting was titled "Prenatal alcohol exposure in the context of multiple factors affecting brain development." The theme was reflected in the interactions between members of the Teratology Society and the FASDSG this year. The first keynote speaker, Elaine Faustman, Ph.D., was a liaison between the societies and spoke about systems biology and the multiple genetic and environmental influences on development. The second keynote speaker, Rebecca Knickmeyer, Ph.D., discussed population neuroscience and multiple influences on brain development. The conference presented updates from three government agencies and short presentations by junior and senior investigators showcasing late-breaking FASD research. The conference was capped by Dr. John Hannigan, Ph.D., the recipient of the 2017 Henry Rosett award for career-long contributions to the field. Copyright © 2017 Elsevier Inc. All rights reserved.
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Braberg, Hannes; Moehle, Erica A.; Shales, Michael; Guthrie, Christine; Krogan, Nevan J.
2014-01-01
We have achieved a residue-level resolution of genetic interaction mapping – a technique that measures how the function of one gene is affected by the alteration of a second gene – by analyzing point mutations. Here, we describe how to interpret point mutant genetic interactions, and outline key applications for the approach, including interrogation of protein interaction interfaces and active sites, and examination of post-translational modifications. Genetic interaction analysis has proven effective for characterizing cellular processes; however, to date, systematic high-throughput genetic interaction screens have relied on gene deletions or knockdowns, which limits the resolution of gene function analysis and poses problems for multifunctional genes. Our point mutant approach addresses these issues, and further provides a tool for in vivo structure-function analysis that complements traditional biophysical methods. We also discuss the potential for genetic interaction mapping of point mutations in human cells and its application to personalized medicine. PMID:24842270
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Lobach, Irvna; Fan, Ruzone; Carroll, Raymond T.
2011-01-01
With the advent of dense single nucleotide polymorphism genotyping, population-based association studies have become the major tools for identifying human disease genes and for fine gene mapping of complex traits. We develop a genotype-based approach for association analysis of case-control studies of gene-environment interactions in the case when environmental factors are measured with error and genotype data are available on multiple genetic markers. To directly use the observed genotype data, we propose two genotype-based models: genotype effect and additive effect models. Our approach offers several advantages. First, the proposed risk functions can directly incorporate the observed genotype data while modeling the linkage disequihbrium information in the regression coefficients, thus eliminating the need to infer haplotype phase. Compared with the haplotype-based approach, an estimating procedure based on the proposed methods can be much simpler and significantly faster. In addition, there is no potential risk due to haplotype phase estimation. Further, by fitting the proposed models, it is possible to analyze the risk alleles/variants of complex diseases, including their dominant or additive effects. To model measurement error, we adopt the pseudo-likelihood method by Lobach et al. [2008]. Performance of the proposed method is examined using simulation experiments. An application of our method is illustrated using a population-based case-control study of association between calcium intake with the risk of colorectal adenoma development. PMID:21031455
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[Application of Multiple Genetic Markers in a Case of Determination of Half Sibling].
Yang, Xue; Shi, Mei-sen; Yuan, Li; Lu, Di
2016-02-01
A case of half sibling was determined with multiple genetic markers, which could be potentially applied for determination of half sibling relationship from same father. Half sibling relationship was detected by 39 autosomal STR genetic markers, 23 Y-chromosomal STR genetic markers and 12 X -chromosomal STR genetic markers among ZHAO -1, ZHAO -2, ZHAO -3, ZHAO -4, and ZHAO-5. According to autosomal STR, Y-STR and X-STR genotyping results, it was determined that ZHAO-4 (alleged half sibling) was unrelated with ZHAO-1 and ZHAO-2; however, ZHAO-3 (alleged half sibling), ZHAO-5 (alleged half sibling) shared same genetic profile with ZHAO-1, and ZHAO-2 from same father. It is reliable to use multiple genetic markers and family gene reconstruction to determine half sibling relationship from same father, but it is difficult to determination by calculating half sibling index with ITO and discriminant functions.
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Speciation through the lens of biomechanics: locomotion, prey capture and reproductive isolation.
Higham, Timothy E; Rogers, Sean M; Langerhans, R Brian; Jamniczky, Heather A; Lauder, George V; Stewart, William J; Martin, Christopher H; Reznick, David N
2016-09-14
Speciation is a multifaceted process that involves numerous aspects of the biological sciences and occurs for multiple reasons. Ecology plays a major role, including both abiotic and biotic factors. Whether populations experience similar or divergent ecological environments, they often adapt to local conditions through divergence in biomechanical traits. We investigate the role of biomechanics in speciation using fish predator-prey interactions, a primary driver of fitness for both predators and prey. We highlight specific groups of fishes, or specific species, that have been particularly valuable for understanding these dynamic interactions and offer the best opportunities for future studies that link genetic architecture to biomechanics and reproductive isolation (RI). In addition to emphasizing the key biomechanical techniques that will be instrumental, we also propose that the movement towards linking biomechanics and speciation will include (i) establishing the genetic basis of biomechanical traits, (ii) testing whether similar and divergent selection lead to biomechanical divergence, and (iii) testing whether/how biomechanical traits affect RI. Future investigations that examine speciation through the lens of biomechanics will propel our understanding of this key process. © 2016 The Author(s).
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Oxytocin and vasopressin systems in genetic syndromes and neurodevelopmental disorders
Francis, S.M.; Sagar, A.; Levin-Decanini, T.; Liu, W.; Carter, C.S.; Jacob, S.
2015-01-01
Oxytocin (OT) and arginine vasopressin (AVP) are two small, related neuropeptide hormones found in many mammalian species, including humans. Dysregulation of these neuropeptides have been associated with changes in behavior, especially social interactions. We review how the OT and AVP systems have been investigated in Autism Spectrum Disorder (ASD), Prader–Willi Syndrome (PWS), Williams Syndrome (WS) and Fragile X syndrome (FXS). All of these neurodevelopmental disorders (NDD) are marked by social deficits. While PWS, WS and FXS have identified genetic mutations, ASD stems from multiple genes with complex interactions. Animal models of NDD are invaluable for studying the role and relatedness of OT and AVP in the developing brain. We present data from a FXS mouse model affecting the fragile X mental retardation 1 (Fmr1) gene, resulting in decreased OT and AVP staining cells in some brain regions. Reviewing the research about OT and AVP in these NDD suggests that altered OT pathways may be downstream from different etiological factors and perturbations in development. This has implications for ongoing studies of the therapeutic application of OT in NDD. PMID:24462936
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HBS1L-MYB intergenic variants modulate fetal hemoglobin via long-range MYB enhancers
Stadhouders, Ralph; Aktuna, Suleyman; Thongjuea, Supat; Aghajanirefah, Ali; Pourfarzad, Farzin; van IJcken, Wilfred; Lenhard, Boris; Rooks, Helen; Best, Steve; Menzel, Stephan; Grosveld, Frank; Thein, Swee Lay; Soler, Eric
2014-01-01
Genetic studies have identified common variants within the intergenic region (HBS1L-MYB) between GTP-binding elongation factor HBS1L and myeloblastosis oncogene MYB on chromosome 6q that are associated with elevated fetal hemoglobin (HbF) levels and alterations of other clinically important human erythroid traits. It is unclear how these noncoding sequence variants affect multiple erythrocyte characteristics. Here, we determined that several HBS1L-MYB intergenic variants affect regulatory elements that are occupied by key erythroid transcription factors within this region. These elements interact with MYB, a critical regulator of erythroid development and HbF levels. We found that several HBS1L-MYB intergenic variants reduce transcription factor binding, affecting long-range interactions with MYB and MYB expression levels. These data provide a functional explanation for the genetic association of HBS1L-MYB intergenic polymorphisms with human erythroid traits and HbF levels. Our results further designate MYB as a target for therapeutic induction of HbF to ameliorate sickle cell and β-thalassemia disease severity. PMID:24614105
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Sessa, Alessandro; Ciabatti, Ernesto; Drechsel, Daniela; Massimino, Luca; Colasante, Gaia; Giannelli, Serena; Satoh, Takashi; Akira, Shizuo; Guillemot, Francois; Broccoli, Vania
2017-06-01
The T-box containing Tbr2 gene encodes for a transcription factor essential for the specification of the intermediate neural progenitors (INPs) originating the excitatory neurons of the cerebral cortex. However, its overall mechanism of action, direct target genes and cofactors remain unknown. Herein, we carried out global gene expression profiling combined with genome-wide binding site identification to determine the molecular pathways regulated by TBR2 in INPs. This analysis led to the identification of novel protein-protein interactions that control multiple features of INPs including cell-type identity, morphology, proliferation and migration dynamics. In particular, NEUROG2 and JMJD3 were found to associate with TBR2 revealing unexplored TBR2-dependent mechanisms. These interactions can explain, at least in part, the role of this transcription factor in the implementation of the molecular program controlling developmental milestones during corticogenesis. These data identify TBR2 as a major determinant of the INP-specific traits by regulating both genetic and epigenetic pathways. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Speciation through the lens of biomechanics: locomotion, prey capture and reproductive isolation
Rogers, Sean M.; Langerhans, R. Brian; Jamniczky, Heather A.; Lauder, George V.; Stewart, William J.; Martin, Christopher H.; Reznick, David N.
2016-01-01
Speciation is a multifaceted process that involves numerous aspects of the biological sciences and occurs for multiple reasons. Ecology plays a major role, including both abiotic and biotic factors. Whether populations experience similar or divergent ecological environments, they often adapt to local conditions through divergence in biomechanical traits. We investigate the role of biomechanics in speciation using fish predator–prey interactions, a primary driver of fitness for both predators and prey. We highlight specific groups of fishes, or specific species, that have been particularly valuable for understanding these dynamic interactions and offer the best opportunities for future studies that link genetic architecture to biomechanics and reproductive isolation (RI). In addition to emphasizing the key biomechanical techniques that will be instrumental, we also propose that the movement towards linking biomechanics and speciation will include (i) establishing the genetic basis of biomechanical traits, (ii) testing whether similar and divergent selection lead to biomechanical divergence, and (iii) testing whether/how biomechanical traits affect RI. Future investigations that examine speciation through the lens of biomechanics will propel our understanding of this key process. PMID:27629033
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Genetic vulnerability to diabetes and obesity: does education offset the risk?
Liu, S Y; Walter, S; Marden, J; Rehkopf, D H; Kubzansky, L D; Nguyen, T; Glymour, M M
2015-02-01
The prevalence of type 2 diabetes (T2D) and obesity has recently increased dramatically. These common diseases are likely to arise from the interaction of multiple genetic, socio-demographic and environmental risk factors. While previous research has found genetic risk and education to be strong predictors of these diseases, few studies to date have examined their joint effects. This study investigates whether education modifies the association between genetic background and risk for type 2 diabetes (T2D) and obesity. Using data from non-Hispanic Whites in the Health and Retirement Study (HRS, n = 8398), we tested whether education modifies genetic risk for obesity and T2D, offsetting genetic effects; whether this effect is larger for individuals who have high risk for other (unobserved) reasons, i.e., at higher quantiles of HbA1c and BMI; and whether effects differ by gender. We measured T2D risk using Hemoglobin A1c (HbA1c) level, and obesity risk using body-mass index (BMI). We constructed separate genetic risk scores (GRS) for obesity and diabetes respectively based on the most current available information on the single nucleotide polymorphism (SNPs) confirmed as genome-wide significant predictors for BMI (29 SNPs) and diabetes risk (39 SNPs). Linear regression models with years of schooling indicate that the effect of genetic risk on HbA1c is smaller among people with more years of schooling and larger among those with less than a high school (HS) degree compared to HS degree-holders. Quantile regression models show that the GRS × education effect systematically increased along the HbA1c outcome distribution; for example the GRS × years of education interaction coefficient was -0.01 (95% CI = -0.03, 0.00) at the 10th percentile compared to -0.03 (95% CI = -0.07, 0.00) at the 90th percentile. These results suggest that education may be an important socioeconomic source of heterogeneity in responses to genetic vulnerability to T2D. Copyright © 2014. Published by Elsevier Ltd.
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Langenberg, C; Sharp, S; Forouhi, NG; Franks, P; Schulze, MB; Kerrison, N; Ekelund, U; Barroso, I; Panico, S; Tormo, M; Spranger, J; Griffin, S; van der Schouw, YT; Amiano, P; Ardanaz, E; Arriola, L; Balkau, B; Barricarte, A; Beulens, JWJ; Boeing, H; Bueno-de-Mesquita, HB; Buijsse, BB; Chirlaque Lopez, MD; Clavel-Chapelon, F; Crowe, FL; de Lauzon-Guillan, B; Deloukas, P; Dorronsoro, M; Drogan, DD; Froguel, P; Gonzalez, C; Grioni, S; Groop, L; Groves, C; Hainaut, P; Halkjaer, J; Hallmans, G; Hansen, T; Kaaks, R; Key, TJ; Khaw, K; Koulman, A; Mattiello, A; Navarro, C; Nilsson, P; Norat, T; Overvad, K; Palla, L; Palli, D; Pedersen, O; Peeters, PH; Quirós, JR; Ramachandran, A; Rodriguez-Suarez, L; Rolandsson, O; Romaguera, D; Romieu, I; Sacerdote, C; Sánchez, M; Sandbaek, A; Slimani, N; Sluijs, I; Spijkerman, AMW; Teucher, B; Tjonneland, A; Tumino, R; van der A, DL; Verschuren, WMM; Tuomilehto, J; Feskens, E; McCarthy, M; Riboli, E; Wareham, NJ
2014-01-01
Background Studying gene-lifestyle interaction may help to identify lifestyle factors that modify genetic susceptibility and uncover genetic loci exerting important subgroup effects. Adequately powered studies with prospective, unbiased, standardised assessment of key behavioural factors for gene-lifestyle studies are lacking. Objective To establish a type 2 diabetes case-cohort study designed to investigate how genetic and potentially modifiable lifestyle and behavioral factors, particularly diet and physical activity, interact in their influence on the risk of developing type 2 diabetes. Methods Funded by the Sixth European Framework Programme, InterAct consortium partners ascertained and verified incident cases of type 2 diabetes occurring in European Prospective Investigation into Cancer and Nutrition (EPIC) cohorts between 1991 and 2007 from 8 of the 10 EPIC countries. A pragmatic, high sensitivity approach was used for case ascertainment including multiple sources at each EPIC centre, followed by diagnostic verification. Prentice-weighted Cox regression and random effects meta-analyses were used to investigate differences in diabetes incidence by age and sex. Results A total of 12,403 verified incident cases of type 2 diabetes occurred during 3.99 million person-years of follow-up of 340,234 EPIC participants eligible for InterAct. We defined a centre stratified subcohort of 16,154 individuals for comparative analyses. Individuals with incident diabetes that were randomly selected into the subcohort (n=778) were included as cases in the analyses. All prevalent diabetes cases were excluded from the study. InterAct cases were followed-up for an average of 6.9 years, 49.7% were men. Mean baseline age and age at diagnosis were 55.6 and 62.5 years, mean BMI and waist were 29.4 kg/m2 and 102.7 cm in men, and 30.1 kg/m2 and 92.8 cm in women, respectively. Risk of type 2 diabetes increased linearly with age, with an overall hazard ratio (95% CI) of 1.56 (1.48; 1.64) for a 10 year age difference, adjusted for sex. A male excess in the risk of incident diabetes was consistently observed across all countries, with a pooled hazard ratio of 1.51 (1.39; 1.64), adjusted for age. Conclusions InterAct is a large, well powered, prospective study which will inform our understanding of the interplay between genes and lifestyle factors on the risk of type 2 diabetes development. PMID:21717116
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Myopathology of Adult and Paediatric Mitochondrial Diseases
Phadke, Rahul
2017-01-01
Mitochondria are dynamic organelles ubiquitously present in nucleated eukaryotic cells, subserving multiple metabolic functions, including cellular ATP generation by oxidative phosphorylation (OXPHOS). The OXPHOS machinery comprises five transmembrane respiratory chain enzyme complexes (RC). Defective OXPHOS gives rise to mitochondrial diseases (mtD). The incredible phenotypic and genetic diversity of mtD can be attributed at least in part to the RC dual genetic control (nuclear DNA (nDNA) and mitochondrial DNA (mtDNA)) and the complex interaction between the two genomes. Despite the increasing use of next-generation-sequencing (NGS) and various omics platforms in unravelling novel mtD genes and pathomechanisms, current clinical practice for investigating mtD essentially involves a multipronged approach including clinical assessment, metabolic screening, imaging, pathological, biochemical and functional testing to guide molecular genetic analysis. This review addresses the broad muscle pathology landscape including genotype–phenotype correlations in adult and paediatric mtD, the role of immunodiagnostics in understanding some of the pathomechanisms underpinning the canonical features of mtD, and recent diagnostic advances in the field. PMID:28677615
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OncoSimulR: genetic simulation with arbitrary epistasis and mutator genes in asexual populations.
Diaz-Uriarte, Ramon
2017-06-15
OncoSimulR implements forward-time genetic simulations of biallelic loci in asexual populations with special focus on cancer progression. Fitness can be defined as an arbitrary function of genetic interactions between multiple genes or modules of genes, including epistasis, restrictions in the order of accumulation of mutations, and order effects. Mutation rates can differ among genes, and can be affected by (anti)mutator genes. Also available are sampling from simulations (including single-cell sampling), plotting the genealogical relationships of clones and generating and plotting fitness landscapes. Implemented in R and C ++, freely available from BioConductor for Linux, Mac and Windows under the GNU GPL license. Version 2.5.9 or higher available from: http://www.bioconductor.org/packages/devel/bioc/html/OncoSimulR.html . GitHub repository at: https://github.com/rdiaz02/OncoSimul. ramon.diaz@iib.uam.es. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.
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Development and Evolution of Character Displacement
Pfennig, David W.; Pfennig, Karin S.
2012-01-01
Character displacement occurs when competition for either resources or successful reproduction imposes divergent selection on interacting species, causing divergence in traits associated with resource use or reproduction. Here, we describe how character displacement can be mediated either by genetically canalized changes (i.e., changes that reflect allelic or genotype frequency changes) or by phenotypic plasticity. We also discuss how these two mechanisms influence the tempo of character displacement. Specifically, we suggest that, under some conditions, character displacement mediated by phenotypic plasticity might occur more rapidly than that mediated by genetically canalized changes. Finally, we describe how these two mechanisms may act together and determine character displacement’s mode, such that it proceeds through an initial phase in which trait divergence is environmentally induced to a later phase in which divergence becomes genetically canalized. This plasticity-first hypothesis predicts that character displacement should be generally mediated by ancestral plasticity and that it will arise similarly in multiple, independently evolving populations. We conclude by highlighting future directions for research that would test these predictions. PMID:22257002
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MOLECULAR ALTERATIONS IN GLIOBLASTOMA: POTENTIAL TARGETS FOR IMMUNOTHERAPY
Haque, Azizul; Banik, Naren L.; Ray, Swapan K.
2015-01-01
Glioblastoma is the most common and deadly brain tumor, possibly arising from genetic and epigenetic alterations in normal astroglial cells. Multiple cytogenetic, chromosomal, and genetic alterations have been identified in glioblastoma, with distinct expression of antigens (Ags) and biomarkers that may alter therapeutic potential of this aggressive cancer. Current therapy consists of surgical resection, followed by radiation therapy and chemotherapy. In spite of these treatments, the prognosis for glioblastoma patients is poor. Although recent studies have focused on the development of novel immunotherapeutics against glioblastoma, little is known about glioblastoma specific immune responses. A better understanding of the molecular interactions among glioblastoma tumors, host immune cells, and the tumor microenvironment may give rise to novel integrated approaches for the simultaneous control of tumor escape pathways and the activation of antitumor immune responses. This review provides a detailed overview concerning genetic alterations in glioblastoma, their effects on Ag and biomarker expression and the future design of chemoimmunotherapeutics against glioblastoma. PMID:21199773
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Ouzir, Mounir; Errami, Mohammed
2016-09-01
Currently, about 246 million people around the world have used an illicit drug. The reasons for this use are multiple: e.g. to augment the sensation of pleasure or to reduce the withdrawal and other aversive effects of a given substance. This raises the problem of addiction, which remains a disease of modern society. This review offers a comprehensive update of the different theories about the etiology of addictive behaviors with emphasis on the neurobiological, environmental, psychopathological, behavioural and genetic aspects of addictions, discussed from an evolutionary perspective. The main conclusion of this review is that vulnerability to drug addiction suggests an interaction between many brain systems (including the reward, decision-making, serotonergic, oxytocin, interoceptive insula, CRF, norepinephrine, dynorphin/KOR, orexin and vasopressin systems), genetic predisposition, sociocultural context, impulsivity and drugs types. Further advances in biological and psychological science are needed to address the problems of addiction at its roots. Copyright © 2016 Elsevier Inc. All rights reserved.
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Bacteria Facilitate Enteric Virus Co-infection of Mammalian Cells and Promote Genetic Recombination.
Erickson, Andrea K; Jesudhasan, Palmy R; Mayer, Melinda J; Narbad, Arjan; Winter, Sebastian E; Pfeiffer, Julie K
2018-01-10
RNA viruses exist in genetically diverse populations due to high levels of mutations, many of which reduce viral fitness. Interestingly, intestinal bacteria can promote infection of several mammalian enteric RNA viruses, but the mechanisms and consequences are unclear. We screened a panel of 41 bacterial strains as a platform to determine how different bacteria impact infection of poliovirus, a model enteric virus. Most bacterial strains, including those extracted from cecal contents of mice, bound poliovirus, with each bacterium binding multiple virions. Certain bacterial strains increased viral co-infection of mammalian cells even at a low virus-to-host cell ratio. Bacteria-mediated viral co-infection correlated with bacterial adherence to cells. Importantly, bacterial strains that induced viral co-infection facilitated genetic recombination between two different viruses, thereby removing deleterious mutations and restoring viral fitness. Thus, bacteria-virus interactions may increase viral fitness through viral recombination at initial sites of infection, potentially limiting abortive infections. Copyright © 2017 Elsevier Inc. All rights reserved.
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Functional mapping of yeast genomes by saturated transposition
Michel, Agnès H; Hatakeyama, Riko; Kimmig, Philipp; Arter, Meret; Peter, Matthias; Matos, Joao; De Virgilio, Claudio; Kornmann, Benoît
2017-01-01
Yeast is a powerful model for systems genetics. We present a versatile, time- and labor-efficient method to functionally explore the Saccharomyces cerevisiae genome using saturated transposon mutagenesis coupled to high-throughput sequencing. SAturated Transposon Analysis in Yeast (SATAY) allows one-step mapping of all genetic loci in which transposons can insert without disrupting essential functions. SATAY is particularly suited to discover loci important for growth under various conditions. SATAY (1) reveals positive and negative genetic interactions in single and multiple mutant strains, (2) can identify drug targets, (3) detects not only essential genes, but also essential protein domains, (4) generates both null and other informative alleles. In a SATAY screen for rapamycin-resistant mutants, we identify Pib2 (PhosphoInositide-Binding 2) as a master regulator of TORC1. We describe two antagonistic TORC1-activating and -inhibiting activities located on opposite ends of Pib2. Thus, SATAY allows to easily explore the yeast genome at unprecedented resolution and throughput. DOI: http://dx.doi.org/10.7554/eLife.23570.001 PMID:28481201
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Genetics Reasoning with Multiple External Representations.
ERIC Educational Resources Information Center
Tsui, Chi-Yan; Treagust, David F.
2003-01-01
Explores a case study of a class of 10th grade students whose learning of genetics involved activities using BioLogica, a computer program that features multiple external representations (MERs). Findings indicate that the MERs in BioLogica contributed to students' development of genetics reasoning by engendering their motivation and interest but…
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Abdeltawab, Nourtan F.; Aziz, Ramy K.; Kansal, Rita; Rowe, Sarah L.; Su, Yin; Gardner, Lidia; Brannen, Charity; Nooh, Mohammed M.; Attia, Ramy R.; Abdelsamed, Hossam A.; Taylor, William L.; Lu, Lu; Williams, Robert W.; Kotb, Malak
2008-01-01
Striking individual differences in severity of group A streptococcal (GAS) sepsis have been noted, even among patients infected with the same bacterial strain. We had provided evidence that HLA class II allelic variation contributes significantly to differences in systemic disease severity by modulating host responses to streptococcal superantigens. Inasmuch as the bacteria produce additional virulence factors that participate in the pathogenesis of this complex disease, we sought to identify additional gene networks modulating GAS sepsis. Accordingly, we applied a systems genetics approach using a panel of advanced recombinant inbred mice. By analyzing disease phenotypes in the context of mice genotypes we identified a highly significant quantitative trait locus (QTL) on Chromosome 2 between 22 and 34 Mb that strongly predicts disease severity, accounting for 25%–30% of variance. This QTL harbors several polymorphic genes known to regulate immune responses to bacterial infections. We evaluated candidate genes within this QTL using multiple parameters that included linkage, gene ontology, variation in gene expression, cocitation networks, and biological relevance, and identified interleukin1 alpha and prostaglandin E synthases pathways as key networks involved in modulating GAS sepsis severity. The association of GAS sepsis with multiple pathways underscores the complexity of traits modulating GAS sepsis and provides a powerful approach for analyzing interactive traits affecting outcomes of other infectious diseases. PMID:18421376
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Transgressive Hybrids as Hopeful Monsters.
Dittrich-Reed, Dylan R; Fitzpatrick, Benjamin M
2013-06-01
The origin of novelty is a critical subject for evolutionary biologists. Early geneticists speculated about the sudden appearance of new species via special macromutations, epitomized by Goldschmidt's infamous "hopeful monster". Although these ideas were easily dismissed by the insights of the Modern Synthesis, a lingering fascination with the possibility of sudden, dramatic change has persisted. Recent work on hybridization and gene exchange suggests an underappreciated mechanism for the sudden appearance of evolutionary novelty that is entirely consistent with the principles of modern population genetics. Genetic recombination in hybrids can produce transgressive phenotypes, "monstrous" phenotypes beyond the range of parental populations. Transgressive phenotypes can be products of epistatic interactions or additive effects of multiple recombined loci. We compare several epistatic and additive models of transgressive segregation in hybrids and find that they are special cases of a general, classic quantitative genetic model. The Dobzhansky-Muller model predicts "hopeless" monsters, sterile and inviable transgressive phenotypes. The Bateson model predicts "hopeful" monsters with fitness greater than either parental population. The complementation model predicts both. Transgressive segregation after hybridization can rapidly produce novel phenotypes by recombining multiple loci simultaneously. Admixed populations will also produce many similar recombinant phenotypes at the same time, increasing the probability that recombinant "hopeful monsters" will establish true-breeding evolutionary lineages. Recombination is not the only (or even most common) process generating evolutionary novelty, but might be the most credible mechanism for sudden appearance of new forms.
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Li, Qiang; Byrns, Brook; Badawi, Mohamed A.; Diallo, Abdoulaye Banire; Danyluk, Jean; Sarhan, Fathey; Zou, Jitao
2018-01-01
Cold acclimation and winter survival in cereal species is determined by complicated environmentally regulated gene expression. However, studies investigating these complex cold responses are mostly conducted in controlled environments that only consider the responses to single environmental variables. In this study, we have comprehensively profiled global transcriptional responses in crowns of field-grown spring and winter wheat (Triticum aestivum) genotypes and their near-isogenic lines with the VRN-A1 alleles swapped. This in-depth analysis revealed multiple signaling, interactive pathways that influence cold tolerance and phenological development to optimize plant growth and development in preparation for a wide range of over-winter stresses. Investigation of genetic differences at the VRN-A1 locus revealed that a vernalization requirement maintained a higher level of cold response pathways while VRN-A1 genetically promoted floral development. Our results also demonstrated the influence of genetic background on the expression of cold and flowering pathways. The link between delayed shoot apex development and the induction of cold tolerance was reflected by the gradual up-regulation of abscisic acid-dependent and C-REPEAT-BINDING FACTOR pathways. This was accompanied by the down-regulation of key genes involved in meristem development as the autumn progressed. The chromosome location of differentially expressed genes between the winter and spring wheat genetic backgrounds showed a striking pattern of biased gene expression on chromosomes 6A and 6D, indicating a transcriptional regulation at the genome level. This finding adds to the complexity of the genetic cascades and gene interactions that determine the evolutionary patterns of both phenological development and cold tolerance traits in wheat. PMID:29259104
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Jääskeläinen, Tiina; Paananen, Jussi; Lindström, Jaana; Eriksson, Johan G; Tuomilehto, Jaakko; Uusitupa, Matti
2013-11-01
Recent genome-wide association studies have identified multiple loci associated with BMI or the waist:hip ratio (WHR). However, evidence on gene-lifestyle interactions is still scarce, and investigation of the effects of well-documented dietary and other lifestyle data is warranted to assess whether genetic risk can be modified by lifestyle. We assessed whether previously established BMI and WHR genetic variants associate with obesity and weight change in the Finnish Diabetes Prevention Study, and whether the associations are modified by dietary factors or physical activity. Individuals (n 459) completed a 3 d food record and were genotyped for twenty-six BMI- and fourteen WHR-related variants. The effects of the variants individually and in combination were investigated in relation to obesity and to 1- and 3-year weight change by calculating genetic risk scores (GRS). The GRS were separately calculated for BMI and the WHR by summing the increasing alleles weighted by their published effect sizes. At baseline, the GRS were not associated with total intakes of energy, macronutrients or fibre. The mean 1- and 3-year weight changes were not affected by the BMI or WHR GRS. During the 3-year follow-up, a trend for higher BMI by the GRS was detected especially in those who reported a diet low in fibre (P for interaction=0·065). Based on the present findings, it appears unlikely that obesity-predisposing variants substantially modify the effect of lifestyle modification on the success of weight reduction in the long term. In addition, these findings suggest that the association between the BMI-related genetic variants and obesity could be modulated by the diet.
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Klempan, Timothy A; Ernst, Carl; Deleva, Vesselina; Labonte, Benoit; Turecki, Gustavo
2009-11-01
A number of studies have suggested deficits in myelination and glial gene expression in different psychiatric disorders. We examined the brain expression and genetic/epigenetic regulation of QKI, an oligodendrocyte-specific RNA binding protein important for cell development and myelination. The microarray-based expression of QKI was evaluated in cortical and subcortical brain regions from suicide victims with a diagnosis of major depression (n = 16) and control subjects (n = 13). These findings were also assessed with a real-time (quantitative polymerase chain reaction [qPCR]) approach, with QKI protein levels evaluated through immunoblotting. Identification of a QKI promoter sequence was then used to examine genetic and epigenetic variation at the QKI locus. The messenger RNA (mRNA) levels of multiple transcripts of QKI were evaluated on Affymetrix microarrays, revealing significant reductions in 11 cortical regions and the hippocampus and amygdala of suicide victims compared with control subjects. Microarray findings were confirmed by qPCR, and reduced expression of QKI protein was identified in orbitofrontal cortex. Analysis of promoter variation and methylation state in a subset of individuals did not identify differences at the genetic or epigenetic level between depressed suicide victims and control subjects. The observation of consistent reductions in multiple isoforms of QKI mRNA in depressed suicide victims supports the growing body of evidence for a role of myelination-related deficits in the etiology of psychiatric disorders. A specific role of QKI in this process is implied by its reduced expression and known interactions with genes involved in oligodendrocyte determination; however, QKI gene variation responsible for these changes remains to be identified.
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Genetics of coronary artery disease and myocardial infarction
Dai, Xuming; Wiernek, Szymon; Evans, James P; Runge, Marschall S
2016-01-01
Atherosclerotic coronary artery disease (CAD) comprises a broad spectrum of clinical entities that include asymptomatic subclinical atherosclerosis and its clinical complications, such as angina pectoris, myocardial infarction (MI) and sudden cardiac death. CAD continues to be the leading cause of death in industrialized society. The long-recognized familial clustering of CAD suggests that genetics plays a central role in its development, with the heritability of CAD and MI estimated at approximately 50% to 60%. Understanding the genetic architecture of CAD and MI has proven to be difficult and costly due to the heterogeneity of clinical CAD and the underlying multi-decade complex pathophysiological processes that involve both genetic and environmental interactions. This review describes the clinical heterogeneity of CAD and MI to clarify the disease spectrum in genetic studies, provides a brief overview of the historical understanding and estimation of the heritability of CAD and MI, recounts major gene discoveries of potential causal mutations in familial CAD and MI, summarizes CAD and MI-associated genetic variants identified using candidate gene approaches and genome-wide association studies (GWAS), and summarizes the current status of the construction and validations of genetic risk scores for lifetime risk prediction and guidance for preventive strategies. Potential protective genetic factors against the development of CAD and MI are also discussed. Finally, GWAS have identified multiple genetic factors associated with an increased risk of in-stent restenosis following stent placement for obstructive CAD. This review will also address genetic factors associated with in-stent restenosis, which may ultimately guide clinical decision-making regarding revascularization strategies for patients with CAD and MI. PMID:26839654
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Trotter, R. Talbot; Cobb, Neil S.; Whitham, Thomas G.
2002-01-01
To understand climate change, dendrochronologists have used tree ring analyses to reconstruct past climates, as well as ecological processes such as herbivore population dynamics. Such reconstructions, however, have been hindered by a lack of experiments that separate the influences of confounding impacts on tree rings, such as herbivores and the interactions of multiple factors. Our long-term experiments with scale insects on resistant and susceptible pines demonstrate three major points that are important to the application of this commonly used tool. (i) Herbivory reduced tree ring growth by 25–35%. (ii) The impact on ring growth distorted climate reconstruction, resulting in the overestimation of past moisture levels by more than 2-fold. Our data suggest that, if distortion because of herbivory has been a problem in previous reconstructions, estimates of the magnitude of recent climate changes are likely to be conservative. (iii) Our studies support a detectible plant resistance × herbivore × climate interaction in the tree ring record. Because resistance and susceptibility to herbivory are known to be genetically based in many systems, the potential exists to incorporate plant genetics into the field of dendrochronology, where it may be used to screen distortions from the tree ring record. PMID:12110729
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Multi-variant study of obesity risk genes in African Americans: The Jackson Heart Study.
Liu, Shijian; Wilson, James G; Jiang, Fan; Griswold, Michael; Correa, Adolfo; Mei, Hao
2016-11-30
Genome-wide association study (GWAS) has been successful in identifying obesity risk genes by single-variant association analysis. For this study, we designed steps of analysis strategy and aimed to identify multi-variant effects on obesity risk among candidate genes. Our analyses were focused on 2137 African American participants with body mass index measured in the Jackson Heart Study and 657 common single nucleotide polymorphisms (SNPs) genotyped at 8 GWAS-identified obesity risk genes. Single-variant association test showed that no SNPs reached significance after multiple testing adjustment. The following gene-gene interaction analysis, which was focused on SNPs with unadjusted p-value<0.10, identified 6 significant multi-variant associations. Logistic regression showed that SNPs in these associations did not have significant linear interactions; examination of genetic risk score evidenced that 4 multi-variant associations had significant additive effects of risk SNPs; and haplotype association test presented that all multi-variant associations contained one or several combinations of particular alleles or haplotypes, associated with increased obesity risk. Our study evidenced that obesity risk genes generated multi-variant effects, which can be additive or non-linear interactions, and multi-variant study is an important supplement to existing GWAS for understanding genetic effects of obesity risk genes. Copyright © 2016 Elsevier B.V. All rights reserved.
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Combinatorial interaction between CCM pathway genes precipitates hemorrhagic stroke.
Gore, Aniket V; Lampugnani, Maria Grazia; Dye, Louis; Dejana, Elisabetta; Weinstein, Brant M
2008-01-01
Intracranial hemorrhage (ICH) is a particularly severe form of stroke whose etiology remains poorly understood, with a highly variable appearance and onset of the disease (Felbor et al., 2006; Frizzell, 2005; Lucas et al., 2003). In humans, mutations in any one of three CCM genes causes an autosomal dominant genetic ICH disorder characterized by cerebral cavernous malformations (CCM). Recent evidence highlighting multiple interactions between the three CCM gene products and other proteins regulating endothelial junctional integrity suggests that minor deficits in these other proteins could potentially predispose to, or help to initiate, CCM, and that combinations of otherwise silent genetic deficits in both the CCM and interacting proteins might explain some of the variability in penetrance and expressivity of human ICH disorders. Here, we test this idea by combined knockdown of CCM pathway genes in zebrafish. Reducing the function of rap1b, which encodes a Ras GTPase effector protein for CCM1/Krit1, disrupts endothelial junctions in vivo and in vitro, showing it is a crucial player in the CCM pathway. Importantly, a minor reduction of Rap1b in combination with similar reductions in the products of other CCM pathway genes results in a high incidence of ICH. These findings support the idea that minor polygenic deficits in the CCM pathway can strongly synergize to initiate ICH.
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An integrated approach to characterize genetic interaction networks in yeast metabolism
Szappanos, Balázs; Kovács, Károly; Szamecz, Béla; Honti, Frantisek; Costanzo, Michael; Baryshnikova, Anastasia; Gelius-Dietrich, Gabriel; Lercher, Martin J.; Jelasity, Márk; Myers, Chad L.; Andrews, Brenda J.; Boone, Charles; Oliver, Stephen G.; Pál, Csaba; Papp, Balázs
2011-01-01
Intense experimental and theoretical efforts have been made to globally map genetic interactions, yet we still do not understand how gene-gene interactions arise from the operation of biomolecular networks. To bridge the gap between empirical and computational studies, we: i) quantitatively measure genetic interactions between ~185,000 metabolic gene pairs in Saccharomyces cerevisiae, ii) superpose the data on a detailed systems biology model of metabolism, and iii) introduce a machine-learning method to reconcile empirical interaction data with model predictions. We systematically investigate the relative impacts of functional modularity and metabolic flux coupling on the distribution of negative and positive genetic interactions. We also provide a mechanistic explanation for the link between the degree of genetic interaction, pleiotropy, and gene dispensability. Last, we demonstrate the feasibility of automated metabolic model refinement by correcting misannotations in NAD biosynthesis and confirming them by in vivo experiments. PMID:21623372
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A predictive model for canine dilated cardiomyopathy-a meta-analysis of Doberman Pinscher data.
Simpson, Siobhan; Edwards, Jennifer; Emes, Richard D; Cobb, Malcolm A; Mongan, Nigel P; Rutland, Catrin S
2015-01-01
Dilated cardiomyopathy is a prevalent and often fatal disease in humans and dogs. Indeed dilated cardiomyopathy is the third most common form of cardiac disease in humans, reported to affect approximately 36 individuals per 100,000 individuals. In dogs, dilated cardiomyopathy is the second most common cardiac disease and is most prevalent in the Irish Wolfhound, Doberman Pinscher and Newfoundland breeds. Dilated cardiomyopathy is characterised by ventricular chamber enlargement and systolic dysfunction which often leads to congestive heart failure. Although multiple human loci have been implicated in the pathogenesis of dilated cardiomyopathy, the identified variants are typically associated with rare monogenic forms of dilated cardiomyopathy. The potential for multigenic interactions contributing to human dilated cardiomyopathy remains poorly understood. Consistent with this, several known human dilated cardiomyopathy loci have been excluded as common causes of canine dilated cardiomyopathy, although canine dilated cardiomyopathy resembles the human disease functionally. This suggests additional genetic factors contribute to the dilated cardiomyopathy phenotype.This study represents a meta-analysis of available canine dilated cardiomyopathy genetic datasets with the goal of determining potential multigenic interactions relating the sex chromosome genotype (XX vs. XY) with known dilated cardiomyopathy associated loci on chromosome 5 and the PDK4 gene in the incidence and progression of dilated cardiomyopathy. The results show an interaction between known canine dilated cardiomyopathy loci and an unknown X-linked locus. Our study is the first to test a multigenic contribution to dilated cardiomyopathy and suggest a genetic basis for the known sex-disparity in dilated cardiomyopathy outcomes.
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Foley, B R; Rose, C G; Rundle, D E; Leong, W; Edmands, S
2013-11-01
Detailed studies of the genetics of speciation have focused on a few model systems, particularly Drosophila. The copepod Tigriopus californicus offers an alternative that differs from standard animal models in that it lacks heteromorphic chromosomes (instead, sex determination is polygenic) and has reduced opportunities for sexual conflict, because females mate only once. Quantitative trait loci (QTL) mapping was conducted on reciprocal F2 hybrids between two strongly differentiated populations, using a saturated linkage map spanning all 12 autosomes and the mitochondrion. By comparing sexes, a possible sex ratio distorter was found but no sex chromosomes. Although studies of standard models often find an excess of hybrid male sterility factors, we found no QTL for sterility and multiple QTL for hybrid viability (indicated by non-Mendelian adult ratios) and other characters. Viability problems were found to be stronger in males, but the usual explanations for weaker hybrid males (sex chromosomes, sensitivity of spermatogenesis, sexual selection) cannot fully account for these male viability problems. Instead, higher metabolic rates may amplify deleterious effects in males. Although many studies of standard speciation models find the strongest genetic incompatibilities to be nuclear-nuclear (specifically X chromosome-autosome), we found the strongest deleterious interaction in this system was mito-nuclear. Consistent with the snowball theory of incompatibility accumulation, we found that trigenic interactions in this highly divergent cross were substantially more frequent (>6×) than digenic interactions. This alternative system thus allows important comparisons to studies of the genetics of reproductive isolation in more standard model systems.
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Lu, Guanjun; Lin, Aiqing; Luo, Jinhong; Blondel, Dimitri V; Meiklejohn, Kelly A; Sun, Keping; Feng, Jiang
2013-11-05
China is characterized by complex topographic structure and dramatic palaeoclimatic changes, making species biogeography studies particularly interesting. Previous researchers have also demonstrated multiple species experienced complex population histories, meanwhile multiple shelters existed in Chinese mainland. Despite this, species phylogeography is still largely unexplored. In the present study, we used a combination of microsatellites and mitochondrial DNA (mtDNA) to investigate the phylogeography of the east Asian fish-eating bat (Myotis pilosus). Phylogenetic analyses showed that M. pilosus comprised three main lineages: A, B and C, which corresponded to distinct geographic populations of the Yangtze Plain (YTP), Sichuan Basin (SCB) and North and South of China (NSC), respectively. The most recent common ancestor of M. pilosus was dated as 0.25 million years before present (BP). Population expansion events were inferred for populations of Clade C, North China Plain region, Clade B and YunGui Plateau region at 38,700, 15,900, 4,520 and 4,520 years BP, respectively. Conflicting results were obtained from mtDNA and microsatellite analyses; strong population genetic structure was obtained from mtDNA data but not microsatellite data. The microsatellite data indicated that genetic subdivision fits an isolation-by-distance (IBD) model, but the mtDNA data failed to support this model. Our results suggested that Pleistocene climatic oscillations might have had a profound influence on the demographic history of M. pilosus. Spatial genetic structures of maternal lineages that are different from those observed in other sympatric bats species may be as a result of interactions among special population history and local environmental factors. There are at least three possible refugia for M. pilosus during glacial episodes. Apparently contradictory genetic structure patterns of mtDNA and microsatellite could be explained by male-mediated gene flow among populations. This study also provides insights on the necessity of conservation of M. pilosus populations to conserve this genetic biodiversity, especially in the areas of YTP, SCB and NSC regions.
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Environmental confounding in gene-environment interaction studies.
Vanderweele, Tyler J; Ko, Yi-An; Mukherjee, Bhramar
2013-07-01
We show that, in the presence of uncontrolled environmental confounding, joint tests for the presence of a main genetic effect and gene-environment interaction will be biased if the genetic and environmental factors are correlated, even if there is no effect of either the genetic factor or the environmental factor on the disease. When environmental confounding is ignored, such tests will in fact reject the joint null of no genetic effect with a probability that tends to 1 as the sample size increases. This problem with the joint test vanishes under gene-environment independence, but it still persists if estimating the gene-environment interaction parameter itself is of interest. Uncontrolled environmental confounding will bias estimates of gene-environment interaction parameters even under gene-environment independence, but it will not do so if the unmeasured confounding variable itself does not interact with the genetic factor. Under gene-environment independence, if the interaction parameter without controlling for the environmental confounder is nonzero, then there is gene-environment interaction either between the genetic factor and the environmental factor of interest or between the genetic factor and the unmeasured environmental confounder. We evaluate several recently proposed joint tests in a simulation study and discuss the implications of these results for the conduct of gene-environment interaction studies.
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Genome-wide interaction study of smoking and bladder cancer risk
Figueroa, Jonine D.; Han, Summer S.; Garcia-Closas, Montserrat; Baris, Dalsu; Jacobs, Eric J.; Kogevinas, Manolis; Schwenn, Molly; Malats, Nuria; Johnson, Alison; Purdue, Mark P.; Caporaso, Neil; Landi, Maria Teresa; Prokunina-Olsson, Ludmila; Wang, Zhaoming; Hutchinson, Amy; Burdette, Laurie; Wheeler, William; Vineis, Paolo; Siddiq, Afshan; Cortessis, Victoria K.; Kooperberg, Charles; Cussenot, Olivier; Benhamou, Simone; Prescott, Jennifer; Porru, Stefano; Bueno-de-Mesquita, H.Bas; Trichopoulos, Dimitrios; Ljungberg, Börje; Clavel-Chapelon, Françoise; Weiderpass, Elisabete; Krogh, Vittorio; Dorronsoro, Miren; Travis, Ruth; Tjønneland, Anne; Brenan, Paul; Chang-Claude, Jenny; Riboli, Elio; Conti, David; Gago-Dominguez, Manuela; Stern, Mariana C.; Pike, Malcolm C.; Van Den Berg, David; Yuan, Jian-Min; Hohensee, Chancellor; Rodabough, Rebecca; Cancel-Tassin, Geraldine; Roupret, Morgan; Comperat, Eva; Chen, Constance; De Vivo, Immaculata; Giovannucci, Edward; Hunter, David J.; Kraft, Peter; Lindstrom, Sara; Carta, Angela; Pavanello, Sofia; Arici, Cecilia; Mastrangelo, Giuseppe; Karagas, Margaret R.; Schned, Alan; Armenti, Karla R.; Hosain, G.M.Monawar; Haiman, Chris A.; Fraumeni, Joseph F.; Chanock, Stephen J.; Chatterjee, Nilanjan; Rothman, Nathaniel; Silverman, Debra T.
2014-01-01
Bladder cancer is a complex disease with known environmental and genetic risk factors. We performed a genome-wide interaction study (GWAS) of smoking and bladder cancer risk based on primary scan data from 3002 cases and 4411 controls from the National Cancer Institute Bladder Cancer GWAS. Alternative methods were used to evaluate both additive and multiplicative interactions between individual single nucleotide polymorphisms (SNPs) and smoking exposure. SNPs with interaction P values < 5 × 10− 5 were evaluated further in an independent dataset of 2422 bladder cancer cases and 5751 controls. We identified 10 SNPs that showed association in a consistent manner with the initial dataset and in the combined dataset, providing evidence of interaction with tobacco use. Further, two of these novel SNPs showed strong evidence of association with bladder cancer in tobacco use subgroups that approached genome-wide significance. Specifically, rs1711973 (FOXF2) on 6p25.3 was a susceptibility SNP for never smokers [combined odds ratio (OR) = 1.34, 95% confidence interval (CI) = 1.20–1.50, P value = 5.18 × 10− 7]; and rs12216499 (RSPH3-TAGAP-EZR) on 6q25.3 was a susceptibility SNP for ever smokers (combined OR = 0.75, 95% CI = 0.67–0.84, P value = 6.35 × 10− 7). In our analysis of smoking and bladder cancer, the tests for multiplicative interaction seemed to more commonly identify susceptibility loci with associations in never smokers, whereas the additive interaction analysis identified more loci with associations among smokers—including the known smoking and NAT2 acetylation interaction. Our findings provide additional evidence of gene–environment interactions for tobacco and bladder cancer. PMID:24662972
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2012-01-01
Background Understanding gene interactions is a fundamental question in systems biology. Currently, modeling of gene regulations using the Bayesian Network (BN) formalism assumes that genes interact either instantaneously or with a certain amount of time delay. However in reality, biological regulations, both instantaneous and time-delayed, occur simultaneously. A framework that can detect and model both these two types of interactions simultaneously would represent gene regulatory networks more accurately. Results In this paper, we introduce a framework based on the Bayesian Network (BN) formalism that can represent both instantaneous and time-delayed interactions between genes simultaneously. A novel scoring metric having firm mathematical underpinnings is also proposed that, unlike other recent methods, can score both interactions concurrently and takes into account the reality that multiple regulators can regulate a gene jointly, rather than in an isolated pair-wise manner. Further, a gene regulatory network (GRN) inference method employing an evolutionary search that makes use of the framework and the scoring metric is also presented. Conclusion By taking into consideration the biological fact that both instantaneous and time-delayed regulations can occur among genes, our approach models gene interactions with greater accuracy. The proposed framework is efficient and can be used to infer gene networks having multiple orders of instantaneous and time-delayed regulations simultaneously. Experiments are carried out using three different synthetic networks (with three different mechanisms for generating synthetic data) as well as real life networks of Saccharomyces cerevisiae, E. coli and cyanobacteria gene expression data. The results show the effectiveness of our approach. PMID:22691450
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Seow, Wei Jie; Pan, Wen-Chi; Kile, Molly L; Tong, Lin; Baccarelli, Andrea A; Quamruzzaman, Quazi; Rahman, Mahmuder; Mostofa, Golam; Rakibuz-Zaman, Muhammad; Kibriya, Muhammad; Ahsan, Habibul; Lin, Xihong; Christiani, David C
2015-07-01
Single-nucleotide polymorphisms (SNPs) in inflammation, one-carbon metabolism, and skin cancer genes might influence susceptibility to arsenic-induced skin lesions. A case-control study was conducted in Pabna, Bangladesh (2001-2003), and the drinking-water arsenic concentration was measured for each participant. A panel of 25 candidate SNPs was analyzed in 540 cases and 400 controls. Logistic regression was used to estimate the association between each SNP and the potential for gene-environment interactions in the skin lesion risk, with adjustments for relevant covariates. Replication testing was conducted in an independent Bangladesh population with 488 cases and 2,794 controls. In the discovery population, genetic variants in the one-carbon metabolism genes phosphatidylethanolamine N-methyltransferase (rs2278952, P for interaction = .004; rs897453, P for interaction = .05) and dihydrofolate reductase (rs1650697, P for interaction = .02), the inflammation gene interleukin 10 (rs3024496, P for interaction =.04), and the skin cancer genes inositol polyphosphate-5-phosphatase (INPP5A; rs1133400, P for interaction = .03) and xeroderma pigmentosum complementation group C (rs2228000, P for interaction = .01) significantly modified the association between arsenic and skin lesions after adjustments for multiple comparisons. The significant gene-environment interaction between a SNP in the INPP5A gene (rs1133400) and water arsenic with respect to the skin lesion risk was successfully replicated in an independent population (P for interaction = .03). Minor allele carriers of the skin cancer gene INPP5A modified the odds of arsenic-induced skin lesions in both main and replicative populations. Genetic variation in INPP5A appears to have a role in susceptibility to arsenic toxicity. © 2015 American Cancer Society.
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Yin, Tong; König, Sven
2018-03-01
The most common approach in dairy cattle to prove genotype by environment interactions is a multiple-trait model application, and considering the same traits in different environments as different traits. We enhanced such concepts by defining continuous phenotypic, genetic, and genomic herd descriptors, and applying random regression sire models. Traits of interest were test-day traits for milk yield, fat percentage, protein percentage, and somatic cell score, considering 267,393 records from 32,707 first-lactation Holstein cows. Cows were born in the years 2010 to 2013, and kept in 52 large-scale herds from 2 federal states of north-east Germany. The average number of genotyped cows per herd (45,613 single nucleotide polymorphism markers per cow) was 133.5 (range: 45 to 415 genotyped cows). Genomic herd descriptors were (1) the level of linkage disequilibrium (r 2 ) within specific chromosome segments, and (2) the average allele frequency for single nucleotide polymorphisms in close distance to a functional mutation. Genetic herd descriptors were the (1) intra-herd inbreeding coefficient, and (2) the percentage of daughters from foreign sires. Phenotypic herd descriptors were (1) herd size, and (2) the herd mean for nonreturn rate. Most correlations among herd descriptors were close to 0, indicating independence of genomic, genetic, and phenotypic characteristics. Heritabilities for milk yield increased with increasing intra-herd linkage disequilibrium, inbreeding, and herd size. Genetic correlations in same traits between adjacent levels of herd descriptors were close to 1, but declined for descriptor levels in greater distance. Genetic correlation declines were more obvious for somatic cell score, compared with test-day traits with larger heritabilities (fat percentage and protein percentage). Also, for milk yield, alterations of herd descriptor levels had an obvious effect on heritabilities and genetic correlations. By trend, multiple trait model results (based on created discrete herd classes) confirmed the random regression estimates. Identified alterations of breeding values in dependency of herd descriptors suggest utilization of specific sires for specific herd structures, offering new possibilities to improve sire selection strategies. Regarding genomic selection designs and genetic gain transfer into commercial herds, cow herds for the utilization in cow training sets should reflect the genomic, genetic, and phenotypic pattern of the broad population. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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USDA-ARS?s Scientific Manuscript database
Little is known about genetic variation of Lymantria dispar multiple nucleopolyhedrovirus (LdMNPV; Baculoviridae: Alphabaculovirus) at the nucleotide sequence level. To obtain a more comprehensive view of genetic diversity among isolates of LdMNPV, partial sequences of the lef-8 gene were generated...
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USDA-ARS?s Scientific Manuscript database
Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait predicti...
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Maintenance of genetic diversity through plant-herbivore interactions
Gloss, Andrew D.; Dittrich, Anna C. Nelson; Goldman-Huertas, Benjamin; Whiteman, Noah K.
2013-01-01
Identifying the factors governing the maintenance of genetic variation is a central challenge in evolutionary biology. New genomic data, methods and conceptual advances provide increasing evidence that balancing selection, mediated by antagonistic species interactions, maintains functionally-important genetic variation within species and natural populations. Because diverse interactions between plants and herbivorous insects dominate terrestrial communities, they provide excellent systems to address this hypothesis. Population genomic studies of Arabidopsis thaliana and its relatives suggest spatial variation in herbivory maintains adaptive genetic variation controlling defense phenotypes, both within and among populations. Conversely, inter-species variation in plant defenses promotes adaptive genetic variation in herbivores. Emerging genomic model herbivores of Arabidopsis could illuminate how genetic variation in herbivores and plants interact simultaneously. PMID:23834766
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God and Genes in the Caring Professions: Clinician and Clergy Perceptions of Religion and Genetics
Bartlett, Virginia L; Johnson, Rolanda L
2013-01-01
Little is known about how care providers’ perceptions of religion and genetics affect interactions with patients/parishioners. This study investigates clinicians’ and clergy’s perceptions of and experiences with religion and genetics in their clinical and pastoral interactions. An exploratory qualitative study designed to elicit care providers’ descriptions of experiences with religion and genetics in clinical or pastoral interactions. Thirteen focus groups were conducted with members of the caring professions: physicians, nurses, and genetics counselors (clinicians), ministers and chaplains (clergy). Preliminary analysis of qualitative data is presented here. Preliminary analysis highlights four positions in professional perceptions of the relationship between science and faith. Further, differences among professional perceptions appear to influence perceptions of needed or available resources for interactions with religion and genetics. Clinicians’ and clergy’s perceptions of how religion and genetics relate are not defined solely by professional affiliation. These non-role-defined perceptions may affect clinical and pastoral interactions, especially regarding resources for patients and parishioners. PMID:19170091
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Genetic variation influences glutamate concentrations in brains of patients with multiple sclerosis.
Baranzini, Sergio E; Srinivasan, Radhika; Khankhanian, Pouya; Okuda, Darin T; Nelson, Sarah J; Matthews, Paul M; Hauser, Stephen L; Oksenberg, Jorge R; Pelletier, Daniel
2010-09-01
Glutamate is the main excitatory neurotransmitter in the mammalian brain. Appropriate transmission of nerve impulses through glutamatergic synapses is required throughout the brain and forms the basis of many processes including learning and memory. However, abnormally high levels of extracellular brain glutamate can lead to neuroaxonal cell death. We have previously reported elevated glutamate levels in the brains of patients suffering from multiple sclerosis. Here two complementary analyses to assess the extent of genomic control over glutamate levels were used. First, a genome-wide association analysis in 382 patients with multiple sclerosis using brain glutamate concentration as a quantitative trait was conducted. In a second approach, a protein interaction network was used to find associated genes within the same pathway. The top associated marker was rs794185 (P < 6.44 x 10(-7)), a non-coding single nucleotide polymorphism within the gene sulphatase modifying factor 1. Our pathway approach identified a module composed of 70 genes with high relevance to glutamate biology. Individuals carrying a higher number of associated alleles from genes in this module showed the highest levels of glutamate. These individuals also showed greater decreases in N-acetylaspartate and in brain volume over 1 year of follow-up. Patients were then stratified by the amount of annual brain volume loss and the same approach was performed in the 'high' (n = 250) and 'low' (n = 132) neurodegeneration groups. The association with rs794185 was highly significant in the group with high neurodegeneration. Further, results from the network-based pathway analysis remained largely unchanged even after stratification. Results from these analyses indicated that variance in the activity of neurochemical pathways implicated in neurodegeneration is explained, at least in part, by the inheritance of common genetic polymorphisms. Spectroscopy-based imaging provides a novel quantitative endophenotype for genetic association studies directed towards identifying new factors that contribute to the heterogeneity of clinical expression of multiple sclerosis.
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Ting, See-Yeun; Yan, Nicholas L; Schilke, Brenda A; Craig, Elizabeth A
2017-01-01
Proteins destined for the mitochondrial matrix are targeted to the inner membrane Tim17/23 translocon by their presequences. Inward movement is driven by the matrix-localized, Hsp70-based motor. The scaffold Tim44, interacting with the matrix face of the translocon, recruits other motor subunits and binds incoming presequence. The basis of these interactions and their functional relationships remains unclear. Using site-specific in vivo crosslinking and genetic approaches in Saccharomyces cerevisiae, we found that both domains of Tim44 interact with the major matrix-exposed loop of Tim23, with the C-terminal domain (CTD) binding Tim17 as well. Results of in vitro experiments showed that the N-terminal domain (NTD) is intrinsically disordered and binds presequence near a region important for interaction with Hsp70 and Tim23. Our data suggest a model in which the CTD serves primarily to anchor Tim44 to the translocon, whereas the NTD is a dynamic arm, interacting with multiple components to drive efficient translocation. DOI: http://dx.doi.org/10.7554/eLife.23609.001 PMID:28440746
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Understanding Evolutionary Potential in Virtual CPU Instruction Set Architectures
Bryson, David M.; Ofria, Charles
2013-01-01
We investigate fundamental decisions in the design of instruction set architectures for linear genetic programs that are used as both model systems in evolutionary biology and underlying solution representations in evolutionary computation. We subjected digital organisms with each tested architecture to seven different computational environments designed to present a range of evolutionary challenges. Our goal was to engineer a general purpose architecture that would be effective under a broad range of evolutionary conditions. We evaluated six different types of architectural features for the virtual CPUs: (1) genetic flexibility: we allowed digital organisms to more precisely modify the function of genetic instructions, (2) memory: we provided an increased number of registers in the virtual CPUs, (3) decoupled sensors and actuators: we separated input and output operations to enable greater control over data flow. We also tested a variety of methods to regulate expression: (4) explicit labels that allow programs to dynamically refer to specific genome positions, (5) position-relative search instructions, and (6) multiple new flow control instructions, including conditionals and jumps. Each of these features also adds complication to the instruction set and risks slowing evolution due to epistatic interactions. Two features (multiple argument specification and separated I/O) demonstrated substantial improvements in the majority of test environments, along with versions of each of the remaining architecture modifications that show significant improvements in multiple environments. However, some tested modifications were detrimental, though most exhibit no systematic effects on evolutionary potential, highlighting the robustness of digital evolution. Combined, these observations enhance our understanding of how instruction architecture impacts evolutionary potential, enabling the creation of architectures that support more rapid evolution of complex solutions to a broad range of challenges. PMID:24376669
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Systematic reconstruction of autism biology from massive genetic mutation profiles
Zhang, Chaolin; Jiang, Yong-hui
2018-01-01
Autism spectrum disorder (ASD) affects 1% of world population and has become a pressing medical and social problem worldwide. As a paradigmatic complex genetic disease, ASD has been intensively studied and thousands of gene mutations have been reported. Because these mutations rarely recur, it is difficult to (i) pinpoint the fewer disease-causing versus majority random events and (ii) replicate or verify independent studies. A coherent and systematic understanding of autism biology has not been achieved. We analyzed 3392 and 4792 autism-related mutations from two large-scale whole-exome studies across multiple resolution levels, that is, variants (single-nucleotide), genes (protein-coding unit), and pathways (molecular module). These mutations do not recur or replicate at the variant level, but significantly and increasingly do so at gene and pathway levels. Genetic association reveals a novel gene + pathway dual-hit model, where the mutation burden becomes less relevant. In multiple independent analyses, hundreds of variants or genes repeatedly converge to several canonical pathways, either novel or literature-supported. These pathways define recurrent and systematic ASD biology, distinct from previously reported gene groups or networks. They also present a catalog of novel ASD risk factors including 118 variants and 72 genes. At a subpathway level, most variants disrupt the pathway-related gene functions, and in the same gene, they tend to hit residues extremely close to each other and in the same domain. Multiple interacting variants spotlight key modules, including the cAMP (adenosine 3′,5′-monophosphate) second-messenger system and mGluR (metabotropic glutamate receptor) signaling regulation by GRKs (G protein–coupled receptor kinases). At a superpathway level, distinct pathways further interconnect and converge to three biology themes: synaptic function, morphology, and plasticity. PMID:29651456
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Systematic reconstruction of autism biology from massive genetic mutation profiles.
Luo, Weijun; Zhang, Chaolin; Jiang, Yong-Hui; Brouwer, Cory R
2018-04-01
Autism spectrum disorder (ASD) affects 1% of world population and has become a pressing medical and social problem worldwide. As a paradigmatic complex genetic disease, ASD has been intensively studied and thousands of gene mutations have been reported. Because these mutations rarely recur, it is difficult to (i) pinpoint the fewer disease-causing versus majority random events and (ii) replicate or verify independent studies. A coherent and systematic understanding of autism biology has not been achieved. We analyzed 3392 and 4792 autism-related mutations from two large-scale whole-exome studies across multiple resolution levels, that is, variants (single-nucleotide), genes (protein-coding unit), and pathways (molecular module). These mutations do not recur or replicate at the variant level, but significantly and increasingly do so at gene and pathway levels. Genetic association reveals a novel gene + pathway dual-hit model, where the mutation burden becomes less relevant. In multiple independent analyses, hundreds of variants or genes repeatedly converge to several canonical pathways, either novel or literature-supported. These pathways define recurrent and systematic ASD biology, distinct from previously reported gene groups or networks. They also present a catalog of novel ASD risk factors including 118 variants and 72 genes. At a subpathway level, most variants disrupt the pathway-related gene functions, and in the same gene, they tend to hit residues extremely close to each other and in the same domain. Multiple interacting variants spotlight key modules, including the cAMP (adenosine 3',5'-monophosphate) second-messenger system and mGluR (metabotropic glutamate receptor) signaling regulation by GRKs (G protein-coupled receptor kinases). At a superpathway level, distinct pathways further interconnect and converge to three biology themes: synaptic function, morphology, and plasticity.
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Multigene interactions and the prediction of depression in the Wisconsin Longitudinal Study
Roetker, Nicholas S; Yonker, James A; Lee, Chee; Chang, Vicky; Basson, Jacob J; Roan, Carol L; Hauser, Taissa S; Hauser, Robert M
2012-01-01
Objectives Single genetic loci offer little predictive power for the identification of depression. This study examined whether an analysis of gene–gene (G × G) interactions of 78 single nucleotide polymorphisms (SNPs) in genes associated with depression and age-related diseases would identify significant interactions with increased predictive power for depression. Design A retrospective cohort study. Setting A survey of participants in the Wisconsin Longitudinal Study. Participants A total of 4811 persons (2464 women and 2347 men) who provided saliva for genotyping; the group comes from a randomly selected sample of Wisconsin high school graduates from the class of 1957 as well as a randomly selected sibling, almost all of whom are non-Hispanic white. Primary outcome measure Depression as determine by the Composite International Diagnostic Interview–Short-Form. Results Using a classification tree approach (recursive partitioning (RP)), the authors identified a number of candidate G × G interactions associated with depression. The primary SNP splits revealed by RP (ANKK1 rs1800497 (also known as DRD2 Taq1A) in men and DRD2 rs224592 in women) were found to be significant as single factors by logistic regression (LR) after controlling for multiple testing (p=0.001 for both). Without considering interaction effects, only one of the five subsequent RP splits reached nominal significance in LR (FTO rs1421085 in women, p=0.008). However, after controlling for G × G interactions by running LR on RP-specific subsets, every split became significant and grew larger in magnitude (OR (before) → (after): men: GNRH1 novel SNP: (1.43 → 1.57); women: APOC3 rs2854116: (1.28 → 1.55), ACVR2B rs3749386: (1.11 → 2.17), FTO rs1421085: (1.32 → 1.65), IL6 rs1800795: (1.12 → 1.85)). Conclusions The results suggest that examining G × G interactions improves the identification of genetic associations predictive of depression. 4 of the SNPs identified in these interactions were located in two pathways well known to impact depression: neurotransmitter (ANKK1 and DRD2) and neuroendocrine (GNRH1 and ACVR2B) signalling. This study demonstrates the utility of RP analysis as an efficient and powerful exploratory analysis technique for uncovering genetic and molecular pathway interactions associated with disease aetiology. PMID:22761283
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Kartzinel, Tyler R.; Hamrick, J. L.; Wang, Chongyun; Bowsher, Alan W.; Quigley, Bryan G. P.
2015-01-01
Background and Aims Viny species are among the most serious invasive plants, and better knowledge of how vines grow to dominate landscapes is needed. Patches may contain a single genotype (i.e. genet), a competitively dominant genet or many independent but interacting genets, yet the clonal structure of vining species is often not apparent. Molecular markers can discriminate among the genetic identities of entwined vines to reveal the number and spatial distribution of genets. This study investigated how genets are spatially distributed within and among discrete patches of the invasive vine kudzu, Pueraria montana var. lobata, in the United States. It was expected that ramets of genets would be spatially clustered within patches, and that an increase in the number of genets within a patch would be associated with a decrease in the average size of each genet. Methods Six discrete kudzu patches were sampled across 2 years, and 1257 samples were genotyped at 21 polymorphic allozyme loci. Variation in genotypic and genetic diversity among patches was quantified and patterns of genet interdigitation were analysed. Key Results Substantial genotypic and genetic variation occurred within and among patches. As few as ten overlapping genets spanned up to 68 m2 in one patch, while >90 % of samples were genetically unique in another patch. Genotypic diversity within patches increased as mean clone size decreased, although spatially widespread genets did not preclude interdigitation. Eight genets were shared across ≥2 patches, suggesting that vegetative dispersal can occur among patches. Conclusions Genetically unique kudzu vines are highly interdigitated. Multiple vegetative propagules have become established in spatially discrete patches, probably through the movement of highway construction or maintenance machinery. The results suggest that common methods for controlling invasive vines (e.g. mowing) may inadvertently increase genotypic diversity. Thus, understanding vine architecture and growth has practical implications. PMID:26229064
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Kwon, Inchan; Choi, Eun Sil
2016-01-01
Multiple-site-specific incorporation of a noncanonical amino acid into a recombinant protein would be a very useful technique to generate multiple chemical handles for bioconjugation and multivalent binding sites for the enhanced interaction. Previously combination of a mutant yeast phenylalanyl-tRNA synthetase variant and the yeast phenylalanyl-tRNA containing the AAA anticodon was used to incorporate a noncanonical amino acid into multiple UUU phenylalanine (Phe) codons in a site-specific manner. However, due to the less selective codon recognition of the AAA anticodon, there was significant misincorporation of a noncanonical amino acid into unwanted UUC Phe codons. To enhance codon selectivity, we explored degenerate leucine (Leu) codons instead of Phe degenerate codons. Combined use of the mutant yeast phenylalanyl-tRNA containing the CAA anticodon and the yPheRS_naph variant allowed incorporation of a phenylalanine analog, 2-naphthylalanine, into murine dihydrofolate reductase in response to multiple UUG Leu codons, but not to other Leu codon sites. Despite the moderate UUG codon occupancy by 2-naphthylalaine, these results successfully demonstrated that the concept of forced ambiguity of the genetic code can be achieved for the Leu codons, available for multiple-site-specific incorporation. PMID:27028506
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Kwon, Inchan; Choi, Eun Sil
2016-01-01
Multiple-site-specific incorporation of a noncanonical amino acid into a recombinant protein would be a very useful technique to generate multiple chemical handles for bioconjugation and multivalent binding sites for the enhanced interaction. Previously combination of a mutant yeast phenylalanyl-tRNA synthetase variant and the yeast phenylalanyl-tRNA containing the AAA anticodon was used to incorporate a noncanonical amino acid into multiple UUU phenylalanine (Phe) codons in a site-specific manner. However, due to the less selective codon recognition of the AAA anticodon, there was significant misincorporation of a noncanonical amino acid into unwanted UUC Phe codons. To enhance codon selectivity, we explored degenerate leucine (Leu) codons instead of Phe degenerate codons. Combined use of the mutant yeast phenylalanyl-tRNA containing the CAA anticodon and the yPheRS_naph variant allowed incorporation of a phenylalanine analog, 2-naphthylalanine, into murine dihydrofolate reductase in response to multiple UUG Leu codons, but not to other Leu codon sites. Despite the moderate UUG codon occupancy by 2-naphthylalaine, these results successfully demonstrated that the concept of forced ambiguity of the genetic code can be achieved for the Leu codons, available for multiple-site-specific incorporation.
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The role of immune cells, glia and neurons in white and gray matter pathology in multiple sclerosis
Bernstock, Joshua D.; Pluchino, Stefano
2015-01-01
Multiple sclerosis is one of the most common causes of chronic neurological disability beginning in early to middle adult life. Multiple sclerosis is idiopathic in nature, yet increasing correlative evidence supports a strong association between one’s genetic predisposition, the environment and the immune system. Symptoms of multiple sclerosis have primarily been shown to result from a disruption in the integrity of myelinated tracts within the white matter of the central nervous system. However, recent research has also highlighted the hitherto underappreciated involvement of gray matter in multiple sclerosis disease pathophysiology, which may be especially relevant when considering the accumulation of irreversible damage and progressive disability. This review aims at providing a comprehensive overview of the interplay between inflammation, glial/neuronal damage and regeneration throughout the course of multiple sclerosis via the analysis of both white and gray matter lesional pathology. Further, we describe the common pathological mechanisms underlying both relapsing and progressive forms of multiple sclerosis, and analyze how current (as well as future) treatments may interact and/or interfere with its pathology. Understanding the putative mechanisms that drive disease pathogenesis will be key in helping to develop effective therapeutic strategies to prevent, mitigate, and treat the diverse morbidities associated with multiple sclerosis. PMID:25802011
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Friedrich, Anne; Garnier, Nicolas; Gagnière, Nicolas; Nguyen, Hoan; Albou, Laurent-Philippe; Biancalana, Valérie; Bettler, Emmanuel; Deléage, Gilbert; Lecompte, Odile; Muller, Jean; Moras, Dino; Mandel, Jean-Louis; Toursel, Thierry; Moulinier, Luc; Poch, Olivier
2010-02-01
Understanding how genetic alterations affect gene products at the molecular level represents a first step in the elucidation of the complex relationships between genotypic and phenotypic variations, and is thus a major challenge in the postgenomic era. Here, we present SM2PH-db (http://decrypthon.igbmc.fr/sm2ph), a new database designed to investigate structural and functional impacts of missense mutations and their phenotypic effects in the context of human genetic diseases. A wealth of up-to-date interconnected information is provided for each of the 2,249 disease-related entry proteins (August 2009), including data retrieved from biological databases and data generated from a Sequence-Structure-Evolution Inference in Systems-based approach, such as multiple alignments, three-dimensional structural models, and multidimensional (physicochemical, functional, structural, and evolutionary) characterizations of mutations. SM2PH-db provides a robust infrastructure associated with interactive analysis tools supporting in-depth study and interpretation of the molecular consequences of mutations, with the more long-term goal of elucidating the chain of events leading from a molecular defect to its pathology. The entire content of SM2PH-db is regularly and automatically updated thanks to a computational grid data federation facilities provided in the context of the Decrypthon program. (c) 2009 Wiley-Liss, Inc.
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Baxter, Amanda J.; Hughes, Maria Celia; Kvaskoff, Marina; Siskind, Victor; Shekar, Sri; Aitken, Joanne F.; Green, Adele C.; Duffy, David L.; Hayward, Nicholas K.; Martin, Nicholas G.; Whiteman, David C.
2013-01-01
Cutaneous malignant melanoma (CMM) is a major health issue in Queensland, Australia which has the world’s highest incidence. Recent molecular and epidemiologic studies suggest that CMM arises through multiple etiological pathways involving gene-environment interactions. Understanding the potential mechanisms leading to CMM requires larger studies than those previously conducted. This article describes the design and baseline characteristics of Q-MEGA, the Queensland study of Melanoma: Environmental and Genetic Associations, which followed-up four population-based samples of CMM patients in Queensland, including children, adolescents, men aged over 50, and a large sample of adult cases and their families, including twins. Q-MEGA aims to investigate the roles of genetic and environmental factors, and their interaction, in the etiology of melanoma. 3,471 participants took part in the follow-up study and were administered a computer-assisted telephone interview in 2002–2005. Updated data on environmental and phenotypic risk factors, and 2,777 blood samples were collected from interviewed participants as well as a subset of relatives. This study provides a large and well-described population-based sample of CMM cases with follow-up data. Characteristics of the cases and repeatability of sun exposure and phenotype measures between the baseline and the follow-up surveys, from six to 17 years later, are also described. PMID:18361720
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Tucker-Drob, Elliot M.; Briley, Daniel A.
2014-01-01
The longitudinal rank-order stability of cognitive ability increases dramatically over the lifespan. Multiple theoretical perspectives have proposed that genetic and/or environmental mechanisms underlie the longitudinal stability of cognition, and developmental trends therein. However, the patterns of stability of genetic and environmental influences on cognition over the lifespan largely remain poorly understood. We searched for longitudinal studies of cognition that reported raw genetically-informative longitudinal correlations or parameter estimates from longitudinal behavior genetic models. We identified 150 combinations of time points and measures from 15 independent longitudinal samples. In total, longitudinal data came from 4,538 monozygotic twin pairs raised together, 7,777 dizygotic twin pairs raised together, 34 monozygotic twin pairs raised apart, 78 dizygotic twin pairs raised apart, 141 adoptive sibling pairs, and 143 non-adoptive sibling pairs, ranging in age from infancy through late adulthood. At all ages, cross-time genetic correlations and shared environmental correlations were substantially larger than cross-time nonshared environmental correlations. Cross-time correlations for genetic and shared environmental components were low during early childhood, increased sharply over child development, and remained relatively high from adolescence through late adulthood. Cross-time correlations for nonshared environmental components were low across childhood and increased gradually to moderate magnitudes in adulthood. Increasing phenotypic stability over child development was almost entirely mediated by genetic factors. Time-based decay of genetic and shared environmental stability was more pronounced earlier in child development. Results are interpreted in reference to theories of gene-environment interaction and correlation. PMID:24611582
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Li, Cheng-Wei; Chen, Bor-Sen
2016-01-01
Epigenetic and microRNA (miRNA) regulation are associated with carcinogenesis and the development of cancer. By using the available omics data, including those from next-generation sequencing (NGS), genome-wide methylation profiling, candidate integrated genetic and epigenetic network (IGEN) analysis, and drug response genome-wide microarray analysis, we constructed an IGEN system based on three coupling regression models that characterize protein-protein interaction networks (PPINs), gene regulatory networks (GRNs), miRNA regulatory networks (MRNs), and epigenetic regulatory networks (ERNs). By applying system identification method and principal genome-wide network projection (PGNP) to IGEN analysis, we identified the core network biomarkers to investigate bladder carcinogenic mechanisms and design multiple drug combinations for treating bladder cancer with minimal side-effects. The progression of DNA repair and cell proliferation in stage 1 bladder cancer ultimately results not only in the derepression of miR-200a and miR-200b but also in the regulation of the TNF pathway to metastasis-related genes or proteins, cell proliferation, and DNA repair in stage 4 bladder cancer. We designed a multiple drug combination comprising gefitinib, estradiol, yohimbine, and fulvestrant for treating stage 1 bladder cancer with minimal side-effects, and another multiple drug combination comprising gefitinib, estradiol, chlorpromazine, and LY294002 for treating stage 4 bladder cancer with minimal side-effects.
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Programmed Cell Death During Caenorhabditis elegans Development
Conradt, Barbara; Wu, Yi-Chun; Xue, Ding
2016-01-01
Programmed cell death is an integral component of Caenorhabditis elegans development. Genetic and reverse genetic studies in C. elegans have led to the identification of many genes and conserved cell death pathways that are important for the specification of which cells should live or die, the activation of the suicide program, and the dismantling and removal of dying cells. Molecular, cell biological, and biochemical studies have revealed the underlying mechanisms that control these three phases of programmed cell death. In particular, the interplay of transcriptional regulatory cascades and networks involving multiple transcriptional regulators is crucial in activating the expression of the key death-inducing gene egl-1 and, in some cases, the ced-3 gene in cells destined to die. A protein interaction cascade involving EGL-1, CED-9, CED-4, and CED-3 results in the activation of the key cell death protease CED-3, which is tightly controlled by multiple positive and negative regulators. The activation of the CED-3 caspase then initiates the cell disassembly process by cleaving and activating or inactivating crucial CED-3 substrates; leading to activation of multiple cell death execution events, including nuclear DNA fragmentation, mitochondrial elimination, phosphatidylserine externalization, inactivation of survival signals, and clearance of apoptotic cells. Further studies of programmed cell death in C. elegans will continue to advance our understanding of how programmed cell death is regulated, activated, and executed in general. PMID:27516615
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Krementsov, Dimitry N; Case, Laure K; Hickey, William F; Teuscher, Cory
2015-08-01
Multiple sclerosis (MS) is a debilitating autoimmune neuroinflammatory disease influenced by genetics and the environment. MS incidence in female subjects has approximately tripled in the last century, suggesting a sex-specific environmental influence. Recent animal and human studies have implicated dietary sodium as a risk factor in MS, whereby high sodium augmented the generation of T helper (Th) 17 cells and exacerbated experimental autoimmune encephalomyelitis (EAE), the principal model of MS. However, whether dietary sodium interacts with sex or genetics remains unknown. Here, we show that high dietary sodium exacerbates EAE in a strain- and sex-specific fashion. In C57BL6/J mice, exposure to a high-salt diet exacerbated disease in both sexes, while in SJL/JCrHsd mice, it did so only in females. In further support of a genetic component, we found that sodium failed to modify EAE course in C57BL6/J mice carrying a 129/Sv-derived interval on chromosome 17. Furthermore, we found that the high-sodium diet did not augment Th17 or Th1 responses, but it did result in increased blood-brain barrier permeability and brain pathology. Our results demonstrate that the effects of dietary sodium on autoimmune neuroinflammation are sex specific, genetically controlled, and CNS mediated. © FASEB.