Modeling synthetic lethality

PubMed Central

Le Meur, Nolwenn; Gentleman, Robert

2008-01-01

Background Synthetic lethality defines a genetic interaction where the combination of mutations in two or more genes leads to cell death. The implications of synthetic lethal screens have been discussed in the context of drug development as synthetic lethal pairs could be used to selectively kill cancer cells, but leave normal cells relatively unharmed. A challenge is to assess genome-wide experimental data and integrate the results to better understand the underlying biological processes. We propose statistical and computational tools that can be used to find relationships between synthetic lethality and cellular organizational units. Results In Saccharomyces cerevisiae, we identified multi-protein complexes and pairs of multi-protein complexes that share an unusually high number of synthetic genetic interactions. As previously predicted, we found that synthetic lethality can arise from subunits of an essential multi-protein complex or between pairs of multi-protein complexes. Finally, using multi-protein complexes allowed us to take into account the pleiotropic nature of the gene products. Conclusions Modeling synthetic lethality using current estimates of the yeast interactome is an efficient approach to disentangle some of the complex molecular interactions that drive a cell. Our model in conjunction with applied statistical methods and computational methods provides new tools to better characterize synthetic genetic interactions. PMID:18789146

Targeting the complex interactions between microbiota, host epithelial and immune cells in inflammatory bowel disease.

PubMed

Hirata, Yoshihiro; Ihara, Sozaburo; Koike, Kazuhiko

2016-11-01

Inflammatory bowel disease (IBD) is a chronic inflammatory intestinal disorder that includes two distinct disease categories: ulcerative colitis and Crohn's disease. Epidemiological, genetic, and experimental studies have revealed many important aspects of IBD. Genetic susceptibility, inappropriate immune responses, environmental changes, and intestinal microbiota are all associated with the development of IBD. However, the exact mechanisms of the disease and the interactions among these pathogenic factors are largely unknown. Here we introduce recent findings from experimental colitis models that investigated the interactions between host genetic susceptibility and gut microbiota. In addition, we discuss new strategies for the treatment of IBD, focusing on the complex interactions between microbiota and host epithelial and immune cells. Copyright © 2016 Elsevier Ltd. All rights reserved.

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

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.

The genetic landscape of a physical interaction

PubMed Central

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

Gene-Lifestyle Interactions in Complex Diseases: Design and Description of the GLACIER and VIKING Studies

PubMed Central

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

Gene-Lifestyle Interactions in Complex Diseases: Design and Description of the GLACIER and VIKING Studies.

PubMed

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.

Dissection of the complex genetic basis of craniofacial anomalies using haploid genetics and interspecies hybrids in Nasonia wasps

PubMed Central

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

Primary Sex Determination in Drosophila melanogaster Does Not Rely on the Male-Specific Lethal Complex.

PubMed

Erickson, James W

2016-02-01

It has been proposed that the Male Specific Lethal (MSL) complex is active in Drosophila melanogaster embryos of both sexes prior to the maternal-to-zygotic transition. Elevated gene expression from the two X chromosomes of female embryos is proposed to facilitate the stable establishment of Sex-lethal (Sxl) expression, which determines sex and represses further activity of the MSL complex, leaving it active only in males. Important supporting data included female-lethal genetic interactions between the seven msl genes and either Sxl or scute and sisterlessA, two of the X-signal elements (XSE) that regulate early Sxl expression. Here I report contrary findings that there are no female-lethal genetic interactions between the msl genes and Sxl or its XSE regulators. Fly stocks containing the msl3(1) allele were found to exhibit a maternal-effect interaction with Sxl, scute, and sisterlessA mutations, but genetic complementation experiments showed that msl3 is neither necessary nor sufficient for the female-lethal interactions, which appear to be due to an unidentified maternal regulator of Sxl. Published data cited as evidence for an early function of the MSL complex in females, including a maternal effect of msl2, have been reevaluated and found not to support a maternal, or other effect, of the MSL complex in sex determination. These findings suggest that the MSL complex is not involved in primary sex determination or in X chromosome dosage compensation prior to the maternal-to-zygotic transition. Copyright © 2016 by the Genetics Society of America.

The Value of Extended Pedigrees for Next-Generation Analysis of Complex Disease in the Rhesus Macaque

PubMed Central

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

An organelle-specific protein landscape identifies novel diseases and molecular mechanisms

PubMed Central

Boldt, Karsten; van Reeuwijk, Jeroen; Lu, Qianhao; Koutroumpas, Konstantinos; Nguyen, Thanh-Minh T.; Texier, Yves; van Beersum, Sylvia E. C.; Horn, Nicola; Willer, Jason R.; Mans, Dorus A.; Dougherty, Gerard; Lamers, Ideke J. C.; Coene, Karlien L. M.; Arts, Heleen H.; Betts, Matthew J.; Beyer, Tina; Bolat, Emine; Gloeckner, Christian Johannes; Haidari, Khatera; Hetterschijt, Lisette; Iaconis, Daniela; Jenkins, Dagan; Klose, Franziska; Knapp, Barbara; Latour, Brooke; Letteboer, Stef J. F.; Marcelis, Carlo L.; Mitic, Dragana; Morleo, Manuela; Oud, Machteld M.; Riemersma, Moniek; Rix, Susan; Terhal, Paulien A.; Toedt, Grischa; van Dam, Teunis J. P.; de Vrieze, Erik; Wissinger, Yasmin; Wu, Ka Man; Apic, Gordana; Beales, Philip L.; Blacque, Oliver E.; Gibson, Toby J.; Huynen, Martijn A.; Katsanis, Nicholas; Kremer, Hannie; Omran, Heymut; van Wijk, Erwin; Wolfrum, Uwe; Kepes, François; Davis, Erica E.; Franco, Brunella; Giles, Rachel H.; Ueffing, Marius; Russell, Robert B.; Roepman, Ronald; Al-Turki, Saeed; Anderson, Carl; Antony, Dinu; Barroso, Inês; Bentham, Jamie; Bhattacharya, Shoumo; Carss, Keren; Chatterjee, Krishna; Cirak, Sebahattin; Cosgrove, Catherine; Danecek, Petr; Durbin, Richard; Fitzpatrick, David; Floyd, Jamie; Reghan Foley, A.; Franklin, Chris; Futema, Marta; Humphries, Steve E.; Hurles, Matt; Joyce, Chris; McCarthy, Shane; Mitchison, Hannah M.; Muddyman, Dawn; Muntoni, Francesco; O'Rahilly, Stephen; Onoufriadis, Alexandros; Payne, Felicity; Plagnol, Vincent; Raymond, Lucy; Savage, David B.; Scambler, Peter; Schmidts, Miriam; Schoenmakers, Nadia; Semple, Robert; Serra, Eva; Stalker, Jim; van Kogelenberg, Margriet; Vijayarangakannan, Parthiban; Walter, Klaudia; Whittall, Ros; Williamson, Kathy

2016-01-01

Cellular organelles provide opportunities to relate biological mechanisms to disease. Here we use affinity proteomics, genetics and cell biology to interrogate cilia: poorly understood organelles, where defects cause genetic diseases. Two hundred and seventeen tagged human ciliary proteins create a final landscape of 1,319 proteins, 4,905 interactions and 52 complexes. Reverse tagging, repetition of purifications and statistical analyses, produce a high-resolution network that reveals organelle-specific interactions and complexes not apparent in larger studies, and links vesicle transport, the cytoskeleton, signalling and ubiquitination to ciliary signalling and proteostasis. We observe sub-complexes in exocyst and intraflagellar transport complexes, which we validate biochemically, and by probing structurally predicted, disruptive, genetic variants from ciliary disease patients. The landscape suggests other genetic diseases could be ciliary including 3M syndrome. We show that 3M genes are involved in ciliogenesis, and that patient fibroblasts lack cilia. Overall, this organelle-specific targeting strategy shows considerable promise for Systems Medicine. PMID:27173435

Challenges and Opportunities in Genome-Wide Environmental Interaction (GWEI) studies

PubMed Central

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

Helminths and the microbiota: parts of the hygiene hypothesis

PubMed Central

Loke, P’ng; Lim, Yvonne A.L.

2015-01-01

In modern societies, diseases that are driven by dysregulated immune responses are increasing at an alarming pace, such as inflammatory bowel diseases and diabetes. There is an urgent need to understand these epidemiological trends, which are likely to be driven by the changing environment of the last few decades. There are complex interactions between human genetic factors and this changing environment that is leading to the increasing prevalence of metabolic and inflammatory diseases. Alterations to human gut bacterial communities (the microbiota) and lowered prevalence of helminth infections are potential environmental factors contributing to immune dysregulation. Helminths have co-evolved with the gut microbiota and their mammalian hosts. This three-way interaction is beginning to be characterized and the knowledge gained may enable the design of new therapeutic strategies to treat metabolic and inflammatory diseases. However, these complex interactions need to be carefully investigated in the context of host genetic backgrounds in order to identify optimal treatment strategies. The complex nature of these interactions raises the possibility that only with highly personalized treatment, with knowledge of individual genetic and microbiota communities, will therapeutic interventions be successful for a majority of the individuals suffering from these complex diseases of immune dysregulation. PMID:25869420

Helminths and the microbiota: parts of the hygiene hypothesis.

PubMed

Loke, P; Lim, Y A L

2015-06-01

In modern societies, diseases that are driven by dysregulated immune responses are increasing at an alarming pace, such as inflammatory bowel diseases and diabetes. There is an urgent need to understand these epidemiological trends, which are likely to be driven by the changing environment of the last few decades. There are complex interactions between human genetic factors and this changing environment that is leading to the increasing prevalence of metabolic and inflammatory diseases. Alterations to human gut bacterial communities (the microbiota) and lowered prevalence of helminth infections are potential environmental factors contributing to immune dysregulation. Helminths have co-evolved with the gut microbiota and their mammalian hosts. This three-way interaction is beginning to be characterized, and the knowledge gained may enable the design of new therapeutic strategies to treat metabolic and inflammatory diseases. However, these complex interactions need to be carefully investigated in the context of host genetic backgrounds to identify optimal treatment strategies. The complex nature of these interactions raises the possibility that only with highly personalized treatment, with knowledge of individual genetic and microbiota communities, will therapeutic interventions be successful for a majority of the individuals suffering from these complex diseases of immune dysregulation. © 2015 John Wiley & Sons Ltd.

Small- and Large-Effect Quantitative Trait Locus Interactions Underlie Variation in Yeast Sporulation Efficiency

PubMed Central

Lorenz, Kim; Cohen, Barak A.

2012-01-01

Quantitative trait loci (QTL) with small effects on phenotypic variation can be difficult to detect and analyze. Because of this a large fraction of the genetic architecture of many complex traits is not well understood. Here we use sporulation efficiency in Saccharomyces cerevisiae as a model complex trait to identify and study small-effect QTL. In crosses where the large-effect quantitative trait nucleotides (QTN) have been genetically fixed we identify small-effect QTL that explain approximately half of the remaining variation not explained by the major effects. We find that small-effect QTL are often physically linked to large-effect QTL and that there are extensive genetic interactions between small- and large-effect QTL. A more complete understanding of quantitative traits will require a better understanding of the numbers, effect sizes, and genetic interactions of small-effect QTL. PMID:22942125

Machine Learning for Detecting Gene-Gene Interactions

PubMed Central

McKinney, Brett A.; Reif, David M.; Ritchie, Marylyn D.; Moore, Jason H.

2011-01-01

Complex interactions among genes and environmental factors are known to play a role in common human disease aetiology. There is a growing body of evidence to suggest that complex interactions are ‘the norm’ and, rather than amounting to a small perturbation to classical Mendelian genetics, interactions may be the predominant effect. Traditional statistical methods are not well suited for detecting such interactions, especially when the data are high dimensional (many attributes or independent variables) or when interactions occur between more than two polymorphisms. In this review, we discuss machine-learning models and algorithms for identifying and characterising susceptibility genes in common, complex, multifactorial human diseases. We focus on the following machine-learning methods that have been used to detect gene-gene interactions: neural networks, cellular automata, random forests, and multifactor dimensionality reduction. We conclude with some ideas about how these methods and others can be integrated into a comprehensive and flexible framework for data mining and knowledge discovery in human genetics. PMID:16722772

Epistasis and Its Implications for Personal Genetics

PubMed Central

Moore, Jason H.; Williams, Scott M.

2009-01-01

The widespread availability of high-throughput genotyping technology has opened the door to the era of personal genetics, which brings to consumers the promise of using genetic variations to predict individual susceptibility to common diseases. Despite easy access to commercial personal genetics services, our knowledge of the genetic architecture of common diseases is still very limited and has not yet fulfilled the promise of accurately predicting most people at risk. This is partly because of the complexity of the mapping relationship between genotype and phenotype that is a consequence of epistasis (gene-gene interaction) and other phenomena such as gene-environment interaction and locus heterogeneity. Unfortunately, these aspects of genetic architecture have not been addressed in most of the genetic association studies that provide the knowledge base for interpreting large-scale genetic association results. We provide here an introductory review of how epistasis can affect human health and disease and how it can be detected in population-based studies. We provide some thoughts on the implications of epistasis for personal genetics and some recommendations for improving personal genetics in light of this complexity. PMID:19733727

Epistasis and its implications for personal genetics.

PubMed

Moore, Jason H; Williams, Scott M

2009-09-01

The widespread availability of high-throughput genotyping technology has opened the door to the era of personal genetics, which brings to consumers the promise of using genetic variations to predict individual susceptibility to common diseases. Despite easy access to commercial personal genetics services, our knowledge of the genetic architecture of common diseases is still very limited and has not yet fulfilled the promise of accurately predicting most people at risk. This is partly because of the complexity of the mapping relationship between genotype and phenotype that is a consequence of epistasis (gene-gene interaction) and other phenomena such as gene-environment interaction and locus heterogeneity. Unfortunately, these aspects of genetic architecture have not been addressed in most of the genetic association studies that provide the knowledge base for interpreting large-scale genetic association results. We provide here an introductory review of how epistasis can affect human health and disease and how it can be detected in population-based studies. We provide some thoughts on the implications of epistasis for personal genetics and some recommendations for improving personal genetics in light of this complexity.

The Set1/COMPASS histone H3 methyltransferase helps regulate mitosis with the CDK1 and NIMA mitotic kinases in Aspergillus nidulans.

PubMed

Govindaraghavan, Meera; Anglin, Sarah Lea; Osmani, Aysha H; Osmani, Stephen A

2014-08-01

Mitosis is promoted and regulated by reversible protein phosphorylation catalyzed by the essential NIMA and CDK1 kinases in the model filamentous fungus Aspergillus nidulans. Protein methylation mediated by the Set1/COMPASS methyltransferase complex has also been shown to regulate mitosis in budding yeast with the Aurora mitotic kinase. We uncover a genetic interaction between An-swd1, which encodes a subunit of the Set1 protein methyltransferase complex, with NIMA as partial inactivation of nimA is poorly tolerated in the absence of swd1. This genetic interaction is additionally seen without the Set1 methyltransferase catalytic subunit. Importantly partial inactivation of NIMT, a mitotic activator of the CDK1 kinase, also causes lethality in the absence of Set1 function, revealing a functional relationship between the Set1 complex and two pivotal mitotic kinases. The main target for Set1-mediated methylation is histone H3K4. Mutational analysis of histone H3 revealed that modifying the H3K4 target residue of Set1 methyltransferase activity phenocopied the lethality seen when either NIMA or CDK1 are partially functional. We probed the mechanistic basis of these genetic interactions and find that the Set1 complex performs functions with CDK1 for initiating mitosis and with NIMA during progression through mitosis. The studies uncover a joint requirement for the Set1 methyltransferase complex with the CDK1 and NIMA kinases for successful mitosis. The findings extend the roles of the Set1 complex to include the initiation of mitosis with CDK1 and mitotic progression with NIMA in addition to its previously identified interactions with Aurora and type 1 phosphatase in budding yeast. Copyright © 2014 by the Genetics Society of America.

The mathematical limits of genetic prediction for complex chronic disease.

PubMed

Keyes, Katherine M; Smith, George Davey; Koenen, Karestan C; Galea, Sandro

2015-06-01

Attempts at predicting individual risk of disease based on common germline genetic variation have largely been disappointing. The present paper formalises why genetic prediction at the individual level is and will continue to have limited utility given the aetiological architecture of most common complex diseases. Data were simulated on one million populations with 10 000 individuals in each populations with varying prevalences of a genetic risk factor, an interacting environmental factor and the background rate of disease. The determinant risk ratio and risk difference magnitude for the association between a gene variant and disease is a function of the prevalence of the interacting factors that activate the gene, and the background rate of disease. The risk ratio and total excess cases due to the genetic factor increase as the prevalence of interacting factors increase, and decrease as the background rate of disease increases. Germline genetic variations have high predictive capacity for individual disease only under conditions of high heritability of particular genetic sequences, plausible only under rare variant hypotheses. Under a model of common germline genetic variants that interact with other genes and/or environmental factors in order to cause disease, the predictive capacity of common genetic variants is determined by the prevalence of the factors that interact with the variant and the background rate. A focus on estimating genetic associations for the purpose of prediction without explicitly grounding such work in an understanding of modifiable (including environmentally influenced) factors will be limited in its ability to yield important insights about the risk of disease. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Markov Logic Networks in the Analysis of Genetic Data

PubMed Central

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

Association analysis of three diverse rice (Oryza sativa L.) germplasm collections for loci regulating grain quality traits

USDA-ARS?s Scientific Manuscript database

In rice (Oryza sativa L.), end-use/cooking quality is vital for producers and millions of consumers worldwide. Grain quality is a complex trait with interacting genetic and environmental factors. Deciphering the complex genetic architecture associated with grain quality, will provide vital informati...

Annual Research Review: Developmental Considerations of Gene by Environment Interactions

ERIC Educational Resources Information Center

Lenroot, Rhoshel K.; Giedd, Jay N.

2011-01-01

Biological development is driven by a complex dance between nurture and nature, determined not only by the specific features of the interacting genetic and environmental influences but also by the timing of their rendezvous. The initiation of large-scale longitudinal studies, ever-expanding knowledge of genetics, and increasing availability of…

Epistasis-list.org: A Curated Database of Gene-Gene and Gene-Environment Interactions in Human Epidemiology

EPA Science Inventory

The field of human genetics has experienced a paradigm shift in that common diseases are now thought to be due to the complex interactions among numerous genetic and environmental factors. This paradigm shift has prompted the development of myriad novel methods to detect such int...

EINVis: a visualization tool for analyzing and exploring genetic interactions in large-scale association studies.

PubMed

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.

Genetic interactions within inositol-related pathways are associated with longitudinal changes in ventricle size

PubMed Central

Koran, Mary Ellen I.; Hohman, Timothy J.; Meda, Shashwath A.; Thornton-Wells, Tricia A.

2013-01-01

The genetic etiology of late onset Alzheimer disease (LOAD) has proven complex, involving clinical and genetic heterogeneity and gene-gene interactions. Recent genome wide association studies (GWAS) in LOAD have led to the discovery of novel genetic risk factors; however, the investigation of gene-gene interactions has been limited. Conventional genetic studies often use binary disease status as the primary phenotype, but for complex brain-based diseases, neuroimaging data can serve as quantitative endophenotypes that correlate with disease status and closely reflect pathological changes. In the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, we tested for association of genetic interactions with longitudinal MRI measurements of the inferior lateral ventricles (ILVs), which have repeatedly shown a relationship to LOAD status and progression. We performed linear regression to evaluate the ability of pathway-derived SNP-SNP pairs to predict the slope of change in volume of the ILVs. After Bonferroni correction, we identified four significant interactions in the right ILV (RILV) corresponding to gene-gene pairs SYNJ2-PI4KA, PARD3-MYH2, PDE3A-ABHD12B and OR2L13-PRKG1 and one significant interaction in the left ILV (LILV) corresponding to SYNJ2-PI4KA. The SNP-SNP interaction corresponding to SYNJ2-PI4KA was identical in the RILV and LILV and was the most significant interaction in each (RILV: p=9.10×10−12; LILV: p=8.20×10−13). Both genes belong to the inositol phosphate signaling pathway which has been previously associated with neurodegeneration in AD and we discuss the possibility that perturbation of this pathway results in a down-regulation of the Akt cell survival pathway and, thereby, decreased neuronal survival, as reflected by increased volume of the ventricles. PMID:24077433

Epistasis interaction of QTL effects as a genetic parameter influencing estimation of the genetic additive effect.

PubMed

Bocianowski, Jan

2013-03-01

Epistasis, an additive-by-additive interaction between quantitative trait loci, has been defined as a deviation from the sum of independent effects of individual genes. Epistasis between QTLs assayed in populations segregating for an entire genome has been found at a frequency close to that expected by chance alone. Recently, epistatic effects have been considered by many researchers as important for complex traits. In order to understand the genetic control of complex traits, it is necessary to clarify additive-by-additive interactions among genes. Herein we compare estimates of a parameter connected with the additive gene action calculated on the basis of two models: a model excluding epistasis and a model with additive-by-additive interaction effects. In this paper two data sets were analysed: 1) 150 barley doubled haploid lines derived from the Steptoe × Morex cross, and 2) 145 DH lines of barley obtained from the Harrington × TR306 cross. The results showed that in cases when the effect of epistasis was different from zero, the coefficient of determination was larger for the model with epistasis than for the one excluding epistasis. These results indicate that epistatic interaction plays an important role in controlling the expression of complex traits.

Complexity Theory

USGS Publications Warehouse

Lee, William H K.

2016-01-01

A complex system consists of many interacting parts, generates new collective behavior through self organization, and adaptively evolves through time. Many theories have been developed to study complex systems, including chaos, fractals, cellular automata, self organization, stochastic processes, turbulence, and genetic algorithms.

GENOME-WIDE GENETIC INTERACTION ANALYSIS OF GLAUCOMA USING EXPERT KNOWLEDGE DERIVED FROM HUMAN PHENOTYPE NETWORKS

PubMed Central

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

Feeding and Swallowing Dysfunction in Genetic Syndromes

ERIC Educational Resources Information Center

Cooper-Brown, Linda; Copeland, Sara; Dailey, Scott; Downey, Debora; Petersen, Mario Cesar; Stimson, Cheryl; Van Dyke, Don C.

2008-01-01

Children with genetic syndromes frequently have feeding problems and swallowing dysfunction as a result of the complex interactions between anatomical, medical, physiological, and behavioral factors. Feeding problems associated with genetic disorders may also cause feeding to be unpleasant, negative, or even painful because of choking, coughing,…

Evolving hard problems: Generating human genetics datasets with a complex etiology.

PubMed

Himmelstein, Daniel S; Greene, Casey S; Moore, Jason H

2011-07-07

A goal of human genetics is to discover genetic factors that influence individuals' susceptibility to common diseases. Most common diseases are thought to result from the joint failure of two or more interacting components instead of single component failures. This greatly complicates both the task of selecting informative genetic variants and the task of modeling interactions between them. We and others have previously developed algorithms to detect and model the relationships between these genetic factors and disease. Previously these methods have been evaluated with datasets simulated according to pre-defined genetic models. Here we develop and evaluate a model free evolution strategy to generate datasets which display a complex relationship between individual genotype and disease susceptibility. We show that this model free approach is capable of generating a diverse array of datasets with distinct gene-disease relationships for an arbitrary interaction order and sample size. We specifically generate eight-hundred Pareto fronts; one for each independent run of our algorithm. In each run the predictiveness of single genetic variation and pairs of genetic variants have been minimized, while the predictiveness of third, fourth, or fifth-order combinations is maximized. Two hundred runs of the algorithm are further dedicated to creating datasets with predictive four or five order interactions and minimized lower-level effects. This method and the resulting datasets will allow the capabilities of novel methods to be tested without pre-specified genetic models. This allows researchers to evaluate which methods will succeed on human genetics problems where the model is not known in advance. We further make freely available to the community the entire Pareto-optimal front of datasets from each run so that novel methods may be rigorously evaluated. These 76,600 datasets are available from http://discovery.dartmouth.edu/model_free_data/.

Host Genotype and Microbiota Contribute Asymmetrically to Transcriptional Variation in the Threespine Stickleback Gut

PubMed Central

Small, Clayton M.; Milligan-Myhre, Kathryn; Bassham, Susan; Guillemin, Karen

2017-01-01

Recent studies of interactions between hosts and their resident microbes have revealed important ecological and evolutionary consequences that emerge from these complex interspecies relationships, including diseases that occur when the interactions go awry. Given the preponderance of these interactions, we hypothesized that effects of the microbiota on gene expression in the developing gut—an important aspect of host biology—would be pervasive, and that these effects would be both comparable in magnitude to and contingent on effects of the host genetic background. To evaluate the effects of the microbiota, host genotype, and their interaction on gene expression in the gut of a genetically diverse, gnotobiotic host model, the threespine stickleback (Gasterosteus aculeatus), we compared RNA-seq data among 84 larval fish. Surprisingly, we found that stickleback population and family differences explained substantially more gene expression variation than the presence of microbes. Expression levels of 72 genes, however, were affected by our microbiota treatment. These genes, including many associated with innate immunity, comprise a tractable subset of host genetic factors for precise, systems-level study of host–microbe interactions in the future. Importantly, our data also suggest subtle signatures of a statistical interaction between host genotype and the microbiota on expression patterns of genetic pathways associated with innate immunity, coagulation and complement cascades, focal adhesion, cancer, and peroxisomes. These genotype-by-environment interactions may prove to be important leads to the understanding of host genetic mechanisms commonly at the root of sometimes complex molecular relationships between hosts and their resident microbes. PMID:28391321

Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models

PubMed Central

Marr, Julia; Bock, Gavin; Desbonnet, Lieve; Waddington, John

2016-01-01

The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia. PMID:27725886

A Balanced Accuracy Fitness Function Leads to Robust Analysis Using Grammatical Evolution Neural Networks in the Case of Class Imbalance

EPA Science Inventory

The identification and characterization of genetic and environmental factors that predict common, complex disease is a major goal of human genetics. The ubiquitous nature of epistatic interaction in the underlying genetic etiology of such disease presents a difficult analytical ...

Inferring Mechanisms of Compensation from E-MAP and SGA Data Using Local Search Algorithms for Max Cut

NASA Astrophysics Data System (ADS)

Leiserson, Mark D. M.; Tatar, Diana; Cowen, Lenore J.; Hescott, Benjamin J.

A new method based on a mathematically natural local search framework for max cut is developed to uncover functionally coherent module and BPM motifs in high-throughput genetic interaction data. Unlike previous methods which also consider physical protein-protein interaction data, our method utilizes genetic interaction data only; this becomes increasingly important as high-throughput genetic interaction data is becoming available in settings where less is known about physical interaction data. We compare modules and BPMs obtained to previous methods and across different datasets. Despite needing no physical interaction information, the BPMs produced by our method are competitive with previous methods. Biological findings include a suggested global role for the prefoldin complex and a SWR subcomplex in pathway buffering in the budding yeast interactome.

Inferring mechanisms of compensation from E-MAP and SGA data using local search algorithms for max cut.

PubMed

Leiserson, Mark D M; Tatar, Diana; Cowen, Lenore J; Hescott, Benjamin J

2011-11-01

A new method based on a mathematically natural local search framework for max cut is developed to uncover functionally coherent module and BPM motifs in high-throughput genetic interaction data. Unlike previous methods, which also consider physical protein-protein interaction data, our method utilizes genetic interaction data only; this becomes increasingly important as high-throughput genetic interaction data is becoming available in settings where less is known about physical interaction data. We compare modules and BPMs obtained to previous methods and across different datasets. Despite needing no physical interaction information, the BPMs produced by our method are competitive with previous methods. Biological findings include a suggested global role for the prefoldin complex and a SWR subcomplex in pathway buffering in the budding yeast interactome.

Redefining the endophenotype concept to accommodate transdiagnostic vulnerabilities and etiological complexity.

PubMed

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.

The genetics of human longevity: an intricacy of genes, environment, culture and microbiome.

PubMed

Dato, Serena; Rose, Giuseppina; Crocco, Paolina; Monti, Daniela; Garagnani, Paolo; Franceschi, Claudio; Passarino, Giuseppe

2017-07-01

Approximately one-quarter of the variation in lifespan in developed countries can be attributed to genetic factors. However, even large population based studies investigating genetic influence on human lifespan have been disappointing, identifying only a few genes accounting for genetic susceptibility to longevity. Some environmental and lifestyle determinants associated with longevity have been identified, which interplay with genetic factors in an intricate way. The study of gene-environment and gene-gene interactions can significantly improve our chance to disentangle this complex scenario. In this review, we first describe the most recent approaches for genetic studies of longevity, from those enriched with health parameters and frailty measures to pathway-based and SNP-SNP interaction analyses. Then, we go deeper into the concept of "environmental influences" in human aging and longevity, focusing on the contribution of life style changes, social and cultural influences, as important determinants of survival differences among individuals in a population. Finally, we discuss the contribution of the microbiome in human longevity, as an example of complex interaction between organism and environment. In conclusion, evidences collected from the latest studies on human longevity provide a support for the collection of life-long genetic and environmental/lifestyle variables with beneficial or detrimental effects on health, to improve our understanding of the determinants of human lifespan. Copyright © 2017 Elsevier B.V. All rights reserved.

Nutritional habits, lifestyle, and genetic predisposition in cardiovascular and metabolic traits in Turkish population.

PubMed

Karaca, Sefayet; Erge, Sema; Cesuroglu, Tomris; Polimanti, Renato

2016-06-01

Cardiovascular and metabolic traits (CMT) are influenced by complex interactive processes including diet, lifestyle, and genetic predisposition. The present study investigated the interactions of these risk factors in relation to CMTs in the Turkish population. We applied bootstrap agglomerative hierarchical clustering and Bayesian network learning algorithms to identify the causative relationships among genes involved in different biological mechanisms (i.e., lipid metabolism, hormone metabolism, cellular detoxification, aging, and energy metabolism), lifestyle (i.e., physical activity, smoking behavior, and metropolitan residency), anthropometric traits (i.e., body mass index, body fat ratio, and waist-to-hip ratio), and dietary habits (i.e., daily intakes of macro- and micronutrients) in relation to CMTs (i.e., health conditions and blood parameters). We identified significant correlations between dietary habits (soybean and vitamin B12 intakes) and different cardiometabolic diseases that were confirmed by the Bayesian network-learning algorithm. Genetic factors contributed to these disease risks also through the pleiotropy of some genetic variants (i.e., F5 rs6025 and MTR rs180508). However, we also observed that certain genetic associations are indirect since they are due to the causative relationships among the CMTs (e.g., APOC3 rs5128 is associated with low-density lipoproteins cholesterol and, by extension, total cholesterol). Our study applied a novel approach to integrate various sources of information and dissect the complex interactive processes related to CMTs. Our data indicated that complex causative networks are present: causative relationships exist among CMTs and are affected by genetic factors (with pleiotropic and non-pleiotropic effects) and dietary habits. Copyright © 2016 Elsevier Inc. All rights reserved.

A strategy to apply quantitative epistasis analysis on developmental traits.

PubMed

Labocha, Marta K; Yuan, Wang; Aleman-Meza, Boanerges; Zhong, Weiwei

2017-05-15

Genetic interactions are keys to understand complex traits and evolution. Epistasis analysis is an effective method to map genetic interactions. Large-scale quantitative epistasis analysis has been well established for single cells. However, there is a substantial lack of such studies in multicellular organisms and their complex phenotypes such as development. Here we present a method to extend quantitative epistasis analysis to developmental traits. In the nematode Caenorhabditis elegans, we applied RNA interference on mutants to inactivate two genes, used an imaging system to quantitatively measure phenotypes, and developed a set of statistical methods to extract genetic interactions from phenotypic measurement. Using two different C. elegans developmental phenotypes, body length and sex ratio, as examples, we showed that this method could accommodate various metazoan phenotypes with performances comparable to those methods in single cell growth studies. Comparing with qualitative observations, this method of quantitative epistasis enabled detection of new interactions involving subtle phenotypes. For example, several sex-ratio genes were found to interact with brc-1 and brd-1, the orthologs of the human breast cancer genes BRCA1 and BARD1, respectively. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3 (ortholog of HORMAD1, HORMAD2), sdc-1, and set-2 (ortholog of SETD1A, SETD1B, KMT2C, KMT2D), validating the effectiveness of our method in detecting genetic interactions. We developed a reliable, high-throughput method for quantitative epistasis analysis of developmental phenotypes.

What Gene-Environment Interactions Can Tell Us about Social Competence in Typical and Atypical Populations

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…

Juxtaposed Polycomb complexes co-regulate vertebral identity.

PubMed

Kim, Se Young; Paylor, Suzanne W; Magnuson, Terry; Schumacher, Armin

2006-12-01

Best known as epigenetic repressors of developmental Hox gene transcription, Polycomb complexes alter chromatin structure by means of post-translational modification of histone tails. Depending on the cellular context, Polycomb complexes of diverse composition and function exhibit cooperative interaction or hierarchical interdependency at target loci. The present study interrogated the genetic, biochemical and molecular interaction of BMI1 and EED, pivotal constituents of heterologous Polycomb complexes, in the regulation of vertebral identity during mouse development. Despite a significant overlap in dosage-sensitive homeotic phenotypes and co-repression of a similar set of Hox genes, genetic analysis implicated eed and Bmi1 in parallel pathways, which converge at the level of Hox gene regulation. Whereas EED and BMI1 formed separate biochemical entities with EzH2 and Ring1B, respectively, in mid-gestation embryos, YY1 engaged in both Polycomb complexes. Strikingly, methylated lysine 27 of histone H3 (H3-K27), a mediator of Polycomb complex recruitment to target genes, stably associated with the EED complex during the maintenance phase of Hox gene repression. Juxtaposed EED and BMI1 complexes, along with YY1 and methylated H3-K27, were detected in upstream regulatory regions of Hoxc8 and Hoxa5. The combined data suggest a model wherein epigenetic and genetic elements cooperatively recruit and retain juxtaposed Polycomb complexes in mammalian Hox gene clusters toward co-regulation of vertebral identity.

Gene-Environment Interactions in Cardiovascular Disease

PubMed Central

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

Inferring Mechanisms of Compensation from E-MAP and SGA Data Using Local Search Algorithms for Max Cut

PubMed Central

Leiserson, Mark D.M.; Tatar, Diana; Cowen, Lenore J.

2011-01-01

Abstract A new method based on a mathematically natural local search framework for max cut is developed to uncover functionally coherent module and BPM motifs in high-throughput genetic interaction data. Unlike previous methods, which also consider physical protein-protein interaction data, our method utilizes genetic interaction data only; this becomes increasingly important as high-throughput genetic interaction data is becoming available in settings where less is known about physical interaction data. We compare modules and BPMs obtained to previous methods and across different datasets. Despite needing no physical interaction information, the BPMs produced by our method are competitive with previous methods. Biological findings include a suggested global role for the prefoldin complex and a SWR subcomplex in pathway buffering in the budding yeast interactome. PMID:21882903

Learning directed acyclic graphs from large-scale genomics data.

PubMed

Nikolay, Fabio; Pesavento, Marius; Kritikos, George; Typas, Nassos

2017-09-20

In this paper, we consider the problem of learning the genetic interaction map, i.e., the topology of a directed acyclic graph (DAG) of genetic interactions from noisy double-knockout (DK) data. Based on a set of well-established biological interaction models, we detect and classify the interactions between genes. We propose a novel linear integer optimization program called the Genetic-Interactions-Detector (GENIE) to identify the complex biological dependencies among genes and to compute the DAG topology that matches the DK measurements best. Furthermore, we extend the GENIE program by incorporating genetic interaction profile (GI-profile) data to further enhance the detection performance. In addition, we propose a sequential scalability technique for large sets of genes under study, in order to provide statistically significant results for real measurement data. Finally, we show via numeric simulations that the GENIE program and the GI-profile data extended GENIE (GI-GENIE) program clearly outperform the conventional techniques and present real data results for our proposed sequential scalability technique.

Mapping complex traits as a dynamic system

PubMed Central

Sun, Lidan; Wu, Rongling

2017-01-01

Despite increasing emphasis on the genetic study of quantitative traits, we are still far from being able to chart a clear picture of their genetic architecture, given an inherent complexity involved in trait formation. A competing theory for studying such complex traits has emerged by viewing their phenotypic formation as a “system” in which a high-dimensional group of interconnected components act and interact across different levels of biological organization from molecules through cells to whole organisms. This system is initiated by a machinery of DNA sequences that regulate a cascade of biochemical pathways to synthesize endophenotypes and further assemble these endophenotypes toward the end-point phenotype in virtue of various developmental changes. This review focuses on a conceptual framework for genetic mapping of complex traits by which to delineate the underlying components, interactions and mechanisms that govern the system according to biological principles and understand how these components function synergistically under the control of quantitative trait loci (QTLs) to comprise a unified whole. This framework is built by a system of differential equations that quantifies how alterations of different components lead to the global change of trait development and function, and provides a quantitative and testable platform for assessing the multiscale interplay between QTLs and development. The method will enable geneticists to shed light on the genetic complexity of any biological system and predict, alter or engineer its physiological and pathological states. PMID:25772476

Genetics, mental illness, and complex disease: development and distribution of an interactive CD-ROM for genetic counselors. Final report for period 15 August 2000 - 31 December 2002

DOE Office of Scientific and Technical Information (OSTI.GOV)

McInerney, Joseph D.

2003-03-31

"Genetics and Major Psychiatric Disorders: A Program for Genetic Counselors" provides an introduction to psychiatric genetics, with a focus on the genetics of common complex disease, for genetics professionals. The program is available as a CD-ROM and an online educational resource. The on-line version requires a direct internet connection. Each educational module begins with an interactive case study that raises significant issues addressed in each module. In addition, case studies provided throughout the educational materials support teaching of major concepts. Incorporated throughout the content are expert video clips, video clips from individuals affected by psychiatric illness, and optional "learn more"more » materials that offer greater depth about a particular topic. The structure of the CD-ROM permits self-navigation, but we have suggested a sequence that allows materials to build upon each other. At any point in the materials, users may pause and look up terms in the glossary or review the DSM-IV criteria for selected psychiatric disorders. A detailed site map is available for those who choose to self navigate through the content.« less

Gene–environment interaction in tobacco-related cancers

PubMed Central

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

The Complex Genetic Basis of Congenital Heart Defects

PubMed Central

Akhirome, Ehiole; Walton, Nephi A.; Nogee, Julie M.; Jay, Patrick Y.

2017-01-01

Twenty years ago, chromosomal abnormalities were the only identifiable genetic causes of a small fraction of congenital heart defects (CHD). Today, a de novo or inherited genetic abnormality can be identified as pathogenic in one-third of cases. We refer to them here as monogenic causes, insofar as the genetic abnormality has a readily detectable, large effect. What explains the other two-thirds? This review considers a complex genetic basis. That is, a combination of genetic mutations or variants that individually may have little or no detectable effect contribute to the pathogenesis of a heart defect. Genes in the embryo that act directly in cardiac developmental pathways have received the most attention, but genes in the mother that establish the gestational milieu via pathways related to metabolism and aging also have an effect. A growing body of evidence highlights the pathogenic significance of genetic interactions in the embryo and maternal effects that have a genetic basis. The investigation of CHD as guided by a complex genetic model could help estimate risk more precisely and logically lead to a means of prevention. PMID:28381817

Application of molecular genetic tools to studies of forest pathosystems [Chapter 2

Treesearch

Mee-Sook Kim; Ned B. Klopfenstein; Richard C. Hamelin

2005-01-01

The use of molecular genetics in forest pathology has greatly increased over the past 10 years. For the most part, molecular genetic tools were initially developed to focus on individual components (e.g., pathogen, host) of forest pathosystems. As part of broader forest ecosystem complexes, forest pathosystems involve dynamic interactions among living components (e.g...

DNA Polymerase α Subunit Residues and Interactions Required for Efficient Initiation Complex Formation Identified by a Genetic Selection.

PubMed

Lindow, Janet C; Dohrmann, Paul R; McHenry, Charles S

2015-07-03

Biophysical and structural studies have defined many of the interactions that occur between individual components or subassemblies of the bacterial replicase, DNA polymerase III holoenzyme (Pol III HE). Here, we extended our knowledge of residues and interactions that are important for the first step of the replicase reaction: the ATP-dependent formation of an initiation complex between the Pol III HE and primed DNA. We exploited a genetic selection using a dominant negative variant of the polymerase catalytic subunit that can effectively compete with wild-type Pol III α and form initiation complexes, but cannot elongate. Suppression of the dominant negative phenotype was achieved by secondary mutations that were ineffective in initiation complex formation. The corresponding proteins were purified and characterized. One class of mutant mapped to the PHP domain of Pol III α, ablating interaction with the ϵ proofreading subunit and distorting the polymerase active site in the adjacent polymerase domain. Another class of mutation, found near the C terminus, interfered with τ binding. A third class mapped within the known β-binding domain, decreasing interaction with the β2 processivity factor. Surprisingly, mutations within the β binding domain also ablated interaction with τ, suggesting a larger τ binding site than previously recognized. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Genotype-based association models of complex diseases to detect gene-gene and gene-environment interactions.

PubMed

Lobach, Iryna; Fan, Ruzong; Manga, Prashiela

A central problem in genetic epidemiology is to identify and rank genetic markers involved in a disease. Complex diseases, such as cancer, hypertension, diabetes, are thought to be caused by an interaction of a panel of genetic factors, that can be identified by markers, which modulate environmental factors. Moreover, the effect of each genetic marker may be small. Hence, the association signal may be missed unless a large sample is considered, or a priori biomedical data are used. Recent advances generated a vast variety of a priori information, including linkage maps and information about gene regulatory dependence assembled into curated pathway databases. We propose a genotype-based approach that takes into account linkage disequilibrium (LD) information between genetic markers that are in moderate LD while modeling gene-gene and gene-environment interactions. A major advantage of our method is that the observed genetic information enters a model directly thus eliminating the need to estimate haplotype-phase. Our approach results in an algorithm that is inexpensive computationally and does not suffer from bias induced by haplotype-phase ambiguity. We investigated our model in a series of simulation experiments and demonstrated that the proposed approach results in estimates that are nearly unbiased and have small variability. We applied our method to the analysis of data from a melanoma case-control study and investigated interaction between a set of pigmentation genes and environmental factors defined by age and gender. Furthermore, an application of our method is demonstrated using a study of Alcohol Dependence.

The binary protein-protein interaction landscape of Escherichia coli

PubMed Central

Rajagopala, Seesandra V.; Vlasblom, James; Arnold, Roland; Franca-Koh, Jonathan; Pakala, Suman B.; Phanse, Sadhna; Ceol, Arnaud; Häuser, Roman; Siszler, Gabriella; Wuchty, Stefan; Emili, Andrew; Babu, Mohan; Aloy, Patrick; Pieper, Rembert; Uetz, Peter

2014-01-01

Efforts to map the Escherichia coli interactome have identified several hundred macromolecular complexes, but direct binary protein-protein interactions (PPIs) have not been surveyed on a large scale. Here we performed yeast two-hybrid screens of 3,305 baits against 3,606 preys (~70% of the E. coli proteome) in duplicate to generate a map of 2,234 interactions, approximately doubling the number of known binary PPIs in E. coli. Integration of binary PPIs and genetic interactions revealed functional dependencies among components involved in cellular processes, including envelope integrity, flagellum assembly and protein quality control. Many of the binary interactions that could be mapped within multi-protein complexes were informative regarding internal topology and indicated that interactions within complexes are significantly more conserved than those interactions connecting different complexes. This resource will be useful for inferring bacterial gene function and provides a draft reference of the basic physical wiring network of this evolutionarily significant model microbe. PMID:24561554

Interaction-based evolution: how natural selection and nonrandom mutation work together.

PubMed

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.

Research Review: The Neurobiology and Genetics of Maltreatment and Adversity

ERIC Educational Resources Information Center

McCrory, Eamon; De Brito, Stephane A.; Viding, Essi

2010-01-01

The neurobiological mechanisms by which childhood maltreatment heightens vulnerability to psychopathology remain poorly understood. It is likely that a complex interaction between environmental experiences (including poor caregiving) and an individual's genetic make-up influence neurobiological development across infancy and childhood, which in…

Teleosts as Model Organisms To Understand Host-Microbe Interactions.

PubMed

Lescak, Emily A; Milligan-Myhre, Kathryn C

2017-08-01

Host-microbe interactions are influenced by complex host genetics and environment. Studies across animal taxa have aided our understanding of how intestinal microbiota influence vertebrate development, disease, and physiology. However, traditional mammalian studies can be limited by the use of isogenic strains, husbandry constraints that result in small sample sizes and limited statistical power, reliance on indirect characterization of gut microbial communities from fecal samples, and concerns of whether observations in artificial conditions are actually reflective of what occurs in the wild. Fish models are able to overcome many of these limitations. The extensive variation in the physiology, ecology, and natural history of fish enriches studies of the evolution and ecology of host-microbe interactions. They share physiological and immunological features common among vertebrates, including humans, and harbor complex gut microbiota, which allows identification of the mechanisms driving microbial community assembly. Their accelerated life cycles and large clutch sizes and the ease of sampling both internal and external microbial communities make them particularly well suited for robust statistical studies of microbial diversity. Gnotobiotic techniques, genetic manipulation of the microbiota and host, and transparent juveniles enable novel insights into mechanisms underlying development of the digestive tract and disease states. Many diseases involve a complex combination of genes which are difficult to manipulate in homogeneous model organisms. By taking advantage of the natural genetic variation found in wild fish populations, as well as of the availability of powerful genetic tools, future studies should be able to identify conserved genes and pathways that contribute to human genetic diseases characterized by dysbiosis. Copyright © 2017 Lescak and Milligan-Myhre.

Teleosts as Model Organisms To Understand Host-Microbe Interactions

PubMed Central

2017-01-01

ABSTRACT Host-microbe interactions are influenced by complex host genetics and environment. Studies across animal taxa have aided our understanding of how intestinal microbiota influence vertebrate development, disease, and physiology. However, traditional mammalian studies can be limited by the use of isogenic strains, husbandry constraints that result in small sample sizes and limited statistical power, reliance on indirect characterization of gut microbial communities from fecal samples, and concerns of whether observations in artificial conditions are actually reflective of what occurs in the wild. Fish models are able to overcome many of these limitations. The extensive variation in the physiology, ecology, and natural history of fish enriches studies of the evolution and ecology of host-microbe interactions. They share physiological and immunological features common among vertebrates, including humans, and harbor complex gut microbiota, which allows identification of the mechanisms driving microbial community assembly. Their accelerated life cycles and large clutch sizes and the ease of sampling both internal and external microbial communities make them particularly well suited for robust statistical studies of microbial diversity. Gnotobiotic techniques, genetic manipulation of the microbiota and host, and transparent juveniles enable novel insights into mechanisms underlying development of the digestive tract and disease states. Many diseases involve a complex combination of genes which are difficult to manipulate in homogeneous model organisms. By taking advantage of the natural genetic variation found in wild fish populations, as well as of the availability of powerful genetic tools, future studies should be able to identify conserved genes and pathways that contribute to human genetic diseases characterized by dysbiosis. PMID:28439034

Functioning of the Drosophila Wilms'-Tumor-1-Associated Protein Homolog, Fl(2)d, in Sex-Lethal-Dependent Alternative Splicing

PubMed Central

Penn, Jill K. M.; Graham, Patricia; Deshpande, Girish; Calhoun, Gretchen; Chaouki, Ahmad Sami; Salz, Helen K.; Schedl, Paul

2008-01-01

fl(2)d, the Drosophila homolog of Wilms'-tumor-1-associated protein (WTAP), regulates the alternative splicing of Sex-lethal (Sxl), transformer (tra), and Ultrabithorax (Ubx). Although WTAP has been found in functional human spliceosomes, exactly how it contributes to the splicing process remains unknown. Here we attempt to identify factors that interact genetically and physically with fl(2)d. We begin by analyzing the Sxl-Fl(2)d protein–protein interaction in detail and present evidence suggesting that the female-specific fl(2)d1 allele is antimorphic with respect to the process of sex determination. Next we show that fl(2)d interacts genetically with early acting general splicing regulators and that Fl(2)d is present in immunoprecipitable complexes with Snf, U2AF50, U2AF38, and U1-70K. By contrast, we could not detect Fl(2)d complexes containing the U5 snRNP protein U5-40K or with a protein that associates with the activated B spliceosomal complex SKIP. Significantly, the genetic and molecular interactions observed for Sxl are quite similar to those detected for fl(2)d. Taken together, our findings suggest that Sxl and fl(2)d function to alter splice-site selection at an early step in spliceosome assembly. PMID:18245840

A CRISPR Cas9-based gene drive platform for genetic interaction analysis in Candida albicans

PubMed Central

Shapiro, Rebecca S.; Chavez, Alejandro; Porter, Caroline B. M.; Hamblin, Meagan; Kaas, Christian S.; DiCarlo, James E.; Zeng, Guisheng; Xu, Xiaoli; Revtovich, Alexey V.; Kirienko, Natalia V.; Wang, Yue; Church, George M.; Collins, James J.

2018-01-01

Candida albicans is the leading cause of fungal infections; yet, complex genetic interaction analysis remains cumbersome in this diploid pathogen. Here, we developed a CRISPR-Cas9-based ‘gene drive array’ (GDA) platform to facilitate efficient genetic analysis in C. albicans. In our system, a modified DNA donor molecule acts as a selfish genetic element, replaces the targeted site, and propagates to replace additional wild-type loci. Using mating-competent C. albicans haploids, each carrying a different gene drive disabling a gene of interest, we are able to create diploid strains that are homozygous double-deletion mutants. We generate double-gene deletion libraries to demonstrate this technology, targeting antifungal efflux and biofilm adhesion factors. We screen these libraries to identify virulence regulators and determine how genetic networks shift under diverse conditions. This platform transforms our ability to perform genetic interaction analysis in C. albicans and is readily extended to other fungal pathogens. PMID:29062088

A novel approach to simulate gene-environment interactions in complex diseases.

PubMed

Amato, Roberto; Pinelli, Michele; D'Andrea, Daniel; Miele, Gennaro; Nicodemi, Mario; Raiconi, Giancarlo; Cocozza, Sergio

2010-01-05

Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.). Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS), a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte Carlo process allows random variability. A knowledge-based approach reduces the complexity of the mathematical model by using reasonable biological constraints and makes the simulation more understandable in biological terms. Simulated data sets can be used for the assessment of novel statistical methods or for the evaluation of the statistical power when designing a study.

Design and analysis issues in gene and environment studies

PubMed Central

2012-01-01

Both nurture (environmental) and nature (genetic factors) play an important role in human disease etiology. Traditionally, these effects have been thought of as independent. This perspective is ill informed for non-mendelian complex disorders which result as an interaction between genetics and environment. To understand health and disease we must study how nature and nurture interact. Recent advances in human genomics and high-throughput biotechnology make it possible to study large numbers of genetic markers and gene products simultaneously to explore their interactions with environment. The purpose of this review is to discuss design and analytic issues for gene-environment interaction studies in the “-omics” era, with a focus on environmental and genetic epidemiological studies. We present an expanded environmental genomic disease paradigm. We discuss several study design issues for gene-environmental interaction studies, including confounding and selection bias, measurement of exposures and genotypes. We discuss statistical issues in studying gene-environment interactions in different study designs, such as choices of statistical models, assumptions regarding biological factors, and power and sample size considerations, especially in genome-wide gene-environment studies. Future research directions are also discussed. PMID:23253229

Design and analysis issues in gene and environment studies.

PubMed

Liu, Chen-yu; Maity, Arnab; Lin, Xihong; Wright, Robert O; Christiani, David C

2012-12-19

Both nurture (environmental) and nature (genetic factors) play an important role in human disease etiology. Traditionally, these effects have been thought of as independent. This perspective is ill informed for non-mendelian complex disorders which result as an interaction between genetics and environment. To understand health and disease we must study how nature and nurture interact. Recent advances in human genomics and high-throughput biotechnology make it possible to study large numbers of genetic markers and gene products simultaneously to explore their interactions with environment. The purpose of this review is to discuss design and analytic issues for gene-environment interaction studies in the "-omics" era, with a focus on environmental and genetic epidemiological studies. We present an expanded environmental genomic disease paradigm. We discuss several study design issues for gene-environmental interaction studies, including confounding and selection bias, measurement of exposures and genotypes. We discuss statistical issues in studying gene-environment interactions in different study designs, such as choices of statistical models, assumptions regarding biological factors, and power and sample size considerations, especially in genome-wide gene-environment studies. Future research directions are also discussed.

Life history determines genetic structure and evolutionary potential of host–parasite interactions

PubMed Central

Barrett, Luke G.; Thrall, Peter H.; Burdon, Jeremy J.; Linde, Celeste C.

2009-01-01

Measures of population genetic structure and diversity of disease-causing organisms are commonly used to draw inferences regarding their evolutionary history and potential to generate new variation in traits that determine interactions with their hosts. Parasite species exhibit a range of population structures and life-history strategies, including different transmission modes, life-cycle complexity, off-host survival mechanisms and dispersal ability. These are important determinants of the frequency and predictability of interactions with host species. Yet the complex causal relationships between spatial structure, life history and the evolutionary dynamics of parasite populations are not well understood. We demonstrate that a clear picture of the evolutionary potential of parasitic organisms and their demographic and evolutionary histories can only come from understanding the role of life history and spatial structure in influencing population dynamics and epidemiological patterns. PMID:18947899

Life history determines genetic structure and evolutionary potential of host-parasite interactions.

PubMed

Barrett, Luke G; Thrall, Peter H; Burdon, Jeremy J; Linde, Celeste C

2008-12-01

Measures of population genetic structure and diversity of disease-causing organisms are commonly used to draw inferences regarding their evolutionary history and potential to generate new variation in traits that determine interactions with their hosts. Parasite species exhibit a range of population structures and life-history strategies, including different transmission modes, life-cycle complexity, off-host survival mechanisms and dispersal ability. These are important determinants of the frequency and predictability of interactions with host species. Yet the complex causal relationships between spatial structure, life history and the evolutionary dynamics of parasite populations are not well understood. We demonstrate that a clear picture of the evolutionary potential of parasitic organisms and their demographic and evolutionary histories can only come from understanding the role of life history and spatial structure in influencing population dynamics and epidemiological patterns.

A computational interactome for prioritizing genes associated with complex agronomic traits in rice (Oryza sativa).

PubMed

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.

Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease

PubMed Central

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

Discovery of gene-gene interactions across multiple independent data sets of late onset Alzheimer disease from the Alzheimer Disease Genetics Consortium.

PubMed

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.

A kernel regression approach to gene-gene interaction detection for case-control studies.

PubMed

Larson, Nicholas B; Schaid, Daniel J

2013-11-01

Gene-gene interactions are increasingly being addressed as a potentially important contributor to the variability of complex traits. Consequently, attentions have moved beyond single locus analysis of association to more complex genetic models. Although several single-marker approaches toward interaction analysis have been developed, such methods suffer from very high testing dimensionality and do not take advantage of existing information, notably the definition of genes as functional units. Here, we propose a comprehensive family of gene-level score tests for identifying genetic elements of disease risk, in particular pairwise gene-gene interactions. Using kernel machine methods, we devise score-based variance component tests under a generalized linear mixed model framework. We conducted simulations based upon coalescent genetic models to evaluate the performance of our approach under a variety of disease models. These simulations indicate that our methods are generally higher powered than alternative gene-level approaches and at worst competitive with exhaustive SNP-level (where SNP is single-nucleotide polymorphism) analyses. Furthermore, we observe that simulated epistatic effects resulted in significant marginal testing results for the involved genes regardless of whether or not true main effects were present. We detail the benefits of our methods and discuss potential genome-wide analysis strategies for gene-gene interaction analysis in a case-control study design. © 2013 WILEY PERIODICALS, INC.

Environmentally induced changes in correlated responses to selection reveal variable pleiotropy across a complex genetic network.

PubMed

Sikkink, Kristin L; Reynolds, Rose M; Cresko, William A; Phillips, Patrick C

2015-05-01

Selection in novel environments can lead to a coordinated evolutionary response across a suite of characters. Environmental conditions can also potentially induce changes in the genetic architecture of complex traits, which in turn could alter the pattern of the multivariate response to selection. We describe a factorial selection experiment using the nematode Caenorhabditis remanei in which two different stress-related phenotypes (heat and oxidative stress resistance) were selected under three different environmental conditions. The pattern of covariation in the evolutionary response between phenotypes or across environments differed depending on the environment in which selection occurred, including asymmetrical responses to selection in some cases. These results indicate that variation in pleiotropy across the stress response network is highly sensitive to the external environment. Our findings highlight the complexity of the interaction between genes and environment that influences the ability of organisms to acclimate to novel environments. They also make clear the need to identify the underlying genetic basis of genetic correlations in order understand how patterns of pleiotropy are distributed across complex genetic networks. © 2015 The Author(s).

ENVIRONMENTALLY INDUCED CHANGES IN CORRELATED RESPONSES TO SELECTION REVEAL VARIABLE PLEIOTROPY ACROSS A COMPLEX GENETIC NETWORK

PubMed Central

Sikkink, Kristin L.; Reynolds, Rose M.; Cresko, William A.; Phillips, Patrick C.

2017-01-01

Selection in novel environments can lead to a coordinated evolutionary response across a suite of characters. Environmental conditions can also potentially induce changes in the genetic architecture of complex traits, which in turn could alter the pattern of the multivariate response to selection. We describe a factorial selection experiment using the nematode Caenorhabditis remanei in which two different stress-related phenotypes (heat and oxidative stress resistance) were selected under three different environmental conditions. The pattern of covariation in the evolutionary response between phenotypes or across environments differed depending on the environment in which selection occurred, including asymmetrical responses to selection in some cases. These results indicate that variation in pleiotropy across the stress response network is highly sensitive to the external environment. Our findings highlight the complexity of the interaction between genes and environment that influences the ability of organisms to acclimate to novel environments. They also make clear the need to identify the underlying genetic basis of genetic correlations in order understand how patterns of pleiotropy are distributed across complex genetic networks. PMID:25809411

Mitochondrial-Nuclear Epistasis: Implications for Human Aging and Longevity

PubMed Central

Tranah, Gregory

2010-01-01

There is substantial evidence that mitochondria are involved in the aging process. Mitochondrial function requires the coordinated expression of hundreds of nuclear genes and a few dozen mitochondrial genes, many of which have been associated with either extended or shortened life span. Impaired mitochondrial function resulting from mtDNA and nuclear DNA variation is likely to contribute to an imbalance in cellular energy homeostasis, increased vulnerability to oxidative stress, and an increased rate of cellular senescence and aging. The complex genetic architecture of mitochondria suggests that there may be an equally complex set of gene interactions (epistases) involving genetic variation in the nuclear and mitochondrial genomes. Results from Drosophila suggest that the effects of mtDNA haplotypes on longevity vary among different nuclear allelic backgrounds, which could account for the inconsistent associations that have been observed between mitochondrial DNA (mtDNA) haplogroups and survival in humans. A diversity of pathways may influence the way mitochondria and nuclear – mitochondrial interactions modulate longevity, including: oxidative phosphorylation; mitochondrial uncoupling; antioxidant defenses; mitochondrial fission and fusion; and sirtuin regulation of mitochondrial genes. We hypothesize that aging and longevity, as complex traits having a significant genetic component, are likely to be controlled by nuclear gene variants interacting with both inherited and somatic mtDNA variability. PMID:20601194

Dissection of complicate genetic architecture and breeding perspective of cottonseed traits by genome-wide association study.

PubMed

Du, Xiongming; Liu, Shouye; Sun, Junling; Zhang, Gengyun; Jia, Yinhua; Pan, Zhaoe; Xiang, Haitao; He, Shoupu; Xia, Qiuju; Xiao, Songhua; Shi, Weijun; Quan, Zhiwu; Liu, Jianguang; Ma, Jun; Pang, Baoyin; Wang, Liru; Sun, Gaofei; Gong, Wenfang; Jenkins, Johnie N; Lou, Xiangyang; Zhu, Jun; Xu, Haiming

2018-06-13

Cottonseed is one of the most important raw materials for plant protein, oil and alternative biofuel for diesel engines. Understanding the complex genetic basis of cottonseed traits is requisite for achieving efficient genetic improvement of the traits. However, it is not yet clear about their genetic architecture in genomic level. GWAS has been an effective way to explore genetic basis of quantitative traits in human and many crops. This study aims to dissect genetic mechanism seven cottonseed traits by a GWAS for genetic improvement. A genome-wide association study (GWAS) based on a full gene model with gene effects as fixed and gene-environment interaction as random, was conducted for protein, oil and 5 fatty acids using 316 accessions and ~ 390 K SNPs. Totally, 124 significant quantitative trait SNPs (QTSs), consisting of 16, 21, 87 for protein, oil and fatty acids (palmitic, linoleic, oleic, myristic, stearic), respectively, were identified and the broad-sense heritability was estimated from 71.62 to 93.43%; no QTS-environment interaction was detected for the protein, the palmitic and the oleic contents; the protein content was predominantly controlled by epistatic effects accounting for 65.18% of the total variation, but the oil content and the fatty acids except the palmitic were mainly determined by gene main effects and no epistasis was detected for the myristic and the stearic. Prediction of superior pure line and hybrid revealed the potential of the QTSs in the improvement of cottonseed traits, and the hybrid could achieve higher or lower genetic values compared with pure lines. This study revealed complex genetic architecture of seven cottonseed traits at whole genome-wide by mixed linear model approach; the identified genetic variants and estimated genetic component effects of gene, gene-gene and gene-environment interaction provide cotton geneticist or breeders new knowledge on the genetic mechanism of the traits and the potential molecular breeding design strategy.

Connecting the Human Variome Project to nutrigenomics.

PubMed

Kaput, Jim; Evelo, Chris T; Perozzi, Giuditta; van Ommen, Ben; Cotton, Richard

2010-12-01

Nutrigenomics is the science of analyzing and understanding gene-nutrient interactions, which because of the genetic heterogeneity, varying degrees of interaction among gene products, and the environmental diversity is a complex science. Although much knowledge of human diversity has been accumulated, estimates suggest that ~90% of genetic variation has not yet been characterized. Identification of the DNA sequence variants that contribute to nutrition-related disease risk is essential for developing a better understanding of the complex causes of disease in humans, including nutrition-related disease. The Human Variome Project (HVP; http://www.humanvariomeproject.org/) is an international effort to systematically identify genes, their mutations, and their variants associated with phenotypic variability and indications of human disease or phenotype. Since nutrigenomic research uses genetic information in the design and analysis of experiments, the HVP is an essential collaborator for ongoing studies of gene-nutrient interactions. With the advent of next generation sequencing methodologies and the understanding of the undiscovered variation in human genomes, the nutrigenomic community will be generating novel sequence data and results. The guidelines and practices of the HVP can guide and harmonize these efforts.

Connecting the Human Variome Project to nutrigenomics

PubMed Central

Evelo, Chris T.; Perozzi, Giuditta; van Ommen, Ben; Cotton, Richard

2010-01-01

Nutrigenomics is the science of analyzing and understanding gene–nutrient interactions, which because of the genetic heterogeneity, varying degrees of interaction among gene products, and the environmental diversity is a complex science. Although much knowledge of human diversity has been accumulated, estimates suggest that ~90% of genetic variation has not yet been characterized. Identification of the DNA sequence variants that contribute to nutrition-related disease risk is essential for developing a better understanding of the complex causes of disease in humans, including nutrition-related disease. The Human Variome Project (HVP; http://www.humanvariomeproject.org/) is an international effort to systematically identify genes, their mutations, and their variants associated with phenotypic variability and indications of human disease or phenotype. Since nutrigenomic research uses genetic information in the design and analysis of experiments, the HVP is an essential collaborator for ongoing studies of gene–nutrient interactions. With the advent of next generation sequencing methodologies and the understanding of the undiscovered variation in human genomes, the nutrigenomic community will be generating novel sequence data and results. The guidelines and practices of the HVP can guide and harmonize these efforts. PMID:28300226

Host genetic variation impacts microbiome composition across human body sites.

PubMed

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.

Interactions Between Anandamide and Corticotropin-Releasing Factor Signaling Modulate Human Amygdala Function and Risk for Anxiety Disorders: An Imaging Genetics Strategy for Modeling Molecular Interactions.

PubMed

Demers, Catherine H; Drabant Conley, Emily; Bogdan, Ryan; Hariri, Ahmad R

2016-09-01

Preclinical models reveal that stress-induced amygdala activity and impairment in fear extinction reflect reductions in anandamide driven by corticotropin-releasing factor receptor type 1 (CRF1) potentiation of the anandamide catabolic enzyme fatty acid amide hydrolase. Here, we provide clinical translation for the importance of these molecular interactions using an imaging genetics strategy to examine whether interactions between genetic polymorphisms associated with differential anandamide (FAAH rs324420) and CRF1 (CRHR1 rs110402) signaling modulate amygdala function and anxiety disorder diagnosis. Analyses revealed that individuals with a genetic background predicting relatively high anandamide and CRF1 signaling exhibited blunted basolateral amygdala habituation, which further mediated increased risk for anxiety disorders among these same individuals. The convergence of preclinical and clinical data suggests that interactions between anandamide and CRF1 represent a fundamental molecular mechanism regulating amygdala function and anxiety. Our results further highlight the potential of imaging genetics to powerfully translate complex preclinical findings to clinically meaningful human phenotypes. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Systems genetics: a paradigm to improve discovery of candidate genes and mechanisms underlying complex traits.

PubMed

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.

Environmental Sensing of Expert Knowledge in a Computational Evolution System for Complex Problem Solving in Human Genetics

NASA Astrophysics Data System (ADS)

Greene, Casey S.; Hill, Douglas P.; Moore, Jason H.

The relationship between interindividual variation in our genomes and variation in our susceptibility to common diseases is expected to be complex with multiple interacting genetic factors. A central goal of human genetics is to identify which DNA sequence variations predict disease risk in human populations. Our success in this endeavour will depend critically on the development and implementation of computational intelligence methods that are able to embrace, rather than ignore, the complexity of the genotype to phenotype relationship. To this end, we have developed a computational evolution system (CES) to discover genetic models of disease susceptibility involving complex relationships between DNA sequence variations. The CES approach is hierarchically organized and is capable of evolving operators of any arbitrary complexity. The ability to evolve operators distinguishes this approach from artificial evolution approaches using fixed operators such as mutation and recombination. Our previous studies have shown that a CES that can utilize expert knowledge about the problem in evolved operators significantly outperforms a CES unable to use this knowledge. This environmental sensing of external sources of biological or statistical knowledge is important when the search space is both rugged and large as in the genetic analysis of complex diseases. We show here that the CES is also capable of evolving operators which exploit one of several sources of expert knowledge to solve the problem. This is important for both the discovery of highly fit genetic models and because the particular source of expert knowledge used by evolved operators may provide additional information about the problem itself. This study brings us a step closer to a CES that can solve complex problems in human genetics in addition to discovering genetic models of disease.

Identifying Genotype-by-Environment Interactions in the Metabolism of Germinating Arabidopsis Seeds Using Generalized Genetical Genomics 1[C][W][OA

PubMed Central

Joosen, Ronny Viktor Louis; Arends, Danny; Li, Yang; Willems, Leo A.J.; Keurentjes, Joost J.B.; Ligterink, Wilco; Jansen, Ritsert C.; Hilhorst, Henk W.M.

2013-01-01

A complex phenotype such as seed germination is the result of several genetic and environmental cues and requires the concerted action of many genes. The use of well-structured recombinant inbred lines in combination with “omics” analysis can help to disentangle the genetic basis of such quantitative traits. This so-called genetical genomics approach can effectively capture both genetic and epistatic interactions. However, to understand how the environment interacts with genomic-encoded information, a better understanding of the perception and processing of environmental signals is needed. In a classical genetical genomics setup, this requires replication of the whole experiment in different environmental conditions. A novel generalized setup overcomes this limitation and includes environmental perturbation within a single experimental design. We developed a dedicated quantitative trait loci mapping procedure to implement this approach and used existing phenotypical data to demonstrate its power. In addition, we studied the genetic regulation of primary metabolism in dry and imbibed Arabidopsis (Arabidopsis thaliana) seeds. In the metabolome, many changes were observed that were under both environmental and genetic controls and their interaction. This concept offers unique reduction of experimental load with minimal compromise of statistical power and is of great potential in the field of systems genetics, which requires a broad understanding of both plasticity and dynamic regulation. PMID:23606598

Genes for normal sleep and sleep disorders.

PubMed

Tafti, Mehdi; Maret, Stéphanie; Dauvilliers, Yves

2005-01-01

Sleep and wakefulness are complex behaviors that are influenced by many genetic and environmental factors, which are beginning to be discovered. The contribution of genetic components to sleep disorders is also increasingly recognized as important. Point mutations in the prion protein, period 2, and the prepro-hypocretin/orexin gene have been found as the cause of a few sleep disorders but the possibility that other gene defects may contribute to the pathophysiology of major sleep disorders is worth in-depth investigations. However, single gene disorders are rare and most common disorders are complex in terms of their genetic susceptibility, environmental effects, gene-gene, and gene-environment interactions. We review here the current progress in the genetics of normal and pathological sleep.

Discovering Hematopoietic Mechanisms Through Genome-Wide Analysis of GATA Factor Chromatin Occupancy

PubMed Central

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

Design of a Family Study Among High-Risk Caribbean Hispanics: The Northern Manhattan Family Study

PubMed Central

Sacco, Ralph L.; Sabala, Edison A.; Rundek, Tanja; Juo, Suh-Hang Hank; Huang, Jinaping Sam; DiTullio, Marco; Homma, Shunichi; Almonte, Katihurka; Lithgow, Carlos García; Boden-Albala, Bernadette

2008-01-01

Stroke continues to kill disproportionately more Blacks and Hispanics than Whites in the United States. Racial/ethnic variations in the incidence of stroke and prevalence of stroke risk factors are probably explained by both genetic and environmental influences. Family studies can help identify genetic predisposition to stroke and potential stroke precursors. Few studies have evaluated the heritability of these stroke risk factors among non-White populations, and none have focused on Caribbean Hispanic populations. The aim of the Northern Manhattan Family Study (NOMAFS) is to investigate the gene-environment interaction of stroke risk factors among Caribbean Hispanics. The unique recruitment and methodologic approaches used in this study are relevant to the design and conduct of genetic aggregation studies to investigate complex genetic disorders in non-White populations. The aim of this paper is to describe the NOMAFS and report enrollment and characteristics of the participants. The NO-MAFS will provide a data resource for the exploration of the genetic determinants of highly heritable stroke precursor phenotypes that are less complex than the stroke phenotype. Understanding the gene environment interaction is the critical next step toward the development of new and unique approaches to disease prevention and interventions. PMID:17682370

Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases

PubMed Central

Ritchie, Marylyn D; White, Bill C; Parker, Joel S; Hahn, Lance W; Moore, Jason H

2003-01-01

Background Appropriate definition of neural network architecture prior to data analysis is crucial for successful data mining. This can be challenging when the underlying model of the data is unknown. The goal of this study was to determine whether optimizing neural network architecture using genetic programming as a machine learning strategy would improve the ability of neural networks to model and detect nonlinear interactions among genes in studies of common human diseases. Results Using simulated data, we show that a genetic programming optimized neural network approach is able to model gene-gene interactions as well as a traditional back propagation neural network. Furthermore, the genetic programming optimized neural network is better than the traditional back propagation neural network approach in terms of predictive ability and power to detect gene-gene interactions when non-functional polymorphisms are present. Conclusion This study suggests that a machine learning strategy for optimizing neural network architecture may be preferable to traditional trial-and-error approaches for the identification and characterization of gene-gene interactions in common, complex human diseases. PMID:12846935

Gemini surfactants mediate efficient mitochondrial gene delivery and expression.

PubMed

Cardoso, Ana M; Morais, Catarina M; Cruz, A Rita; Cardoso, Ana L; Silva, Sandra G; do Vale, M Luísa; Marques, Eduardo F; Pedroso de Lima, Maria C; Jurado, Amália S

2015-03-02

Gene delivery targeting mitochondria has the potential to transform the therapeutic landscape of mitochondrial genetic diseases. Taking advantage of the nonuniversal genetic code used by mitochondria, a plasmid DNA construct able to be specifically expressed in these organelles was designed by including a codon, which codes for an amino acid only if read by the mitochondrial ribosomes. In the present work, gemini surfactants were shown to successfully deliver plasmid DNA to mitochondria. Gemini surfactant-based DNA complexes were taken up by cells through a variety of routes, including endocytic pathways, and showed propensity for inducing membrane destabilization under acidic conditions, thus facilitating cytoplasmic release of DNA. Furthermore, the complexes interacted extensively with lipid membrane models mimicking the composition of the mitochondrial membrane, which predicts a favored interaction of the complexes with mitochondria in the intracellular environment. This work unravels new possibilities for gene therapy toward mitochondrial diseases.

Structural reducibility of multilayer networks

NASA Astrophysics Data System (ADS)

de Domenico, Manlio; Nicosia, Vincenzo; Arenas, Alexandre; Latora, Vito

2015-04-01

Many complex systems can be represented as networks consisting of distinct types of interactions, which can be categorized as links belonging to different layers. For example, a good description of the full protein-protein interactome requires, for some organisms, up to seven distinct network layers, accounting for different genetic and physical interactions, each containing thousands of protein-protein relationships. A fundamental open question is then how many layers are indeed necessary to accurately represent the structure of a multilayered complex system. Here we introduce a method based on quantum theory to reduce the number of layers to a minimum while maximizing the distinguishability between the multilayer network and the corresponding aggregated graph. We validate our approach on synthetic benchmarks and we show that the number of informative layers in some real multilayer networks of protein-genetic interactions, social, economical and transportation systems can be reduced by up to 75%.

Genome Island: A Virtual Science Environment in Second Life

ERIC Educational Resources Information Center

Clark, Mary Anne

2009-01-01

Mary Anne CLark describes the organization and uses of Genome Island, a virtual laboratory complex constructed in Second Life. Genome Island was created for teaching genetics to university undergraduates but also provides a public space where anyone interested in genetics can spend a few minutes, or a few hours, interacting with genetic…

Multigenic Natural Variation Underlies Caenorhabditis elegans Olfactory Preference for the Bacterial Pathogen Serratia marcescens

PubMed Central

Glater, Elizabeth E.; Rockman, Matthew V.; Bargmann, Cornelia I.

2013-01-01

The nematode Caenorhabditis elegans can use olfaction to discriminate among different kinds of bacteria, its major food source. We asked how natural genetic variation contributes to choice behavior, focusing on differences in olfactory preference behavior between two wild-type C. elegans strains. The laboratory strain N2 strongly prefers the odor of Serratia marcescens, a soil bacterium that is pathogenic to C. elegans, to the odor of Escherichia coli, a commonly used laboratory food source. The divergent Hawaiian strain CB4856 has a weaker attraction to Serratia than the N2 strain, and this behavioral difference has a complex genetic basis. At least three quantitative trait loci (QTLs) from the CB4856 Hawaii strain (HW) with large effect sizes lead to reduced Serratia preference when introgressed into an N2 genetic background. These loci interact and have epistatic interactions with at least two antagonistic QTLs from HW that increase Serratia preference. The complex genetic architecture of this C. elegans trait is reminiscent of the architecture of mammalian metabolic and behavioral traits. PMID:24347628

The Meckel syndrome- associated protein MKS1 functionally interacts with components of the BBSome and IFT complexes to mediate ciliary trafficking and hedgehog signaling

PubMed Central

Barrington, Chloe L.; Katsanis, Nicholas

2017-01-01

The importance of primary cilia in human health is underscored by the link between ciliary dysfunction and a group of primarily recessive genetic disorders with overlapping clinical features, now known as ciliopathies. Many of the proteins encoded by ciliopathy-associated genes are components of a handful of multi-protein complexes important for the transport of cargo to the basal body and/or into the cilium. A key question is whether different complexes cooperate in cilia formation, and whether they participate in cilium assembly in conjunction with intraflagellar transport (IFT) proteins. To examine how ciliopathy protein complexes might function together, we have analyzed double mutants of an allele of the Meckel syndrome (MKS) complex protein MKS1 and the BBSome protein BBS4. We find that Mks1; Bbs4 double mutant mouse embryos exhibit exacerbated defects in Hedgehog (Hh) dependent patterning compared to either single mutant, and die by E14.5. Cells from double mutant embryos exhibit a defect in the trafficking of ARL13B, a ciliary membrane protein, resulting in disrupted ciliary structure and signaling. We also examined the relationship between the MKS complex and IFT proteins by analyzing double mutant between Mks1 and a hypomorphic allele of the IFTB component Ift172. Despite each single mutant surviving until around birth, Mks1; Ift172avc1 double mutants die at mid-gestation, and exhibit a dramatic failure of cilia formation. We also find that Mks1 interacts genetically with an allele of Dync2h1, the IFT retrograde motor. Thus, we have demonstrated that the MKS transition zone complex cooperates with the BBSome to mediate trafficking of specific trans-membrane receptors to the cilium. Moreover, the genetic interaction of Mks1 with components of IFT machinery suggests that the transition zone complex facilitates IFT to promote cilium assembly and structure. PMID:28291807

Environmental Interactions and Epistasis Are Revealed in the Proteomic Responses to Complex Stimuli

PubMed Central

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

Interaction-based evolution: how natural selection and nonrandom mutation work together

PubMed Central

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

Genetics of preeclampsia: what are the challenges?

PubMed

Bernard, Nathalie; Giguère, Yves

2003-07-01

Despite recent efforts to identify susceptibility genes of preeclampsia, the genetic determinants of the condition remain ill-defined, as is the situation for most disorders of complex inheritance patterns. The angiotensinogen, factor V, and methylenetetrahydrofolate reductase genes have been investigated in different populations, as have other genes involved in blood pressure, vascular volume control, thrombophilia, lipid metabolism, oxidative stress, and endothelial dysfunction. The study of the genetics of complex traits is faced with both methodological and genetic issues; these include adequate sample size to allow for the identification of modest genetic effects, of gene-gene and gene-environment interactions, the study of adequate quantitative traits and extreme phenotypes, haplotype analyses, statistical genetics, genome-wide (hypothesis-free) versus candidate-gene (hypothesis-driven) approaches, and the validation of positive associations. The use of genetically well-characterized populations showing a founder effect, such as the French-Canadian population of Quebec, in genetic association studies, may help to unravel the susceptibility genes of disorders showing complex inheritance, such as preeclampsia. It is necessary to better evaluate the role of the fetal genome in the resulting predisposition to preeclampsia and its complications. Eventually, we may be able to integrate genetic information to better identify the women at risk of developing preeclampsia, and to improve the management of those suffering from this condition.

No boundaries: genomes, organisms, and ecological interactions responsible for divergence and reproductive isolation.

PubMed

Etges, William J

2014-01-01

Revealing the genetic basis of traits that cause reproductive isolation, particularly premating or sexual isolation, usually involves the same challenges as most attempts at genotype-phenotype mapping and so requires knowledge of how these traits are expressed in different individuals, populations, and environments, particularly under natural conditions. Genetic dissection of speciation phenotypes thus requires understanding of the internal and external contexts in which underlying genetic elements are expressed. Gene expression is a product of complex interacting factors internal and external to the organism including developmental programs, the genetic background including nuclear-cytotype interactions, epistatic relationships, interactions among individuals or social effects, stochasticity, and prevailing variation in ecological conditions. Understanding of genomic divergence associated with reproductive isolation will be facilitated by functional expression analysis of annotated genomes in organisms with well-studied evolutionary histories, phylogenetic affinities, and known patterns of ecological variation throughout their life cycles. I review progress and prospects for understanding the pervasive role of host plant use on genetic and phenotypic expression of reproductive isolating mechanisms in cactophilic Drosophila mojavensis and suggest how this system can be used as a model for revealing the genetic basis for species formation in organisms where speciation phenotypes are under the joint influences of genetic and environmental factors. © The American Genetic Association. 2014. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Complex interactions amongst N-cadherin, DLAR, and Liprin-α regulate Drosophila photoreceptor axon targeting

PubMed Central

Prakash, Saurabh; Maclendon, Helen; Dubreuil, Catherine I.; Ghose, Aurnab; Hwa, Jennifer; Dennehy, Kelly A.; Tomalty, Katharine M.H.; Clark, Kelsey; Van Vactor, David; Clandinin, Thomas R.

2009-01-01

The formation of stable adhesive contacts between pre- and post-synaptic neurons represents the initial step in synapse assembly. The cell adhesion molecule N-cadherin, the receptor tyrosine phosphatase DLAR, and the scaffolding molecule Liprin-α play critical, evolutionarily conserved roles in this process. However, how these proteins signal to the growth cone, and are themselves regulated, remains poorly understood. Using Drosophila photoreceptors (R cells) as a model, we evaluate genetic and physical interactions among these three proteins. We demonstrate that DLAR function in this context is independent of phosphatase activity, but requires interactions mediated by its intracellular domain. Genetic studies reveal both positive and, surprisingly, inhibitory interactions amongst all three genes. These observations are corroborated by biochemical studies demonstrating that DLAR physically associates via its phosphatase domain with N-cadherin in Drosophila embryos. Together, these data demonstrate that N-cadherin, DLAR, and Liprin-α function in a complex to regulate adhesive interactions between pre- and post-synaptic cells, and provide a novel mechanism for controlling the activity of liprin-α in the developing growth cone. PMID:19766621

Gene-gene and gene-environment interactions defining lipid-related traits.

PubMed

Ordovás, José M; Robertson, Ruairi; Cléirigh, Ellen Ní

2011-04-01

Steps towards reducing chronic disease progression are continuously being taken through the form of genomic research. Studies over the last year have highlighted more and more polymorphisms, pathways and interactions responsible for metabolic disorders such as cardiovascular disease, obesity and dyslipidemia. Many of these chronic illnesses can be partially blamed by altered lipid metabolism, combined with individual genetic components. Critical evaluation and comparison of these recent studies is essential in order to comprehend the results, conclusions and future prospects in the field of genomics as a whole. Recent literature elucidates significant gene--diet and gene--environment interactions resulting in altered lipid metabolism, inflammation and other metabolic imbalances leading to cardiovascular disease and obesity. Epigenetic and epistatic interactions are now becoming more significantly associated with such disorders, as genomic research digs deeper into the complex nature of genetic individuality and heritability. The vast array of data collected from genome-wide association studies must now be empowered and explored through more complex interaction studies, using standardized methods and larger sample sizes. In doing so the etiology of chronic disease progression will be further understood.

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

DOE PAGES

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

2017-10-13

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

Cross-Study Comparison Reveals Common Genomic, Network, and Functional Signatures of Desiccation Resistance in Drosophila melanogaster

PubMed Central

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

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis.

PubMed

Sakhanenko, Nikita A; Kunert-Graf, James; Galas, David J

2017-12-01

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. We present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discrete variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis-that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. We illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.

Next Generation Analytic Tools for Large Scale Genetic Epidemiology Studies of Complex Diseases

PubMed Central

Mechanic, Leah E.; Chen, Huann-Sheng; Amos, Christopher I.; Chatterjee, Nilanjan; Cox, Nancy J.; Divi, Rao L.; Fan, Ruzong; Harris, Emily L.; Jacobs, Kevin; Kraft, Peter; Leal, Suzanne M.; McAllister, Kimberly; Moore, Jason H.; Paltoo, Dina N.; Province, Michael A.; Ramos, Erin M.; Ritchie, Marylyn D.; Roeder, Kathryn; Schaid, Daniel J.; Stephens, Matthew; Thomas, Duncan C.; Weinberg, Clarice R.; Witte, John S.; Zhang, Shunpu; Zöllner, Sebastian; Feuer, Eric J.; Gillanders, Elizabeth M.

2012-01-01

Over the past several years, genome-wide association studies (GWAS) have succeeded in identifying hundreds of genetic markers associated with common diseases. However, most of these markers confer relatively small increments of risk and explain only a small proportion of familial clustering. To identify obstacles to future progress in genetic epidemiology research and provide recommendations to NIH for overcoming these barriers, the National Cancer Institute sponsored a workshop entitled “Next Generation Analytic Tools for Large-Scale Genetic Epidemiology Studies of Complex Diseases” on September 15–16, 2010. The goal of the workshop was to facilitate discussions on (1) statistical strategies and methods to efficiently identify genetic and environmental factors contributing to the risk of complex disease; and (2) how to develop, apply, and evaluate these strategies for the design, analysis, and interpretation of large-scale complex disease association studies in order to guide NIH in setting the future agenda in this area of research. The workshop was organized as a series of short presentations covering scientific (gene-gene and gene-environment interaction, complex phenotypes, and rare variants and next generation sequencing) and methodological (simulation modeling and computational resources and data management) topic areas. Specific needs to advance the field were identified during each session and are summarized. PMID:22147673

Complex Adaptive System Models and the Genetic Analysis of Plasma HDL-Cholesterol Concentration

PubMed Central

Rea, Thomas J.; Brown, Christine M.; Sing, Charles F.

2006-01-01

Despite remarkable advances in diagnosis and therapy, ischemic heart disease (IHD) remains a leading cause of morbidity and mortality in industrialized countries. Recent efforts to estimate the influence of genetic variation on IHD risk have focused on predicting individual plasma high-density lipoprotein cholesterol (HDL-C) concentration. Plasma HDL-C concentration (mg/dl), a quantitative risk factor for IHD, has a complex multifactorial etiology that involves the actions of many genes. Single gene variations may be necessary but are not individually sufficient to predict a statistically significant increase in risk of disease. The complexity of phenotype-genotype-environment relationships involved in determining plasma HDL-C concentration has challenged commonly held assumptions about genetic causation and has led to the question of which combination of variations, in which subset of genes, in which environmental strata of a particular population significantly improves our ability to predict high or low risk phenotypes. We document the limitations of inferences from genetic research based on commonly accepted biological models, consider how evidence for real-world dynamical interactions between HDL-C determinants challenges the simplifying assumptions implicit in traditional linear statistical genetic models, and conclude by considering research options for evaluating the utility of genetic information in predicting traits with complex etiologies. PMID:17146134

Bovine coronavirus antibody titers at weaning negatively correlate with incidence of bovine respiratory disease in the feed yard

USDA-ARS?s Scientific Manuscript database

Bovine respiratory disease complex (BRDC) is a multifactorial disease caused by complex interactions among viral and bacterial pathogens, stressful management practices and host genetic variability. Although vaccines and antibiotic treatments are readily available to prevent and treat infection caus...

Evolutionary diversification of protein-protein interactions by interface add-ons.

PubMed

Plach, Maximilian G; Semmelmann, Florian; Busch, Florian; Busch, Markus; Heizinger, Leonhard; Wysocki, Vicki H; Merkl, Rainer; Sterner, Reinhard

2017-10-03

Cells contain a multitude of protein complexes whose subunits interact with high specificity. However, the number of different protein folds and interface geometries found in nature is limited. This raises the question of how protein-protein interaction specificity is achieved on the structural level and how the formation of nonphysiological complexes is avoided. Here, we describe structural elements called interface add-ons that fulfill this function and elucidate their role for the diversification of protein-protein interactions during evolution. We identified interface add-ons in 10% of a representative set of bacterial, heteromeric protein complexes. The importance of interface add-ons for protein-protein interaction specificity is demonstrated by an exemplary experimental characterization of over 30 cognate and hybrid glutamine amidotransferase complexes in combination with comprehensive genetic profiling and protein design. Moreover, growth experiments showed that the lack of interface add-ons can lead to physiologically harmful cross-talk between essential biosynthetic pathways. In sum, our complementary in silico, in vitro, and in vivo analysis argues that interface add-ons are a practical and widespread evolutionary strategy to prevent the formation of nonphysiological complexes by specializing protein-protein interactions.

Identifying Protein-protein Interaction in Drosophila Adult Heads by Tandem Affinity Purification (TAP)

PubMed Central

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

A genetic stochastic process model for genome-wide joint analysis of biomarker dynamics and disease susceptibility with longitudinal data.

PubMed

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.

The Genetics Underlying Natural Variation in the Biotic Interactions of Arabidopsis thaliana: The Challenges of Linking Evolutionary Genetics and Community Ecology.

PubMed

Roux, F; Bergelson, J

2016-01-01

In the context of global change, predicting the responses of plant communities in an ever-changing biotic environment calls for a multipronged approach at the interface of evolutionary genetics and community ecology. However, our understanding of the genetic basis of natural variation involved in mediating biotic interactions, and associated adaptive dynamics of focal plants in their natural communities, is still in its infancy. Here, we review the genetic and molecular bases of natural variation in the response to biotic interactions (viruses, bacteria, fungi, oomycetes, herbivores, and plants) in the model plant Arabidopsis thaliana as well as the adaptive value of these bases. Among the 60 identified genes are a number that encode nucleotide-binding site leucine-rich repeat (NBS-LRR)-type proteins, consistent with early examples of plant defense genes. However, recent studies have revealed an extensive diversity in the molecular mechanisms of defense. Many types of genetic variants associate with phenotypic variation in biotic interactions, even among the genes of large effect that tend to be identified. In general, we found that (i) balancing selection rather than directional selection explains the observed patterns of genetic diversity within A. thaliana and (ii) the cost/benefit tradeoffs of adaptive alleles can be strongly dependent on both genomic and environmental contexts. Finally, because A. thaliana rarely interacts with only one biotic partner in nature, we highlight the benefit of exploring diffuse biotic interactions rather than tightly associated host-enemy pairs. This challenge would help to improve our understanding of coevolutionary quantitative genetics within the context of realistic community complexity. © 2016 Elsevier Inc. All rights reserved.

Complex and unexpected dynamics in simple genetic regulatory networks

NASA Astrophysics Data System (ADS)

Borg, Yanika; Ullner, Ekkehard; Alagha, Afnan; Alsaedi, Ahmed; Nesbeth, Darren; Zaikin, Alexey

2014-03-01

One aim of synthetic biology is to construct increasingly complex genetic networks from interconnected simpler ones to address challenges in medicine and biotechnology. However, as systems increase in size and complexity, emergent properties lead to unexpected and complex dynamics due to nonlinear and nonequilibrium properties from component interactions. We focus on four different studies of biological systems which exhibit complex and unexpected dynamics. Using simple synthetic genetic networks, small and large populations of phase-coupled quorum sensing repressilators, Goodwin oscillators, and bistable switches, we review how coupled and stochastic components can result in clustering, chaos, noise-induced coherence and speed-dependent decision making. A system of repressilators exhibits oscillations, limit cycles, steady states or chaos depending on the nature and strength of the coupling mechanism. In large repressilator networks, rich dynamics can also be exhibited, such as clustering and chaos. In populations of Goodwin oscillators, noise can induce coherent oscillations. In bistable systems, the speed with which incoming external signals reach steady state can bias the network towards particular attractors. These studies showcase the range of dynamical behavior that simple synthetic genetic networks can exhibit. In addition, they demonstrate the ability of mathematical modeling to analyze nonlinearity and inhomogeneity within these systems.

Childhood and adolescent anxiety and depression: beyond heritability.

PubMed

Franić, Sanja; Middeldorp, Christel M; Dolan, Conor V; Ligthart, Lannie; Boomsma, Dorret I

2010-08-01

To review the methodology of behavior genetics studies addressing research questions that go beyond simple heritability estimation and illustrate these using representative research on childhood and adolescent anxiety and depression. The classic twin design and its extensions may be used to examine age and gender differences in the genetic determinants of complex traits and disorders, the role of genetic factors in explaining comorbidity, the interaction of genes and the environment, and the effect of social interaction among family members. An overview of the methods typically employed to address such questions is illustrated by a review of 34 recent studies on childhood anxiety and depression. The review provides relatively consistent evidence for small to negligible sex differences in the genetic etiology of childhood anxiety and depression, a substantial role of genetic factors in accounting for the temporal stability of these disorders, a partly genetic basis of the comorbidity between anxiety and depression, a possible role of the interaction between genotype and the environment in affecting liability to these disorders, a role of genotype-environment correlation, and a minor, if any, etiological role of sibling interaction. The results clearly demonstrate a role for genetic factors in the etiology and temporal stability of individual differences in childhood anxiety and depression. Clinical implications of the findings are discussed. 2010 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Application of network methods for understanding evolutionary dynamics in discrete habitats.

PubMed

Greenbaum, Gili; Fefferman, Nina H

2017-06-01

In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene-flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population-genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene-flow patterns. In the last decades, network theory - a branch of discrete mathematics concerned with complex interactions between discrete elements - has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population-genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology. © 2017 John Wiley & Sons Ltd.

Functional genomics platform for pooled screening and mammalian genetic interaction maps

PubMed Central

Kampmann, Martin; Bassik, Michael C.; Weissman, Jonathan S.

2014-01-01

Systematic genetic interaction maps in microorganisms are powerful tools for identifying functional relationships between genes and defining the function of uncharacterized genes. We have recently implemented this strategy in mammalian cells as a two-stage approach. First, genes of interest are robustly identified in a pooled genome-wide screen using complex shRNA libraries. Second, phenotypes for all pairwise combinations of hit genes are measured in a double-shRNA screen and used to construct a genetic interaction map. Our protocol allows for rapid pooled screening under various conditions without a requirement for robotics, in contrast to arrayed approaches. Each stage of the protocol can be implemented in ~2 weeks, with additional time for analysis and generation of reagents. We discuss considerations for screen design, and present complete experimental procedures as well as a full computational analysis suite for identification of hits in pooled screens and generation of genetic interaction maps. While the protocols outlined here were developed for our original shRNA-based approach, they can be applied more generally, including to CRISPR-based approaches. PMID:24992097

Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns.

PubMed

Lezon, Timothy R; Banavar, Jayanth R; Cieplak, Marek; Maritan, Amos; Fedoroff, Nina V

2006-12-12

We describe a method based on the principle of entropy maximization to identify the gene interaction network with the highest probability of giving rise to experimentally observed transcript profiles. In its simplest form, the method yields the pairwise gene interaction network, but it can also be extended to deduce higher-order interactions. Analysis of microarray data from genes in Saccharomyces cerevisiae chemostat cultures exhibiting energy metabolic oscillations identifies a gene interaction network that reflects the intracellular communication pathways that adjust cellular metabolic activity and cell division to the limiting nutrient conditions that trigger metabolic oscillations. The success of the present approach in extracting meaningful genetic connections suggests that the maximum entropy principle is a useful concept for understanding living systems, as it is for other complex, nonequilibrium systems.

"Touching Triton": Building Student Understanding of Complex Disease Risk.

PubMed

Loftin, Madelene; East, Kelly; Hott, Adam; Lamb, Neil

2016-01-01

Life science classrooms often emphasize the exception to the rule when it comes to teaching genetics, focusing heavily on rare single-gene and Mendelian traits. By contrast, the vast majority of human traits and diseases are caused by more complicated interactions between genetic and environmental factors. Research indicates that students have a deterministic view of genetics, generalize Mendelian inheritance patterns to all traits, and have unrealistic expectations of genetic technologies. The challenge lies in how to help students analyze complex disease risk with a lack of curriculum materials. Providing open access to both content resources and an engaging storyline can be achieved using a "serious game" model. "Touching Triton" was developed as a serious game in which students are asked to analyze data from a medical record, family history, and genomic report in order to develop an overall lifetime risk estimate of six common, complex diseases. Evaluation of student performance shows significant learning gains in key content areas along with a high level of engagement.

Studying Gene and Gene-Environment Effects of Uncommon and Common Variants on Continuous Traits: A Marker-Set Approach Using Gene-Trait Similarity Regression

PubMed Central

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

A review of vulnerability and risks for schizophrenia: Beyond the two hit hypothesis

PubMed Central

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

Interactions between Gut Microbiota, Host Genetics and Diet Modulate the Predisposition to Obesity and Metabolic Syndrome.

PubMed

Ussar, Siegfried; Griffin, Nicholas W; Bezy, Olivier; Fujisaka, Shiho; Vienberg, Sara; Softic, Samir; Deng, Luxue; Bry, Lynn; Gordon, Jeffrey I; Kahn, C Ronald

2015-09-01

Obesity, diabetes, and metabolic syndrome result from complex interactions between genetic and environmental factors, including the gut microbiota. To dissect these interactions, we utilized three commonly used inbred strains of mice-obesity/diabetes-prone C57Bl/6J mice, obesity/diabetes-resistant 129S1/SvImJ from Jackson Laboratory, and obesity-prone but diabetes-resistant 129S6/SvEvTac from Taconic-plus three derivative lines generated by breeding these strains in a new, common environment. Analysis of metabolic parameters and gut microbiota in all strains and their environmentally normalized derivatives revealed strong interactions between microbiota, diet, breeding site, and metabolic phenotype. Strain-dependent and strain-independent correlations were found between specific microbiota and phenotypes, some of which could be transferred to germ-free recipient animals by fecal transplantation. Environmental reprogramming of microbiota resulted in 129S6/SvEvTac becoming obesity resistant. Thus, development of obesity/metabolic syndrome is the result of interactions between gut microbiota, host genetics, and diet. In permissive genetic backgrounds, environmental reprograming of microbiota can ameliorate development of metabolic syndrome. Copyright © 2015 Elsevier Inc. All rights reserved.

Prioritisation of associations between protein domains and complex diseases using domain-domain interaction networks.

PubMed

Wang, W; Zhang, W; Jiang, R; Luan, Y

2010-05-01

It is of vital importance to find genetic variants that underlie human complex diseases and locate genes that are responsible for these diseases. Since proteins are typically composed of several structural domains, it is reasonable to assume that harmful genetic variants may alter structures of protein domains, affect functions of proteins and eventually cause disorders. With this understanding, the authors explore the possibility of recovering associations between protein domains and complex diseases. The authors define associations between protein domains and disease families on the basis of associations between non-synonymous single nucleotide polymorphisms (nsSNPs) and complex diseases, similarities between diseases, and relations between proteins and domains. Based on a domain-domain interaction network, the authors propose a 'guilt-by-proximity' principle to rank candidate domains according to their average distance to a set of seed domains in the domain-domain interaction network. The authors validate the method through large-scale cross-validation experiments on simulated linkage intervals, random controls and the whole genome. Results show that areas under receiver operating characteristic curves (AUC scores) can be as high as 77.90%, and the mean rank ratios can be as low as 21.82%. The authors further offer a freely accessible web interface for a genome-wide landscape of associations between domains and disease families.

Epistatic Effects Contribute to Variation in BMD in Fischer 344 × Lewis F2 Rats

PubMed Central

Koller, Daniel L; Liu, Lixiang; Alam, Imranul; Sun, Qiwei; Econs, Michael J; Foroud, Tatiana; Turner, Charles H

2008-01-01

To further delineate the factors underlying the complex genetic architecture of BMD in the rat model, a genome screen for epistatic interactions was conducted. Several significant interactions were identified, involving both previously identified and novel QTLs. Introduction The variation in several of the risk factors for osteoporotic fracture, including BMD, has been shown to be caused largely by genetic differences. However, the genetic architecture of BMD is complex in both humans and in model organisms. We have previously reported quantitative trait locus (QTL) results for BMD from a genome screen of 595 female F2 progeny of Fischer 344 and Lewis rats. These progeny also provide an excellent opportunity to search for epistatic effects, or interaction between genetic loci, that contribute to fracture risk. Materials and Methods Microsatellite marker data from a 20-cM genome screen was analyzed along with weight-adjusted BMD (DXA and pQCT) phenotypic data using the R/qtl software package. Genotype and phenotype data were permuted to determine a genome-wide significance threshold for the epistasis or interaction LOD score corresponding to an α level of 0.01. Results and Conclusions Novel loci on chromosomes 12 and 15 showed a strong epistatic effect on total BMD at the femoral midshaft by pQCT (LOD = 5.4). A previously reported QTL on chromosome 7 was found to interact with a novel locus on chromosome 20 to affect whole lumbar BMD by pQCT (LOD = 6.2). These results provide new information regarding the mode of action of previously identified rat QTLs, as well as identifying novel loci that act in combination with known QTLs or with other novel loci to contribute to the risk factors for osteoporotic fracture. PMID:17907919

Epistatic effects contribute to variation in BMD in Fischer 344 x Lewis F2 rats.

PubMed

Koller, Daniel L; Liu, Lixiang; Alam, Imranul; Sun, Qiwei; Econs, Michael J; Foroud, Tatiana; Turner, Charles H

2008-01-01

To further delineate the factors underlying the complex genetic architecture of BMD in the rat model, a genome screen for epistatic interactions was conducted. Several significant interactions were identified, involving both previously identified and novel QTLs. The variation in several of the risk factors for osteoporotic fracture, including BMD, has been shown to be caused largely by genetic differences. However, the genetic architecture of BMD is complex in both humans and in model organisms. We have previously reported quantitative trait locus (QTL) results for BMD from a genome screen of 595 female F(2) progeny of Fischer 344 and Lewis rats. These progeny also provide an excellent opportunity to search for epistatic effects, or interaction between genetic loci, that contribute to fracture risk. Microsatellite marker data from a 20-cM genome screen was analyzed along with weight-adjusted BMD (DXA and pQCT) phenotypic data using the R/qtl software package. Genotype and phenotype data were permuted to determine a genome-wide significance threshold for the epistasis or interaction LOD score corresponding to an alpha level of 0.01. Novel loci on chromosomes 12 and 15 showed a strong epistatic effect on total BMD at the femoral midshaft by pQCT (LOD = 5.4). A previously reported QTL on chromosome 7 was found to interact with a novel locus on chromosome 20 to affect whole lumbar BMD by pQCT (LOD = 6.2). These results provide new information regarding the mode of action of previously identified rat QTLs, as well as identifying novel loci that act in combination with known QTLs or with other novel loci to contribute to the risk factors for osteoporotic fracture.

Translating Mendelian and complex inheritance of Alzheimer's disease genes for predicting unique personal genome variants

PubMed Central

Regan, Kelly; Wang, Kanix; Doughty, Emily; Li, Haiquan; Li, Jianrong; Lee, Younghee; Kann, Maricel G

2012-01-01

Objective Although trait-associated genes identified as complex versus single-gene inheritance differ substantially in odds ratio, the authors nonetheless posit that their mechanistic concordance can reveal fundamental properties of the genetic architecture, allowing the automated interpretation of unique polymorphisms within a personal genome. Materials and methods An analytical method, SPADE-gen, spanning three biological scales was developed to demonstrate the mechanistic concordance between Mendelian and complex inheritance of Alzheimer's disease (AD) genes: biological functions (BP), protein interaction modeling, and protein domain implicated in the disease-associated polymorphism. Results Among Gene Ontology (GO) biological processes (BP) enriched at a false detection rate <5% in 15 AD genes of Mendelian inheritance (Online Mendelian Inheritance in Man) and independently in those of complex inheritance (25 host genes of intragenic AD single-nucleotide polymorphisms confirmed in genome-wide association studies), 16 overlapped (empirical p=0.007) and 45 were similar (empirical p<0.009; information theory). SPAN network modeling extended the canonical pathway of AD (KEGG) with 26 new protein interactions (empirical p<0.0001). Discussion The study prioritized new AD-associated biological mechanisms and focused the analysis on previously unreported interactions associated with the biological processes of polymorphisms that affect specific protein domains within characterized AD genes and their direct interactors using (1) concordant GO-BP and (2) domain interactions within STRING protein–protein interactions corresponding to the genomic location of the AD polymorphism (eg, EPHA1, APOE, and CD2AP). Conclusion These results are in line with unique-event polymorphism theory, indicating how disease-associated polymorphisms of Mendelian or complex inheritance relate genetically to those observed as ‘unique personal variants’. They also provide insight for identifying novel targets, for repositioning drugs, and for personal therapeutics. PMID:22319180

Insight into genome variability in the Fusarium Incarnatum-equiseti species complex through comparative analysis of secondary metabolic biosynthetic gene clusters

USDA-ARS?s Scientific Manuscript database

The genus Fusarium comprises 22 species complexes that together include approximately 300 phylogenetically distinct species. A major focus in Fusarium literature is to understand the genetic basis of niche specialization, secondary metabolites (SM) production, and host interactions in closely relate...

Genetic control of root growth: from genes to networks

PubMed Central

Slovak, Radka; Ogura, Takehiko; Satbhai, Santosh B.; Ristova, Daniela; Busch, Wolfgang

2016-01-01

Background Roots are essential organs for higher plants. They provide the plant with nutrients and water, anchor the plant in the soil, and can serve as energy storage organs. One remarkable feature of roots is that they are able to adjust their growth to changing environments. This adjustment is possible through mechanisms that modulate a diverse set of root traits such as growth rate, diameter, growth direction and lateral root formation. The basis of these traits and their modulation are at the cellular level, where a multitude of genes and gene networks precisely regulate development in time and space and tune it to environmental conditions. Scope This review first describes the root system and then presents fundamental work that has shed light on the basic regulatory principles of root growth and development. It then considers emerging complexities and how they have been addressed using systems-biology approaches, and then describes and argues for a systems-genetics approach. For reasons of simplicity and conciseness, this review is mostly limited to work from the model plant Arabidopsis thaliana, in which much of the research in root growth regulation at the molecular level has been conducted. Conclusions While forward genetic approaches have identified key regulators and genetic pathways, systems-biology approaches have been successful in shedding light on complex biological processes, for instance molecular mechanisms involving the quantitative interaction of several molecular components, or the interaction of large numbers of genes. However, there are significant limitations in many of these methods for capturing dynamic processes, as well as relating these processes to genotypic and phenotypic variation. The emerging field of systems genetics promises to overcome some of these limitations by linking genotypes to complex phenotypic and molecular data using approaches from different fields, such as genetics, genomics, systems biology and phenomics. PMID:26558398

Decoding the complex genetic causes of heart diseases using systems biology.

PubMed

Djordjevic, Djordje; Deshpande, Vinita; Szczesnik, Tomasz; Yang, Andrian; Humphreys, David T; Giannoulatou, Eleni; Ho, Joshua W K

2015-03-01

The pace of disease gene discovery is still much slower than expected, even with the use of cost-effective DNA sequencing and genotyping technologies. It is increasingly clear that many inherited heart diseases have a more complex polygenic aetiology than previously thought. Understanding the role of gene-gene interactions, epigenetics, and non-coding regulatory regions is becoming increasingly critical in predicting the functional consequences of genetic mutations identified by genome-wide association studies and whole-genome or exome sequencing. A systems biology approach is now being widely employed to systematically discover genes that are involved in heart diseases in humans or relevant animal models through bioinformatics. The overarching premise is that the integration of high-quality causal gene regulatory networks (GRNs), genomics, epigenomics, transcriptomics and other genome-wide data will greatly accelerate the discovery of the complex genetic causes of congenital and complex heart diseases. This review summarises state-of-the-art genomic and bioinformatics techniques that are used in accelerating the pace of disease gene discovery in heart diseases. Accompanying this review, we provide an interactive web-resource for systems biology analysis of mammalian heart development and diseases, CardiacCode ( http://CardiacCode.victorchang.edu.au/ ). CardiacCode features a dataset of over 700 pieces of manually curated genetic or molecular perturbation data, which enables the inference of a cardiac-specific GRN of 280 regulatory relationships between 33 regulator genes and 129 target genes. We believe this growing resource will fill an urgent unmet need to fully realise the true potential of predictive and personalised genomic medicine in tackling human heart disease.

Gene-Environment Interactions in Genome-Wide Association Studies: Current Approaches and New Directions

ERIC Educational Resources Information Center

Winham, Stacey J.; Biernacka, Joanna M.

2013-01-01

Background: Complex psychiatric traits have long been thought to be the result of a combination of genetic and environmental factors, and gene-environment interactions are thought to play a crucial role in behavioral phenotypes and the susceptibility and progression of psychiatric disorders. Candidate gene studies to investigate hypothesized…

LPHN3 and Attention-Deficit/Hyperactivity Disorder: Interaction with Maternal Stress during Pregnancy

ERIC Educational Resources Information Center

Choudhry, Zia; Sengupta, Sarojini M.; Grizenko, Natalie; Fortier, Marie-Eve; Thakur, Geeta A.; Bellingham, Johanne; Joober, Ridha

2012-01-01

Background: Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous behavioral disorder, complex both in etiology and clinical expression. Both genetic and environmental factors have been implicated, and it has been suggested that gene-environment interactions may play a pivotal role in the disorder. Recently, a significant association…

Antioxidant Defense Enzyme Genes and Asthma Susceptibility: Gender-Specific Effects and Heterogeneity in Gene-Gene Interactions between Pathogenetic Variants of the Disease

PubMed Central

Polonikov, Alexey V.; Ivanov, Vladimir P.; Bogomazov, Alexey D.; Freidin, Maxim B.; Illig, Thomas; Solodilova, Maria A.

2014-01-01

Oxidative stress resulting from an increased amount of reactive oxygen species and an imbalance between oxidants and antioxidants plays an important role in the pathogenesis of asthma. The present study tested the hypothesis that genetic susceptibility to allergic and nonallergic variants of asthma is determined by complex interactions between genes encoding antioxidant defense enzymes (ADE). We carried out a comprehensive analysis of the associations between adult asthma and 46 single nucleotide polymorphisms of 34 ADE genes and 12 other candidate genes of asthma in Russian population using set association analysis and multifactor dimensionality reduction approaches. We found for the first time epistatic interactions between ADE genes underlying asthma susceptibility and the genetic heterogeneity between allergic and nonallergic variants of the disease. We identified GSR (glutathione reductase) and PON2 (paraoxonase 2) as novel candidate genes for asthma susceptibility. We observed gender-specific effects of ADE genes on the risk of asthma. The results of the study demonstrate complexity and diversity of interactions between genes involved in oxidative stress underlying susceptibility to allergic and nonallergic asthma. PMID:24895604

Genetic interactions underlying hybrid male sterility in the Drosophila bipectinata species complex.

PubMed

Mishra, Paras Kumar; Singh, Bashisth Narayan

2006-06-01

Understanding genetic mechanisms underlying hybrid male sterility is one of the most challenging problems in evolutionary biology especially speciation. By using the interspecific hybridization method roles of Y chromosome, Major Hybrid Sterility (MHS) genes and cytoplasm in sterility of hybrid males have been investigated in a promising group, the Drosophila bipectinata species complex that consists of four closely related species: D. pseudoananassae, D. bipectinata, D. parabipectinata and D. malerkotliana. The interspecific introgression analyses show that neither cytoplasm nor MHS genes are involved but X-Y interactions may be playing major role in hybrid male sterility between D. pseudoananassae and the other three species. The results of interspecific introgression analyses also show considerable decrease in the number of males in the backcross offspring and all males have atrophied testes. There is a significant positive correlation between sex - ratio distortion and severity of sterility in backcross males. These findings provide evidence that D. pseudoananassae is remotely related with other three species of the D. bipectinata species complex.

Genome-wide mapping in a house mouse hybrid zone reveals hybrid sterility loci and Dobzhansky-Muller interactions.

PubMed

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.

Autism risk factors: genes, environment, and gene-environment interactions

PubMed Central

Chaste, Pauline; Leboyer, Marion

2012-01-01

The aim of this review is to summarize the key findings from genetic and epidemiological research, which show that autism is a complex disorder resulting from the combination of genetic and environmental factors. Remarkable advances in the knowledge of genetic causes of autism have resulted from the great efforts made in the field of genetics. The identification of specific alleles contributing to the autism spectrum has supplied important pieces for the autism puzzle. However, many questions remain unanswered, and new questions are raised by recent results. Moreover, given the amount of evidence supporting a significant contribution of environmental factors to autism risk, it is now clear that the search for environmental factors should be reinforced. One aspect of this search that has been neglected so far is the study of interactions between genes and environmental factors. PMID:23226953

Power of data mining methods to detect genetic associations and interactions.

PubMed

Molinaro, Annette M; Carriero, Nicholas; Bjornson, Robert; Hartge, Patricia; Rothman, Nathaniel; Chatterjee, Nilanjan

2011-01-01

Genetic association studies, thus far, have focused on the analysis of individual main effects of SNP markers. Nonetheless, there is a clear need for modeling epistasis or gene-gene interactions to better understand the biologic basis of existing associations. Tree-based methods have been widely studied as tools for building prediction models based on complex variable interactions. An understanding of the power of such methods for the discovery of genetic associations in the presence of complex interactions is of great importance. Here, we systematically evaluate the power of three leading algorithms: random forests (RF), Monte Carlo logic regression (MCLR), and multifactor dimensionality reduction (MDR). We use the algorithm-specific variable importance measures (VIMs) as statistics and employ permutation-based resampling to generate the null distribution and associated p values. The power of the three is assessed via simulation studies. Additionally, in a data analysis, we evaluate the associations between individual SNPs in pro-inflammatory and immunoregulatory genes and the risk of non-Hodgkin lymphoma. The power of RF is highest in all simulation models, that of MCLR is similar to RF in half, and that of MDR is consistently the lowest. Our study indicates that the power of RF VIMs is most reliable. However, in addition to tuning parameters, the power of RF is notably influenced by the type of variable (continuous vs. categorical) and the chosen VIM. Copyright © 2011 S. Karger AG, Basel.

Gene-Environment Interplay in Common Complex Diseases: Forging an Integrative Model—Recommendations From an NIH Workshop

PubMed Central

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

Computational intelligence in bioinformatics: SNP/haplotype data in genetic association study for common diseases.

PubMed

Kelemen, Arpad; Vasilakos, Athanasios V; Liang, Yulan

2009-09-01

Comprehensive evaluation of common genetic variations through association of single-nucleotide polymorphism (SNP) structure with common complex disease in the genome-wide scale is currently a hot area in human genome research due to the recent development of the Human Genome Project and HapMap Project. Computational science, which includes computational intelligence (CI), has recently become the third method of scientific enquiry besides theory and experimentation. There have been fast growing interests in developing and applying CI in disease mapping using SNP and haplotype data. Some of the recent studies have demonstrated the promise and importance of CI for common complex diseases in genomic association study using SNP/haplotype data, especially for tackling challenges, such as gene-gene and gene-environment interactions, and the notorious "curse of dimensionality" problem. This review provides coverage of recent developments of CI approaches for complex diseases in genetic association study with SNP/haplotype data.

Genetics Home Reference: Ewing sarcoma

MedlinePlus

... FLI-1, is associated with both TFIID and RNA polymerase II: interactions between two members of the ... EWS and hTAFII68, and subunits of TFIID and RNA polymerase II complexes. Mol Cell Biol. 1998 Mar; ...

Interactome of Obesity: Obesidome : Genetic Obesity, Stress Induced Obesity, Pathogenic Obesity Interaction.

PubMed

Geronikolou, Styliani A; Pavlopoulou, Athanasia; Cokkinos, Dennis; Chrousos, George

2017-01-01

Obesity is a chronic disease of increasing prevalence reaching epidemic proportions. Genetic defects as well as epigenetic effects contribute to the obesity phenotype. Investigating gene (e.g. MC4R defects)-environment (behavior, infectious agents, stress) interactions is a relative new field of great research interest. In this study, we have made an effort to create an interactome (henceforth referred to as "obesidome"), where extrinsic stressors response, intrinsic predisposition, immunity response to inflammation and autonomous nervous system implications are integrated. These pathways are presented in one interactome network for the first time. In our study, obesity-related genes/gene products were found to form a complex interactions network.

Phenotypic plasticity in female mate choice behavior is mediated by an interaction of direct and indirect genetic effects in Drosophila melanogaster.

PubMed

Filice, David C S; Long, Tristan A F

2017-05-01

Female mate choice is a complex decision-making process that involves many context-dependent factors. In Drosophila melanogaster , a model species for the study of sexual selection, indirect genetic effects (IGEs) of general social interactions can influence female mate choice behaviors, but the potential impacts of IGEs associated with mating experiences are poorly understood. Here, we examined whether the IGEs associated with a previous mating experience had an effect on subsequent female mate choice behaviors and quantified the degree of additive genetic variation associated with this effect. Females from 21 different genetic backgrounds were housed with males from one of two distinct genetic backgrounds for either a short (3 hr) or long (48 hr) exposure period and their subsequent mate choice behaviors were scored. We found that the genetic identity of a previous mate significantly influenced a female's subsequent interest in males and preference of males. Additionally, a hemiclonal analysis revealed significant additive genetic variation associated with experience-dependent mate choice behaviors, indicating a genotype-by-environment interaction for both of these parameters. We discuss the significance of these results with regard to the evolution of plasticity in female mate choice behaviors and the maintenance of variation in harmful male traits.

[Neuroanatomical, genetic and neurochemical aspects of infantile autism].

PubMed

Gerhant, Aneta; Olajossy, Marcin; Olajossy-Hilkesberger, Luiza

2013-01-01

Infantile autism is a neurodevelopmental disorder characterized by impairments in communication, reciprocal social interaction and restricted repetitive behaviors or interests. Although the cause of these disorders is not yet known, studies strongly suggest a genetic basis with a complex mode of inheritance. The etiopathogenetic processes of autism are extremely complex, which is reflected in the varying course and its symptomatology. Trajectories of brain development and volumes of its structures are aberrant in autistic patients. It is suggested that disturbances in sertotoninergic, gabaergic, glutaminergic, cholinergic and dopaminergic neurotransmission can be responsible for symptoms of autism as well as can disturb the development of the young brain. The objective of this article is to present the results of reasearch on neuroanatomical, neurochemical and genetic aspects of autism.

Phosphatidylcholine transfer protein interacts with thioesterase superfamily member 2 to attenuate insulin signaling.

PubMed

Ersoy, Baran A; Tarun, Akansha; D'Aquino, Katharine; Hancer, Nancy J; Ukomadu, Chinweike; White, Morris F; Michel, Thomas; Manning, Brendan D; Cohen, David E

2013-07-30

Phosphatidylcholine transfer protein (PC-TP) is a phospholipid-binding protein that is enriched in liver and that interacts with thioesterase superfamily member 2 (THEM2). Mice lacking either protein exhibit improved hepatic glucose homeostasis and are resistant to diet-induced diabetes. Insulin receptor substrate 2 (IRS2) and mammalian target of rapamycin complex 1 (mTORC1) are key effectors of insulin signaling, which is attenuated in diabetes. We found that PC-TP inhibited IRS2, as evidenced by insulin-independent IRS2 activation after knockdown, genetic ablation, or chemical inhibition of PC-TP. In addition, IRS2 was activated after knockdown of THEM2, providing support for a role for the interaction of PC-TP with THEM2 in suppressing insulin signaling. Additionally, we showed that PC-TP bound to tuberous sclerosis complex 2 (TSC2) and stabilized the components of the TSC1-TSC2 complex, which functions to inhibit mTORC1. Preventing phosphatidylcholine from binding to PC-TP disrupted interactions of PC-TP with THEM2 and TSC2, and disruption of the PC-TP-THEM2 complex was associated with increased activation of both IRS2 and mTORC1. In livers of mice with genetic ablation of PC-TP or that had been treated with a PC-TP inhibitor, steady-state amounts of IRS2 were increased, whereas those of TSC2 were decreased. These findings reveal a phospholipid-dependent mechanism that suppresses insulin signaling downstream of its receptor.

Phosphatidylcholine Transfer Protein Interacts with Thioesterase Superfamily Member 2 to Attenuate Insulin Signaling

PubMed Central

Ersoy, Baran A.; Tarun, Akansha; D’Aquino, Katharine; Hancer, Nancy J.; Ukomadu, Chinweike; White, Morris F.; Michel, Thomas; Manning, Brendan D.; Cohen, David E.

2014-01-01

Phosphatidylcholine transfer protein (PC-TP) is a phospholipid-binding protein that is enriched in liver and that interacts with thioesterase superfamily member 2 (THEM2). Mice lacking either protein exhibit improved hepatic glucose homeostasis and are resistant to diet-induced diabetes. Insulin receptor substrate 2 (IRS2) and mammalian target of rapamycin complex 1 (mTORC1) are key effectors of insulin signaling, which is attenuated in diabetes. We found that PC-TP inhibited IRS2, as evidenced by insulin-independent IRS2 activation following knockdown, genetic ablation, or chemical inhibition of PC-TP. In addition, IRS2 was activated after knockdown of THEM2, providing support for a role for the interaction of PC-TP with THEM2 in suppressing insulin signaling. Additionally, we showed that PC-TP bound to tuberous sclerosis complex 2 (TSC2) and stabilized the components of the TSC1-TSC2 complex, which functions to inhibit mTORC1. Preventing phosphatidylcholine from binding to PC-TP disrupted interactions of PC-TP with THEM2 and TSC2, and disruption of the PC-TP–THEM2 complex was associated with increased activation of both IRS2 and mTORC1. In livers of mice with genetic ablation of PC-TP or that had been treated with a PC-TP inhibitor, steady-state amounts of IRS2 were increased, whereas those of TSC2 were decreased. These findings reveal a phospholipid-dependent mechanism that suppresses insulin signaling downstream of its receptor. PMID:23901139

Including non-additive genetic effects in Bayesian methods for the prediction of genetic values based on genome-wide markers

PubMed Central

2011-01-01

Background Molecular marker information is a common source to draw inferences about the relationship between genetic and phenotypic variation. Genetic effects are often modelled as additively acting marker allele effects. The true mode of biological action can, of course, be different from this plain assumption. One possibility to better understand the genetic architecture of complex traits is to include intra-locus (dominance) and inter-locus (epistasis) interaction of alleles as well as the additive genetic effects when fitting a model to a trait. Several Bayesian MCMC approaches exist for the genome-wide estimation of genetic effects with high accuracy of genetic value prediction. Including pairwise interaction for thousands of loci would probably go beyond the scope of such a sampling algorithm because then millions of effects are to be estimated simultaneously leading to months of computation time. Alternative solving strategies are required when epistasis is studied. Methods We extended a fast Bayesian method (fBayesB), which was previously proposed for a purely additive model, to include non-additive effects. The fBayesB approach was used to estimate genetic effects on the basis of simulated datasets. Different scenarios were simulated to study the loss of accuracy of prediction, if epistatic effects were not simulated but modelled and vice versa. Results If 23 QTL were simulated to cause additive and dominance effects, both fBayesB and a conventional MCMC sampler BayesB yielded similar results in terms of accuracy of genetic value prediction and bias of variance component estimation based on a model including additive and dominance effects. Applying fBayesB to data with epistasis, accuracy could be improved by 5% when all pairwise interactions were modelled as well. The accuracy decreased more than 20% if genetic variation was spread over 230 QTL. In this scenario, accuracy based on modelling only additive and dominance effects was generally superior to that of the complex model including epistatic effects. Conclusions This simulation study showed that the fBayesB approach is convenient for genetic value prediction. Jointly estimating additive and non-additive effects (especially dominance) has reasonable impact on the accuracy of prediction and the proportion of genetic variation assigned to the additive genetic source. PMID:21867519

Genome-wide association study of bipolar disorder accounting for effect of body mass index identifies a new risk allele in TCF7L2.

PubMed

Winham, S J; Cuellar-Barboza, A B; Oliveros, A; McElroy, S L; Crow, S; Colby, C; Choi, D-S; Chauhan, M; Frye, M; Biernacka, J M

2014-09-01

Bipolar disorder (BD) is associated with higher body mass index (BMI) and increased metabolic comorbidity. Considering the associated phenotypic traits in genetic studies of complex diseases, either by adjusting for covariates or by investigating interactions between genetic variants and covariates, may help to uncover the missing heritability. However, obesity-related traits have not been incorporated in prior genome-wide analyses of BD as covariates or potential interacting factors. To investigate the genetic factors underlying BD while considering BMI, we conducted genome-wide analyses using data from the Genetic Association Information Network BD study. We analyzed 729,454 genotyped single-nucleotide polymorphism (SNP) markers on 388 European-American BD cases and 1020 healthy controls with available data for maximum BMI. We performed genome-wide association analyses of the genetic effects while accounting for the effect of maximum BMI, and also evaluated SNP-BMI interactions. A joint test of main and interaction effects demonstrated significant evidence of association at the genome-wide level with rs12772424 in an intron of TCF7L2 (P=2.85E-8). This SNP exhibited interaction effects, indicating that the bipolar susceptibility risk of this SNP is dependent on BMI. TCF7L2 codes for the transcription factor TCF/LF, part of the Wnt canonical pathway, and is one of the strongest genetic risk variants for type 2 diabetes (T2D). This is consistent with BD pathophysiology, as the Wnt pathway has crucial implications in neurodevelopment, neurogenesis and neuroplasticity, and is involved in the mechanisms of action of BD and depression treatments. We hypothesize that genetic risk for BD is BMI dependent, possibly related to common genetic risk with T2D.

The "periodic table" of the genetic code: A new way to look at the code and the decoding process.

PubMed

Komar, Anton A

2016-01-01

Henri Grosjean and Eric Westhof recently presented an information-rich, alternative view of the genetic code, which takes into account current knowledge of the decoding process, including the complex nature of interactions between mRNA, tRNA and rRNA that take place during protein synthesis on the ribosome, and it also better reflects the evolution of the code. The new asymmetrical circular genetic code has a number of advantages over the traditional codon table and the previous circular diagrams (with a symmetrical/clockwise arrangement of the U, C, A, G bases). Most importantly, all sequence co-variances can be visualized and explained based on the internal logic of the thermodynamics of codon-anticodon interactions.

Advances in asthma and allergy genetics in 2007.

PubMed

Vercelli, Donata

2008-08-01

This review discusses the main advances in the genetics of asthma and allergy published in the Journal in 2007. The association studies discussed herein addressed 3 main topics: the effect of the environment and gene-environment interactions on asthma/allergy susceptibility, the contribution of T(H)2 immunity gene variants to allergic inflammation, and the role of filaggrin mutations in atopic dermatitis and associated phenotypes. Other articles revealed novel, potentially important candidate genes or confirmed known ones. Collectively, the works published in 2007 reiterate that allergy and asthma are typical complex diseases; that is, they are disorders in which intricate interactions among environmental and genetic factors modify disease susceptibility by altering the fundamental structural and functional properties of target organs at critical developmental windows.

Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns

PubMed Central

Lezon, Timothy R.; Banavar, Jayanth R.; Cieplak, Marek; Maritan, Amos; Fedoroff, Nina V.

2006-01-01

We describe a method based on the principle of entropy maximization to identify the gene interaction network with the highest probability of giving rise to experimentally observed transcript profiles. In its simplest form, the method yields the pairwise gene interaction network, but it can also be extended to deduce higher-order interactions. Analysis of microarray data from genes in Saccharomyces cerevisiae chemostat cultures exhibiting energy metabolic oscillations identifies a gene interaction network that reflects the intracellular communication pathways that adjust cellular metabolic activity and cell division to the limiting nutrient conditions that trigger metabolic oscillations. The success of the present approach in extracting meaningful genetic connections suggests that the maximum entropy principle is a useful concept for understanding living systems, as it is for other complex, nonequilibrium systems. PMID:17138668

Evolutionary diversification of protein–protein interactions by interface add-ons

PubMed Central

Plach, Maximilian G.; Semmelmann, Florian; Busch, Florian; Busch, Markus; Heizinger, Leonhard; Wysocki, Vicki H.; Sterner, Reinhard

2017-01-01

Cells contain a multitude of protein complexes whose subunits interact with high specificity. However, the number of different protein folds and interface geometries found in nature is limited. This raises the question of how protein–protein interaction specificity is achieved on the structural level and how the formation of nonphysiological complexes is avoided. Here, we describe structural elements called interface add-ons that fulfill this function and elucidate their role for the diversification of protein–protein interactions during evolution. We identified interface add-ons in 10% of a representative set of bacterial, heteromeric protein complexes. The importance of interface add-ons for protein–protein interaction specificity is demonstrated by an exemplary experimental characterization of over 30 cognate and hybrid glutamine amidotransferase complexes in combination with comprehensive genetic profiling and protein design. Moreover, growth experiments showed that the lack of interface add-ons can lead to physiologically harmful cross-talk between essential biosynthetic pathways. In sum, our complementary in silico, in vitro, and in vivo analysis argues that interface add-ons are a practical and widespread evolutionary strategy to prevent the formation of nonphysiological complexes by specializing protein–protein interactions. PMID:28923934

Modeling the Normal and Neoplastic Cell Cycle with 'Realistic Boolean Genetic Networks': Their Application for Understanding Carcinogenesis and Assessing Therapeutic Strategies

NASA Technical Reports Server (NTRS)

Szallasi, Zoltan; Liang, Shoudan

2000-01-01

In this paper we show how Boolean genetic networks could be used to address complex problems in cancer biology. First, we describe a general strategy to generate Boolean genetic networks that incorporate all relevant biochemical and physiological parameters and cover all of their regulatory interactions in a deterministic manner. Second, we introduce 'realistic Boolean genetic networks' that produce time series measurements very similar to those detected in actual biological systems. Third, we outline a series of essential questions related to cancer biology and cancer therapy that could be addressed by the use of 'realistic Boolean genetic network' modeling.

Combined zebrafish-yeast chemical-genetic screens reveal gene-copper-nutrition interactions that modulate melanocyte pigmentation.

PubMed

Ishizaki, Hironori; Spitzer, Michaela; Wildenhain, Jan; Anastasaki, Corina; Zeng, Zhiqiang; Dolma, Sonam; Shaw, Michael; Madsen, Erik; Gitlin, Jonathan; Marais, Richard; Tyers, Mike; Patton, E Elizabeth

2010-01-01

Hypopigmentation is a feature of copper deficiency in humans, as caused by mutation of the copper (Cu(2+)) transporter ATP7A in Menkes disease, or an inability to absorb copper after gastric surgery. However, many causes of copper deficiency are unknown, and genetic polymorphisms might underlie sensitivity to suboptimal environmental copper conditions. Here, we combined phenotypic screens in zebrafish for compounds that affect copper metabolism with yeast chemical-genetic profiles to identify pathways that are sensitive to copper depletion. Yeast chemical-genetic interactions revealed that defects in intracellular trafficking pathways cause sensitivity to low-copper conditions; partial knockdown of the analogous Ap3s1 and Ap1s1 trafficking components in zebrafish sensitized developing melanocytes to hypopigmentation in low-copper environmental conditions. Because trafficking pathways are essential for copper loading into cuproproteins, our results suggest that hypomorphic alleles of trafficking components might underlie sensitivity to reduced-copper nutrient conditions. In addition, we used zebrafish-yeast screening to identify a novel target pathway in copper metabolism for the small-molecule MEK kinase inhibitor U0126. The zebrafish-yeast screening method combines the power of zebrafish as a disease model with facile genome-scale identification of chemical-genetic interactions in yeast to enable the discovery and dissection of complex multigenic interactions in disease-gene networks.

ATHENA: A knowledge-based hybrid backpropagation-grammatical evolution neural network algorithm for discovering epistasis among quantitative trait Loci

PubMed Central

2010-01-01

Background Growing interest and burgeoning technology for discovering genetic mechanisms that influence disease processes have ushered in a flood of genetic association studies over the last decade, yet little heritability in highly studied complex traits has been explained by genetic variation. Non-additive gene-gene interactions, which are not often explored, are thought to be one source of this "missing" heritability. Methods Stochastic methods employing evolutionary algorithms have demonstrated promise in being able to detect and model gene-gene and gene-environment interactions that influence human traits. Here we demonstrate modifications to a neural network algorithm in ATHENA (the Analysis Tool for Heritable and Environmental Network Associations) resulting in clear performance improvements for discovering gene-gene interactions that influence human traits. We employed an alternative tree-based crossover, backpropagation for locally fitting neural network weights, and incorporation of domain knowledge obtainable from publicly accessible biological databases for initializing the search for gene-gene interactions. We tested these modifications in silico using simulated datasets. Results We show that the alternative tree-based crossover modification resulted in a modest increase in the sensitivity of the ATHENA algorithm for discovering gene-gene interactions. The performance increase was highly statistically significant when backpropagation was used to locally fit NN weights. We also demonstrate that using domain knowledge to initialize the search for gene-gene interactions results in a large performance increase, especially when the search space is larger than the search coverage. Conclusions We show that a hybrid optimization procedure, alternative crossover strategies, and incorporation of domain knowledge from publicly available biological databases can result in marked increases in sensitivity and performance of the ATHENA algorithm for detecting and modelling gene-gene interactions that influence a complex human trait. PMID:20875103

The genetic interacting landscape of 63 candidate genes in Major Depressive Disorder: an explorative study.

PubMed

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.

Nonclassical Regulation of Transcription: Interchromosomal Interactions at the Malic enzyme Locus of Drosophila melanogaster

PubMed Central

Lum, Thomas E.; Merritt, Thomas J. S.

2011-01-01

Regulation of transcription can be a complex process in which many cis- and trans-interactions determine the final pattern of expression. Among these interactions are trans-interactions mediated by the pairing of homologous chromosomes. These trans-effects are wide ranging, affecting gene regulation in many species and creating complex possibilities in gene regulation. Here we describe a novel case of trans-interaction between alleles of the Malic enzyme (Men) locus in Drosophila melanogaster that results in allele-specific, non-additive gene expression. Using both empirical biochemical and predictive bioinformatic approaches, we show that the regulatory elements of one allele are capable of interacting in trans with, and modifying the expression of, the second allele. Furthermore, we show that nonlocal factors—different genetic backgrounds—are capable of significant interactions with individual Men alleles, suggesting that these trans-effects can be modified by both locally and distantly acting elements. In sum, these results emphasize the complexity of gene regulation and the need to understand both small- and large-scale interactions as more complete models of the role of trans-interactions in gene regulation are developed. PMID:21900270

Bell miner provisioning calls are more similar among relatives and are used by helpers at the nest to bias their effort towards kin

PubMed Central

McDonald, Paul G.; Wright, Jonathan

2011-01-01

Kin selection predicts that helpers in cooperative systems should preferentially aid relatives to maximize fitness. In family-based groups, this can be accomplished simply by assisting all group members. In more complex societies, where large numbers of kin and non-kin regularly interact, more sophisticated kin-recognition mechanisms are needed. Bell miners (Manorina melanophrys) are just such a system where individuals regularly interact with both kin and non-kin within large colonies. Despite this complexity, individual helpers of both sexes facultatively work harder when provisioning the young of closer genetic relatedness. We investigated the mechanism by which such adaptive discrimination occurs by assessing genetic kinship influences on the structure of more than 1900 provisioning vocalizations of 185 miners. These ‘mew’ calls showed a significant, positive linear increase in call similarity with increasing genetic relatedness, most especially in comparisons between male helpers and the breeding male. Furthermore, individual helping effort was more heavily influenced by call similarity to breeding males than to genetic relatedness, as predicted if call similarity is indeed the rule-of-thumb used to discriminate kin in this system. Individual mew call structure appeared to be inflexible and innate, providing an effective mechanism by which helpers can assess their relatedness to any individual. This provides, to our knowledge, the first example of a mechanism for fine-scale kin discrimination in a complex avian society. PMID:21450738

Determination of nonlinear genetic architecture using compressed sensing.

PubMed

Ho, Chiu Man; Hsu, Stephen D H

2015-01-01

One of the fundamental problems of modern genomics is to extract the genetic architecture of a complex trait from a data set of individual genotypes and trait values. Establishing this important connection between genotype and phenotype is complicated by the large number of candidate genes, the potentially large number of causal loci, and the likely presence of some nonlinear interactions between different genes. Compressed Sensing methods obtain solutions to under-constrained systems of linear equations. These methods can be applied to the problem of determining the best model relating genotype to phenotype, and generally deliver better performance than simply regressing the phenotype against each genetic variant, one at a time. We introduce a Compressed Sensing method that can reconstruct nonlinear genetic models (i.e., including epistasis, or gene-gene interactions) from phenotype-genotype (GWAS) data. Our method uses L1-penalized regression applied to nonlinear functions of the sensing matrix. The computational and data resource requirements for our method are similar to those necessary for reconstruction of linear genetic models (or identification of gene-trait associations), assuming a condition of generalized sparsity, which limits the total number of gene-gene interactions. An example of a sparse nonlinear model is one in which a typical locus interacts with several or even many others, but only a small subset of all possible interactions exist. It seems plausible that most genetic architectures fall in this category. We give theoretical arguments suggesting that the method is nearly optimal in performance, and demonstrate its effectiveness on broad classes of nonlinear genetic models using simulated human genomes and the small amount of currently available real data. A phase transition (i.e., dramatic and qualitative change) in the behavior of the algorithm indicates when sufficient data is available for its successful application. Our results indicate that predictive models for many complex traits, including a variety of human disease susceptibilities (e.g., with additive heritability h (2)∼0.5), can be extracted from data sets comprised of n ⋆∼100s individuals, where s is the number of distinct causal variants influencing the trait. For example, given a trait controlled by ∼10 k loci, roughly a million individuals would be sufficient for application of the method.

Visual analysis of geocoded twin data puts nature and nurture on the map.

PubMed

Davis, O S P; Haworth, C M A; Lewis, C M; Plomin, R

2012-09-01

Twin studies allow us to estimate the relative contributions of nature and nurture to human phenotypes by comparing the resemblance of identical and fraternal twins. Variation in complex traits is a balance of genetic and environmental influences; these influences are typically estimated at a population level. However, what if the balance of nature and nurture varies depending on where we grow up? Here we use statistical and visual analysis of geocoded data from over 6700 families to show that genetic and environmental contributions to 45 childhood cognitive and behavioral phenotypes vary geographically in the United Kingdom. This has implications for detecting environmental exposures that may interact with the genetic influences on complex traits, and for the statistical power of samples recruited for genetic association studies. More broadly, our experience demonstrates the potential for collaborative exploratory visualization to act as a lingua franca for large-scale interdisciplinary research.

Comparing GWAS Results of Complex Traits Using Full Genetic Model and Additive Models for Revealing Genetic Architecture

PubMed Central

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

Growth and Development of Dentofacial Complex influenced by Genetic and Environmental Factors using Monozygotic Twins.

PubMed

Manjusha, K K; Jyothindrakumar, K; Nishad, A; Manoj, K Madhav

2017-09-01

The purpose of this study was to determine the possible effects of genetic and environmental factors on dentofacial complex using monozygotic twins. The study sample was made of 21 pairs of monozygotic twins (14 female pairs and seven male pairs) between 10 and 25 years. Pretreatment lateral cephalo-grams were used which were traced and digitized, and various landmarks to determine the anteroposterior and vertical proportions were marked. Samples were divided into two groups. The correlation between groups was found by calculating Pearson's product moment correlation coefficients. The range of the correlation coefficient was from 0.705 to 0.952. Gonial angle showed the highest correlation coefficient (0.952), while saddle angle showed the lowest correlation coefficient (0.705). The growth and development of craniofacial complex is under mutifactorial control. However, genetic influences do tend to play a dominant role. By studying identical twins, we can study about the interaction of the environment with the genes and how it affects the growth and development of the body in general and dentofacial complex in particular. By utilizing twin studies, we can identify whether a particular trait, disease, or disorder is influenced more strongly by genetics or by the environment. Success of orthodontic treatment depends on a proper diagnosis of the problem including its etiological factors. Genetic studies let the orthodontists to understand the effects of genetic and environmental factors in the growth and development of dentofacial complex better and allows to prevent or treat malocclusions and skeletal anomalies in better ways.

Genetic architectures of seropositive and seronegative rheumatic diseases.

PubMed

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.

Kernel-Based Measure of Variable Importance for Genetic Association Studies.

PubMed

Gallego, Vicente; Luz Calle, M; Oller, Ramon

2017-06-17

The identification of genetic variants that are associated with disease risk is an important goal of genetic association studies. Standard approaches perform univariate analysis where each genetic variant, usually Single Nucleotide Polymorphisms (SNPs), is tested for association with disease status. Though many genetic variants have been identified and validated so far using this univariate approach, for most complex diseases a large part of their genetic component is still unknown, the so called missing heritability. We propose a Kernel-based measure of variable importance (KVI) that provides the contribution of a SNP, or a group of SNPs, to the joint genetic effect of a set of genetic variants. KVI can be used for ranking genetic markers individually, sets of markers that form blocks of linkage disequilibrium or sets of genetic variants that lie in a gene or a genetic pathway. We prove that, unlike the univariate analysis, KVI captures the relationship with other genetic variants in the analysis, even when measured at the individual level for each genetic variable separately. This is specially relevant and powerful for detecting genetic interactions. We illustrate the results with data from an Alzheimer's disease study and show through simulations that the rankings based on KVI improve those rankings based on two measures of importance provided by the Random Forest. We also prove with a simulation study that KVI is very powerful for detecting genetic interactions.

Genome-wide mapping in a house mouse hybrid zone reveals hybrid sterility loci and Dobzhansky-Muller interactions

PubMed Central

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

Genetic variation in Toll-like receptors and disease susceptibility.

PubMed

Netea, Mihai G; Wijmenga, Cisca; O'Neill, Luke A J

2012-05-18

Toll-like receptors (TLRs) are key initiators of the innate immune response and promote adaptive immunity. Much has been learned about the role of TLRs in human immunity from studies linking TLR genetic variation with disease. First, monogenic disorders associated with complete deficiency in certain TLR pathways, such as MyD88-IRAK4 or TLR3-Unc93b-TRIF-TRAF3, have demonstrated the specific roles of these pathways in host defense against pyogenic bacteria and herpesviruses, respectively. Second, common polymorphisms in genes encoding several TLRs and associated genes have been associated with both infectious and autoimmune diseases. The study of genetic variation in TLRs in various populations combined with information on infection has demonstrated complex interaction between genetic variation in TLRs and environmental factors. This interaction explains the differences in the effect of TLR polymorphisms on susceptibility to infection and autoimmune disease in various populations.

Are Interactions between cis-Regulatory Variants Evidence for Biological Epistasis or Statistical Artifacts?

PubMed

Fish, Alexandra E; Capra, John A; Bush, William S

2016-10-06

The importance of epistasis-or statistical interactions between genetic variants-to the development of complex disease in humans has been controversial. Genome-wide association studies of statistical interactions influencing human traits have recently become computationally feasible and have identified many putative interactions. However, statistical models used to detect interactions can be confounded, which makes it difficult to be certain that observed statistical interactions are evidence for true molecular epistasis. In this study, we investigate whether there is evidence for epistatic interactions between genetic variants within the cis-regulatory region that influence gene expression after accounting for technical, statistical, and biological confounding factors. We identified 1,119 (FDR = 5%) interactions that appear to regulate gene expression in human lymphoblastoid cell lines, a tightly controlled, largely genetically determined phenotype. Many of these interactions replicated in an independent dataset (90 of 803 tested, Bonferroni threshold). We then performed an exhaustive analysis of both known and novel confounders, including ceiling/floor effects, missing genotype combinations, haplotype effects, single variants tagged through linkage disequilibrium, and population stratification. Every interaction could be explained by at least one of these confounders, and replication in independent datasets did not protect against some confounders. Assuming that the confounding factors provide a more parsimonious explanation for each interaction, we find it unlikely that cis-regulatory interactions contribute strongly to human gene expression, which calls into question the relevance of cis-regulatory interactions for other human phenotypes. We additionally propose several best practices for epistasis testing to protect future studies from confounding. Copyright © 2016 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Root Systems Biology: Integrative Modeling across Scales, from Gene Regulatory Networks to the Rhizosphere1

PubMed Central

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

Leucine-Rich Repeat Kinase 2 interacts with Parkin, DJ-1 and PINK-1 in a Drosophila melanogaster model of Parkinson's disease.

PubMed

Venderova, Katerina; Kabbach, Ghassan; Abdel-Messih, Elizabeth; Zhang, Yi; Parks, Robin J; Imai, Yuzuru; Gehrke, Stephan; Ngsee, Johnny; Lavoie, Matthew J; Slack, Ruth S; Rao, Yong; Zhang, Zhuohua; Lu, Bingwei; Haque, M Emdadul; Park, David S

2009-11-15

Mutations in the LRRK2 gene are the most common genetic cause of familial Parkinson's disease (PD). However, its physiological and pathological functions are unknown. Therefore, we generated several independent Drosophila lines carrying WT or mutant human LRRK2 (mutations in kinase, COR or LRR domains, resp.). Ectopic expression of WT or mutant LRRK2 in dopaminergic neurons caused their significant loss accompanied by complex age-dependent changes in locomotor activity. Overall, the ubiquitous expression of LRRK2 increased lifespan and fertility of the flies. However, these flies were more sensitive to rotenone. LRRK2 expression in the eye exacerbated retinal degeneration. Importantly, in double transgenic flies, various indices of the eye and dopaminergic survival were modified in a complex fashion by a concomitant expression of PINK1, DJ-1 or Parkin. This evidence suggests a genetic interaction between these PD-relevant genes.

Genetic Basis of Haloperidol Resistance in Saccharomyces cerevisiae Is Complex and Dose Dependent

PubMed Central

Wang, Xin; Kruglyak, Leonid

2014-01-01

The genetic basis of most heritable traits is complex. Inhibitory compounds and their effects in model organisms have been used in many studies to gain insights into the genetic architecture underlying quantitative traits. However, the differential effect of compound concentration has not been studied in detail. In this study, we used a large segregant panel from a cross between two genetically divergent yeast strains, BY4724 (a laboratory strain) and RM11_1a (a vineyard strain), to study the genetic basis of variation in response to different doses of a drug. Linkage analysis revealed that the genetic architecture of resistance to the small-molecule therapeutic drug haloperidol is highly dose-dependent. Some of the loci identified had effects only at low doses of haloperidol, while other loci had effects primarily at higher concentrations of the drug. We show that a major QTL affecting resistance across all concentrations of haloperidol is caused by polymorphisms in SWH1, a homologue of human oxysterol binding protein. We identify a complex set of interactions among the alleles of the genes SWH1, MKT1, and IRA2 that are most pronounced at a haloperidol dose of 200 µM and are only observed when the remainder of the genome is of the RM background. Our results provide further insight into the genetic basis of drug resistance. PMID:25521586

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm.

PubMed

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene x gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene x gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms.

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm

PubMed Central

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene × gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene × gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms. PMID:18466570

Identification of susceptible genes for complex chronic diseases based on disease risk functional SNPs and interaction networks.

PubMed

Li, Wan; Zhu, Lina; Huang, Hao; He, Yuehan; Lv, Junjie; Li, Weimin; Chen, Lina; He, Weiming

2017-10-01

Complex chronic diseases are caused by the effects of genetic and environmental factors. Single nucleotide polymorphisms (SNPs), one common type of genetic variations, played vital roles in diseases. We hypothesized that disease risk functional SNPs in coding regions and protein interaction network modules were more likely to contribute to the identification of disease susceptible genes for complex chronic diseases. This could help to further reveal the pathogenesis of complex chronic diseases. Disease risk SNPs were first recognized from public SNP data for coronary heart disease (CHD), hypertension (HT) and type 2 diabetes (T2D). SNPs in coding regions that were classified into nonsense and missense by integrating several SNP functional annotation databases were treated as functional SNPs. Then, regions significantly associated with each disease were screened using random permutations for disease risk functional SNPs. Corresponding to these regions, 155, 169 and 173 potential disease susceptible genes were identified for CHD, HT and T2D, respectively. A disease-related gene product interaction network in environmental context was constructed for interacting gene products of both disease genes and potential disease susceptible genes for these diseases. After functional enrichment analysis for disease associated modules, 5 CHD susceptible genes, 7 HT susceptible genes and 3 T2D susceptible genes were finally identified, some of which had pleiotropic effects. Most of these genes were verified to be related to these diseases in literature. This was similar for disease genes identified from another method proposed by Lee et al. from a different aspect. This research could provide novel perspectives for diagnosis and treatment of complex chronic diseases and susceptible genes identification for other diseases. Copyright © 2017 Elsevier Inc. All rights reserved.

Epigenetics in Developmental Disorder: ADHD and Endophenotypes

PubMed Central

Archer, Trevor; Oscar-Berman, Marlene; Blum, Kenneth

2011-01-01

Heterogeneity in attention-deficit/hyperactivity disorder (ADHD), with complex interactive operations of genetic and environmental factors, is expressed in a variety of disorder manifestations: severity, co-morbidities of symptoms, and the effects of genes on phenotypes. Neurodevelopmental influences of genomic imprinting have set the stage for the structural-physiological variations that modulate the cognitive, affective, and pathophysiological domains of ADHD. The relative contributions of genetic and environmental factors provide rapidly proliferating insights into the developmental trajectory of the condition, both structurally and functionally. Parent-of-origin effects seem to support the notion that genetic risks for disease process debut often interact with the social environment, i.e., the parental environment in infants and young children. The notion of endophenotypes, markers of an underlying liability to the disorder, may facilitate detection of genetic risks relative to a complex clinical disorder. Simple genetic association has proven insufficient to explain the spectrum of ADHD. At a primary level of analysis, the consideration of epigenetic regulation of brain signalling mechanisms, dopamine, serotonin, and noradrenaline is examined. Neurotrophic factors that participate in the neurogenesis, survival, and functional maintenance of brain systems, are involved in neuroplasticity alterations underlying brain disorders, and are implicated in the genetic predisposition to ADHD, but not obviously, nor in a simple or straightforward fashion. In the context of intervention, genetic linkage studies of ADHD pharmacological intervention have demonstrated that associations have fitted the “drug response phenotype,” rather than the disorder diagnosis. Despite conflicting evidence for the existence, or not, of genetic associations between disorder diagnosis and genes regulating the structure and function of neurotransmitters and brain-derived neurotrophic factor (BDNF), associations between symptoms-profiles endophenotypes and single nucleotide polymorphisms appear reassuring. PMID:22224195

Individual Differences in Pain: Understanding the Mosaic that Makes Pain Personal

PubMed Central

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

General and craniofacial development are complex adaptive processes influenced by diversity.

PubMed

Brook, A H; O'Donnell, M Brook; Hone, A; Hart, E; Hughes, T E; Smith, R N; Townsend, G C

2014-06-01

Complex systems are present in such diverse areas as social systems, economies, ecosystems and biology and, therefore, are highly relevant to dental research, education and practice. A Complex Adaptive System in biological development is a dynamic process in which, from interacting components at a lower level, higher level phenomena and structures emerge. Diversity makes substantial contributions to the performance of complex adaptive systems. It enhances the robustness of the process, allowing multiple responses to external stimuli as well as internal changes. From diversity comes variation in outcome and the possibility of major change; outliers in the distribution enhance the tipping points. The development of the dentition is a valuable, accessible model with extensive and reliable databases for investigating the role of complex adaptive systems in craniofacial and general development. The general characteristics of such systems are seen during tooth development: self-organization; bottom-up emergence; multitasking; self-adaptation; variation; tipping points; critical phases; and robustness. Dental findings are compatible with the Random Network Model, the Threshold Model and also with the Scale Free Network Model which has a Power Law distribution. In addition, dental development shows the characteristics of Modularity and Clustering to form Hierarchical Networks. The interactions between the genes (nodes) demonstrate Small World phenomena, Subgraph Motifs and Gene Regulatory Networks. Genetic mechanisms are involved in the creation and evolution of variation during development. The genetic factors interact with epigenetic and environmental factors at the molecular level and form complex networks within the cells. From these interactions emerge the higher level tissues, tooth germs and mineralized teeth. Approaching development in this way allows investigation of why there can be variations in phenotypes from identical genotypes; the phenotype is the outcome of perturbations in the cellular systems and networks, as well as of the genotype. Understanding and applying complexity theory will bring about substantial advances not only in dental research and education but also in the organization and delivery of oral health care. © 2014 Australian Dental Association.

Accounting for Population Structure in Gene-by-Environment Interactions in Genome-Wide Association Studies Using Mixed Models.

PubMed

Sul, Jae Hoon; Bilow, Michael; Yang, Wen-Yun; Kostem, Emrah; Furlotte, Nick; He, Dan; Eskin, Eleazar

2016-03-01

Although genome-wide association studies (GWASs) have discovered numerous novel genetic variants associated with many complex traits and diseases, those genetic variants typically explain only a small fraction of phenotypic variance. Factors that account for phenotypic variance include environmental factors and gene-by-environment interactions (GEIs). Recently, several studies have conducted genome-wide gene-by-environment association analyses and demonstrated important roles of GEIs in complex traits. One of the main challenges in these association studies is to control effects of population structure that may cause spurious associations. Many studies have analyzed how population structure influences statistics of genetic variants and developed several statistical approaches to correct for population structure. However, the impact of population structure on GEI statistics in GWASs has not been extensively studied and nor have there been methods designed to correct for population structure on GEI statistics. In this paper, we show both analytically and empirically that population structure may cause spurious GEIs and use both simulation and two GWAS datasets to support our finding. We propose a statistical approach based on mixed models to account for population structure on GEI statistics. We find that our approach effectively controls population structure on statistics for GEIs as well as for genetic variants.

Proteomics-Based Analysis of Protein Complexes in Pluripotent Stem Cells and Cancer Biology.

PubMed

Sudhir, Putty-Reddy; Chen, Chung-Hsuan

2016-03-22

A protein complex consists of two or more proteins that are linked together through protein-protein interactions. The proteins show stable/transient and direct/indirect interactions within the protein complex or between the protein complexes. Protein complexes are involved in regulation of most of the cellular processes and molecular functions. The delineation of protein complexes is important to expand our knowledge on proteins functional roles in physiological and pathological conditions. The genetic yeast-2-hybrid method has been extensively used to characterize protein-protein interactions. Alternatively, a biochemical-based affinity purification coupled with mass spectrometry (AP-MS) approach has been widely used to characterize the protein complexes. In the AP-MS method, a protein complex of a target protein of interest is purified using a specific antibody or an affinity tag (e.g., DYKDDDDK peptide (FLAG) and polyhistidine (His)) and is subsequently analyzed by means of MS. Tandem affinity purification, a two-step purification system, coupled with MS has been widely used mainly to reduce the contaminants. We review here a general principle for AP-MS-based characterization of protein complexes and we explore several protein complexes identified in pluripotent stem cell biology and cancer biology as examples.

Proteomics-Based Analysis of Protein Complexes in Pluripotent Stem Cells and Cancer Biology

PubMed Central

Sudhir, Putty-Reddy; Chen, Chung-Hsuan

2016-01-01

A protein complex consists of two or more proteins that are linked together through protein–protein interactions. The proteins show stable/transient and direct/indirect interactions within the protein complex or between the protein complexes. Protein complexes are involved in regulation of most of the cellular processes and molecular functions. The delineation of protein complexes is important to expand our knowledge on proteins functional roles in physiological and pathological conditions. The genetic yeast-2-hybrid method has been extensively used to characterize protein-protein interactions. Alternatively, a biochemical-based affinity purification coupled with mass spectrometry (AP-MS) approach has been widely used to characterize the protein complexes. In the AP-MS method, a protein complex of a target protein of interest is purified using a specific antibody or an affinity tag (e.g., DYKDDDDK peptide (FLAG) and polyhistidine (His)) and is subsequently analyzed by means of MS. Tandem affinity purification, a two-step purification system, coupled with MS has been widely used mainly to reduce the contaminants. We review here a general principle for AP-MS-based characterization of protein complexes and we explore several protein complexes identified in pluripotent stem cell biology and cancer biology as examples. PMID:27011181

Oxidative stress/damage induces multimerization and interaction of Fanconi anemia proteins.

PubMed

Park, Su-Jung; Ciccone, Samantha L M; Beck, Brian D; Hwang, Byounghoon; Freie, Brian; Clapp, D Wade; Lee, Suk-Hee

2004-07-16

Fanconi anemia (FANC) is a heterogeneous genetic disorder characterized by a hypersensitivity to DNA-damaging agents, chromosomal instability, and defective DNA repair. Eight FANC genes have been identified so far, and five of them (FANCA, -C, -E, -F, and -G) assemble in a multinuclear complex and function at least in part in a complex to activate FANCD2 by monoubiquitination. Here we show that FANCA and FANCG are redox-sensitive proteins that are multimerized and/or form a nuclear complex in response to oxidative stress/damage. Both FANCA and FANCG proteins exist as monomers under non-oxidizing conditions, whereas they become multimers following H2O2 treatment. Treatment of cells with oxidizing agent not only triggers the multimeric complex of FANCA and FANCG in vivo but also induces the interaction between FANCA and FANCG. N-Ethylmaleimide treatment abolishes multimerization and interaction of FANCA and FANCG in vitro. Taken together, our results lead us to conclude that FANCA and FANCG uniquely respond to oxidative damage by forming complex(es) via intermolecular disulfide linkage(s), which may be crucial in forming such complexes and in determining their function.

[Genetics of sudden unexplained death].

PubMed

Campuzano, Oscar; Allegue, Catarina; Brugada, Ramon

2014-03-20

Sudden unexplained death is defined by death without a conclusive diagnosis after autopsy and it is responsible for a large percentage of sudden deaths. The progressive interaction between genetics and forensics in post-mortem studies has identified inheritable alterations responsible for pathologies associated with arrhythmic sudden death. The genetic diagnosis of the deceased enables the undertaking of preventive measures in family members, many of them asymptomatic but at risk. The implications of this multidisciplinary translational medical approach are complex, requiring the dedication of a specialized team. Copyright © 2013 Elsevier España, S.L. All rights reserved.

Phenotypic plasticity in a complex world: interactive effects of food and temperature on fitness components of a seed beetle.

PubMed

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.

Genome-wide search followed by replication reveals genetic interaction of CD80 and ALOX5AP associated with systemic lupus erythematosus in Asian populations.

PubMed

Zhang, Yan; Yang, Jing; Zhang, Jing; Sun, Liangdan; Hirankarn, Nattiya; Pan, Hai-Feng; Lau, Chak Sing; Chan, Tak Mao; Lee, Tsz Leung; Leung, Alexander Moon Ho; Mok, Chi Chiu; Zhang, Lu; Wang, Yongfei; Shen, Jiangshan Jane; Wong, Sik Nin; Lee, Ka Wing; Ho, Marco Hok Kung; Lee, Pamela Pui Wah; Chung, Brian Hon-Yin; Chong, Chun Yin; Wong, Raymond Woon Sing; Mok, Mo Yin; Wong, Wilfred Hing Sang; Tong, Kwok Lung; Tse, Niko Kei Chiu; Li, Xiang-Pei; Avihingsanon, Yingyos; Rianthavorn, Pornpimol; Deekajorndej, Thavatchai; Suphapeetiporn, Kanya; Shotelersuk, Vorasuk; Ying, Shirley King Yee; Fung, Samuel Ka Shun; Lai, Wai Ming; Wong, Chun-Ming; Ng, Irene Oi Lin; Garcia-Barcelo, Maria-Merce; Cherny, Stacey S; Cui, Yong; Sham, Pak Chung; Yang, Sen; Ye, Dong-Qing; Zhang, Xue-Jun; Lau, Yu Lung; Yang, Wanling

2016-05-01

Genetic interaction has been considered as a hallmark of the genetic architecture of systemic lupus erythematosus (SLE). Based on two independent genome-wide association studies (GWAS) on Chinese populations, we performed a genome-wide search for genetic interactions contributing to SLE susceptibility. The study involved a total of 1 659 cases and 3 398 controls in the discovery stage and 2 612 cases and 3 441 controls in three cohorts for replication. Logistic regression and multifactor dimensionality reduction were used to search for genetic interaction. Interaction of CD80 (rs2222631) and ALOX5AP (rs12876893) was found to be significantly associated with SLE (OR_int=1.16, P_int_all=7.7E-04 at false discovery rate<0.05). Single nuclear polymorphism rs2222631 was found associated with SLE with genome-wide significance (P_all=4.5E-08, OR=0.86) and is independent of rs6804441 in CD80, whose association was reported previously. Significant correlation was observed between expression of these two genes in healthy controls and SLE cases, together with differential expression of these genes between cases and controls, observed from individuals from the Hong Kong cohort. Genetic interactions between BLK (rs13277113) and DDX6 (rs4639966), and between TNFSF4 (rs844648) and PXK (rs6445975) were also observed in both GWAS data sets. Our study represents the first genome-wide evaluation of epistasis interactions on SLE and the findings suggest interactions and independent variants may help partially explain missing heritability for complex diseases. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

The evolution of phenotypic integration: How directional selection reshapes covariation in mice

PubMed Central

Penna, Anna; Melo, Diogo; Bernardi, Sandra; Oyarzabal, Maria Inés; Marroig, Gabriel

2017-01-01

Abstract Variation is the basis for evolution, and understanding how variation can evolve is a central question in biology. In complex phenotypes, covariation plays an even more important role, as genetic associations between traits can bias and alter evolutionary change. Covariation can be shaped by complex interactions between loci, and this genetic architecture can also change during evolution. In this article, we analyzed mouse lines experimentally selected for changes in size to address the question of how multivariate covariation changes under directional selection, as well as to identify the consequences of these changes to evolution. Selected lines showed a clear restructuring of covariation in their cranium and, instead of depleting their size variation, these lines increased their magnitude of integration and the proportion of variation associated with the direction of selection. This result is compatible with recent theoretical works on the evolution of covariation that take the complexities of genetic architecture into account. This result also contradicts the traditional view of the effects of selection on available covariation and suggests a much more complex view of how populations respond to selection. PMID:28685813

Dissecting social cell biology and tumors using Drosophila genetics.

PubMed

Pastor-Pareja, José Carlos; Xu, Tian

2013-01-01

Cancer was seen for a long time as a strictly cell-autonomous process in which oncogenes and tumor-suppressor mutations drive clonal cell expansions. Research in the past decade, however, paints a more integrative picture of communication and interplay between neighboring cells in tissues. It is increasingly clear as well that tumors, far from being homogenous lumps of cells, consist of different cell types that function together as complex tissue-level communities. The repertoire of interactive cell behaviors and the quantity of cellular players involved call for a social cell biology that investigates these interactions. Research into this social cell biology is critical for understanding development of normal and tumoral tissues. Such complex social cell biology interactions can be parsed in Drosophila. Techniques in Drosophila for analysis of gene function and clonal behavior allow us to generate tumors and dissect their complex interactive biology with cellular resolution. Here, we review recent Drosophila research aimed at understanding tissue-level biology and social cell interactions in tumors, highlighting the principles these studies reveal.

An integrative model of evolutionary covariance: a symposium on body shape in fishes.

PubMed

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).

A mitochondrial-focused genetic interaction map reveals a scaffold-like complex required for inner membrane organization in mitochondria

PubMed Central

Hoppins, Suzanne; Collins, Sean R.; Cassidy-Stone, Ann; Hummel, Eric; DeVay, Rachel M.; Lackner, Laura L.; Westermann, Benedikt; Schuldiner, Maya

2011-01-01

To broadly explore mitochondrial structure and function as well as the communication of mitochondria with other cellular pathways, we constructed a quantitative, high-density genetic interaction map (the MITO-MAP) in Saccharomyces cerevisiae. The MITO-MAP provides a comprehensive view of mitochondrial function including insights into the activity of uncharacterized mitochondrial proteins and the functional connection between mitochondria and the ER. The MITO-MAP also reveals a large inner membrane–associated complex, which we term MitOS for mitochondrial organizing structure, comprised of Fcj1/Mitofilin, a conserved inner membrane protein, and five additional components. MitOS physically and functionally interacts with both outer and inner membrane components and localizes to extended structures that wrap around the inner membrane. We show that MitOS acts in concert with ATP synthase dimers to organize the inner membrane and promote normal mitochondrial morphology. We propose that MitOS acts as a conserved mitochondrial skeletal structure that differentiates regions of the inner membrane to establish the normal internal architecture of mitochondria. PMID:21987634

Progress in Using Mouse Inbred Strains, Consomics, and Mutants to Identify Genes Related to Stress, Anxiety, and Alcohol Phenotypes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goldowitz, Daniel; Matthews, Douglas B.; Hamre, Kristin M.

ALCOHOL ABUSE AND alcoholism result from the complex interplay of genetic and environmental factors. Stress is a factor that is widely thought to contribute to excessive drinking and alcoholism. One consequence of stressful experiences is anxiety, and there is a rich literature on the interactions between alcohol and anxiety. Less is known about brain mechanisms at the molecular, cellular, and system levels that mediate stress effects that contribute to excessive drinking and alcoholism. In addition, it is not clear whether and/or how genetic factors that contribute to excessive drinking interact with neural stress mechanisms.

Inferring genetic interactions via a nonlinear model and an optimization algorithm.

PubMed

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.

Inflammatory bowel disease: pathogenesis.

PubMed

Zhang, Yi-Zhen; Li, Yong-Yu

2014-01-07

Inflammatory bowel disease (IBD), including Crohn's disease and ulcerative colitis, is characterized by chronic relapsing intestinal inflammation. It has been a worldwide health-care problem with a continually increasing incidence. It is thought that IBD results from an aberrant and continuing immune response to the microbes in the gut, catalyzed by the genetic susceptibility of the individual. Although the etiology of IBD remains largely unknown, it involves a complex interaction between the genetic, environmental or microbial factors and the immune responses. Of the four components of IBD pathogenesis, most rapid progress has been made in the genetic study of gut inflammation. The latest internationally collaborative studies have ascertained 163 susceptibility gene loci for IBD. The genes implicated in childhood-onset and adult-onset IBD overlap, suggesting similar genetic predispositions. However, the fact that genetic factors account for only a portion of overall disease variance indicates that microbial and environmental factors may interact with genetic elements in the pathogenesis of IBD. Meanwhile, the adaptive immune response has been classically considered to play a major role in the pathogenesis of IBD, as new studies in immunology and genetics have clarified that the innate immune response maintains the same importance in inducing gut inflammation. Recent progress in understanding IBD pathogenesis sheds lights on relevant disease mechanisms, including the innate and adaptive immunity, and the interactions between genetic factors and microbial and environmental cues. In this review, we provide an update on the major advances that have occurred in above areas.

Genetic determinants of prepubertal and pubertal growth and development.

PubMed

Thomis, Martine A; Towne, Bradford

2006-12-01

This article surveys the current general understanding of genetic influences on within- and between-population variation in growth and development in the context of establishing an International Growth Standard for Preadolescent and Adolescent Children. Traditional genetic epidemiologic analysis methods are reviewed, and evidence from family studies for genetic effects on different measures of growth and development is then presented. Findings from linkage and association studies seeking to identify specific genomic locations and allelic variants of genes influencing variation in growth and maturation are then summarized. Special mention is made of the need to study the interactions between genes and environments. At present, specific genes and polymorphisms contributing to variation in growth and maturation are only beginning to be identified. Larger genetic epidemiologic studies are needed in different parts of the world to better explore population differences in gene frequencies and gene-environment interactions. As advances continue to be made in molecular and statistical genetic methods, the genetic architecture of complex processes, including those of growth and development, will become better elucidated. For now, it can only be concluded that although the fundamental genetic underpinnings of the growth and development of children worldwide are likely to be essentially the same, there are also likely to be differences between populations in the frequencies of allelic gene variants that influence growth and maturation and in the nature of gene-environment interactions. This does not necessarily preclude an international growth reference, but it does have important implications for the form that such a reference might ultimately take.

Synthetic Genetic Arrays: Automation of Yeast Genetics.

PubMed

Kuzmin, Elena; Costanzo, Michael; Andrews, Brenda; Boone, Charles

2016-04-01

Genome-sequencing efforts have led to great strides in the annotation of protein-coding genes and other genomic elements. The current challenge is to understand the functional role of each gene and how genes work together to modulate cellular processes. Genetic interactions define phenotypic relationships between genes and reveal the functional organization of a cell. Synthetic genetic array (SGA) methodology automates yeast genetics and enables large-scale and systematic mapping of genetic interaction networks in the budding yeast,Saccharomyces cerevisiae SGA facilitates construction of an output array of double mutants from an input array of single mutants through a series of replica pinning steps. Subsequent analysis of genetic interactions from SGA-derived mutants relies on accurate quantification of colony size, which serves as a proxy for fitness. Since its development, SGA has given rise to a variety of other experimental approaches for functional profiling of the yeast genome and has been applied in a multitude of other contexts, such as genome-wide screens for synthetic dosage lethality and integration with high-content screening for systematic assessment of morphology defects. SGA-like strategies can also be implemented similarly in a number of other cell types and organisms, includingSchizosaccharomyces pombe,Escherichia coli, Caenorhabditis elegans, and human cancer cell lines. The genetic networks emerging from these studies not only generate functional wiring diagrams but may also play a key role in our understanding of the complex relationship between genotype and phenotype. © 2016 Cold Spring Harbor Laboratory Press.

Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals.

PubMed

Morgante, Fabio; Huang, Wen; Maltecca, Christian; Mackay, Trudy F C

2018-06-01

Predicting complex phenotypes from genomic data is a fundamental aim of animal and plant breeding, where we wish to predict genetic merits of selection candidates; and of human genetics, where we wish to predict disease risk. While genomic prediction models work well with populations of related individuals and high linkage disequilibrium (LD) (e.g., livestock), comparable models perform poorly for populations of unrelated individuals and low LD (e.g., humans). We hypothesized that low prediction accuracies in the latter situation may occur when the genetics architecture of the trait departs from the infinitesimal and additive architecture assumed by most prediction models. We used simulated data for 10,000 lines based on sequence data from a population of unrelated, inbred Drosophila melanogaster lines to evaluate this hypothesis. We show that, even in very simplified scenarios meant as a stress test of the commonly used Genomic Best Linear Unbiased Predictor (G-BLUP) method, using all common variants yields low prediction accuracy regardless of the trait genetic architecture. However, prediction accuracy increases when predictions are informed by the genetic architecture inferred from mapping the top variants affecting main effects and interactions in the training data, provided there is sufficient power for mapping. When the true genetic architecture is largely or partially due to epistatic interactions, the additive model may not perform well, while models that account explicitly for interactions generally increase prediction accuracy. Our results indicate that accounting for genetic architecture can improve prediction accuracy for quantitative traits.

Ten years of genetics and genomics: what have we achieved and where are we heading?

PubMed Central

Heard, Edith; Tishkoff, Sarah; Todd, John A.; Vidal, Marc; Wagner, Günter P.; Wang, Jun; Weigel, Detlef; Young, Richard

2010-01-01

To celebrate the first 10 years of Nature Reviews Genetics, we asked eight leading researchers for their views on the key developments in genetics and genomics in the past decade and the prospects for the future. Their responses highlight the incredible changes that the field has seen, from the explosion of genomic data and the many possibilities it has opened up to the ability to reprogramme adult cells to pluripotency. The way ahead looks similarly exciting as we address questions such as how cells function as systems and how complex interactions among genetics, epigenetics and the environment combine to shape phenotypes. PMID:20820184

Socioeconomic status and genetic influences on cognitive development.

PubMed

Figlio, David N; Freese, Jeremy; Karbownik, Krzysztof; Roth, Jeffrey

2017-12-19

Accurate understanding of environmental moderation of genetic influences is vital to advancing the science of cognitive development as well as for designing interventions. One widely reported idea is increasing genetic influence on cognition for children raised in higher socioeconomic status (SES) families, including recent proposals that the pattern is a particularly US phenomenon. We used matched birth and school records from Florida siblings and twins born in 1994-2002 to provide the largest, most population-diverse consideration of this hypothesis to date. We found no evidence of SES moderation of genetic influence on test scores, suggesting that articulating gene-environment interactions for cognition is more complex and elusive than previously supposed.

How spatio-temporal habitat connectivity affects amphibian genetic structure.

PubMed

Watts, Alexander G; Schlichting, Peter E; Billerman, Shawn M; Jesmer, Brett R; Micheletti, Steven; Fortin, Marie-Josée; Funk, W Chris; Hapeman, Paul; Muths, Erin; Murphy, Melanie A

2015-01-01

Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations.

Obstructive Sleep Apnea Syndrome: From Phenotype to Genetic Basis

PubMed Central

Casale, M; Pappacena, M; Rinaldi, V; Bressi, F; Baptista, P; Salvinelli, F

2009-01-01

Obstructive sleep apnea syndrome (OSAS) is a complex chronic clinical syndrome, characterized by snoring, periodic apnea, hypoxemia during sleep, and daytime hypersomnolence. It affects 4-5% of the general population. Racial studies and chromosomal mapping, familial studies and twin studies have provided evidence for the possible link between the OSAS and genetic factors and also most of the risk factors involved in the pathogenesis of OSAS are largely genetically determined. A percentage of 35-40% of its variance can be attributed to genetic factors. It is likely that genetic factors associated with craniofacial structure, body fat distribution and neural control of the upper airway muscles interact to produce the OSAS phenotype. Although the role of specific genes that influence the development of OSAS has not yet been identified, current researches, especially in animal model, suggest that several genetic systems may be important. In this chapter, we will first define the OSAS phenotype, the pathogenesis and the risk factors involved in the OSAS that may be inherited, then, we will review the current progress in the genetics of OSAS and suggest a few future perspectives in the development of therapeutic agents for this complex disease entity. PMID:19794884

Gene and environment interaction: is the differential susceptibility hypothesis relevant for obesity?

PubMed Central

Dalle Molle, Roberta; Fatemi, Hajar; Dagher, Alain; Levitan, Robert D.; Silveira, Patricia P.; Dubé, Laurette

2017-01-01

The differential susceptibility model states that a given genetic variant is associated with an increased risk of pathology in negative environments but greater than average resilience in enriched ones. While this theory was first implemented in psychiatric-genetic research, it may also help us to unravel the complex ways that genes and environments interact to influence feeding behavior and obesity. We reviewed evidence on gene vs. environment interactions that influence obesity development, aiming to support the applicability of the differential susceptibility model for this condition, and propose that various environmental “layers” relevant for human development should be considered when bearing the differential susceptibility model in mind. Mother-child relationship, socioeconomic status and individual's response are important modifiers of BMI and food intake when interacting with gene variants, “for better and for worse”. While only a few studies to date have investigated obesity outcomes using this approach, we propose that the differential susceptibility hypothesis is in fact highly applicable to the study of genetic and environmental influences on feeding behavior and obesity risk. PMID:28024828

Genetic control of root growth: from genes to networks.

PubMed

Slovak, Radka; Ogura, Takehiko; Satbhai, Santosh B; Ristova, Daniela; Busch, Wolfgang

2016-01-01

Roots are essential organs for higher plants. They provide the plant with nutrients and water, anchor the plant in the soil, and can serve as energy storage organs. One remarkable feature of roots is that they are able to adjust their growth to changing environments. This adjustment is possible through mechanisms that modulate a diverse set of root traits such as growth rate, diameter, growth direction and lateral root formation. The basis of these traits and their modulation are at the cellular level, where a multitude of genes and gene networks precisely regulate development in time and space and tune it to environmental conditions. This review first describes the root system and then presents fundamental work that has shed light on the basic regulatory principles of root growth and development. It then considers emerging complexities and how they have been addressed using systems-biology approaches, and then describes and argues for a systems-genetics approach. For reasons of simplicity and conciseness, this review is mostly limited to work from the model plant Arabidopsis thaliana, in which much of the research in root growth regulation at the molecular level has been conducted. While forward genetic approaches have identified key regulators and genetic pathways, systems-biology approaches have been successful in shedding light on complex biological processes, for instance molecular mechanisms involving the quantitative interaction of several molecular components, or the interaction of large numbers of genes. However, there are significant limitations in many of these methods for capturing dynamic processes, as well as relating these processes to genotypic and phenotypic variation. The emerging field of systems genetics promises to overcome some of these limitations by linking genotypes to complex phenotypic and molecular data using approaches from different fields, such as genetics, genomics, systems biology and phenomics. © The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Genetically contextual effects of smoking on genome wide DNA methylation.

PubMed

Dogan, Meeshanthini V; Beach, Steven R H; Philibert, Robert A

2017-09-01

Smoking is the leading cause of death in the United States. It exerts its effects by increasing susceptibility to a variety of complex disorders among those who smoke, and if pregnant, to their unborn children. In prior efforts to understand the epigenetic mechanisms through which this increased vulnerability is conveyed, a number of investigators have conducted genome wide methylation analyses. Unfortunately, secondary to methodological limitations, these studies were unable to examine methylation in gene regions with significant amounts of genetic variation. Using genome wide genetic and epigenetic data from the Framingham Heart Study, we re-examined the relationship of smoking status to genome wide methylation status. When only methylation status is considered, smoking was significantly associated with differential methylation in 310 genes that map to a variety of biological process and cellular differentiation pathways. However, when SNP effects on the magnitude of smoking associated methylation changes are also considered, cis and trans-interaction effects were noted at a total of 266 and 4353 genes with no marked enrichment for any biological pathways. Furthermore, the SNP variation participating in the significant interaction effects is enriched for loci previously associated with complex medical illnesses. The enlarged scope of the methylome shown to be affected by smoking may better explicate the mediational pathways linking smoking with a myriad of smoking related complex syndromes. Additionally, these results strongly suggest that combined epigenetic and genetic data analyses may be critical for a more complete understanding of the relationship between environmental variables, such as smoking, and pathophysiological outcomes. © 2017 Wiley Periodicals, Inc.

The Genetics of Stress-Related Disorders: PTSD, Depression, and Anxiety Disorders

PubMed Central

Smoller, Jordan W

2016-01-01

Research into the causes of psychopathology has largely focused on two broad etiologic factors: genetic vulnerability and environmental stressors. An important role for familial/heritable factors in the etiology of a broad range of psychiatric disorders was established well before the modern era of genomic research. This review focuses on the genetic basis of three disorder categories—posttraumatic stress disorder (PTSD), major depressive disorder (MDD), and the anxiety disorders—for which environmental stressors and stress responses are understood to be central to pathogenesis. Each of these disorders aggregates in families and is moderately heritable. More recently, molecular genetic approaches, including genome-wide studies of genetic variation, have been applied to identify specific risk variants. In this review, I summarize evidence for genetic contributions to PTSD, MDD, and the anxiety disorders including genetic epidemiology, the role of common genetic variation, the role of rare and structural variation, and the role of gene–environment interaction. Available data suggest that stress-related disorders are highly complex and polygenic and, despite substantial progress in other areas of psychiatric genetics, few risk loci have been identified for these disorders. Progress in this area will likely require analysis of much larger sample sizes than have been reported to date. The phenotypic complexity and genetic overlap among these disorders present further challenges. The review concludes with a discussion of prospects for clinical translation of genetic findings and future directions for research. PMID:26321314

Pathology supported genetic testing and treatment of cardiovascular disease in middle age for prevention of Alzheimer's disease.

PubMed

Kotze, Maritha J; van Rensburg, Susan J

2012-09-01

Chronic, multi-factorial conditions caused by a complex interaction between genetic and environmental risk factors frequently share common disease mechanisms, as evidenced by an overlap between genetic risk factors for cardiovascular disease (CVD) and Alzheimer's disease (AD). Single nucleotide polymorphisms (SNPs) in several genes including ApoE, MTHFR, HFE and FTO are known to increase the risk of both conditions. The E4 allele of the ApoE polymorphism is the most extensively studied risk factor for AD and increases the risk of coronary heart disease by approximately 40%. It furthermore displays differential therapeutic responses with use of cholesterol-lowering statins and acetylcholinesterase inhibitors, which may also be due to variation in the CYP2D6 gene in some patients. Disease expression may be triggered by gene-environment interaction causing conversion of minor metabolic abnormalities into major brain disease due to cumulative risk. A growing body of evidence supports the assessment and treatment of CVD risk factors in midlife as a preventable cause of cognitive decline, morbidity and mortality in old age. In this review, the concept of pathology supported genetic testing (PSGT) for CVD is described in this context. PSGT combines DNA testing with biochemical measurements to determine gene expression and to monitor response to treatment. The aim is to diagnose treatable disease subtypes of complex disorders, facilitate prevention of cumulative risk and formulate intervention strategies guided from the genetic background. CVD provides a model to address the lifestyle link in most chronic diseases with a genetic component. Similar preventative measures would apply for optimisation of heart and brain health.

Genetic interactions between the chromosome axis-associated protein Hop1 and homologous recombination determinants in Schizosaccharomyces pombe.

PubMed

Brown, Simon David; Jarosinska, Olga Dorota; Lorenz, Alexander

2018-03-17

Hop1 is a component of the meiosis-specific chromosome axis and belongs to the evolutionarily conserved family of HORMA domain proteins. Hop1 and its orthologs in higher eukaryotes are a major factor in promoting double-strand DNA break formation and inter-homolog recombination. In budding yeast and mammals, they are also involved in a meiotic checkpoint kinase cascade monitoring the completion of double-strand DNA break repair. We used the fission yeast, Schizosaccharomyces pombe, which lacks a canonical synaptonemal complex to test whether Hop1 has a role beyond supporting the generation of double-strand DNA breaks and facilitating inter-homolog recombination events. We determined how mutants of homologous recombination factors genetically interact with hop1, studied the role(s) of the HORMA domain of Hop1, and characterized a bio-informatically predicted interactor of Hop1, Aho1 (SPAC688.03c). Our observations indicate that in fission yeast, Hop1 does require its HORMA domain to support wild-type levels of meiotic recombination and localization to meiotic chromatin. Furthermore, we show that hop1∆ only weakly interacts genetically with mutants of homologous recombination factors, and in fission yeast likely has no major role beyond break formation and promoting inter-homolog events. We speculate that after the evolutionary loss of the synaptonemal complex, Hop1 likely has become less important for modulating recombination outcome during meiosis in fission yeast, and that this led to a concurrent rewiring of genetic pathways controlling meiotic recombination.

Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens.

PubMed

Pan, Joshua; Meyers, Robin M; Michel, Brittany C; Mashtalir, Nazar; Sizemore, Ann E; Wells, Jonathan N; Cassel, Seth H; Vazquez, Francisca; Weir, Barbara A; Hahn, William C; Marsh, Joseph A; Tsherniak, Aviad; Kadoch, Cigall

2018-05-23

Protein complexes are assemblies of subunits that have co-evolved to execute one or many coordinated functions in the cellular environment. Functional annotation of mammalian protein complexes is critical to understanding biological processes, as well as disease mechanisms. Here, we used genetic co-essentiality derived from genome-scale RNAi- and CRISPR-Cas9-based fitness screens performed across hundreds of human cancer cell lines to assign measures of functional similarity. From these measures, we systematically built and characterized functional similarity networks that recapitulate known structural and functional features of well-studied protein complexes and resolve novel functional modules within complexes lacking structural resolution, such as the mammalian SWI/SNF complex. Finally, by integrating functional networks with large protein-protein interaction networks, we discovered novel protein complexes involving recently evolved genes of unknown function. Taken together, these findings demonstrate the utility of genetic perturbation screens alone, and in combination with large-scale biophysical data, to enhance our understanding of mammalian protein complexes in normal and disease states. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Suffering in silence: why a developmental psychopathology perspective on selective mutism is needed.

PubMed

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.

Characterizing the Pyrenophora teres f. maculata–Barley Interaction Using Pathogen Genetics

PubMed Central

Carlsen, Steven A.; Neupane, Anjan; Wyatt, Nathan A.; Richards, Jonathan K.; Faris, Justin D.; Xu, Steven S.; Brueggeman, Robert S.; Friesen, Timothy L.

2017-01-01

Pyrenophora teres f. maculata is the cause of the foliar disease spot form net blotch (SFNB) on barley. To evaluate pathogen genetics underlying the P. teres f. maculata–barley interaction, we developed a 105-progeny population by crossing two globally diverse isolates, one from North Dakota and the other from Western Australia. Progeny were phenotyped on a set of four barley genotypes showing a differential reaction to the parental isolates, then genotyped using a restriction site-associated-genotype-by-sequencing (RAD-GBS) approach. Genetic maps were developed for use in quantitative trait locus (QTL) analysis to identify virulence-associated QTL. Six QTL were identified on five different linkage groups and individually accounted for 20–37% of the disease variation, with the number of significant QTL ranging from two to four for the barley genotypes evaluated. The data presented demonstrate the complexity of virulence involved in the P. teres f. maculata–barley pathosystem and begins to lay the foundation for understanding this important interaction. PMID:28659291

Evaluation of genetic and metabolic role of SKIP11 in Arabidopsis thaliana

NASA Astrophysics Data System (ADS)

Hassan, Muhammad Naeem ul; Ismail, Ismanizan

2015-09-01

Most of the regulatory proteins are degraded by 26S proteasome complex, only when they are tagged by Ubiquitin. A complex of four proteins, SKP1-Cullin-Ring box-F box (SCF) catalyses the final step to link the Ubiquitin tag with the target proteins. SCF complex interacts with the target proteins through F-box proteins, which confer the overall substrate specificity to the complex. F-box proteins, one of the largest family of proteins in plants have an N-terminal F-box domain and variable C-terminal domains, like leucine-rich repeat, WD-40 repeat and the kelch-repeat domains. In this study, we analysed the role of SKIP11, a kelch containing F-box protein (KFB) from Arabidopsis thaliana, by using reverse genetics strategy. The results show that SKIP11 is involved in the down-regulation of oxylipin pathway, possibly through the degradation of enzymes or/ and the regulatory factors of the pathway.

Genomic networks of hybrid sterility.

PubMed

Turner, Leslie M; White, Michael A; Tautz, Diethard; Payseur, Bret A

2014-02-01

Hybrid dysfunction, a common feature of reproductive barriers between species, is often caused by negative epistasis between loci ("Dobzhansky-Muller incompatibilities"). The nature and complexity of hybrid incompatibilities remain poorly understood because identifying interacting loci that affect complex phenotypes is difficult. With subspecies in the early stages of speciation, an array of genetic tools, and detailed knowledge of reproductive biology, house mice (Mus musculus) provide a model system for dissecting hybrid incompatibilities. Male hybrids between M. musculus subspecies often show reduced fertility. Previous studies identified loci and several X chromosome-autosome interactions that contribute to sterility. To characterize the genetic basis of hybrid sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL). Many trans eQTL cluster into eleven 'hotspots,' seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL-but not cis eQTL-were substantially lower when mapping was restricted to a 'fertile' subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility. The integrated mapping approach we employed is applicable in a broad range of organisms and we advocate for widespread adoption of a network-centered approach in speciation genetics.

Genomic Networks of Hybrid Sterility

PubMed Central

Turner, Leslie M.; White, Michael A.; Tautz, Diethard; Payseur, Bret A.

2014-01-01

Hybrid dysfunction, a common feature of reproductive barriers between species, is often caused by negative epistasis between loci (“Dobzhansky-Muller incompatibilities”). The nature and complexity of hybrid incompatibilities remain poorly understood because identifying interacting loci that affect complex phenotypes is difficult. With subspecies in the early stages of speciation, an array of genetic tools, and detailed knowledge of reproductive biology, house mice (Mus musculus) provide a model system for dissecting hybrid incompatibilities. Male hybrids between M. musculus subspecies often show reduced fertility. Previous studies identified loci and several X chromosome-autosome interactions that contribute to sterility. To characterize the genetic basis of hybrid sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL). Many trans eQTL cluster into eleven ‘hotspots,’ seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL—but not cis eQTL—were substantially lower when mapping was restricted to a ‘fertile’ subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility. The integrated mapping approach we employed is applicable in a broad range of organisms and we advocate for widespread adoption of a network-centered approach in speciation genetics. PMID:24586194

Rethinking the dispersal of Homo sapiens out of Africa.

PubMed

Groucutt, Huw S; Petraglia, Michael D; Bailey, Geoff; Scerri, Eleanor M L; Parton, Ash; Clark-Balzan, Laine; Jennings, Richard P; Lewis, Laura; Blinkhorn, James; Drake, Nick A; Breeze, Paul S; Inglis, Robyn H; Devès, Maud H; Meredith-Williams, Matthew; Boivin, Nicole; Thomas, Mark G; Scally, Aylwyn

2015-01-01

Current fossil, genetic, and archeological data indicate that Homo sapiens originated in Africa in the late Middle Pleistocene. By the end of the Late Pleistocene, our species was distributed across every continent except Antarctica, setting the foundations for the subsequent demographic and cultural changes of the Holocene. The intervening processes remain intensely debated and a key theme in hominin evolutionary studies. We review archeological, fossil, environmental, and genetic data to evaluate the current state of knowledge on the dispersal of Homo sapiens out of Africa. The emerging picture of the dispersal process suggests dynamic behavioral variability, complex interactions between populations, and an intricate genetic and cultural legacy. This evolutionary and historical complexity challenges simple narratives and suggests that hybrid models and the testing of explicit hypotheses are required to understand the expansion of Homo sapiens into Eurasia. © 2015 Wiley Periodicals, Inc.

Construction of the model for the Genetic Analysis Workshop 14 simulated data: genotype-phenotype relationships, gene interaction, linkage, association, disequilibrium, and ascertainment effects for a complex phenotype.

PubMed

Greenberg, David A; Zhang, Junying; Shmulewitz, Dvora; Strug, Lisa J; Zimmerman, Regina; Singh, Veena; Marathe, Sudhir

2005-12-30

The Genetic Analysis Workshop 14 simulated dataset was designed 1) To test the ability to find genes related to a complex disease (such as alcoholism). Such a disease may be given a variety of definitions by different investigators, have associated endophenotypes that are common in the general population, and is likely to be not one disease but a heterogeneous collection of clinically similar, but genetically distinct, entities. 2) To observe the effect on genetic analysis and gene discovery of a complex set of gene x gene interactions. 3) To allow comparison of microsatellite vs. large-scale single-nucleotide polymorphism (SNP) data. 4) To allow testing of association to identify the disease gene and the effect of moderate marker x marker linkage disequilibrium. 5) To observe the effect of different ascertainment/disease definition schemes on the analysis. Data was distributed in two forms. Data distributed to participants contained about 1,000 SNPs and 400 microsatellite markers. Internet-obtainable data consisted of a finer 10,000 SNP map, which also contained data on controls. While disease characteristics and parameters were constant, four "studies" used varying ascertainment schemes based on differing beliefs about disease characteristics. One of the studies contained multiplex two- and three-generation pedigrees with at least four affected members. The simulated disease was a psychiatric condition with many associated behaviors (endophenotypes), almost all of which were genetic in origin. The underlying disease model contained four major genes and two modifier genes. The four major genes interacted with each other to produce three different phenotypes, which were themselves heterogeneous. The population parameters were calibrated so that the major genes could be discovered by linkage analysis in most datasets. The association evidence was more difficult to calibrate but was designed to find statistically significant association in 50% of datasets. We also simulated some marker x marker linkage disequilibrium around some of the genes and also in areas without disease genes. We tried two different methods to simulate the linkage disequilibrium.

Complex Patterns of Admixture across the Indonesian Archipelago

PubMed Central

Hudjashov, Georgi; Karafet, Tatiana M.; Lawson, Daniel J.; Downey, Sean; Savina, Olga; Sudoyo, Herawati; Lansing, J. Stephen; Hammer, Michael F.; Cox, Murray P.

2017-01-01

Abstract Indonesia, an island nation as large as continental Europe, hosts a sizeable proportion of global human diversity, yet remains surprisingly undercharacterized genetically. Here, we substantially expand on existing studies by reporting genome-scale data for nearly 500 individuals from 25 populations in Island Southeast Asia, New Guinea, and Oceania, notably including previously unsampled islands across the Indonesian archipelago. We use high-resolution analyses of haplotype diversity to reveal fine detail of regional admixture patterns, with a particular focus on the Holocene. We find that recent population history within Indonesia is complex, and that populations from the Philippines made important genetic contributions in the early phases of the Austronesian expansion. Different, but interrelated processes, acted in the east and west. The Austronesian migration took several centuries to spread across the eastern part of the archipelago, where genetic admixture postdates the archeological signal. As with the Neolithic expansion further east in Oceania and in Europe, genetic mixing with local inhabitants in eastern Indonesia lagged behind the arrival of farming populations. In contrast, western Indonesia has a more complicated admixture history shaped by interactions with mainland Asian and Austronesian newcomers, which for some populations occurred more than once. Another layer of complexity in the west was introduced by genetic contact with South Asia and strong demographic events in isolated local groups. PMID:28957506

Identifying Interacting Genetic Variations by Fish-Swarm Logic Regression

PubMed Central

Yang, Aiyuan; Yan, Chunxia; Zhu, Feng; Zhao, Zhongmeng; Cao, Zhi

2013-01-01

Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR) is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR), which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds. PMID:23984382

GENETIC VARIATION IN BABOON CRANIOFACIAL SEXUAL DIMORPHISM

PubMed Central

Willmore, Katherine E.; Roseman, Charles C.; Rogers, Jeffrey; Richtsmeier, Joan T.; Cheverud, James M.

2010-01-01

Sexual dimorphism is a widespread phenomenon and contributes greatly to intraspecies variation. Despite a long history of active research, the genetic basis of dimorphism for complex traits remains unknown. Understanding the sex-specific differences in genetic architecture for cranial traits in a highly dimorphic species could identify possible mechanisms through which selection acts to produce dimorphism. Using distances calculated from three-dimensional landmark data from CT scans of 402 baboon skulls from a known genealogy, we estimated genetic variance parameters in both sexes to determine the presence of gene-by-sex (G × S) interactions and X-linked heritability. We hypothesize that traits exhibiting the greatest degree of sexual dimorphism (facial traits in baboons) will demonstrate either stronger G × S interactions or X-linked effects. We found G × S interactions and X-linked effects for a few measures that span the areas connecting the face to the neurocranium but for no traits restricted to the face. This finding suggests that facial traits will have a limited response to selection for further evolution of dimorphism in this population. We discuss the implications of our results with respect to the origins of cranial sexual dimorphism in this baboon sample, and how the genetic architecture of these traits affects their potential for future evolution. PMID:19210535

The genetic regulatory network centered on Pto-Wuschela and its targets involved in wood formation revealed by association studies.

PubMed

Yang, Xiaohui; Wei, Zunzheng; Du, Qingzhang; Chen, Jinhui; Wang, Qingshi; Quan, Mingyang; Song, Yuepeng; Xie, Jianbo; Zhang, Deqiang

2015-11-09

Transcription factors (TFs) regulate gene expression and can strongly affect phenotypes. However, few studies have examined TF variants and TF interactions with their targets in plants. Here, we used genetic association in 435 unrelated individuals of Populus tomentosa to explore the variants in Pto-Wuschela and its targets to decipher the genetic regulatory network of Pto-Wuschela. Our bioinformatics and co-expression analysis identified 53 genes with the motif TCACGTGA as putative targets of Pto-Wuschela. Single-marker association analysis showed that Pto-Wuschela was associated with wood properties, which is in agreement with the observation that it has higher expression in stem vascular tissues in Populus. Also, SNPs in the 53 targets were associated with growth or wood properties under additive or dominance effects, suggesting these genes and Pto-Wuschela may act in the same genetic pathways that affect variation in these quantitative traits. Epistasis analysis indicated that 75.5% of these genes directly or indirectly interacted Pto-Wuschela, revealing the coordinated genetic regulatory network formed by Pto-Wuschela and its targets. Thus, our study provides an alternative method for dissection of the interactions between a TF and its targets, which will strength our understanding of the regulatory roles of TFs in complex traits in plants.

Genetic susceptibility to Grave's disease.

PubMed

Li, Hong; Chen, Qiuying

2013-06-01

The variety of clinical presentations of eye changes in patients with Graves' disease (GD) suggests that complex interactions between genetic, environmental, endogenous and local factors influence the severity of Graves' ophthalmopathy (GO). It is thought that the development of GO might be influenced by genetic factors and environmental factors, such as cigarette smoking. At present, however, the role of genetic factors in the development of GO is not known. On the basis of studies with candidate genes and other genetic approaches, several susceptibility loci in GO have been proposed, including immunological genes, human leukocyte antigen (HLA), cytotoxic T-lymphocyte antigen-4 (CTLA-4), regulatory T-cell genes and thyroid-specific genes. This review gives a brief overview of the current range of major susceptibility genes found for GD.

Beyond DNA: integrating inclusive inheritance into an extended theory of evolution.

PubMed

Danchin, Étienne; Charmantier, Anne; Champagne, Frances A; Mesoudi, Alex; Pujol, Benoit; Blanchet, Simon

2011-06-17

Many biologists are calling for an 'extended evolutionary synthesis' that would 'modernize the modern synthesis' of evolution. Biological information is typically considered as being transmitted across generations by the DNA sequence alone, but accumulating evidence indicates that both genetic and non-genetic inheritance, and the interactions between them, have important effects on evolutionary outcomes. We review the evidence for such effects of epigenetic, ecological and cultural inheritance and parental effects, and outline methods that quantify the relative contributions of genetic and non-genetic heritability to the transmission of phenotypic variation across generations. These issues have implications for diverse areas, from the question of missing heritability in human complex-trait genetics to the basis of major evolutionary transitions.

Summarizing techniques that combine three non-parametric scores to detect disease-associated 2-way SNP-SNP interactions.

PubMed

Sengupta Chattopadhyay, Amrita; Hsiao, Ching-Lin; Chang, Chien Ching; Lian, Ie-Bin; Fann, Cathy S J

2014-01-01

Identifying susceptibility genes that influence complex diseases is extremely difficult because loci often influence the disease state through genetic interactions. Numerous approaches to detect disease-associated SNP-SNP interactions have been developed, but none consistently generates high-quality results under different disease scenarios. Using summarizing techniques to combine a number of existing methods may provide a solution to this problem. Here we used three popular non-parametric methods-Gini, absolute probability difference (APD), and entropy-to develop two novel summary scores, namely principle component score (PCS) and Z-sum score (ZSS), with which to predict disease-associated genetic interactions. We used a simulation study to compare performance of the non-parametric scores, the summary scores, the scaled-sum score (SSS; used in polymorphism interaction analysis (PIA)), and the multifactor dimensionality reduction (MDR). The non-parametric methods achieved high power, but no non-parametric method outperformed all others under a variety of epistatic scenarios. PCS and ZSS, however, outperformed MDR. PCS, ZSS and SSS displayed controlled type-I-errors (<0.05) compared to GS, APDS, ES (>0.05). A real data study using the genetic-analysis-workshop 16 (GAW 16) rheumatoid arthritis dataset identified a number of interesting SNP-SNP interactions. © 2013 Elsevier B.V. All rights reserved.

Nutrigenomics in cardiovascular disease: implications for the future.

PubMed

Engler, Mary B

2009-12-01

Cardiovascular disease (CVD), the leading cause of morbidity and mortality worldwide, is a complex multifactorial disease which is influenced by environmental and genetic factors. There is substantial evidence on the relationship between diet and CVD risk. An understanding of how genetic variation interacts with the diet to influence CVD risk is a rapidly evolving area of research. Since diet is the mainstay of risk factor modification, it is important to consider potential genetic influences on CVD risk. Nutrigenomics is the study of the interaction between diet and an individual's genetic makeup. Single nucleotide polymorphisms are the key factors in human genetic variation and provide a molecular basis for phenotypic differences between individuals. Whole genome and candidate gene association studies are two main approaches used in cardiovascular genetics to identify disease-causing genes. Recent nutrigenomics studies show the influence of genotype on the responsiveness to dietary factors or nutrients that may reduce CVD risk. Nutrigenomics research is expected to provide the scientific evidence for genotype-based personalized nutrition to promote health and prevent chronic disease, including CVD. It is imperative that healthcare providers, including cardiovascular nurses, are trained in genetics to foster delivery of competent genetic- and genomic-focused care and to facilitate incorporation of this new knowledge into current clinical practice, education, and research.

Identifying novel interventional strategies for psychiatric disorders: integrating genomics, 'enviromics' and gene-environment interactions in valid preclinical models.

PubMed

McOmish, Caitlin E; Burrows, Emma L; Hannan, Anthony J

2014-10-01

Psychiatric disorders affect a substantial proportion of the population worldwide. This high prevalence, combined with the chronicity of the disorders and the major social and economic impacts, creates a significant burden. As a result, an important priority is the development of novel and effective interventional strategies for reducing incidence rates and improving outcomes. This review explores the progress that has been made to date in establishing valid animal models of psychiatric disorders, while beginning to unravel the complex factors that may be contributing to the limitations of current methodological approaches. We propose some approaches for optimizing the validity of animal models and developing effective interventions. We use schizophrenia and autism spectrum disorders as examples of disorders for which development of valid preclinical models, and fully effective therapeutics, have proven particularly challenging. However, the conclusions have relevance to various other psychiatric conditions, including depression, anxiety and bipolar disorders. We address the key aspects of construct, face and predictive validity in animal models, incorporating genetic and environmental factors. Our understanding of psychiatric disorders is accelerating exponentially, revealing extraordinary levels of genetic complexity, heterogeneity and pleiotropy. The environmental factors contributing to individual, and multiple, disorders also exhibit breathtaking complexity, requiring systematic analysis to experimentally explore the environmental mediators and modulators which constitute the 'envirome' of each psychiatric disorder. Ultimately, genetic and environmental factors need to be integrated via animal models incorporating the spatiotemporal complexity of gene-environment interactions and experience-dependent plasticity, thus better recapitulating the dynamic nature of brain development, function and dysfunction. © 2014 The British Pharmacological Society.

Systems genetics of obesity in an F2 pig model by genome-wide association, genetic network, and pathway analyses

PubMed Central

Kogelman, Lisette J. A.; Pant, Sameer D.; Fredholm, Merete; Kadarmideen, Haja N.

2014-01-01

Obesity is a complex condition with world-wide exponentially rising prevalence rates, linked with severe diseases like Type 2 Diabetes. Economic and welfare consequences have led to a raised interest in a better understanding of the biological and genetic background. To date, whole genome investigations focusing on single genetic variants have achieved limited success, and the importance of including genetic interactions is becoming evident. Here, the aim was to perform an integrative genomic analysis in an F2 pig resource population that was constructed with an aim to maximize genetic variation of obesity-related phenotypes and genotyped using the 60K SNP chip. Firstly, Genome Wide Association (GWA) analysis was performed on the Obesity Index to locate candidate genomic regions that were further validated using combined Linkage Disequilibrium Linkage Analysis and investigated by evaluation of haplotype blocks. We built Weighted Interaction SNP Hub (WISH) and differentially wired (DW) networks using genotypic correlations amongst obesity-associated SNPs resulting from GWA analysis. GWA results and SNP modules detected by WISH and DW analyses were further investigated by functional enrichment analyses. The functional annotation of SNPs revealed several genes associated with obesity, e.g., NPC2 and OR4D10. Moreover, gene enrichment analyses identified several significantly associated pathways, over and above the GWA study results, that may influence obesity and obesity related diseases, e.g., metabolic processes. WISH networks based on genotypic correlations allowed further identification of various gene ontology terms and pathways related to obesity and related traits, which were not identified by the GWA study. In conclusion, this is the first study to develop a (genetic) obesity index and employ systems genetics in a porcine model to provide important insights into the complex genetic architecture associated with obesity and many biological pathways that underlie it. PMID:25071839

Cytochrome P450 drug interactions with statin therapy.

PubMed

Goh, Ivanna Xin Wei; How, Choon How; Tavintharan, Subramaniam

2013-03-01

Statins are commonly used in the treatment of hyperlipidaemia. Although the benefits of statins are well-documented, they have the potential to cause myopathy and rhabdomyolysis due to the complex interactions of drugs, comorbidities and genetics. The cytochrome P450 family consists of major enzymes involved in drug metabolism and bioactivation. This article aims to highlight drug interactions involving statins, as well as provide updated recommendations and approaches regarding the safe and appropriate use of statins in the primary care setting.

Education influences the association between genetic variants and refractive error: a meta-analysis of five Singapore studies

PubMed Central

Fan, Qiao; Wojciechowski, Robert; Kamran Ikram, M.; Cheng, Ching-Yu; Chen, Peng; Zhou, Xin; Pan, Chen-Wei; Khor, Chiea-Chuen; Tai, E-Shyong; Aung, Tin; Wong, Tien-Yin; Teo, Yik-Ying; Saw, Seang-Mei

2014-01-01

Refractive error is a complex ocular trait governed by both genetic and environmental factors and possibly their interplay. Thus far, data on the interaction between genetic variants and environmental risk factors for refractive errors are largely lacking. By using findings from recent genome-wide association studies, we investigated whether the main environmental factor, education, modifies the effect of 40 single nucleotide polymorphisms on refractive error among 8461 adults from five studies including ethnic Chinese, Malay and Indian residents of Singapore. Three genetic loci SHISA6-DNAH9, GJD2 and ZMAT4-SFRP1 exhibited a strong association with myopic refractive error in individuals with higher secondary or university education (SHISA6-DNAH9: rs2969180 A allele, β = −0.33 D, P = 3.6 × 10–6; GJD2: rs524952 A allele, β = −0.31 D, P = 1.68 × 10−5; ZMAT4-SFRP1: rs2137277 A allele, β = −0.47 D, P = 1.68 × 10−4), whereas the association at these loci was non-significant or of borderline significance in those with lower secondary education or below (P for interaction: 3.82 × 10−3–4.78 × 10−4). The evidence for interaction was strengthened when combining the genetic effects of these three loci (P for interaction = 4.40 × 10−8), and significant interactions with education were also observed for axial length and myopia. Our study shows that low level of education may attenuate the effect of risk alleles on myopia. These findings further underline the role of gene–environment interactions in the pathophysiology of myopia. PMID:24014484

Estimating directional epistasis

PubMed Central

Le Rouzic, Arnaud

2014-01-01

Epistasis, i.e., the fact that gene effects depend on the genetic background, is a direct consequence of the complexity of genetic architectures. Despite this, most of the models used in evolutionary and quantitative genetics pay scant attention to genetic interactions. For instance, the traditional decomposition of genetic effects models epistasis as noise around the evolutionarily-relevant additive effects. Such an approach is only valid if it is assumed that there is no general pattern among interactions—a highly speculative scenario. Systematic interactions generate directional epistasis, which has major evolutionary consequences. In spite of its importance, directional epistasis is rarely measured or reported by quantitative geneticists, not only because its relevance is generally ignored, but also due to the lack of simple, operational, and accessible methods for its estimation. This paper describes conceptual and statistical tools that can be used to estimate directional epistasis from various kinds of data, including QTL mapping results, phenotype measurements in mutants, and artificial selection responses. As an illustration, I measured directional epistasis from a real-life example. I then discuss the interpretation of the estimates, showing how they can be used to draw meaningful biological inferences. PMID:25071828

Failure to Replicate a Genetic Association May Provide Important Clues About Genetic Architecture

PubMed Central

Greene, Casey S.; Penrod, Nadia M.; Williams, Scott M.; Moore, Jason H.

2009-01-01

Replication has become the gold standard for assessing statistical results from genome-wide association studies. Unfortunately this replication requirement may cause real genetic effects to be missed. A real result can fail to replicate for numerous reasons including inadequate sample size or variability in phenotype definitions across independent samples. In genome-wide association studies the allele frequencies of polymorphisms may differ due to sampling error or population differences. We hypothesize that some statistically significant independent genetic effects may fail to replicate in an independent dataset when allele frequencies differ and the functional polymorphism interacts with one or more other functional polymorphisms. To test this hypothesis, we designed a simulation study in which case-control status was determined by two interacting polymorphisms with heritabilities ranging from 0.025 to 0.4 with replication sample sizes ranging from 400 to 1600 individuals. We show that the power to replicate the statistically significant independent main effect of one polymorphism can drop dramatically with a change of allele frequency of less than 0.1 at a second interacting polymorphism. We also show that differences in allele frequency can result in a reversal of allelic effects where a protective allele becomes a risk factor in replication studies. These results suggest that failure to replicate an independent genetic effect may provide important clues about the complexity of the underlying genetic architecture. We recommend that polymorphisms that fail to replicate be checked for interactions with other polymorphisms, particularly when samples are collected from groups with distinct ethnic backgrounds or different geographic regions. PMID:19503614

Diet, Cardiometabolic Factors and Type-2 Diabetes Mellitus: The Role of Genetics.

PubMed

Marcadenti, Aline

2016-01-01

Type 2 diabetes mellitus (T2DM) is a highly prevalent condition and is associated with a number of metabolic risk factors such as excess of weight, impaired lipid profile and higher levels of blood pressure. As other complex diseases, it is strongly related to an environmental component such as sedentarism and unhealthy diet, and also to a genetic component. A cluster of variants (polymorphisms) in a large number of genes seem to interact with nutrients/dietary factors in modulating cardiometabolic parameters in healthy individuals. The role of total calories intake and also different kind of carbohydrates and dietary fats in worsening the excess of weight and/or metabolic profile in patients with diabetes is well known, but the extent to which genetic factors can modify these associations is not yet fully understood. Therefore, the aim of this mini-review is to discuss the interaction of genetics and diet in the T2DM setting, since both are strongly involved in the genesis and development of the disease.

The Effect of PCDH15 Gene Variations on the Risk of Noise-induced Hearing Loss in a Chinese Population.

PubMed

Xu, Xiang Rong; Wang, Jing Jing; Yang, Qiu Yue; Jiao, Jie; He, Li Hua; Yu, Shan Fa; Gu, Gui Zhen; Chen, Guo Shun; Zhou, Wen Hui; Wu, Hui; Li, Yan Hong; Zhang, Huan Ling; Zhang, Zeng Rui; Jin, Xian Ning

2017-02-01

Noise-induced hearing loss (NIHL) is a complex disease caused by interactions between environmental and genetic factors. This study investigated whether genetic variability in protocadherin related 15 (PCDH15) underlies an increased susceptibility to the development of NIHL in a Chinese population. The results showed that compared with the TT genotype of rs11004085, CT/CC genotypes were associated with an increased risk of NIHL [adjusted odds ratio (OR) = 2.64; 95% confidence interval (CI): 1.14-6.11, P = 0.024]. Additionally, significant interactions between the rs11004085 and rs978842 genetic variations and noise exposure were observed in the high-level exposure groups (P < 0.05). Furthermore, the risk haplotype TAGCC was observed when combined with higher levels of noise exposure (P < 0.05). Thus, our study confirms that genetic variations in PCDH15 modify the susceptibility to NIHL development in humans. Copyright © 2017 The Editorial Board of Biomedical and Environmental Sciences. Published by China CDC. All rights reserved.

Gene by Social-Context Interactions for Number of Sexual Partners Among White Male Youths: Genetics-informed Sociology

PubMed Central

Guo, Guang; Tong, Yuying; Cai, Tianji

2010-01-01

In this study, we set out to investigate whether introducing molecular genetic measures into an analysis of sexual partner variety will yield novel sociological insights. The data source is the white male DNA sample in the National Longitudinal Study of Adolescent Health. Our empirical analysis has produced a robust protective effect of the 9R/9R genotype relative to the Any10R genotype in the dopamine transporter gene (DAT1). The gene-environment interaction analysis demonstrates that the protective effect of 9R/9R tends to be lost in schools in which higher proportions of students start having sex early or among those with relatively low levels of cognitive ability. Our genetics-informed sociological analysis suggests that the “one size” of a single social theory may not fit all. Explaining a human trait or behavior may require a theory that accommodates the complex interplay between social contextual and individual influences and genetic predispositions. PMID:19569400

An evolutionary algorithm that constructs recurrent neural networks.

PubMed

Angeline, P J; Saunders, G M; Pollack, J B

1994-01-01

Standard methods for simultaneously inducing the structure and weights of recurrent neural networks limit every task to an assumed class of architectures. Such a simplification is necessary since the interactions between network structure and function are not well understood. Evolutionary computations, which include genetic algorithms and evolutionary programming, are population-based search methods that have shown promise in many similarly complex tasks. This paper argues that genetic algorithms are inappropriate for network acquisition and describes an evolutionary program, called GNARL, that simultaneously acquires both the structure and weights for recurrent networks. GNARL's empirical acquisition method allows for the emergence of complex behaviors and topologies that are potentially excluded by the artificial architectural constraints imposed in standard network induction methods.

Dissection of Host Susceptibility to Bacterial Infections and Its Toxins.

PubMed

Nashef, Aysar; Agbaria, Mahmoud; Shusterman, Ariel; Lorè, Nicola Ivan; Bragonzi, Alessandra; Wiess, Ervin; Houri-Haddad, Yael; Iraqi, Fuad A

2017-01-01

Infection is one of the leading causes of human mortality and morbidity. Exposure to microbial agents is obviously required. However, also non-microbial environmental and host factors play a key role in the onset, development and outcome of infectious disease, resulting in large of clinical variability between individuals in a population infected with the same microbe. Controlled and standardized investigations of the genetics of susceptibility to infectious disease are almost impossible to perform in humans whereas mouse models allow application of powerful genomic techniques to identify and validate causative genes underlying human diseases with complex etiologies. Most of current animal models used in complex traits diseases genetic mapping have limited genetic diversity. This limitation impedes the ability to create incorporated network using genetic interactions, epigenetics, environmental factors, microbiota, and other phenotypes. A novel mouse genetic reference population for high-resolution mapping and subsequently identifying genes underlying the QTL, namely the Collaborative Cross (CC) mouse genetic reference population (GRP) was recently developed. In this chapter, we discuss a variety of approaches using CC mice for mapping genes underlying quantitative trait loci (QTL) to dissect the host response to polygenic traits, including infectious disease caused by bacterial agents and its toxins.

Genetic effects on mating success and partner choice in a social mammal

PubMed Central

Tung, Jenny; Charpentier, Marie JE; Mukherjee, Sayan; Altmann, Jeanne; Alberts, Susan C

2012-01-01

Mating behavior has profound consequences for two phenomena – individual reproductive success and the maintenance of species boundaries – that contribute to evolutionary processes. Studies of mating behavior in relation to individual reproductive success are common in many species, but studies of mating behavior in relation to genetic variation and species boundaries are less commonly conducted in socially complex species. Here, we leveraged extensive observations of a wild yellow baboon (Papio cynocephalus) population that has experienced recent gene flow from a close sister taxon, the anubis baboon (Papio anubis), to examine how admixture-related genetic background affects mating behavior. We identified novel effects of genetic background on mating patterns, including an advantage accruing to anubis-like males and assortative mating among both yellow-like and anubis-like pairs. These genetic effects acted alongside social dominance rank, inbreeding avoidance, and age to produce highly nonrandom mating patterns. Our results suggest that this population may be undergoing admixture-related evolutionary change, driven in part by nonrandom mating. However, the strength of the genetic effects is mediated by behavioral plasticity and social interactions, emphasizing the strong influence of social context on mating behavior in socially complex species. PMID:22673655

Cultural evolutionary theory: How culture evolves and why it matters

PubMed Central

Creanza, Nicole; Kolodny, Oren; Feldman, Marcus W.

2017-01-01

Human cultural traits—behaviors, ideas, and technologies that can be learned from other individuals—can exhibit complex patterns of transmission and evolution, and researchers have developed theoretical models, both verbal and mathematical, to facilitate our understanding of these patterns. Many of the first quantitative models of cultural evolution were modified from existing concepts in theoretical population genetics because cultural evolution has many parallels with, as well as clear differences from, genetic evolution. Furthermore, cultural and genetic evolution can interact with one another and influence both transmission and selection. This interaction requires theoretical treatments of gene–culture coevolution and dual inheritance, in addition to purely cultural evolution. In addition, cultural evolutionary theory is a natural component of studies in demography, human ecology, and many other disciplines. Here, we review the core concepts in cultural evolutionary theory as they pertain to the extension of biology through culture, focusing on cultural evolutionary applications in population genetics, ecology, and demography. For each of these disciplines, we review the theoretical literature and highlight relevant empirical studies. We also discuss the societal implications of the study of cultural evolution and of the interactions of humans with one another and with their environment. PMID:28739941

Piecemeal Buildup of the Genetic Code, Ribosomes, and Genomes from Primordial tRNA Building Blocks

PubMed Central

Caetano-Anollés, Derek; Caetano-Anollés, Gustavo

2016-01-01

The origin of biomolecular machinery likely centered around an ancient and central molecule capable of interacting with emergent macromolecular complexity. tRNA is the oldest and most central nucleic acid molecule of the cell. Its co-evolutionary interactions with aminoacyl-tRNA synthetase protein enzymes define the specificities of the genetic code and those with the ribosome their accurate biosynthetic interpretation. Phylogenetic approaches that focus on molecular structure allow reconstruction of evolutionary timelines that describe the history of RNA and protein structural domains. Here we review phylogenomic analyses that reconstruct the early history of the synthetase enzymes and the ribosome, their interactions with RNA, and the inception of amino acid charging and codon specificities in tRNA that are responsible for the genetic code. We also trace the age of domains and tRNA onto ancient tRNA homologies that were recently identified in rRNA. Our findings reveal a timeline of recruitment of tRNA building blocks for the formation of a functional ribosome, which holds both the biocatalytic functions of protein biosynthesis and the ability to store genetic memory in primordial RNA genomic templates. PMID:27918435

Piecemeal Buildup of the Genetic Code, Ribosomes, and Genomes from Primordial tRNA Building Blocks.

PubMed

Caetano-Anollés, Derek; Caetano-Anollés, Gustavo

2016-12-02

The origin of biomolecular machinery likely centered around an ancient and central molecule capable of interacting with emergent macromolecular complexity. tRNA is the oldest and most central nucleic acid molecule of the cell. Its co-evolutionary interactions with aminoacyl-tRNA synthetase protein enzymes define the specificities of the genetic code and those with the ribosome their accurate biosynthetic interpretation. Phylogenetic approaches that focus on molecular structure allow reconstruction of evolutionary timelines that describe the history of RNA and protein structural domains. Here we review phylogenomic analyses that reconstruct the early history of the synthetase enzymes and the ribosome, their interactions with RNA, and the inception of amino acid charging and codon specificities in tRNA that are responsible for the genetic code. We also trace the age of domains and tRNA onto ancient tRNA homologies that were recently identified in rRNA. Our findings reveal a timeline of recruitment of tRNA building blocks for the formation of a functional ribosome, which holds both the biocatalytic functions of protein biosynthesis and the ability to store genetic memory in primordial RNA genomic templates.

Cultural evolutionary theory: How culture evolves and why it matters.

PubMed

Creanza, Nicole; Kolodny, Oren; Feldman, Marcus W

2017-07-24

Human cultural traits-behaviors, ideas, and technologies that can be learned from other individuals-can exhibit complex patterns of transmission and evolution, and researchers have developed theoretical models, both verbal and mathematical, to facilitate our understanding of these patterns. Many of the first quantitative models of cultural evolution were modified from existing concepts in theoretical population genetics because cultural evolution has many parallels with, as well as clear differences from, genetic evolution. Furthermore, cultural and genetic evolution can interact with one another and influence both transmission and selection. This interaction requires theoretical treatments of gene-culture coevolution and dual inheritance, in addition to purely cultural evolution. In addition, cultural evolutionary theory is a natural component of studies in demography, human ecology, and many other disciplines. Here, we review the core concepts in cultural evolutionary theory as they pertain to the extension of biology through culture, focusing on cultural evolutionary applications in population genetics, ecology, and demography. For each of these disciplines, we review the theoretical literature and highlight relevant empirical studies. We also discuss the societal implications of the study of cultural evolution and of the interactions of humans with one another and with their environment.

Assessment of the reliability of protein-protein interactions and protein function prediction.

PubMed

Deng, Minghua; Sun, Fengzhu; Chen, Ting

2003-01-01

As more and more high-throughput protein-protein interaction data are collected, the task of estimating the reliability of different data sets becomes increasingly important. In this paper, we present our study of two groups of protein-protein interaction data, the physical interaction data and the protein complex data, and estimate the reliability of these data sets using three different measurements: (1) the distribution of gene expression correlation coefficients, (2) the reliability based on gene expression correlation coefficients, and (3) the accuracy of protein function predictions. We develop a maximum likelihood method to estimate the reliability of protein interaction data sets according to the distribution of correlation coefficients of gene expression profiles of putative interacting protein pairs. The results of the three measurements are consistent with each other. The MIPS protein complex data have the highest mean gene expression correlation coefficients (0.256) and the highest accuracy in predicting protein functions (70% sensitivity and specificity), while Ito's Yeast two-hybrid data have the lowest mean (0.041) and the lowest accuracy (15% sensitivity and specificity). Uetz's data are more reliable than Ito's data in all three measurements, and the TAP protein complex data are more reliable than the HMS-PCI data in all three measurements as well. The complex data sets generally perform better in function predictions than do the physical interaction data sets. Proteins in complexes are shown to be more highly correlated in gene expression. The results confirm that the components of a protein complex can be assigned to functions that the complex carries out within a cell. There are three interaction data sets different from the above two groups: the genetic interaction data, the in-silico data and the syn-express data. Their capability of predicting protein functions generally falls between that of the Y2H data and that of the MIPS protein complex data. The supplementary information is available at the following Web site: http://www-hto.usc.edu/-msms/AssessInteraction/.

Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean.

PubMed

Fang, Chao; Ma, Yanming; Wu, Shiwen; Liu, Zhi; Wang, Zheng; Yang, Rui; Hu, Guanghui; Zhou, Zhengkui; Yu, Hong; Zhang, Min; Pan, Yi; Zhou, Guoan; Ren, Haixiang; Du, Weiguang; Yan, Hongrui; Wang, Yanping; Han, Dezhi; Shen, Yanting; Liu, Shulin; Liu, Tengfei; Zhang, Jixiang; Qin, Hao; Yuan, Jia; Yuan, Xiaohui; Kong, Fanjiang; Liu, Baohui; Li, Jiayang; Zhang, Zhiwu; Wang, Guodong; Zhu, Baoge; Tian, Zhixi

2017-08-24

Soybean (Glycine max [L.] Merr.) is one of the most important oil and protein crops. Ever-increasing soybean consumption necessitates the improvement of varieties for more efficient production. However, both correlations among different traits and genetic interactions among genes that affect a single trait pose a challenge to soybean breeding. To understand the genetic networks underlying phenotypic correlations, we collected 809 soybean accessions worldwide and phenotyped them for two years at three locations for 84 agronomic traits. Genome-wide association studies identified 245 significant genetic loci, among which 95 genetically interacted with other loci. We determined that 14 oil synthesis-related genes are responsible for fatty acid accumulation in soybean and function in line with an additive model. Network analyses demonstrated that 51 traits could be linked through the linkage disequilibrium of 115 associated loci and these links reflect phenotypic correlations. We revealed that 23 loci, including the known Dt1, E2, E1, Ln, Dt2, Fan, and Fap loci, as well as 16 undefined associated loci, have pleiotropic effects on different traits. This study provides insights into the genetic correlation among complex traits and will facilitate future soybean functional studies and breeding through molecular design.

Identification of fertiity restores for S male-sterile maize: beyond PPRs

USDA-ARS?s Scientific Manuscript database

Nuclear genes are essential for expression of the mitochondrial genome and for the function of mitochondrial protein complexes. Interaction of the plant mitochondrial and nuclear genetic systems is exemplified by mitochondrial-encoded cytoplasmic male sterility (CMS) under the control of nuclear fe...

Mandible shape in hybrid mice.

PubMed

Renaud, Sabrina; Alibert, Paul; Auffray, Jean-Christophe

2009-09-01

Hybridisation between closely related species is frequently seen as retarding evolutionary divergence and can also promote it by creating novel phenotypes due to new genetic combinations and developmental interactions. We therefore investigated how hybridisation affects the shape of the mouse mandible, a well-known feature in evo-devo studies. Parental groups corresponded to two strains of the European mouse sub-species Mus musculus domesticus and Mus musculus musculus. Parents and hybrids were bred in controlled conditions. The mandibles of F(1) hybrids are mostly intermediate between parental phenotypes as expected for a complex multigenic character. Nevertheless, a transgressive effect as well as an increased phenotypic variance characterise the hybrids. This suggests that hybridisation between the two subspecies could lead to a higher phenotypic variance due to complex interactions among the parental genomes including non-additive genetic effects. The major direction of variance is conserved, however, among hybrids and parent groups. Hybridisation may thus play a role in the production of original transgressive phenotypes occurring following pre-existing patterns of variance.

A Simple and Computationally Efficient Sampling Approach to Covariate Adjustment for Multifactor Dimensionality Reduction Analysis of Epistasis

PubMed Central

Gui, Jiang; Andrew, Angeline S.; Andrews, Peter; Nelson, Heather M.; Kelsey, Karl T.; Karagas, Margaret R.; Moore, Jason H.

2010-01-01

Epistasis or gene-gene interaction is a fundamental component of the genetic architecture of complex traits such as disease susceptibility. Multifactor dimensionality reduction (MDR) was developed as a nonparametric and model-free method to detect epistasis when there are no significant marginal genetic effects. However, in many studies of complex disease, other covariates like age of onset and smoking status could have a strong main effect and may potentially interfere with MDR's ability to achieve its goal. In this paper, we present a simple and computationally efficient sampling method to adjust for covariate effects in MDR. We use simulation to show that after adjustment, MDR has sufficient power to detect true gene-gene interactions. We also compare our method with the state-of-art technique in covariate adjustment. The results suggest that our proposed method performs similarly, but is more computationally efficient. We then apply this new method to an analysis of a population-based bladder cancer study in New Hampshire. PMID:20924193

An overview of the genetic dissection of complex traits.

PubMed

Rao, D C

2008-01-01

Thanks to the recent revolutionary genomic advances such as the International HapMap consortium, resolution of the genetic architecture of common complex traits is beginning to look hopeful. While demonstrating the feasibility of genome-wide association (GWA) studies, the pathbreaking Wellcome Trust Case Control Consortium (WTCCC) study also serves to underscore the critical importance of very large sample sizes and draws attention to potential problems, which need to be addressed as part of the study design. Even the large WTCCC study had vastly inadequate power for several of the associations reported (and confirmed) and, therefore, most of the regions harboring relevant associations may not be identified anytime soon. This chapter provides an overview of some of the key developments in the methodological approaches to genetic dissection of common complex traits. Constrained Bayesian networks are suggested as especially useful for analysis of pathway-based SNPs. Likewise, composite likelihood is suggested as a promising method for modeling complex systems. It discusses the key steps in a study design, with an emphasis on GWA studies. Potential limitations highlighted by the WTCCC GWA study are discussed, including problems associated with massive genotype imputation, analysis of pooled national samples, shared controls, and the critical role of interactions. GWA studies clearly need massive sample sizes that are only possible through genuine collaborations. After all, for common complex traits, the question is not whether we can find some pieces of the puzzle, but how large and what kind of a sample we need to (nearly) solve the genetic puzzle.

Gut-associated microbes of Drosophila melanogaster

PubMed Central

Broderick, Nichole; Lemaitre, Bruno

2012-01-01

There is growing interest in using Drosophila melanogaster to elucidate mechanisms that underlie the complex relationships between a host and its microbiota. In addition to the many genetic resources and tools Drosophila provides, its associated microbiota is relatively simple (1–30 taxa), in contrast to the complex diversity associated with vertebrates (> 500 taxa). These attributes highlight the potential of this system to dissect the complex cellular and molecular interactions that occur between a host and its microbiota. In this review, we summarize what is known regarding the composition of gut-associated microbes of Drosophila and their impact on host physiology. We also discuss these interactions in the context of their natural history and ecology and describe some recent insights into mechanisms by which Drosophila and its gut microbiota interact. “Workers with Drosophila have been considered fortunate in that they deal with the first multicellular invertebrate to be cultured monoxenically (Delcourt and Guyenot, 1910); the first to be handled axenically on a semisynthetic diet (Guyenot, 1917); and the first to be grown on a defined diet (Schultz et al., 1946). This list of advantages is somewhat embarrassing, since it implies an interest in nutrition that, in reality, was only secondary. The very first studies were concerned with the reduction of variability in genetic experiments (Delcourt and Guyenot, 1910) and standardization of the nutritional environment.” -James Sang, 1959 Ann NY Acad 1 PMID:22572876

The evolution of phenotypic integration: How directional selection reshapes covariation in mice.

PubMed

Penna, Anna; Melo, Diogo; Bernardi, Sandra; Oyarzabal, Maria Inés; Marroig, Gabriel

2017-10-01

Variation is the basis for evolution, and understanding how variation can evolve is a central question in biology. In complex phenotypes, covariation plays an even more important role, as genetic associations between traits can bias and alter evolutionary change. Covariation can be shaped by complex interactions between loci, and this genetic architecture can also change during evolution. In this article, we analyzed mouse lines experimentally selected for changes in size to address the question of how multivariate covariation changes under directional selection, as well as to identify the consequences of these changes to evolution. Selected lines showed a clear restructuring of covariation in their cranium and, instead of depleting their size variation, these lines increased their magnitude of integration and the proportion of variation associated with the direction of selection. This result is compatible with recent theoretical works on the evolution of covariation that take the complexities of genetic architecture into account. This result also contradicts the traditional view of the effects of selection on available covariation and suggests a much more complex view of how populations respond to selection. © 2017 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.

Shadows of complexity: what biological networks reveal about epistasis and pleiotropy

PubMed Central

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

Integrating modelling and phenotyping approaches to identify and screen complex traits - Illustration for transpiration efficiency in cereals.

PubMed

Chenu, K; van Oosterom, E J; McLean, G; Deifel, K S; Fletcher, A; Geetika, G; Tirfessa, A; Mace, E S; Jordan, D R; Sulman, R; Hammer, G L

2018-02-21

Following advances in genetics, genomics, and phenotyping, trait selection in breeding is limited by our ability to understand interactions within the plants and with their environments, and to target traits of most relevance for the target population of environments. We propose an integrated approach that combines insights from crop modelling, physiology, genetics, and breeding to identify traits valuable for yield gain in the target population of environments, develop relevant high-throughput phenotyping platforms, and identify genetic controls and their values in production environments. This paper uses transpiration efficiency (biomass produced per unit of water used) as an example of a complex trait of interest to illustrate how the approach can guide modelling, phenotyping, and selection in a breeding program. We believe that this approach, by integrating insights from diverse disciplines, can increase the resource use efficiency of breeding programs for improving yield gains in target populations of environments.

Complexity of generic biochemical circuits: topology versus strength of interactions.

PubMed

Tikhonov, Mikhail; Bialek, William

2016-12-06

The historical focus on network topology as a determinant of biological function is still largely maintained today, illustrated by the rise of structure-only approaches to network analysis. However, biochemical circuits and genetic regulatory networks are defined both by their topology and by a multitude of continuously adjustable parameters, such as the strength of interactions between nodes, also recognized as important. Here we present a class of simple perceptron-based Boolean models within which comparing the relative importance of topology versus interaction strengths becomes a quantitatively well-posed problem. We quantify the intuition that for generic networks, optimization of interaction strengths is a crucial ingredient of achieving high complexity, defined here as the number of fixed points the network can accommodate. We propose a new methodology for characterizing the relative role of parameter optimization for topologies of a given class.

SIMILAR PATTERNS OF MITOCHONDRIAL VULNERABILITY AND RESCUE INDUCED BY GENETIC MODIFICATION OF α-SYNUCLEIN, PARKIN AND DJ-1 IN C. ELEGANS*

PubMed Central

Westlund, Beth; Perier, Celine; Burnam, Lucinda; Sluder, Anne; Hoener, Marius; Rodrigues, Cecilia MP; Alfonso, Aixa; Steer, Clifford; Liu, Leo; Przedborski, Serge; Wolozin, Benjamin

2014-01-01

How genetic and environmental factors interact in Parkinson’s disease is poorly understood. We have now compared the patterns of vulnerability and rescue of C. elegans with genetic modifications of three different genetic factors implicated in PD. We observed that expressing α-synuclein, deleting parkin (K08E3.7) or knocking down DJ-1 (B0432.2) or parkin, produces similar patterns of pharmacological vulnerability and rescue. C. elegans lines with these genetic changes were more vulnerable than non-transgenic nematodes to mitochondrial complex I inhibitors, including rotenone, fenperoximate, pyridaben or stigmatellin. In contrast, the genetic manipulations did not increase sensitivity to paraquat, sodium azide, divalent metal ions (FeII or CuII) or etoposide compared to non-transgenic nematodes. Each of the PD-related lines was also partially rescued by the anti-oxidant probucol, the mitochondrial complex II activator, D-β-hydroxybutyrate (DβHB) or the anti-apoptotic bile acid tauroursodeoxycholic acid (TUDCA). Complete protection in all lines was achieved by combining DβHB with TUDCA but not with probucol. These results show that diverse PD-related genetic modifications disrupt mitochondrial function in C. elegans, and they raise the possibility that mitochondrial disruption is a pathway shared in common by many types of familial PD. PMID:16239214

Inherited epilepsy in dogs.

PubMed

Ekenstedt, Kari J; Oberbauer, Anita M

2013-05-01

Epilepsy is the most common neurologic disease in dogs and many forms are considered to have a genetic basis. In contrast, some seizure disorders are also heritable, but are not technically defined as epilepsy. Investigation of true canine epilepsies has uncovered genetic associations in some cases, however, many remain unexplained. Gene mutations have been described for 2 forms of canine epilepsy: primary epilepsy (PE) and progressive myoclonic epilepsies. To date, 9 genes have been described to underlie progressive myoclonic epilepsies in several dog breeds. Investigations into genetic PE have been less successful, with only 1 causative gene described. Genetic testing as an aid to diagnosis, prognosis, and breeding decisions is available for these 10 forms. Additional studies utilizing genome-wide tools have identified PE loci of interest; however, specific genetic tests are not yet developed. Many studies of dog breeds with PE have failed to identify genes or loci of interest, suggesting that, similar to what is seen in many human genetic epilepsies, inheritance is likely complex, involving several or many genes, and reflective of environmental interactions. An individual dog's response to therapeutic intervention for epilepsy may also be genetically complex. Although the field of inherited epilepsy has faced challenges, particularly with PE, newer technologies contribute to further advances. © 2013 Elsevier Inc. All rights reserved.

How spatio-temporal habitat connectivity affects amphibian genetic structure

PubMed Central

Watts, Alexander G.; Schlichting, Peter E.; Billerman, Shawn M.; Jesmer, Brett R.; Micheletti, Steven; Fortin, Marie-Josée; Funk, W. Chris; Hapeman, Paul; Muths, Erin; Murphy, Melanie A.

2015-01-01

Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations. PMID:26442094

How spatio-temporal habitat connectivity affects amphibian genetic structure

USGS Publications Warehouse

Watts, Alexander G.; Schlichting, P; Billerman, S; Jesmer, B; Micheletti, S; Fortin, M.-J.; Funk, W.C.; Hapeman, P; Muths, Erin L.; Murphy, M.A.

2015-01-01

Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations.

A Parallel Genetic Algorithm to Discover Patterns in Genetic Markers that Indicate Predisposition to Multifactorial Disease

PubMed Central

Rausch, Tobias; Thomas, Alun; Camp, Nicola J.; Cannon-Albright, Lisa A.; Facelli, Julio C.

2008-01-01

This paper describes a novel algorithm to analyze genetic linkage data using pattern recognition techniques and genetic algorithms (GA). The method allows a search for regions of the chromosome that may contain genetic variations that jointly predispose individuals for a particular disease. The method uses correlation analysis, filtering theory and genetic algorithms (GA) to achieve this goal. Because current genome scans use from hundreds to hundreds of thousands of markers, two versions of the method have been implemented. The first is an exhaustive analysis version that can be used to visualize, explore, and analyze small genetic data sets for two marker correlations; the second is a GA version, which uses a parallel implementation allowing searches of higher-order correlations in large data sets. Results on simulated data sets indicate that the method can be informative in the identification of major disease loci and gene-gene interactions in genome-wide linkage data and that further exploration of these techniques is justified. The results presented for both variants of the method show that it can help genetic epidemiologists to identify promising combinations of genetic factors that might predispose to complex disorders. In particular, the correlation analysis of IBD expression patterns might hint to possible gene-gene interactions and the filtering might be a fruitful approach to distinguish true correlation signals from noise. PMID:18547558

Innovative Tools and Technology for Analysis of Single Cells and Cell-Cell Interaction.

PubMed

Konry, Tania; Sarkar, Saheli; Sabhachandani, Pooja; Cohen, Noa

2016-07-11

Heterogeneity in single-cell responses and intercellular interactions results from complex regulation of cell-intrinsic and environmental factors. Single-cell analysis allows not only detection of individual cellular characteristics but also correlation of genetic content with phenotypic traits in the same cell. Technological advances in micro- and nanofabrication have benefited single-cell analysis by allowing precise control of the localized microenvironment, cell manipulation, and sensitive detection capabilities. Additionally, microscale techniques permit rapid, high-throughput, multiparametric screening that has become essential for -omics research. This review highlights innovative applications of microscale platforms in genetic, proteomic, and metabolic detection in single cells; cell sorting strategies; and heterotypic cell-cell interaction. We discuss key design aspects of single-cell localization and isolation in microfluidic systems, dynamic and endpoint analyses, and approaches that integrate highly multiplexed detection of various intracellular species.

Stoichiometric differences in food quality: impacts on genetic diversity and the coexistence of aquatic herbivores in a Daphnia hybrid complex.

PubMed

Weider, Lawrence J; Jeyasingh, Punidan D; Looper, Karen G

2008-11-01

The maintenance of genetic and species diversity in an assemblage of genotypes (clones) in the Daphnia pulex species complex (Cladocera: Anomopoda) in response to variation in the carbon:phosphorus ratio (quantity and quality) of the green alga, Scenedesmus acutus, was examined in a 90-day microcosm competition experiment. Results indicated that mixed assemblages of seven distinct genotypes (representing clonal lineages of D. pulex, D. pulicaria and interspecific hybrids) showed rapid loss of genetic diversity in all treatments (2 x 2 factorial design, high vs. low quantity, and high vs. low quality). However, the erosion of diversity (measured as the effective number of clones) was slowest under the poorest food conditions (i.e., low quantity, low quality) and by the conclusion of the experiment (90 days) had resulted in the (low, low) treatment having significantly greater genetic diversity than the other three treatments. In addition, significant genotype (clone) x (food) environment interactions were observed, with a different predominant species/clone found under low food quality versus high food quality (no significant differences were detected for the two food quantities). A clone of D. pulex displaced the other clones under low food quality conditions, while a clone of D. pulicaria displaced the other clones in the high food quality treatments. Subsequent life-history experiments were not sufficient to predict the outcome of competitive interactions among members of this clonal assemblage. Our results suggest that genetic diversity among herbivore species such as Daphnia may be impacted not only by differences in food quantity but also by those in food quality and could be important in the overall maintenance of genetic diversity in natural populations.

Variability in the efficacy of psychopharmaceuticals: contributions from pharmacogenomics, ethnopsychopharmacology, and psychological and psychiatric anthropologies.

PubMed

Ninnemann, Kristi M

2012-03-01

Psychological and psychiatric anthropology have long questioned the universality of psychiatric diagnoses, bringing to light the fluidity of mental disorder, and recognizing that the experience and expression of psychopathology is influenced by complex and interacting genetic, environmental, and cultural factors. The majority of our discussions, however, have remained centered around the role of culture in shaping mental illness: drawing attention to subjective experiences of mental illness and culturally patterned modes of symptom presentation, and interrogating the cogency of universal diagnostic rubrics. Psychological and psychiatric anthropology have yet to robustly engage the broadly assumed universal validity of psychiatric medications and the ways in which they are prescribed and experienced. This article provides an introduction into the fields of pharmacogenomics and ethnopsychopharmacology, areas of inquiry seeking to understand the ways in which genetic variability occurring between, and within, large population groups influences individual ability to metabolize psychotropic medications. This piece further addresses the complex issue of psychopharmaceutical efficacy, stressing the ways in which, just as with psychopathology, medications and their outcomes are likewise influenced by the complex interactions of genes, environment, and culture. Lastly, ways in which anthropology can and should engage with the growing fields of pharmacogenomics and ethnopsychopharmacology are suggested.

Animal models of gene-environment interaction in schizophrenia: a dimensional perspective

PubMed Central

Ayhan, Yavuz; McFarland, Ross; Pletnikov, Mikhail V.

2015-01-01

Schizophrenia has long been considered as a disorder with multifactorial origins. Recent discoveries have advanced our understanding of the genetic architecture of the disease. However, even with the increase of identified risk variants, heritability estimates suggest an important contribution of non-genetic factors. Various environmental risk factors have been proposed to play a role in the etiopathogenesis of schizophrenia. These include season of birth, maternal infections, obstetric complications, adverse events at early childhood, and drug abuse. Despite the progress in identification of genetic and environmental risk factors, we still have a limited understanding of the mechanisms whereby gene-environment interactions (GxE) operate in schizophrenia and psychoses at large. In this review we provide a critical analysis of current animal models of GxE relevant to psychotic disorders and propose that dimensional perspective will advance our understanding of the complex mechanisms of these disorders. PMID:26510407

Challenges in reproducibility of genetic association studies: lessons learned from the obesity field.

PubMed

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.

Sec34p, a Protein Required for Vesicle Tethering to the Yeast Golgi Apparatus, Is in a Complex with Sec35p

PubMed Central

VanRheenen, Susan M.; Cao, Xiaochun; Sapperstein, Stephanie K.; Chiang, Elbert C.; Lupashin, Vladimir V.; Barlowe, Charles; Waters, M. Gerard

1999-01-01

A screen for mutants of Saccharomyces cerevisiae secretory pathway components previously yielded sec34, a mutant that accumulates numerous vesicles and fails to transport proteins from the ER to the Golgi complex at the restrictive temperature (Wuestehube, L.J., R. Duden, A. Eun, S. Hamamoto, P. Korn, R. Ram, and R. Schekman. 1996. Genetics. 142:393–406). We find that SEC34 encodes a novel protein of 93-kD, peripherally associated with membranes. The temperature-sensitive phenotype of sec34-2 is suppressed by the rab GTPase Ypt1p that functions early in the secretory pathway, or by the dominant form of the ER to Golgi complex target-SNARE (soluble N-ethylmaleimide sensitive fusion protein attachment protein receptor)–associated protein Sly1p, Sly1-20p. Weaker suppression is evident upon overexpression of genes encoding the vesicle tethering factor Uso1p or the vesicle-SNAREs Sec22p, Bet1p, or Ykt6p. This genetic suppression profile is similar to that of sec35-1, a mutant allele of a gene encoding an ER to Golgi vesicle tethering factor and, like Sec35p, Sec34p is required in vitro for vesicle tethering. sec34-2 and sec35-1 display a synthetic lethal interaction, a genetic result explained by the finding that Sec34p and Sec35p can interact by two-hybrid analysis. Fractionation of yeast cytosol indicates that Sec34p and Sec35p exist in an ∼750-kD protein complex. Finally, we describe RUD3, a novel gene identified through a genetic screen for multicopy suppressors of a mutation in USO1, which suppresses the sec34-2 mutation as well. PMID:10562277

Polygenic scores predict alcohol problems in an independent sample and show moderation by the environment.

PubMed

Salvatore, Jessica E; Aliev, Fazil; Edwards, Alexis C; Evans, David M; Macleod, John; Hickman, Matthew; Lewis, Glyn; Kendler, Kenneth S; Loukola, Anu; Korhonen, Tellervo; Latvala, Antti; Rose, Richard J; Kaprio, Jaakko; Dick, Danielle M

2014-04-10

Alcohol problems represent a classic example of a complex behavioral outcome that is likely influenced by many genes of small effect. A polygenic approach, which examines aggregate measured genetic effects, can have predictive power in cases where individual genes or genetic variants do not. In the current study, we first tested whether polygenic risk for alcohol problems-derived from genome-wide association estimates of an alcohol problems factor score from the age 18 assessment of the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 4304 individuals of European descent; 57% female)-predicted alcohol problems earlier in development (age 14) in an independent sample (FinnTwin12; n = 1162; 53% female). We then tested whether environmental factors (parental knowledge and peer deviance) moderated polygenic risk to predict alcohol problems in the FinnTwin12 sample. We found evidence for both polygenic association and for additive polygene-environment interaction. Higher polygenic scores predicted a greater number of alcohol problems (range of Pearson partial correlations 0.07-0.08, all p-values ≤ 0.01). Moreover, genetic influences were significantly more pronounced under conditions of low parental knowledge or high peer deviance (unstandardized regression coefficients (b), p-values (p), and percent of variance (R2) accounted for by interaction terms: b = 1.54, p = 0.02, R2 = 0.33%; b = 0.94, p = 0.04, R2 = 0.30%, respectively). Supplementary set-based analyses indicated that the individual top single nucleotide polymorphisms (SNPs) contributing to the polygenic scores were not individually enriched for gene-environment interaction. Although the magnitude of the observed effects are small, this study illustrates the usefulness of polygenic approaches for understanding the pathways by which measured genetic predispositions come together with environmental factors to predict complex behavioral outcomes.

Genetic adaptation as a biological buffer against climate change: potential and limitations.

PubMed

De Meester, Luc; Stoks, Robby; Brans, Kristien I

2017-11-23

Climate change profoundly impacts ecosystems and their biota, resulting in range shifts, novel interactions, food web alterations, changed intensities of host-parasite interactions, and extinctions. An increasing number of studies documented evolutionary changes in, amongst others, phenology and thermal tolerance. In this opinion paper, we argue that, while evolutionary responses have the potential to provide a buffer against extinctions or range shifts, a number of constraints and complexities blur this simple prediction. First, there are limits to evolutionary potential both in terms of genetic variation and demographic effects, and these limits differ strongly among taxa and populations. Secondly, there can be costs associated with genetic adaptation, such as a reduced evolutionary potential towards other (human-induced) environmental stressors or direct fitness costs due to trade-offs. Third, the differential capacity of taxa to genetically respond to climate change results in novel interactions because different organism groups respond to a different degree with local compared to regional (cf. dispersal and range shift) responses. These complexities result in additional changes in the selection pressures on populations. We conclude that evolution can provide an initial buffer against climate change for some taxa and populations, but does not guarantee their survival. It does not necessarily result in reduced extinction risks across the range of taxa in a region or continent. Yet, considering evolution is crucial, as it is likely to strongly change how biota will respond to climate change and will impact which taxa will be the winners or losers at the local, metacommunity, and regional scales. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Genetic background of osteoporosis.

PubMed

Obermayer-Pietsch, B; Chararas, C; Kotschan, S; Walter, D; Leb, G

2000-01-01

Osteoporosis is a systemic disorder of decreased skeletal mass as measured by bone mineral density (BMD), and disturbed skeletal architecture and function which results in an increased risk for bone fractures with consecutively increased morbidity and mortality. Twin and family studies have shown an important genetic component of BMD of about 40-60%. This exceeds other well known factors influencing BMD such as environmental factors like dietary calcium, physical activity or several drugs and diseases. Therefore, interest increased in the genetic background of bone mineral density. Polymorphisms of the Vitamin D receptor gene were the first to be published in this area. Studies on other loci or candidate genes such as the estrogen receptor gene or the collagen type I alpha1 gene also showed associations with bone mineral density that could explain at least a part of the genetic background of osteoporosis. Recently published data suggest that these genetic markers of bone metabolism are important in interaction with each other or in certain bone-affecting diseases. In the future, genetic studies on osteoporosis will have to screen further relevant genes and markers for bone metabolism as well as to evaluate the complex interactions of genetic influences, so that it would be possible to calculate a patient's individual risk for osteoporosis in the context of environmental influences.

pulver: an R package for parallel ultra-rapid p-value computation for linear regression interaction terms.

PubMed

Molnos, Sophie; Baumbach, Clemens; Wahl, Simone; Müller-Nurasyid, Martina; Strauch, Konstantin; Wang-Sattler, Rui; Waldenberger, Melanie; Meitinger, Thomas; Adamski, Jerzy; Kastenmüller, Gabi; Suhre, Karsten; Peters, Annette; Grallert, Harald; Theis, Fabian J; Gieger, Christian

2017-09-29

Genome-wide association studies allow us to understand the genetics of complex diseases. Human metabolism provides information about the disease-causing mechanisms, so it is usual to investigate the associations between genetic variants and metabolite levels. However, only considering genetic variants and their effects on one trait ignores the possible interplay between different "omics" layers. Existing tools only consider single-nucleotide polymorphism (SNP)-SNP interactions, and no practical tool is available for large-scale investigations of the interactions between pairs of arbitrary quantitative variables. We developed an R package called pulver to compute p-values for the interaction term in a very large number of linear regression models. Comparisons based on simulated data showed that pulver is much faster than the existing tools. This is achieved by using the correlation coefficient to test the null-hypothesis, which avoids the costly computation of inversions. Additional tricks are a rearrangement of the order, when iterating through the different "omics" layers, and implementing this algorithm in the fast programming language C++. Furthermore, we applied our algorithm to data from the German KORA study to investigate a real-world problem involving the interplay among DNA methylation, genetic variants, and metabolite levels. The pulver package is a convenient and rapid tool for screening huge numbers of linear regression models for significant interaction terms in arbitrary pairs of quantitative variables. pulver is written in R and C++, and can be downloaded freely from CRAN at https://cran.r-project.org/web/packages/pulver/ .

Nutrigenetics/Nutrigenomics.

PubMed

Simopoulos, Artemis P

2010-01-01

All diseases have a genetic predisposition. Genome-wide association studies (GWASs) by large international consortia are discovering genetic variants that contribute to complex diseases. However, nutrient information is missing, which is essential for the development of dietary advice for prevention and management of disease. Nutrigenetics/nutrigenomics studies provide data on mechanisms of nutrient and gene interactions in health and disease needed for personalized nutrition. A process will be needed to define when gene-nutrient-disease associations are ready to be evaluated as potential tools to improve public health.

Integrated Analysis of Genetic and Proteomic Data Identifies Biomarkers Associated with Adverse Events Following Smallpox Vaccination

EPA Science Inventory

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...

SNPs located at CpG sites modulate genome-epigenome interaction

USDA-ARS?s Scientific Manuscript database

DNA methylation is an important molecular-level phenotype that links genotypes and complex disease traits. Previous studies have found local correlation between genetic variants and DNA methylation levels (cis-meQTLs). However, general mechanisms underlying cis-meQTLs are unclear. We conducted a cis...

Japanese vs. Caucasian Intelligence and Social Attainment.

ERIC Educational Resources Information Center

Nagoshi, Craig T.

1998-01-01

Summarizes a series of studies from the Hawaii Family Study of Cognition on possible genetic and social environmental determinants of individual differences in and racial/ethnic differences between groups on intelligence and attainment. These studies, which focused on Japanese and Caucasian Americans, illustrate the complex, interactive, and…

A systems-genetics approach and data mining tool to assist in the discovery of genes underlying complex traits in Oryza sativa.

PubMed

Ficklin, Stephen P; Feltus, Frank Alex

2013-01-01

Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with significant overlap with blast disease resistance.

A Systems-Genetics Approach and Data Mining Tool to Assist in the Discovery of Genes Underlying Complex Traits in Oryza sativa

PubMed Central

Ficklin, Stephen P.; Feltus, Frank Alex

2013-01-01

Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with significant overlap with blast disease resistance. PMID:23874666

Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae

PubMed Central

Reguly, Teresa; Breitkreutz, Ashton; Boucher, Lorrie; Breitkreutz, Bobby-Joe; Hon, Gary C; Myers, Chad L; Parsons, Ainslie; Friesen, Helena; Oughtred, Rose; Tong, Amy; Stark, Chris; Ho, Yuen; Botstein, David; Andrews, Brenda; Boone, Charles; Troyanskya, Olga G; Ideker, Trey; Dolinski, Kara; Batada, Nizar N; Tyers, Mike

2006-01-01

Background The study of complex biological networks and prediction of gene function has been enabled by high-throughput (HTP) methods for detection of genetic and protein interactions. Sparse coverage in HTP datasets may, however, distort network properties and confound predictions. Although a vast number of well substantiated interactions are recorded in the scientific literature, these data have not yet been distilled into networks that enable system-level inference. Results We describe here a comprehensive database of genetic and protein interactions, and associated experimental evidence, for the budding yeast Saccharomyces cerevisiae, as manually curated from over 31,793 abstracts and online publications. This literature-curated (LC) dataset contains 33,311 interactions, on the order of all extant HTP datasets combined. Surprisingly, HTP protein-interaction datasets currently achieve only around 14% coverage of the interactions in the literature. The LC network nevertheless shares attributes with HTP networks, including scale-free connectivity and correlations between interactions, abundance, localization, and expression. We find that essential genes or proteins are enriched for interactions with other essential genes or proteins, suggesting that the global network may be functionally unified. This interconnectivity is supported by a substantial overlap of protein and genetic interactions in the LC dataset. We show that the LC dataset considerably improves the predictive power of network-analysis approaches. The full LC dataset is available at the BioGRID () and SGD () databases. Conclusion Comprehensive datasets of biological interactions derived from the primary literature provide critical benchmarks for HTP methods, augment functional prediction, and reveal system-level attributes of biological networks. PMID:16762047

LEAP: biomarker inference through learning and evaluating association patterns.

PubMed

Jiang, Xia; Neapolitan, Richard E

2015-03-01

Single nucleotide polymorphism (SNP) high-dimensional datasets are available from Genome Wide Association Studies (GWAS). Such data provide researchers opportunities to investigate the complex genetic basis of diseases. Much of genetic risk might be due to undiscovered epistatic interactions, which are interactions in which combination of several genes affect disease. Research aimed at discovering interacting SNPs from GWAS datasets proceeded in two directions. First, tools were developed to evaluate candidate interactions. Second, algorithms were developed to search over the space of candidate interactions. Another problem when learning interacting SNPs, which has not received much attention, is evaluating how likely it is that the learned SNPs are associated with the disease. A complete system should provide this information as well. We develop such a system. Our system, called LEAP, includes a new heuristic search algorithm for learning interacting SNPs, and a Bayesian network based algorithm for computing the probability of their association. We evaluated the performance of LEAP using 100 1,000-SNP simulated datasets, each of which contains 15 SNPs involved in interactions. When learning interacting SNPs from these datasets, LEAP outperformed seven others methods. Furthermore, only SNPs involved in interactions were found to be probable. We also used LEAP to analyze real Alzheimer's disease and breast cancer GWAS datasets. We obtained interesting and new results from the Alzheimer's dataset, but limited results from the breast cancer dataset. We conclude that our results support that LEAP is a useful tool for extracting candidate interacting SNPs from high-dimensional datasets and determining their probability. © 2015 The Authors. *Genetic Epidemiology published by Wiley Periodicals, Inc.

Genetic mouse models of brain ageing and Alzheimer's disease.

PubMed

Bilkei-Gorzo, Andras

2014-05-01

Progression of brain ageing is influenced by a complex interaction of genetic and environmental factors. Analysis of genetically modified animals with uniform genetic backgrounds in a standardised, controlled environment enables the dissection of critical determinants of brain ageing on a molecular level. Human and animal studies suggest that increased load of damaged macromolecules, efficacy of DNA maintenance, mitochondrial activity, and cellular stress defences are critical determinants of brain ageing. Surprisingly, mouse lines with genetic impairment of anti-oxidative capacity generally did not show enhanced cognitive ageing but rather an increased sensitivity to oxidative challenge. Mouse lines with impaired mitochondrial activity had critically short life spans or severe and rapidly progressing neurodegeneration. Strains with impaired clearance in damaged macromolecules or defects in the regulation of cellular stress defences showed alterations in the onset and progression of cognitive decline. Importantly, reduced insulin/insulin-like growth factor signalling generally increased life span but impaired cognitive functions revealing a complex interaction between ageing of the brain and of the body. Brain ageing is accompanied by an increased risk of developing Alzheimer's disease. Transgenic mouse models expressing high levels of mutant human amyloid precursor protein showed a number of symptoms and pathophysiological processes typical for early phase of Alzheimer's disease. Generally, therapeutic strategies effective against Alzheimer's disease in humans were also active in the Tg2576, APP23, APP/PS1 and 5xFAD lines, but a large number of false positive findings were also reported. The 3xtg AD model likely has the highest face and construct validity but further studies are needed. Copyright © 2013 Elsevier Inc. All rights reserved.

Cdt1p, through its interaction with Mcm6p, is required for the formation, nuclear accumulation and chromatin loading of the MCM complex.

PubMed

Wu, Rentian; Wang, Jiafeng; Liang, Chun

2012-01-01

Regulation of DNA replication initiation is essential for the faithful inheritance of genetic information. Replication initiation is a multi-step process involving many factors including ORC, Cdt1p, Mcm2-7p and other proteins that bind to replication origins to form a pre-replicative complex (pre-RC). As a prerequisite for pre-RC assembly, Cdt1p and the Mcm2-7p heterohexameric complex accumulate in the nucleus in G1 phase in an interdependent manner in budding yeast. However, the nature of this interdependence is not clear, nor is it known whether Cdt1p is required for the assembly of the MCM complex. In this study, we provide the first evidence that Cdt1p, through its interaction with Mcm6p with the C-terminal regions of the two proteins, is crucial for the formation of the MCM complex in both the cytoplasm and nucleoplasm. We demonstrate that disruption of the interaction between Cdt1p and Mcm6p prevents the formation of the MCM complex, excludes Mcm2-7p from the nucleus, and inhibits pre-RC assembly and DNA replication. Our findings suggest a function for Cdt1p in promoting the assembly of the MCM complex and maintaining its integrity by interacting with Mcm6p.

Gene-Diet Interactions in Type 2 Diabetes: The Chicken and Egg Debate

PubMed Central

Ortega, Ángeles; Berná, Genoveva; Rojas, Anabel; Martín, Franz; Soria, Bernat

2017-01-01

Consistent evidence from both experimental and human studies indicates that Type 2 diabetes mellitus (T2DM) is a complex disease resulting from the interaction of genetic, epigenetic, environmental, and lifestyle factors. Nutrients and dietary patterns are important environmental factors to consider in the prevention, development and treatment of this disease. Nutritional genomics focuses on the interaction between bioactive food components and the genome and includes studies of nutrigenetics, nutrigenomics and epigenetic modifications caused by nutrients. There is evidence supporting the existence of nutrient-gene and T2DM interactions coming from animal studies and family-based intervention studies. Moreover, many case-control, cohort, cross-sectional cohort studies and clinical trials have identified relationships between individual genetic load, diet and T2DM. Some of these studies were on a large scale. In addition, studies with animal models and human observational studies, in different countries over periods of time, support a causative relationship between adverse nutritional conditions during in utero development, persistent epigenetic changes and T2DM. This review provides comprehensive information on the current state of nutrient-gene interactions and their role in T2DM pathogenesis, the relationship between individual genetic load and diet, and the importance of epigenetic factors in influencing gene expression and defining the individual risk of T2DM. PMID:28574454

Generation of gene-targeted mice using embryonic stem cells derived from a transgenic mouse model of Alzheimer's disease.

PubMed

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.

Gene Expression Profiling in Rodent Models for Schizophrenia

PubMed Central

Schijndel, Jessica E. Van; Martens, Gerard J.M

2010-01-01

The complex neurodevelopmental disorder schizophrenia is thought to be induced by an interaction between predisposing genes and environmental stressors. In order to get a better insight into the aetiology of this complex disorder, animal models have been developed. In this review, we summarize mRNA expression profiling studies on neurodevelopmental, pharmacological and genetic animal models for schizophrenia. We discuss parallels and contradictions among these studies, and propose strategies for future research. PMID:21629445

Cohesin and related coiled-coil domain-containing complexes physically and functionally connect the dots across the genome

PubMed Central

Poon, Betty P.K

2011-01-01

Interactions between genetic regions located across the genome maintain its three-dimensional organization and function. Recent studies point to key roles for a set of coiled-coil domain-containing complexes (cohibin, cohesin, condensin and monopolin) and related factors in the regulation of DNA-DNA connections across the genome. These connections are critical to replication, recombination, gene expression as well as chromosome segregation. PMID:21822055

Molecular Cloning Designer Simulator (MCDS): All-in-one molecular cloning and genetic engineering design, simulation and management software for complex synthetic biology and metabolic engineering projects.

PubMed

Shi, Zhenyu; Vickers, Claudia E

2016-12-01

Molecular Cloning Designer Simulator (MCDS) is a powerful new all-in-one cloning and genetic engineering design, simulation and management software platform developed for complex synthetic biology and metabolic engineering projects. In addition to standard functions, it has a number of features that are either unique, or are not found in combination in any one software package: (1) it has a novel interactive flow-chart user interface for complex multi-step processes, allowing an integrated overview of the whole project; (2) it can perform a user-defined workflow of cloning steps in a single execution of the software; (3) it can handle multiple types of genetic recombineering, a technique that is rapidly replacing classical cloning for many applications; (4) it includes experimental information to conveniently guide wet lab work; and (5) it can store results and comments to allow the tracking and management of the whole project in one platform. MCDS is freely available from https://mcds.codeplex.com.

Complex Patterns of Admixture across the Indonesian Archipelago.

PubMed

Hudjashov, Georgi; Karafet, Tatiana M; Lawson, Daniel J; Downey, Sean; Savina, Olga; Sudoyo, Herawati; Lansing, J Stephen; Hammer, Michael F; Cox, Murray P

2017-10-01

Indonesia, an island nation as large as continental Europe, hosts a sizeable proportion of global human diversity, yet remains surprisingly undercharacterized genetically. Here, we substantially expand on existing studies by reporting genome-scale data for nearly 500 individuals from 25 populations in Island Southeast Asia, New Guinea, and Oceania, notably including previously unsampled islands across the Indonesian archipelago. We use high-resolution analyses of haplotype diversity to reveal fine detail of regional admixture patterns, with a particular focus on the Holocene. We find that recent population history within Indonesia is complex, and that populations from the Philippines made important genetic contributions in the early phases of the Austronesian expansion. Different, but interrelated processes, acted in the east and west. The Austronesian migration took several centuries to spread across the eastern part of the archipelago, where genetic admixture postdates the archeological signal. As with the Neolithic expansion further east in Oceania and in Europe, genetic mixing with local inhabitants in eastern Indonesia lagged behind the arrival of farming populations. In contrast, western Indonesia has a more complicated admixture history shaped by interactions with mainland Asian and Austronesian newcomers, which for some populations occurred more than once. Another layer of complexity in the west was introduced by genetic contact with South Asia and strong demographic events in isolated local groups. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Nature versus nurture in determining athletic ability.

PubMed

Brutsaert, Tom D; Parra, Esteban J

2009-01-01

This chapter provides an overview of the truism that both nature and nurture determine human athletic ability. The major thesis developed is that environmental effects work through the process of growth and development and interact with an individual's genetic background to produce a specific adult phenotype, i.e. an athletic or nonathletic phenotype. On the nature side (genetics), a brief historical review is provided with emphasis on several areas that are likely to command future attention including the rise of genome-wide association as a mapping strategy, the problem of false positives using association approaches, as well as the relatively unknown effects of gene-gene interaction(epistasis), gene-environment interaction, and genome structure on complex trait variance. On the nurture side (environment), common environmental effects such as training-level and sports nutrition are largely ignored in favor of developmental environmental effects that are channeled through growth and development processes. Developmental effects are difficult to distinguish from genetic effects as phenotypic plasticity in response to early life environmental perturbation can produce lasting effects into adulthood. In this regard, the fetal programming (FP) hypothesis is reviewed in some detail as FP provides an excellent example of how developmental effects work and also interact with genetics. In general, FP has well-documented effects on adult body composition and the risk for adult chronic disease, but there is emerging evidence that FP affects human athletic performance as well. 2009 S. Karger AG, Basel

Genetic Mechanisms Leading to Sex Differences Across Common Diseases and Anthropometric Traits.

PubMed

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.

Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits.

PubMed

Yadav, Anupama; Dhole, Kaustubh; Sinha, Himanshu

2016-12-01

Cryptic genetic variation (CGV) refers to genetic variants whose effects are buffered in most conditions but manifest phenotypically upon specific genetic and environmental perturbations. Despite having a central role in adaptation, contribution of CGV to regulation of quantitative traits is unclear. Instead, a relatively simplistic architecture of additive genetic loci is known to regulate phenotypic variation in most traits. In this paper, we investigate the regulation of CGV and its implication on the genetic architecture of quantitative traits at a genome-wide level. We use a previously published dataset of biparental recombinant population of Saccharomyces cerevisiae phenotyped in 34 diverse environments to perform single locus, two-locus, and covariance mapping. We identify loci that have independent additive effects as well as those which regulate the phenotypic manifestation of other genetic variants (variance QTL). We find that whereas additive genetic variance is predominant, a higher order genetic interaction network regulates variation in certain environments. Despite containing pleiotropic loci, with effects across environments, these genetic networks are highly environment specific. CGV is buffered under most allelic combinations of these networks and perturbed only in rare combinations resulting in high phenotypic variance. The presence of such environment specific genetic networks is the underlying cause of abundant gene–environment interactions. We demonstrate that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation. Such an integrated approach applied to human disease datasets has the potential to improve the ability to predict disease predisposition and identify specific therapeutic targets.

Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits

PubMed Central

Yadav, Anupama; Dhole, Kaustubh

2016-01-01

Cryptic genetic variation (CGV) refers to genetic variants whose effects are buffered in most conditions but manifest phenotypically upon specific genetic and environmental perturbations. Despite having a central role in adaptation, contribution of CGV to regulation of quantitative traits is unclear. Instead, a relatively simplistic architecture of additive genetic loci is known to regulate phenotypic variation in most traits. In this paper, we investigate the regulation of CGV and its implication on the genetic architecture of quantitative traits at a genome-wide level. We use a previously published dataset of biparental recombinant population of Saccharomyces cerevisiae phenotyped in 34 diverse environments to perform single locus, two-locus, and covariance mapping. We identify loci that have independent additive effects as well as those which regulate the phenotypic manifestation of other genetic variants (variance QTL). We find that whereas additive genetic variance is predominant, a higher order genetic interaction network regulates variation in certain environments. Despite containing pleiotropic loci, with effects across environments, these genetic networks are highly environment specific. CGV is buffered under most allelic combinations of these networks and perturbed only in rare combinations resulting in high phenotypic variance. The presence of such environment specific genetic networks is the underlying cause of abundant gene–environment interactions. We demonstrate that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation. Such an integrated approach applied to human disease datasets has the potential to improve the ability to predict disease predisposition and identify specific therapeutic targets. PMID:28172852

Genetic potential of common bean progenies obtained by different breeding methods evaluated in various environments.

PubMed

Pontes Júnior, V A; Melo, P G S; Pereira, H S; Melo, L C

2016-09-02

Grain yield is strongly influenced by the environment, has polygenic and complex inheritance, and is a key trait in the selection and recommendation of cultivars. Breeding programs should efficiently explore the genetic variability resulting from crosses by selecting the most appropriate method for breeding in segregating populations. The goal of this study was to evaluate and compare the genetic potential of common bean progenies of carioca grain for grain yield, obtained by different breeding methods and evaluated in different environments. Progenies originating from crosses between lines and CNFC 7812 and CNFC 7829 were replanted up to the F 7 generation using three breeding methods in segregating populations: population (bulk), bulk within F 2 progenies, and single-seed descent (SSD). Fifteen F 8 progenies per method, two controls (BRS Estilo and Perola), and the parents were evaluated in a 7 x 7 simple lattice design, with plots of two 4-m rows. The tests were conducted in 10 environments in four States of Brazil and in three growing seasons in 2009 and 2010. Genetic parameters including genetic variance, heritability, variance of interaction, and expected selection gain were estimated. Genetic variability among progenies and the effect of progeny-environment interactions were determined for the three methods. The breeding methods differed significantly due to the effects of sampling procedures on the progenies and due to natural selection, which mainly affected the bulk method. The SSD and bulk methods provided populations with better estimates of genetic parameters and more stable progenies that were less affected by interaction with the environment.

A Nutrigenomic Approach to Non-Alcoholic Fatty Liver Disease.

PubMed

Dongiovanni, Paola; Valenti, Luca

2017-07-16

Following the epidemics of obesity due to the consumption of high-calorie diet and sedentary lifestyle, nonalcoholic fatty liver disease (NAFLD) is now the leading cause of liver disease in Western countries. NAFLD is epidemiologically associated with metabolic syndrome and insulin resistance, and in susceptible individuals it may progress to cirrhosis and hepatocellular carcinoma. Genetic factors play a key role in NAFLD predisposition by interacting with nutritional and other environmental factors. To date, there is no drug therapy for the treatment of NAFLD, and the main clinical recommendation is lifestyle modification. In the last years, nutrigenomics is promoting an increased understanding of how nutrition affects the switch from health to disease by altering the expression of an individual's genetic makeup. The present review tries to summarize the most recent data evidencing how the interactions between nutrients and genetic factors can influence NAFLD development. The final goal should be to develop tools to quantify these complex interactions. The definition of a "nutrigenomic risk score" for each individual may represent a novel therapeutic approach for the management of NAFLD patients.

Simple F Test Reveals Gene-Gene Interactions in Case-Control Studies

PubMed Central

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

Genetic interaction networks: better understand to better predict

PubMed Central

Boucher, Benjamin; Jenna, Sarah

2013-01-01

A genetic interaction (GI) between two genes generally indicates that the phenotype of a double mutant differs from what is expected from each individual mutant. In the last decade, genome scale studies of quantitative GIs were completed using mainly synthetic genetic array technology and RNA interference in yeast and Caenorhabditis elegans. These studies raised questions regarding the functional interpretation of GIs, the relationship of genetic and molecular interaction networks, the usefulness of GI networks to infer gene function and co-functionality, the evolutionary conservation of GI, etc. While GIs have been used for decades to dissect signaling pathways in genetic models, their functional interpretations are still not trivial. The existence of a GI between two genes does not necessarily imply that these two genes code for interacting proteins or that the two genes are even expressed in the same cell. In fact, a GI only implies that the two genes share a functional relationship. These two genes may be involved in the same biological process or pathway; or they may also be involved in compensatory pathways with unrelated apparent function. Considering the powerful opportunity to better understand gene function, genetic relationship, robustness and evolution, provided by a genome-wide mapping of GIs, several in silico approaches have been employed to predict GIs in unicellular and multicellular organisms. Most of these methods used weighted data integration. In this article, we will review the later knowledge acquired on GI networks in metazoans by looking more closely into their relationship with pathways, biological processes and molecular complexes but also into their modularity and organization. We will also review the different in silico methods developed to predict GIs and will discuss how the knowledge acquired on GI networks can be used to design predictive tools with higher performances. PMID:24381582

Autism genetics: Methodological issues and experimental design.

PubMed

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.

Multimodal Brain Imaging in Autism Spectrum Disorder and the Promise of Twin Research

ERIC Educational Resources Information Center

Mevel, Katell; Fransson, Peter; Bölte, Sven

2015-01-01

Current evidence suggests the phenotype of autism spectrum disorder to be driven by a complex interaction of genetic and environmental factors impacting onto brain maturation, synaptic function, and cortical networks. However, findings are heterogeneous, and the exact neurobiological pathways of autism spectrum disorder still remain poorly…

Rapid Assessment Of The Fundamental Property Variation Of Wood

Treesearch

Chi-Leung So; Leslie H. Groom; Timothy G. Rials; Rebecca Snell; Stephen S. Kelley; Robert Meglen

2002-01-01

Abstract - Genetic variation, site conditions, silvicultural treatments, seasonal effects, and their complex interaction are all vitally-important factors accounting for the variability and quality of the raw material produced - wood. Quality can be measured in several ways that generally influence the end use. The most desirable measure is the...

Postdoctoral Fellow | Center for Cancer Research

Cancer.gov

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

What Does Culture Have to Do with Teaching Science?

ERIC Educational Resources Information Center

Madden, Lauren; Joshi, Arti

2013-01-01

In nearly every elementary school, plants are an important part of the science curriculum. Understanding basic ideas about plants prepares children to study more complicated scientific concepts including cell biology, genetics and heredity, complex ecosystem interactions, and evolution. It is especially important that teachers of children at the…

Metabotropic glutamate receptor 5 couples cellular prion protein to intracellular signalling in Alzheimer’s disease

PubMed Central

Haas, Laura T.; Salazar, Santiago V.; Kostylev, Mikhail A.; Um, Ji Won; Kaufman, Adam C.

2016-01-01

Alzheimer’s disease-related phenotypes in mice can be rescued by blockade of either cellular prion protein or metabotropic glutamate receptor 5. We sought genetic and biochemical evidence that these proteins function cooperatively as an obligate complex in the brain. We show that cellular prion protein associates via transmembrane metabotropic glutamate receptor 5 with the intracellular protein mediators Homer1b/c, calcium/calmodulin-dependent protein kinase II, and the Alzheimer’s disease risk gene product protein tyrosine kinase 2 beta. Coupling of cellular prion protein to these intracellular proteins is modified by soluble amyloid-β oligomers, by mouse brain Alzheimer’s disease transgenes or by human Alzheimer’s disease pathology. Amyloid-β oligomer-triggered phosphorylation of intracellular protein mediators and impairment of synaptic plasticity in vitro requires Prnp–Grm5 genetic interaction, being absent in transheterozygous loss-of-function, but present in either single heterozygote. Importantly, genetic coupling between Prnp and Grm5 is also responsible for signalling, for survival and for synapse loss in Alzheimer’s disease transgenic model mice. Thus, the interaction between metabotropic glutamate receptor 5 and cellular prion protein has a central role in Alzheimer’s disease pathogenesis, and the complex is a potential target for disease-modifying intervention. PMID:26667279

From genotype to phenotype: genetics and medical practice in the new millennium.

PubMed Central

Weatherall, D

1999-01-01

The completion of the human genome project will provide a vast amount of information about human genetic diversity. One of the major challenges for the medical sciences will be to relate genotype to phenotype. Over recent years considerable progress has been made in relating the molecular pathology of monogenic diseases to the associated clinical phenotypes. Studies of the inherited disorders of haemoglobin, notably the thalassaemias, have shown how even in these, the simplest of monogenic diseases, there is remarkable complexity with respect to their phenotypic expression. Although studies of other monogenic diseases are less far advanced, it is clear that the same level of complexity will exist. This information provides some indication of the difficulties that will be met when trying to define the genes that are involved in common multigenic disorders and, in particular, in trying to relate disease phenotypes to the complex interactions between many genes and multiple environmental factors. PMID:10670020

Genetic Correlation and Gene–Environment Interaction Between Alcohol Problems and Educational Level in Young Adulthood*

PubMed Central

Latvala, Antti; Dick, Danielle M.; Tuulio-Henriksson, Annamari; Suvisaari, Jaana; Viken, Richard J.; Rose, Richard J.; Kaprio, Jaakko

2011-01-01

Objective: A lower level of education often co-occurs with alcohol problems, but factors underlying this co-occurrence are not well understood. Specifically, whether these outcomes share part of their underlying genetic influences has not been widely studied. Educational level also reflects various environmental influences that may moderate the genetic etiology of alcohol problems, but gene–environment interactions between educational attainment and alcohol problems are unknown. Method: We studied the two nonmutually exclusive possibilities of common genetic influences and gene–environment interaction between alcohol problems and low education using a population-based sample (n = 4,858) of Finnish young adult twins (Mage = 24.5 years, range: 22.8–28.6 years). Alcohol problems were assessed with the Rutgers Alcohol Problem Index and self-reported maximum number of drinks consumed in a 24-hour period. Years of education, based on completed and ongo-ing studies, represented educational level. Results: Educational level was inversely associated with alcohol problems in young adulthood, and this association was most parsimoniously explained by overlapping genetic influences. Independent of this co-occurrence, higher education was associated with increased relative importance of genetic influences on alcohol problems, whereas environmental factors had a greater effect among twins with lower education. Conclusions: Our findings suggest a complex relationship between educational level and alcohol problems in young adulthood. Lower education is related to higher levels of alcohol problems, and this co-occurrence is influenced by genetic factors affecting both phenotypes. In addition, educational level moderates the importance of genetic and environmental influences on alcohol problems, possibly reflecting differences in social-control mechanisms related to educational level. PMID:21388594

Cooperation of TOM and TIM23 complexes during translocation of proteins into mitochondria.

PubMed

Waegemann, Karin; Popov-Čeleketić, Dušan; Neupert, Walter; Azem, Abdussalam; Mokranjac, Dejana

2015-03-13

Translocation of the majority of mitochondrial proteins from the cytosol into mitochondria requires the cooperation of TOM and TIM23 complexes in the outer and inner mitochondrial membranes. The molecular mechanisms underlying this cooperation remain largely unknown. Here, we present biochemical and genetic evidence that at least two contacts from the side of the TIM23 complex play an important role in TOM-TIM23 cooperation in vivo. Tim50, likely through its very C-terminal segment, interacts with Tom22. This interaction is stimulated by translocating proteins and is independent of any other TOM-TIM23 contact known so far. Furthermore, the exposure of Tim23 on the mitochondrial surface depends not only on its interaction with Tim50 but also on the dynamics of the TOM complex. Destabilization of the individual contacts reduces the efficiency of import of proteins into mitochondria and destabilization of both contacts simultaneously is not tolerated by yeast cells. We conclude that an intricate and coordinated network of protein-protein interactions involving primarily Tim50 and also Tim23 is required for efficient translocation of proteins across both mitochondrial membranes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Mining nutrigenetics patterns related to obesity: use of parallel multifactor dimensionality reduction.

PubMed

Karayianni, Katerina N; Grimaldi, Keith A; Nikita, Konstantina S; Valavanis, Ioannis K

2015-01-01

This paper aims to enlighten the complex etiology beneath obesity by analysing data from a large nutrigenetics study, in which nutritional and genetic factors associated with obesity were recorded for around two thousand individuals. In our previous work, these data have been analysed using artificial neural network methods, which identified optimised subsets of factors to predict one's obesity status. These methods did not reveal though how the selected factors interact with each other in the obtained predictive models. For that reason, parallel Multifactor Dimensionality Reduction (pMDR) was used here to further analyse the pre-selected subsets of nutrigenetic factors. Within pMDR, predictive models using up to eight factors were constructed, further reducing the input dimensionality, while rules describing the interactive effects of the selected factors were derived. In this way, it was possible to identify specific genetic variations and their interactive effects with particular nutritional factors, which are now under further study.

Regulation of mitochondria-dynactin interaction and mitochondrial retrograde transport in axons.

PubMed

Drerup, Catherine M; Herbert, Amy L; Monk, Kelly R; Nechiporuk, Alex V

2017-04-17

Mitochondrial transport in axons is critical for neural circuit health and function. While several proteins have been found that modulate bidirectional mitochondrial motility, factors that regulate unidirectional mitochondrial transport have been harder to identify. In a genetic screen, we found a zebrafish strain in which mitochondria fail to attach to the dynein retrograde motor. This strain carries a loss-of-function mutation in actr10 , a member of the dynein-associated complex dynactin. The abnormal axon morphology and mitochondrial retrograde transport defects observed in actr10 mutants are distinct from dynein and dynactin mutant axonal phenotypes. In addition, Actr10 lacking the dynactin binding domain maintains its ability to bind mitochondria, arguing for a role for Actr10 in dynactin-mitochondria interaction. Finally, genetic interaction studies implicated Drp1 as a partner in Actr10-dependent mitochondrial retrograde transport. Together, this work identifies Actr10 as a factor necessary for dynactin-mitochondria interaction, enhancing our understanding of how mitochondria properly localize in axons.

Gene-Environment Interplay in the Association between Pubertal Timing and Delinquency in Adolescent Girls

PubMed Central

Harden, K. Paige; Mendle, Jane

2014-01-01

Early pubertal timing places girls at elevated risk for a breadth of negative outcomes, including involvement in delinquent behavior. While previous developmental research has emphasized the unique social challenges faced by early maturing girls, this relation is complicated by genetic influences for both delinquent behavior and pubertal timing, which are seldom controlled for in existing research. The current study uses genetically informed data on 924 female-female twin and sibling pairs drawn from the National Longitudinal Study of Adolescent Health to (1) disentangle biological versus environmental mechanisms for the effects of early pubertal timing and (2) test for gene-environment interactions. Results indicate that early pubertal timing influences girls’ delinquency through a complex interplay between biological risk and environmental experiences. Genes related to earlier age at menarche and higher perceived development significantly predict increased involvement in both non-violent and violent delinquency. Moreover, after accounting for this genetic association between pubertal timing and delinquency, the impact of non-shared environmental influences on delinquency are significantly moderated by pubertal timing, such that the non-shared environment is most important among early maturing girls. This interaction effect is particularly evident for non-violent delinquency. Overall, results suggest early maturing girls are vulnerable to an interaction between genetic and environmental risks for delinquent behavior. PMID:21668078

A Network-Based Kernel Machine Test for the Identification of Risk Pathways in Genome-Wide Association Studies

PubMed Central

Freytag, Saskia; Manitz, Juliane; Schlather, Martin; Kneib, Thomas; Amos, Christopher I.; Risch, Angela; Chang-Claude, Jenny; Heinrich, Joachim; Bickeböller, Heike

2014-01-01

Biological pathways provide rich information and biological context on the genetic causes of complex diseases. The logistic kernel machine test integrates prior knowledge on pathways in order to analyze data from genome-wide association studies (GWAS). Here, the kernel converts genomic information of two individuals to a quantitative value reflecting their genetic similarity. With the selection of the kernel one implicitly chooses a genetic effect model. Like many other pathway methods, none of the available kernels accounts for topological structure of the pathway or gene-gene interaction types. However, evidence indicates that connectivity and neighborhood of genes are crucial in the context of GWAS, because genes associated with a disease often interact. Thus, we propose a novel kernel that incorporates the topology of pathways and information on interactions. Using simulation studies, we demonstrate that the proposed method maintains the type I error correctly and can be more effective in the identification of pathways associated with a disease than non-network-based methods. We apply our approach to genome-wide association case control data on lung cancer and rheumatoid arthritis. We identify some promising new pathways associated with these diseases, which may improve our current understanding of the genetic mechanisms. PMID:24434848

Nutrigenetics and Metabolic Disease: Current Status and Implications for Personalised Nutrition

PubMed Central

Phillips, Catherine M.

2013-01-01

Obesity, particularly central adiposity, is the primary causal factor in the development of insulin resistance, the hallmark of the metabolic syndrome (MetS), a common condition characterized by dyslipidaemia and hypertension, which is associated with increased risk of cardiovascular disease (CVD) and type 2 diabetes (T2DM). Interactions between genetic and environmental factors such as diet and lifestyle, particularly over-nutrition and sedentary behavior, promote the progression and pathogenesis of these polygenic diet-related diseases. Their current prevalence is increasing dramatically to epidemic proportions. Nutrition is probably the most important environmental factor that modulates expression of genes involved in metabolic pathways and the variety of phenotypes associated with obesity, the MetS and T2DM. Furthermore, the health effects of nutrients may be modulated by genetic variants. Nutrigenomics and nutrigenetics require an understanding of nutrition, genetics, biochemistry and a range of “omic” technologies to investigate the complex interaction between genetic and environmental factors relevant to metabolic health and disease. These rapidly developing fields of nutritional science hold much promise in improving nutrition for optimal personal and public health. This review presents the current state of the art in nutrigenetic research illustrating the significance of gene-nutrient interactions in the context of metabolic disease. PMID:23306188

Nutrigenetics and metabolic disease: current status and implications for personalised nutrition.

PubMed

Phillips, Catherine M

2013-01-10

Obesity, particularly central adiposity, is the primary causal factor in the development of insulin resistance, the hallmark of the metabolic syndrome (MetS), a common condition characterized by dyslipidaemia and hypertension, which is associated with increased risk of cardiovascular disease (CVD) and type 2 diabetes (T2DM). Interactions between genetic and environmental factors such as diet and lifestyle, particularly over-nutrition and sedentary behavior, promote the progression and pathogenesis of these polygenic diet-related diseases. Their current prevalence is increasing dramatically to epidemic proportions. Nutrition is probably the most important environmental factor that modulates expression of genes involved in metabolic pathways and the variety of phenotypes associated with obesity, the MetS and T2DM. Furthermore, the health effects of nutrients may be modulated by genetic variants. Nutrigenomics and nutrigenetics require an understanding of nutrition, genetics, biochemistry and a range of "omic" technologies to investigate the complex interaction between genetic and environmental factors relevant to metabolic health and disease. These rapidly developing fields of nutritional science hold much promise in improving nutrition for optimal personal and public health. This review presents the current state of the art in nutrigenetic research illustrating the significance of gene-nutrient interactions in the context of metabolic disease.

The Genome-Wide Interaction Network of Nutrient Stress Genes in Escherichia coli.

PubMed

Côté, Jean-Philippe; French, Shawn; Gehrke, Sebastian S; MacNair, Craig R; Mangat, Chand S; Bharat, Amrita; Brown, Eric D

2016-11-22

Conventional efforts to describe essential genes in bacteria have typically emphasized nutrient-rich growth conditions. Of note, however, are the set of genes that become essential when bacteria are grown under nutrient stress. For example, more than 100 genes become indispensable when the model bacterium Escherichia coli is grown on nutrient-limited media, and many of these nutrient stress genes have also been shown to be important for the growth of various bacterial pathogens in vivo To better understand the genetic network that underpins nutrient stress in E. coli, we performed a genome-scale cross of strains harboring deletions in some 82 nutrient stress genes with the entire E. coli gene deletion collection (Keio) to create 315,400 double deletion mutants. An analysis of the growth of the resulting strains on rich microbiological media revealed an average of 23 synthetic sick or lethal genetic interactions for each nutrient stress gene, suggesting that the network defining nutrient stress is surprisingly complex. A vast majority of these interactions involved genes of unknown function or genes of unrelated pathways. The most profound synthetic lethal interactions were between nutrient acquisition and biosynthesis. Further, the interaction map reveals remarkable metabolic robustness in E. coli through pathway redundancies. In all, the genetic interaction network provides a powerful tool to mine and identify missing links in nutrient synthesis and to further characterize genes of unknown function in E. coli Moreover, understanding of bacterial growth under nutrient stress could aid in the development of novel antibiotic discovery platforms. With the rise of antibiotic drug resistance, there is an urgent need for new antibacterial drugs. Here, we studied a group of genes that are essential for the growth of Escherichia coli under nutrient limitation, culture conditions that arguably better represent nutrient availability during an infection than rich microbiological media. Indeed, many such nutrient stress genes are essential for infection in a variety of pathogens. Thus, the respective proteins represent a pool of potential new targets for antibacterial drugs that have been largely unexplored. We have created all possible double deletion mutants through a genetic cross of nutrient stress genes and the E. coli deletion collection. An analysis of the growth of the resulting clones on rich media revealed a robust, dense, and complex network for nutrient acquisition and biosynthesis. Importantly, our data reveal new genetic connections to guide innovative approaches for the development of new antibacterial compounds targeting bacteria under nutrient stress. Copyright © 2016 Côté et al.

The genetics of insomnia--evidence for epigenetic mechanisms?

PubMed

Palagini, Laura; Biber, Knut; Riemann, Dieter

2014-06-01

Sleep is a complex physiological process and still remains one of the great mysteries of science. Over the past 10 y, genetic research has provided a new avenue to address the regulation and function of sleep. Gene loci that contribute quantitatively to sleep characteristics and variability have already been identified. However, up to now, a genetic basis has been established only for a few sleep disorders. Little is yet known about the genetic background of insomnia, one of the most common sleep disorders. According to the conceptualisation of the 3P model of insomnia, predisposing, precipitating and perpetuating factors contribute to the development and maintenance of insomnia. Growing evidence from studies of predisposing factors suggests a certain degree of heritability for insomnia and for a reactivity of sleep patterns to stressful events, explaining the emergence of insomnia in response to stressful life events. While a genetic susceptibility may modulate the impact of stress on the brain, this finding does not provide us with a complete understanding of the capacity of stress to produce long-lasting perturbations of brain and behaviour. Epigenetic gene-environment interactions have been identified just recently and may provide a more complex understanding of the genetic control of sleep and its disorders. It was recently hypothesised that stress-response-related brain plasticity might be epigenetically controlled and, moreover, several epigenetic mechanisms have been assumed to be involved in the regulation of sleep. Hence, it might be postulated that insomnia may be influenced by an epigenetic control process of both sleep mechanisms and stress-response-related gene-environment interactions having an impact on brain plasticity. This paper reviews the evidence for the genetic basis of insomnia and recent theories about epigenetic mechanisms involved in both sleep regulation and brain-stress response, leading to the hypothesis of an involvement of epigenetic mechanisms in the development and maintenance of insomnia. Copyright © 2013 Elsevier Ltd. All rights reserved.

Functional analysis of neuronal microRNAs in Caenorhabditis elegans dauer formation by combinational genetics and Neuronal miRISC immunoprecipitation.

PubMed

Than, Minh T; Kudlow, Brian A; Han, Min

2013-06-01

Identifying the physiological functions of microRNAs (miRNAs) is often challenging because miRNAs commonly impact gene expression under specific physiological conditions through complex miRNA::mRNA interaction networks and in coordination with other means of gene regulation, such as transcriptional regulation and protein degradation. Such complexity creates difficulties in dissecting miRNA functions through traditional genetic methods using individual miRNA mutations. To investigate the physiological functions of miRNAs in neurons, we combined a genetic "enhancer" approach complemented by biochemical analysis of neuronal miRNA-induced silencing complexes (miRISCs) in C. elegans. Total miRNA function can be compromised by mutating one of the two GW182 proteins (AIN-1), an important component of miRISC. We found that combining an ain-1 mutation with a mutation in unc-3, a neuronal transcription factor, resulted in an inappropriate entrance into the stress-induced, alternative larval stage known as dauer, indicating a role of miRNAs in preventing aberrant dauer formation. Analysis of this genetic interaction suggests that neuronal miRNAs perform such a role partly by regulating endogenous cyclic guanosine monophosphate (cGMP) signaling, potentially influencing two other dauer-regulating pathways. Through tissue-specific immunoprecipitations of miRISC, we identified miRNAs and their likely target mRNAs within neuronal tissue. We verified the biological relevance of several of these miRNAs and found that many miRNAs likely regulate dauer formation through multiple dauer-related targets. Further analysis of target mRNAs suggests potential miRNA involvement in various neuronal processes, but the importance of these miRNA::mRNA interactions remains unclear. Finally, we found that neuronal genes may be more highly regulated by miRNAs than intestinal genes. Overall, our study identifies miRNAs and their targets, and a physiological function of these miRNAs in neurons. It also suggests that compromising other aspects of gene expression, along with miRISC, can be an effective approach to reveal miRNA functions in specific tissues under specific physiological conditions.

Nutrigenomics and nutrigenetics in inflammatory bowel diseases.

PubMed

Gruber, Lisa; Lichti, Pia; Rath, Eva; Haller, Dirk

2012-10-01

Inflammatory bowel diseases (IBD) including ulcerative colitis and Crohn's disease are chronically relapsing, immune-mediated disorders of the gastrointestinal tract. A major challenge in the treatment of IBD is the heterogenous nature of these pathologies. Both, ulcerative colitis and Crohn's disease are of multifactorial etiology and feature a complex interaction of host genetic susceptibility and environmental factors such as diet and gut microbiota. Genome-wide association studies identified disease-relevant single-nucleotide polymorphisms in approximately 100 genes, but at the same time twin studies also clearly indicated a strong environmental impact in disease development. However, attempts to link dietary factors to the risk of developing IBD, based on epidemiological observations showed controversial outcomes. Yet, emerging high-throughput technologies implying complete biological systems might allow taking nutrient-gene interactions into account for a better classification of patient subsets in the future. In this context, 2 new scientific fields, "nutrigenetics" and "nutrigenomics" have been established. "Nutrigenetics," studying the effect of genetic variations on nutrient-gene interactions and "Nutrigenomics," describing the impact of nutrition on physiology and health status on the level of gene transcription, protein expression, and metabolism. It is hoped that the integration of both research areas will promote the understanding of the complex gene-environment interaction in IBD etiology and in the long-term will lead to personalized nutrition for disease prevention and treatment. This review briefly summarizes data on the impact of nutrients on intestinal inflammation, highlights nutrient-gene interactions, and addresses the potential of applying "omic" technologies in the context of IBD.

Genetic and hormonal control of hepatic steatosis in female and male mice.

PubMed

Norheim, Frode; Hui, Simon T; Kulahcioglu, Emre; Mehrabian, Margarete; Cantor, Rita M; Pan, Calvin; Parks, Brian W; Lusis, Aldons J

2017-01-01

The etiology of nonalcoholic fatty liver disease is complex and influenced by factors such as obesity, insulin resistance, hyperlipidemia, and sex. We now report a study on sex difference in hepatic steatosis in the context of genetic variation using a population of inbred strains of mice. While male mice generally exhibited higher concentration of hepatic TG levels on a high-fat high-sucrose diet, sex differences showed extensive interaction with genetic variation. Differences in percentage body fat were the best predictor of hepatic steatosis among the strains and explained about 30% of the variation in both sexes. The difference in percent gonadal fat and HDL explained 9.6% and 6.7% of the difference in hepatic TGs between the sexes, respectively. Genome-wide association mapping of hepatic TG revealed some striking differences in genetic control of hepatic steatosis between females and males. Gonadectomy increased the hepatic TG to body fat percentage ratio among male, but not female, mice. Our data suggest that the difference between the sexes in hepatic TG can be partly explained by differences in body fat distribution, plasma HDL, and genetic regulation. Future studies are required to understand the molecular interactions between sex, genetics, and the environment. Copyright © 2017 by the American Society for Biochemistry and Molecular Biology, Inc.

Genetics and evolution of triatomines: from phylogeny to vector control

PubMed Central

Gourbière, S; Dorn, P; Tripet, F; Dumonteil, E

2012-01-01

Triatomines are hemipteran bugs acting as vectors of the protozoan parasite Trypanosoma cruzi. This parasite causes Chagas disease, one of the major parasitic diseases in the Americas. Studies of triatomine genetics and evolution have been particularly useful in the design of rational vector control strategies, and are reviewed here. The phylogeography of several triatomine species is now slowly emerging, and the struggle to reconcile the phenotypic, phylogenetic, ecological and epidemiological species concepts makes for a very dynamic field. Population genetic studies using different markers indicate a wide range of population structures, depending on the triatomine species, ranging from highly fragmented to mobile, interbreeding populations. Triatomines transmit T. cruzi in the context of complex interactions between the insect vectors, their bacterial symbionts and the parasites; however, an integrated view of the significance of these interactions in triatomine biology, evolution and in disease transmission is still lacking. The development of novel genetic markers, together with the ongoing sequencing of the Rhodnius prolixus genome and more integrative studies, will provide key tools to expanding our understanding of these important insect vectors and allow the design of improved vector control strategies. PMID:21897436

Individual differences in cognition, affect, and performance: Behavioral, neuroimaging, and molecular genetic approaches

PubMed Central

Parasuraman, Raja; Jiang, Yang

2012-01-01

We describe the use of behavioral, neuroimaging, and genetic methods to examine individual differences in cognition and affect, guided by three criteria: (1) relevance to human performance in work and everyday settings; (2) interactions between working memory, decision-making, and affective processing; and (3) examination of individual differences. The results of behavioral, functional MRI (fMRI), event-related potential (ERP), and molecular genetic studies show that analyses at the group level often mask important findings associated with sub-groups of individuals. Dopaminergic/noradrenergic genes influencing prefrontal cortex activity contribute to inter-individual variation in working memory and decision behavior, including performance in complex simulations of military decision-making. The interactive influences of individual differences in anxiety, sensation seeking, and boredom susceptibility on evaluative decision-making can be systematically described using ERP and fMRI methods. We conclude that a multi-modal neuroergonomic approach to examining brain function (using both neuroimaging and molecular genetics) can be usefully applied to understanding individual differences in cognition and affect and has implications for human performance at work. PMID:21569853

Childhood temperament: passive gene-environment correlation, gene-environment interaction, and the hidden importance of the family environment.

PubMed

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.

Genetics and Psychopharmacology: Prospects for Individualized Treatment

PubMed Central

Nnadi, Charles U.; Goldberg, Joseph F.; Malhotra, Anil K.

2008-01-01

This article provides a clear and succinct description of the components of inheritance, such as trait transmission, genetic variability, and gene interaction. Genetic sequences constitute the prime focus of pharmacogenetic studies. Variations in drug-metabolizing enzyme systems tend to be monogenic, whereas the pharmacologic effects of medications appear to be polygenic, i.e., complex phenotypes shaped by the interaction of genes and environment. Translated into clinical terms, a history of a good response to a drug in a close relative of a patient is presumed to indicate a good response to the same medication by the patient. This seems to hold for antidepressants, antipsychotics, and lithium, but the evidential studies generally have meaningful limitations. Bit by bit, information about the relationship between particular genetic formations and the effectiveness of these medications as well as their side effects, is appearing. The authors cite a number of examples, one such being an association between impaired antidepressant activity and the short allele of SLC6A4. This research promises to strengthen the accuracy, effectiveness, safety, and cost of our psychopharmacological practices. PMID:16041916

Genetics and psychopharmacology: prospects for individualized treatment.

PubMed

Nnadi, Charles U; Goldberg, Joseph F; Malhotra, Anil K

2005-01-01

This article provides a clear and succinct description of the components of inheritance, such as trait transmission, genetic variability, and gene interaction. Genetic sequences constitute the prime focus of pharmacogenetic studies. Variations in drug-metabolizing enzyme systems tend to be monogenic, whereas the pharmacologic effects of medications appear to be polygenic, i.e., complex phenotypes shaped by the interaction of genes and environment. Translated into clinical terms, a history of a good response to a drug in a close relative of a patient is presumed to predict a good response to the same medication by the patient. This seems to hold for antidepressants, antipsychotics, and lithium, but the evidential studies generally have meaningful limitations. Bit by bit, information about the relationship between particular genetic formations and the effectiveness of these medications as well as their side effects, is appearing. The authors cite a number of examples, one such being an association between impaired antidepressant activity and the short allele of SLC6A4. This research promises to strengthen the accuracy, effectiveness, safety, and cost of our psychopharmacological practices.

Genetic Interaction of Centrosomin and Bazooka in Apical Domain Regulation in Drosophila Photoreceptor

PubMed Central

Chen, Geng; Rogers, Alicia K.; League, Garrett P.; Nam, Sang-Chul

2011-01-01

Background Cell polarity genes including Crumbs (Crb) and Par complexes are essential for controlling photoreceptor morphogenesis. Among the Crb and Par complexes, Bazooka (Baz, Par-3 homolog) acts as a nodal component for other cell polarity proteins. Therefore, finding other genes interacting with Baz will help us to understand the cell polarity genes' role in photoreceptor morphogenesis. Methodology/Principal Findings Here, we have found a genetic interaction between baz and centrosomin (cnn). Cnn is a core protein for centrosome which is a major microtubule-organizing center. We analyzed the effect of the cnn mutation on developing eyes to determine its role in photoreceptor morphogenesis. We found that Cnn is dispensable for retinal differentiation in eye imaginal discs during the larval stage. However, photoreceptors deficient in Cnn display dramatic morphogenesis defects including the mislocalization of Crumbs (Crb) and Bazooka (Baz) during mid-stage pupal eye development, suggesting that Cnn is specifically required for photoreceptor morphogenesis during pupal eye development. This role of Cnn in apical domain modulation was further supported by Cnn's gain-of-function phenotype. Cnn overexpression in photoreceptors caused the expansion of the apical Crb membrane domain, Baz and adherens junctions (AJs). Conclusions/Significance These results strongly suggest that the interaction of Baz and Cnn is essential for apical domain and AJ modulation during photoreceptor morphogenesis, but not for the initial photoreceptor differentiation in the Drosophila photoreceptor. PMID:21253601

Ethical and clinical practice considerations for genetic counselors related to direct-to-consumer marketing of genetic tests.

PubMed

Wade, Christopher H; Wilfond, Benjamin S

2006-11-15

Several companies utilize direct-to-consumer (DTC) advertising for genetic tests and some, but not all, bypass clinician involvement by offering DTC purchase of the tests. This article examines how DTC marketing strategies may affect genetic counselors, using available cardiovascular disease susceptibility tests as an illustration. The interpretation of these tests is complex and includes consideration of clinical validity and utility, and the further complications of gene-environment interactions and pleiotropy. Although it is unclear to what extent genetic counselors will encounter clients who have been exposed to DTC marketing strategies, these strategies may influence genetic counseling interactions if they produce directed interest in specific tests and unrealistic expectations for the tests' capacity to predict disease. Often, a client's concern about risk for cardiovascular diseases is best addressed by established clinical tests and a family history assessment. Ethical dilemmas may arise for genetic counselors who consider whether to accept clients who request test interpretation or to order DTC-advertised tests that require a clinician's authorization. Genetic counselors' obligations to care for clients extend to interpreting DTC tests, although this obligation may be fulfilled by referral or consultation with specialists. Genetic counselors do not have an obligation to order DTC-advertised tests that have minimal clinical validity and utility at a client's request. This can be a justified restriction on autonomy based on consideration of risks to the client, the costs, and the implications for society. Published 2006 Wiley-Liss, Inc.

Differential influences of local subpopulations on regional diversity and differentiation for greater sage-grouse (Centrocercus urophasianus)

USGS Publications Warehouse

Row, Jeffery R.; Oyler-McCance, Sara J.; Fedy, Brad C.

2016-01-01

The distribution of spatial genetic variation across a region can shape evolutionary dynamics and impact population persistence. Local population dynamics and among-population dispersal rates are strong drivers of this spatial genetic variation, yet for many species we lack a clear understanding of how these population processes interact in space to shape within-species genetic variation. Here, we used extensive genetic and demographic data from 10 subpopulations of greater sage-grouse to parameterize a simulated approximate Bayesian computation (ABC) model and (i) test for regional differences in population density and dispersal rates for greater sage-grouse subpopulations in Wyoming, and (ii) quantify how these differences impact subpopulation regional influence on genetic variation. We found a close match between observed and simulated data under our parameterized model and strong variation in density and dispersal rates across Wyoming. Sensitivity analyses suggested that changes in dispersal (via landscape resistance) had a greater influence on regional differentiation, whereas changes in density had a greater influence on mean diversity across all subpopulations. Local subpopulations, however, varied in their regional influence on genetic variation. Decreases in the size and dispersal rates of central populations with low overall and net immigration (i.e. population sources) had the greatest negative impact on genetic variation. Overall, our results provide insight into the interactions among demography, dispersal and genetic variation and highlight the potential of ABC to disentangle the complexity of regional population dynamics and project the genetic impact of changing conditions.

Architecture of the Saccharomyces cerevisiae SAGA transcription coactivator complex

PubMed Central

Han, Yan; Luo, Jie; Ranish, Jeffrey; Hahn, Steven

2014-01-01

The conserved transcription coactivator SAGA is comprised of several modules that are involved in activator binding, TBP binding, histone acetylation (HAT) and deubiquitination (DUB). Crosslinking and mass spectrometry, together with genetic and biochemical analyses, were used to determine the molecular architecture of the SAGA-TBP complex. We find that the SAGA Taf and Taf-like subunits form a TFIID-like core complex at the center of SAGA that makes extensive interactions with all other SAGA modules. SAGA-TBP binding involves a network of interactions between subunits Spt3, Spt8, Spt20, and Spt7. The HAT and DUB modules are in close proximity, and the DUB module modestly stimulates HAT function. The large activator-binding subunit Tra1 primarily connects to the TFIID-like core via its FAT domain. These combined results were used to derive a model for the arrangement of the SAGA subunits and its interactions with TBP. Our results provide new insight into SAGA function in gene regulation, its structural similarity with TFIID, and functional interactions between the SAGA modules. PMID:25216679

What is microbial community ecology?

PubMed

Konopka, Allan

2009-11-01

The activities of complex communities of microbes affect biogeochemical transformations in natural, managed and engineered ecosystems. Meaningfully defining what constitutes a community of interacting microbial populations is not trivial, but is important for rigorous progress in the field. Important elements of research in microbial community ecology include the analysis of functional pathways for nutrient resource and energy flows, mechanistic understanding of interactions between microbial populations and their environment, and the emergent properties of the complex community. Some emergent properties mirror those analyzed by community ecologists who study plants and animals: biological diversity, functional redundancy and system stability. However, because microbes possess mechanisms for the horizontal transfer of genetic information, the metagenome may also be considered as a community property.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Konopka, Allan

The activities of complex communities of microbes affect biogeochemical transformations in natural, managed and engineered ecosystems. Meaningfully defining what constitutes a community of interacting microbial populations is not trivial, but is important for rigorous progress in the field. Important elements of research in microbial community ecology include the analysis of functional pathways for nutrient resource and energy flows, mechanistic understanding of interactions between microbial populations and their environment, and the emergent properties of the complex community. Some emergent properties mirror those analyzed by community ecologists who study plants and animals: biological diversity, functional redundancy and system stability. However, because microbesmore » possess mechanisms for the horizontal transfer of genetic information, the metagenome may also be considered a community property.« less

Testing for gene-environment interaction under exposure misspecification.

PubMed

Sun, Ryan; Carroll, Raymond J; Christiani, David C; Lin, Xihong

2017-11-09

Complex interplay between genetic and environmental factors characterizes the etiology of many diseases. Modeling gene-environment (GxE) interactions is often challenged by the unknown functional form of the environment term in the true data-generating mechanism. We study the impact of misspecification of the environmental exposure effect on inference for the GxE interaction term in linear and logistic regression models. We first examine the asymptotic bias of the GxE interaction regression coefficient, allowing for confounders as well as arbitrary misspecification of the exposure and confounder effects. For linear regression, we show that under gene-environment independence and some confounder-dependent conditions, when the environment effect is misspecified, the regression coefficient of the GxE interaction can be unbiased. However, inference on the GxE interaction is still often incorrect. In logistic regression, we show that the regression coefficient is generally biased if the genetic factor is associated with the outcome directly or indirectly. Further, we show that the standard robust sandwich variance estimator for the GxE interaction does not perform well in practical GxE studies, and we provide an alternative testing procedure that has better finite sample properties. © 2017, The International Biometric Society.

The role of gene-environment interplay in occupational and environmental diseases: current concepts and knowledge gaps.

PubMed

Kwo, Elizabeth; Christiani, David

2017-03-01

The interplay between genetic susceptibilities and environmental exposures in the pathogenesis of a variety of diseases is an area of increased scientific, epidemiologic, and social interest. Given the variation in methodologies used in the field, this review aims to create a framework to help understand occupational exposures as they currently exist and provide a foundation for future inquiries into the biological mechanisms of the gene-environment interactions. Understanding of this complex interplay will be important in the context of occupational health, given the public health concerns surrounding a variety of occupational exposures. Studies found evidence that suggest genetics influence the progression of disease postberyllium exposure through genetically encoded major histocompatibility complex, class II, DP alpha 2 (HLA-DP2)-peptide complexes as it relates to T-helper cells. This was characterized at the molecular level by the accumulation of Be-responsive CD4 T cells in the lung, which resulted in posttranslational change in the HLA-DPB1 complex. These studies provide important evidence of gene-environment association, and many provide insights into specific pathogenic mechanisms. The following includes a review of the literature regarding gene-environment associations with a focus on pulmonary diseases as they relate to the workplace.

The transformative potential of an integrative approach to pregnancy.

PubMed

Eidem, Haley R; McGary, Kriston L; Capra, John A; Abbot, Patrick; Rokas, Antonis

2017-09-01

Complex traits typically involve diverse biological pathways and are shaped by numerous genetic and environmental factors. Pregnancy-associated traits and pathologies are further complicated by extensive communication across multiple tissues in two individuals, interactions between two genomes-maternal and fetal-that obscure causal variants and lead to genetic conflict, and rapid evolution of pregnancy-associated traits across mammals and in the human lineage. Given the multi-faceted complexity of human pregnancy, integrative approaches that synthesize diverse data types and analyses harbor tremendous promise to identify the genetic architecture and environmental influences underlying pregnancy-associated traits and pathologies. We review current research that addresses the extreme complexities of traits and pathologies associated with human pregnancy. We find that successful efforts to address the many complexities of pregnancy-associated traits and pathologies often harness the power of many and diverse types of data, including genome-wide association studies, evolutionary analyses, multi-tissue transcriptomic profiles, and environmental conditions. We propose that understanding of pregnancy and its pathologies will be accelerated by computational platforms that provide easy access to integrated data and analyses. By simplifying the integration of diverse data, such platforms will provide a comprehensive synthesis that transcends many of the inherent challenges present in studies of pregnancy. Copyright © 2017 Elsevier Ltd. All rights reserved.

What Risk Assessments of Genetically Modified Organisms Can Learn from Institutional Analyses of Public Health Risks

PubMed Central

Rajan, S. Ravi; Letourneau, Deborah K.

2012-01-01

The risks of genetically modified organisms (GMOs) are evaluated traditionally by combining hazard identification and exposure estimates to provide decision support for regulatory agencies. We question the utility of the classical risk paradigm and discuss its evolution in GMO risk assessment. First, we consider the problem of uncertainty, by comparing risk assessment for environmental toxins in the public health domain with genetically modified organisms in the environment; we use the specific comparison of an insecticide to a transgenic, insecticidal food crop. Next, we examine normal accident theory (NAT) as a heuristic to consider runaway effects of GMOs, such as negative community level consequences of gene flow from transgenic, insecticidal crops. These examples illustrate how risk assessments are made more complex and contentious by both their inherent uncertainty and the inevitability of failure beyond expectation in complex systems. We emphasize the value of conducting decision-support research, embracing uncertainty, increasing transparency, and building interdisciplinary institutions that can address the complex interactions between ecosystems and society. In particular, we argue against black boxing risk analysis, and for a program to educate policy makers about uncertainty and complexity, so that eventually, decision making is not the burden that falls upon scientists but is assumed by the public at large. PMID:23193357

What risk assessments of genetically modified organisms can learn from institutional analyses of public health risks.

PubMed

Rajan, S Ravi; Letourneau, Deborah K

2012-01-01

The risks of genetically modified organisms (GMOs) are evaluated traditionally by combining hazard identification and exposure estimates to provide decision support for regulatory agencies. We question the utility of the classical risk paradigm and discuss its evolution in GMO risk assessment. First, we consider the problem of uncertainty, by comparing risk assessment for environmental toxins in the public health domain with genetically modified organisms in the environment; we use the specific comparison of an insecticide to a transgenic, insecticidal food crop. Next, we examine normal accident theory (NAT) as a heuristic to consider runaway effects of GMOs, such as negative community level consequences of gene flow from transgenic, insecticidal crops. These examples illustrate how risk assessments are made more complex and contentious by both their inherent uncertainty and the inevitability of failure beyond expectation in complex systems. We emphasize the value of conducting decision-support research, embracing uncertainty, increasing transparency, and building interdisciplinary institutions that can address the complex interactions between ecosystems and society. In particular, we argue against black boxing risk analysis, and for a program to educate policy makers about uncertainty and complexity, so that eventually, decision making is not the burden that falls upon scientists but is assumed by the public at large.

Epistatic Interactions within the Influenza A Virus Polymerase Complex Mediate Mutagen Resistance and Replication Fidelity

PubMed Central

Pauly, Matthew D.; Lyons, Daniel M.; Fitzsimmons, William J.

2017-01-01

ABSTRACT Lethal mutagenesis is a broad-spectrum antiviral strategy that employs mutagenic nucleoside analogs to exploit the high mutation rate and low mutational tolerance of many RNA viruses. Studies of mutagen-resistant viruses have identified determinants of replicative fidelity and the importance of mutation rate to viral population dynamics. We have previously demonstrated the effective lethal mutagenesis of influenza A virus using three nucleoside analogs as well as the virus’s high genetic barrier to mutagen resistance. Here, we investigate the mutagen-resistant phenotypes of mutations that were enriched in drug-treated populations. We find that PB1 T123A has higher replicative fitness than the wild type, PR8, and maintains its level of genome production during 5-fluorouracil (2,4-dihydroxy-5-fluoropyrimidine) treatment. Surprisingly, this mutagen-resistant variant also has an increased baseline rate of C-to-U and G-to-A mutations. A second drug-selected mutation, PA T97I, interacts epistatically with PB1 T123A to mediate high-level mutagen resistance, predominantly by limiting the inhibitory effect of nucleosides on polymerase activity. Consistent with the importance of epistatic interactions in the influenza virus polymerase, our data suggest that nucleoside analog resistance and replication fidelity are strain dependent. Two previously identified ribavirin {1-[(2R,3R,4S,5R)-3,4-dihydroxy-5-(hydroxymethyl)oxolan-2-yl]-1H-1,2,4-triazole-3-carboxamide} resistance mutations, PB1 V43I and PB1 D27N, do not confer drug resistance in the PR8 background, and the PR8-PB1 V43I polymerase exhibits a normal baseline mutation rate. Our results highlight the genetic complexity of the influenza A virus polymerase and demonstrate that increased replicative capacity is a mechanism by which an RNA virus can counter the negative effects of elevated mutation rates. IMPORTANCE RNA viruses exist as genetically diverse populations. This standing genetic diversity gives them the potential to adapt rapidly, evolve resistance to antiviral therapeutics, and evade immune responses. Viral mutants with altered mutation rates or mutational tolerance have provided insights into how genetic diversity arises and how it affects the behavior of RNA viruses. To this end, we identified variants within the polymerase complex of influenza virus that are able to tolerate drug-mediated increases in viral mutation rates. We find that drug resistance is highly dependent on interactions among mutations in the polymerase complex. In contrast to other viruses, influenza virus counters the effect of higher mutation rates primarily by maintaining high levels of genome replication. These findings suggest the importance of maintaining large population sizes for viruses with high mutation rates and show that multiple proteins can affect both mutation rate and genome synthesis. PMID:28815216

Cytoplasmic FANCA-FANCC Complex Interacts and Stabilizes the Cytoplasm-dislocalized Leukemic Nucleophosmin Protein (NPMc)*

PubMed Central

Du, Wei; Li, Jie; Sipple, Jared; Chen, Jianjun; Pang, Qishen

2010-01-01

Eight of the Fanconi anemia (FA) proteins form a core complex that activates the FA pathway. Some core complex components also form subcomplexes for yet-to-be-elucidated functions. Here, we have analyzed the interaction between a cytoplasmic FA subcomplex and the leukemic nucleophosmin (NPMc). Exogenous NPMc was degraded rapidly in FA acute myeloid leukemia bone marrow cells. Knockdown of FANCA or FANCC in leukemic OCI/AML3 cells induced rapid degradation of endogenous NPMc. NPMc degradation was mediated by the ubiquitin-proteasome pathway involving the IBR-type RING-finger E3 ubiquitin ligase IBRDC2, and genetic correction of FA-A or FA-C lymphoblasts prevented NPMc ubiquitination. Moreover, cytoplasmic FANCA and FANCC formed a cytoplasmic complex and interacted with NPMc. Using a patient-derived FANCC mutant and a nuclearized FANCC, we demonstrated that the cytoplasmic FANCA-FANCC complex was essential for NPMc stability. Finally, depletion of FANCA and FANCC in NPMc-positive leukemic cells significantly increased inflammation and chemoresistance through NF-κB activation. Our findings not only reveal the molecular mechanism involving cytoplasmic retention of NPMc but also suggest cytoplasmic function of FANCA and FANCC in NPMc-related leukemogenesis. PMID:20864535

Interactions Among Polymorphisms of Susceptibility Loci for Alzheimer’s Disease or Depressive Disorder

PubMed Central

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

Systems Modeling at Multiple Levels of Regulation: Linking Systems and Genetic Networks to Spatially Explicit Plant Populations

PubMed Central

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

Histone modifications influence mediator interactions with chromatin

PubMed Central

Zhu, Xuefeng; Zhang, Yongqiang; Bjornsdottir, Gudrun; Liu, Zhongle; Quan, Amy; Costanzo, Michael; Dávila López, Marcela; Westholm, Jakub Orzechowski; Ronne, Hans; Boone, Charles; Gustafsson, Claes M.; Myers, Lawrence C.

2011-01-01

The Mediator complex transmits activation signals from DNA bound transcription factors to the core transcription machinery. Genome wide localization studies have demonstrated that Mediator occupancy not only correlates with high levels of transcription, but that the complex also is present at transcriptionally silenced locations. We provide evidence that Mediator localization is guided by an interaction with histone tails, and that this interaction is regulated by their post-translational modifications. A quantitative, high-density genetic interaction map revealed links between Mediator components and factors affecting chromatin structure, especially histone deacetylases. Peptide binding assays demonstrated that pure wild-type Mediator forms stable complexes with the tails of Histone H3 and H4. These binding assays also showed Mediator—histone H4 peptide interactions are specifically inhibited by acetylation of the histone H4 lysine 16, a residue critical in transcriptional silencing. Finally, these findings were validated by tiling array analysis that revealed a broad correlation between Mediator and nucleosome occupancy in vivo, but a negative correlation between Mediator and nucleosomes acetylated at histone H4 lysine 16. Our studies show that chromatin structure and the acetylation state of histones are intimately connected to Mediator localization. PMID:21742760

Evolutionary perspectives on the links between mitochondrial genotype and disease phenotype.

PubMed

Dowling, Damian K

2014-04-01

Disorders of the mitochondrial respiratory chain are heterogeneous in their symptoms and underlying genetics. Simple links between candidate mutations and expression of disease phenotype typically do not exist. It thus remains unclear how the genetic variation in the mitochondrial genome contributes to the phenotypic expression of complex traits and disease phenotypes. I summarize the basic genetic processes known to underpin mitochondrial disease. I highlight other plausible processes, drawn from the evolutionary biological literature, whose contribution to mitochondrial disease expression remains largely empirically unexplored. I highlight recent advances to the field, and discuss common-ground and -goals shared by researchers across medical and evolutionary domains. Mitochondrial genetic variance is linked to phenotypic variance across a variety of traits (e.g. reproductive function, life expectancy) fundamental to the upkeep of good health. Evolutionary theory predicts that mitochondrial genomes are destined to accumulate male-harming (but female-friendly) mutations, and this prediction has received proof-of-principle support. Furthermore, mitochondrial effects on the phenotype are typically manifested via interactions between mitochondrial and nuclear genes. Thus, whether a mitochondrial mutation is pathogenic in effect can depend on the nuclear genotype in which is it expressed. Many disease phenotypes associated with OXPHOS malfunction might be determined by the outcomes of mitochondrial-nuclear interactions, and by the evolutionary forces that historically shaped mitochondrial DNA (mtDNA) sequences. Concepts and results drawn from the evolutionary sciences can have broad, but currently under-utilized, applicability to the medical sciences and provide new insights into understanding the complex genetics of mitochondrial disease. This article is part of a Special Issue entitled Frontiers of Mitochondrial Research. Copyright © 2013. Published by Elsevier B.V.

Transcriptomic Insights into Phenological Development and Cold Tolerance of Wheat Grown in the Field1[OPEN

PubMed Central

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

Landscape-scale evaluation of genetic structure among barrier-isolated populations of coastal cutthroat trout, Oncorhynchus clarkii clarkii

USGS Publications Warehouse

Guy, T.J.; Gresswell, R.E.; Banks, M.A.

2008-01-01

Relationships among landscape structure, stochastic disturbance, and genetic diversity were assessed by examining interactions between watershed-scale environmental factors and genetic diversity of coastal cutthroat trout (Oncorhynchus clarkii clarkii) in 27 barrier-isolated watersheds from western Oregon, USA. Headwater populations of coastal cutthroat trout were genetically differentiated (mean FST = 0.33) using data from seven microsatellite loci (2232 individuals), but intrapopulation microsatellite genetic diversity (mean number of alleles per locus = 5, mean He = 0.60) was only moderate. Genetic diversity of coastal cutthroat trout was greater (P = 0.02) in the Coast Range ecoregion (mean alleles = 47) than in the Cascades ecoregion (mean alleles = 30), and differences coincided with indices of regional within-watershed complexity and connectivity. Furthermore, regional patterns of diversity evident from isolation-by-distance plots suggested that retention of within-population genetic diversity in the Coast Range ecoregion is higher than that in the Cascades, where genetic drift is the dominant factor influencing genetic patterns. Thus, it appears that physical landscape features have influenced genetic patterns in these populations isolated from short-term immigration. ?? 2008 NRC.

Trends in childhood cancer incidence: review of environmental linkages.

PubMed

Buka, Irena; Koranteng, Samuel; Osornio Vargas, Alvaro R

2007-02-01

Cancer in children is rare and accounts for about 1% of all malignancies. In the developed world, however, it is the commonest cause of disease-related deaths in childhood, carrying with it a great economic and emotional cost. Cancers are assumed to be multivariate, multifactorial diseases that occur when a complex and prolonged process involving genetic and environmental factors interact in a multistage sequence. This article explores the available evidence for this process, primarily from the environmental linkages perspective but including some evidence of the genetic factors.

Structural insights of the MLF1/14-3-3 interaction.

PubMed

Molzan, Manuela; Weyand, Michael; Rose, Rolf; Ottmann, Christian

2012-02-01

Myeloid leukaemia factor 1 (MLF1) binds to 14-3-3 adapter proteins by a sequence surrounding Ser34 with the functional consequences of this interaction largely unknown. We present here the high-resolution crystal structure of this binding motif [MLF1(29-42)pSer34] in complex with 14-3-3ε and analyse the interaction with isothermal titration calorimetry. Fragment-based ligand discovery employing crystals of the binary 14-3-3ε/MLF1(29-42)pSer34 complex was used to identify a molecule that binds to the interface rim of the two proteins, potentially representing the starting point for the development of a small molecule that stabilizes the MLF1/14-3-3 protein-protein interaction. Such a compound might be used as a chemical biology tool to further analyse the 14-3-3/MLF1 interaction without the use of genetic methods. Database Structural data are available in the Protein Data Bank under the accession number(s) 3UAL [14-3-3ε/MLF1(29-42)pSer34 complex] and 3UBW [14-3-3ε/MLF1(29-42)pSer34/3-pyrrolidinol complex] Structured digital abstract •  14-3-3 epsilon and MLF1 bind by x-ray crystallography (View interaction) •  14-3-3 epsilon and MLF1 bind by isothermal titration calorimetry (View Interaction: 1, 2). © 2011 The Authors Journal compilation © 2011 FEBS.

Enhancing Subjective Well-Being in Individuals with Asthma

ERIC Educational Resources Information Center

Bray, Melissa A.; Kehle, Thomas J.; Peck, Heather L.; Theodore, Lea A.; Zhou, Zheng

2004-01-01

Asthma, a chronic respiratory disease, is caused by a complex interaction between genetic and environmental variables. The intent of this article is to propose a theory that provides an explanation for the reduction of emotionally triggered asthma through treatments derived from positive psychology. The basic tenet of the theory is that physical…

Quantitative gene-gene and gene-environment mapping for leaf shape variation using tree-based models

USDA-ARS?s Scientific Manuscript database

Leaf shape traits have long been a focus of many disciplines, but searching for complex genetic and environmental interactive mechanisms regulating leaf shape variation has not yet been well developed. The question of the respective roles of gene and environment and how they interplay to modulate l...

Accounting for genotype–by-environment interactions and non-additive genetic variation in genomic selection for water-soluble carbohydrate concentration in wheat

USDA-ARS?s Scientific Manuscript database

Abiotic stress tolerance traits are often complex and recalcitrant targets for conventional breeding improvement in many crop species. This study evaluated the potential of genomic selection to predict water-soluble carbohydrate concentration (WSCC), an important drought tolerance trait, in wheat un...

Use of quantitative traits to assess aggressiveness of Phakopsora pachyrhizi isolates from Nigeria and the United States

USDA-ARS?s Scientific Manuscript database

Soybean rust, caused by Phakopsora pachyrhizi, is one of the most important foliar diseases of soybean worldwide. The soybean-P. pachyrhizi interaction is often complex because of the genetic variability in host and pathogen genotypes. In a compatible reaction, soybean genotypes produce tan colored ...

Predictors for reproductive isolation in a ring species complex following genetic and ecological divergence.

PubMed

Pereira, Ricardo J; Monahan, William B; Wake, David B

2011-07-06

Reproductive isolation (RI) is widely accepted as an important "check point" in the diversification process, since it defines irreversible evolutionary trajectories. Much less consensus exists about the processes that might drive RI. Here, we employ a formal quantitative analysis of genetic interactions at several stages of divergence within the ring species complex Ensatina eschscholtzii in order to assess the relative contribution of genetic and ecological divergence for the development of RI. By augmenting previous genetic datasets and adding new ecological data, we quantify levels of genetic and ecological divergence between populations and test how they correlate with a restriction of genetic admixture upon secondary contact. Our results indicate that the isolated effect of ecological divergence between parental populations does not result in reproductively isolated taxa, even when genetic transitions between parental taxa are narrow. Instead, processes associated with overall genetic divergence are the best predictors of reproductive isolation, and when parental taxa diverge in nuclear markers we observe a complete cessation of hybridization, even to sympatric occurrence of distinct evolutionary lineages. Although every parental population has diverged in mitochondrial DNA, its degree of divergence does not predict the extent of RI. These results show that in Ensatina, the evolutionary outcomes of ecological divergence differ from those of genetic divergence. While evident properties of taxa may emerge via ecological divergence, such as adaptation to local environment, RI is likely to be a byproduct of processes that contribute to overall genetic divergence, such as time in geographic isolation, rather than being a direct outcome of local adaptation.

Biomechanical cell regulatory networks as complex adaptive systems in relation to cancer.

PubMed

Feller, Liviu; Khammissa, Razia Abdool Gafaar; Lemmer, Johan

2017-01-01

Physiological structure and function of cells are maintained by ongoing complex dynamic adaptive processes in the intracellular molecular pathways controlling the overall profile of gene expression, and by genes in cellular gene regulatory circuits. Cytogenetic mutations and non-genetic factors such as chronic inflammation or repetitive trauma, intrinsic mechanical stresses within extracellular matrix may induce redirection of gene regulatory circuits with abnormal reactivation of embryonic developmental programmes which can now drive cell transformation and cancer initiation, and later cancer progression and metastasis. Some of the non-genetic factors that may also favour cancerization are dysregulation in epithelial-mesenchymal interactions, in cell-to-cell communication, in extracellular matrix turnover, in extracellular matrix-to-cell interactions and in mechanotransduction pathways. Persistent increase in extracellular matrix stiffness, for whatever reason, has been shown to play an important role in cell transformation, and later in cancer cell invasion. In this article we review certain cell regulatory networks driving carcinogenesis, focussing on the role of mechanical stresses modulating structure and function of cells and their extracellular matrices.

Characterizing Male–Female Interactions Using Natural Genetic Variation in Drosophila melanogaster

PubMed Central

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

[Nutritional genomics: an approach to the genome-environment interaction].

PubMed

Xacur-García, Fiona; Castillo-Quan, Jorge I; Hernández-Escalante, Víctor M; Laviada-Molina, Hugo

2008-11-01

Nutritional genomics forms part of the genomic sciences and addresses the interaction between genes and the human diet, its influence on metabolism and subsequent susceptibility to develop common diseases. It encompasses both nutrigenomics, which explores the effects of nutrients on the genome, proteome and metabolome; and nutrigenetics, that explores the effects of genetic variations on the diet/disease interaction. A number of mechanisms drive the gene/diet interaction: elements in the diet can act as links for transcription factor receptors and after intermediary concentrations, thereby modifying chromatin and impacting genetic regulation; affect signal pathways, regulating phosphorylation of tyrosine in receptors; decrease signaling through the inositol pathway; and act through epigenetic mechanisms, silencing DNA fragments by methylation of cytosine. The signals generated by polyunsaturated fatty acids are so powerful that they can even bypass insulin mediated lipogenesis, stimulated by carbohydrates. Some fatty acids modify the expression of genes that participate in fatty acid transport by lipoproteins. Nutritional genomics has myriad possible therapeutic and preventive applications: in patients with enzymatic deficiencies; in those with a genetic predisposition to complex diseases such as dyslipidemia, diabetes and cancer; in those that already suffer these diseases; in those with altered mood or memory; during the aging process; in pregnant women; and as a preventive measure in the healthy population.

The genetics of childhood obesity and interaction with dietary macronutrients.

PubMed

Garver, William S; Newman, Sara B; Gonzales-Pacheco, Diana M; Castillo, Joseph J; Jelinek, David; Heidenreich, Randall A; Orlando, Robert A

2013-05-01

The genes contributing to childhood obesity are categorized into three different types based on distinct genetic and phenotypic characteristics. These types of childhood obesity are represented by rare monogenic forms of syndromic or non-syndromic childhood obesity, and common polygenic childhood obesity. In some cases, genetic susceptibility to these forms of childhood obesity may result from different variations of the same gene. Although the prevalence for rare monogenic forms of childhood obesity has not increased in recent times, the prevalence of common childhood obesity has increased in the United States and developing countries throughout the world during the past few decades. A number of recent genome-wide association studies and mouse model studies have established the identification of susceptibility genes contributing to common childhood obesity. Accumulating evidence suggests that this type of childhood obesity represents a complex metabolic disease resulting from an interaction with environmental factors, including dietary macronutrients. The objective of this article is to provide a review on the origins, mechanisms, and health consequences of obesity susceptibility genes and interaction with dietary macronutrients that predispose to childhood obesity. It is proposed that increased knowledge of these obesity susceptibility genes and interaction with dietary macronutrients will provide valuable insight for individual, family, and community preventative lifestyle intervention, and eventually targeted nutritional and medicinal therapies.

Genetic Basis of Atherosclerosis: Insights from Mice and Humans

PubMed Central

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

Genetic factors of age-related macular degeneration

PubMed Central

Tuo, Jingsheng; Bojanowski, Christine M.; Chan, Chi-Chao

2007-01-01

Age-related macular degeneration (AMD) is a leading cause of blindness in the United States and developed countries. Although the etiology and pathogenesis of AMD remain unknown, a complex interaction of genetic and environmental factors is thought to exist. The incidence and progression of all of the features of AMD are known to increase significantly with age. The tendency for familial aggregation and the findings of gene variation association studies implicate a significant genetic component in the development of AMD. This review summarizes in detail the AMD-related genes identified by studies on genetically engineered and spontaneously gene-mutated (naturally mutated) animals, AMD chromosomal loci identified by linkage studies, AMD-related genes identified through studies of monogenic degenerative retinal diseases, and AMD-related gene variation identified by association studies. PMID:15094132

Genetic programming approach to evaluate complexity of texture images

NASA Astrophysics Data System (ADS)

Ciocca, Gianluigi; Corchs, Silvia; Gasparini, Francesca

2016-11-01

We adopt genetic programming (GP) to define a measure that can predict complexity perception of texture images. We perform psychophysical experiments on three different datasets to collect data on the perceived complexity. The subjective data are used for training, validation, and test of the proposed measure. These data are also used to evaluate several possible candidate measures of texture complexity related to both low level and high level image features. We select four of them (namely roughness, number of regions, chroma variance, and memorability) to be combined in a GP framework. This approach allows a nonlinear combination of the measures and could give hints on how the related image features interact in complexity perception. The proposed complexity measure M exhibits Pearson correlation coefficients of 0.890 on the training set, 0.728 on the validation set, and 0.724 on the test set. M outperforms each of all the single measures considered. From the statistical analysis of different GP candidate solutions, we found that the roughness measure evaluated on the gray level image is the most dominant one, followed by the memorability, the number of regions, and finally the chroma variance.

Genetic analysis of the cytoplasmic dynein subunit families.

PubMed

Pfister, K Kevin; Shah, Paresh R; Hummerich, Holger; Russ, Andreas; Cotton, James; Annuar, Azlina Ahmad; King, Stephen M; Fisher, Elizabeth M C

2006-01-01

Cytoplasmic dyneins, the principal microtubule minus-end-directed motor proteins of the cell, are involved in many essential cellular processes. The major form of this enzyme is a complex of at least six protein subunits, and in mammals all but one of the subunits are encoded by at least two genes. Here we review current knowledge concerning the subunits, their interactions, and their functional roles as derived from biochemical and genetic analyses. We also carried out extensive database searches to look for new genes and to clarify anomalies in the databases. Our analysis documents evolutionary relationships among the dynein subunits of mammals and other model organisms, and sheds new light on the role of this diverse group of proteins, highlighting the existence of two cytoplasmic dynein complexes with distinct cellular roles.

Genetic Analysis of the Cytoplasmic Dynein Subunit Families

PubMed Central

Pfister, K. Kevin; Shah, Paresh R; Hummerich, Holger; Russ, Andreas; Cotton, James; Annuar, Azlina Ahmad; King, Stephen M; Fisher, Elizabeth M. C

2006-01-01

Cytoplasmic dyneins, the principal microtubule minus-end-directed motor proteins of the cell, are involved in many essential cellular processes. The major form of this enzyme is a complex of at least six protein subunits, and in mammals all but one of the subunits are encoded by at least two genes. Here we review current knowledge concerning the subunits, their interactions, and their functional roles as derived from biochemical and genetic analyses. We also carried out extensive database searches to look for new genes and to clarify anomalies in the databases. Our analysis documents evolutionary relationships among the dynein subunits of mammals and other model organisms, and sheds new light on the role of this diverse group of proteins, highlighting the existence of two cytoplasmic dynein complexes with distinct cellular roles. PMID:16440056

Genetic mouse models relevant to schizophrenia: taking stock and looking forward.

PubMed

Harrison, Paul J; Pritchett, David; Stumpenhorst, Katharina; Betts, Jill F; Nissen, Wiebke; Schweimer, Judith; Lane, Tracy; Burnet, Philip W J; Lamsa, Karri P; Sharp, Trevor; Bannerman, David M; Tunbridge, Elizabeth M

2012-03-01

Genetic mouse models relevant to schizophrenia complement, and have to a large extent supplanted, pharmacological and lesion-based rat models. The main attraction is that they potentially have greater construct validity; however, they share the fundamental limitations of all animal models of psychiatric disorder, and must also be viewed in the context of the uncertain and complex genetic architecture of psychosis. Some of the key issues, including the choice of gene to target, the manner of its manipulation, gene-gene and gene-environment interactions, and phenotypic characterization, are briefly considered in this commentary, illustrated by the relevant papers reported in this special issue. Copyright © 2011 Elsevier Ltd. All rights reserved.

Biomarkers in Autism

PubMed Central

Goldani, Andre A. S.; Downs, Susan R.; Widjaja, Felicia; Lawton, Brittany; Hendren, Robert L.

2014-01-01

Autism spectrum disorders (ASDs) are complex, heterogeneous disorders caused by an interaction between genetic vulnerability and environmental factors. In an effort to better target the underlying roots of ASD for diagnosis and treatment, efforts to identify reliable biomarkers in genetics, neuroimaging, gene expression, and measures of the body’s metabolism are growing. For this article, we review the published studies of potential biomarkers in autism and conclude that while there is increasing promise of finding biomarkers that can help us target treatment, there are none with enough evidence to support routine clinical use unless medical illness is suspected. Promising biomarkers include those for mitochondrial function, oxidative stress, and immune function. Genetic clusters are also suggesting the potential for useful biomarkers. PMID:25161627

Myopathology of Adult and Paediatric Mitochondrial Diseases

PubMed Central

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

SLP-2 interacts with Parkin in mitochondria and prevents mitochondrial dysfunction in Parkin-deficient human iPSC-derived neurons and Drosophila.

PubMed

Zanon, Alessandra; Kalvakuri, Sreehari; Rakovic, Aleksandar; Foco, Luisa; Guida, Marianna; Schwienbacher, Christine; Serafin, Alice; Rudolph, Franziska; Trilck, Michaela; Grünewald, Anne; Stanslowsky, Nancy; Wegner, Florian; Giorgio, Valentina; Lavdas, Alexandros A; Bodmer, Rolf; Pramstaller, Peter P; Klein, Christine; Hicks, Andrew A; Pichler, Irene; Seibler, Philip

2017-07-01

Mutations in the Parkin gene (PARK2) have been linked to a recessive form of Parkinson's disease (PD) characterized by the loss of dopaminergic neurons in the substantia nigra. Deficiencies of mitochondrial respiratory chain complex I activity have been observed in the substantia nigra of PD patients, and loss of Parkin results in the reduction of complex I activity shown in various cell and animal models. Using co-immunoprecipitation and proximity ligation assays on endogenous proteins, we demonstrate that Parkin interacts with mitochondrial Stomatin-like protein 2 (SLP-2), which also binds the mitochondrial lipid cardiolipin and functions in the assembly of respiratory chain proteins. SH-SY5Y cells with a stable knockdown of Parkin or SLP-2, as well as induced pluripotent stem cell-derived neurons from Parkin mutation carriers, showed decreased complex I activity and altered mitochondrial network morphology. Importantly, induced expression of SLP-2 corrected for these mitochondrial alterations caused by reduced Parkin function in these cells. In-vivo Drosophila studies showed a genetic interaction of Parkin and SLP-2, and further, tissue-specific or global overexpression of SLP-2 transgenes rescued parkin mutant phenotypes, in particular loss of dopaminergic neurons, mitochondrial network structure, reduced ATP production, and flight and motor dysfunction. The physical and genetic interaction between Parkin and SLP-2 and the compensatory potential of SLP-2 suggest a functional epistatic relationship to Parkin and a protective role of SLP-2 in neurons. This finding places further emphasis on the significance of Parkin for the maintenance of mitochondrial function in neurons and provides a novel target for therapeutic strategies. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Clinical Applications of Molecular Genetic Discoveries

PubMed Central

Marian, A.J.

2015-01-01

Genome-wide association studies (GWAS) of complex traits have mapped more than 15,000 common single nucleotide variants (SNVs). Likewise, applications of massively parallel nucleic acid sequencing technologies often referred to as Next Generation Sequencing, to molecular genetic studies of complex traits have catalogued a large number of rare variants (population frequency of <0.01) in cases with complex traits. Moreover, high throughput nucleic acid sequencing, variant burden analysis, and linkage studies are illuminating the presence of large number of SNVs in cases and families with single gene disorders. The plethora of the genetic variants has exposed the formidable challenge of identifying the causal and pathogenic variants from the enormous number of innocuous common and rare variants that exist in the population as well as in an individual genome. The arduous task of identifying the causal and pathogenic variants is further compounded by the pleiotropic effects of the variants, complexity of cis and trans interactions in the genome, variability in phenotypic expression of the disease, as well as phenotypic plasticity, and the multifarious determinants of the phenotype. Population genetic studies offer the initial roadmaps and have the potential to elucidate novel pathways involved in the pathogenesis of the disease. However, the genome of an individual is unique, rendering unambiguous identification of the causal or pathogenic variant in a single individual exceedingly challenging. Yet, the focus of the practice of medicine is on the individual, as Sir William Osler elegantly expressed in his insightful quotation: “The good physician treats the disease; the great physician treats the patient who has the disease.” The daunting task facing physicians, patients, and researchers alike is to apply the modern genetic discoveries to care of the individual with or at risk of the disease. PMID:26548329

Genetic Interactions Between the Meiosis-Specific Cohesin Components, STAG3, REC8, and RAD21L.

PubMed

Ward, Ayobami; Hopkins, Jessica; Mckay, Matthew; Murray, Steve; Jordan, Philip W

2016-06-01

Cohesin is an essential structural component of chromosomes that ensures accurate chromosome segregation during mitosis and meiosis. Previous studies have shown that there are cohesin complexes specific to meiosis, required to mediate homologous chromosome pairing, synapsis, recombination, and segregation. Meiosis-specific cohesin complexes consist of two structural maintenance of chromosomes proteins (SMC1α/SMC1β and SMC3), an α-kleisin protein (RAD21, RAD21L, or REC8), and a stromal antigen protein (STAG1, 2, or 3). STAG3 is exclusively expressed during meiosis, and is the predominant STAG protein component of cohesin complexes in primary spermatocytes from mouse, interacting directly with each α-kleisin subunit. REC8 and RAD21L are also meiosis-specific cohesin components. Stag3 mutant spermatocytes arrest in early prophase ("zygotene-like" stage), displaying failed homolog synapsis and persistent DNA damage, as a result of unstable loading of cohesin onto the chromosome axes. Interestingly, Rec8, Rad21L double mutants resulted in an earlier "leptotene-like" arrest, accompanied by complete absence of STAG3 loading. To assess genetic interactions between STAG3 and α-kleisin subunits RAD21L and REC8, our lab generated Stag3, Rad21L, and Stag3, Rec8 double knockout mice, and compared them to the Rec8, Rad21L double mutant. These double mutants are phenotypically distinct from one another, and more severe than each single knockout mutant with regards to chromosome axis formation, cohesin loading, and sister chromatid cohesion. The Stag3, Rad21L, and Stag3, Rec8 double mutants both progress further into prophase I than the Rec8, Rad21L double mutant. Our genetic analysis demonstrates that cohesins containing STAG3 and REC8 are the main complex required for centromeric cohesion, and RAD21L cohesins are required for normal clustering of pericentromeric heterochromatin. Furthermore, the STAG3/REC8 and STAG3/RAD21L cohesins are the primary cohesins required for axis formation. Copyright © 2016 Ward et al.

The golgin protein Coy1 functions in intra-Golgi retrograde transport and interacts with the COG complex and Golgi SNAREs

PubMed Central

Anderson, Nadine S.; Mukherjee, Indrani; Bentivoglio, Christine M.; Barlowe, Charles

2017-01-01

Extended coiled-coil proteins of the golgin family play prominent roles in maintaining the structure and function of the Golgi complex. Here we further investigate the golgin protein Coy1 and document its function in retrograde transport between early Golgi compartments. Cells that lack Coy1 displayed a reduced half-life of the Och1 mannosyltransferase, an established cargo of intra-Golgi retrograde transport. Combining the coy1Δ mutation with deletions in other putative retrograde golgins (sgm1Δ and rud3Δ) caused strong glycosylation and growth defects and reduced membrane association of the conserved oligomeric Golgi (COG) complex. In contrast, overexpression of COY1 inhibited the growth of mutant strains deficient in fusion activity at the Golgi (sed5-1 and sly1-ts). To map Coy1 protein interactions, coimmunoprecipitation experiments revealed an association with the COG complex and with intra-Golgi SNARE proteins. These physical interactions are direct, as Coy1 was efficiently captured in vitro by Lobe A of the COG complex and the purified SNARE proteins Gos1, Sed5, and Sft1. Thus our genetic, in vivo, and biochemical data indicate a role for Coy1 in regulating COG complex-dependent fusion of retrograde-directed COPI vesicles. PMID:28794270

Screening large-scale association study data: exploiting interactions using random forests.

PubMed

Lunetta, Kathryn L; Hayward, L Brooke; Segal, Jonathan; Van Eerdewegh, Paul

2004-12-10

Genome-wide association studies for complex diseases will produce genotypes on hundreds of thousands of single nucleotide polymorphisms (SNPs). A logical first approach to dealing with massive numbers of SNPs is to use some test to screen the SNPs, retaining only those that meet some criterion for further study. For example, SNPs can be ranked by p-value, and those with the lowest p-values retained. When SNPs have large interaction effects but small marginal effects in a population, they are unlikely to be retained when univariate tests are used for screening. However, model-based screens that pre-specify interactions are impractical for data sets with thousands of SNPs. Random forest analysis is an alternative method that produces a single measure of importance for each predictor variable that takes into account interactions among variables without requiring model specification. Interactions increase the importance for the individual interacting variables, making them more likely to be given high importance relative to other variables. We test the performance of random forests as a screening procedure to identify small numbers of risk-associated SNPs from among large numbers of unassociated SNPs using complex disease models with up to 32 loci, incorporating both genetic heterogeneity and multi-locus interaction. Keeping other factors constant, if risk SNPs interact, the random forest importance measure significantly outperforms the Fisher Exact test as a screening tool. As the number of interacting SNPs increases, the improvement in performance of random forest analysis relative to Fisher Exact test for screening also increases. Random forests perform similarly to the univariate Fisher Exact test as a screening tool when SNPs in the analysis do not interact. In the context of large-scale genetic association studies where unknown interactions exist among true risk-associated SNPs or SNPs and environmental covariates, screening SNPs using random forest analyses can significantly reduce the number of SNPs that need to be retained for further study compared to standard univariate screening methods.

Genetic Mechanisms Leading to Sex Differences Across Common Diseases and Anthropometric Traits

PubMed Central

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

Inference of RhoGAP/GTPase regulation using single-cell morphological data from a combinatorial RNAi screen.

PubMed

Nir, Oaz; Bakal, Chris; Perrimon, Norbert; Berger, Bonnie

2010-03-01

Biological networks are highly complex systems, consisting largely of enzymes that act as molecular switches to activate/inhibit downstream targets via post-translational modification. Computational techniques have been developed to perform signaling network inference using some high-throughput data sources, such as those generated from transcriptional and proteomic studies, but comparable methods have not been developed to use high-content morphological data, which are emerging principally from large-scale RNAi screens, to these ends. Here, we describe a systematic computational framework based on a classification model for identifying genetic interactions using high-dimensional single-cell morphological data from genetic screens, apply it to RhoGAP/GTPase regulation in Drosophila, and evaluate its efficacy. Augmented by knowledge of the basic structure of RhoGAP/GTPase signaling, namely, that GAPs act directly upstream of GTPases, we apply our framework for identifying genetic interactions to predict signaling relationships between these proteins. We find that our method makes mediocre predictions using only RhoGAP single-knockdown morphological data, yet achieves vastly improved accuracy by including original data from a double-knockdown RhoGAP genetic screen, which likely reflects the redundant network structure of RhoGAP/GTPase signaling. We consider other possible methods for inference and show that our primary model outperforms the alternatives. This work demonstrates the fundamental fact that high-throughput morphological data can be used in a systematic, successful fashion to identify genetic interactions and, using additional elementary knowledge of network structure, to infer signaling relations.

Genetic architecture of natural variation in Drosophila melanogaster aggressive behavior

PubMed Central

Shorter, John; Couch, Charlene; Huang, Wen; Carbone, Mary Anna; Peiffer, Jason; Anholt, Robert R. H.; Mackay, Trudy F. C.

2015-01-01

Aggression is an evolutionarily conserved complex behavior essential for survival and the organization of social hierarchies. With the exception of genetic variants associated with bioamine signaling, which have been implicated in aggression in many species, the genetic basis of natural variation in aggression is largely unknown. Drosophila melanogaster is a favorable model system for exploring the genetic basis of natural variation in aggression. Here, we performed genome-wide association analyses using the inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) and replicate advanced intercross populations derived from the most and least aggressive DGRP lines. We identified genes that have been previously implicated in aggressive behavior as well as many novel loci, including gustatory receptor 63a (Gr63a), which encodes a subunit of the receptor for CO2, and genes associated with development and function of the nervous system. Although genes from the two association analyses were largely nonoverlapping, they mapped onto a genetic interaction network inferred from an analysis of pairwise epistasis in the DGRP. We used mutations and RNAi knock-down alleles to functionally validate 79% of the candidate genes and 75% of the candidate epistatic interactions tested. Epistasis for aggressive behavior causes cryptic genetic variation in the DGRP that is revealed by changing allele frequencies in the outbred populations derived from extreme DGRP lines. This phenomenon may pertain to other fitness traits and species, with implications for evolution, applied breeding, and human genetics. PMID:26100892

A System-Level Pathway-Phenotype Association Analysis Using Synthetic Feature Random Forest

PubMed Central

Pan, Qinxin; Hu, Ting; Malley, James D.; Andrew, Angeline S.; Karagas, Margaret R.; Moore, Jason H.

2015-01-01

As the cost of genome-wide genotyping decreases, the number of genome-wide association studies (GWAS) has increased considerably. However, the transition from GWAS findings to the underlying biology of various phenotypes remains challenging. As a result, due to its system-level interpretability, pathway analysis has become a popular tool for gaining insights on the underlying biology from high-throughput genetic association data. In pathway analyses, gene sets representing particular biological processes are tested for significant associations with a given phenotype. Most existing pathway analysis approaches rely on single-marker statistics and assume that pathways are independent of each other. As biological systems are driven by complex biomolecular interactions, embracing the complex relationships between single-nucleotide polymorphisms (SNPs) and pathways needs to be addressed. To incorporate the complexity of gene-gene interactions and pathway-pathway relationships, we propose a system-level pathway analysis approach, synthetic feature random forest (SF-RF), which is designed to detect pathway-phenotype associations without making assumptions about the relationships among SNPs or pathways. In our approach, the genotypes of SNPs in a particular pathway are aggregated into a synthetic feature representing that pathway via Random Forest (RF). Multiple synthetic features are analyzed using RF simultaneously and the significance of a synthetic feature indicates the significance of the corresponding pathway. We further complement SF-RF with pathway-based Statistical Epistasis Network (SEN) analysis that evaluates interactions among pathways. By investigating the pathway SEN, we hope to gain additional insights into the genetic mechanisms contributing to the pathway-phenotype association. We apply SF-RF to a population-based genetic study of bladder cancer and further investigate the mechanisms that help explain the pathway-phenotype associations using SEN. The bladder cancer associated pathways we found are both consistent with existing biological knowledge and reveal novel and plausible hypotheses for future biological validations. PMID:24535726

Genome-Wide Analysis of Grain Yield Stability and Environmental Interactions in a Multiparental Soybean Population.

PubMed

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.

Genetic risk variants as therapeutic targets for Crohn's disease.

PubMed

Gabbani, Tommaso; Deiana, Simona; Marocchi, Margherita; Annese, Vito

2017-04-01

The pathogenesis of Inflammatory bowel diseases (IBD) is multifactorial, with interactions between genetic and environmental factors. Despite the existence of genetic factors being largely demonstrated by epidemiological data and several genetic studies, only a few findings have been useful in term of disease prediction, disease progression and targeting therapy. Areas covered: This review summarizes the results of genome-wide association studies in Crohn's disease, the role of epigenetics and the recent discovery by genetic studies of new pathogenetic pathways. Furthermore, it focuses on the importance of applying genetic data to clinical practice, and more specifically how to better target therapy and predict potential drug-related toxicity. Expert opinion: Some genetic markers identified in Crohn`s disease have allowed investigators to hypothesize about, and in some cases, prove the usefulness of new specific therapeutic agents. However, the heterogeneity and complexity of this disease has so far limited the daily clinical use of genetic information. Finally, the study of the implications of genetics on therapy, either to predict efficacy or avoid toxicity, is considered still to be in its infancy.

Beyond genome-wide association studies: genetic heterogeneity and individual predisposition to cancer

PubMed Central

Galvan, Antonella; Ioannidis, John P.A.; Dragani, Tommaso A.

2010-01-01

Genome-wide association studies (GWAS) using population-based designs have identified many genetic loci associated with risk of a range of complex diseases including cancer; however, each locus exerts a very small effect and most heritability remains unexplained. Family-based pedigree studies have also suggested tentative loci linked to increased cancer risk, often characterized by pedigree-specificity. However, a comparison between the results of population-and those of family-based studies shows little concordance. Explanations for this unidentified genetic ‘dark matter’ of cancer include phenotype ascertainment issues, limited power, gene-gene and gene-environment interactions, population heterogeneity, parent-of-origin-specific effects, rare and unexplored variants. Many of these reasons converge towards the concept of genetic heterogeneity that might implicate hundreds of genetic variants in regulating cancer risk. Dissecting the dark matter is a challenging task. Further insights can be gained from both population association and pedigree studies. PMID:20106545

Interaction between catechol-O-methyltransferase (COMT) Val158Met genotype and genetic vulnerability to schizophrenia during explicit processing of aversive facial stimuli.

PubMed

Lo Bianco, L; Blasi, G; Taurisano, P; Di Giorgio, A; Ferrante, F; Ursini, G; Fazio, L; Gelao, B; Romano, R; Papazacharias, A; Caforio, G; Sinibaldi, L; Popolizio, T; Bellantuono, C; Bertolino, A

2013-02-01

Emotion dysregulation is a key feature of schizophrenia, a brain disorder strongly associated with genetic risk and aberrant dopamine signalling. Dopamine is inactivated by catechol-O-methyltransferase (COMT), whose gene contains a functional polymorphism (COMT Val158Met) associated with differential activity of the enzyme and with brain physiology of emotion processing. The aim of the present study was to investigate whether genetic risk for schizophrenia and COMT Val158Met genotype interact on brain activity during implicit and explicit emotion processing. A total of 25 patients with schizophrenia, 23 healthy siblings of patients and 24 comparison subjects genotyped for COMT Val158Met underwent functional magnetic resonance imaging during implicit and explicit processing of facial stimuli with negative emotional valence. We found a main effect of diagnosis in the right amygdala, with decreased activity in patients and siblings compared with control subjects. Furthermore, a genotype × diagnosis interaction was found in the left middle frontal gyrus, such that the effect of genetic risk for schizophrenia was evident in the context of the Val/Val genotype only, i.e. the phenotype of reduced activity was present especially in Val/Val patients and siblings. Finally, a complete inversion of the COMT effect between patients and healthy subjects was found in the left striatum during explicit processing. Overall, these results suggest complex interactions between genetically determined dopamine signalling and risk for schizophrenia on brain activity in the prefrontal cortex during emotion processing. On the other hand, the effects in the striatum may represent state-related epiphenomena of the disorder itself.

Investigating the modulation of genetic effects on late AMD by age and sex: Lessons learned and two additional loci

PubMed Central

Grassmann, Felix; Gorski, Mathias; Loss, Julika; Heid, Iris M.

2018-01-01

Late-stage age-related macular degeneration (AMD) is the leading cause of visual impairment in the elderly with a complex etiology. The most important non-modifiable risk factors for onset and progression of late AMD are age and genetic risk factors, however, little is known about the interplay between genetics and age or sex. Here, we conducted a large-scale age- and sex-stratified genome-wide association study (GWAS) using 1000 Genomes imputed genome-wide and ExomeChip data (>12 million variants). The data were established by the International Age-related Macular Degeneration Genomics Consortium (IAMDGC) from 16,144 late AMD cases and 17,832 controls. Our systematic search for interaction effects yielded significantly stronger effects among younger individuals at two known AMD loci (near CFH and ARMS2/HTRA1). Accounting for age and gene-age interaction using a joint test identified two additional AMD loci compared to the previous main effect scan. One of these two is a novel AMD GWAS locus, near the retinal clusterin-like protein (CLUL1) gene, and the other, near the retinaldehyde binding protein 1 (RLBP1), was recently identified in a joint analysis of nuclear and mitochondrial variants. Despite considerable power in our data, neither sex-dependent effects nor effects with opposite directions between younger and older individuals were observed. This is the first genome-wide interaction study to incorporate age, sex and their interaction with genetic effects for late AMD. Results diminish the potential for a role of sex in the etiology of late AMD yet highlight the importance and existence of age-dependent genetic effects. PMID:29529059

An information-gain approach to detecting three-way epistatic interactions in genetic association studies

PubMed Central

Hu, Ting; Chen, Yuanzhu; Kiralis, Jeff W; Collins, Ryan L; Wejse, Christian; Sirugo, Giorgio; Williams, Scott M; Moore, Jason H

2013-01-01

Background Epistasis has been historically used to describe the phenomenon that the effect of a given gene on a phenotype can be dependent on one or more other genes, and is an essential element for understanding the association between genetic and phenotypic variations. Quantifying epistasis of orders higher than two is very challenging due to both the computational complexity of enumerating all possible combinations in genome-wide data and the lack of efficient and effective methodologies. Objectives In this study, we propose a fast, non-parametric, and model-free measure for three-way epistasis. Methods Such a measure is based on information gain, and is able to separate all lower order effects from pure three-way epistasis. Results Our method was verified on synthetic data and applied to real data from a candidate-gene study of tuberculosis in a West African population. In the tuberculosis data, we found a statistically significant pure three-way epistatic interaction effect that was stronger than any lower-order associations. Conclusion Our study provides a methodological basis for detecting and characterizing high-order gene-gene interactions in genetic association studies. PMID:23396514

The genetic basis of developmental abnormalities in interpopulation hybrids of the moss Ceratodon purpureus.

PubMed

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.

QTL analysis of genotype x environment interactions affecting cotton fiber quality.

PubMed

Paterson, A H; Saranga, Y; Menz, M; Jiang, C-X; Wright, R J

2003-02-01

Cotton is unusual among major crops in that large acreages are grown under both irrigated and rainfed conditions, making genotype x environment interactions of even greater importance than usual in designing crop-improvement strategies. We describe the impact of well-watered versus water-limited growth conditions on the genetic control of fiber quality, a complex suite of traits that collectively determine the utility of cotton. Fiber length, length uniformity, elongation, strength, fineness, and color (yellowness) were influenced by 6, 7, 9, 21, 25 and 11 QTLs (respectively) that could be detected in one or more treatments. The genetic control of cotton fiber quality was markedly affected both by general differences between growing seasons ("years") and by specific differences in water management regimes. Seventeen QTLs were detected only in the water-limited treatment while only two were specific to the well-watered treatment, suggesting that improvement of fiber quality under water stress may be even more complicated than improvement of this already complex trait under well-watered conditions. In crops such as cotton with widespread use of both irrigated and rainfed production systems, the need to manipulate larger numbers of genes to confer adequate quality under both sets of conditions will reduce the expected rate of genetic gain. These difficulties may be partly ameliorated by efficiencies gained through identification and use of diagnostic DNA markers, including those identified herein.

Interactions of the Immune System with Skin and Bone Tissue in Psoriatic Arthritis: A Comprehensive Review.

PubMed

Sukhov, Andrea; Adamopoulos, Iannis E; Maverakis, Emanual

2016-08-01

Cutaneous psoriasis (e.g., psoriasis vulgaris (PsV)) and psoriatic arthritis (PsA) are complex heterogeneous diseases thought to have similar pathophysiology. The soluble and cellular mediators of these closely related diseases are being elucidated through genetic approaches such as genome-wide association studies (GWAS), as well as animal and molecular models. Novel therapeutics targeting these mediators (IL-12, IL-23, IL-17, IL-17 receptor, TNF) are effective in treating both the skin and joint manifestations of psoriasis, reaffirming the shared pathophysiology of PsV and PsA. However, the molecular and cellular interactions between skin and joint disease have not been well characterized. Clearly, PsV and PsA are highly variable in terms of their clinical manifestations, and this heterogeneity can partially be explained by differences in HLA-associations (HLA-Cw*0602 versus HLA-B*27, for example). In addition, there are numerous other genetic susceptibility loci (LCE3, CARD14, NOS2, NFKBIA, PSMA6, ERAP1, TRAF3IP2, IL12RB2, IL23R, IL12B, TNIP1, TNFAIP3, TYK2) and geoepidemiologic factors that contribute to the wide variability seen in psoriasis. Herein, we review the complex interplay between the genetic, cellular, ethnic, and geographic mediators of psoriasis, focusing on the shared mechanisms of PsV and PsA.

Mitochondrial DNA diversity in two ethnic groups in southeastern Kenya: perspectives from the northeastern periphery of the Bantu expansion

PubMed Central

Batai, Ken; Babrowski, Kara B.; Arroyo, Juan Pablo; Kusimba, Chapurukha M.; Williams, Sloan R.

2013-01-01

The Bantu languages are widely distributed throughout sub-Saharan Africa. Genetic research supports linguists and historians who argue that migration played an important role in the spread of this language family, but the genetic data also indicates a more complex process involving substantial gene flow with resident populations. In order to understand the Bantu expansion process in east Africa, mtDNA hypervariable region I variation in 352 individuals from the Taita and Mijikenda ethnic groups was analyzed, and we evaluated the interactions that took place between the Bantu- and non-Bantu-speaking populations in east Africa. The Taita and Mijikenda are Bantu-speaking agropastoralists from southeastern Kenya, at least some of whose ancestors probably migrated into the area as part of Bantu migrations that began around 3,000 BCE. Our analyses indicate that they show some distinctive differences that reflect their unique cultural histories. The Taita are genetically more diverse than the Mijikenda with larger estimates of genetic diversity. The Taita cluster with other east African groups, having high frequencies of haplogroups from that region, while the Mijikenda have high frequencies of central African haplogroups and cluster more closely with central African Bantu-speaking groups. The non-Bantu speakers who lived in southeastern Kenya before Bantu speaking groups arrived were at least partially incorporated into what are now Bantu-speaking Taita groups. In contrast, gene flow from non-Bantu speakers into the Mijikenda was more limited. These results suggest a more complex demographic history where the nature of Bantu and non-Bantu interactions varied throughout the area. PMID:23382080

Nasal Bone Shape Is under Complex Epistatic Genetic Control in Mouse Interspecific Recombinant Congenic Strains

PubMed Central

Burgio, Gaétan; Baylac, Michel; Heyer, Evelyne; Montagutelli, Xavier

2012-01-01

Background Genetic determinism of cranial morphology in the mouse is still largely unknown, despite the localization of putative QTLs and the identification of genes associated with Mendelian skull malformations. To approach the dissection of this multigenic control, we have used a set of interspecific recombinant congenic strains (IRCS) produced between C57BL/6 and mice of the distant species Mus spretus (SEG/Pas). Each strain has inherited 1.3% of its genome from SEG/Pas under the form of few, small-sized, chromosomal segments. Results The shape of the nasal bone was studied using outline analysis combined with Fourier descriptors, and differential features were identified between IRCS BcG-66H and C57BL/6. An F2 cross between BcG-66H and C57BL/6 revealed that, out of the three SEG/Pas-derived chromosomal regions present in BcG-66H, two were involved. Segments on chromosomes 1 (∼32 Mb) and 18 (∼13 Mb) showed additive effect on nasal bone shape. The three chromosomal regions present in BcG-66H were isolated in congenic strains to study their individual effect. Epistatic interactions were assessed in bicongenic strains. Conclusions Our results show that, besides a strong individual effect, the QTL on chromosome 1 interacts with genes on chromosomes 13 and 18. This study demonstrates that nasal bone shape is under complex genetic control but can be efficiently dissected in the mouse using appropriate genetic tools and shape descriptors. PMID:22662199

Spatio-temporal variation in parasite communities maintains diversity at the major histocompatibility complex class IIβ in the endangered Rio Grande silvery minnow.

PubMed

Osborne, Megan J; Pilger, Tyler J; Lusk, Joel D; Turner, Thomas F

2017-01-01

Climate change will strongly impact aquatic ecosystems particularly in arid and semi-arid regions. Fish-parasite interactions will also be affected by predicted altered flow and temperature regimes, and other environmental stressors. Hence, identifying environmental and genetic factors associated with maintaining diversity at immune genes is critical for understanding species' adaptive capacity. Here, we combine genetic (MHC class IIβ and microsatellites), parasitological and ecological data to explore the relationship between these factors in the remnant wild Rio Grande silvery minnow (Hybognathus amarus) population, an endangered species found in the southwestern United States. Infections with multiple parasites on the gills were observed and there was spatio-temporal variation in parasite communities and patterns of infection among individuals. Despite its highly endangered status and chronically low genetic effective size, Rio Grande silvery minnow had high allelic diversity at MHC class IIβ with more alleles recognized at the presumptive DAB1 locus compared to the DAB3 locus. We identified significant associations between specific parasites and MHC alleles against a backdrop of generalist parasite prevalence. We also found that individuals with higher individual neutral heterozygosity and higher amino acid divergence between MHC alleles had lower parasite abundance and diversity. Taken together, these results suggest a role for fluctuating selection imposed by spatio-temporal variation in pathogen communities and divergent allele advantage in maintenance of high MHC polymorphism. Understanding the complex interaction of habitat, pathogens and immunity in protected species will require integrated experimental, genetic and field studies. © 2016 John Wiley & Sons Ltd.

The filamentous fungus Sordaria macrospora as a genetic model to study fruiting body development.

PubMed

Teichert, Ines; Nowrousian, Minou; Pöggeler, Stefanie; Kück, Ulrich

2014-01-01

Filamentous fungi are excellent experimental systems due to their short life cycles as well as easy and safe manipulation in the laboratory. They form three-dimensional structures with numerous different cell types and have a long tradition as genetic model organisms used to unravel basic mechanisms underlying eukaryotic cell differentiation. The filamentous ascomycete Sordaria macrospora is a model system for sexual fruiting body (perithecia) formation. S. macrospora is homothallic, i.e., self-fertile, easily genetically tractable, and well suited for large-scale genomics, transcriptomics, and proteomics studies. Specific features of its life cycle and the availability of a developmental mutant library make it an excellent system for studying cellular differentiation at the molecular level. In this review, we focus on recent developments in identifying gene and protein regulatory networks governing perithecia formation. A number of tools have been developed to genetically analyze developmental mutants and dissect transcriptional profiles at different developmental stages. Protein interaction studies allowed us to identify a highly conserved eukaryotic multisubunit protein complex, the striatin-interacting phosphatase and kinase complex and its role in sexual development. We have further identified a number of proteins involved in chromatin remodeling and transcriptional regulation of fruiting body development. Furthermore, we review the involvement of metabolic processes from both primary and secondary metabolism, and the role of nutrient recycling by autophagy in perithecia formation. Our research has uncovered numerous players regulating multicellular development in S. macrospora. Future research will focus on mechanistically understanding how these players are orchestrated in this fungal model system. Copyright © 2014 Elsevier Inc. All rights reserved.

The Interactions between the Long Non-coding RNA NERDL and Its Target Gene Affect Wood Formation in Populus tomentosa

PubMed Central

Shi, Wan; Quan, Mingyang; Du, Qingzhang; Zhang, Deqiang

2017-01-01

Long non-coding RNAs (lncRNAs) are important regulatory factors for plant growth and development, but little is known about the allelic interactions of lncRNAs with mRNA in perennial plants. Here, we analyzed the interaction of the NERD (Needed for RDR2-independent DNA methylation) Populus tomentosa gene PtoNERD with its putative regulator, the lncRNA NERDL (NERD-related lncRNA), which partially overlaps with the promoter region of this gene. Expression analysis in eight tissues showed a positive correlation between NERDL and PtoNERD (r = 0.62), suggesting that the interaction of NERDL with its putative target might be involved in wood formation. We conducted association mapping in a natural population of P. tomentosa (435 unrelated individuals) to evaluate genetic variation and the interaction of the lncRNA NERDL with PtoNERD. Using additive and dominant models, we identified 30 SNPs (P < 0.01) associated with five tree growth and wood property traits. Each SNP explained 3.90–8.57% of phenotypic variance, suggesting that NERDL and its putative target play a common role in wood formation. Epistasis analysis uncovered nine SNP-SNP association pairs between NERDL and PtoNERD, with an information gain of -7.55 to 2.16%, reflecting the strong interactions between NERDL and its putative target. This analysis provides a powerful method for deciphering the genetic interactions of lncRNAs with mRNA and dissecting the complex genetic network of quantitative traits in trees. PMID:28674544

eQTL networks unveil enriched mRNA master integrators downstream of complex disease-associated SNPs.

PubMed

Li, Haiquan; Pouladi, Nima; Achour, Ikbel; Gardeux, Vincent; Li, Jianrong; Li, Qike; Zhang, Hao Helen; Martinez, Fernando D; 'Skip' Garcia, Joe G N; Lussier, Yves A

2015-12-01

The causal and interplay mechanisms of Single Nucleotide Polymorphisms (SNPs) associated with complex diseases (complex disease SNPs) investigated in genome-wide association studies (GWAS) at the transcriptional level (mRNA) are poorly understood despite recent advancements such as discoveries reported in the Encyclopedia of DNA Elements (ENCODE) and Genotype-Tissue Expression (GTex). Protein interaction network analyses have successfully improved our understanding of both single gene diseases (Mendelian diseases) and complex diseases. Whether the mRNAs downstream of complex disease genes are central or peripheral in the genetic information flow relating DNA to mRNA remains unclear and may be disease-specific. Using expression Quantitative Trait Loci (eQTL) that provide DNA to mRNA associations and network centrality metrics, we hypothesize that we can unveil the systems properties of information flow between SNPs and the transcriptomes of complex diseases. We compare different conditions such as naïve SNP assignments and stringent linkage disequilibrium (LD) free assignments for transcripts to remove confounders from LD. Additionally, we compare the results from eQTL networks between lymphoblastoid cell lines and liver tissue. Empirical permutation resampling (p<0.001) and theoretic Mann-Whitney U test (p<10(-30)) statistics indicate that mRNAs corresponding to complex disease SNPs via eQTL associations are likely to be regulated by a larger number of SNPs than expected. We name this novel property mRNA hubness in eQTL networks, and further term mRNAs with high hubness as master integrators. mRNA master integrators receive and coordinate the perturbation signals from large numbers of polymorphisms and respond to the personal genetic architecture integratively. This genetic signal integration contrasts with the mechanism underlying some Mendelian diseases, where a genetic polymorphism affecting a single protein hub produces a divergent signal that affects a large number of downstream proteins. Indeed, we verify that this property is independent of the hubness in protein networks for which these mRNAs are transcribed. Our findings provide novel insights into the pleiotropy of mRNAs targeted by complex disease polymorphisms and the architecture of the information flow between the genetic polymorphisms and transcriptomes of complex diseases. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

The effectiveness of argumentation in tutorial dialogues with an Intelligent Tutoring System for genetic risk of breast cancer.

PubMed

Cedillos-Whynott, Elizabeth M; Wolfe, Christopher R; Widmer, Colin L; Brust-Renck, Priscila G; Weil, Audrey; Reyna, Valerie F

2016-09-01

BRCA Gist is an Intelligent Tutoring System that helps women understand issues related to genetic testing and breast cancer risk. In two laboratory experiments and a field experiment with community and web-based samples, an avatar asked 120 participants to produce arguments for and against genetic testing for breast cancer risk. Two raters assessed the number of argumentation elements (claim, reason, backing, etc.) found in response to prompts soliciting arguments for and against genetic testing for breast cancer risk (IRR=.85). When asked to argue for genetic testing, 53.3 % failed to meet the minimum operational definition of making an argument, a claim supported by one or more reasons. When asked to argue against genetic testing, 59.3 % failed to do so. Of those who failed to generate arguments most simply listed disconnected reasons. However, participants who provided arguments against testing (40.7 %) performed significantly higher on a posttest of declarative knowledge. In each study we found positive correlations between the quality of arguments against genetic testing (i.e., number of argumentation elements) and genetic risk categorization scores. Although most interactions did not contain two or more argument elements, when more elements of arguments were included in the argument against genetic testing interaction, participants had greater learning outcomes. Apparently, many participants lack skills in making coherent arguments. These results suggest an association between argumentation ability (knowing how to make complex arguments) and subsequent learning. Better education in developing arguments may be necessary for people to learn from generating arguments within Intelligent Tutoring Systems and other settings.

The effectiveness of argumentation in tutorial dialogues with an Intelligent Tutoring System for genetic risk of breast cancer

PubMed Central

Cedillos-Whynott, Elizabeth M.; Wolfe, Christopher R.; Widmer, Colin L.; Brust-Renck, Priscila G.; Weil, Audrey; Reyna, Valerie F.

2017-01-01

BRCA Gist is an Intelligent Tutoring System that helps women understand issues related to genetic testing and breast cancer risk. In two laboratory experiments and a field experiment with community and web-based samples, an avatar asked 120 participants to produce arguments for and against genetic testing for breast cancer risk. Two raters assessed the number of argumentation elements (claim, reason, backing, etc.) found in response to prompts soliciting arguments for and against genetic testing for breast cancer risk (IRR=.85). When asked to argue for genetic testing, 53.3 % failed to meet the minimum operational definition of making an argument, a claim supported by one or more reasons. When asked to argue against genetic testing, 59.3 % failed to do so. Of those who failed to generate arguments most simply listed disconnected reasons. However, participants who provided arguments against testing (40.7 %) performed significantly higher on a posttest of declarative knowledge. In each study we found positive correlations between the quality of arguments against genetic testing (i.e., number of argumentation elements) and genetic risk categorization scores. Although most interactions did not contain two or more argument elements, when more elements of arguments were included in the argument against genetic testing interaction, participants had greater learning outcomes. Apparently, many participants lack skills in making coherent arguments. These results suggest an association between argumentation ability (knowing how to make complex arguments) and subsequent learning. Better education in developing arguments may be necessary for people to learn from generating arguments within Intelligent Tutoring Systems and other settings. PMID:26511370

LINE-1 silencing by retinoblastoma proteins is effected through the nucleosomal and remodeling deacetylase multiprotein complex.

PubMed

Montoya-Durango, Diego E; Ramos, Kenneth A; Bojang, Pasano; Ruiz, Lorell; Ramos, Irma N; Ramos, Kenneth S

2016-01-25

Long Interspersed Nuclear Element-1 (L1) is an oncogenic mammalian retroelement silenced early in development via tightly controlled epigenetic mechanisms. We have previously shown that the regulatory region of human and murine L1s interact with retinoblastoma (RB) proteins to effect retroelement silencing. The present studies were conducted to identify the corepressor complex responsible for RB-mediated silencing of L1. Chromatin immunoprecipitation and silencing RNA technology were used to identify the repressor complex that silences L1 in human and murine cells. Components of the Nucleosomal and Remodeling Deacetylase (NuRD) multiprotein complex specifically enriched the L1 5'-untranslated DNA sequence in human and murine cells. Genetic ablation of RB proteins in murine cells destabilized interactions within the NuRD macromolecular complex and mediated nuclear rearrangement of Mi2-β, an ATP-dependent helicase subunit with nucleosome remodeling activity. Depletion of Mi2-β, RbAP46 and HDAC2 reduced the repressor activity of the NuRD complex and reactivated a synthetic L1 reporter in human cells. Epigenetic reactivation of L1 in RB-null cells by DNA damage was markedly enhanced compared to wild type cells. RB proteins stabilize interactions of the NuRD corepressor complex within the L1 promoter to effect L1 silencing. L1 retroelements may serve as a scaffold on which RB builds heterochromatic regions that regulate chromatin function.

Assessing oral literacy demand in genetic counseling dialogue: preliminary test of a conceptual framework.

PubMed

Roter, Debra L; Erby, Lori H; Larson, Susan; Ellington, Lee

2007-10-01

Health literacy deficits affect half the American patient population and are linked to poor health, ineffective disease management and high rates of hospitalization. Restricted literacy has also been linked with less satisfying medical visits and communication difficulties, particularly in terms of the interpersonal and informational aspects of care. Despite growing attention to these issues by researchers and policy makers, few studies have attempted to conceptualize and assess those aspects of dialogue that challenge persons with low literacy skills, i.e., the oral literacy demand within medical encounters. The current study uses videotapes and transcripts of 152 prenatal and cancer pretest genetic counseling sessions recorded with simulated clients to develop a conceptual framework to explore oral literacy demand and its consequences for medical interaction and related outcomes. Ninety-six prenatal and 81 cancer genetic counselors-broadly representative of the US National Society of Genetic Counselors-participated in the study. Key elements of the conceptual framework used to define oral literacy demand include: (1) use of unfamiliar technical terms; (2) general language complexity, reflected in the application of Microsoft Word grammar summary statistics to session transcripts; and, (3) structural characteristics of dialogue, including pacing, density, and interactivity. Genetic counselor outcomes include self-ratings of session satisfaction, informativeness, and development of rapport. The simulated clients rated their satisfaction with session communication, the counselor's effective use of nonverbal skills, and the counselor's affective demeanor during the session. Sessions with greater overall technical term use were longer and used more complex language reflected in readability indices and multi-syllabic vocabulary (measures averaging p<.05). Sessions with a high proportionate use of technical terms were characterized by shorter visits, high readability demand, slow speech speed, fewer and more dense counselor speaking turns and low interactivity (p<.05). The higher the use of technical terms, and the more dense and less interactive the dialogue, the less satisfied the simulated clients were and the lower their ratings were of counselors' nonverbal effectiveness and affective demeanor (all relationships p<.05). Counselors' self-ratings of informativeness were also inversely related to use of technical terms (p<.05). Just as print material can be made more reader-friendly and effective following established guidelines, the medical dialogue may also be made more patient-centered and meaningful by having providers monitor their vocabulary and language, as well as the structural characteristics of interaction, thereby lowering the literacy demand of routine medical dialogue. These consequences are important for all patients but may be even more so for patients with restricted literacy.

The Rise of Complexity: Do the Pavilion Lake Microbialites Suggest a Way to Build a Macroorganism?

NASA Astrophysics Data System (ADS)

Schulze-Makuch, D.; Laval, B.; Lim, D. S.; Irwin, L. N.

2005-12-01

The distinctive assemblage of freshwater calcite microbialites discovered at Pavilion Lake, BC, has been associated with organisms such as Epiphyton and Girvanella, fossils from just before the Cambrian explosion about 550 million years ago (Laval et al., 2000). The presence of the microbialite structures in a dimictic mid-latitude lake and their establishment after the last ice age about 10,000 years ago is puzzling. Their distinctive morphologies include cone-shaped seepage structures 2 m or more in height with hollow internal conduits that open at the top of the cones, and dense artichoke-like structures with calcite "leaves" greater than 1 m in height. These structures are astounding as they imply functional properties. In principle, this is not unlike the interaction of individual cells in a macroorganism, in which many different types of specialized cells interact with each other to the benefit of the whole organism (e.g. interaction of blood, integument, and organ cells within animals). Certainly, the complex interaction of these microbial cells is not equivalent to the collaboration of cells within an individual multicellular organism, where each cell has the same genetic information but differential gene expression provides well-defined cellular specializations. However, the microbialites raise the question of how much complexity and structure can be achieved by a high degree of communication within a multitude of microbial cells. Our findings indicate a complex and interacting microbial consortium associated with the structures at Pavilion Lake, and revealed biomarkers for proteobacteria, sulphur reducing bacteria, and firmicutes (possibly photosynthetic heliobacteria), among others. Types of genetic exchange among these microbial cells may include lateral gene transfer via conjugation, transformation, and transduction, or other mechanisms. This finding may have significant implications for the evolution of life on Earth and possible life on other planets. References: Laval, B., Cady, S.L., Pollack, J.C., McKay, C.P., Bird, J.S., Grotzinger, J.P., Ford, D.C., and Bohm, H.R. (2000) Modern freshwater microbialite analogues for ancient dendritic reef structures. Nature 407, 626-629.

Microbiome and Malignancy

PubMed Central

Plottel, Claudia S.; Blaser, Martin J.

2011-01-01

Current knowledge is insufficient to explain why only a proportion of individuals exposed to environmental carcinogens or carrying a genetic predisposition to cancer develop disease. Clearly, other factors must be important and one such element that has recently received attention is the human microbiome, the residential microbes including Bacteria, Archaea, Eukaryotes, and viruses that colonize humans. Here, we review principles and paradigms of microbiome-related malignancy, as illustrated by three specific microbial-host interactions. We review the effects of the microbiota on local and adjacent-neoplasia, present the estrobolome model of distant effects, and discuss the complex interactions with a latent virus leading to malignancy. These are separate facets of a complex biology interfacing all the microbial species we harbor from birth onward toward early reproductive success and eventual senescence. PMID:22018233

The population genetics of X-autosome synthetic lethals and steriles.

PubMed

Lachance, Joseph; Johnson, Norman A; True, John R

2011-11-01

Epistatic interactions are widespread, and many of these interactions involve combinations of alleles at different loci that are deleterious when present in the same individual. The average genetic environment of sex-linked genes differs from that of autosomal genes, suggesting that the population genetics of interacting X-linked and autosomal alleles may be complex. Using both analytical theory and computer simulations, we analyzed the evolutionary trajectories and mutation-selection balance conditions for X-autosome synthetic lethals and steriles. Allele frequencies follow a set of fundamental trajectories, and incompatible alleles are able to segregate at much higher frequencies than single-locus expectations. Equilibria exist, and they can involve fixation of either autosomal or X-linked alleles. The exact equilibrium depends on whether synthetic alleles are dominant or recessive and whether fitness effects are seen in males, females, or both sexes. When single-locus fitness effects and synthetic incompatibilities are both present, population dynamics depend on the dominance of alleles and historical contingency (i.e., whether X-linked or autosomal mutations occur first). Recessive synthetic lethality can result in high-frequency X-linked alleles, and dominant synthetic lethality can result in high-frequency autosomal alleles. Many X-autosome incompatibilities in natural populations may be cryptic, appearing to be single-locus effects because one locus is fixed. We also discuss the implications of these findings with respect to standing genetic variation and the origins of Haldane's rule.

Transcription closed and open complex dynamics studies reveal balance between genetic determinants and co-factors

NASA Astrophysics Data System (ADS)

Sala, Adrien; Shoaib, Muhammad; Anufrieva, Olga; Mutharasu, Gnanavel; Jahan Hoque, Rawnak; Yli-Harja, Olli; Kandhavelu, Meenakshisundaram

2015-05-01

In E. coli, promoter closed and open complexes are key steps in transcription initiation, where magnesium-dependent RNA polymerase catalyzes RNA synthesis. However, the exact mechanism of initiation remains to be fully elucidated. Here, using single mRNA detection and dual reporter studies, we show that increased intracellular magnesium concentration affects Plac initiation complex formation resulting in a highly dynamic process over the cell growth phases. Mg2+ regulates transcription transition, which modulates bimodality of mRNA distribution in the exponential phase. We reveal that Mg2+ regulates the size and frequency of the mRNA burst by changing the open complex duration. Moreover, increasing magnesium concentration leads to higher intrinsic and extrinsic noise in the exponential phase. RNAP-Mg2+ interaction simulation reveals critical movements creating a shorter contact distance between aspartic acid residues and Nucleotide Triphosphate residues and increasing electrostatic charges in the active site. Our findings provide unique biophysical insights into the balanced mechanism of genetic determinants and magnesium ion in transcription initiation regulation during cell growth.

The EARP Complex and Its Interactor EIPR-1 Are Required for Cargo Sorting to Dense-Core Vesicles

PubMed Central

Topalidou, Irini; Cattin-Ortolá, Jérôme; MacCoss, Michael J.

2016-01-01

The dense-core vesicle is a secretory organelle that mediates the regulated release of peptide hormones, growth factors, and biogenic amines. Dense-core vesicles originate from the trans-Golgi of neurons and neuroendocrine cells, but it is unclear how this specialized organelle is formed and acquires its specific cargos. To identify proteins that act in dense-core vesicle biogenesis, we performed a forward genetic screen in Caenorhabditis elegans for mutants defective in dense-core vesicle function. We previously reported the identification of two conserved proteins that interact with the small GTPase RAB-2 to control normal dense-core vesicle cargo-sorting. Here we identify several additional conserved factors important for dense-core vesicle cargo sorting: the WD40 domain protein EIPR-1 and the endosome-associated recycling protein (EARP) complex. By assaying behavior and the trafficking of dense-core vesicle cargos, we show that mutants that lack EIPR-1 or EARP have defects in dense-core vesicle cargo-sorting similar to those of mutants in the RAB-2 pathway. Genetic epistasis data indicate that RAB-2, EIPR-1 and EARP function in a common pathway. In addition, using a proteomic approach in rat insulinoma cells, we show that EIPR-1 physically interacts with the EARP complex. Our data suggest that EIPR-1 is a new interactor of the EARP complex and that dense-core vesicle cargo sorting depends on the EARP-dependent trafficking of cargo through an endosomal sorting compartment. PMID:27191843

An Introduction to Recursive Partitioning: Rationale, Application, and Characteristics of Classification and Regression Trees, Bagging, and Random Forests

ERIC Educational Resources Information Center

Strobl, Carolin; Malley, James; Tutz, Gerhard

2009-01-01

Recursive partitioning methods have become popular and widely used tools for nonparametric regression and classification in many scientific fields. Especially random forests, which can deal with large numbers of predictor variables even in the presence of complex interactions, have been applied successfully in genetics, clinical medicine, and…

Probabilities and Predictions: Modeling the Development of Scientific Problem-Solving Skills

ERIC Educational Resources Information Center

Stevens, Ron; Johnson, David F.; Soller, Amy

2005-01-01

The IMMEX (Interactive Multi-Media Exercises) Web-based problem set platform enables the online delivery of complex, multimedia simulations, the rapid collection of student performance data, and has already been used in several genetic simulations. The next step is the use of these data to understand and improve student learning in a formative…

Sporophytic self-incompatibility in Senecio squalidus (Asteraceae): S allele dominance interactions and modifiers of cross-compatibility and selfing rates

PubMed Central

Brennan, A C; Tabah, D A; Harris, S A; Hiscock, S J

2011-01-01

Understanding genetic mechanisms of self-incompatibility (SI) and how they evolve is central to understanding the mating behaviour of most outbreeding angiosperms. Sporophytic SI (SSI) is controlled by a single multi-allelic locus, S, which is expressed in the diploid (sporophyte) plant to determine the SI phenotype of its haploid (gametophyte) pollen. This allows complex patterns of independent S allele dominance interactions in male (pollen) and female (pistil) reproductive tissues. Senecio squalidus is a useful model for studying the genetic regulation and evolution of SSI because of its population history as an alien invasive species in the UK. S. squalidus maintains a small number of S alleles (7–11) with a high frequency of dominance interactions. Some S. squalidus individuals also show partial selfing and/or greater levels of cross-compatibility than expected under SSI. We previously speculated that these might be adaptations to invasiveness. Here we describe a detailed characterization of the regulation of SSI in S. squalidus. Controlled crosses were used to determine the S allele dominance hierarchy of six S alleles and effects of modifiers on cross-compatibility and partial selfing. Complex dominance interactions among S alleles were found with at least three levels of dominance and tissue-specific codominance. Evidence for S gene modifiers that increase selfing and/or cross-compatibility was also found. These empirical findings are discussed in the context of theoretical predictions for maintenance of S allele dominance interactions, and the role of modifier loci in the evolution of SI. PMID:20372180

Sporophytic self-incompatibility in Senecio squalidus (Asteraceae): S allele dominance interactions and modifiers of cross-compatibility and selfing rates.

PubMed

Brennan, A C; Tabah, D A; Harris, S A; Hiscock, S J

2011-01-01

Understanding genetic mechanisms of self-incompatibility (SI) and how they evolve is central to understanding the mating behaviour of most outbreeding angiosperms. Sporophytic SI (SSI) is controlled by a single multi-allelic locus, S, which is expressed in the diploid (sporophyte) plant to determine the SI phenotype of its haploid (gametophyte) pollen. This allows complex patterns of independent S allele dominance interactions in male (pollen) and female (pistil) reproductive tissues. Senecio squalidus is a useful model for studying the genetic regulation and evolution of SSI because of its population history as an alien invasive species in the UK. S. squalidus maintains a small number of S alleles (7-11) with a high frequency of dominance interactions. Some S. squalidus individuals also show partial selfing and/or greater levels of cross-compatibility than expected under SSI. We previously speculated that these might be adaptations to invasiveness. Here we describe a detailed characterization of the regulation of SSI in S. squalidus. Controlled crosses were used to determine the S allele dominance hierarchy of six S alleles and effects of modifiers on cross-compatibility and partial selfing. Complex dominance interactions among S alleles were found with at least three levels of dominance and tissue-specific codominance. Evidence for S gene modifiers that increase selfing and/or cross-compatibility was also found. These empirical findings are discussed in the context of theoretical predictions for maintenance of S allele dominance interactions, and the role of modifier loci in the evolution of SI.

Amoebae, Giant Viruses, and Virophages Make Up a Complex, Multilayered Threesome

PubMed Central

Diesend, Jan; Kruse, Janis; Hagedorn, Monica; Hammann, Christian

2018-01-01

Viral infection had not been observed for amoebae, until the Acanthamoeba polyphaga mimivirus (APMV) was discovered in 2003. APMV belongs to the nucleocytoplasmatic large DNA virus (NCLDV) family and infects not only A. polyphaga, but also other professional phagocytes. Here, we review the Megavirales to give an overview of the current members of the Mimi- and Marseilleviridae families and their structural features during amoebal infection. We summarize the different steps of their infection cycle in A. polyphaga and Acanthamoeba castellani. Furthermore, we dive into the emerging field of virophages, which parasitize upon viral factories of the Megavirales family. The discovery of virophages in 2008 and research in recent years revealed an increasingly complex network of interactions between cell, giant virus, and virophage. Virophages seem to be highly abundant in the environment and occupy the same niches as the Mimiviridae and their hosts. Establishment of metagenomic and co-culture approaches rapidly increased the number of detected virophages over the recent years. Genetic interaction of cell and virophage might constitute a potent defense machinery against giant viruses and seems to be important for survival of the infected cell during mimivirus infections. Nonetheless, the molecular events during co-infection and the interactions of cell, giant virus, and virophage have not been elucidated, yet. However, the genetic interactions of these three, suggest an intricate, multilayered network during amoebal (co-)infections. Understanding these interactions could elucidate molecular events essential for proper viral factory activity and could implicate new ways of treating viruses that form viral factories. PMID:29376032

Genetic variability and ontogeny predict microbiome structure in a disease-challenged montane amphibian.

PubMed

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.

Beliefs about the etiology of homosexuality and about the ramifications of discovering its possible genetic origin.

PubMed

Sheldon, Jane P; Pfeffer, Carla A; Jayaratne, Toby Epstein; Feldbaum, Merle; Petty, Elizabeth M

2007-01-01

Homosexuality is viewed by many as a social problem. As such, there is a keen interest in elucidating the origins of homosexuality among many scholars, from anthropologists to zoologists, from psychologists to theologians. Research has shown that those who believe sexual orientation is inborn are more likely to have tolerant attitudes toward gay men and lesbians, whereas those who believe it is a choice have less tolerant attitudes. The current qualitative study used in-depth, open-ended telephone interviews with 42 White and 44 Black Americans to gain insight into the public's beliefs about the possible genetic origins of homosexuality. Along with etiological beliefs (and the sources of information used to develop these beliefs), we asked respondents to describe the benefits and dangers of scientists discovering the possible genetic basis for homosexuality. We found that although limited understanding and biased perspectives likely led to simplistic reasoning concerning the origins and genetic basis of homosexuality, many individuals appreciated the complex and interactive etiological perspectives. These interactive perspectives often included recognition of some type of inherent aspect, such as a genetic factor(s), that served as an underlying predisposition that would be manifested after being influenced by other factors such as choice or environmental exposures. We also found that beliefs in a genetic basis for homosexuality could be used to support very diverse opinions including those in accordance with negative eugenic agendas.

Beliefs about the Etiology of Homosexuality and about the Ramifications of Discovering Its Possible Genetic Origin

PubMed Central

Sheldon, Jane P.; Pfeffer, Carla A.; Jayaratne, Toby Epstein; Feldbaum, Merle; Petty, Elizabeth M.

2013-01-01

Homosexuality is viewed by many as a social problem. As such, there has been keen interest in elucidating the origins of homosexuality among many scholars, from anthropologists to zoologists, psychologists to theologians. Research has shown that those who believe sexual orientation is inborn are more likely to have tolerant attitudes toward gay men and lesbians, whereas those who believe it is a choice have less tolerant attitudes. The current qualitative study used in-depth, open-ended telephone interviews with 42 White and 44 Black Americans to gain insight into the public's beliefs about the possible genetic origins of homosexuality. Along with etiological beliefs (and the sources of information used to develop those beliefs), we asked respondents to describe the benefits and dangers of scientists discovering the possible genetic basis for homosexuality. We found that although limited understanding and biased perspectives likely led to simplistic reasoning concerning the origins and genetic basis of homosexuality, many individuals appreciated complex and interactive etiological perspectives. These interactive perspectives often included recognition of some type of inherent aspect, such as a genetic factor(s), that served as an underlying predisposition that would be manifested after being influenced by other factors such as choice or environmental exposures. We also found that beliefs in a genetic basis for homosexuality could be used to support very diverse opinions, including those in accordance with negative eugenic agendas. PMID:17594974

The selfish Segregation Distorter gene complex of Drosophila melanogaster.

PubMed

Larracuente, Amanda M; Presgraves, Daven C

2012-09-01

Segregation Distorter (SD) is an autosomal meiotic drive gene complex found worldwide in natural populations of Drosophila melanogaster. During spermatogenesis, SD induces dysfunction of SD(+) spermatids so that SD/SD(+) males sire almost exclusively SD-bearing progeny rather than the expected 1:1 Mendelian ratio. SD is thus evolutionarily "selfish," enhancing its own transmission at the expense of its bearers. Here we review the molecular and evolutionary genetics of SD. Genetic analyses show that the SD is a multilocus gene complex involving two key loci--the driver, Segregation distorter (Sd), and the target of drive, Responder (Rsp)--and at least three upward modifiers of distortion. Molecular analyses show that Sd encodes a truncated duplication of the gene RanGAP, whereas Rsp is a large pericentromeric block of satellite DNA. The Sd-RanGAP protein is enzymatically wild type but mislocalized within cells and, for reasons that remain unclear, appears to disrupt the histone-to-protamine transition in drive-sensitive spermatids bearing many Rsp satellite repeats but not drive-insensitive spermatids bearing few or no Rsp satellite repeats. Evolutionary analyses show that the Sd-RanGAP duplication arose recently within the D. melanogaster lineage, exploiting the preexisting and considerably older Rsp satellite locus. Once established, the SD haplotype collected enhancers of distortion and suppressors of recombination. Further dissection of the molecular genetic and cellular basis of SD-mediated distortion seems likely to provide insights into several important areas currently understudied, including the genetic control of spermatogenesis, the maintenance and evolution of satellite DNAs, the possible roles of small interfering RNAs in the germline, and the molecular population genetics of the interaction of genetic linkage and natural selection.

Predicting attention-deficit/hyperactivity disorder severity from psychosocial stress and stress-response genes: a random forest regression approach

PubMed Central

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

Gene-environment interactions in cancer epidemiology: a National Cancer Institute Think Tank report.

PubMed

Hutter, Carolyn M; Mechanic, Leah E; Chatterjee, Nilanjan; Kraft, Peter; Gillanders, Elizabeth M

2013-11-01

Cancer risk is determined by a complex interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified hundreds of common (minor allele frequency [MAF] > 0.05) and less common (0.01 < MAF < 0.05) genetic variants associated with cancer. The marginal effects of most of these variants have been small (odds ratios: 1.1-1.4). There remain unanswered questions on how best to incorporate the joint effects of genes and environment, including gene-environment (G × E) interactions, into epidemiologic studies of cancer. To help address these questions, and to better inform research priorities and allocation of resources, the National Cancer Institute sponsored a "Gene-Environment Think Tank" on January 10-11, 2012. The objective of the Think Tank was to facilitate discussions on (1) the state of the science, (2) the goals of G × E interaction studies in cancer epidemiology, and (3) opportunities for developing novel study designs and analysis tools. This report summarizes the Think Tank discussion, with a focus on contemporary approaches to the analysis of G × E interactions. Selecting the appropriate methods requires first identifying the relevant scientific question and rationale, with an important distinction made between analyses aiming to characterize the joint effects of putative or established genetic and environmental factors and analyses aiming to discover novel risk factors or novel interaction effects. Other discussion items include measurement error, statistical power, significance, and replication. Additional designs, exposure assessments, and analytical approaches need to be considered as we move from the current small number of success stories to a fuller understanding of the interplay of genetic and environmental factors. © 2013 WILEY PERIODICALS, INC.

Gene-Environment Interactions in Cancer Epidemiology: A National Cancer Institute Think Tank Report

PubMed Central

Hutter, Carolyn M.; Mechanic, Leah E.; Chatterjee, Nilanjan; Kraft, Peter; Gillander, Elizabeth M.

2014-01-01

Cancer risk is determined by a complex interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified hundreds of common (minor allele frequency [MAF]>0.05) and less common (0.01

Contribution of genome-environment interaction to pre-eclampsia in a Havana Maternity Hospital.

PubMed

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.

Combining research approaches to advance our understanding of drug addiction.

PubMed

van den Bree, Marianne B M

2005-04-01

Drug addiction is a complex behavior, likely to be influenced by various genes, environmental factors, and gene-gene and gene-environment interactions. Various aspects of addiction are studied by different disciplines. Animal studies are increasing insight into brain regions and genes associated with addiction. Epidemiologic studies are establishing the factors increasing risk for initiation and continuation of substance use. Twin and adoption studies are increasing our understanding of the complex mechanisms involved in substance use, including comorbidity and gene environment interaction. Finally, molecular genetic studies in humans are starting to yield some converging findings. It is argued and illustrated with examples that greater awareness of progress in other disciplines can speed up our understanding of the complex processes involved in addiction. This should help our ability to identify who is at increased risk of becoming addicted and the development of prevention and intervention strategies targeted at an individual's specific needs.

The Complex Relationship between Virulence and Antibiotic Resistance

PubMed Central

Schroeder, Meredith; Brooks, Benjamin D.; Brooks, Amanda E.

2017-01-01

Antibiotic resistance, prompted by the overuse of antimicrobial agents, may arise from a variety of mechanisms, particularly horizontal gene transfer of virulence and antibiotic resistance genes, which is often facilitated by biofilm formation. The importance of phenotypic changes seen in a biofilm, which lead to genotypic alterations, cannot be overstated. Irrespective of if the biofilm is single microbe or polymicrobial, bacteria, protected within a biofilm from the external environment, communicate through signal transduction pathways (e.g., quorum sensing or two-component systems), leading to global changes in gene expression, enhancing virulence, and expediting the acquisition of antibiotic resistance. Thus, one must examine a genetic change in virulence and resistance not only in the context of the biofilm but also as inextricably linked pathologies. Observationally, it is clear that increased virulence and the advent of antibiotic resistance often arise almost simultaneously; however, their genetic connection has been relatively ignored. Although the complexities of genetic regulation in a multispecies community may obscure a causative relationship, uncovering key genetic interactions between virulence and resistance in biofilm bacteria is essential to identifying new druggable targets, ultimately providing a drug discovery and development pathway to improve treatment options for chronic and recurring infection. PMID:28106797

Nature, nurture and evolution of intra-species variation in mosquito arbovirus transmission competence.

PubMed

Tabachnick, Walter J

2013-01-11

Mosquitoes vary in their competence or ability to transmit arthropod-borne viruses (arboviruses). Many arboviruses cause disease in humans and animals. Identifying the environmental and genetic causes of variation in mosquito competence for arboviruses is one of the great challenges in public health. Progress identifying genetic (nature) and environmental (nurture) factors influencing mosquito competence for arboviruses is reviewed. There is great complexity in the various traits that comprise mosquito competence. The complex interactions between environmental and genetic factors controlling these traits and the factors shaping variation in Nature are largely unknown. The norms of reaction of specific genes influencing competence, their distributions in natural populations and the effects of genetic polymorphism on phenotypic variation need to be determined. Mechanisms influencing competence are not likely due to natural selection because of the direct effects of the arbovirus on mosquito fitness. More likely the traits for mosquito competence for arboviruses are the effects of adaptations for other functions of these competence mechanisms. Determining these other functions is essential to understand the evolution and distributions of competence for arboviruses. This information is needed to assess risk from mosquito-borne disease, predict new mosquito-arbovirus systems, and provide novel strategies to mitigate mosquito-borne arbovirus transmission.

Mapping of epistatic quantitative trait loci in four-way crosses.

PubMed

He, Xiao-Hong; Qin, Hongde; Hu, Zhongli; Zhang, Tianzhen; Zhang, Yuan-Ming

2011-01-01

Four-way crosses (4WC) involving four different inbred lines often appear in plant and animal commercial breeding programs. Direct mapping of quantitative trait loci (QTL) in these commercial populations is both economical and practical. However, the existing statistical methods for mapping QTL in a 4WC population are built on the single-QTL genetic model. This simple genetic model fails to take into account QTL interactions, which play an important role in the genetic architecture of complex traits. In this paper, therefore, we attempted to develop a statistical method to detect epistatic QTL in 4WC population. Conditional probabilities of QTL genotypes, computed by the multi-point single locus method, were used to sample the genotypes of all putative QTL in the entire genome. The sampled genotypes were used to construct the design matrix for QTL effects. All QTL effects, including main and epistatic effects, were simultaneously estimated by the penalized maximum likelihood method. The proposed method was confirmed by a series of Monte Carlo simulation studies and real data analysis of cotton. The new method will provide novel tools for the genetic dissection of complex traits, construction of QTL networks, and analysis of heterosis.

'RetinoGenetics': a comprehensive mutation database for genes related to inherited retinal degeneration.

PubMed

Ran, Xia; Cai, Wei-Jun; Huang, Xiu-Feng; Liu, Qi; Lu, Fan; Qu, Jia; Wu, Jinyu; Jin, Zi-Bing

2014-01-01

Inherited retinal degeneration (IRD), a leading cause of human blindness worldwide, is exceptionally heterogeneous with clinical heterogeneity and genetic variety. During the past decades, tremendous efforts have been made to explore the complex heterogeneity, and massive mutations have been identified in different genes underlying IRD with the significant advancement of sequencing technology. In this study, we developed a comprehensive database, 'RetinoGenetics', which contains informative knowledge about all known IRD-related genes and mutations for IRD. 'RetinoGenetics' currently contains 4270 mutations in 186 genes, with detailed information associated with 164 phenotypes from 934 publications and various types of functional annotations. Then extensive annotations were performed to each gene using various resources, including Gene Ontology, KEGG pathways, protein-protein interaction, mutational annotations and gene-disease network. Furthermore, by using the search functions, convenient browsing ways and intuitive graphical displays, 'RetinoGenetics' could serve as a valuable resource for unveiling the genetic basis of IRD. Taken together, 'RetinoGenetics' is an integrative, informative and updatable resource for IRD-related genetic predispositions. Database URL: http://www.retinogenetics.org/. © The Author(s) 2014. Published by Oxford University Press.

Why genes don't count (for racial differences in health).

PubMed Central

Goodman, A H

2000-01-01

There is a paradoxical relationship between "race" and genetics. Whereas genetic data were first used to prove the validity of race, since the early 1970s they have been used to illustrate the invalidity of biological races. Indeed, race does not account for human genetic variation, which is continuous, complexly structured, constantly changing, and predominantly within "races." Despite the disproof of race-as-biology, genetic variation continues to be used to explain racial differences. Such explanations require the acceptance of 2 disproved assumptions: that genetic variation explains variation in disease and that genetic variation explains racial variation in disease. While the former is a form of geneticization, the notion that genes are the primary determinants of biology and behavior, the latter represents a form of racialization, an exaggeration of the salience of race. Using race as a proxy for genetic differences limits understandings of the complex interactions among political-economic processes, lived experiences, and human biologies. By moving beyond studies of racialized genetics, we can clarify the processes by which varied and interwoven forms of racialization and racism affect individuals "under the skin." PMID:11076233

Why genes don't count (for racial differences in health).

PubMed

Goodman, A H

2000-11-01

There is a paradoxical relationship between "race" and genetics. Whereas genetic data were first used to prove the validity of race, since the early 1970s they have been used to illustrate the invalidity of biological races. Indeed, race does not account for human genetic variation, which is continuous, complexly structured, constantly changing, and predominantly within "races." Despite the disproof of race-as-biology, genetic variation continues to be used to explain racial differences. Such explanations require the acceptance of 2 disproved assumptions: that genetic variation explains variation in disease and that genetic variation explains racial variation in disease. While the former is a form of geneticization, the notion that genes are the primary determinants of biology and behavior, the latter represents a form of racialization, an exaggeration of the salience of race. Using race as a proxy for genetic differences limits understandings of the complex interactions among political-economic processes, lived experiences, and human biologies. By moving beyond studies of racialized genetics, we can clarify the processes by which varied and interwoven forms of racialization and racism affect individuals "under the skin."

The Major Histocompatibility Complex and Autism Spectrum Disorder

PubMed Central

Needleman, Leigh A.; McAllister, A. Kimberley

2015-01-01

Autism spectrum disorder (ASD) is a complex disorder that appears to be caused by interactions between genetic changes and environmental insults during early development. A wide range of factors have been linked to the onset of ASD, but recently both genetic associations and environmental factors point to a central role for immune- related genes and immune responses to environmental stimuli. Specifically, many of the proteins encoded by the major histocompatibility complex (MHC) play a vital role in the formation, refinement, maintenance, and plasticity of the brain. Manipulations of levels of MHC molecules have illustrated how disrupted MHC signaling can significantly alter brain connectivity and function. Thus, an emerging hypothesis in our field is that disruptions in MHC expression in the developing brain caused by mutations and/or immune dysregulation may contribute to the altered brain connectivity and function characteristic of ASD. This review provides an overview of the structure and function of the three classes of MHC molecules in the immune system, healthy brain, and their possible involvement in ASD. PMID:22760919

In vivo insertion pool sequencing identifies virulence factors in a complex fungal–host interaction

PubMed Central

Uhse, Simon; Pflug, Florian G.; Stirnberg, Alexandra; Ehrlinger, Klaus; von Haeseler, Arndt

2018-01-01

Large-scale insertional mutagenesis screens can be powerful genome-wide tools if they are streamlined with efficient downstream analysis, which is a serious bottleneck in complex biological systems. A major impediment to the success of next-generation sequencing (NGS)-based screens for virulence factors is that the genetic material of pathogens is often underrepresented within the eukaryotic host, making detection extremely challenging. We therefore established insertion Pool-Sequencing (iPool-Seq) on maize infected with the biotrophic fungus U. maydis. iPool-Seq features tagmentation, unique molecular barcodes, and affinity purification of pathogen insertion mutant DNA from in vivo-infected tissues. In a proof of concept using iPool-Seq, we identified 28 virulence factors, including 23 that were previously uncharacterized, from an initial pool of 195 candidate effector mutants. Because of its sensitivity and quantitative nature, iPool-Seq can be applied to any insertional mutagenesis library and is especially suitable for genetically complex setups like pooled infections of eukaryotic hosts. PMID:29684023

The Major Histocompatibility Complex in Bovines: A Review

PubMed Central

Behl, Jyotsna Dhingra; Verma, N. K.; Tyagi, Neha; Mishra, Priyanka; Behl, Rahul; Joshi, B. K.

2012-01-01

Productivity in dairy cattle and buffaloes depends on the genetic factors governing the production of milk and milk constituents as well as genetic factors controlling disease resistance or susceptibility. The immune system is the adaptive defense system that has evolved in vertebrates to protect them from invading pathogens and also carcinomas. It is remarkable in the sense that it is able to generate an enormous variety of cells and biomolecules which interact with each other in numerous ways to form a complex network that helps to recognize, counteract, and eliminate the apparently limitless number of foreign invading pathogens/molecules. The major histocompatibility complex which is found to occur in all mammalian species plays a central role in the development of the immune system. It is an important candidate gene involved in susceptibility/resistance to various diseases. It is associated with intercellular recognition and with self/nonself discrimination. It plays major role in determining whether transplanted tissue will be accepted as self or rejected as foreign. PMID:23738132

Actor-network theory: a tool to support ethical analysis of commercial genetic testing.

PubMed

Williams-Jones, Bryn; Graham, Janice E

2003-12-01

Social, ethical and policy analysis of the issues arising from gene patenting and commercial genetic testing is enhanced by the application of science and technology studies, and Actor-Network Theory (ANT) in particular. We suggest the potential for transferring ANT's flexible nature to an applied heuristic methodology for gathering empirical information and for analysing the complex networks involved in the development of genetic technologies. Three concepts are explored in this paper--actor-networks, translation, and drift--and applied to the case of Myriad Genetics and their commercial BRACAnalysis genetic susceptibility test for hereditary breast cancer. Treating this test as an active participant in socio-technical networks clarifies the extent to which it interacts with, shapes and is shaped by people, other technologies, and institutions. Such an understanding enables more sophisticated and nuanced technology assessment, academic analysis, as well as public debate about the social, ethical and policy implications of the commercialization of new genetic technologies.

[Genetic testing in polygenic diseases : Atrial fibrillation, arterial hypertension and coronary artery disease].

PubMed

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.

A method to estimate the contribution of regional genetic associations to complex traits from summary association statistics.

PubMed

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.

Peripartum Cardiomyopathy: Moving Towards a More Central Role of Genetics#

PubMed Central

Cemin, Roberto; Janardhanan, Rajesh; Donazzan, Luca; Daves, Massimo

2013-01-01

Peripartum cardiomyopathy (PCM) is a relatively rare disease with potentially devasting consequences requiring prompt identification and correct treatment. Overall prognosis is good in majority of the cases, although some patients may progress to irreversible heart failure. Early diagnosis is important and effective treatment reduces mortality rates and increases the chance of complete recovery of ventricular systolic function. The aetiology and pathogenesis seems to be multifactorial and poorly understood, with the available literature rather conflicting. In recent years, there has been increased interest in the role played by genetic predisposition in the development of PCM. It probably develops as a result of a complex interaction of pregnancy-associated factors and genetic factors and recently there have been many observations pointing out the central role played by a genetic predisposition. The direct and indirect observations on genetic susceptibility may offer new insights into the pathogenesis of PCM. However, larger studies are needed before advising routine genetic testing in these patients. PMID:23909634

A method to estimate the contribution of regional genetic associations to complex traits from summary association statistics

PubMed Central

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

Direct visualization reveals kinetics of meiotic chromosome synapsis

DOE PAGES

Rog, Ofer; Dernburg, Abby  F.

2015-03-17

The synaptonemal complex (SC) is a conserved protein complex that stabilizes interactions along homologous chromosomes (homologs) during meiosis. The SC regulates genetic exchanges between homologs, thereby enabling reductional division and the production of haploid gametes. Here, we directly observe SC assembly (synapsis) by optimizing methods for long-term fluorescence recording in C. elegans. We report that synapsis initiates independently on each chromosome pair at or near pairing centers—specialized regions required for homolog associations. Once initiated, the SC extends rapidly and mostly irreversibly to chromosome ends. Quantitation of SC initiation frequencies and extension rates reveals that initiation is a rate-limiting step inmore » homolog interactions. Eliminating the dynein-driven chromosome movements that accompany synapsis severely retards SC extension, revealing a new role for these conserved motions. This work provides the first opportunity to directly observe and quantify key aspects of meiotic chromosome interactions and will enable future in vivo analysis of germline processes.« less

Attachment in integrative neuroscientific perspective.

PubMed

Hruby, Radovan; Hasto, Jozef; Minarik, Peter

2011-01-01

Attachment theory is a very influential general concept of human social and emotional development, which emphasizes the role of early mother-infant interactions for infant's adaptive behavioural and stress copying strategies, personality organization and mental health. Individuals with disrupted development of secure attachment to mother/primary caregiver are at higher risk of developing mental disorders. This theory consists of the complex developmental psycho-neurobiological model of attachment and emerges from principles of psychoanalysis, evolutionary biology, cognitive-developmental psychology, ethology, physiology and control systems theory. The progress of modern neuroscience enables interpretation of neurobiological aspects of the theory as multi-level neural interactions and functional development of important neural structures, effects of neuromediattors, hormones and essential neurobiological processes including emotional, cognitive, social interactions and the special key role of mentalizing. It has multiple neurobiological, neuroendocrine, neurophysiological, ethological, genetic, developmental, psychological, psychotherapeutic and neuropsychiatric consequences and is a prototype of complex neuroscientific concept as interpretation of modern integrated neuroscience.

Mitochondria: A Common Target for Genetic Mutations and Environmental Toxicants in Parkinson’s Disease

PubMed Central

Helley, Martin P.; Pinnell, Jennifer; Sportelli, Carolina; Tieu, Kim

2017-01-01

Parkinson’s disease (PD) is a devastating neurological movement disorder. Since its first discovery 200 years ago, genetic and environmental factors have been identified to play a role in PD development and progression. Although genetic studies have been the predominant driving force in PD research over the last few decades, currently only a small fraction of PD cases can be directly linked to monogenic mutations. The remaining cases have been attributed to other risk associated genes, environmental exposures and gene–environment interactions, making PD a multifactorial disorder with a complex etiology. However, enormous efforts from global research have yielded significant insights into pathogenic mechanisms and potential therapeutic targets for PD. This review will highlight mitochondrial dysfunction as a common pathway involved in both genetic mutations and environmental toxicants linked to PD. PMID:29204154

HcRed, a Genetically Encoded Fluorescent Binary Cross-Linking Agent for Cross-Linking of Mitochondrial ATP Synthase in Saccharomyces cerevisiae

PubMed Central

Gong, Lan; Ramm, Georg; Devenish, Rodney J.; Prescott, Mark

2012-01-01

Genetically encoded fluorescent cross-linking agents represent powerful tools useful both for visualising and modulating protein interactions in living cells. The far-red fluorescent protein HcRed, which is fluorescent only in a dimer form, can be used to promote the homo-dimerisation of target proteins, and thereby yield useful information about biological processes. We have in yeast cells expressed HcRed fused to a subunit of mitochondrial ATP synthase (mtATPase). This resulted in cross-linking of the large multi-subunit mtATPase complex within the inner-membrane of the mitochondrion. Fluorescence microscopy revealed aberrant mitochondrial morphology, and mtATPase complexes isolated from mitochondria were recovered as fluorescent dimers under conditions where complexes from control mitochondria were recovered as monomers. When viewed by electron microscopy normal cristae were absent from mitochondria in cells in which mATPase complexes were cross-linked. mtATPase dimers are believed to be the building blocks that are assembled into supramolecular mtATPase ribbons that promote the formation of mitochondrial cristae. We propose that HcRed cross-links mATPase complexes in the mitochondrial membrane hindering the normal assembly/disassembly of the supramolecular forms of mtATPase. PMID:22496895

Architecture of human translation initiation factor 3

PubMed Central

Querol-Audi, Jordi; Sun, Chaomin; Vogan, Jacob M.; Smith, Duane; Gu, Yu; Cate, Jamie; Nogales, Eva

2013-01-01

SUMMARY Eukaryotic translation initiation factor 3 (eIF3) plays a central role in protein synthesis by organizing the formation of the 43S preinitiation complex. Using genetic tag visualization by electron microscopy, we reveal the molecular organization of ten human eIF3 subunits, including an octameric core. The structure of eIF3 bears a close resemblance to that of the proteasome lid, with a conserved spatial organization of eight core subunits containing PCI and MPN domains that coordinate functional interactions in both complexes. We further show that eIF3 subunits a and c interact with initiation factors eIF1 and eIF1A, which control the stringency of start codon selection. Finally, we find that subunit j, which modulates messenger RNA interactions with the small ribosomal subunit, makes multiple independent interactions with the eIF3 octameric core. These results highlight the conserved architecture of eIF3 and how it scaffolds key factors that control translation initiation in higher eukaryotes, including humans. PMID:23623729

Commensurate distances and similar motifs in genetic congruence and protein interaction networks in yeast

PubMed Central

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

Present status of understanding on the genetic etiology of polycystic ovary syndrome.

PubMed

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.

Periodontal and inflammatory bowel diseases: Is there evidence of complex pathogenic interactions?

PubMed

Lira-Junior, Ronaldo; Figueredo, Carlos Marcelo

2016-09-21

Periodontal disease and inflammatory bowel disease (IBD) are both chronic inflammatory diseases. Their pathogenesis is mediated by a complex interplay between a dysbiotic microbiota and the host immune-inflammatory response, and both are influenced by genetic and environmental factors. This review aimed to provide an overview of the evidence dealing with a possible pathogenic interaction between periodontal disease and IBD. There seems to be an increased prevalence of periodontal disease in patients with IBD when compared to healthy controls, probably due to changes in the oral microbiota and a higher inflammatory response. Moreover, the induction of periodontitis seems to result in gut dysbiosis and altered gut epithelial cell barrier function, which might contribute to the pathogenesis of IBD. Considering the complexity of both periodontal disease and IBD, it is very challenging to understand the possible pathways involved in their coexistence. In conclusion, this review points to a complex pathogenic interaction between periodontal disease and IBD, in which one disease might alter the composition of the microbiota and increase the inflammatory response related to the other. However, we still need more data derived from human studies to confirm results from murine models. Thus, mechanistic studies are definitely warranted to clarify this possible bidirectional association.

Childhood Temperament: Passive Gene-Environment Correlation, Gene-Environment Interaction, and the Hidden Importance of the Family Environment

PubMed Central

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

A New Method, "Reverse Yeast Two-Hybrid Array" (RYTHA), Identifies Mutants that Dissociate the Physical Interaction Between Elg1 and Slx5.

PubMed

Lev, Ifat; Shemesh, Keren; Volpe, Marina; Sau, Soumitra; Levinton, Nelly; Molco, Maya; Singh, Shivani; Liefshitz, Batia; Ben Aroya, Shay; Kupiec, Martin

2017-07-01

The vast majority of processes within the cell are carried out by proteins working in conjunction. The Yeast Two-Hybrid (Y2H) methodology allows the detection of physical interactions between any two interacting proteins. Here, we describe a novel systematic genetic methodology, "Reverse Yeast Two-Hybrid Array" (RYTHA), that allows the identification of proteins required for modulating the physical interaction between two given proteins. Our assay starts with a yeast strain in which the physical interaction of interest can be detected by growth on media lacking histidine, in the context of the Y2H methodology. By combining the synthetic genetic array technology, we can systematically screen mutant libraries of the yeast Saccharomyces cerevisiae to identify trans -acting mutations that disrupt the physical interaction of interest. We apply this novel method in a screen for mutants that disrupt the interaction between the N-terminus of Elg1 and the Slx5 protein. Elg1 is part of an alternative replication factor C-like complex that unloads PCNA during DNA replication and repair. Slx5 forms, together with Slx8, a SUMO-targeted ubiquitin ligase (STUbL) believed to send proteins to degradation. Our results show that the interaction requires both the STUbL activity and the PCNA unloading by Elg1, and identify topoisomerase I DNA-protein cross-links as a major factor in separating the two activities. Thus, we demonstrate that RYTHA can be applied to gain insights about particular pathways in yeast, by uncovering the connection between the proteasomal ubiquitin-dependent degradation pathway, DNA replication, and repair machinery, which can be separated by the topoisomerase-mediated cross-links to DNA. Copyright © 2017 by the Genetics Society of America.

Protein-protein interactions and cancer: targeting the central dogma.

PubMed

Garner, Amanda L; Janda, Kim D

2011-01-01

Between 40,000 and 200,000 protein-protein interactions have been predicted to exist within the human interactome. As these interactions are of a critical nature in many important cellular functions and their dysregulation is causal of disease, the modulation of these binding events has emerged as a leading, yet difficult therapeutic arena. In particular, the targeting of protein-protein interactions relevant to cancer is of fundamental importance as the tumor-promoting function of several aberrantly expressed proteins in the cancerous state is directly resultant of its ability to interact with a protein-binding partner. Of significance, these protein complexes play a crucial role in each of the steps of the central dogma of molecular biology, the fundamental processes of genetic transmission. With the many important discoveries being made regarding the mechanisms of these genetic process, the identification of new chemical probes are needed to better understand and validate the druggability of protein-protein interactions related to the central dogma. In this review, we provide an overview of current small molecule-based protein-protein interaction inhibitors for each stage of the central dogma: transcription, mRNA splicing and translation. Importantly, through our analysis we have uncovered a lack of necessary probes targeting mRNA splicing and translation, thus, opening up the possibility for expansion of these fields.

Early Life Precursors, Epigenetics, and the Development of Food Allergy1

PubMed Central

Hong, Xiumei; Wang, Xiaobin

2012-01-01

Food allergy (FA), a major clinical and public health concern worldwide, is caused by a complex interplay of environmental exposures, genetic variants, gene-environment interactions, and epigenetic alterations. This review summarizes recent advances surrounding these key factors, with a particular focus on the potential role of epigenetics in the development of FA. Epidemiologic studies have reported a number of non-genetic factors that may influence the risk of FA, such as timing of food introduction and feeding pattern, diet/nutrition, exposure to environmental tobacco smoking, prematurity and low birthweight, microbial exposure, and race/ethnicity. Current studies on the genetics of FA are mainly conducted using candidate gene approaches, which have linked more than 10 genes to the genetic susceptibility of FA. Studies on gene-environment interactions of FA are very limited. Epigenetic alteration has been proposed as one of the mechanisms to mediate the influence of early-life environmental exposures and gene-environment interactions on the development of diseases later in life. The role of epigenetics in the regulation of the immune system and the epigenetic effects of some FA-associated environmental exposures are discussed in this review. There is a particular lack of large-scale prospective birth cohort studies that simultaneously assess the inter-relationships of early life exposures, genetic susceptibility, epigenomic alterations and the development of FA. The identification of these key factors and their independent and joint contributions to FA will allow us to gain important insight into the biological mechanisms by which environmental exposures and genetic susceptibility affect the risk of FA, and will provide essential information to develop more effective new paradigms in the diagnosis, prevention and management of FA. PMID:22777545

Vector-virus interactions and transmission dynamics of West Nile virus.

PubMed

Ciota, Alexander T; Kramer, Laura D

2013-12-09

West Nile virus (WNV; Flavivirus; Flaviviridae) is the cause of the most widespread arthropod-borne viral disease in the world and the largest outbreak of neuroinvasive disease ever observed. Mosquito-borne outbreaks are influenced by intrinsic (e.g., vector and viral genetics, vector and host competence, vector life-history traits) and extrinsic (e.g., temperature, rainfall, human land use) factors that affect virus activity and mosquito biology in complex ways. The concept of vectorial capacity integrates these factors to address interactions of the virus with the arthropod host, leading to a clearer understanding of their complex interrelationships, how they affect transmission of vector-borne disease, and how they impact human health. Vertebrate factors including host competence, population dynamics, and immune status also affect transmission dynamics. The complexity of these interactions are further exacerbated by the fact that not only can divergent hosts differentially alter the virus, but the virus also can affect both vertebrate and invertebrate hosts in ways that significantly alter patterns of virus transmission. This chapter concentrates on selected components of the virus-vector-vertebrate interrelationship, focusing specifically on how interactions between vector, virus, and environment shape the patterns and intensity of WNV transmission.

Vector-Virus Interactions and Transmission Dynamics of West Nile Virus

PubMed Central

Ciota, Alexander T.; Kramer, Laura D.

2013-01-01

West Nile virus (WNV; Flavivirus; Flaviviridae) is the cause of the most widespread arthropod-borne viral disease in the world and the largest outbreak of neuroinvasive disease ever observed. Mosquito-borne outbreaks are influenced by intrinsic (e.g., vector and viral genetics, vector and host competence, vector life-history traits) and extrinsic (e.g., temperature, rainfall, human land use) factors that affect virus activity and mosquito biology in complex ways. The concept of vectorial capacity integrates these factors to address interactions of the virus with the arthropod host, leading to a clearer understanding of their complex interrelationships, how they affect transmission of vector-borne disease, and how they impact human health. Vertebrate factors including host competence, population dynamics, and immune status also affect transmission dynamics. The complexity of these interactions are further exacerbated by the fact that not only can divergent hosts differentially alter the virus, but the virus also can affect both vertebrate and invertebrate hosts in ways that significantly alter patterns of virus transmission. This chapter concentrates on selected components of the virus-vector-vertebrate interrelationship, focusing specifically on how interactions between vector, virus, and environment shape the patterns and intensity of WNV transmission. PMID:24351794

Mirror Neurons through the Lens of Epigenetics

PubMed Central

Ferrari, Pier F.; Tramacere, Antonella; Simpson, Elizabeth A.; Iriki, Atsushi

2013-01-01

The consensus view in mirror neuron research is that mirror neurons comprise a uniform, stable execution-observation matching system. In this article, we argue that, in light of recent evidence, this is, at best, an incomplete and oversimplified view of mirror neurons, whose activity is actually quite variable and more plastic than previously theorized. We propose an epigenetic account for understanding developmental changes in sensorimotor systems, including variations in mirror neuron activity. Although extant associative and genetic accounts fail to consider the complexity of genetic and non-genetic interactions, we propose a new Evo-Devo perspective, which predicts that environmental differences early in development, or through sensorimotor training, should produce variations in mirror neuron response patterns, tuning them to the social environment. PMID:23953747

Chemical genetics and regeneration.

PubMed

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.

The E3 ligase Ubr3 regulates Usher syndrome and MYH9 disorder proteins in the auditory organs of Drosophila and mammals.

PubMed

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.

A Comparative Study on Multifactor Dimensionality Reduction Methods for Detecting Gene-Gene Interactions with the Survival Phenotype

PubMed Central

Lee, Seungyeoun; Kim, Yongkang; Kwon, Min-Seok; Park, Taesung

2015-01-01

Genome-wide association studies (GWAS) have extensively analyzed single SNP effects on a wide variety of common and complex diseases and found many genetic variants associated with diseases. However, there is still a large portion of the genetic variants left unexplained. This missing heritability problem might be due to the analytical strategy that limits analyses to only single SNPs. One of possible approaches to the missing heritability problem is to consider identifying multi-SNP effects or gene-gene interactions. The multifactor dimensionality reduction method has been widely used to detect gene-gene interactions based on the constructive induction by classifying high-dimensional genotype combinations into one-dimensional variable with two attributes of high risk and low risk for the case-control study. Many modifications of MDR have been proposed and also extended to the survival phenotype. In this study, we propose several extensions of MDR for the survival phenotype and compare the proposed extensions with earlier MDR through comprehensive simulation studies. PMID:26339630

Chronic Pancreatitis.

PubMed

Stram, Michelle; Liu, Shu; Singhi, Aatur D

2016-12-01

Chronic pancreatitis is a debilitating condition often associated with severe abdominal pain and exocrine and endocrine dysfunction. The underlying cause is multifactorial and involves complex interaction of environmental, genetic, and/or other risk factors. The pathology is dependent on the underlying pathogenesis of the disease. This review describes the clinical, gross, and microscopic findings of the main subtypes of chronic pancreatitis: alcoholic chronic pancreatitis, obstructive chronic pancreatitis, paraduodenal ("groove") pancreatitis, pancreatic divisum, autoimmune pancreatitis, and genetic factors associated with chronic pancreatitis. As pancreatic ductal adenocarcinoma may be confused with chronic pancreatitis, the main distinguishing features between these 2 diseases are discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

Plant genetics and interspecific competitive interactions determine ectomycorrhizal fungal community responses to climate change.

PubMed

Gehring, Catherine; Flores-Rentería, Dulce; Sthultz, Christopher M; Leonard, Tierra M; Flores-Rentería, Lluvia; Whipple, Amy V; Whitham, Thomas G

2014-03-01

Although the importance of plant-associated microbes is increasingly recognized, little is known about the biotic and abiotic factors that determine the composition of that microbiome. We examined the influence of plant genetic variation, and two stressors, one biotic and one abiotic, on the ectomycorrhizal (EM) fungal community of a dominant tree species, Pinus edulis. During three periods across 16 years that varied in drought severity, we sampled the EM fungal communities of a wild stand of P. edulis in which genetically based resistance and susceptibility to insect herbivory was linked with drought tolerance and the abundance of competing shrubs. We found that the EM fungal communities of insect-susceptible trees remained relatively constant as climate dried, while those of insect-resistant trees shifted significantly, providing evidence of a genotype by environment interaction. Shrub removal altered the EM fungal communities of insect-resistant trees, but not insect-susceptible trees, also a genotype by environment interaction. The change in the EM fungal community of insect-resistant trees following shrub removal was associated with greater shoot growth, evidence of competitive release. However, shrub removal had a 7-fold greater positive effect on the shoot growth of insect-susceptible trees than insect-resistant trees when shrub density was taken into account. Insect-susceptible trees had higher growth than insect-resistant trees, consistent with the hypothesis that the EM fungi associated with susceptible trees were superior mutualists. These complex, genetic-based interactions among species (tree-shrub-herbivore-fungus) argue that the ultimate impacts of climate change are both ecological and evolutionary. © 2013 John Wiley & Sons Ltd.

Genetic polymorphism in postoperative sepsis after open heart surgery in infants.

PubMed

Fakhri, Dicky; Djauzi, Samsuridjal; Murni, Tri Wahyu; Rachmat, Jusuf; Harahap, Alida Roswita; Rahayuningsih, Sri Endah; Mansyur, Muchtaruddin; Santoso, Anwar

2016-05-01

Sepsis is one of the complications following open heart surgery. Toll-like receptor 2 and toll-interacting protein polymorphism influence the immune response after open heart surgery. This study aimed to assess the genetic distribution of toll-like receptor 2 N199N and toll-interacting protein rs5743867 polymorphism in the development of postoperative sepsis. A prospective cohort study was conducted in 108 children <1-year old who underwent open heart surgery with a Basic Aristotle score ≥6. Patients with an accompanying congenital anomaly, human immunodeficiency virus infection, or history of previous open heart surgery were excluded. The patients' nutritional status and genetic polymorphism were assessed prior to surgery. The results of genetic polymorphism were obtained through genotyping. Patients' ages on the day of surgery and cardiopulmonary bypass times were recorded. The diagnosis of sepsis was established according to Surviving Sepsis Campaign criteria. Postoperative sepsis was observed in 21% of patients. There were 92.6% patients with toll-like receptor 2 N199N polymorphism and 52.8% with toll-interacting protein rs5743867 polymorphism. Toll-like receptor 2 N199N polymorphism tends to increase the risk of sepsis (odds ratio = 1.974; 95% confidence interval: 0.23-16.92; p = 0.504), while toll-interacting protein rs5743867 polymorphism tends to decrease the risk of sepsis (odds ratio = 0.496; 95% confidence interval: 0.19-1.27; p = 0.139) in infants <1-year old undergoing complex open heart surgery. © The Author(s) 2016.

Conceptual shifts needed to understand the dynamic interactions of genes, environment, epigenetics, social processes, and behavioral choices.

PubMed

Jackson, Fatimah L C; Niculescu, Mihai D; Jackson, Robert T

2013-10-01

Social and behavioral research in public health is often intimately tied to profound, but frequently neglected, biological influences from underlying genetic, environmental, and epigenetic events. The dynamic interplay between the life, social, and behavioral sciences often remains underappreciated and underutilized in addressing complex diseases and disorders and in developing effective remediation strategies. Using a case-study format, we present examples as to how the inclusion of genetic, environmental, and epigenetic data can augment social and behavioral health research by expanding the parameters of such studies, adding specificity to phenotypic assessments, and providing additional internal control in comparative studies. We highlight the important roles of gene-environment interactions and epigenetics as sources of phenotypic change and as a bridge between the life and social and behavioral sciences in the development of robust interdisciplinary analyses.

Genetics of nonsyndromic obesity.

PubMed

Lee, Yung Seng

2013-12-01

Common obesity is widely regarded as a complex, multifactorial trait influenced by the 'obesogenic' environment, sedentary behavior, and genetic susceptibility contributed by common and rare genetic variants. This review describes the recent advances in understanding the role of genetics in obesity. New susceptibility loci and genetic variants are being uncovered, but the collective effect is relatively small and could not explain most of the BMI heritability. Yet-to-be identified common and rare variants, epistasis, and heritable epigenetic changes may account for part of the 'missing heritability'. Evidence is emerging about the role of epigenetics in determining obesity susceptibility, mediating developmental plasticity, which confers obesity risk from early life experiences. Genetic prediction scores derived from selected genetic variants, and also differential DNA methylation levels and methylation scores, have been shown to correlate with measures of obesity and response to weight loss intervention. Genetic variants, which confer susceptibility to obesity-related morbidities like nonalcoholic fatty liver disease, were also discovered recently. We can expect discovery of more rare genetic variants with the advent of whole exome and genome sequencing, and also greater understanding of epigenetic mechanisms by which environment influences genetic expression and which mediate the gene-environment interaction.

SCAR/WAVE: A complex issue.

PubMed

Davidson, Andrew J; Insall, Robert H

2013-11-01

The SCAR/WAVE complex drives the actin polymerisation that underlies protrusion of the front of the cell and thus drives migration. However, it is not understood how the activity of SCAR/WAVE is regulated to generate the infinite range of cellular shape changes observed during cell motility. What are the relative roles of the subunits of the SCAR/WAVE complex? What signaling molecules do they interact with? And how does the complex integrate all this information in order to control the temporal and spatial polymerisation of actin during protrusion formation? Unfortunately, the interdependence of SCAR complex members has made genetic dissection hard. In our recent paper,(1) we describe stabilization of the Dictyostelium SCAR complex by a small fragment of Abi. Here we summarize the main findings and discuss how this approach can help reveal the inner workings of this impenetrable complex.

Genetic education for primary care providers

PubMed Central

Carroll, June C.; Rideout, Andrea L.; Wilson, Brenda J.; Allanson, Judith MD; Blaine, Sean M.; Esplen, Mary Jane; Farrell, Sandra A.; Graham, Gail E.; MacKenzie, Jennifer; Meschino, Wendy; Miller, Fiona; Prakash, Preeti; Shuman, Cheryl; Summers, Anne; Taylor, Sherry

2009-01-01

ABSTRACT OBJECTIVE To increase primary care providers’ awareness and use of genetic services; increase their knowledge of genetic issues; increase their confidence in core genetic competencies; change their attitudes toward genetic testing for hereditary diseases; and increase their confidence as primary care genetic resources. DESIGN Participants completed a workshop and 3 questionnaires: a baseline questionnaire, a survey that provided immediate feedback on the workshop itself, and a follow-up questionnaire 6 months later. SETTING Ontario. PARTICIPANTS Primary care providers suggested by deans of nursing, midwifery, family medicine, and obstetric programs, as well as coordinators of nurse practitioner programs, in Ontario and by the Ontario College of Family Physicians. INTERVENTION A complex educational intervention was developed, including an interactive workshop and PowerPoint educational modules on genetic topics for participants’ use (available at www.mtsinai.on.ca/FamMedGen/). MAIN OUTCOME MEASURES Awareness and use of genetic services, knowledge of genetics, confidence in core clinical genetic skills, attitudes toward genetic testing, and teaching activities related to genetics. RESULTS The workshop was attended by 29 participants; of those, 21 completed the baseline questionnaire and the 6-month follow-up questionnaire. There was no significant change found in awareness or reported use of genetic services. There was significant improvement in self-assessed knowledge of (P = .001) and confidence in (P = .005) skills related to adult-onset genetic disorders. There were significant increases in confidence in many core genetic competencies, including assessing risk of hereditary disorders (P = .033), deciding who should be offered referral for genetic counseling (P = .003), discussing prenatal testing options (P = .034), discussing benefits, risks, and limitations of genetic testing (P = .033), and describing what to expect at a genetic counseling session (P = .022). There was a significant increase in the number of primary care providers agreeing that genetic testing was beneficial in the management of adult-onset diseases (P = .031) and in their confidence in being primary care genetic resources for adult-onset genetic disorders (P = .006). CONCLUSION Educational interventions that include interactive peer resource workshops and educational modules can increase knowledge of and confidence in the core competencies needed for the delivery of genetic services in primary care. PMID:20008584

A random set scoring model for prioritization of disease candidate genes using protein complexes and data-mining of GeneRIF, OMIM and PubMed records.

PubMed

Jiang, Li; Edwards, Stefan M; Thomsen, Bo; Workman, Christopher T; Guldbrandtsen, Bernt; Sørensen, Peter

2014-09-24

Prioritizing genetic variants is a challenge because disease susceptibility loci are often located in genes of unknown function or the relationship with the corresponding phenotype is unclear. A global data-mining exercise on the biomedical literature can establish the phenotypic profile of genes with respect to their connection to disease phenotypes. The importance of protein-protein interaction networks in the genetic heterogeneity of common diseases or complex traits is becoming increasingly recognized. Thus, the development of a network-based approach combined with phenotypic profiling would be useful for disease gene prioritization. We developed a random-set scoring model and implemented it to quantify phenotype relevance in a network-based disease gene-prioritization approach. We validated our approach based on different gene phenotypic profiles, which were generated from PubMed abstracts, OMIM, and GeneRIF records. We also investigated the validity of several vocabulary filters and different likelihood thresholds for predicted protein-protein interactions in terms of their effect on the network-based gene-prioritization approach, which relies on text-mining of the phenotype data. Our method demonstrated good precision and sensitivity compared with those of two alternative complex-based prioritization approaches. We then conducted a global ranking of all human genes according to their relevance to a range of human diseases. The resulting accurate ranking of known causal genes supported the reliability of our approach. Moreover, these data suggest many promising novel candidate genes for human disorders that have a complex mode of inheritance. We have implemented and validated a network-based approach to prioritize genes for human diseases based on their phenotypic profile. We have devised a powerful and transparent tool to identify and rank candidate genes. Our global gene prioritization provides a unique resource for the biological interpretation of data from genome-wide association studies, and will help in the understanding of how the associated genetic variants influence disease or quantitative phenotypes.

Allele-specific gene expression in a wild nonhuman primate population

PubMed Central

Tung, J.; Akinyi, M. Y.; Mutura, S.; Altmann, J.; Wray, G. A.; Alberts, S. C.

2015-01-01

Natural populations hold enormous potential for evolutionary genetic studies, especially when phenotypic, genetic and environmental data are all available on the same individuals. However, untangling the genotype-phenotype relationship in natural populations remains a major challenge. Here, we describe results of an investigation of one class of phenotype, allele-specific gene expression (ASGE), in the well-studied natural population of baboons of the Amboseli basin, Kenya. ASGE measurements identify cases in which one allele of a gene is overexpressed relative to the alternative allele of the same gene, within individuals, thus providing a control for background genetic and environmental effects. Here, we characterize the incidence of ASGE in the Amboseli baboon population, focusing on the genetic and environmental contributions to ASGE in a set of eleven genes involved in immunity and defence. Within this set, we identify evidence for common ASGE in four genes. We also present examples of two relationships between cis-regulatory genetic variants and the ASGE phenotype. Finally, we identify one case in which this relationship is influenced by a novel gene-environment interaction. Specifically, the dominance rank of an individual’s mother during its early life (an aspect of that individual’s social environment) influences the expression of the gene CCL5 via an interaction with cis-regulatory genetic variation. These results illustrate how environmental and ecological data can be integrated into evolutionary genetic studies of functional variation in natural populations. They also highlight the potential importance of early life environmental variation in shaping the genetic architecture of complex traits in wild mammals. PMID:21226779

A robust multifactor dimensionality reduction method for detecting gene-gene interactions with application to the genetic analysis of bladder cancer susceptibility

PubMed Central

Gui, Jiang; Andrew, Angeline S.; Andrews, Peter; Nelson, Heather M.; Kelsey, Karl T.; Karagas, Margaret R.; Moore, Jason H.

2010-01-01

A central goal of human genetics is to identify and characterize susceptibility genes for common complex human diseases. An important challenge in this endeavor is the modeling of gene-gene interaction or epistasis that can result in non-additivity of genetic effects. The multifactor dimensionality reduction (MDR) method was developed as machine learning alternative to parametric logistic regression for detecting interactions in absence of significant marginal effects. The goal of MDR is to reduce the dimensionality inherent in modeling combinations of polymorphisms using a computational approach called constructive induction. Here, we propose a Robust Multifactor Dimensionality Reduction (RMDR) method that performs constructive induction using a Fisher’s Exact Test rather than a predetermined threshold. The advantage of this approach is that only those genotype combinations that are determined to be statistically significant are considered in the MDR analysis. We use two simulation studies to demonstrate that this approach will increase the success rate of MDR when there are only a few genotype combinations that are significantly associated with case-control status. We show that there is no loss of success rate when this is not the case. We then apply the RMDR method to the detection of gene-gene interactions in genotype data from a population-based study of bladder cancer in New Hampshire. PMID:21091664

Capsaicin consumption, Helicobacter pylori CagA status and IL1B-31C > T genotypes: A host and environment interaction in gastric cancer

PubMed Central

López-Carrillo, Lizbeth; Camargo, M. Constanza; Schneider, Barbara G.; Sicinschi, Liviu A.; Hernández-Ramírez, Raúl U.; Correa, Pelayo; Cebrian, Mariano E.

2013-01-01

Gastric cancer (GC) has been associated with a complex combination of genetic and environmental factors. In contrast to most countries, available information on GC mortality trends showed a gradual increase in Mexico. Our aim was to explore potential interactions among dietary (chili pepper consumption), infectious (Helicobacter pylori) and genetic factors (IL1B-31 genotypes) on GC risk. The study was performed in three areas of Mexico, with different GC mortality rates. We included 158 GC patients and 317 clinical controls. Consumption of capsaicin (Cap), the pungent active substance of chili peppers, was estimated by food frequency questionnaire. H. pylori CagA status was assessed by ELISA, and IL1B-31 genotypes were determined by TaqMan assays and Pyrosequencing in DNA samples. Multivariate unconditional logistic regression was used to estimate potential interactions. Moderate to high Cap consumption synergistically increased GC risk in genetically susceptible individuals (IL1B-31C allele carriers) infected with the more virulent H. pylori (CagA+) strains. The combined presence of these factors might explain the absence of a decreasing trend for GC in Mexico. However, further research on gene–environment interactions is required to fully understand the factors determining GC patterns in susceptible populations, with the aim of recommending preventive measures for high risk individuals. PMID:22414649

Genome-Wide Protein Interaction Screens Reveal Functional Networks Involving Sm-Like Proteins

PubMed Central

Fromont-Racine, Micheline; Mayes, Andrew E.; Brunet-Simon, Adeline; Rain, Jean-Christophe; Colley, Alan; Dix, Ian; Decourty, Laurence; Joly, Nicolas; Ricard, Florence; Beggs, Jean D.

2000-01-01

A set of seven structurally related Sm proteins forms the core of the snRNP particles containing the spliceosomal U1, U2, U4 and U5 snRNAs. A search of the genomic sequence of Saccharomyces cerevisiae has identified a number of open reading frames that potentially encode structurally similar proteins termed Lsm (Like Sm) proteins. With the aim of analysing all possible interactions between the Lsm proteins and any protein encoded in the yeast genome, we performed exhaustive and iterative genomic two-hybrid screens, starting with the Lsm proteins as baits. Indeed, extensive interactions amongst eight Lsm proteins were found that suggest the existence of a Lsm complex or complexes. These Lsm interactions apparently involve the conserved Sm domain that also mediates interactions between the Sm proteins. The screens also reveal functionally significant interactions with splicing factors, in particular with Prp4 and Prp24, compatible with genetic studies and with the reported association of Lsm proteins with spliceosomal U6 and U4/U6 particles. In addition, interactions with proteins involved in mRNA turnover, such as Mrt1, Dcp1, Dcp2 and Xrn1, point to roles for Lsm complexes in distinct RNA metabolic processes, that are confirmed in independent functional studies. These results provide compelling evidence that two-hybrid screens yield functionally meaningful information about protein–protein interactions and can suggest functions for uncharacterized proteins, especially when they are performed on a genome-wide scale. PMID:10900456

Pathogenesis of Crohn's disease

PubMed Central

Boyapati, Ray; Satsangi, Jack

2015-01-01

Significant progress in our understanding of Crohn's disease (CD), an archetypal common, complex disease, has now been achieved. Our ability to interrogate the deep complexities of the biological processes involved in maintaining gut mucosal homeostasis is a major over-riding factor underpinning this rapid progress. Key studies now offer many novel and expansive insights into the interacting roles of genetic susceptibility, immune function, and the gut microbiota in CD. Here, we provide overviews of these recent advances and new mechanistic themes, and address the challenges and prospects for translation from concept to clinic. PMID:26097717

A method to associate all possible combinations of genetic and environmental factors using GxE landscape plot.

PubMed

Nagaie, Satoshi; Ogishima, Soichi; Nakaya, Jun; Tanaka, Hiroshi

2015-01-01

Genome-wide association studies (GWAS) and linkage analysis has identified many single nucleotide polymorphisms (SNPs) related to disease. There are many unknown SNPs whose minor allele frequencies (MAFs) as low as 0.005 having intermediate effects with odds ratio between 1.5~3.0. Low frequency variants having intermediate effects on disease pathogenesis are believed to have complex interactions with environmental factors called gene-environment interactions (GxE). Hence, we describe a model using 3D Manhattan plot called GxE landscape plot to visualize the association of p-values for gene-environment interactions (GxE). We used the Gene-Environment iNteraction Simulator 2 (GENS2) program to simulate interactions between two genetic loci and one environmental factor in this exercise. The dataset used for training contains disease status, gender, 20 environmental exposures and 100 genotypes for 170 subjects, and p-values were calculated by Cochran-Mantel-Haenszel chi-squared test on known data. Subsequently, we created a 3D GxE landscape plot of negative logarithm of the association of p-values for all the possible combinations of genetic and environmental factors with their hierarchical clustering. Thus, the GxE landscape plot is a valuable model to predict association of p-values for GxE and similarity among genotypes and environments in the context of disease pathogenesis. GxE - Gene-environment interactions, GWAS - Genome-wide association study, MAFs - Minor allele frequencies, SNPs - Single nucleotide polymorphisms, EWAS - Environment-wide association study, FDR - False discovery rate, JPT+CHB - HapMap population of Japanese in Tokyo, Japan - Han Chinese in Beijing.

Synaptic Targeting and Function of SAPAPs Mediated by Phosphorylation-Dependent Binding to PSD-95 MAGUKs.

PubMed

Zhu, Jinwei; Zhou, Qingqing; Shang, Yuan; Li, Hao; Peng, Mengjuan; Ke, Xiao; Weng, Zhuangfeng; Zhang, Rongguang; Huang, Xuhui; Li, Shawn S C; Feng, Guoping; Lu, Youming; Zhang, Mingjie

2017-12-26

The PSD-95/SAPAP/Shank complex functions as the major scaffold in orchestrating the formation and plasticity of the post-synaptic densities (PSDs). We previously demonstrated that the exquisitely specific SAPAP/Shank interaction is critical for Shank synaptic targeting and Shank-mediated synaptogenesis. Here, we show that the PSD-95/SAPAP interaction, SAPAP synaptic targeting, and SAPAP-mediated synaptogenesis require phosphorylation of the N-terminal repeat sequences of SAPAPs. The atomic structure of the PSD-95 guanylate kinase (GK) in complex with a phosphor-SAPAP repeat peptide, together with biochemical studies, reveals the molecular mechanism underlying the phosphorylation-dependent PSD-95/SAPAP interaction, and it also provides an explanation of a PSD-95 mutation found in patients with intellectual disabilities. Guided by the structural data, we developed potent non-phosphorylated GK inhibitory peptides capable of blocking the PSD-95/SAPAP interaction and interfering with PSD-95/SAPAP-mediated synaptic maturation and strength. These peptides are genetically encodable for investigating the functions of the PSD-95/SAPAP interaction in vivo. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

The ribonuclease polynucleotide phosphorylase can interact with small regulatory RNAs in both protective and degradative modes.

PubMed

Bandyra, Katarzyna J; Sinha, Dhriti; Syrjanen, Johanna; Luisi, Ben F; De Lay, Nicholas R

2016-03-01

In all bacterial species examined thus far, small regulatory RNAs (sRNAs) contribute to intricate patterns of dynamic genetic regulation. Many of the actions of these nucleic acids are mediated by well-characterized chaperones such as the Hfq protein, but genetic screens have also recently identified the 3'-to-5' exoribonuclease polynucleotide phosphorylase (PNPase) as an unexpected stabilizer and facilitator of sRNAs in vivo. To understand how a ribonuclease might mediate these effects, we tested the interactions of PNPase with sRNAs and found that the enzyme can readily degrade these nucleic acids in vitro but, nonetheless, copurifies from cell extracts with the same sRNAs without discernible degradation or modification to their 3' ends, suggesting that the associated RNA is protected against the destructive activity of the ribonuclease. In vitro, PNPase, Hfq, and sRNA can form a ternary complex in which the ribonuclease plays a nondestructive, structural role. Such ternary complexes might be formed transiently in vivo, but could help to stabilize particular sRNAs and remodel their population on Hfq. Taken together, our results indicate that PNPase can be programmed to act on RNA in either destructive or stabilizing modes in vivo and may form complex, protective ribonucleoprotein assemblies that shape the landscape of sRNAs available for action. © 2016 Bandyra et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

The ribonuclease polynucleotide phosphorylase can interact with small regulatory RNAs in both protective and degradative modes

PubMed Central

Bandyra, Katarzyna J.; Sinha, Dhriti; Syrjanen, Johanna; Luisi, Ben F.; De Lay, Nicholas R.

2016-01-01

In all bacterial species examined thus far, small regulatory RNAs (sRNAs) contribute to intricate patterns of dynamic genetic regulation. Many of the actions of these nucleic acids are mediated by well-characterized chaperones such as the Hfq protein, but genetic screens have also recently identified the 3′-to-5′ exoribonuclease polynucleotide phosphorylase (PNPase) as an unexpected stabilizer and facilitator of sRNAs in vivo. To understand how a ribonuclease might mediate these effects, we tested the interactions of PNPase with sRNAs and found that the enzyme can readily degrade these nucleic acids in vitro but, nonetheless, copurifies from cell extracts with the same sRNAs without discernible degradation or modification to their 3′ ends, suggesting that the associated RNA is protected against the destructive activity of the ribonuclease. In vitro, PNPase, Hfq, and sRNA can form a ternary complex in which the ribonuclease plays a nondestructive, structural role. Such ternary complexes might be formed transiently in vivo, but could help to stabilize particular sRNAs and remodel their population on Hfq. Taken together, our results indicate that PNPase can be programmed to act on RNA in either destructive or stabilizing modes in vivo and may form complex, protective ribonucleoprotein assemblies that shape the landscape of sRNAs available for action. PMID:26759452

Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network.

PubMed

Al-Harazi, Olfat; Al Insaif, Sadiq; Al-Ajlan, Monirah A; Kaya, Namik; Dzimiri, Nduna; Colak, Dilek

2016-06-20

A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network (interactome) indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy (IDCM) data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field. Copyright © 2015 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

Dissecting genetic architecture of grape proanthocyanidin composition through quantitative trait locus mapping

PubMed Central

2012-01-01

Background Proanthocyanidins (PAs), or condensed tannins, are flavonoid polymers, widespread throughout the plant kingdom, which provide protection against herbivores while conferring organoleptic and nutritive values to plant-derived foods, such as wine. However, the genetic basis of qualitative and quantitative PA composition variation is still poorly understood. To elucidate the genetic architecture of the complex grape PA composition, we first carried out quantitative trait locus (QTL) analysis on a 191-individual pseudo-F1 progeny. Three categories of PA variables were assessed: total content, percentages of constitutive subunits and composite ratio variables. For nine functional candidate genes, among which eight co-located with QTLs, we performed association analyses using a diversity panel of 141 grapevine cultivars in order to identify causal SNPs. Results Multiple QTL analysis revealed a total of 103 and 43 QTLs, respectively for seed and skin PA variables. Loci were mainly of additive effect while some loci were primarily of dominant effect. Results also showed a large involvement of pairwise epistatic interactions in shaping PA composition. QTLs for PA variables in skin and seeds differed in number, position, involvement of epistatic interaction and allelic effect, thus revealing different genetic determinisms for grape PA composition in seeds and skin. Association results were consistent with QTL analyses in most cases: four out of nine tested candidate genes (VvLAR1, VvMYBPA2, VvCHI1, VvMYBPA1) showed at least one significant association with PA variables, especially VvLAR1 revealed as of great interest for further functional investigation. Some SNP-phenotype associations were observed only in the diversity panel. Conclusions This study presents the first QTL analysis on grape berry PA composition with a comparison between skin and seeds, together with an association study. Our results suggest a complex genetic control for PA traits and different genetic architectures for grape PA composition between berry skin and seeds. This work also uncovers novel genomic regions for further investigation in order to increase our knowledge of the genetic basis of PA composition. PMID:22369244

Understanding the complexities of Salmonella-host crosstalk as revealed by in vivo model organisms.

PubMed

Verma, Smriti; Srikanth, Chittur V

2015-07-01

Foodborne infections caused by non-typhoidal Salmonellae, such as Salmonella enterica serovar Typhimurium (ST), pose a major challenge in the developed and developing world. With constant rise of drug-resistant strains, understanding the epidemiology, microbiology, pathogenesis and host-pathogen interactions biology is a mandatory requirement to enable health systems to be ready to combat these illnesses. Patient data from hospitals, at least from some parts of the world, have aided in epidemiological understanding of ST-mediated disease. Most of the other aspects connected to Salmonella-host crosstalk have come from model systems that offer convenience, genetic tractability and low maintenance costs that make them extremely valuable tools. Complex model systems such as the bovine model have helped in understanding key virulence factors needed for infection. Simple systems such as fruit flies and Caenorhabditis elegans have aided in identification of novel virulence factors, host pathways and mechanistic details of interactions. Some of the path-breaking concepts of the field have come from mice model of ST colitis, which allows genetic manipulations as well as high degree of similarity to human counterpart. Together, they are invaluable for correlating in vitro findings of ST-induced disease progression in vivo. The current review is a compilation of various advances of ST-host interactions at cellular and molecular levels that has come from investigations involving model organisms. © 2015 International Union of Biochemistry and Molecular Biology.

Vfa1 binds to the N-terminal microtubule-interacting and trafficking (MIT) domain of Vps4 and stimulates its ATPase activity.

PubMed

Vild, Cody J; Xu, Zhaohui

2014-04-11

The endosomal sorting complexes required for transport (ESCRT) are responsible for multivesicular body biogenesis, membrane abscission during cytokinesis, and retroviral budding. They function as transiently assembled molecular complexes on the membrane, and their disassembly requires the action of the AAA-ATPase Vps4. Vps4 is regulated by a multitude of ESCRT and ESCRT-related proteins. Binding of these proteins to Vps4 is often mediated via the microtubule-interacting and trafficking (MIT) domain of Vps4. Recently, a new Vps4-binding protein Vfa1 was identified in a yeast genetic screen, where overexpression of Vfa1 caused defects in vacuolar morphology. However, the function of Vfa1 and its role in vacuolar biology were largely unknown. Here, we provide the first detailed biochemical and biophysical study of Vps4-Vfa1 interaction. The MIT domain of Vps4 binds to the C-terminal 17 residues of Vfa1. This interaction is of high affinity and greatly stimulates the ATPase activity of Vps4. The crystal structure of the Vps4-Vfa1 complex shows that Vfa1 adopts a canonical MIT-interacting motif 2 structure that has been observed previously in other Vps4-ESCRT interactions. These findings suggest that Vfa1 is a novel positive regulator of Vps4 function.

Vfa1 Binds to the N-terminal Microtubule-interacting and Trafficking (MIT) Domain of Vps4 and Stimulates Its ATPase Activity*

PubMed Central

Vild, Cody J.; Xu, Zhaohui

2014-01-01

The endosomal sorting complexes required for transport (ESCRT) are responsible for multivesicular body biogenesis, membrane abscission during cytokinesis, and retroviral budding. They function as transiently assembled molecular complexes on the membrane, and their disassembly requires the action of the AAA-ATPase Vps4. Vps4 is regulated by a multitude of ESCRT and ESCRT-related proteins. Binding of these proteins to Vps4 is often mediated via the microtubule-interacting and trafficking (MIT) domain of Vps4. Recently, a new Vps4-binding protein Vfa1 was identified in a yeast genetic screen, where overexpression of Vfa1 caused defects in vacuolar morphology. However, the function of Vfa1 and its role in vacuolar biology were largely unknown. Here, we provide the first detailed biochemical and biophysical study of Vps4-Vfa1 interaction. The MIT domain of Vps4 binds to the C-terminal 17 residues of Vfa1. This interaction is of high affinity and greatly stimulates the ATPase activity of Vps4. The crystal structure of the Vps4-Vfa1 complex shows that Vfa1 adopts a canonical MIT-interacting motif 2 structure that has been observed previously in other Vps4-ESCRT interactions. These findings suggest that Vfa1 is a novel positive regulator of Vps4 function. PMID:24567329

CTR1 phosphorylates the central regulator EIN2 to control ethylene hormone signaling from the ER membrane to the nucleus in Arabidopsis

USDA-ARS?s Scientific Manuscript database

The gaseous phytohormone ethylene (C2H4) mediates numerous aspects of growth and development. Genetic analysis has identified a number of critical elements in the ethylene signaling (1), but how these elements interact biochemically to transduce the signal from the ethylene receptor complex at the e...

Influence of host resistance on the genetic structure of the white pine blister rust fungus in the western United States

Treesearch

B. A. Richardson; N. B. Klopfenstein; P. J. Zambino; G. I. McDonald; B. W. Geils; L. M. Carris

2008-01-01

Cronartium ribicola, the causal agent of white pine blister rust, has been devastating to five-needled white pines in North America since its introduction nearly a century ago. However, dynamic and complex interactions occur among C. ribicola, five-needled white pines, and the environment. To examine potential evolutionary...

Commentary: Fundamental problems with candidate gene-by-environment interaction studies - reflections on Moore and Thoemmes (2016).

PubMed

Border, Richard; Keller, Matthew C

2017-03-01

Moore and Thoemmes elaborate on one particular source of difficulty in the study of candidate gene-by-environment interactions (cG × E): how different biologically plausible configurations of gene-environment covariation can bias estimates of cG × E when not explicitly modeled. However, even if cG × E investigators were able to account for the sources of bias Moore and Thoemmes elaborate, it is unlikely that conventional approaches would yield reliable results. Published cG × E findings to date have generally employed inadequate analytic procedures, have relied on samples orders of magnitude too small to detect plausible effects, and have relied on a particular candidate gene approach that has been unfruitful and largely jettisoned in mainstream genetic analyses of complex traits. Analytic procedures for the study of gene-environment interplay must evolve to meet the challenges that the genetic architecture of complex traits presents, and investigators must collaborate on grander scales if we hope to begin to understand how specific genes and environments combine to affect behavior. © 2017 Association for Child and Adolescent Mental Health.

Mapping the Schizophrenia Genes by Neuroimaging: The Opportunities and the Challenges

PubMed Central

2018-01-01

Schizophrenia (SZ) is a heritable brain disease originating from a complex interaction of genetic and environmental factors. The genes underpinning the neurobiology of SZ are largely unknown but recent data suggest strong evidence for genetic variations, such as single nucleotide polymorphisms, making the brain vulnerable to the risk of SZ. Structural and functional brain mapping of these genetic variations are essential for the development of agents and tools for better diagnosis, treatment and prevention of SZ. Addressing this, neuroimaging methods in combination with genetic analysis have been increasingly used for almost 20 years. So-called imaging genetics, the opportunities of this approach along with its limitations for SZ research will be outlined in this invited paper. While the problems such as reproducibility, genetic effect size, specificity and sensitivity exist, opportunities such as multivariate analysis, development of multisite consortia for large-scale data collection, emergence of non-candidate gene (hypothesis-free) approach of neuroimaging genetics are likely to contribute to a rapid progress for gene discovery besides to gene validation studies that are related to SZ. PMID:29324666

Pharmacogenetics of drug-drug interaction and drug-drug-gene interaction: a systematic review on CYP2C9, CYP2C19 and CYP2D6.

PubMed

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.

Spatial mapping and quantification of developmental branching morphogenesis.

PubMed

Short, Kieran; Hodson, Mark; Smyth, Ian

2013-01-15

Branching morphogenesis is a fundamental developmental mechanism that shapes the formation of many organs. The complex three-dimensional shapes derived by this process reflect equally complex genetic interactions between branching epithelia and their surrounding mesenchyme. Despite the importance of this process to normal adult organ function, analysis of branching has been stymied by the absence of a bespoke method to quantify accurately the complex spatial datasets that describe it. As a consequence, although many developmentally important genes are proposed to influence branching morphogenesis, we have no way of objectively assessing their individual contributions to this process. We report the development of a method for accurately quantifying many aspects of branching morphogenesis and we demonstrate its application to the study of organ development. As proof of principle we have employed this approach to analyse the developing mouse lung and kidney, describing the spatial characteristics of the branching ureteric bud and pulmonary epithelia. To demonstrate further its capacity to profile unrecognised genetic contributions to organ development, we examine Tgfb2 mutant kidneys, identifying elements of both developmental delay and specific spatial dysmorphology caused by haplo-insufficiency for this gene. This technical advance provides a crucial resource that will enable rigorous characterisation of the genetic and environmental factors that regulate this essential and evolutionarily conserved developmental mechanism.

Research advances on microbial genetics in China in 2015.

PubMed

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.

LONI visualization environment.

PubMed

Dinov, Ivo D; Valentino, Daniel; Shin, Bae Cheol; Konstantinidis, Fotios; Hu, Guogang; MacKenzie-Graham, Allan; Lee, Erh-Fang; Shattuck, David; Ma, Jeff; Schwartz, Craig; Toga, Arthur W

2006-06-01

Over the past decade, the use of informatics to solve complex neuroscientific problems has increased dramatically. Many of these research endeavors involve examining large amounts of imaging, behavioral, genetic, neurobiological, and neuropsychiatric data. Superimposing, processing, visualizing, or interpreting such a complex cohort of datasets frequently becomes a challenge. We developed a new software environment that allows investigators to integrate multimodal imaging data, hierarchical brain ontology systems, on-line genetic and phylogenic databases, and 3D virtual data reconstruction models. The Laboratory of Neuro Imaging visualization environment (LONI Viz) consists of the following components: a sectional viewer for imaging data, an interactive 3D display for surface and volume rendering of imaging data, a brain ontology viewer, and an external database query system. The synchronization of all components according to stereotaxic coordinates, region name, hierarchical ontology, and genetic labels is achieved via a comprehensive BrainMapper functionality, which directly maps between position, structure name, database, and functional connectivity information. This environment is freely available, portable, and extensible, and may prove very useful for neurobiologists, neurogenetisists, brain mappers, and for other clinical, pedagogical, and research endeavors.

Between “design” and “bricolage”: Genetic networks, levels of selection, and adaptive evolution

PubMed Central

Wilkins, Adam S.

2007-01-01

The extent to which “developmental constraints” in complex organisms restrict evolutionary directions remains contentious. Yet, other forms of internal constraint, which have received less attention, may also exist. It will be argued here that a set of partial constraints below the level of phenotypes, those involving genes and molecules, influences and channels the set of possible evolutionary trajectories. At the top-most organizational level there are the genetic network modules, whose operations directly underlie complex morphological traits. The properties of these network modules, however, have themselves been set by the evolutionary history of the component genes and their interactions. Characterization of the components, structures, and operational dynamics of specific genetic networks should lead to a better understanding not only of the morphological traits they underlie but of the biases that influence the directions of evolutionary change. Furthermore, such knowledge may permit assessment of the relative degrees of probability of short evolutionary trajectories, those on the microevolutionary scale. In effect, a “network perspective” may help transform evolutionary biology into a scientific enterprise with greater predictive capability than it has hitherto possessed. PMID:17494754

Between "design" and "bricolage": genetic networks, levels of selection, and adaptive evolution.

PubMed

Wilkins, Adam S

2007-05-15

The extent to which "developmental constraints" in complex organisms restrict evolutionary directions remains contentious. Yet, other forms of internal constraint, which have received less attention, may also exist. It will be argued here that a set of partial constraints below the level of phenotypes, those involving genes and molecules, influences and channels the set of possible evolutionary trajectories. At the top-most organizational level there are the genetic network modules, whose operations directly underlie complex morphological traits. The properties of these network modules, however, have themselves been set by the evolutionary history of the component genes and their interactions. Characterization of the components, structures, and operational dynamics of specific genetic networks should lead to a better understanding not only of the morphological traits they underlie but of the biases that influence the directions of evolutionary change. Furthermore, such knowledge may permit assessment of the relative degrees of probability of short evolutionary trajectories, those on the microevolutionary scale. In effect, a "network perspective" may help transform evolutionary biology into a scientific enterprise with greater predictive capability than it has hitherto possessed.

Genetics, environmental factors and the emerging role of epigenetics in neurodegenerative diseases.

PubMed

Migliore, Lucia; Coppedè, Fabio

2009-07-10

In the present review we summarize recent advances in the understanding of the interaction between genetics and environmental factors involved in complex multi-factorial neurodegenerative disorders such as Alzheimer's disease (AD), Parkinson's disease (PD) and Amyotrophic Lateral Sclerosis (ALS). The discovery of several genes responsible for the familial forms has led to a better comprehension of the molecular pathways involved in the selective neuronal degeneration which is specific for each of these disorders. However, the vast majority of the cases occurs as sporadic forms, likely resulting from complex gene-gene and gene-environment interplay. Several environmental factors, including, pesticides, metals, head injuries, lifestyles and dietary habits have been associated with increased disease risk or even with protection. Hundreds of genetic variants have been investigated as possible risk factors for the sporadic forms, but results are often conflicting, not repeated or inconclusive. New approaches to environmental health research are revealing us that at the basis there could be chemically induced changes in gene regulation and emphasise the importance of understanding the susceptibility of the human epigenome to dietary and other environmental effects.

Chemical and Biological Tools for the Preparation of Modified Histone Proteins

PubMed Central

Howard, Cecil J.; Yu, Ruixuan R.; Gardner, Miranda L.; Shimko, John C.; Ottesen, Jennifer J.

2016-01-01

Eukaryotic chromatin is a complex and dynamic system in which the DNA double helix is organized and protected by interactions with histone proteins. This system is regulated through, a large network of dynamic post-translational modifications (PTMs) exists to ensure proper gene transcription, DNA repair, and other processes involving DNA. Homogenous protein samples with precisely characterized modification sites are necessary to better understand the functions of modified histone proteins. Here, we discuss sets of chemical and biological tools that have been developed for the preparation of modified histones, with a focus on the appropriate choice of tool for a given target. We start with genetic approaches for the creation of modified histones, including the incorporation of genetic mimics of histone modifications, chemical installation of modification analogs, and the use of the expanded genetic code to incorporate modified amino acids. Additionally, we will cover the chemical ligation techniques that have been invaluable in the generation of complex modified histones that are indistinguishable from the natural counterparts. Finally, we will end with a prospectus on future directions of synthetic chromatin in living systems. PMID:25863817

Genetic architecture of hybrid male sterility in Drosophila: analysis of intraspecies variation for interspecies isolation.

PubMed

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.

Trans-Homolog Interactions Facilitating Paramutation in Maize

PubMed Central

2015-01-01

Paramutations represent locus-specific trans-homolog interactions affecting the heritable silencing properties of endogenous alleles. Although examples of paramutation are well studied in maize (Zea mays), the responsible mechanisms remain unclear. Genetic analyses indicate roles for plant-specific DNA-dependent RNA polymerases that generate small RNAs, and current working models hypothesize that these small RNAs direct heritable changes at sequences often acting as transcriptional enhancers. Several studies have defined specific sequences that mediate paramutation behaviors, and recent results identify a diversity of DNA-dependent RNA polymerase complexes operating in maize. Other reports ascribe broader roles for some of these complexes in normal genome function. This review highlights recent research to understand the molecular mechanisms of paramutation and examines evidence relevant to small RNA-based modes of transgenerational epigenetic inheritance. PMID:26149572

The microgeographical patterns of morphological and molecular variation of a mixed ploidy population in the species complex Actinidia chinensis.

PubMed

Liu, Yifei; Li, Dawei; Yan, Ling; Huang, Hongwen

2015-01-01

Polyploidy and hybridization are thought to have significant impacts on both the evolution and diversification of the genus Actinidia, but the structure and patterns of morphology and molecular diversity relating to ploidy variation of wild Actinidia plants remain much less understood. Here, we examine the distribution of morphological variation and ploidy levels along geographic and environmental variables of a large mixed-ploidy population of the A. chinensis species complex. We then characterize the extent of both genetic and epigenetic diversity and differentiation exhibited between individuals of different ploidy levels. Our results showed that while there are three ploidy levels in this population, hexaploids were constituted the majority (70.3%). Individuals with different ploidy levels were microgeographically structured in relation to elevation and extent of niche disturbance. The morphological characters examined revealed clear difference between diploids and hexaploids, however tetraploids exhibited intermediate forms. Both genetic and epigenetic diversity were high but the differentiation among cytotypes was weak, suggesting extensive gene flow and/or shared ancestral variation occurred in this population even across ploidy levels. Epigenetic variation was clearly correlated with changes in altitudes, a trend of continuous genetic variation and gradual increase of epigenomic heterogeneities of individuals was also observed. Our results show that complex interactions between the locally microgeographical environment, ploidy and gene flow impact A. chinensis genetic and epigenetic variation. We posit that an increase in ploidy does not broaden the species habitat range, but rather permits A. chinensis adaptation to specific niches.

Prasinoviruses reveal a complex evolutionary history and a patchy environmental distribution

NASA Astrophysics Data System (ADS)

Finke, J. F.; Suttle, C.

2016-02-01

Prasinophytes constitute a group of eukaryotic phytoplankton that has a global distribution and is a major component of coastal and oceanic communities. Members of this group are infected by large double-stranded DNA viruses that can be significant agents of mortality, and which show evidence of substantial horizontal transfer of genes from their hosts and other organisms. However, information on the genetic diversity of these viruses and their environmental distribution is limited. This study examines the genetic repertoire, phylogeny and environmental distribution of large double-stranded DNA viruses infecting Micromonas pusilla and other prasinophytes. The genomes of viruses infecting M. pusilla were sequenced and compared to those of viruses infecting other prasinophytes, revealing a relatively small set of core genes and a larger flexible pan genome. Comparing genomes among prasinoviruses highlights their variable genetic content and complex evolutionary history. While some of the pan genome is clearly host derived, many open reading frames are most similar to those found in other eukaryotes and bacteria. Gene content of the viruses is is congruent with phylogenetic analysis of viral DNA polymerase sequences and indicates that two clades of M. pusilla viruses are less related to each other than to other prasinoviruses. Moreover, the environmental distribution of prasinovirus DNA polymerase sequences indicates a complex pattern of virus-host interactions in nature. Ultimately, these patterns are influenced by the genetic repertoire encoded by prasinoviruses, and the distribution of the hosts they infect.

NuA4 Lysine Acetyltransferase Complex Contributes to Phospholipid Homeostasis in Saccharomyces cerevisiae.

PubMed

Dacquay, Louis; Flint, Annika; Butcher, James; Salem, Danny; Kennedy, Michael; Kaern, Mads; Stintzi, Alain; Baetz, Kristin

2017-06-07

Actively proliferating cells constantly monitor and readjust their metabolic pathways to ensure the replenishment of phospholipids necessary for membrane biogenesis and intracellular trafficking. In Saccharomyces cerevisiae , multiple studies have suggested that the lysine acetyltransferase complex NuA4 plays a role in phospholipid homeostasis. For one, NuA4 mutants induce the expression of the inositol-3-phosphate synthase gene, INO1 , which leads to excessive accumulation of inositol, a key metabolite used for phospholipid biosynthesis. Additionally, NuA4 mutants also display negative genetic interactions with sec14-1 ts , a mutant of a lipid-binding gene responsible for phospholipid remodeling of the Golgi. Here, using a combination of genetics and transcriptional profiling, we explore the connections between NuA4, inositol, and Sec14 Surprisingly, we found that NuA4 mutants did not suppress but rather exacerbated the growth defects of sec14-1 ts under inositol-depleted conditions. Transcriptome studies reveal that while loss of the NuA4 subunit EAF1 in sec14-1 ts does derepress INO1 expression, it does not derepress all inositol/choline-responsive phospholipid genes, suggesting that the impact of Eaf1 on phospholipid homeostasis extends beyond inositol biosynthesis. In fact, we find that NuA4 mutants have impaired lipid droplet levels and through genetic and chemical approaches, we determine that the genetic interaction between sec14-1 ts and NuA4 mutants potentially reflects a role for NuA4 in fatty acid biosynthesis. Altogether, our work identifies a new role for NuA4 in phospholipid homeostasis. Copyright © 2017 Dacquay et al.

NLR mutations suppressing immune hybrid incompatibility and their effects on disease resistance.

PubMed

Atanasov, Kostadin Evgeniev; Liu, Changxin; Erban, Alexander; Kopka, Joachim; Parker, Jane E; Alcázar, Rubén

2018-05-23

Genetic divergence between populations can lead to reproductive isolation. Hybrid incompatibilities (HI) represent intermediate points along a continuum towards speciation. In plants, genetic variation in disease resistance (R) genes underlies several cases of HI. The progeny of a cross between Arabidopsis (Arabidopsis thaliana) accessions Landsberg (Ler, Poland) and Kashmir-2 (Kas-2, central Asia) exhibits immune-related HI. This incompatibility is due to a genetic interaction between a cluster of eight TNL (TOLL/INTERLEUKIN1 RECEPTOR- NUCLEOTIDE BINDING - LEUCINE RICH REPEAT) RPP1 (RECOGNITION OF PERONOSPORA PARASITICA 1)- like genes (R1- R8) from Ler and central Asian alleles of a Strubbelig-family receptor-like kinase (SRF3) from Kas-2. In characterizing mutants altered in Ler/Kas-2 HI, we mapped multiple mutations to the RPP1-like Ler locus. Analysis of these suppressor of Ler/Kas-2 incompatibility (sulki) mutants reveals complex, additive and epistatic interactions underlying RPP1-like Ler locus activity. The effects of these mutations were measured on basal defense, global gene expression, primary metabolism, and disease resistance to a local Hyaloperonospora arabidopsidis isolate (Hpa Gw) collected from Gorzów (Gw), where the Landsberg accession originated. Gene expression sectors and metabolic hallmarks identified for HI are both dependent and independent of RPP1-like Ler members. We establish that mutations suppressing immune-related Ler/Kas-2 HI do not compromise resistance to Hpa Gw. QTL mapping analysis of Hpa Gw resistance point to RPP7 as the causal locus. This work provides insight into the complex genetic architecture of the RPP1-like Ler locus and immune-related HI in Arabidopsis and into the contributions of RPP1-like genes to HI and defense. {copyright, serif} 2018 American Society of Plant Biologists. All rights reserved.

Diversity in Genetic In Vivo Methods for Protein-Protein Interaction Studies: from the Yeast Two-Hybrid System to the Mammalian Split-Luciferase System

PubMed Central

Stynen, Bram; Tournu, Hélène; Tavernier, Jan

2012-01-01

Summary: The yeast two-hybrid system pioneered the field of in vivo protein-protein interaction methods and undisputedly gave rise to a palette of ingenious techniques that are constantly pushing further the limits of the original method. Sensitivity and selectivity have improved because of various technical tricks and experimental designs. Here we present an exhaustive overview of the genetic approaches available to study in vivo binary protein interactions, based on two-hybrid and protein fragment complementation assays. These methods have been engineered and employed successfully in microorganisms such as Saccharomyces cerevisiae and Escherichia coli, but also in higher eukaryotes. From single binary pairwise interactions to whole-genome interactome mapping, the self-reassembly concept has been employed widely. Innovative studies report the use of proteins such as ubiquitin, dihydrofolate reductase, and adenylate cyclase as reconstituted reporters. Protein fragment complementation assays have extended the possibilities in protein-protein interaction studies, with technologies that enable spatial and temporal analyses of protein complexes. In addition, one-hybrid and three-hybrid systems have broadened the types of interactions that can be studied and the findings that can be obtained. Applications of these technologies are discussed, together with the advantages and limitations of the available assays. PMID:22688816

Whirlin and PDZ domain-containing 7 (PDZD7) proteins are both required to form the quaternary protein complex associated with Usher syndrome type 2.

PubMed

Chen, Qian; Zou, Junhuang; Shen, Zuolian; Zhang, Weiping; Yang, Jun

2014-12-26

Usher syndrome (USH) is the leading genetic cause of combined hearing and vision loss. Among the three USH clinical types, type 2 (USH2) occurs most commonly. USH2A, GPR98, and WHRN are three known causative genes of USH2, whereas PDZD7 is a modifier gene found in USH2 patients. The proteins encoded by these four USH genes have been proposed to form a multiprotein complex, the USH2 complex, due to interactions found among some of these proteins in vitro, their colocalization in vivo, and mutual dependence of some of these proteins for their normal in vivo localizations. However, evidence showing the formation of the USH2 complex is missing, and details on how this complex is formed remain elusive. Here, we systematically investigated interactions among the intracellular regions of the four USH proteins using colocalization, yeast two-hybrid, and pull-down assays. We show that multiple domains of the four USH proteins interact among one another. Importantly, both WHRN and PDZD7 are required for the complex formation with USH2A and GPR98. In this USH2 quaternary complex, WHRN prefers to bind to USH2A, whereas PDZD7 prefers to bind to GPR98. Interaction between WHRN and PDZD7 is the bridge between USH2A and GPR98. Additionally, the USH2 quaternary complex has a variable stoichiometry. These findings suggest that a non-obligate, short term, and dynamic USH2 quaternary protein complex may exist in vivo. Our work provides valuable insight into the physiological role of the USH2 complex in vivo and informs possible reconstruction of the USH2 complex for future therapy. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

Evolution of complex adaptations in molecular systems

PubMed Central

Pál, Csaba; Papp, Balázs

2017-01-01

A central challenge in evolutionary biology concerns the mechanisms by which complex adaptations arise. Such adaptations depend on the fixation of multiple, highly specific mutations, where intermediate stages of evolution seemingly provide little or no benefit. It is generally assumed that the establishment of complex adaptations is very slow in nature, as evolution of such traits demands special population genetic or environmental circumstances. However, blueprints of complex adaptations in molecular systems are pervasive, indicating that they can readily evolve. We discuss the prospects and limitations of non-adaptive scenarios, which assume multiple neutral or deleterious steps in the evolution of complex adaptations. Next, we examine how complex adaptations can evolve by natural selection in changing environment. Finally, we argue that molecular ’springboards’, such as phenotypic heterogeneity and promiscuous interactions facilitate this process by providing access to new adaptive paths. PMID:28782044

Connecting the dots between genes, biochemistry, and disease susceptibility: systems biology modeling in human genetics.

PubMed

Moore, Jason H; Boczko, Erik M; Summar, Marshall L

2005-02-01

Understanding how DNA sequence variations impact human health through a hierarchy of biochemical and physiological systems is expected to improve the diagnosis, prevention, and treatment of common, complex human diseases. We have previously developed a hierarchical dynamic systems approach based on Petri nets for generating biochemical network models that are consistent with genetic models of disease susceptibility. This modeling approach uses an evolutionary computation approach called grammatical evolution as a search strategy for optimal Petri net models. We have previously demonstrated that this approach routinely identifies biochemical network models that are consistent with a variety of genetic models in which disease susceptibility is determined by nonlinear interactions between two or more DNA sequence variations. We review here this approach and then discuss how it can be used to model biochemical and metabolic data in the context of genetic studies of human disease susceptibility.

Physiological breeding.

PubMed

Reynolds, Matthew; Langridge, Peter

2016-06-01

Physiological breeding crosses parents with different complex but complementary traits to achieve cumulative gene action for yield, while selecting progeny using remote sensing, possibly in combination with genomic selection. Physiological approaches have already demonstrated significant genetic gains in Australia and several developing countries of the International Wheat Improvement Network. The techniques involved (see Graphical Abstract) also provide platforms for research and refinement of breeding methodologies. Recent examples of these include screening genetic resources for novel expression of Calvin cycle enzymes, identification of common genetic bases for heat and drought adaptation, and genetic dissection of trade-offs among yield components. Such information, combined with results from physiological crosses designed to test novel trait combinations, lead to more precise breeding strategies, and feed models of genotype-by-environment interaction to help build new plant types and experimental environments for future climates. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Genetics of schizophrenia in the context of integrative psychiatry.

PubMed

Sagud, Marina; Mihaljević-Peles, Alma; Pivac, Nela; Muck-Seler, Dorotea; Simunović, Ivona; Jakovljević, Miro

2008-09-01

Epidemiological studies suggest a strong heritability in schizophrenia. Positive family history is the greatest risk factor for developing schizophrenia. However, regarding the genetic factors in schizophrenia, there is a lot of the inconsistency (i.e. non-replication) in the literature of the associations of different genes with schizophrenia. The presence of a single gene is neither sufficient, nor necessary to cause schizophrenia. The understanding of the genetic basis of schizophrenia is complex. Besides different gene polymorphisms, numerous environmental factors, interacting with genes, contribute to susceptibility to schizophrenia. Such factors include the use of street drugs, childhood head injury, maternal infection during pregnancy, paternal age at conception, stressful life events and urban upbringing. While knowing genetic risks, integrative psychiatry may have a role in reducing other modifiable risk factors, including reduction of stress level, stress management strategies, family consultation/education, education against street drugs use, treatment of prodromal symptoms and development of social skills.

Exome sequence analysis suggests genetic burden contributes to phenotypic variability and complex neuropathy

PubMed Central

Gonzaga-Jauregui, Claudia; Harel, Tamar; Gambin, Tomasz; Kousi, Maria; Griffin, Laurie B.; Francescatto, Ludmila; Ozes, Burcak; Karaca, Ender; Jhangiani, Shalini; Bainbridge, Matthew N.; Lawson, Kim S.; Pehlivan, Davut; Okamoto, Yuji; Withers, Marjorie; Mancias, Pedro; Slavotinek, Anne; Reitnauer, Pamela J; Goksungur, Meryem T.; Shy, Michael; Crawford, Thomas O.; Koenig, Michel; Willer, Jason; Flores, Brittany N.; Pediaditrakis, Igor; Us, Onder; Wiszniewski, Wojciech; Parman, Yesim; Antonellis, Anthony; Muzny, Donna M.; Katsanis, Nicholas; Battaloglu, Esra; Boerwinkle, Eric; Gibbs, Richard A.; Lupski, James R.

2015-01-01

Charcot-Marie-Tooth (CMT) disease is a clinically and genetically heterogeneous distal symmetric polyneuropathy. Whole-exome sequencing (WES) of 40 individuals from 37 unrelated families with CMT-like peripheral neuropathy refractory to molecular diagnosis identified apparent causal mutations in ~45% (17/37) of families. Three candidate disease genes are proposed, supported by a combination of genetic and in vivo studies. Aggregate analysis of mutation data revealed a significantly increased number of rare variants across 58 neuropathy associated genes in subjects versus controls; confirmed in a second ethnically discrete neuropathy cohort, suggesting mutation burden potentially contributes to phenotypic variability. Neuropathy genes shown to have highly penetrant Mendelizing variants (HMPVs) and implicated by burden in families were shown to interact genetically in a zebrafish assay exacerbating the phenotype established by the suppression of single genes. Our findings suggest that the combinatorial effect of rare variants contributes to disease burden and variable expressivity. PMID:26257172

Breaking barriers in the genomics and pharmacogenetics of drug addiction

PubMed Central

Ho, MK; Goldman, D; Heinz, A; Kaprio, J; Kreek, MJ; Li, MD; Munafò, MR; Tyndale, RF

2013-01-01

Drug addictions remain a substantial health issue, with limited treatment options currently available. Despite considerable advances in the understanding of our genetic architecture, the genetic underpinning of complex disorders remains elusive. Numerous candidate genes have been implicated in the etiology and response to treatment for different addictions based on our current understanding of the neurobiology. Genome-wide association studies have also provided novel targets. However, replication of these studies is often lacking which complicates interpretation; this will improve as issues such as phenotypic characterization, the apparent “missing heritability”, the identification of functional variants, and possible gene-environment interactions are addressed. In addition, there is growing evidence that genetic information can be useful for refining the choice of addiction treatment. As genetic testing becomes more common in the practice of medicine, a variety of ethical and practical challenges, some of which are unique to drug addiction, will also need to be considered. PMID:20981002

Host Genetic and Environmental Effects on Mouse Cecum Microbiota

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campbell, James H; Foster, Carmen M; Vishnivetskaya, Tatiana A

2012-01-01

The mammalian gut harbors complex and variable microbial communities, across both host phylogenetic space and conspecific individuals. A synergy of host genetic and environmental factors shape these communities and account for their variability, but their individual contributions and the selective pressures involved are still not well understood. We employed barcoded pyrosequencing of V1-2 and V4 regions of bacterial small subunit ribosomal RNA genes to characterize the effects of host genetics and environment on cecum assemblages in 10 genetically distinct, inbred mouse strains. Eight of these strains are the foundation of the Collaborative Cross (CC), a panel of mice derived frommore » a genetically diverse set of inbred founder strains, designed specifically for complex trait analysis. Diversity of gut microbiota was characterized by complementing phylogenetic and distance-based, sequence-clustering approaches. Significant correlations were found between the mouse strains and their gut microbiota, reflected by distinct bacterial communities. Cohabitation and litter had a reduced, although detectable effect, and the microbiota response to these factors varied by strain. We identified bacterial phylotypes that appear to be discriminative and strain-specific to each mouse line used. Cohabitation of different strains of mice revealed an interaction of host genetic and environmental factors in shaping gut bacterial consortia, in which bacterial communities became more similar but retained strain specificity. This study provides a baseline analysis of intestinal bacterial communities in the eight CC progenitor strains and will be linked to integrated host genotype, phenotype and microbiota research on the resulting CC panel.« less

Genetic control of floral zygomorphy in pea (Pisum sativum L.).

PubMed

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.

Mouse Models for Investigating the Developmental Bases of Human Birth Defects

PubMed Central

MOON, ANNE M.

2006-01-01

Clinicians and basic scientists share an interest in discovering how genetic or environmental factors interact to perturb normal development and cause birth defects and human disease. Given the complexity of such interactions, it is not surprising that 4% of human infants are born with a congenital malformation, and cardiovascular defects occur in nearly 1%. Our research is based on the fundamental hypothesis that an understanding of normal and abnormal development will permit us to generate effective strategies for both prevention and treatment of human birth defects. Animal models are invaluable in these efforts because they allow one to interrogate the genetic, molecular and cellular events that distinguish normal from abnormal development. Several features of the mouse make it a particularly powerful experimental model: it is a mammalian system with similar embryology, anatomy and physiology to humans; genes, proteins and regulatory programs are largely conserved between human and mouse; and finally, gene targeting in murine embryonic stem cells has made the mouse genome amenable to sophisticated genetic manipulation currently unavailable in any other model organism. PMID:16641221

Petri net modeling of high-order genetic systems using grammatical evolution.

PubMed

Moore, Jason H; Hahn, Lance W

2003-11-01

Understanding how DNA sequence variations impact human health through a hierarchy of biochemical and physiological systems is expected to improve the diagnosis, prevention, and treatment of common, complex human diseases. We have previously developed a hierarchical dynamic systems approach based on Petri nets for generating biochemical network models that are consistent with genetic models of disease susceptibility. This modeling approach uses an evolutionary computation approach called grammatical evolution as a search strategy for optimal Petri net models. We have previously demonstrated that this approach routinely identifies biochemical network models that are consistent with a variety of genetic models in which disease susceptibility is determined by nonlinear interactions between two DNA sequence variations. In the present study, we evaluate whether the Petri net approach is capable of identifying biochemical networks that are consistent with disease susceptibility due to higher order nonlinear interactions between three DNA sequence variations. The results indicate that our model-building approach is capable of routinely identifying good, but not perfect, Petri net models. Ideas for improving the algorithm for this high-dimensional problem are presented.

Multi-omics analysis of inflammatory bowel disease.

PubMed

Huang, Hu; Vangay, Pajau; McKinlay, Christopher E; Knights, Dan

2014-12-01

Crohn's disease and ulcerative colitis, known together as inflammatory bowel disease (IBD), are severe autoimmune disorders now causing gut inflammation and ulceration, among other symptoms, in up to 1 in 250 people worldwide. Incidence and prevalence of IBD have been increasing dramatically over the past several decades, although the causes for this increase are still unknown. IBD has both a complex genotype and a complex phenotype, and although it has received substantial attention from the medical research community over recent years, much of the etiology remains unexplained. Genome-wide association studies have identified a rich genetic signature of disease risk in patients with IBD, consisting of at least 163 genetic loci. Many of these loci contain genes directly involved in microbial handling, indicating that the genetic architecture of the disease has been driven by host-microbe interactions. In addition, systematic shifts in gut microbiome structure (enterotype) and function have been observed in patients with IBD. Furthermore, both the host genotype and enterotype are associated with aspects of the disease phenotype, including location of the disease. This provides strong evidence of interactions between host genotype and enterotype; however, there is a lack of published multi-omics data from IBD patients, and a lack of bioinformatics tools for modeling such systems. In this article we discuss, from a computational biologist's point of view, the potential benefits of and the challenges involved in designing and analyzing such multi-omics studies of IBD. Copyright © 2014 Elsevier B.V. All rights reserved.

Analyses of Dynein Heavy Chain Mutations Reveal Complex Interactions Between Dynein Motor Domains and Cellular Dynein Functions

PubMed Central

Sivagurunathan, Senthilkumar; Schnittker, Robert R.; Razafsky, David S.; Nandini, Swaran; Plamann, Michael D.; King, Stephen J.

2012-01-01

Cytoplasmic dynein transports cargoes for a variety of crucial cellular functions. However, since dynein is essential in most eukaryotic organisms, the in-depth study of the cellular function of dynein via genetic analysis of dynein mutations has not been practical. Here, we identify and characterize 34 different dynein heavy chain mutations using a genetic screen of the ascomycete fungus Neurospora crassa, in which dynein is nonessential. Interestingly, our studies show that these mutations segregate into five different classes based on the in vivo localization of the mutated dynein motors. Furthermore, we have determined that the different classes of dynein mutations alter vesicle trafficking, microtubule organization, and nuclear distribution in distinct ways and require dynactin to different extents. In addition, biochemical analyses of dynein from one mutant strain show a strong correlation between its in vitro biochemical properties and the aberrant intracellular function of that altered dynein. When the mutations were mapped to the published dynein crystal structure, we found that the three-dimensional structural locations of the heavy chain mutations were linked to particular classes of altered dynein functions observed in cells. Together, our data indicate that the five classes of dynein mutations represent the entrapment of dynein at five separate points in the dynein mechanochemical and transport cycles. We have developed N. crassa as a model system where we can dissect the complexities of dynein structure, function, and interaction with other proteins with genetic, biochemical, and cell biological studies. PMID:22649085

The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases.

PubMed

Heidema, A Geert; Boer, Jolanda M A; Nagelkerke, Nico; Mariman, Edwin C M; van der A, Daphne L; Feskens, Edith J M

2006-04-21

Genetic epidemiologists have taken the challenge to identify genetic polymorphisms involved in the development of diseases. Many have collected data on large numbers of genetic markers but are not familiar with available methods to assess their association with complex diseases. Statistical methods have been developed for analyzing the relation between large numbers of genetic and environmental predictors to disease or disease-related variables in genetic association studies. In this commentary we discuss logistic regression analysis, neural networks, including the parameter decreasing method (PDM) and genetic programming optimized neural networks (GPNN) and several non-parametric methods, which include the set association approach, combinatorial partitioning method (CPM), restricted partitioning method (RPM), multifactor dimensionality reduction (MDR) method and the random forests approach. The relative strengths and weaknesses of these methods are highlighted. Logistic regression and neural networks can handle only a limited number of predictor variables, depending on the number of observations in the dataset. Therefore, they are less useful than the non-parametric methods to approach association studies with large numbers of predictor variables. GPNN on the other hand may be a useful approach to select and model important predictors, but its performance to select the important effects in the presence of large numbers of predictors needs to be examined. Both the set association approach and random forests approach are able to handle a large number of predictors and are useful in reducing these predictors to a subset of predictors with an important contribution to disease. The combinatorial methods give more insight in combination patterns for sets of genetic and/or environmental predictor variables that may be related to the outcome variable. As the non-parametric methods have different strengths and weaknesses we conclude that to approach genetic association studies using the case-control design, the application of a combination of several methods, including the set association approach, MDR and the random forests approach, will likely be a useful strategy to find the important genes and interaction patterns involved in complex diseases.

A Hypothesis for Using Pathway Genetic Load Analysis for Understanding Complex Outcomes in Bilirubin Encephalopathy

PubMed Central

Riordan, Sean M.; Bittel, Douglas C.; Le Pichon, Jean-Baptiste; Gazzin, Silvia; Tiribelli, Claudio; Watchko, Jon F.; Wennberg, Richard P.; Shapiro, Steven M.

2016-01-01

Genetic-based susceptibility to bilirubin neurotoxicity and chronic bilirubin encephalopathy (kernicterus) is still poorly understood. Neonatal jaundice affects 60–80% of newborns, and considerable effort goes into preventing this relatively benign condition from escalating into the development of kernicterus making the incidence of this potentially devastating condition very rare in more developed countries. The current understanding of the genetic background of kernicterus is largely comprised of mutations related to alterations of bilirubin production, elimination, or both. Less is known about mutations that may predispose or protect against CNS bilirubin neurotoxicity. The lack of a monogenetic source for this risk of bilirubin neurotoxicity suggests that disease progression is dependent upon an overall decrease in the functionality of one or more essential genetically controlled metabolic pathways. In other words, a “load” is placed on key pathways in the form of multiple genetic variants that combine to create a vulnerable phenotype. The idea of epistatic interactions creating a pathway genetic load (PGL) that affects the response to a specific insult has been previously reported as a PGL score. We hypothesize that the PGL score can be used to investigate whether increased susceptibility to bilirubin-induced CNS damage in neonates is due to a mutational load being placed on key genetic pathways important to the central nervous system's response to bilirubin neurotoxicity. We propose a modification of the PGL score method that replaces the use of a canonical pathway with custom gene lists organized into three tiers with descending levels of evidence combined with the utilization of single nucleotide polymorphism (SNP) causality prediction methods. The PGL score has the potential to explain the genetic background of complex bilirubin induced neurological disorders (BIND) such as kernicterus and could be the key to understanding ranges of outcome severity in complex diseases. We anticipate that this method could be useful for improving the care of jaundiced newborns through its use as an at-risk screen. Importantly, this method would also be useful in uncovering basic knowledge about this and other polygenetic diseases whose genetic source is difficult to discern through traditional means such as a genome-wide association study. PMID:27587993

Caenorhabditis elegans ABCRNAi transporters interact genetically with rde-2 and mut-7.

PubMed

Sundaram, Prema; Han, Wang; Cohen, Nancy; Echalier, Benjamin; Albin, John; Timmons, Lisa

2008-02-01

RNA interference (RNAi) mechanisms are conserved and consist of an interrelated network of activities that not only respond to exogenous dsRNA, but also perform endogenous functions required in the fine tuning of gene expression and in maintaining genome integrity. Not surprisingly, RNAi functions have widespread influences on cellular function and organismal development. Previously, we observed a reduced capacity to mount an RNAi response in nine Caenorhabditis elegans mutants that are defective in ABC transporter genes (ABC(RNAi) mutants). Here, we report an exhaustive study of mutants, collectively defective in 49 different ABC transporter genes, that allowed for the categorization of one additional transporter into the ABC(RNAi) gene class. Genetic complementation tests reveal functions for ABC(RNAi) transporters in the mut-7/rde-2 branch of the RNAi pathway. These second-site noncomplementation interactions suggest that ABC(RNAi) proteins and MUT-7/RDE-2 function together in parallel pathways and/or as multiprotein complexes. Like mut-7 and rde-2, some ABC(RNAi) mutants display transposon silencing defects. Finally, our analyses reveal a genetic interaction network of ABC(RNAi) gene function with respect to this part of the RNAi pathway. From our results, we speculate that the coordinated activities of ABC(RNAi) transporters, through their effects on endogenous RNAi-related mechanisms, ultimately affect chromosome function and integrity.

Caenorhabditis elegans ABCRNAi Transporters Interact Genetically With rde-2 and mut-7

PubMed Central

Sundaram, Prema; Han, Wang; Cohen, Nancy; Echalier, Benjamin; Albin, John; Timmons, Lisa

2008-01-01

RNA interference (RNAi) mechanisms are conserved and consist of an interrelated network of activities that not only respond to exogenous dsRNA, but also perform endogenous functions required in the fine tuning of gene expression and in maintaining genome integrity. Not surprisingly, RNAi functions have widespread influences on cellular function and organismal development. Previously, we observed a reduced capacity to mount an RNAi response in nine Caenorhabditis elegans mutants that are defective in ABC transporter genes (ABCRNAi mutants). Here, we report an exhaustive study of mutants, collectively defective in 49 different ABC transporter genes, that allowed for the categorization of one additional transporter into the ABCRNAi gene class. Genetic complementation tests reveal functions for ABCRNAi transporters in the mut-7/rde-2 branch of the RNAi pathway. These second-site noncomplementation interactions suggest that ABCRNAi proteins and MUT-7/RDE-2 function together in parallel pathways and/or as multiprotein complexes. Like mut-7 and rde-2, some ABCRNAi mutants display transposon silencing defects. Finally, our analyses reveal a genetic interaction network of ABCRNAi gene function with respect to this part of the RNAi pathway. From our results, we speculate that the coordinated activities of ABCRNAi transporters, through their effects on endogenous RNAi-related mechanisms, ultimately affect chromosome function and integrity. PMID:18245353

Genetic determinants of drug responsiveness and drug interactions.

PubMed

Caraco, Y

1998-10-01

Six cytochrome P450 enzymes mediate the oxidative metabolism of most drugs in common use: CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4. These enzymes have selective substrate specificity, and their activity is characterized by marked interindividual variation. Some of these systems (CYP2C19, CYP2D6) are polymorphically distributed; thus, a subset of the population may be genetically deficient in enzyme activity. Phenotyping procedures designed to identify subjects with impaired metabolism who may be at increased risk for drug toxicity have been developed and validated. This has been supplemented in recent years by the availability of genetic analysis and the identification of specific alleles that are associated with altered (i.e., reduced, deficient, or increased) enzyme activity. The potential of genotyping to predict pharmacodynamics holds great promise for the future because it does not involve the administration of exogenous compound and is not confounded by drug therapy. Drug interactions caused by the inhibition or induction of oxidative drug metabolism may be of great clinical importance because they may result in drug toxicity or therapeutic failure. Further understanding of cytochrome P450 complexity may allow, through a combined in vitro-in vivo approach, the reliable prediction and possible prevention of deleterious drug interactions.

Hepatitis A virus: host interactions, molecular epidemiology and evolution.

PubMed

Vaughan, Gilberto; Goncalves Rossi, Livia Maria; Forbi, Joseph C; de Paula, Vanessa S; Purdy, Michael A; Xia, Guoliang; Khudyakov, Yury E

2014-01-01

Infection with hepatitis A virus (HAV) is the commonest viral cause of liver disease and presents an important public health problem worldwide. Several unique HAV properties and molecular mechanisms of its interaction with host were recently discovered and should aid in clarifying the pathogenesis of hepatitis A. Genetic characterization of HAV strains have resulted in the identification of different genotypes and subtypes, which exhibit a characteristic worldwide distribution. Shifts in HAV endemicity occurring in different parts of the world, introduction of genetically diverse strains from geographically distant regions, genotype displacement observed in some countries and population expansion detected in the last decades of the 20th century using phylogenetic analysis are important factors contributing to the complex dynamics of HAV infections worldwide. Strong selection pressures, some of which, like usage of deoptimized codons, are unique to HAV, limit genetic variability of the virus. Analysis of subgenomic regions has been proven useful for outbreak investigations. However, sharing short sequences among epidemiologically unrelated strains indicates that specific identification of HAV strains for molecular surveillance can be achieved only using whole-genome sequences. Here, we present up-to-date information on the HAV molecular epidemiology and evolution, and highlight the most relevant features of the HAV-host interactions. Published by Elsevier B.V.

Kernel-based whole-genome prediction of complex traits: a review.

PubMed

Morota, Gota; Gianola, Daniel

2014-01-01

Prediction of genetic values has been a focus of applied quantitative genetics since the beginning of the 20th century, with renewed interest following the advent of the era of whole genome-enabled prediction. Opportunities offered by the emergence of high-dimensional genomic data fueled by post-Sanger sequencing technologies, especially molecular markers, have driven researchers to extend Ronald Fisher and Sewall Wright's models to confront new challenges. In particular, kernel methods are gaining consideration as a regression method of choice for genome-enabled prediction. Complex traits are presumably influenced by many genomic regions working in concert with others (clearly so when considering pathways), thus generating interactions. Motivated by this view, a growing number of statistical approaches based on kernels attempt to capture non-additive effects, either parametrically or non-parametrically. This review centers on whole-genome regression using kernel methods applied to a wide range of quantitative traits of agricultural importance in animals and plants. We discuss various kernel-based approaches tailored to capturing total genetic variation, with the aim of arriving at an enhanced predictive performance in the light of available genome annotation information. Connections between prediction machines born in animal breeding, statistics, and machine learning are revisited, and their empirical prediction performance is discussed. Overall, while some encouraging results have been obtained with non-parametric kernels, recovering non-additive genetic variation in a validation dataset remains a challenge in quantitative genetics.

The Genetic Architecture of Noise-Induced Hearing Loss: Evidence for a Gene-by-Environment Interaction.

PubMed

Lavinsky, Joel; Ge, Marshall; Crow, Amanda L; Pan, Calvin; Wang, Juemei; Salehi, Pezhman; Myint, Anthony; Eskin, Eleazar; Allayee, Hooman; Lusis, Aldons J; Friedman, Rick A

2016-10-13

The discovery of environmentally specific genetic effects is crucial to the understanding of complex traits, such as susceptibility to noise-induced hearing loss (NIHL). We describe the first genome-wide association study (GWAS) for NIHL in a large and well-characterized population of inbred mouse strains, known as the Hybrid Mouse Diversity Panel (HMDP). We recorded auditory brainstem response (ABR) thresholds both pre and post 2-hr exposure to 10-kHz octave band noise at 108 dB sound pressure level in 5-6-wk-old female mice from the HMDP (4-5 mice/strain). From the observation that NIHL susceptibility varied among the strains, we performed a GWAS with correction for population structure and mapped a locus on chromosome 6 that was statistically significantly associated with two adjacent frequencies. We then used a "genetical genomics" approach that included the analysis of cochlear eQTLs to identify candidate genes within the GWAS QTL. In order to validate the gene-by-environment interaction, we compared the effects of the postnoise exposure locus with that from the same unexposed strains. The most significant SNP at chromosome 6 (rs37517079) was associated with noise susceptibility, but was not significant at the same frequencies in our unexposed study. These findings demonstrate that the genetic architecture of NIHL is distinct from that of unexposed hearing levels and provide strong evidence for gene-by-environment interactions in NIHL. Copyright © 2016 Lavinsky et al.

Analysis of the trap gene provides evidence for the role of elevation and vector abundance in the genetic diversity of Plasmodium relictum in Hawaii

USGS Publications Warehouse

Farias, Margaret E.M.; Atkinson, Carter T.; LaPointe, Dennis A.; Jarvi, Susan I.

2012-01-01

Background: The avian disease system in Hawaii offers an ideal opportunity to investigate host-pathogen interactions in a natural setting. Previous studies have recognized only a single mitochondrial lineage of avian malaria (Plasmodium relictum) in the Hawaiian Islands, but cloning and sequencing of nuclear genes suggest a higher degree of genetic diversity. Methods: In order to evaluate genetic diversity of P. relictum at the population level and further understand host-parasite interactions, a modified single-base extension (SBE) method was used to explore spatial and temporal distribution patterns of single nucleotide polymorphisms (SNPs) in the thrombospondin-related anonymous protein (trap) gene of P. relictum infections from 121 hatch-year amakihi (Hemignathus virens) on the east side of Hawaii Island. Results: Rare alleles and mixed infections were documented at three of eight SNP loci; this is the first documentation of genetically diverse infections of P. relictum at the population level in Hawaii. Logistic regression revealed that the likelihood of infection with a rare allele increased at low-elevation, but decreased as mosquito capture rates increased. The inverse relationship between vector capture rates and probability of infection with a rare allele is unexpected given current theories of epidemiology developed in human malarias. Conclusions: The results of this study suggest that pathogen diversity in Hawaii may be driven by a complex interaction of factors including transmission rates, host immune pressures, and parasite-parasite competition.

Analysis of the trap gene provides evidence for the role of elevation and vector abundance in the genetic diversity of Plasmodium relictum in Hawaii

PubMed Central

2012-01-01

Background The avian disease system in Hawaii offers an ideal opportunity to investigate host-pathogen interactions in a natural setting. Previous studies have recognized only a single mitochondrial lineage of avian malaria (Plasmodium relictum) in the Hawaiian Islands, but cloning and sequencing of nuclear genes suggest a higher degree of genetic diversity. Methods In order to evaluate genetic diversity of P. relictum at the population level and further understand host-parasite interactions, a modified single-base extension (SBE) method was used to explore spatial and temporal distribution patterns of single nucleotide polymorphisms (SNPs) in the thrombospondin-related anonymous protein (trap) gene of P. relictum infections from 121 hatch-year amakihi (Hemignathus virens) on the east side of Hawaii Island. Results Rare alleles and mixed infections were documented at three of eight SNP loci; this is the first documentation of genetically diverse infections of P. relictum at the population level in Hawaii. Logistic regression revealed that the likelihood of infection with a rare allele increased at low-elevation, but decreased as mosquito capture rates increased. The inverse relationship between vector capture rates and probability of infection with a rare allele is unexpected given current theories of epidemiology developed in human malarias. Conclusions The results of this study suggest that pathogen diversity in Hawaii may be driven by a complex interaction of factors including transmission rates, host immune pressures, and parasite-parasite competition. PMID:22943788