Quantitative genetics of age at reproduction in wild swans: Support for antagonistic pleiotropy models of senescence

PubMed Central

Charmantier, Anne; Perrins, Christopher; McCleery, Robin H.; Sheldon, Ben C.

2006-01-01

Why do individuals stop reproducing after a certain age, and how is this age determined? The antagonistic pleiotropy theory for the evolution of senescence predicts that increased early-life performance should be accompanied by earlier (or faster) senescence. Hence, an individual that has started to breed early should also lose its reproductive capacities early. We investigate here the relationship between age at first reproduction (AFR) and age at last reproduction (ALR) in a free-ranging mute swan (Cygnus olor) population monitored for 36 years. Using multivariate analyses on the longitudinal data, we show that both traits are strongly selected in opposite directions. Analysis of the phenotypic covariance between these characters shows that individuals vary in their inherent quality, such that some individuals have earlier AFR and later ALR than expected. Quantitative genetic pedigree analyses show that both traits possess additive genetic variance but also that AFR and ALR are positively genetically correlated. Hence, although both traits display heritable variation and are under opposing directional selection, their evolution is constrained by a strong evolutionary tradeoff. These results are consistent with the theory that increased early-life performance comes with faster senescence because of genetic tradeoffs. PMID:16618935

Harnessing quantitative genetics and genomics for understanding and improving complex traits in crops

USDA-ARS?s Scientific Manuscript database

Classical quantitative genetics aids crop improvement by providing the means to estimate heritability, genetic correlations, and predicted responses to various selection schemes. Genomics has the potential to aid quantitative genetics and applied crop improvement programs via large-scale, high-thro...

Breeding and quantitative genetics advances in sunflower Sclerotinia research

USDA-ARS?s Scientific Manuscript database

Genetic research of the sunflower research unit, USDA-ARS, in Fargo, ND, was discussed in a presentation to a group of producers, industry representatives, and scientists. The need for sunflower quantitative genetics research to find and capture Sclerotinia resistance is increasing with every year t...

Analysis of genetic effects of nuclear-cytoplasmic interaction on quantitative traits: genetic model for diploid plants.

PubMed

Han, Lide; Yang, Jian; Zhu, Jun

2007-06-01

A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.

Quantitative maps of genetic interactions in yeast - comparative evaluation and integrative analysis.

PubMed

Lindén, Rolf O; Eronen, Ville-Pekka; Aittokallio, Tero

2011-03-24

High-throughput genetic screening approaches have enabled systematic means to study how interactions among gene mutations contribute to quantitative fitness phenotypes, with the aim of providing insights into the functional wiring diagrams of genetic interaction networks on a global scale. However, it is poorly known how well these quantitative interaction measurements agree across the screening approaches, which hinders their integrated use toward improving the coverage and quality of the genetic interaction maps in yeast and other organisms. Using large-scale data matrices from epistatic miniarray profiling (E-MAP), genetic interaction mapping (GIM), and synthetic genetic array (SGA) approaches, we carried out here a systematic comparative evaluation among these quantitative maps of genetic interactions in yeast. The relatively low association between the original interaction measurements or their customized scores could be improved using a matrix-based modelling framework, which enables the use of single- and double-mutant fitness estimates and measurements, respectively, when scoring genetic interactions. Toward an integrative analysis, we show how the detections from the different screening approaches can be combined to suggest novel positive and negative interactions which are complementary to those obtained using any single screening approach alone. The matrix approximation procedure has been made available to support the design and analysis of the future screening studies. We have shown here that even if the correlation between the currently available quantitative genetic interaction maps in yeast is relatively low, their comparability can be improved by means of our computational matrix approximation procedure, which will enable integrative analysis and detection of a wider spectrum of genetic interactions using data from the complementary screening approaches.

Quantitative Genetics in the Era of Molecular Genetics: Learning Abilities and Disabilities as an Example

ERIC Educational Resources Information Center

Haworth, Claire M. A.; Plomin, Robert

2010-01-01

Objective: To consider recent findings from quantitative genetic research in the context of molecular genetic research, especially genome-wide association studies. We focus on findings that go beyond merely estimating heritability. We use learning abilities and disabilities as examples. Method: Recent twin research in the area of learning…

QUANTITATIVE GENETIC ACTIVITY GRAPHICAL PROFILES FOR USE IN CHEMICAL EVALUATION

EPA Science Inventory

A graphic approach termed a Genetic Activity Profile (GAP) has been developed to display a matrix of data on the genetic and related effects of selected chemical agents. he profiles provide a visual overview of the quantitative (doses) and qualitative (test results) data for each...

Genetics and Justice: Must One Theory Fit All Contexts?

PubMed

Gunson, Darryl

2018-04-01

Appeals to social justice that argue medicine and healthcare should have certain priorities and not others are common. It is an obvious question to ask: What does social justice demand of the new genetic technologies? However, it is important to note that there are many theories and sub-theories of justice. There are utilitarian theories, libertarian theories, and egalitarian theories. There are so-called luck egalitarians, equality-as-fairness thinkers, and capability theorists, with each having his or her own distinctive approach to the distribution of medical goods and technologies, and to healthcare priorities. This article argues that the discussion surrounding this question is potentially hampered by an implicit assumption that if one theory of justice is applicable in one context, then it must also be applicable in others. Instead, it is proposed that one adopt the stance, influenced by Michael Waltzer, that different theories with their opposing principles may be applicable to different questions regarding justice and genetics. The specific view advanced is that to answer questions about what justice requires regarding the therapeutic and enhancement use of genetic techniques, a method of reflective equilibrium can show how intuitions, in context, may support different theories of justice. When particular pre-theoretic ethical judgments are balanced against the theories that might explain or justify them, and are in accord with what seems emotionally acceptable, then it can be seen how different general theories may be applicable in the different contexts in which questions of justice and genetics arise.

Question 6: coevolution theory of the genetic code: a proven theory.

PubMed

Wong, Jeffrey Tze-Fei

2007-10-01

The coevolution theory proposes that primordial proteins consisted only of those amino acids readily obtainable from the prebiotic environment, representing about half the twenty encoded amino acids of today, and the missing amino acids entered the system as the code expanded along with pathways of amino acid biosynthesis. The isolation of genetic code mutants, and the antiquity of pretran synthesis revealed by the comparative genomics of tRNAs and aminoacyl-tRNA synthetases, have combined to provide a rigorous proof of the four fundamental tenets of the theory, thus solving the riddle of the structure of the universal genetic code.

Genetic toxicology at the crossroads-from qualitative hazard evaluation to quantitative risk assessment.

PubMed

White, Paul A; Johnson, George E

2016-05-01

Applied genetic toxicology is undergoing a transition from qualitative hazard identification to quantitative dose-response analysis and risk assessment. To facilitate this change, the Health and Environmental Sciences Institute (HESI) Genetic Toxicology Technical Committee (GTTC) sponsored a workshop held in Lancaster, UK on July 10-11, 2014. The event included invited speakers from several institutions and the contents was divided into three themes-1: Point-of-departure Metrics for Quantitative Dose-Response Analysis in Genetic Toxicology; 2: Measurement and Estimation of Exposures for Better Extrapolation to Humans and 3: The Use of Quantitative Approaches in Genetic Toxicology for human health risk assessment (HHRA). A host of pertinent issues were discussed relating to the use of in vitro and in vivo dose-response data, the development of methods for in vitro to in vivo extrapolation and approaches to use in vivo dose-response data to determine human exposure limits for regulatory evaluations and decision-making. This Special Issue, which was inspired by the workshop, contains a series of papers that collectively address topics related to the aforementioned themes. The Issue includes contributions that collectively evaluate, describe and discuss in silico, in vitro, in vivo and statistical approaches that are facilitating the shift from qualitative hazard evaluation to quantitative risk assessment. The use and application of the benchmark dose approach was a central theme in many of the workshop presentations and discussions, and the Special Issue includes several contributions that outline novel applications for the analysis and interpretation of genetic toxicity data. Although the contents of the Special Issue constitutes an important step towards the adoption of quantitative methods for regulatory assessment of genetic toxicity, formal acceptance of quantitative methods for HHRA and regulatory decision-making will require consensus regarding the

Genetic Architectures of Quantitative Variation in RNA Editing Pathways

PubMed Central

Gu, Tongjun; Gatti, Daniel M.; Srivastava, Anuj; Snyder, Elizabeth M.; Raghupathy, Narayanan; Simecek, Petr; Svenson, Karen L.; Dotu, Ivan; Chuang, Jeffrey H.; Keller, Mark P.; Attie, Alan D.; Braun, Robert E.; Churchill, Gary A.

2016-01-01

RNA editing refers to post-transcriptional processes that alter the base sequence of RNA. Recently, hundreds of new RNA editing targets have been reported. However, the mechanisms that determine the specificity and degree of editing are not well understood. We examined quantitative variation of site-specific editing in a genetically diverse multiparent population, Diversity Outbred mice, and mapped polymorphic loci that alter editing ratios globally for C-to-U editing and at specific sites for A-to-I editing. An allelic series in the C-to-U editing enzyme Apobec1 influences the editing efficiency of Apob and 58 additional C-to-U editing targets. We identified 49 A-to-I editing sites with polymorphisms in the edited transcript that alter editing efficiency. In contrast to the shared genetic control of C-to-U editing, most of the variable A-to-I editing sites were determined by local nucleotide polymorphisms in proximity to the editing site in the RNA secondary structure. Our results indicate that RNA editing is a quantitative trait subject to genetic variation and that evolutionary constraints have given rise to distinct genetic architectures in the two canonical types of RNA editing. PMID:26614740

Modeling development and quantitative trait mapping reveal independent genetic modules for leaf size and shape.

PubMed

Baker, Robert L; Leong, Wen Fung; Brock, Marcus T; Markelz, R J Cody; Covington, Michael F; Devisetty, Upendra K; Edwards, Christine E; Maloof, Julin; Welch, Stephen; Weinig, Cynthia

2015-10-01

Improved predictions of fitness and yield may be obtained by characterizing the genetic controls and environmental dependencies of organismal ontogeny. Elucidating the shape of growth curves may reveal novel genetic controls that single-time-point (STP) analyses do not because, in theory, infinite numbers of growth curves can result in the same final measurement. We measured leaf lengths and widths in Brassica rapa recombinant inbred lines (RILs) throughout ontogeny. We modeled leaf growth and allometry as function valued traits (FVT), and examined genetic correlations between these traits and aspects of phenology, physiology, circadian rhythms and fitness. We used RNA-seq to construct a SNP linkage map and mapped trait quantitative trait loci (QTL). We found genetic trade-offs between leaf size and growth rate FVT and uncovered differences in genotypic and QTL correlations involving FVT vs STPs. We identified leaf shape (allometry) as a genetic module independent of length and width and identified selection on FVT parameters of development. Leaf shape is associated with venation features that affect desiccation resistance. The genetic independence of leaf shape from other leaf traits may therefore enable crop optimization in leaf shape without negative effects on traits such as size, growth rate, duration or gas exchange. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

A nursing theory-guided framework for genetic and epigenetic research.

PubMed

Maki, Katherine A; DeVon, Holli A

2018-04-01

The notion that genetics, through natural selection, determines innate traits has led to much debate and divergence of thought on the impact of innate traits on the human phenotype. The purpose of this synthesis was to examine how innate theory informs genetic research and how understanding innate theory through the lens of Martha Rogers' theory of unitary human beings can offer a contemporary view of how innate traits can inform epigenetic and genetic research. We also propose a new conceptual model for genetic and epigenetic research. The philosophical, theoretical, and research literatures were examined for this synthesis. We have merged philosophical and conceptual phenomena from innate theory with the theory of unitary beings into the University of Illinois at Chicago model for genetic and epigenetic research. Innate traits are the cornerstone of the framework but may be modified epigenetically by biological, physiological, psychological, and social determinants as they are transcribed. These modifiers serve as important links between the concept of innate traits and epigenetic modifications, and, like the theory of unitary human beings, the process is understood in the context of individual and environmental interaction that has the potential to evolve as the determinants change. © 2018 John Wiley & Sons Ltd.

Quantitative genetic methods depending on the nature of the phenotypic trait.

PubMed

de Villemereuil, Pierre

2018-01-24

A consequence of the assumptions of the infinitesimal model, one of the most important theoretical foundations of quantitative genetics, is that phenotypic traits are predicted to be most often normally distributed (so-called Gaussian traits). But phenotypic traits, especially those interesting for evolutionary biology, might be shaped according to very diverse distributions. Here, I show how quantitative genetics tools have been extended to account for a wider diversity of phenotypic traits using first the threshold model and then more recently using generalized linear mixed models. I explore the assumptions behind these models and how they can be used to study the genetics of non-Gaussian complex traits. I also comment on three recent methodological advances in quantitative genetics that widen our ability to study new kinds of traits: the use of "modular" hierarchical modeling (e.g., to study survival in the context of capture-recapture approaches for wild populations); the use of aster models to study a set of traits with conditional relationships (e.g., life-history traits); and, finally, the study of high-dimensional traits, such as gene expression. © 2018 New York Academy of Sciences.

Quantitative genetics of immunity and life history under different photoperiods.

PubMed

Hammerschmidt, K; Deines, P; Wilson, A J; Rolff, J

2012-05-01

Insects with complex life-cycles should optimize age and size at maturity during larval development. When inhabiting seasonal environments, organisms have limited reproductive periods and face fundamental decisions: individuals that reach maturity late in season have to either reproduce at a small size or increase their growth rates. Increasing growth rates is costly in insects because of higher juvenile mortality, decreased adult survival or increased susceptibility to parasitism by bacteria and viruses via compromised immune function. Environmental changes such as seasonality can also alter the quantitative genetic architecture. Here, we explore the quantitative genetics of life history and immunity traits under two experimentally induced seasonal environments in the cricket Gryllus bimaculatus. Seasonality affected the life history but not the immune phenotypes. Individuals under decreasing day length developed slower and grew to a bigger size. We found ample additive genetic variance and heritability for components of immunity (haemocyte densities, proPhenoloxidase activity, resistance against Serratia marcescens), and for the life history traits, age and size at maturity. Despite genetic covariance among traits, the structure of G was inconsistent with genetically based trade-off between life history and immune traits (for example, a strong positive genetic correlation between growth rate and haemocyte density was estimated). However, conditional evolvabilities support the idea that genetic covariance structure limits the capacity of individual traits to evolve independently. We found no evidence for G × E interactions arising from the experimentally induced seasonality.

Detecting Genetic Interactions for Quantitative Traits Using m-Spacing Entropy Measure

PubMed Central

Yee, Jaeyong; Kwon, Min-Seok; Park, Taesung; Park, Mira

2015-01-01

A number of statistical methods for detecting gene-gene interactions have been developed in genetic association studies with binary traits. However, many phenotype measures are intrinsically quantitative and categorizing continuous traits may not always be straightforward and meaningful. Association of gene-gene interactions with an observed distribution of such phenotypes needs to be investigated directly without categorization. Information gain based on entropy measure has previously been successful in identifying genetic associations with binary traits. We extend the usefulness of this information gain by proposing a nonparametric evaluation method of conditional entropy of a quantitative phenotype associated with a given genotype. Hence, the information gain can be obtained for any phenotype distribution. Because any functional form, such as Gaussian, is not assumed for the entire distribution of a trait or a given genotype, this method is expected to be robust enough to be applied to any phenotypic association data. Here, we show its use to successfully identify the main effect, as well as the genetic interactions, associated with a quantitative trait. PMID:26339620

Quantitative genetic tools for insecticide resistance risk assessment: estimating the heritability of resistance

Treesearch

Michael J. Firko; Jane Leslie Hayes

1990-01-01

Quantitative genetic studies of resistance can provide estimates of genetic parameters not available with other types of genetic analyses. Three methods are discussed for estimating the amount of additive genetic variation in resistance to individual insecticides and subsequent estimation of heritability (h2) of resistance. Sibling analysis and...

Quantitative Genetics Identifies Cryptic Genetic Variation Involved in the Paternal Regulation of Seed Development

PubMed Central

Pires, Nuno D.; Bemer, Marian; Müller, Lena M.; Baroux, Célia; Spillane, Charles; Grossniklaus, Ueli

2016-01-01

Embryonic development requires a correct balancing of maternal and paternal genetic information. This balance is mediated by genomic imprinting, an epigenetic mechanism that leads to parent-of-origin-dependent gene expression. The parental conflict (or kinship) theory proposes that imprinting can evolve due to a conflict between maternal and paternal alleles over resource allocation during seed development. One assumption of this theory is that paternal alleles can regulate seed growth; however, paternal effects on seed size are often very low or non-existent. We demonstrate that there is a pool of cryptic genetic variation in the paternal control of Arabidopsis thaliana seed development. Such cryptic variation can be exposed in seeds that maternally inherit a medea mutation, suggesting that MEA acts as a maternal buffer of paternal effects. Genetic mapping using recombinant inbred lines, and a novel method for the mapping of parent-of-origin effects using whole-genome sequencing of segregant bulks, indicate that there are at least six loci with small, paternal effects on seed development. Together, our analyses reveal the existence of a pool of hidden genetic variation on the paternal control of seed development that is likely shaped by parental conflict. PMID:26811909

Quantitative Genetics Identifies Cryptic Genetic Variation Involved in the Paternal Regulation of Seed Development.

PubMed

Pires, Nuno D; Bemer, Marian; Müller, Lena M; Baroux, Célia; Spillane, Charles; Grossniklaus, Ueli

2016-01-01

Embryonic development requires a correct balancing of maternal and paternal genetic information. This balance is mediated by genomic imprinting, an epigenetic mechanism that leads to parent-of-origin-dependent gene expression. The parental conflict (or kinship) theory proposes that imprinting can evolve due to a conflict between maternal and paternal alleles over resource allocation during seed development. One assumption of this theory is that paternal alleles can regulate seed growth; however, paternal effects on seed size are often very low or non-existent. We demonstrate that there is a pool of cryptic genetic variation in the paternal control of Arabidopsis thaliana seed development. Such cryptic variation can be exposed in seeds that maternally inherit a medea mutation, suggesting that MEA acts as a maternal buffer of paternal effects. Genetic mapping using recombinant inbred lines, and a novel method for the mapping of parent-of-origin effects using whole-genome sequencing of segregant bulks, indicate that there are at least six loci with small, paternal effects on seed development. Together, our analyses reveal the existence of a pool of hidden genetic variation on the paternal control of seed development that is likely shaped by parental conflict.

Quantitative theory of diffraction by cylindrical scroll nanotubes.

PubMed

Khadiev, Azat; Khalitov, Zufar

2018-05-01

A quantitative theory of Fraunhofer diffraction by right- and left-handed multiwalled cylindrical scroll nanotubes is developed on the basis of the kinematical approach. The proposed theory is mainly dedicated to structural studies of individual nanotubes by the selected-area electron diffraction technique. Strong and diffuse reflections of the scroll nanotube were studied and explicit formulas that govern relations between the direct and reciprocal lattice of the scroll nanotube are achieved.

Genetics of the peloponnesean populations and the theory of extinction of the medieval peloponnesean Greeks

PubMed Central

Stamatoyannopoulos, George; Bose, Aritra; Teodosiadis, Athanasios; Tsetsos, Fotis; Plantinga, Anna; Psatha, Nikoletta; Zogas, Nikos; Yannaki, Evangelia; Zalloua, Pierre; Kidd, Kenneth K; Browning, Brian L; Stamatoyannopoulos, John; Paschou, Peristera; Drineas, Petros

2017-01-01

Peloponnese has been one of the cradles of the Classical European civilization and an important contributor to the ancient European history. It has also been the subject of a controversy about the ancestry of its population. In a theory hotly debated by scholars for over 170 years, the German historian Jacob Philipp Fallmerayer proposed that the medieval Peloponneseans were totally extinguished by Slavic and Avar invaders and replaced by Slavic settlers during the 6th century CE. Here we use 2.5 million single-nucleotide polymorphisms to investigate the genetic structure of Peloponnesean populations in a sample of 241 individuals originating from all districts of the peninsula and to examine predictions of the theory of replacement of the medieval Peloponneseans by Slavs. We find considerable heterogeneity of Peloponnesean populations exemplified by genetically distinct subpopulations and by gene flow gradients within Peloponnese. By principal component analysis (PCA) and ADMIXTURE analysis the Peloponneseans are clearly distinguishable from the populations of the Slavic homeland and are very similar to Sicilians and Italians. Using a novel method of quantitative analysis of ADMIXTURE output we find that the Slavic ancestry of Peloponnesean subpopulations ranges from 0.2 to 14.4%. Subpopulations considered by Fallmerayer to be Slavic tribes or to have Near Eastern origin, have no significant ancestry of either. This study rejects the theory of extinction of medieval Peloponneseans and illustrates how genetics can clarify important aspects of the history of a human population. PMID:28272534

Reinventing the ames test as a quantitative lab that connects classical and molecular genetics.

PubMed

Goodson-Gregg, Nathan; De Stasio, Elizabeth A

2009-01-01

While many institutions use a version of the Ames test in the undergraduate genetics laboratory, students typically are not exposed to techniques or procedures beyond qualitative analysis of phenotypic reversion, thereby seriously limiting the scope of learning. We have extended the Ames test to include both quantitative analysis of reversion frequency and molecular analysis of revertant gene sequences. By giving students a role in designing their quantitative methods and analyses, students practice and apply quantitative skills. To help students connect classical and molecular genetic concepts and techniques, we report here procedures for characterizing the molecular lesions that confer a revertant phenotype. We suggest undertaking reversion of both missense and frameshift mutants to allow a more sophisticated molecular genetic analysis. These modifications and additions broaden the educational content of the traditional Ames test teaching laboratory, while simultaneously enhancing students' skills in experimental design, quantitative analysis, and data interpretation.

Genetic contribution to 'theory of mind' in adolescence.

PubMed

Warrier, Varun; Baron-Cohen, Simon

2018-02-22

Difficulties in 'theory of mind' (the ability to attribute mental states to oneself or others, and to make predictions about another's behaviour based on these attributions) have been observed in several psychiatric conditions. We investigate the genetic architecture of theory of mind in 4,577 13-year-olds who completed the Emotional Triangles Task (Triangles Task), a first-order test of theory of mind. We observe a small but significant female-advantage on the Triangles Task (Cohen's d = 0.19, P < 0.01), in keeping with previous work using other tests of theory of mind. Genome-wide association analyses did not identify any significant loci, and SNP heritability was non-significant. Polygenic scores for six psychiatric conditions (ADHD, anorexia, autism, bipolar disorder, depression, and schizophrenia), and empathy were not associated with scores on the Triangles Task. However, polygenic scores of cognitive aptitude, and cognitive empathy, a term synonymous with theory of mind and measured using the "Reading the Mind in the Eyes" Test, were significantly associated with scores on the Triangles Task at multiple P-value thresholds, suggesting shared genetics between different measures of theory of mind and cognition.

SOME USES OF MODELS OF QUANTITATIVE GENETIC SELECTION IN SOCIAL SCIENCE.

PubMed

Weight, Michael D; Harpending, Henry

2017-01-01

The theory of selection of quantitative traits is widely used in evolutionary biology, agriculture and other related fields. The fundamental model known as the breeder's equation is simple, robust over short time scales, and it is often possible to estimate plausible parameters. In this paper it is suggested that the results of this model provide useful yardsticks for the description of social traits and the evaluation of transmission models. The differences on a standard personality test between samples of Old Order Amish and Indiana rural young men from the same county and the decline of homicide in Medieval Europe are used as illustrative examples of the overall approach. It is shown that the decline of homicide is unremarkable under a threshold model while the differences between rural Amish and non-Amish young men are too large to be a plausible outcome of simple genetic selection in which assortative mating by affiliation is equivalent to truncation selection.

The quantitative theory of within-host viral evolution

NASA Astrophysics Data System (ADS)

Rouzine, Igor M.; Weinberger, Leor S.

2013-01-01

During the 1990s, a group of virologists and physicists began development of a quantitative theory to explain the rapid evolution of human immunodeficiency virus type 1 (HIV-1). This theory also proved to be instrumental in understanding the rapid emergence of drug resistance in patients. Over the past two decades, this theory expanded to account for a broad array of factors important to viral evolution and propelled development of a generalized theory applicable to a broad range of asexual and partly sexual populations with many evolving sites. Here, we discuss the conceptual and theoretical tools developed to calculate the speed and other parameters of evolution, with a particular focus on the concept of ‘clonal interference’ and its applications to untreated patients.

Indirect scaling methods for testing quantitative emotion theories.

PubMed

Junge, Martin; Reisenzein, Rainer

2013-01-01

Two studies investigated the utility of indirect scaling methods, based on graded pair comparisons, for the testing of quantitative emotion theories. In Study 1, we measured the intensity of relief and disappointment caused by lottery outcomes, and in Study 2, the intensity of disgust evoked by pictures, using both direct intensity ratings and graded pair comparisons. The stimuli were systematically constructed to reflect variables expected to influence the intensity of the emotions according to theoretical models of relief/disappointment and disgust, respectively. Two probabilistic scaling methods were used to estimate scale values from the pair comparison judgements: Additive functional measurement (AFM) and maximum likelihood difference scaling (MLDS). The emotion models were fitted to the direct and indirect intensity measurements using nonlinear regression (Study 1) and analysis of variance (Study 2). Both studies found substantially improved fits of the emotion models for the indirectly determined emotion intensities, with their advantage being evident particularly at the level of individual participants. The results suggest that indirect scaling methods yield more precise measurements of emotion intensity than rating scales and thereby provide stronger tests of emotion theories in general and quantitative emotion theories in particular.

Quantitative characterization of genetic parts and circuits for plant synthetic biology.

PubMed

Schaumberg, Katherine A; Antunes, Mauricio S; Kassaw, Tessema K; Xu, Wenlong; Zalewski, Christopher S; Medford, June I; Prasad, Ashok

2016-01-01

Plant synthetic biology promises immense technological benefits, including the potential development of a sustainable bio-based economy through the predictive design of synthetic gene circuits. Such circuits are built from quantitatively characterized genetic parts; however, this characterization is a significant obstacle in work with plants because of the time required for stable transformation. We describe a method for rapid quantitative characterization of genetic plant parts using transient expression in protoplasts and dual luciferase outputs. We observed experimental variability in transient-expression assays and developed a mathematical model to describe, as well as statistical normalization methods to account for, this variability, which allowed us to extract quantitative parameters. We characterized >120 synthetic parts in Arabidopsis and validated our method by comparing transient expression with expression in stably transformed plants. We also tested >100 synthetic parts in sorghum (Sorghum bicolor) protoplasts, and the results showed that our method works in diverse plant groups. Our approach enables the construction of tunable gene circuits in complex eukaryotic organisms.

Genetic interactions contribute less than additive effects to quantitative trait variation in yeast

PubMed Central

Bloom, Joshua S.; Kotenko, Iulia; Sadhu, Meru J.; Treusch, Sebastian; Albert, Frank W.; Kruglyak, Leonid

2015-01-01

Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTL–QTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL–QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies. PMID:26537231

Towards a Quantitative Endogenous Network Theory of Cancer Genesis and Progression: beyond ``cancer as diseases of genome''

NASA Astrophysics Data System (ADS)

Ao, Ping

2011-03-01

There has been a tremendous progress in cancer research. However, it appears the current dominant cancer research framework of regarding cancer as diseases of genome leads impasse. Naturally questions have been asked that whether it is possible to develop alternative frameworks such that they can connect both to mutations and other genetic/genomic effects and to environmental factors. Furthermore, such framework can be made quantitative and with predictions experimentally testable. In this talk, I will present a positive answer to this calling. I will explain on our construction of endogenous network theory based on molecular-cellular agencies as dynamical variable. Such cancer theory explicitly demonstrates a profound connection to many fundamental concepts in physics, as such stochastic non-equilibrium processes, ``energy'' landscape, metastability, etc. It suggests that neneath cancer's daunting complexity may lie a simplicity that gives grounds for hope. The rationales behind such theory, its predictions, and its initial experimental verifications will be presented. Supported by USA NIH and China NSF.

"The Theory was Beautiful Indeed": Rise, Fall and Circulation of Maximizing Methods in Population Genetics (1930-1980).

PubMed

Grodwohl, Jean-Baptiste

2017-08-01

Describing the theoretical population geneticists of the 1960s, Joseph Felsenstein reminisced: "our central obsession was finding out what function evolution would try to maximize. Population geneticists used to think, following Sewall Wright, that mean relative fitness, W, would be maximized by natural selection" (Felsenstein 2000). The present paper describes the genesis, diffusion and fall of this "obsession", by giving a biography of the mean fitness function in population genetics. This modeling method devised by Sewall Wright in the 1930s found its heyday in the late 1950s and early 1960s, in the wake of Motoo Kimura's and Richard Lewontin's works. It seemed a reliable guide in the mathematical study of deterministic effects (the study of natural selection in populations of infinite size, with no drift), leading to powerful generalizations presenting law-like properties. Progress in population genetics theory, it then seemed, would come from the application of this method to the study of systems with several genes. This ambition came to a halt in the context of the influential objections made by the Australian mathematician Patrick Moran in 1963. These objections triggered a controversy between mathematically- and biologically-inclined geneticists, with affected both the formal standards and the aims of population genetics as a science. Over the course of the 1960s, the mean fitness method withered with the ambition of developing the deterministic theory. The mathematical theory became increasingly complex. Kimura re-focused his modeling work on the theory of random processes; as a result of his computer simulations, Lewontin became the staunchest critic of maximizing principles in evolutionary biology. The mean fitness method then migrated to other research areas, being refashioned and used in evolutionary quantitative genetics and behavioral ecology.

Refining Intervention Targets in Family-Based Research: Lessons From Quantitative Behavioral Genetics

PubMed Central

Leve, Leslie D.; Harold, Gordon T.; Ge, Xiaojia; Neiderhiser, Jenae M.; Patterson, Gerald

2010-01-01

The results from a large body of family-based research studies indicate that modifying the environment (specifically dimensions of the social environment) through intervention is an effective mechanism for achieving positive outcomes. Parallel to this work is a growing body of evidence from genetically informed studies indicating that social environmental factors are central to enhancing or offsetting genetic influences. Increased precision in the understanding of the role of the social environment in offsetting genetic risk might provide new information about environmental mechanisms that could be applied to prevention science. However, at present, the multifaceted conceptualization of the environment in prevention science is mismatched with the more limited measurement of the environment in many genetically informed studies. A framework for translating quantitative behavioral genetic research to inform the development of preventive interventions is presented in this article. The measurement of environmental indices amenable to modification is discussed within the context of quantitative behavioral genetic studies. In particular, emphasis is placed on the necessary elements that lead to benefits in prevention science, specifically the development of evidence-based interventions. An example from an ongoing prospective adoption study is provided to illustrate the potential of this translational process to inform the selection of preventive intervention targets. PMID:21188273

A discriminative test among the different theories proposed to explain the origin of the genetic code: the coevolution theory finds additional support.

PubMed

Giulio, Massimo Di

2018-05-19

A discriminative statistical test among the different theories proposed to explain the origin of the genetic code is presented. Gathering the amino acids into polarity and biosynthetic classes that are the first expression of the physicochemical theory of the origin of the genetic code and the second expression of the coevolution theory, these classes are utilized in the Fisher's exact test to establish their significance within the genetic code table. Linking to the rows and columns of the genetic code of probabilities that express the statistical significance of these classes, I have finally been in the condition to be able to calculate a χ value to link to both the physicochemical theory and to the coevolution theory that would express the corroboration level referred to these theories. The comparison between these two χ values showed that the coevolution theory is able to explain - in this strictly empirical analysis - the origin of the genetic code better than that of the physicochemical theory. Copyright © 2018 Elsevier B.V. All rights reserved.

Quantitative genetic-interaction mapping in mammalian cells

PubMed Central

Roguev, Assen; Talbot, Dale; Negri, Gian Luca; Shales, Michael; Cagney, Gerard; Bandyopadhyay, Sourav; Panning, Barbara; Krogan, Nevan J

2013-01-01

Mapping genetic interactions (GIs) by simultaneously perturbing pairs of genes is a powerful tool for understanding complex biological phenomena. Here we describe an experimental platform for generating quantitative GI maps in mammalian cells using a combinatorial RNA interference strategy. We performed ~11,000 pairwise knockdowns in mouse fibroblasts, focusing on 130 factors involved in chromatin regulation to create a GI map. Comparison of the GI and protein-protein interaction (PPI) data revealed that pairs of genes exhibiting positive GIs and/or similar genetic profiles were predictive of the corresponding proteins being physically associated. The mammalian GI map identified pathways and complexes but also resolved functionally distinct submodules within larger protein complexes. By integrating GI and PPI data, we created a functional map of chromatin complexes in mouse fibroblasts, revealing that the PAF complex is a central player in the mammalian chromatin landscape. PMID:23407553

Extensions and evaluations of a general quantitative theory of forest structure and dynamics

PubMed Central

Enquist, Brian J.; West, Geoffrey B.; Brown, James H.

2009-01-01

Here, we present the second part of a quantitative theory for the structure and dynamics of forests under demographic and resource steady state. The theory is based on individual-level allometric scaling relations for how trees use resources, fill space, and grow. These scale up to determine emergent properties of diverse forests, including size–frequency distributions, spacing relations, canopy configurations, mortality rates, population dynamics, successional dynamics, and resource flux rates. The theory uniquely makes quantitative predictions for both stand-level scaling exponents and normalizations. We evaluate these predictions by compiling and analyzing macroecological datasets from several tropical forests. The close match between theoretical predictions and data suggests that forests are organized by a set of very general scaling rules. Our mechanistic theory is based on allometric scaling relations, is complementary to “demographic theory,” but is fundamentally different in approach. It provides a quantitative baseline for understanding deviations from predictions due to other factors, including disturbance, variation in branching architecture, asymmetric competition, resource limitation, and other sources of mortality, which are not included in the deliberately simplified theory. The theory should apply to a wide range of forests despite large differences in abiotic environment, species diversity, and taxonomic and functional composition. PMID:19363161

Quantitative confirmation of diffusion-limited oxidation theories

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

Gillen, K.T.; Clough, R.L.

1990-01-01

Diffusion-limited (heterogeneous) oxidation effects are often important for studies of polymer degradation. Such effects are common in polymers subjected to ionizing radiation at relatively high dose rate. To better understand the underlying oxidation processes and to aid in the planning of accelerated aging studies, it would be desirable to be able to monitor and quantitatively understand these effects. In this paper, we briefly review a theoretical diffusion approach which derives model profiles for oxygen surrounded sheets of material by combining oxygen permeation rates with kinetically based oxygen consumption expressions. The theory leads to a simple governing expression involving the oxygenmore » consumption and permeation rates together with two model parameters {alpha} and {beta}. To test the theory, gamma-initiated oxidation of a sheet of commercially formulated EPDM rubber was performed under conditions which led to diffusion-limited oxidation. Profile shapes from the theoretical treatments are shown to accurately fit experimentally derived oxidation profiles. In addition, direct measurements on the same EPDM material of the oxygen consumption and permeation rates, together with values of {alpha} and {beta} derived from the fitting procedure, allow us to quantitatively confirm for the first time the governing theoretical relationship. 17 refs., 3 figs.« less

General Methods for Evolutionary Quantitative Genetic Inference from Generalized Mixed Models.

PubMed

de Villemereuil, Pierre; Schielzeth, Holger; Nakagawa, Shinichi; Morrissey, Michael

2016-11-01

Methods for inference and interpretation of evolutionary quantitative genetic parameters, and for prediction of the response to selection, are best developed for traits with normal distributions. Many traits of evolutionary interest, including many life history and behavioral traits, have inherently nonnormal distributions. The generalized linear mixed model (GLMM) framework has become a widely used tool for estimating quantitative genetic parameters for nonnormal traits. However, whereas GLMMs provide inference on a statistically convenient latent scale, it is often desirable to express quantitative genetic parameters on the scale upon which traits are measured. The parameters of fitted GLMMs, despite being on a latent scale, fully determine all quantities of potential interest on the scale on which traits are expressed. We provide expressions for deriving each of such quantities, including population means, phenotypic (co)variances, variance components including additive genetic (co)variances, and parameters such as heritability. We demonstrate that fixed effects have a strong impact on those parameters and show how to deal with this by averaging or integrating over fixed effects. The expressions require integration of quantities determined by the link function, over distributions of latent values. In general cases, the required integrals must be solved numerically, but efficient methods are available and we provide an implementation in an R package, QGglmm. We show that known formulas for quantities such as heritability of traits with binomial and Poisson distributions are special cases of our expressions. Additionally, we show how fitted GLMM can be incorporated into existing methods for predicting evolutionary trajectories. We demonstrate the accuracy of the resulting method for evolutionary prediction by simulation and apply our approach to data from a wild pedigreed vertebrate population. Copyright © 2016 de Villemereuil et al.

From information theory to quantitative description of steric effects.

PubMed

Alipour, Mojtaba; Safari, Zahra

2016-07-21

Immense efforts have been made in the literature to apply the information theory descriptors for investigating the electronic structure theory of various systems. In the present study, the information theoretic quantities, such as Fisher information, Shannon entropy, Onicescu information energy, and Ghosh-Berkowitz-Parr entropy, have been used to present a quantitative description for one of the most widely used concepts in chemistry, namely the steric effects. Taking the experimental steric scales for the different compounds as benchmark sets, there are reasonable linear relationships between the experimental scales of the steric effects and theoretical values of steric energies calculated from information theory functionals. Perusing the results obtained from the information theoretic quantities with the two representations of electron density and shape function, the Shannon entropy has the best performance for the purpose. On the one hand, the usefulness of considering the contributions of functional groups steric energies and geometries, and on the other hand, dissecting the effects of both global and local information measures simultaneously have also been explored. Furthermore, the utility of the information functionals for the description of steric effects in several chemical transformations, such as electrophilic and nucleophilic reactions and host-guest chemistry, has been analyzed. The functionals of information theory correlate remarkably with the stability of systems and experimental scales. Overall, these findings show that the information theoretic quantities can be introduced as quantitative measures of steric effects and provide further evidences of the quality of information theory toward helping theoreticians and experimentalists to interpret different problems in real systems.

Genetic Epidemiology and Public Health: The Evolution From Theory to Technology.

PubMed

Fallin, M Daniele; Duggal, Priya; Beaty, Terri H

2016-03-01

Genetic epidemiology represents a hybrid of epidemiologic designs and statistical models that explicitly consider both genetic and environmental risk factors for disease. It is a relatively new field in public health; the term was first coined only 35 years ago. In this short time, the field has been through a major evolution, changing from a field driven by theory, without the technology for genetic measurement or computational capacity to apply much of the designs and methods developed, to a field driven by rapidly expanding technology in genomic measurement and computational analyses while epidemiologic theory struggles to keep up. In this commentary, we describe 4 different eras of genetic epidemiology, spanning this evolution from theory to technology, what we have learned, what we have added to the broader field of public health, and what remains to be done. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Quantitative genetic bases of anthocyanin variation in grape (Vitis vinifera L. ssp. sativa) berry: a quantitative trait locus to quantitative trait nucleotide integrated study.

PubMed

Fournier-Level, Alexandre; Le Cunff, Loïc; Gomez, Camila; Doligez, Agnès; Ageorges, Agnès; Roux, Catherine; Bertrand, Yves; Souquet, Jean-Marc; Cheynier, Véronique; This, Patrice

2009-11-01

The combination of QTL mapping studies of synthetic lines and association mapping studies of natural diversity represents an opportunity to throw light on the genetically based variation of quantitative traits. With the positional information provided through quantitative trait locus (QTL) mapping, which often leads to wide intervals encompassing numerous genes, it is now feasible to directly target candidate genes that are likely to be responsible for the observed variation in completely sequenced genomes and to test their effects through association genetics. This approach was performed in grape, a newly sequenced genome, to decipher the genetic architecture of anthocyanin content. Grapes may be either white or colored, ranging from the lightest pink to the darkest purple tones according to the amount of anthocyanin accumulated in the berry skin, which is a crucial trait for both wine quality and human nutrition. Although the determinism of the white phenotype has been fully identified, the genetic bases of the quantitative variation of anthocyanin content in berry skin remain unclear. A single QTL responsible for up to 62% of the variation in the anthocyanin content was mapped on a Syrah x Grenache F(1) pseudo-testcross. Among the 68 unigenes identified in the grape genome within the QTL interval, a cluster of four Myb-type genes was selected on the basis of physiological evidence (VvMybA1, VvMybA2, VvMybA3, and VvMybA4). From a core collection of natural resources (141 individuals), 32 polymorphisms revealed significant association, and extended linkage disequilibrium was observed. Using a multivariate regression method, we demonstrated that five polymorphisms in VvMybA genes except VvMybA4 (one retrotransposon, three single nucleotide polymorphisms and one 2-bp insertion/deletion) accounted for 84% of the observed variation. All these polymorphisms led to either structural changes in the MYB proteins or differences in the VvMybAs promoters. We concluded that

Pangenesis as a source of new genetic information. The history of a now disproven theory.

PubMed

Bergman, Gerald

2006-01-01

Evolution is based on natural selection of existing biological phenotypic traits. Natural selection can only eliminate traits. It cannot create new ones, requiring a theory to explain the origin of new genetic information. The theory of pangenesis was a major attempt to explain the source of new genetic information required to produce phenotypic variety. This theory, advocated by Darwin as the main source of genetic variety, has now been empirically disproved. It is currently a theory mainly of interest to science historians.

Influence of mom and dad: quantitative genetic models for maternal effects and genomic imprinting.

PubMed

Santure, Anna W; Spencer, Hamish G

2006-08-01

The expression of an imprinted gene is dependent on the sex of the parent it was inherited from, and as a result reciprocal heterozygotes may display different phenotypes. In contrast, maternal genetic terms arise when the phenotype of an offspring is influenced by the phenotype of its mother beyond the direct inheritance of alleles. Both maternal effects and imprinting may contribute to resemblance between offspring of the same mother. We demonstrate that two standard quantitative genetic models for deriving breeding values, population variances and covariances between relatives, are not equivalent when maternal genetic effects and imprinting are acting. Maternal and imprinting effects introduce both sex-dependent and generation-dependent effects that result in differences in the way additive and dominance effects are defined for the two approaches. We use a simple example to demonstrate that both imprinting and maternal genetic effects add extra terms to covariances between relatives and that model misspecification may over- or underestimate true covariances or lead to extremely variable parameter estimation. Thus, an understanding of various forms of parental effects is essential in correctly estimating quantitative genetic variance components.

Information theory and the ethylene genetic network.

PubMed

González-García, José S; Díaz, José

2011-10-01

The original aim of the Information Theory (IT) was to solve a purely technical problem: to increase the performance of communication systems, which are constantly affected by interferences that diminish the quality of the transmitted information. That is, the theory deals only with the problem of transmitting with the maximal precision the symbols constituting a message. In Shannon's theory messages are characterized only by their probabilities, regardless of their value or meaning. As for its present day status, it is generally acknowledged that Information Theory has solid mathematical foundations and has fruitful strong links with Physics in both theoretical and experimental areas. However, many applications of Information Theory to Biology are limited to using it as a technical tool to analyze biopolymers, such as DNA, RNA or protein sequences. The main point of discussion about the applicability of IT to explain the information flow in biological systems is that in a classic communication channel, the symbols that conform the coded message are transmitted one by one in an independent form through a noisy communication channel, and noise can alter each of the symbols, distorting the message; in contrast, in a genetic communication channel the coded messages are not transmitted in the form of symbols but signaling cascades transmit them. Consequently, the information flow from the emitter to the effector is due to a series of coupled physicochemical processes that must ensure the accurate transmission of the message. In this review we discussed a novel proposal to overcome this difficulty, which consists of the modeling of gene expression with a stochastic approach that allows Shannon entropy (H) to be directly used to measure the amount of uncertainty that the genetic machinery has in relation to the correct decoding of a message transmitted into the nucleus by a signaling pathway. From the value of H we can define a function I that measures the amount of

Quantitative genetic analysis of injury liability in infants and toddlers

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

Phillips, K.; Matheny, A.P. Jr.

1995-02-27

A threshold model of latent liability was applied to infant and toddler twin data on total count of injuries sustained during the interval from birth to 36 months of age. A quantitative genetic analysis of estimated twin correlations in injury liability indicated strong genetic dominance effects, but no additive genetic variance was detected. Because interpretations involving overdominance have little research support, the results may be due to low order epistasis or other interaction effects. Boys had more injuries than girls, but this effect was found only for groups whose parents were prompted and questioned in detail about their children`s injuries.more » Activity and impulsivity are two behavioral predictors of childhood injury, and the results are discussed in relation to animal research on infant and adult activity levels, and impulsivity in adult humans. Genetic epidemiological approaches to childhood injury should aid in targeting higher risk children for preventive intervention. 30 refs., 4 figs., 3 tabs.« less

Quantitative verification of ab initio self-consistent laser theory.

PubMed

Ge, Li; Tandy, Robert J; Stone, A D; Türeci, Hakan E

2008-10-13

We generalize and test the recent "ab initio" self-consistent (AISC) time-independent semiclassical laser theory. This self-consistent formalism generates all the stationary lasing properties in the multimode regime (frequencies, thresholds, internal and external fields, output power and emission pattern) from simple inputs: the dielectric function of the passive cavity, the atomic transition frequency, and the transverse relaxation time of the lasing transition.We find that the theory gives excellent quantitative agreement with full time-dependent simulations of the Maxwell-Bloch equations after it has been generalized to drop the slowly-varying envelope approximation. The theory is infinite order in the non-linear hole-burning interaction; the widely used third order approximation is shown to fail badly.

Arms race between selfishness and policing: two-trait quantitative genetic model for caste fate conflict in eusocial Hymenoptera.

PubMed

Dobata, Shigeto

2012-12-01

Policing against selfishness is now regarded as the main force maintaining cooperation, by reducing costly conflict in complex social systems. Although policing has been studied extensively in social insect colonies, its coevolution against selfishness has not been fully captured by previous theories. In this study, I developed a two-trait quantitative genetic model of the conflict between selfish immature females (usually larvae) and policing workers in eusocial Hymenoptera over the immatures' propensity to develop into new queens. This model allows for the analysis of coevolution between genomes expressed in immatures and workers that collectively determine the immatures' queen caste fate. The main prediction of the model is that a higher level of polyandry leads to a smaller fraction of queens produced among new females through caste fate policing. The other main prediction of the present model is that, as a result of arms race, caste fate policing by workers coevolves with exaggerated selfishness of the immatures achieving maximum potential to develop into queens. Moreover, the model can incorporate genetic correlation between traits, which has been largely unexplored in social evolution theory. This study highlights the importance of understanding social traits as influenced by the coevolution of conflicting genomes. © 2012 The Author. Evolution© 2012 The Society for the Study of Evolution.

The Mapping Model: A Cognitive Theory of Quantitative Estimation

ERIC Educational Resources Information Center

von Helversen, Bettina; Rieskamp, Jorg

2008-01-01

How do people make quantitative estimations, such as estimating a car's selling price? Traditionally, linear-regression-type models have been used to answer this question. These models assume that people weight and integrate all information available to estimate a criterion. The authors propose an alternative cognitive theory for quantitative…

Quantitative autistic trait measurements index background genetic risk for ASD in Hispanic families.

PubMed

Page, Joshua; Constantino, John Nicholas; Zambrana, Katherine; Martin, Eden; Tunc, Ilker; Zhang, Yi; Abbacchi, Anna; Messinger, Daniel

2016-01-01

Recent studies have indicated that quantitative autistic traits (QATs) of parents reflect inherited liabilities that may index background genetic risk for clinical autism spectrum disorder (ASD) in their offspring. Moreover, preferential mating for QATs has been observed as a potential factor in concentrating autistic liabilities in some families across generations. Heretofore, intergenerational studies of QATs have focused almost exclusively on Caucasian populations-the present study explored these phenomena in a well-characterized Hispanic population. The present study examined QAT scores in siblings and parents of 83 Hispanic probands meeting research diagnostic criteria for ASD, and 64 non-ASD controls, using the Social Responsiveness Scale-2 (SRS-2). Ancestry of the probands was characterized by genotype, using information from 541,929 single nucleotide polymorphic markers. In families of Hispanic children with an ASD diagnosis, the pattern of quantitative trait correlations observed between ASD-affected children and their first-degree relatives (ICCs on the order of 0.20), between unaffected first-degree relatives in ASD-affected families (sibling/mother ICC = 0.36; sibling/father ICC = 0.53), and between spouses (mother/father ICC = 0.48) were in keeping with the influence of transmitted background genetic risk and strong preferential mating for variation in quantitative autistic trait burden. Results from analysis of ancestry-informative genetic markers among probands in this sample were consistent with that from other Hispanic populations. Quantitative autistic traits represent measurable indices of inherited liability to ASD in Hispanic families. The accumulation of autistic traits occurs within generations, between spouses, and across generations, among Hispanic families affected by ASD. The occurrence of preferential mating for QATs-the magnitude of which may vary across cultures-constitutes a mechanism by which background genetic liability

Some pungent arguments against the physico-chemical theories of the origin of the genetic code and corroborating the coevolution theory.

PubMed

Di Giulio, Massimo

2017-02-07

Whereas it is extremely easy to prove that "if the biosynthetic relationships between amino acids were fundamental in the structuring of the genetic code, then their physico-chemical properties might also be revealed in the genetic code table"; it is, on the contrary, impossible to prove that "if the physico-chemical properties of amino acids were fundamental in the structuring of the genetic code, then the presence of the biosynthetic relationships between amino acids should not be revealed in the genetic code". And, given that in the genetic code table are mirrored both the biosynthetic relationships between amino acids and their physico-chemical properties, all this would be a test that would falsify the physico-chemical theories of the origin of the genetic code. That is to say, if the physico-chemical properties of amino acids had a fundamental role in organizing the genetic code, then we would not have duly revealed the presence - in the genetic code - of the biosynthetic relationships between amino acids, and on the contrary this has been observed. Therefore, this falsifies the physico-chemical theories of genetic code origin. Whereas, the coevolution theory of the origin of the genetic code would be corroborated by this analysis, because it would be able to give a description of evolution of the genetic code more coherent with the indisputable empirical observations that link both the biosynthetic relationships of amino acids and their physico-chemical properties to the evolutionary organization of the genetic code. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Quantitative Basis of the Arabidopsis Innate Immune System to Endemic Pathogens Depends on Pathogen Genetics

PubMed Central

Corwin, Jason A.; Copeland, Daniel; Feusier, Julie; Subedy, Anushriya; Eshbaugh, Robert; Palmer, Christine; Maloof, Julin; Kliebenstein, Daniel J.

2016-01-01

The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B. cinerea, we identified a total of 2,982 genes associated with quantitative resistance using lesion area and 3,354 genes associated with camalexin production as measures of the interaction. Most genes were associated with resistance to a specific Botrytis isolate, which demonstrates the influence of pathogen genetic variation in analyzing host quantitative resistance. While known resistance genes, such as receptor-like kinases (RLKs) and nucleotide-binding site leucine-rich repeat proteins (NLRs), were found to be enriched among associated genes, they only account for a small fraction of the total genes associated with quantitative resistance. Using publically available co-expression data, we condensed the quantitative resistance associated genes into co-expressed gene networks. GO analysis of these networks implicated several biological processes commonly connected to disease resistance, including defense hormone signaling and ROS production, as well as novel processes, such as leaf development. Validation of single gene T-DNA knockouts in a Col-0 background demonstrate a high success rate (60%) when accounting for differences in environmental and Botrytis genetic variation. This study shows that the genetic architecture underlying host innate immune system is extremely complex and is likely able to sense and respond to differential virulence among pathogen genotypes. PMID:26866607

The Quantitative Basis of the Arabidopsis Innate Immune System to Endemic Pathogens Depends on Pathogen Genetics.

PubMed

Corwin, Jason A; Copeland, Daniel; Feusier, Julie; Subedy, Anushriya; Eshbaugh, Robert; Palmer, Christine; Maloof, Julin; Kliebenstein, Daniel J

2016-02-01

The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B. cinerea, we identified a total of 2,982 genes associated with quantitative resistance using lesion area and 3,354 genes associated with camalexin production as measures of the interaction. Most genes were associated with resistance to a specific Botrytis isolate, which demonstrates the influence of pathogen genetic variation in analyzing host quantitative resistance. While known resistance genes, such as receptor-like kinases (RLKs) and nucleotide-binding site leucine-rich repeat proteins (NLRs), were found to be enriched among associated genes, they only account for a small fraction of the total genes associated with quantitative resistance. Using publically available co-expression data, we condensed the quantitative resistance associated genes into co-expressed gene networks. GO analysis of these networks implicated several biological processes commonly connected to disease resistance, including defense hormone signaling and ROS production, as well as novel processes, such as leaf development. Validation of single gene T-DNA knockouts in a Col-0 background demonstrate a high success rate (60%) when accounting for differences in environmental and Botrytis genetic variation. This study shows that the genetic architecture underlying host innate immune system is extremely complex and is likely able to sense and respond to differential virulence among pathogen genotypes.

Measurement Invariance: A Foundational Principle for Quantitative Theory Building

ERIC Educational Resources Information Center

Nimon, Kim; Reio, Thomas G., Jr.

2011-01-01

This article describes why measurement invariance is a critical issue to quantitative theory building within the field of human resource development. Readers will learn what measurement invariance is and how to test for its presence using techniques that are accessible to applied researchers. Using data from a LibQUAL+[TM] study of user…

Quantitative Genetic Interactions Reveal Layers of Biological Modularity

PubMed Central

Beltrao, Pedro; Cagney, Gerard; Krogan, Nevan J.

2010-01-01

In the past, biomedical research has embraced a reductionist approach, primarily focused on characterizing the individual components that comprise a system of interest. Recent technical developments have significantly increased the size and scope of data describing biological systems. At the same time, advances in the field of systems biology have evoked a broader view of how the underlying components are interconnected. In this essay, we discuss how quantitative genetic interaction mapping has enhanced our view of biological systems, allowing a deeper functional interrogation at different biological scales. PMID:20510918

[Neurosis and genetic theory of etiology and pathogenesis of ulcer disease].

PubMed

Kolotilova, M L; Ivanov, L N

2014-01-01

Based on the analysis of literature data and our own research, we have developed the original concept of etiology and pathogenesis of peptic ulcer disease. An analysis of the literature shows that none of the theories of pathogenesis of peptic ulcer disease does not cover the full diversity of the involved functions and their shifts, which lead to the development of ulcers in the stomach and the duodenum. Our neurogenic-genetic theory of etiology and pathogenesis of gastric ulcer and duodenal ulcer very best explains the cause-and-effect relationships in the patient peptic ulcer, allowing options for predominance in one or the other case factors of neurosis or genetic factors. However, it is clear that the only other: combination of neurogenic factor with genetically modified reactivity of gastroduodenal system (the presence of the target organ) cause the chronicity of the sores. The theory of peptic ulcer disease related to psychosomatic pathologies allows us to develop effective schema therapy, including drugs with psychocorrective action. On the basis of our theory of the role of Helicobacter pylori infection is treated as a pathogenetic factor in the development of peptic ulcer disease.

Heritability and quantitative genetic divergence of serotiny, a fire-persistence plant trait

PubMed Central

Hernández-Serrano, Ana; Verdú, Miguel; Santos-del-Blanco, Luís; Climent, José; González-Martínez, Santiago C.; Pausas, Juli G.

2014-01-01

Background and Aims Although it is well known that fire acts as a selective pressure shaping plant phenotypes, there are no quantitative estimates of the heritability of any trait related to plant persistence under recurrent fires, such as serotiny. In this study, the heritability of serotiny in Pinus halepensis is calculated, and an evaluation is made as to whether fire has left a selection signature on the level of serotiny among populations by comparing the genetic divergence of serotiny with the expected divergence of neutral molecular markers (QST–FST comparison). Methods A common garden of P. halepensis was used, located in inland Spain and composed of 145 open-pollinated families from 29 provenances covering the entire natural range of P. halepensis in the Iberian Peninsula and Balearic Islands. Narrow-sense heritability (h2) and quantitative genetic differentiation among populations for serotiny (QST) were estimated by means of an ‘animal model’ fitted by Bayesian inference. In order to determine whether genetic differentiation for serotiny is the result of differential natural selection, QST estimates for serotiny were compared with FST estimates obtained from allozyme data. Finally, a test was made of whether levels of serotiny in the different provenances were related to different fire regimes, using summer rainfall as a proxy for fire regime in each provenance. Key Results Serotiny showed a significant narrow-sense heritability (h2) of 0·20 (credible interval 0·09–0·40). Quantitative genetic differentiation among provenances for serotiny (QST = 0·44) was significantly higher than expected under a neutral process (FST = 0·12), suggesting adaptive differentiation. A significant negative relationship was found between the serotiny level of trees in the common garden and summer rainfall of their provenance sites. Conclusions Serotiny is a heritable trait in P. halepensis, and selection acts on it, giving rise to contrasting serotiny levels

Introduction to focus issue: quantitative approaches to genetic networks.

PubMed

Albert, Réka; Collins, James J; Glass, Leon

2013-06-01

All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks

Introduction to Focus Issue: Quantitative Approaches to Genetic Networks

NASA Astrophysics Data System (ADS)

Albert, Réka; Collins, James J.; Glass, Leon

2013-06-01

All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks

Theories of schizophrenia: a genetic-inflammatory-vascular synthesis

PubMed Central

Hanson, Daniel R; Gottesman, Irving I

2005-01-01

Background Schizophrenia, a relatively common psychiatric syndrome, affects virtually all brain functions yet has eluded explanation for more than 100 years. Whether by developmental and/or degenerative processes, abnormalities of neurons and their synaptic connections have been the recent focus of attention. However, our inability to fathom the pathophysiology of schizophrenia forces us to challenge our theoretical models and beliefs. A search for a more satisfying model to explain aspects of schizophrenia uncovers clues pointing to genetically mediated CNS microvascular inflammatory disease. Discussion A vascular component to a theory of schizophrenia posits that the physiologic abnormalities leading to illness involve disruption of the exquisitely precise regulation of the delivery of energy and oxygen required for normal brain function. The theory further proposes that abnormalities of CNS metabolism arise because genetically modulated inflammatory reactions damage the microvascular system of the brain in reaction to environmental agents, including infections, hypoxia, and physical trauma. Damage may accumulate with repeated exposure to triggering agents resulting in exacerbation and deterioration, or healing with their removal. There are clear examples of genetic polymorphisms in inflammatory regulators leading to exaggerated inflammatory responses. There is also ample evidence that inflammatory vascular disease of the brain can lead to psychosis, often waxing and waning, and exhibiting a fluctuating course, as seen in schizophrenia. Disturbances of CNS blood flow have repeatedly been observed in people with schizophrenia using old and new technologies. To account for the myriad of behavioral and other curious findings in schizophrenia such as minor physical anomalies, or reported decreased rates of rheumatoid arthritis and highly visible nail fold capillaries, we would have to evoke a process that is systemic such as the vascular and immune

An extension of the coevolution theory of the origin of the genetic code

PubMed Central

Di Giulio, Massimo

2008-01-01

Background The coevolution theory of the origin of the genetic code suggests that the genetic code is an imprint of the biosynthetic relationships between amino acids. However, this theory does not seem to attribute a role to the biosynthetic relationships between the earliest amino acids that evolved along the pathways of energetic metabolism. As a result, the coevolution theory is unable to clearly define the very earliest phases of genetic code origin. In order to remove this difficulty, I here suggest an extension of the coevolution theory that attributes a crucial role to the first amino acids that evolved along these biosynthetic pathways and to their biosynthetic relationships, even when defined by the non-amino acid molecules that are their precursors. Results It is re-observed that the first amino acids to evolve along these biosynthetic pathways are predominantly those codified by codons of the type GNN, and this observation is found to be statistically significant. Furthermore, the close biosynthetic relationships between the sibling amino acids Ala-Ser, Ser-Gly, Asp-Glu, and Ala-Val are not random in the genetic code table and reinforce the hypothesis that the biosynthetic relationships between these six amino acids played a crucial role in defining the very earliest phases of genetic code origin. Conclusion All this leads to the hypothesis that there existed a code, GNS, reflecting the biosynthetic relationships between these six amino acids which, as it defines the very earliest phases of genetic code origin, removes the main difficulty of the coevolution theory. Furthermore, it is here discussed how this code might have naturally led to the code codifying only for the domains of the codons of precursor amino acids, as predicted by the coevolution theory. Finally, the hypothesis here suggested also removes other problems of the coevolution theory, such as the existence for certain pairs of amino acids with an unclear biosynthetic relationship between

A Systematic Review of Genetic Testing and Lifestyle Behaviour Change: Are We Using High-Quality Genetic Interventions and Considering Behaviour Change Theory?

PubMed

Horne, Justine; Madill, Janet; O'Connor, Colleen; Shelley, Jacob; Gilliland, Jason

2018-04-10

Studying the impact of genetic testing interventions on lifestyle behaviour change has been a priority area of research in recent years. Substantial heterogeneity exists in the results and conclusions of this literature, which has yet to be explained using validated behaviour change theory and an assessment of the quality of genetic interventions. The theory of planned behaviour (TPB) helps to explain key contributors to behaviour change. It has been hypothesized that personalization could be added to this theory to help predict changes in health behaviours. This systematic review provides a detailed, comprehensive identification, assessment, and summary of primary research articles pertaining to lifestyle behaviour change (nutrition, physical activity, sleep, and smoking) resulting from genetic testing interventions. The present review further aims to provide in-depth analyses of studies conducted to date within the context of the TPB and the quality of genetic interventions provided to participants while aiming to determine whether or not genetic testing facilitates changes in lifestyle habits. This review is timely in light of a recently published "call-to-action" paper, highlighting the need to incorporate the TPB into personalized healthcare behaviour change research. Three bibliographic databases, one key website, and article reference lists were searched for relevant primary research articles. The PRISMA Flow Diagram and PRISMA Checklist were used to guide the search strategy and manuscript preparation. Out of 32,783 titles retrieved, 26 studies met the inclusion criteria. Three quality assessments were conducted and included: (1) risk of bias, (2) quality of genetic interventions, and (3) consideration of theoretical underpinnings - primarily the TPB. Risk of bias in studies was overall rated to be "fair." Consideration of the TPB was "poor," with no study making reference to this validated theory. While some studies (n = 11; 42%) made reference to other

[The study of tomato fruit weight quantitative trait locus and its application in genetics teaching].

PubMed

Wang, Hai-yan

2015-08-01

The classical research cases, which have greatly promoted the development of genetics in history, can be combined with the content of courses in genetics teaching to train students' ability of scientific thinking and genetic analysis. The localization and clone of gene controlling tomato fruit weight is a pioneer work in quantitative trait locus (QTL) studies and represents a complete process of QTL research in plants. Application of this integrated case in genetics teaching, which showed a wonderful process of scientific discovery and the fascination of genetic research, has inspired students' interest in genetics and achieved a good teaching effect.

An analysis of the metabolic theory of the origin of the genetic code

NASA Technical Reports Server (NTRS)

Amirnovin, R.; Bada, J. L. (Principal Investigator)

1997-01-01

A computer program was used to test Wong's coevolution theory of the genetic code. The codon correlations between the codons of biosynthetically related amino acids in the universal genetic code and in randomly generated genetic codes were compared. It was determined that many codon correlations are also present within random genetic codes and that among the random codes there are always several which have many more correlations than that found in the universal code. Although the number of correlations depends on the choice of biosynthetically related amino acids, the probability of choosing a random genetic code with the same or greater number of codon correlations as the universal genetic code was found to vary from 0.1% to 34% (with respect to a fairly complete listing of related amino acids). Thus, Wong's theory that the genetic code arose by coevolution with the biosynthetic pathways of amino acids, based on codon correlations between biosynthetically related amino acids, is statistical in nature.

Quantitative kinetic theory of active matter

NASA Astrophysics Data System (ADS)

Ihle, Thomas; Chou, Yen-Liang

2014-03-01

Models of self-driven agents similar to the Vicsek model [Phys. Rev. Lett. 75 (1995) 1226] are studied by means of kinetic theory. In these models, particles try to align their travel directions with the average direction of their neighbours. At strong alignment a globally ordered state of collective motion forms. An Enskog-like kinetic theory is derived from the exact Chapman-Kolmogorov equation in phase space using Boltzmann's mean-field approximation of molecular chaos. The kinetic equation is solved numerically by a nonlocal Lattice-Boltzmann-like algorithm. Steep soliton-like waves are observed that lead to an abrupt jump of the global order parameter if the noise level is changed. The shape of the wave is shown to follow a novel scaling law and to quantitatively agree within 3 % with agent-based simulations at large particle speeds. This provides a mean-field mechanism to change the second-order character of the flocking transition to first order. Diagrammatic techniques are used to investigate small particle speeds, where the mean-field assumption of Molecular Chaos is invalid and where correlation effects need to be included.

FRET-based genetically-encoded sensors for quantitative monitoring of metabolites.

PubMed

Mohsin, Mohd; Ahmad, Altaf; Iqbal, Muhammad

2015-10-01

Neighboring cells in the same tissue can exist in different states of dynamic activities. After genomics, proteomics and metabolomics, fluxomics is now equally important for generating accurate quantitative information on the cellular and sub-cellular dynamics of ions and metabolite, which is critical for functional understanding of organisms. Various spectrometry techniques are used for monitoring ions and metabolites, although their temporal and spatial resolutions are limited. Discovery of the fluorescent proteins and their variants has revolutionized cell biology. Therefore, novel tools and methods targeting sub-cellular compartments need to be deployed in specific cells and targeted to sub-cellular compartments in order to quantify the target-molecule dynamics directly. We require tools that can measure cellular activities and protein dynamics with sub-cellular resolution. Biosensors based on fluorescence resonance energy transfer (FRET) are genetically encoded and hence can specifically target sub-cellular organelles by fusion to proteins or targetted sequences. Since last decade, FRET-based genetically encoded sensors for molecules involved in energy production, reactive oxygen species and secondary messengers have helped to unravel key aspects of cellular physiology. This review, describing the design and principles of sensors, presents a database of sensors for different analytes/processes, and illustrate examples of application in quantitative live cell imaging.

Neutral theory, microbial practice: challenges in bacterial population genetics.

PubMed

Rocha, Eduardo P C

2018-04-19

Kimura's outstanding contributions to population genetics included many elegant theoretical results on the vagaries of alleles in populations. Once polymorphism data showed extensive variation in natural populations, these results led naturally to the Neutral Theory. In this article, I'll depart from some of these results to focus on four major open problems in microbial population genetics with direct implications to the study of molecular evolution: the lack of neutral polymorphism, the modeling of genetic exchanges, the population genetics of ill-defined populations, and the difficulty of untangling selection and demography in the light of the previous issues. Whilst studies in population genetics usually focus on single nucleotide polymorphism and allelic recombination, ignoring even small indels, a large fraction of genetic diversification in Bacteria results from horizontal gene transfer. Ignoring this fact defeats the purpose of population genetics: to characterize the genetic variation in populations and their adaptive effects. I'll argue that, following on Kimura's life work, one may need to develop new approaches to study microbes that reproduce asexually but are able to engage in gene exchanges with very distantly related organisms in a context where random sampling is often unachievable, populations are ill-defined, genetic linkage is strong, and random drift is rare.

Using genetic markers to orient the edges in quantitative trait networks: the NEO software.

PubMed

Aten, Jason E; Fuller, Tova F; Lusis, Aldons J; Horvath, Steve

2008-04-15

Systems genetic studies have been used to identify genetic loci that affect transcript abundances and clinical traits such as body weight. The pairwise correlations between gene expression traits and/or clinical traits can be used to define undirected trait networks. Several authors have argued that genetic markers (e.g expression quantitative trait loci, eQTLs) can serve as causal anchors for orienting the edges of a trait network. The availability of hundreds of thousands of genetic markers poses new challenges: how to relate (anchor) traits to multiple genetic markers, how to score the genetic evidence in favor of an edge orientation, and how to weigh the information from multiple markers. We develop and implement Network Edge Orienting (NEO) methods and software that address the challenges of inferring unconfounded and directed gene networks from microarray-derived gene expression data by integrating mRNA levels with genetic marker data and Structural Equation Model (SEM) comparisons. The NEO software implements several manual and automatic methods for incorporating genetic information to anchor traits. The networks are oriented by considering each edge separately, thus reducing error propagation. To summarize the genetic evidence in favor of a given edge orientation, we propose Local SEM-based Edge Orienting (LEO) scores that compare the fit of several competing causal graphs. SEM fitting indices allow the user to assess local and overall model fit. The NEO software allows the user to carry out a robustness analysis with regard to genetic marker selection. We demonstrate the utility of NEO by recovering known causal relationships in the sterol homeostasis pathway using liver gene expression data from an F2 mouse cross. Further, we use NEO to study the relationship between a disease gene and a biologically important gene co-expression module in liver tissue. The NEO software can be used to orient the edges of gene co-expression networks or quantitative trait

Uncovering the genetic signature of quantitative trait evolution with replicated time series data.

PubMed

Franssen, S U; Kofler, R; Schlötterer, C

2017-01-01

The genetic architecture of adaptation in natural populations has not yet been resolved: it is not clear to what extent the spread of beneficial mutations (selective sweeps) or the response of many quantitative trait loci drive adaptation to environmental changes. Although much attention has been given to the genomic footprint of selective sweeps, the importance of selection on quantitative traits is still not well studied, as the associated genomic signature is extremely difficult to detect. We propose 'Evolve and Resequence' as a promising tool, to study polygenic adaptation of quantitative traits in evolving populations. Simulating replicated time series data we show that adaptation to a new intermediate trait optimum has three characteristic phases that are reflected on the genomic level: (1) directional frequency changes towards the new trait optimum, (2) plateauing of allele frequencies when the new trait optimum has been reached and (3) subsequent divergence between replicated trajectories ultimately leading to the loss or fixation of alleles while the trait value does not change. We explore these 3 phase characteristics for relevant population genetic parameters to provide expectations for various experimental evolution designs. Remarkably, over a broad range of parameters the trajectories of selected alleles display a pattern across replicates, which differs both from neutrality and directional selection. We conclude that replicated time series data from experimental evolution studies provide a promising framework to study polygenic adaptation from whole-genome population genetics data.

Marker-based quantitative genetics in the wild?: the heritability and genetic correlation of chemical defenses in eucalyptus.

PubMed

Andrew, R L; Peakall, R; Wallis, I R; Wood, J T; Knight, E J; Foley, W J

2005-12-01

Marker-based methods for estimating heritability and genetic correlation in the wild have attracted interest because traditional methods may be impractical or introduce bias via G x E effects, mating system variation, and sampling effects. However, they have not been widely used, especially in plants. A regression-based approach, which uses a continuous measure of genetic relatedness, promises to be particularly appropriate for use in plants with mixed-mating systems and overlapping generations. Using this method, we found significant narrow-sense heritability of foliar defense chemicals in a natural population of Eucalyptus melliodora. We also demonstrated a genetic basis for the phenotypic correlation underlying an ecological example of conditioned flavor aversion involving different biosynthetic pathways. Our results revealed that heritability estimates depend on the spatial scale of the analysis in a way that offers insight into the distribution of genetic and environmental variance. This study is the first to successfully use a marker-based method to measure quantitative genetic parameters in a tree. We suggest that this method will prove to be a useful tool in other studies and offer some recommendations for future applications of the method.

Statistical genetics and evolution of quantitative traits

NASA Astrophysics Data System (ADS)

Neher, Richard A.; Shraiman, Boris I.

2011-10-01

The distribution and heritability of many traits depends on numerous loci in the genome. In general, the astronomical number of possible genotypes makes the system with large numbers of loci difficult to describe. Multilocus evolution, however, greatly simplifies in the limit of weak selection and frequent recombination. In this limit, populations rapidly reach quasilinkage equilibrium (QLE) in which the dynamics of the full genotype distribution, including correlations between alleles at different loci, can be parametrized by the allele frequencies. This review provides a simplified exposition of the concept and mathematics of QLE which is central to the statistical description of genotypes in sexual populations. Key results of quantitative genetics such as the generalized Fisher’s “fundamental theorem,” along with Wright’s adaptive landscape, are shown to emerge within QLE from the dynamics of the genotype distribution. This is followed by a discussion under what circumstances QLE is applicable, and what the breakdown of QLE implies for the population structure and the dynamics of selection. Understanding the fundamental aspects of multilocus evolution obtained through simplified models may be helpful in providing conceptual and computational tools to address the challenges arising in the studies of complex quantitative phenotypes of practical interest.

Quantitative PCR for Detection and Enumeration of Genetic Markers of Bovine Fecal Pollution

EPA Science Inventory

Accurate assessment of health risks associated with bovine (cattle) fecal pollution requires a reliable host-specific genetic marker and a rapid quantification method. We report the development of quantitative PCR assays for the detection of two recently described cow feces-spec...

Interest in and reactions to genetic risk information: The role of implicit theories and self-affirmation.

PubMed

Taber, Jennifer M; Klein, William M P; Persky, Susan; Ferrer, Rebecca A; Kaufman, Annette R; Thai, Chan L; Harris, Peter R

2017-10-01

Implicit theories reflect core assumptions about whether human attributes are malleable or fixed: Incremental theorists believe a characteristic is malleable whereas entity theorists believe it is fixed. People with entity theories about health may be less likely to engage in risk-mitigating behavior. Spontaneous self-affirmation (e.g., reflecting on one's values when threatened) may lessen defensiveness and unhealthy behaviors associated with fixed beliefs, and reduce the likelihood of responding to health risk information with fixed beliefs. Across two studies conducted in the US from 2012 to 2015, we investigated how self-affirmation and implicit theories about health and body weight were linked to engagement with genetic risk information. In Study 1, participants in a genome sequencing trial (n = 511) completed cross-sectional assessments of implicit theories, self-affirmation, and intentions to learn, share, and use genetic information. In Study 2, overweight women (n = 197) were randomized to receive genetic or behavioral explanations for weight; participants completed surveys assessing implicit theories, self-affirmation, self-efficacy, motivation, and intentions. Fixed beliefs about weight were infrequently endorsed across studies (10.8-15.2%). In Study 1, participants with stronger fixed theories were less interested in learning and using genetic risk information about medically actionable disease; these associations were weaker among participants higher in self-affirmation. In Study 2, among participants given behavioral explanations for weight, stronger fixed theories about weight were associated with lower motivation and intentions to eat a healthy diet. Among participants given genetic explanations, being higher in self-affirmation was associated with less fixed beliefs. Stronger health-related fixed theories may decrease the likelihood of benefiting from genetic information, but less so for people who self-affirm. Published by Elsevier Ltd.

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

Evaluation of an ensemble of genetic models for prediction of a quantitative trait.

PubMed

Milton, Jacqueline N; Steinberg, Martin H; Sebastiani, Paola

2014-01-01

Many genetic markers have been shown to be associated with common quantitative traits in genome-wide association studies. Typically these associated genetic markers have small to modest effect sizes and individually they explain only a small amount of the variability of the phenotype. In order to build a genetic prediction model without fitting a multiple linear regression model with possibly hundreds of genetic markers as predictors, researchers often summarize the joint effect of risk alleles into a genetic score that is used as a covariate in the genetic prediction model. However, the prediction accuracy can be highly variable and selecting the optimal number of markers to be included in the genetic score is challenging. In this manuscript we present a strategy to build an ensemble of genetic prediction models from data and we show that the ensemble-based method makes the challenge of choosing the number of genetic markers more amenable. Using simulated data with varying heritability and number of genetic markers, we compare the predictive accuracy and inclusion of true positive and false positive markers of a single genetic prediction model and our proposed ensemble method. The results show that the ensemble of genetic models tends to include a larger number of genetic variants than a single genetic model and it is more likely to include all of the true genetic markers. This increased sensitivity is obtained at the price of a lower specificity that appears to minimally affect the predictive accuracy of the ensemble.

The Genetic Theory of Infectious Diseases: A Brief History and Selected Illustrations

PubMed Central

Casanova, Jean-Laurent; Abel, Laurent

2016-01-01

Until the mid-nineteenth century, life expectancy at birth averaged 20 years worldwide, owing mostly to childhood fevers. The germ theory of diseases then gradually overcame the belief that diseases were intrinsic. However, around the turn of the twentieth century, asymptomatic infection was discovered to be much more common than clinical disease. Paradoxically, this observation barely challenged the newly developed notion that infectious diseases were fundamentally extrinsic. Moreover, interindividual variability in the course of infection was typically explained by the emerging immunological (or somatic) theory of infectious diseases, best illustrated by the impact of vaccination. This powerful explanation is, however, best applicable to reactivation and secondary infections, particularly in adults; it can less easily account for interindividual variability in the course of primary infection during childhood. Population and clinical geneticists soon proposed a complementary hypothesis, a germline genetic theory of infectious diseases. Over the past century, this idea has gained some support, particularly among clinicians and geneticists, but has also encountered resistance, particularly among microbiologists and immunologists. We present here the genetic theory of infectious diseases and briefly discuss its history and the challenges encountered during its emergence in the context of the apparently competing but actually complementary microbiological and immunological theories. We also illustrate its recent achievements by highlighting inborn errors of immunity underlying eight life-threatening infectious diseases of children and young adults. Finally, we consider the far-reaching biological and clinical implications of the ongoing human genetic dissection of severe infectious diseases. PMID:23724903

The genetic theory of infectious diseases: a brief history and selected illustrations.

PubMed

Casanova, Jean-Laurent; Abel, Laurent

2013-01-01

Until the mid-nineteenth century, life expectancy at birth averaged 20 years worldwide, owing mostly to childhood fevers. The germ theory of diseases then gradually overcame the belief that diseases were intrinsic. However, around the turn of the twentieth century, asymptomatic infection was discovered to be much more common than clinical disease. Paradoxically, this observation barely challenged the newly developed notion that infectious diseases were fundamentally extrinsic. Moreover, interindividual variability in the course of infection was typically explained by the emerging immunological (or somatic) theory of infectious diseases, best illustrated by the impact of vaccination. This powerful explanation is, however, best applicable to reactivation and secondary infections, particularly in adults; it can less easily account for interindividual variability in the course of primary infection during childhood. Population and clinical geneticists soon proposed a complementary hypothesis, a germline genetic theory of infectious diseases. Over the past century, this idea has gained some support, particularly among clinicians and geneticists, but has also encountered resistance, particularly among microbiologists and immunologists. We present here the genetic theory of infectious diseases and briefly discuss its history and the challenges encountered during its emergence in the context of the apparently competing but actually complementary microbiological and immunological theories. We also illustrate its recent achievements by highlighting inborn errors of immunity underlying eight life-threatening infectious diseases of children and young adults. Finally, we consider the far-reaching biological and clinical implications of the ongoing human genetic dissection of severe infectious diseases.

Can sexual selection theory inform genetic management of captive populations? A review

PubMed Central

Chargé, Rémi; Teplitsky, Céline; Sorci, Gabriele; Low, Matthew

2014-01-01

Captive breeding for conservation purposes presents a serious practical challenge because several conflicting genetic processes (i.e., inbreeding depression, random genetic drift and genetic adaptation to captivity) need to be managed in concert to maximize captive population persistence and reintroduction success probability. Because current genetic management is often only partly successful in achieving these goals, it has been suggested that management insights may be found in sexual selection theory (in particular, female mate choice). We review the theoretical and empirical literature and consider how female mate choice might influence captive breeding in the context of current genetic guidelines for different sexual selection theories (i.e., direct benefits, good genes, compatible genes, sexy sons). We show that while mate choice shows promise as a tool in captive breeding under certain conditions, for most species, there is currently too little theoretical and empirical evidence to provide any clear guidelines that would guarantee positive fitness outcomes and avoid conflicts with other genetic goals. The application of female mate choice to captive breeding is in its infancy and requires a goal-oriented framework based on the needs of captive species management, so researchers can make honest assessments of the costs and benefits of such an approach, using simulations, model species and captive animal data. PMID:25553072

[Evolutionary process unveiled by the maximum genetic diversity hypothesis].

PubMed

Huang, Yi-Min; Xia, Meng-Ying; Huang, Shi

2013-05-01

As two major popular theories to explain evolutionary facts, the neutral theory and Neo-Darwinism, despite their proven virtues in certain areas, still fail to offer comprehensive explanations to such fundamental evolutionary phenomena as the genetic equidistance result, abundant overlap sites, increase in complexity over time, incomplete understanding of genetic diversity, and inconsistencies with fossil and archaeological records. Maximum genetic diversity hypothesis (MGD), however, constructs a more complete evolutionary genetics theory that incorporates all of the proven virtues of existing theories and adds to them the novel concept of a maximum or optimum limit on genetic distance or diversity. It has yet to meet a contradiction and explained for the first time the half-century old Genetic Equidistance phenomenon as well as most other major evolutionary facts. It provides practical and quantitative ways of studying complexity. Molecular interpretation using MGD-based methods reveal novel insights on the origins of humans and other primates that are consistent with fossil evidence and common sense, and reestablished the important role of China in the evolution of humans. MGD theory has also uncovered an important genetic mechanism in the construction of complex traits and the pathogenesis of complex diseases. We here made a series of sequence comparisons among yeasts, fishes and primates to illustrate the concept of limit on genetic distance. The idea of limit or optimum is in line with the yin-yang paradigm in the traditional Chinese view of the universal creative law in nature.

Genetic Variants Associated With Quantitative Glucose Homeostasis Traits Translate to Type 2 Diabetes in Mexican Americans: The GUARDIAN (Genetics Underlying Diabetes in Hispanics) Consortium.

PubMed

Palmer, Nicholette D; Goodarzi, Mark O; Langefeld, Carl D; Wang, Nan; Guo, Xiuqing; Taylor, Kent D; Fingerlin, Tasha E; Norris, Jill M; Buchanan, Thomas A; Xiang, Anny H; Haritunians, Talin; Ziegler, Julie T; Williams, Adrienne H; Stefanovski, Darko; Cui, Jinrui; Mackay, Adrienne W; Henkin, Leora F; Bergman, Richard N; Gao, Xiaoyi; Gauderman, James; Varma, Rohit; Hanis, Craig L; Cox, Nancy J; Highland, Heather M; Below, Jennifer E; Williams, Amy L; Burtt, Noel P; Aguilar-Salinas, Carlos A; Huerta-Chagoya, Alicia; Gonzalez-Villalpando, Clicerio; Orozco, Lorena; Haiman, Christopher A; Tsai, Michael Y; Johnson, W Craig; Yao, Jie; Rasmussen-Torvik, Laura; Pankow, James; Snively, Beverly; Jackson, Rebecca D; Liu, Simin; Nadler, Jerry L; Kandeel, Fouad; Chen, Yii-Der I; Bowden, Donald W; Rich, Stephen S; Raffel, Leslie J; Rotter, Jerome I; Watanabe, Richard M; Wagenknecht, Lynne E

2015-05-01

Insulin sensitivity, insulin secretion, insulin clearance, and glucose effectiveness exhibit strong genetic components, although few studies have examined their genetic architecture or influence on type 2 diabetes (T2D) risk. We hypothesized that loci affecting variation in these quantitative traits influence T2D. We completed a multicohort genome-wide association study to search for loci influencing T2D-related quantitative traits in 4,176 Mexican Americans. Quantitative traits were measured by the frequently sampled intravenous glucose tolerance test (four cohorts) or euglycemic clamp (three cohorts), and random-effects models were used to test the association between loci and quantitative traits, adjusting for age, sex, and admixture proportions (Discovery). Analysis revealed a significant (P < 5.00 × 10(-8)) association at 11q14.3 (MTNR1B) with acute insulin response. Loci with P < 0.0001 among the quantitative traits were examined for translation to T2D risk in 6,463 T2D case and 9,232 control subjects of Mexican ancestry (Translation). Nonparametric meta-analysis of the Discovery and Translation cohorts identified significant associations at 6p24 (SLC35B3/TFAP2A) with glucose effectiveness/T2D, 11p15 (KCNQ1) with disposition index/T2D, and 6p22 (CDKAL1) and 11q14 (MTNR1B) with acute insulin response/T2D. These results suggest that T2D and insulin secretion and sensitivity have both shared and distinct genetic factors, potentially delineating genomic components of these quantitative traits that drive the risk for T2D. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

Genetic variation maintained in multilocus models of additive quantitative traits under stabilizing selection.

PubMed Central

Bürger, R; Gimelfarb, A

1999-01-01

Stabilizing selection for an intermediate optimum is generally considered to deplete genetic variation in quantitative traits. However, conflicting results from various types of models have been obtained. While classical analyses assuming a large number of independent additive loci with individually small effects indicated that no genetic variation is preserved under stabilizing selection, several analyses of two-locus models showed the contrary. We perform a complete analysis of a generalization of Wright's two-locus quadratic-optimum model and investigate numerically the ability of quadratic stabilizing selection to maintain genetic variation in additive quantitative traits controlled by up to five loci. A statistical approach is employed by choosing randomly 4000 parameter sets (allelic effects, recombination rates, and strength of selection) for a given number of loci. For each parameter set we iterate the recursion equations that describe the dynamics of gamete frequencies starting from 20 randomly chosen initial conditions until an equilibrium is reached, record the quantities of interest, and calculate their corresponding mean values. As the number of loci increases from two to five, the fraction of the genome expected to be polymorphic declines surprisingly rapidly, and the loci that are polymorphic increasingly are those with small effects on the trait. As a result, the genetic variance expected to be maintained under stabilizing selection decreases very rapidly with increased number of loci. The equilibrium structure expected under stabilizing selection on an additive trait differs markedly from that expected under selection with no constraints on genotypic fitness values. The expected genetic variance, the expected polymorphic fraction of the genome, as well as other quantities of interest, are only weakly dependent on the selection intensity and the level of recombination. PMID:10353920

Growth of wormlike micelles in nonionic surfactant solutions: Quantitative theory vs. experiment.

PubMed

Danov, Krassimir D; Kralchevsky, Peter A; Stoyanov, Simeon D; Cook, Joanne L; Stott, Ian P; Pelan, Eddie G

2018-06-01

Despite the considerable advances of molecular-thermodynamic theory of micelle growth, agreement between theory and experiment has been achieved only in isolated cases. A general theory that can provide self-consistent quantitative description of the growth of wormlike micelles in mixed surfactant solutions, including the experimentally observed high peaks in viscosity and aggregation number, is still missing. As a step toward the creation of such theory, here we consider the simplest system - nonionic wormlike surfactant micelles from polyoxyethylene alkyl ethers, C i E j . Our goal is to construct a molecular-thermodynamic model that is in agreement with the available experimental data. For this goal, we systematized data for the micelle mean mass aggregation number, from which the micelle growth parameter was determined at various temperatures. None of the available models can give a quantitative description of these data. We constructed a new model, which is based on theoretical expressions for the interfacial-tension, headgroup-steric and chain-conformation components of micelle free energy, along with appropriate expressions for the parameters of the model, including their temperature and curvature dependencies. Special attention was paid to the surfactant chain-conformation free energy, for which a new more general formula was derived. As a result, relatively simple theoretical expressions are obtained. All parameters that enter these expressions are known, which facilitates the theoretical modeling of micelle growth for various nonionic surfactants in excellent agreement with the experiment. The constructed model can serve as a basis that can be further upgraded to obtain quantitative description of micelle growth in more complicated systems, including binary and ternary mixtures of nonionic, ionic and zwitterionic surfactants, which determines the viscosity and stability of various formulations in personal-care and house-hold detergency. Copyright © 2018

DENSITY-DEPENDENT SELECTION ON CONTINUOUS CHARACTERS: A QUANTITATIVE GENETIC MODEL.

PubMed

Tanaka, Yoshinari

1996-10-01

A quantitative genetic model of density-dependent selection is presented and analysed with parameter values obtained from laboratory selection experiments conducted by Mueller and his coworkers. The ecological concept of r- and K-selection is formulated in terms of selection gradients on underlying phenotypic characters that influence the density-dependent measure of fitness. Hence the selection gradients on traits are decomposed into two components, one that changes in the direction to increase r, and one that changes in the direction to increase K. The relative importance of the two components is determined by temporal fluctuations in population density. The evolutionary rate of r and K (per-generation changes in r and K due to the genetic responses of the underlying traits) is also formulated. Numerical simulation has shown that with moderate genetic variances of the underlying characters, r and K can evolve rapidly and the evolutionary rate is influenced by synergistic interaction between characters that contribute to r and K. But strong r-selection can occur only with severe and continuous disturbances of populations so that the population density is kept low enough to prevent K-selection. © 1996 The Society for the Study of Evolution.

Population size is weakly related to quantitative genetic variation and trait differentiation in a stream fish.

PubMed

Wood, Jacquelyn L A; Tezel, Defne; Joyal, Destin; Fraser, Dylan J

2015-09-01

How population size influences quantitative genetic variation and differentiation among natural, fragmented populations remains unresolved. Small, isolated populations might occupy poor quality habitats and lose genetic variation more rapidly due to genetic drift than large populations. Genetic drift might furthermore overcome selection as population size decreases. Collectively, this might result in directional changes in additive genetic variation (VA ) and trait differentiation (QST ) from small to large population size. Alternatively, small populations might exhibit larger variation in VA and QST if habitat fragmentation increases variability in habitat types. We explored these alternatives by investigating VA and QST using nine fragmented populations of brook trout varying 50-fold in census size N (179-8416) and 10-fold in effective number of breeders, Nb (18-135). Across 15 traits, no evidence was found for consistent differences in VA and QST with population size and almost no evidence for increased variability of VA or QST estimates at small population size. This suggests that (i) small populations of some species may retain adaptive potential according to commonly adopted quantitative genetic measures and (ii) populations of varying sizes experience a variety of environmental conditions in nature, however extremely large studies are likely required before any firm conclusions can be made. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Metabolite profiling and quantitative genetics of natural variation for flavonoids in Arabidopsis

PubMed Central

Routaboul, Jean-Marc; Dubos, Christian; Beck, Gilles; Marquis, Catherine; Bidzinski, Przemyslaw; Loudet, Olivier; Lepiniec, Loïc

2012-01-01

Little is known about the range and the genetic bases of naturally occurring variation for flavonoids. Using Arabidopsis thaliana seed as a model, the flavonoid content of 41 accessions and two recombinant inbred line (RIL) sets derived from divergent accessions (Cvi-0×Col-0 and Bay-0×Shahdara) were analysed. These accessions and RILs showed mainly quantitative rather than qualitative changes. To dissect the genetic architecture underlying these differences, a quantitative trait locus (QTL) analysis was performed on the two segregating populations. Twenty-two flavonoid QTLs were detected that accounted for 11–64% of the observed trait variations, only one QTL being common to both RIL sets. Sixteen of these QTLs were confirmed and coarsely mapped using heterogeneous inbred families (HIFs). Three genes, namely TRANSPARENT TESTA (TT)7, TT15, and MYB12, were proposed to underlie their variations since the corresponding mutants and QTLs displayed similar specific flavonoid changes. Interestingly, most loci did not co-localize with any gene known to be involved in flavonoid metabolism. This latter result shows that novel functions have yet to be characterized and paves the way for their isolation. PMID:22442426

A population genetic interpretation of GWAS findings for human quantitative traits

PubMed Central

Bullaughey, Kevin; Hudson, Richard R.; Sella, Guy

2018-01-01

Human genome-wide association studies (GWASs) are revealing the genetic architecture of anthropomorphic and biomedical traits, i.e., the frequencies and effect sizes of variants that contribute to heritable variation in a trait. To interpret these findings, we need to understand how genetic architecture is shaped by basic population genetics processes—notably, by mutation, natural selection, and genetic drift. Because many quantitative traits are subject to stabilizing selection and because genetic variation that affects one trait often affects many others, we model the genetic architecture of a focal trait that arises under stabilizing selection in a multidimensional trait space. We solve the model for the phenotypic distribution and allelic dynamics at steady state and derive robust, closed-form solutions for summary statistics of the genetic architecture. Our results provide a simple interpretation for missing heritability and why it varies among traits. They predict that the distribution of variances contributed by loci identified in GWASs is well approximated by a simple functional form that depends on a single parameter: the expected contribution to genetic variance of a strongly selected site affecting the trait. We test this prediction against the results of GWASs for height and body mass index (BMI) and find that it fits the data well, allowing us to make inferences about the degree of pleiotropy and mutational target size for these traits. Our findings help to explain why the GWAS for height explains more of the heritable variance than the similarly sized GWAS for BMI and to predict the increase in explained heritability with study sample size. Considering the demographic history of European populations, in which these GWASs were performed, we further find that most of the associations they identified likely involve mutations that arose shortly before or during the Out-of-Africa bottleneck at sites with selection coefficients around s = 10−3. PMID

Genetic data analysis for plant and animal breeding

USDA-ARS?s Scientific Manuscript database

This book is an advanced textbook covering the application of quantitative genetics theory to analysis of actual data (both trait and DNA marker information) for breeding populations of crops, trees, and animals. Chapter 1 is an introduction to basic software used for trait data analysis. Chapter 2 ...

Filling the knowledge gap: Integrating quantitative genetics and genomics in graduate education and outreach

USDA-ARS?s Scientific Manuscript database

The genomics revolution provides vital tools to address global food security. Yet to be incorporated into livestock breeding, molecular techniques need to be integrated into a quantitative genetics framework. Within the U.S., with shrinking faculty numbers with the requisite skills, the capacity to ...

Quantitative Genetic Architecture at Latitudinal Range Boundaries: Reduced Variation but Higher Trait Independence.

PubMed

Paccard, Antoine; Van Buskirk, Josh; Willi, Yvonne

2016-05-01

Species distribution limits are hypothesized to be caused by small population size and limited genetic variation in ecologically relevant traits, but earlier studies have not evaluated genetic variation in multivariate phenotypes. We asked whether populations at the latitudinal edges of the distribution have altered quantitative genetic architecture of ecologically relevant traits compared with midlatitude populations. We calculated measures of evolutionary potential in nine Arabidopsis lyrata populations spanning the latitudinal range of the species in eastern and midwestern North America. Environments at the latitudinal extremes have reduced water availability, and therefore plants were assessed under wet and dry treatments. We estimated genetic variance-covariance (G-) matrices for 10 traits related to size, development, and water balance. Populations at southern and northern distribution edges had reduced levels of genetic variation across traits, but their G-matrices were more spherical; G-matrix orientation was unrelated to latitude. As a consequence, the predicted short-term response to selection was at least as strong in edge populations as in central populations. These results are consistent with genetic drift eroding variation and reducing the effectiveness of correlational selection at distribution margins. We conclude that genetic variation of isolated traits poorly predicts the capacity to evolve in response to multivariate selection and that the response to selection may frequently be greater than expected at species distribution margins because of genetic drift.

Improving breeding efficiency in potato using molecular and quantitative genetics.

PubMed

Slater, Anthony T; Cogan, Noel O I; Hayes, Benjamin J; Schultz, Lee; Dale, M Finlay B; Bryan, Glenn J; Forster, John W

2014-11-01

Potatoes are highly heterozygous and the conventional breeding of superior germplasm is challenging, but use of a combination of MAS and EBVs can accelerate genetic gain. Cultivated potatoes are highly heterozygous due to their outbreeding nature, and suffer acute inbreeding depression. Modern potato cultivars also exhibit tetrasomic inheritance. Due to this genetic heterogeneity, the large number of target traits and the specific requirements of commercial cultivars, potato breeding is challenging. A conventional breeding strategy applies phenotypic recurrent selection over a number of generations, a process which can take over 10 years. Recently, major advances in genetics and molecular biology have provided breeders with molecular tools to accelerate gains for some traits. Marker-assisted selection (MAS) can be effectively used for the identification of major genes and quantitative trait loci that exhibit large effects. There are also a number of complex traits of interest, such as yield, that are influenced by a large number of genes of individual small effect where MAS will be difficult to deploy. Progeny testing and the use of pedigree in the analysis can provide effective identification of the superior genetic factors that underpin these complex traits. Recently, it has been shown that estimated breeding values (EBVs) can be developed for complex potato traits. Using a combination of MAS and EBVs for simple and complex traits can lead to a significant reduction in the length of the breeding cycle for the identification of superior germplasm.

Quantitative genetic models of sexual conflict based on interacting phenotypes.

PubMed

Moore, Allen J; Pizzari, Tommaso

2005-05-01

Evolutionary conflict arises between reproductive partners when alternative reproductive opportunities are available. Sexual conflict can generate sexually antagonistic selection, which mediates sexual selection and intersexual coevolution. However, despite intense interest, the evolutionary implications of sexual conflict remain unresolved. We propose a novel theoretical approach to study the evolution of sexually antagonistic phenotypes based on quantitative genetics and the measure of social selection arising from male-female interactions. We consider the phenotype of one sex as both a genetically influenced evolving trait as well as the (evolving) social environment in which the phenotype of the opposite sex evolves. Several important points emerge from our analysis, including the relationship between direct selection on one sex and indirect effects through selection on the opposite sex. We suggest that the proposed approach may be a valuable tool to complement other theoretical approaches currently used to study sexual conflict. Most importantly, our approach highlights areas where additional empirical data can help clarify the role of sexual conflict in the evolutionary process.

"Genetically Engineered" Nanoelectronics

NASA Technical Reports Server (NTRS)

Klimeck, Gerhard; Salazar-Lazaro, Carlos H.; Stoica, Adrian; Cwik, Thomas

2000-01-01

The quantum mechanical functionality of nanoelectronic devices such as resonant tunneling diodes (RTDs), quantum well infrared-photodetectors (QWIPs), quantum well lasers, and heterostructure field effect transistors (HFETs) is enabled by material variations on an atomic scale. The design and optimization of such devices requires a fundamental understanding of electron transport in such dimensions. The Nanoelectronic Modeling Tool (NEMO) is a general-purpose quantum device design and analysis tool based on a fundamental non-equilibrium electron transport theory. NEW was combined with a parallelized genetic algorithm package (PGAPACK) to evolve structural and material parameters to match a desired set of experimental data. A numerical experiment that evolves structural variations such as layer widths and doping concentrations is performed to analyze an experimental current voltage characteristic. The genetic algorithm is found to drive the NEMO simulation parameters close to the experimentally prescribed layer thicknesses and doping profiles. With such a quantitative agreement between theory and experiment design synthesis can be performed.

Extension of nanoconfined DNA: Quantitative comparison between experiment and theory

NASA Astrophysics Data System (ADS)

Iarko, V.; Werner, E.; Nyberg, L. K.; Müller, V.; Fritzsche, J.; Ambjörnsson, T.; Beech, J. P.; Tegenfeldt, J. O.; Mehlig, K.; Westerlund, F.; Mehlig, B.

2015-12-01

The extension of DNA confined to nanochannels has been studied intensively and in detail. However, quantitative comparisons between experiments and model calculations are difficult because most theoretical predictions involve undetermined prefactors, and because the model parameters (contour length, Kuhn length, effective width) are difficult to compute reliably, leading to substantial uncertainties. Here we use a recent asymptotically exact theory for the DNA extension in the "extended de Gennes regime" that allows us to compare experimental results with theory. For this purpose, we performed experiments measuring the mean DNA extension and its standard deviation while varying the channel geometry, dye intercalation ratio, and ionic strength of the buffer. The experimental results agree very well with theory at high ionic strengths, indicating that the model parameters are reliable. At low ionic strengths, the agreement is less good. We discuss possible reasons. In principle, our approach allows us to measure the Kuhn length and the effective width of a single DNA molecule and more generally of semiflexible polymers in solution.

Genetic Complexity and Quantitative Trait Loci Mapping of Yeast Morphological Traits

PubMed Central

Nogami, Satoru; Ohya, Yoshikazu; Yvert, Gaël

2007-01-01

Functional genomics relies on two essential parameters: the sensitivity of phenotypic measures and the power to detect genomic perturbations that cause phenotypic variations. In model organisms, two types of perturbations are widely used. Artificial mutations can be introduced in virtually any gene and allow the systematic analysis of gene function via mutants fitness. Alternatively, natural genetic variations can be associated to particular phenotypes via genetic mapping. However, the access to genome manipulation and breeding provided by model organisms is sometimes counterbalanced by phenotyping limitations. Here we investigated the natural genetic diversity of Saccharomyces cerevisiae cellular morphology using a very sensitive high-throughput imaging platform. We quantified 501 morphological parameters in over 50,000 yeast cells from a cross between two wild-type divergent backgrounds. Extensive morphological differences were found between these backgrounds. The genetic architecture of the traits was complex, with evidence of both epistasis and transgressive segregation. We mapped quantitative trait loci (QTL) for 67 traits and discovered 364 correlations between traits segregation and inheritance of gene expression levels. We validated one QTL by the replacement of a single base in the genome. This study illustrates the natural diversity and complexity of cellular traits among natural yeast strains and provides an ideal framework for a genetical genomics dissection of multiple traits. Our results did not overlap with results previously obtained from systematic deletion strains, showing that both approaches are necessary for the functional exploration of genomes. PMID:17319748

The Development of Genetics in the Light of Thomas Kuhn's Theory of Scientific Revolutions.

PubMed

Portin, Petter

2015-01-01

The concept of a paradigm is in the key position in Thomas Kuhn's theory of scientific revolutions. A paradigm is the framework within which the results, concepts, hypotheses and theories of scientific research work are understood. According to Kuhn, a paradigm guides the working and efforts of scientists during the time period which he calls the period of normal science. Before long, however, normal science leads to unexplained matters, a situation that then leads the development of the scientific discipline in question to a paradigm shift--a scientific revolution. When a new theory is born, it has either gradually emerged as an extension of the past theory, or the old theory has become a borderline case in the new theory. In the former case, one can speak of a paradigm extension. According to the present author, the development of modern genetics has, until very recent years, been guided by a single paradigm, the Mendelian paradigm which Gregor Mendel launched 150 years ago, and under the guidance of this paradigm the development of genetics has proceeded in a normal fashion in the spirit of logical positivism. Modern discoveries in genetics have, however, created a situation which seems to be leading toward a paradigm shift. The most significant of these discoveries are the findings of adaptive mutations, the phenomenon of transgenerational epigenetic inheritance, and, above all, the present deeply critical state of the concept of the gene.

Overview of Classical Test Theory and Item Response Theory for Quantitative Assessment of Items in Developing Patient-Reported Outcome Measures

PubMed Central

Cappelleri, Joseph C.; Lundy, J. Jason; Hays, Ron D.

2014-01-01

Introduction The U.S. Food and Drug Administration’s patient-reported outcome (PRO) guidance document defines content validity as “the extent to which the instrument measures the concept of interest” (FDA, 2009, p. 12). “Construct validity is now generally viewed as a unifying form of validity for psychological measurements, subsuming both content and criterion validity” (Strauss & Smith, 2009, p. 7). Hence both qualitative and quantitative information are essential in evaluating the validity of measures. Methods We review classical test theory and item response theory approaches to evaluating PRO measures including frequency of responses to each category of the items in a multi-item scale, the distribution of scale scores, floor and ceiling effects, the relationship between item response options and the total score, and the extent to which hypothesized “difficulty” (severity) order of items is represented by observed responses. Conclusion Classical test theory and item response theory can be useful in providing a quantitative assessment of items and scales during the content validity phase of patient-reported outcome measures. Depending on the particular type of measure and the specific circumstances, either one or both approaches should be considered to help maximize the content validity of PRO measures. PMID:24811753

Application of Fault Management Theory to the Quantitative Selection of a Launch Vehicle Abort Trigger Suite

NASA Technical Reports Server (NTRS)

Lo, Yunnhon; Johnson, Stephen B.; Breckenridge, Jonathan T.

2014-01-01

This paper describes the quantitative application of the theory of System Health Management and its operational subset, Fault Management, to the selection of abort triggers for a human-rated launch vehicle, the United States' National Aeronautics and Space Administration's (NASA) Space Launch System (SLS). The results demonstrate the efficacy of the theory to assess the effectiveness of candidate failure detection and response mechanisms to protect humans from time-critical and severe hazards. The quantitative method was successfully used on the SLS to aid selection of its suite of abort triggers.

Application of Fault Management Theory to the Quantitative Selection of a Launch Vehicle Abort Trigger Suite

NASA Technical Reports Server (NTRS)

Lo, Yunnhon; Johnson, Stephen B.; Breckenridge, Jonathan T.

2014-01-01

This paper describes the quantitative application of the theory of System Health Management and its operational subset, Fault Management, to the selection of Abort Triggers for a human-rated launch vehicle, the United States' National Aeronautics and Space Administration's (NASA) Space Launch System (SLS). The results demonstrate the efficacy of the theory to assess the effectiveness of candidate failure detection and response mechanisms to protect humans from time-critical and severe hazards. The quantitative method was successfully used on the SLS to aid selection of its suite of Abort Triggers.

Extending Theory-Based Quantitative Predictions to New Health Behaviors.

PubMed

Brick, Leslie Ann D; Velicer, Wayne F; Redding, Colleen A; Rossi, Joseph S; Prochaska, James O

2016-04-01

Traditional null hypothesis significance testing suffers many limitations and is poorly adapted to theory testing. A proposed alternative approach, called Testing Theory-based Quantitative Predictions, uses effect size estimates and confidence intervals to directly test predictions based on theory. This paper replicates findings from previous smoking studies and extends the approach to diet and sun protection behaviors using baseline data from a Transtheoretical Model behavioral intervention (N = 5407). Effect size predictions were developed using two methods: (1) applying refined effect size estimates from previous smoking research or (2) using predictions developed by an expert panel. Thirteen of 15 predictions were confirmed for smoking. For diet, 7 of 14 predictions were confirmed using smoking predictions and 6 of 16 using expert panel predictions. For sun protection, 3 of 11 predictions were confirmed using smoking predictions and 5 of 19 using expert panel predictions. Expert panel predictions and smoking-based predictions poorly predicted effect sizes for diet and sun protection constructs. Future studies should aim to use previous empirical data to generate predictions whenever possible. The best results occur when there have been several iterations of predictions for a behavior, such as with smoking, demonstrating that expected values begin to converge on the population effect size. Overall, the study supports necessity in strengthening and revising theory with empirical data.

Using IBMs to Investigate Spatially-dependent Processes in Landscape Genetics Theory

EPA Science Inventory

Much of landscape and conservation genetics theory has been derived using non-spatialmathematical models. Here, we use a mechanistic, spatially-explicit, eco-evolutionary IBM to examine the utility of this theoretical framework in landscapes with spatial structure. Our analysis...

Quantitative and Comparative Profiling of Protease Substrates through a Genetically Encoded Multifunctional Photocrosslinker.

PubMed

He, Dan; Xie, Xiao; Yang, Fan; Zhang, Heng; Su, Haomiao; Ge, Yun; Song, Haiping; Chen, Peng R

2017-11-13

A genetically encoded, multifunctional photocrosslinker was developed for quantitative and comparative proteomics. By bearing a bioorthogonal handle and a releasable linker in addition to its photoaffinity warhead, this probe enables the enrichment of transient and low-abundance prey proteins after intracellular photocrosslinking and prey-bait separation, which can be subject to stable isotope dimethyl labeling and mass spectrometry analysis. This quantitative strategy (termed isoCAPP) allowed a comparative proteomic approach to be adopted to identify the proteolytic substrates of an E. coli protease-chaperone dual machinery DegP. Two newly identified substrates were subsequently confirmed by proteolysis experiments. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative genetic analysis of anxiety trait in bipolar disorder.

PubMed

Contreras, J; Hare, E; Chavarría, G; Raventós, H

2018-01-01

Bipolar disorder type I (BPI) affects approximately 1% of the world population. Although genetic influences on bipolar disorder are well established, identification of genes that predispose to the illness has been difficult. Most genetic studies are based on categorical diagnosis. One strategy to overcome this obstacle is the use of quantitative endophenotypes, as has been done for other medical disorders. We studied 619 individuals, 568 participants from 61 extended families and 51 unrelated healthy controls. The sample was 55% female and had a mean age of 43.25 (SD 13.90; range 18-78). Heritability and genetic correlation of the trait scale from the Anxiety State and Trait Inventory (STAI) was computed by using the general linear model (SOLAR package software). we observed that anxiety trait meets the following criteria for an endophenotype of bipolar disorder type I (BPI): 1) association with BPI (individuals with BPI showed the highest trait score (F = 15.20 [5,24], p = 0.009), 2) state-independence confirmed after conducting a test-retest in 321 subjects, 3) co-segregation within families 4) heritability of 0.70 (SE: 0.060), p = 2.33 × 10 -14 and 5) genetic correlation with BPI was 0.20, (SE = 0.17, p = 3.12 × 10 -5 ). Confounding factors such as comorbid disorders and pharmacological treatment could affect the clinical relationship between BPI and anxiety trait. Further research is needed to evaluate if anxiety traits are specially related to BPI in comparison with other traits such as anger, attention or response inhibition deficit, pathological impulsivity or low self-directedness. Anxiety trait is a heritable phenotype that follows a normal distribution when measured not only in subjects with BPI but also in unrelated healthy controls. It could be used as an endophenotype in BPI for the identification of genomic regions with susceptibility genes for this disorder. Published by Elsevier B.V.

Validation of PCR methods for quantitation of genetically modified plants in food.

PubMed

Hübner, P; Waiblinger, H U; Pietsch, K; Brodmann, P

2001-01-01

For enforcement of the recently introduced labeling threshold for genetically modified organisms (GMOs) in food ingredients, quantitative detection methods such as quantitative competitive (QC-PCR) and real-time PCR are applied by official food control laboratories. The experiences of 3 European food control laboratories in validating such methods were compared to describe realistic performance characteristics of quantitative PCR detection methods. The limit of quantitation (LOQ) of GMO-specific, real-time PCR was experimentally determined to reach 30-50 target molecules, which is close to theoretical prediction. Starting PCR with 200 ng genomic plant DNA, the LOQ depends primarily on the genome size of the target plant and ranges from 0.02% for rice to 0.7% for wheat. The precision of quantitative PCR detection methods, expressed as relative standard deviation (RSD), varied from 10 to 30%. Using Bt176 corn containing test samples and applying Bt176 specific QC-PCR, mean values deviated from true values by -7to 18%, with an average of 2+/-10%. Ruggedness of real-time PCR detection methods was assessed in an interlaboratory study analyzing commercial, homogeneous food samples. Roundup Ready soybean DNA contents were determined in the range of 0.3 to 36%, relative to soybean DNA, with RSDs of about 25%. Taking the precision of quantitative PCR detection methods into account, suitable sample plans and sample sizes for GMO analysis are suggested. Because quantitative GMO detection methods measure GMO contents of samples in relation to reference material (calibrants), high priority must be given to international agreements and standardization on certified reference materials.

Quantitative Genetic Modeling of the Parental Care Hypothesis for the Evolution of Endothermy

PubMed Central

Bacigalupe, Leonardo D.; Moore, Allen J.; Nespolo, Roberto F.; Rezende, Enrico L.; Bozinovic, Francisco

2017-01-01

There are two heuristic explanations proposed for the evolution of endothermy in vertebrates: a correlated response to selection for stable body temperatures, or as a correlated response to increased activity. Parental care has been suggested as a major driving force in this context given its impact on the parents' activity levels and energy budgets, and in the offspring's growth rates due to food provisioning and controlled incubation temperature. This results in a complex scenario involving multiple traits and transgenerational fitness benefits that can be hard to disentangle, quantify and ultimately test. Here we demonstrate how standard quantitative genetic models of maternal effects can be applied to study the evolution of endothermy, focusing on the interplay between daily energy expenditure (DEE) of the mother and growth rates of the offspring. Our model shows that maternal effects can dramatically exacerbate evolutionary responses to selection in comparison to regular univariate models (breeder's equation). This effect would emerge from indirect selection mediated by maternal effects concomitantly with a positive genetic covariance between DEE and growth rates. The multivariate nature of selection, which could favor a higher DEE, higher growth rates or both, might partly explain how high turnover rates were continuously favored in a self-reinforcing process. Overall, our quantitative genetic analysis provides support for the parental care hypothesis for the evolution of endothermy. We contend that much has to be gained from quantifying maternal and developmental effects on metabolic and thermoregulatory variation during adulthood. PMID:29311952

Genetic evolution, plasticity, and bet-hedging as adaptive responses to temporally autocorrelated fluctuating selection: A quantitative genetic model.

PubMed

Tufto, Jarle

2015-08-01

Adaptive responses to autocorrelated environmental fluctuations through evolution in mean reaction norm elevation and slope and an independent component of the phenotypic variance are analyzed using a quantitative genetic model. Analytic approximations expressing the mutual dependencies between all three response modes are derived and solved for the joint evolutionary outcome. Both genetic evolution in reaction norm elevation and plasticity are favored by slow temporal fluctuations, with plasticity, in the absence of microenvironmental variability, being the dominant evolutionary outcome for reasonable parameter values. For fast fluctuations, tracking of the optimal phenotype through genetic evolution and plasticity is limited. If residual fluctuations in the optimal phenotype are large and stabilizing selection is strong, selection then acts to increase the phenotypic variance (bet-hedging adaptive). Otherwise, canalizing selection occurs. If the phenotypic variance increases with plasticity through the effect of microenvironmental variability, this shifts the joint evolutionary balance away from plasticity in favor of genetic evolution. If microenvironmental deviations experienced by each individual at the time of development and selection are correlated, however, more plasticity evolves. The adaptive significance of evolutionary fluctuations in plasticity and the phenotypic variance, transient evolution, and the validity of the analytic approximations are investigated using simulations. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Quantitative genetic correlation between trait and preference supports a sexually selected sperm process

PubMed Central

Simmons, Leigh W.; Kotiaho, Janne S.

2007-01-01

Sperm show patterns of rapid and divergent evolution that are characteristic of sexual selection. Sperm competition has been proposed as an important selective agent in the evolution of sperm morphology. However, several comparative analyses have revealed evolutionary associations between sperm length and female reproductive tract morphology that suggest patterns of male–female coevolution. In the dung beetle Onthophagus taurus, males with short sperm have a fertilization advantage that depends on the size of the female's sperm storage organ, the spermatheca; large spermathecae select for short sperm. Sperm length is heritable and is genetically correlated with male condition. Here we report significant additive genetic variation and heritability for spermatheca size and genetic covariance between spermatheca size and sperm length predicted by both the “good-sperm” and “sexy-sperm” models of postcopulatory female preference. Our data thus provide quantitative genetic support for the role of a sexually selected sperm process in the evolutionary divergence of sperm morphology, in much the same manner as precopulatory female preferences drive the evolutionary divergence of male secondary sexual traits. PMID:17921254

Continuum theory of gene expression waves during vertebrate segmentation.

PubMed

Jörg, David J; Morelli, Luis G; Soroldoni, Daniele; Oates, Andrew C; Jülicher, Frank

2015-09-01

The segmentation of the vertebrate body plan during embryonic development is a rhythmic and sequential process governed by genetic oscillations. These genetic oscillations give rise to traveling waves of gene expression in the segmenting tissue. Here we present a minimal continuum theory of vertebrate segmentation that captures the key principles governing the dynamic patterns of gene expression including the effects of shortening of the oscillating tissue. We show that our theory can quantitatively account for the key features of segmentation observed in zebrafish, in particular the shape of the wave patterns, the period of segmentation and the segment length as a function of time.

Continuum theory of gene expression waves during vertebrate segmentation

PubMed Central

Jörg, David J; Morelli, Luis G; Soroldoni, Daniele; Oates, Andrew C; Jülicher, Frank

2015-01-01

Abstract The segmentation of the vertebrate body plan during embryonic development is a rhythmic and sequential process governed by genetic oscillations. These genetic oscillations give rise to traveling waves of gene expression in the segmenting tissue. Here we present a minimal continuum theory of vertebrate segmentation that captures the key principles governing the dynamic patterns of gene expression including the effects of shortening of the oscillating tissue. We show that our theory can quantitatively account for the key features of segmentation observed in zebrafish, in particular the shape of the wave patterns, the period of segmentation and the segment length as a function of time. PMID:28725158

Quantitative descriptions of generalized arousal, an elementary function of the vertebrate brain

PubMed Central

Quinkert, Amy Wells; Vimal, Vivek; Weil, Zachary M.; Reeke, George N.; Schiff, Nicholas D.; Banavar, Jayanth R.; Pfaff, Donald W.

2011-01-01

We review a concept of the most primitive, fundamental function of the vertebrate CNS, generalized arousal (GA). Three independent lines of evidence indicate the existence of GA: statistical, genetic, and mechanistic. Here we ask, is this concept amenable to quantitative analysis? Answering in the affirmative, four quantitative approaches have proven useful: (i) factor analysis, (ii) information theory, (iii) deterministic chaos, and (iv) application of a Gaussian equation. It strikes us that, to date, not just one but at least four different quantitative approaches seem necessary for describing different aspects of scientific work on GA. PMID:21555568

Inference and Analysis of Population Structure Using Genetic Data and Network Theory.

PubMed

Greenbaum, Gili; Templeton, Alan R; Bar-David, Shirli

2016-04-01

Clustering individuals to subpopulations based on genetic data has become commonplace in many genetic studies. Inference about population structure is most often done by applying model-based approaches, aided by visualization using distance-based approaches such as multidimensional scaling. While existing distance-based approaches suffer from a lack of statistical rigor, model-based approaches entail assumptions of prior conditions such as that the subpopulations are at Hardy-Weinberg equilibria. Here we present a distance-based approach for inference about population structure using genetic data by defining population structure using network theory terminology and methods. A network is constructed from a pairwise genetic-similarity matrix of all sampled individuals. The community partition, a partition of a network to dense subgraphs, is equated with population structure, a partition of the population to genetically related groups. Community-detection algorithms are used to partition the network into communities, interpreted as a partition of the population to subpopulations. The statistical significance of the structure can be estimated by using permutation tests to evaluate the significance of the partition's modularity, a network theory measure indicating the quality of community partitions. To further characterize population structure, a new measure of the strength of association (SA) for an individual to its assigned community is presented. The strength of association distribution (SAD) of the communities is analyzed to provide additional population structure characteristics, such as the relative amount of gene flow experienced by the different subpopulations and identification of hybrid individuals. Human genetic data and simulations are used to demonstrate the applicability of the analyses. The approach presented here provides a novel, computationally efficient model-free method for inference about population structure that does not entail assumption of

Genetic and environmental determinants of violence risk in psychotic disorders: a multivariate quantitative genetic study of 1.8 million Swedish twins and siblings

PubMed Central

Sariaslan, A; Larsson, H; Fazel, S

2016-01-01

Patients diagnosed with psychotic disorders (for example, schizophrenia and bipolar disorder) have elevated risks of committing violent acts, particularly if they are comorbid with substance misuse. Despite recent insights from quantitative and molecular genetic studies demonstrating considerable pleiotropy in the genetic architecture of these phenotypes, there is currently a lack of large-scale studies that have specifically examined the aetiological links between psychotic disorders and violence. Using a sample of all Swedish individuals born between 1958 and 1989 (n=3 332 101), we identified a total of 923 259 twin-sibling pairs. Patients were identified using the National Patient Register using validated algorithms based on International Classification of Diseases (ICD) 8–10. Univariate quantitative genetic models revealed that all phenotypes (schizophrenia, bipolar disorder, substance misuse, and violent crime) were highly heritable (h2=53–71%). Multivariate models further revealed that schizophrenia was a stronger predictor of violence (r=0.32; 95% confidence interval: 0.30–0.33) than bipolar disorder (r=0.23; 0.21–0.25), and large proportions (51–67%) of these phenotypic correlations were explained by genetic factors shared between each disorder, substance misuse, and violence. Importantly, we found that genetic influences that were unrelated to substance misuse explained approximately a fifth (21% 20–22%) of the correlation with violent criminality in bipolar disorder but none of the same correlation in schizophrenia (Pbipolar disorder<0.001; Pschizophrenia=0.55). These findings highlight the problems of not disentangling common and unique sources of covariance across genetically similar phenotypes as the latter sources may include aetiologically important clues. Clinically, these findings underline the importance of assessing risk of different phenotypes together and integrating interventions for psychiatric disorders, substance misuse, and

Genetic and environmental determinants of violence risk in psychotic disorders: a multivariate quantitative genetic study of 1.8 million Swedish twins and siblings.

PubMed

Sariaslan, A; Larsson, H; Fazel, S

2016-09-01

Patients diagnosed with psychotic disorders (for example, schizophrenia and bipolar disorder) have elevated risks of committing violent acts, particularly if they are comorbid with substance misuse. Despite recent insights from quantitative and molecular genetic studies demonstrating considerable pleiotropy in the genetic architecture of these phenotypes, there is currently a lack of large-scale studies that have specifically examined the aetiological links between psychotic disorders and violence. Using a sample of all Swedish individuals born between 1958 and 1989 (n=3 332 101), we identified a total of 923 259 twin-sibling pairs. Patients were identified using the National Patient Register using validated algorithms based on International Classification of Diseases (ICD) 8-10. Univariate quantitative genetic models revealed that all phenotypes (schizophrenia, bipolar disorder, substance misuse, and violent crime) were highly heritable (h(2)=53-71%). Multivariate models further revealed that schizophrenia was a stronger predictor of violence (r=0.32; 95% confidence interval: 0.30-0.33) than bipolar disorder (r=0.23; 0.21-0.25), and large proportions (51-67%) of these phenotypic correlations were explained by genetic factors shared between each disorder, substance misuse, and violence. Importantly, we found that genetic influences that were unrelated to substance misuse explained approximately a fifth (21%; 20-22%) of the correlation with violent criminality in bipolar disorder but none of the same correlation in schizophrenia (Pbipolar disorder<0.001; Pschizophrenia=0.55). These findings highlight the problems of not disentangling common and unique sources of covariance across genetically similar phenotypes as the latter sources may include aetiologically important clues. Clinically, these findings underline the importance of assessing risk of different phenotypes together and integrating interventions for psychiatric disorders, substance misuse, and violence.

Compatibility of breeding for increased wood production and longterm sustainability: the genetic variation of seed orchard seed and associated risks.

Treesearch

R Johnson; S. Lipow

2002-01-01

Because breeding imposes strong artificial selection for a narrow suite of economically important traits, genetic variation is reduced in seedlings derived from operational seed orchards. Both quantitative genetics theory and studies of allozyme variation show that seed orchards contain most of the genetic diversity found in natural populations, although low-frequency...

Evaluation of inbreeding in laying hens by applying optimum genetic contribution and gene flow theory.

PubMed

König, S; Tsehay, F; Sitzenstock, F; von Borstel, U U; Schmutz, M; Preisinger, R; Simianer, H

2010-04-01

Due to consistent increases of inbreeding of on average 0.95% per generation in layer populations, selection tools should consider both genetic gain and genetic relationships in the long term. The optimum genetic contribution theory using official estimated breeding values for egg production was applied for 3 different lines of a layer breeding program to find the optimal allocations of hens and sires. Constraints in different scenarios encompassed restrictions related to additive genetic relationships, the increase of inbreeding, the number of selected sires and hens, and the number of selected offspring per mating. All these constraints enabled higher genetic gain up to 10.9% at the same level of additive genetic relationships or in lower relationships at the same gain when compared with conventional selection schemes ignoring relationships. Increases of inbreeding and genetic gain were associated with the number of selected sires. For the lowest level of the allowed average relationship at 10%, the optimal number of sires was 70 and the estimated breeding value for egg production of the selected group was 127.9. At the highest relationship constraint (16%), the optimal number of sires decreased to 15, and the average genetic value increased to 139.7. Contributions from selected sires and hens were used to develop specific mating plans to minimize inbreeding in the following generation by applying a simulated annealing algorithm. The additional reduction of average additive genetic relationships for matings was up to 44.9%. An innovative deterministic approach to estimate kinship coefficients between and within defined selection groups based on gene flow theory was applied to compare increases of inbreeding from random matings with layer populations undergoing selection. Large differences in rates of inbreeding were found, and they underline the necessity to establish selection tools controlling long-term relationships. Furthermore, it was suggested to use

Real-time quantitative polymerase chain reaction methods for four genetically modified maize varieties and maize DNA content in food.

PubMed

Brodmann, Peter D; Ilg, Evelyn C; Berthoud, Hélène; Herrmann, Andre

2002-01-01

Quantitative detection methods are needed for enforcement of the recently introduced labeling threshold for genetically modified organisms (GMOs) in food ingredients. This labeling threshold, which is set to 1% in the European Union and Switzerland, must be applied to all approved GMOs. Four different varieties of maize are approved in the European Union: the insect-resistant Bt176 maize (Maximizer), Btl 1 maize, Mon810 (YieldGard) maize, and the herbicide-tolerant T25 (Liberty Link) maize. Because the labeling must be considered individually for each ingredient, a quantitation system for the endogenous maize content is needed in addition to the GMO-specific detection systems. Quantitative real-time polymerase chain reaction detection methods were developed for the 4 approved genetically modified maize varieties and for an endogenous maize (invertase) gene system.

Laboratory specimens and genetic privacy: evolution of legal theory.

PubMed

Lewis, Michelle Huckaby

2013-03-01

Although laboratory specimens are an important resource for biomedical research, controversy has arisen when research has been conducted without the knowledge or consent of the individuals who were the source of the specimens. This paper summarizes the most important litigation regarding the research use of laboratory specimens and traces the evolution of legal theory from property claims to claims related to genetic privacy interests. © 2013 American Society of Law, Medicine & Ethics, Inc.

Hybrid wheat: quantitative genetic parameters and consequences for the design of breeding programs.

PubMed

Longin, Carl Friedrich Horst; Gowda, Manje; Mühleisen, Jonathan; Ebmeyer, Erhard; Kazman, Ebrahim; Schachschneider, Ralf; Schacht, Johannes; Kirchhoff, Martin; Zhao, Yusheng; Reif, Jochen Christoph

2013-11-01

Commercial heterosis for grain yield is present in hybrid wheat but long-term competiveness of hybrid versus line breeding depends on the development of heterotic groups to improve hybrid prediction. Detailed knowledge of the amount of heterosis and quantitative genetic parameters are of paramount importance to assess the potential of hybrid breeding. Our objectives were to (1) examine the extent of midparent, better-parent and commercial heterosis in a vast population of 1,604 wheat (Triticum aestivum L.) hybrids and their parental elite inbred lines and (2) discuss the consequences of relevant quantitative parameters for the design of hybrid wheat breeding programs. Fifteen male lines were crossed in a factorial mating design with 120 female lines, resulting in 1,604 of the 1,800 potential single-cross hybrid combinations. The hybrids, their parents, and ten commercial wheat varieties were evaluated in multi-location field experiments for grain yield, plant height, heading time and susceptibility to frost, lodging, septoria tritici blotch, yellow rust, leaf rust, and powdery mildew at up to five locations. We observed that hybrids were superior to the mean of their parents for grain yield (10.7 %) and susceptibility to frost (-7.2 %), leaf rust (-8.4 %) and septoria tritici blotch (-9.3 %). Moreover, 69 hybrids significantly (P < 0.05) outyielded the best commercial inbred line variety underlining the potential of hybrid wheat breeding. The estimated quantitative genetic parameters suggest that the establishment of reciprocal recurrent selection programs is pivotal for a successful long-term hybrid wheat breeding.

An Interpretation of Part of Gilbert Gottlieb's Legacy: Developmental Systems Theory Contra Developmental Behavior Genetics

ERIC Educational Resources Information Center

Molenaar, Peter C. M.

2015-01-01

The main theme of this paper concerns the persistent critique of Gilbert Gottlieb on developmental behavior genetics and my reactions to this critique, the latter changing from rejection to complete acceptation. Concise characterizations of developmental behavior genetics, developmental systems theory (to which Gottlieb made essential…

Genetic approaches in comparative and evolutionary physiology

PubMed Central

Bridgham, Jamie T.; Kelly, Scott A.; Garland, Theodore

2015-01-01

Whole animal physiological performance is highly polygenic and highly plastic, and the same is generally true for the many subordinate traits that underlie performance capacities. Quantitative genetics, therefore, provides an appropriate framework for the analysis of physiological phenotypes and can be used to infer the microevolutionary processes that have shaped patterns of trait variation within and among species. In cases where specific genes are known to contribute to variation in physiological traits, analyses of intraspecific polymorphism and interspecific divergence can reveal molecular mechanisms of functional evolution and can provide insights into the possible adaptive significance of observed sequence changes. In this review, we explain how the tools and theory of quantitative genetics, population genetics, and molecular evolution can inform our understanding of mechanism and process in physiological evolution. For example, lab-based studies of polygenic inheritance can be integrated with field-based studies of trait variation and survivorship to measure selection in the wild, thereby providing direct insights into the adaptive significance of physiological variation. Analyses of quantitative genetic variation in selection experiments can be used to probe interrelationships among traits and the genetic basis of physiological trade-offs and constraints. We review approaches for characterizing the genetic architecture of physiological traits, including linkage mapping and association mapping, and systems approaches for dissecting intermediary steps in the chain of causation between genotype and phenotype. We also discuss the promise and limitations of population genomic approaches for inferring adaptation at specific loci. We end by highlighting the role of organismal physiology in the functional synthesis of evolutionary biology. PMID:26041111

Quantitative genetic models of sexual selection by male choice.

PubMed

Nakahashi, Wataru

2008-09-01

There are many examples of male mate choice for female traits that tend to be associated with high fertility. I develop quantitative genetic models of a female trait and a male preference to show when such a male preference can evolve. I find that a disagreement between the fertility maximum and the viability maximum of the female trait is necessary for directional male preference (preference for extreme female trait values) to evolve. Moreover, when there is a shortage of available male partners or variance in male nongenetic quality, strong male preference can evolve. Furthermore, I also show that males evolve to exhibit a stronger preference for females that are more feminine (less resemblance to males) than the average female when there is a sexual dimorphism caused by fertility selection which acts only on females.

Overview of classical test theory and item response theory for the quantitative assessment of items in developing patient-reported outcomes measures.

PubMed

Cappelleri, Joseph C; Jason Lundy, J; Hays, Ron D

2014-05-01

The US Food and Drug Administration's guidance for industry document on patient-reported outcomes (PRO) defines content validity as "the extent to which the instrument measures the concept of interest" (FDA, 2009, p. 12). According to Strauss and Smith (2009), construct validity "is now generally viewed as a unifying form of validity for psychological measurements, subsuming both content and criterion validity" (p. 7). Hence, both qualitative and quantitative information are essential in evaluating the validity of measures. We review classical test theory and item response theory (IRT) approaches to evaluating PRO measures, including frequency of responses to each category of the items in a multi-item scale, the distribution of scale scores, floor and ceiling effects, the relationship between item response options and the total score, and the extent to which hypothesized "difficulty" (severity) order of items is represented by observed responses. If a researcher has few qualitative data and wants to get preliminary information about the content validity of the instrument, then descriptive assessments using classical test theory should be the first step. As the sample size grows during subsequent stages of instrument development, confidence in the numerical estimates from Rasch and other IRT models (as well as those of classical test theory) would also grow. Classical test theory and IRT can be useful in providing a quantitative assessment of items and scales during the content-validity phase of PRO-measure development. Depending on the particular type of measure and the specific circumstances, the classical test theory and/or the IRT should be considered to help maximize the content validity of PRO measures. Copyright © 2014 Elsevier HS Journals, Inc. All rights reserved.

The genetical theory of social behaviour

PubMed Central

Lehmann, Laurent; Rousset, François

2014-01-01

We survey the population genetic basis of social evolution, using a logically consistent set of arguments to cover a wide range of biological scenarios. We start by reconsidering Hamilton's (Hamilton 1964 J. Theoret. Biol. 7, 1–16 (doi:10.1016/0022-5193(64)90038-4)) results for selection on a social trait under the assumptions of additive gene action, weak selection and constant environment and demography. This yields a prediction for the direction of allele frequency change in terms of phenotypic costs and benefits and genealogical concepts of relatedness, which holds for any frequency of the trait in the population, and provides the foundation for further developments and extensions. We then allow for any type of gene interaction within and between individuals, strong selection and fluctuating environments and demography, which may depend on the evolving trait itself. We reach three conclusions pertaining to selection on social behaviours under broad conditions. (i) Selection can be understood by focusing on a one-generation change in mean allele frequency, a computation which underpins the utility of reproductive value weights; (ii) in large populations under the assumptions of additive gene action and weak selection, this change is of constant sign for any allele frequency and is predicted by a phenotypic selection gradient; (iii) under the assumptions of trait substitution sequences, such phenotypic selection gradients suffice to characterize long-term multi-dimensional stochastic evolution, with almost no knowledge about the genetic details underlying the coevolving traits. Having such simple results about the effect of selection regardless of population structure and type of social interactions can help to delineate the common features of distinct biological processes. Finally, we clarify some persistent divergences within social evolution theory, with respect to exactness, synergies, maximization, dynamic sufficiency and the role of genetic arguments

The genetical theory of social behaviour.

PubMed

Lehmann, Laurent; Rousset, François

2014-05-19

We survey the population genetic basis of social evolution, using a logically consistent set of arguments to cover a wide range of biological scenarios. We start by reconsidering Hamilton's (Hamilton 1964 J. Theoret. Biol. 7, 1-16 (doi:10.1016/0022-5193(64)90038-4)) results for selection on a social trait under the assumptions of additive gene action, weak selection and constant environment and demography. This yields a prediction for the direction of allele frequency change in terms of phenotypic costs and benefits and genealogical concepts of relatedness, which holds for any frequency of the trait in the population, and provides the foundation for further developments and extensions. We then allow for any type of gene interaction within and between individuals, strong selection and fluctuating environments and demography, which may depend on the evolving trait itself. We reach three conclusions pertaining to selection on social behaviours under broad conditions. (i) Selection can be understood by focusing on a one-generation change in mean allele frequency, a computation which underpins the utility of reproductive value weights; (ii) in large populations under the assumptions of additive gene action and weak selection, this change is of constant sign for any allele frequency and is predicted by a phenotypic selection gradient; (iii) under the assumptions of trait substitution sequences, such phenotypic selection gradients suffice to characterize long-term multi-dimensional stochastic evolution, with almost no knowledge about the genetic details underlying the coevolving traits. Having such simple results about the effect of selection regardless of population structure and type of social interactions can help to delineate the common features of distinct biological processes. Finally, we clarify some persistent divergences within social evolution theory, with respect to exactness, synergies, maximization, dynamic sufficiency and the role of genetic arguments.

Inference and Analysis of Population Structure Using Genetic Data and Network Theory

PubMed Central

Greenbaum, Gili; Templeton, Alan R.; Bar-David, Shirli

2016-01-01

Clustering individuals to subpopulations based on genetic data has become commonplace in many genetic studies. Inference about population structure is most often done by applying model-based approaches, aided by visualization using distance-based approaches such as multidimensional scaling. While existing distance-based approaches suffer from a lack of statistical rigor, model-based approaches entail assumptions of prior conditions such as that the subpopulations are at Hardy-Weinberg equilibria. Here we present a distance-based approach for inference about population structure using genetic data by defining population structure using network theory terminology and methods. A network is constructed from a pairwise genetic-similarity matrix of all sampled individuals. The community partition, a partition of a network to dense subgraphs, is equated with population structure, a partition of the population to genetically related groups. Community-detection algorithms are used to partition the network into communities, interpreted as a partition of the population to subpopulations. The statistical significance of the structure can be estimated by using permutation tests to evaluate the significance of the partition’s modularity, a network theory measure indicating the quality of community partitions. To further characterize population structure, a new measure of the strength of association (SA) for an individual to its assigned community is presented. The strength of association distribution (SAD) of the communities is analyzed to provide additional population structure characteristics, such as the relative amount of gene flow experienced by the different subpopulations and identification of hybrid individuals. Human genetic data and simulations are used to demonstrate the applicability of the analyses. The approach presented here provides a novel, computationally efficient model-free method for inference about population structure that does not entail assumption of

The genetic basis of female multiple mating in a polyandrous livebearing fish

PubMed Central

Evans, Jonathan P; Gasparini, Clelia

2013-01-01

The widespread occurrence of female multiple mating (FMM) demands evolutionary explanation, particularly in the light of the costs of mating. One explanation encapsulated by “good sperm” and “sexy-sperm” (GS-SS) theoretical models is that FMM facilitates sperm competition, thus ensuring paternity by males that pass on genes for elevated sperm competitiveness to their male offspring. While support for this component of GS-SS theory is accumulating, a second but poorly tested assumption of these models is that there should be corresponding heritable genetic variation in FMM – the proposed mechanism of postcopulatory preferences underlying GS-SS models. Here, we conduct quantitative genetic analyses on paternal half-siblings to test this component of GS-SS theory in the guppy (Poecilia reticulata), a freshwater fish with some of the highest known rates of FMM in vertebrates. As with most previous quantitative genetic analyses of FMM in other species, our results reveal high levels of phenotypic variation in this trait and a correspondingly low narrow-sense heritability (h2 = 0.11). Furthermore, although our analysis of additive genetic variance in FMM was not statistically significant (probably owing to limited statistical power), the ensuing estimate of mean-standardized additive genetic variance (IA = 0.7) was nevertheless relatively low compared with estimates published for life-history traits across a broad range of taxa. Our results therefore add to a growing body of evidence that FMM is characterized by relatively low additive genetic variation, thus apparently contradicting GS-SS theory. However, we qualify this conclusion by drawing attention to potential deficiencies in most designs (including ours) that have tested for genetic variation in FMM, particularly those that fail to account for intersexual interactions that underlie FMM in many systems. PMID:23403856

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.

An assessment of the reliability of quantitative genetics estimates in study systems with high rate of extra-pair reproduction and low recruitment.

PubMed

Bourret, A; Garant, D

2017-03-01

Quantitative genetics approaches, and particularly animal models, are widely used to assess the genetic (co)variance of key fitness related traits and infer adaptive potential of wild populations. Despite the importance of precision and accuracy of genetic variance estimates and their potential sensitivity to various ecological and population specific factors, their reliability is rarely tested explicitly. Here, we used simulations and empirical data collected from an 11-year study on tree swallow (Tachycineta bicolor), a species showing a high rate of extra-pair paternity and a low recruitment rate, to assess the importance of identity errors, structure and size of the pedigree on quantitative genetic estimates in our dataset. Our simulations revealed an important lack of precision in heritability and genetic-correlation estimates for most traits, a low power to detect significant effects and important identifiability problems. We also observed a large bias in heritability estimates when using the social pedigree instead of the genetic one (deflated heritabilities) or when not accounting for an important cause of resemblance among individuals (for example, permanent environment or brood effect) in model parameterizations for some traits (inflated heritabilities). We discuss the causes underlying the low reliability observed here and why they are also likely to occur in other study systems. Altogether, our results re-emphasize the difficulties of generalizing quantitative genetic estimates reliably from one study system to another and the importance of reporting simulation analyses to evaluate these important issues.

Development and application of SINE multilocus and quantitative genetic markers to study oilseed rape (Brassica napus L.) crops.

PubMed

Allnutt, T R; Roper, K; Henry, C

2008-01-23

A genetic marker system based on the S1 Short Interspersed Elements (SINEs) in the important commercial crop, oilseed rape ( Brassica napus L.) has been developed. SINEs provided a successful multilocus, dominant marker system that was capable of clearly delineating winter- and spring-type crop varieties. Sixteen of 20 varieties tested showed unique profiles from the 17 polymorphic SINE markers generated. The 3' or 5' flank region of nine SINE markers were cloned, and DNA was sequenced. In addition, one putative pre-transposition SINE allele was cloned and sequenced. Two SINE flanking sequences were used to design real-time PCR assays. These quantitative SINE assays were applied to study the genetic structure of eight fields of oilseed rape crops. Studied fields were more genetically diverse than expected for the chosen loci (mean H T = 0.23). The spatial distribution of SINE marker frequencies was highly structured in some fields, suggesting locations of volunteer impurities within the crop. In one case, the assay identified a mislabeling of the crop variety. SINE markers were a useful tool for crop genetics, phylogenetics, variety identification, and purity analysis. The use and further application of quantitative, real-time PCR markers are discussed.

A quantitative theory of the functions of the hippocampal CA3 network in memory

PubMed Central

Rolls, Edmund T.

2013-01-01

A quantitative computational theory of the operation of the hippocampal CA3 system as an autoassociation or attractor network used in episodic memory system is described. In this theory, the CA3 system operates as a single attractor or autoassociation network to enable rapid, one-trial, associations between any spatial location (place in rodents, or spatial view in primates) and an object or reward, and to provide for completion of the whole memory during recall from any part. The theory is extended to associations between time and object or reward to implement temporal order memory, also important in episodic memory. The dentate gyrus (DG) performs pattern separation by competitive learning to produce sparse representations suitable for setting up new representations in CA3 during learning, producing for example neurons with place-like fields from entorhinal cortex grid cells. The dentate granule cells produce by the very small number of mossy fiber (MF) connections to CA3 a randomizing pattern separation effect important during learning but not recall that separates out the patterns represented by CA3 firing to be very different from each other, which is optimal for an unstructured episodic memory system in which each memory must be kept distinct from other memories. The direct perforant path (pp) input to CA3 is quantitatively appropriate to provide the cue for recall in CA3, but not for learning. Tests of the theory including hippocampal subregion analyses and hippocampal NMDA receptor knockouts are described, and support the theory. PMID:23805074

Quantitative analysis of terahertz spectra for illicit drugs using adaptive-range micro-genetic algorithm

NASA Astrophysics Data System (ADS)

Chen, Yi; Ma, Yong; Lu, Zheng; Peng, Bei; Chen, Qin

2011-08-01

In the field of anti-illicit drug applications, many suspicious mixture samples might consist of various drug components—for example, a mixture of methamphetamine, heroin, and amoxicillin—which makes spectral identification very difficult. A terahertz spectroscopic quantitative analysis method using an adaptive range micro-genetic algorithm with a variable internal population (ARVIPɛμGA) has been proposed. Five mixture cases are discussed using ARVIPɛμGA driven quantitative terahertz spectroscopic analysis in this paper. The devised simulation results show agreement with the previous experimental results, which suggested that the proposed technique has potential applications for terahertz spectral identifications of drug mixture components. The results show agreement with the results obtained using other experimental and numerical techniques.

A quantitative genetic analysis of hibernation emergence date in a wild population of Columbian ground squirrels.

PubMed

Lane, J E; Kruuk, L E B; Charmantier, A; Murie, J O; Coltman, D W; Buoro, M; Raveh, S; Dobson, F S

2011-09-01

The life history schedules of wild organisms have long attracted scientific interest, and, in light of ongoing climate change, an understanding of their genetic and environmental underpinnings is increasingly becoming of applied concern. We used a multi-generation pedigree and detailed phenotypic records, spanning 18 years, to estimate the quantitative genetic influences on the timing of hibernation emergence in a wild population of Columbian ground squirrels (Urocitellus columbianus). Emergence date was significantly heritable [h(2) = 0.22 ± 0.05 (in females) and 0.34 ± 0.14 (in males)], and there was a positive genetic correlation (r(G) = 0.76 ± 0.22) between male and female emergence dates. In adult females, the heritabilities of body mass at emergence and oestrous date were h(2) = 0.23 ± 0.09 and h(2) = 0.18 ± 0.12, respectively. The date of hibernation emergence has been hypothesized to have evolved so as to synchronize subsequent reproduction with upcoming peaks in vegetation abundance. In support of this hypothesis, although levels of phenotypic variance in emergence date were higher than oestrous date, there was a highly significant genetic correlation between the two (r(G) = 0.98 ± 0.01). Hibernation is a prominent feature in the annual cycle of many small mammals, but our understanding of its influences lags behind that for phenological traits in many other taxa. Our results provide the first insight into its quantitative genetic influences and thus help contribute to a more general understanding of its evolutionary significance. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

Decay Of Bacterial Pathogens, Fecal Indicators, And Real-Time Quantitative PCR Genetic Markers In Manure-Amended Soils

EPA Science Inventory

This study examined persistence and decay of bacterial pathogens, fecal indicator bacteria (FIB), and emerging real-time quantitative PCR (qPCR) genetic markers for rapid detection of fecal pollution in manure-amended agricultural soils. Known concentrations of transformed green...

Decay Of Bacterial Pathogen, Fecal Indicators, And Real-Time Quantitative PCR Genetic Markers In Manure Amended Soils

EPA Science Inventory

This study examined persistence and decay of bacterial pathogens, fecal indicator bacteria, and emerging real-time quantitative PCR (qPCR) genetic markers for rapid detection of fecal pollution in manre-amended agricultural soils. Known concentrations of transformed green fluore...

Genetic approaches in comparative and evolutionary physiology.

PubMed

Storz, Jay F; Bridgham, Jamie T; Kelly, Scott A; Garland, Theodore

2015-08-01

Whole animal physiological performance is highly polygenic and highly plastic, and the same is generally true for the many subordinate traits that underlie performance capacities. Quantitative genetics, therefore, provides an appropriate framework for the analysis of physiological phenotypes and can be used to infer the microevolutionary processes that have shaped patterns of trait variation within and among species. In cases where specific genes are known to contribute to variation in physiological traits, analyses of intraspecific polymorphism and interspecific divergence can reveal molecular mechanisms of functional evolution and can provide insights into the possible adaptive significance of observed sequence changes. In this review, we explain how the tools and theory of quantitative genetics, population genetics, and molecular evolution can inform our understanding of mechanism and process in physiological evolution. For example, lab-based studies of polygenic inheritance can be integrated with field-based studies of trait variation and survivorship to measure selection in the wild, thereby providing direct insights into the adaptive significance of physiological variation. Analyses of quantitative genetic variation in selection experiments can be used to probe interrelationships among traits and the genetic basis of physiological trade-offs and constraints. We review approaches for characterizing the genetic architecture of physiological traits, including linkage mapping and association mapping, and systems approaches for dissecting intermediary steps in the chain of causation between genotype and phenotype. We also discuss the promise and limitations of population genomic approaches for inferring adaptation at specific loci. We end by highlighting the role of organismal physiology in the functional synthesis of evolutionary biology. Copyright © 2015 the American Physiological Society.

Genetic variation affecting host-parasite interactions: major-effect quantitative trait loci affect the transmission of sigma virus in Drosophila melanogaster.

PubMed

Bangham, Jenny; Knott, Sara A; Kim, Kang-Wook; Young, Robert S; Jiggins, Francis M

2008-09-01

In natural populations, genetic variation affects resistance to disease. Whether that genetic variation comprises lots of small-effect polymorphisms or a small number of large-effect polymorphisms has implications for adaptation, selection and how genetic variation is maintained in populations. Furthermore, how much genetic variation there is, and the genes that underlie this variation, affects models of co-evolution between parasites and their hosts. We are studying the genetic variation that affects the resistance of Drosophila melanogaster to its natural pathogen--the vertically transmitted sigma virus. We have carried out three separate quantitative trait locus mapping analyses to map gene variants on the second chromosome that cause variation in the rate at which males transmit the infection to their offspring. All three crosses identified a locus in a similar chromosomal location that causes a large drop in the rate at which the virus is transmitted. We also found evidence for an additional smaller-effect quantitative trait locus elsewhere on the chromosome. Our data, together with previous experiments on the sigma virus and parasitoid wasps, indicate that the resistance of D. melanogaster to co-evolved pathogens is controlled by a limited number of major-effect polymorphisms.

Genetic perspectives on northern population cycles: bridging the gap between theory and empirical studies.

PubMed

Norén, Karin; Angerbjörn, Anders

2014-05-01

Many key species in northern ecosystems are characterised by high-amplitude cyclic population demography. In 1924, Charles Elton described the ecology and evolution of cyclic populations in a classic paper and, since then, a major focus has been the underlying causes of population cycles. Elton hypothesised that fluctuations reduced population genetic variation and influenced the direction of selection pressures. In concordance with Elton, present theories concern the direct consequences of population cycles for genetic structure due to the processes of genetic drift and selection, but also include feedback models of genetic composition on population dynamics. Most of these theories gained mathematical support during the 1970s and onwards, but due to methodological drawbacks, difficulties in long-term sampling and a complex interplay between microevolutionary processes, clear empirical data allowing the testing of these predictions are still scarce. Current genetic tools allow for estimates of genetic variation and identification of adaptive genomic regions, making this an ideal time to revisit this subject. Herein, we attempt to contribute towards a consensus regarding the enigma described by Elton almost 90 years ago. We present nine predictions covering the direct and genetic feedback consequences of population cycles on genetic variation and population structure, and review the empirical evidence. Generally, empirical support for the predictions was low and scattered, with obvious gaps in the understanding of basic population processes. We conclude that genetic variation in northern cyclic populations generally is high and that the geographic distribution and amount of diversity are usually suggested to be determined by various forms of context- and density-dependent dispersal exceeding the impact of genetic drift. Furthermore, we found few clear signatures of selection determining genetic composition in cyclic populations. Dispersal is assumed to have a strong

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

A formulation of the foundations of genetics and evolution.

PubMed

Bahr, Brian Edward

2016-05-01

This paper proposes a formulation of theories of the foundations of genetics and evolution that can be used to mathematically simulate phenotype expression, reproduction, mutation, and natural selection. It will be shown that Mendelian inheritance can be mathematically simulated with expressions involving matrices and that these expressions can also simulate phenomena that are modifications to Mendel's basic principles, like alleles that give rise to quantitative effects and traits that are the expression of multiple alleles and/or multiple genetic loci. Copyright © 2016 Elsevier Inc. All rights reserved.

Applications of graph theory to landscape genetics

PubMed Central

Garroway, Colin J; Bowman, Jeff; Carr, Denis; Wilson, Paul J

2008-01-01

We investigated the relationships among landscape quality, gene flow, and population genetic structure of fishers (Martes pennanti) in ON, Canada. We used graph theory as an analytical framework considering each landscape as a network node. The 34 nodes were connected by 93 edges. Network structure was characterized by a higher level of clustering than expected by chance, a short mean path length connecting all pairs of nodes, and a resiliency to the loss of highly connected nodes. This suggests that alleles can be efficiently spread through the system and that extirpations and conservative harvest are not likely to affect their spread. Two measures of node centrality were negatively related to both the proportion of immigrants in a node and node snow depth. This suggests that central nodes are producers of emigrants, contain high-quality habitat (i.e., deep snow can make locomotion energetically costly) and that fishers were migrating from high to low quality habitat. A method of community detection on networks delineated five genetic clusters of nodes suggesting cryptic population structure. Our analyses showed that network models can provide system-level insight into the process of gene flow with implications for understanding how landscape alterations might affect population fitness and evolutionary potential. PMID:25567802

Genetic background effects in quantitative genetics: gene-by-system interactions.

PubMed

Sardi, Maria; Gasch, Audrey P

2018-04-11

Proper cell function depends on networks of proteins that interact physically and functionally to carry out physiological processes. Thus, it seems logical that the impact of sequence variation in one protein could be significantly influenced by genetic variants at other loci in a genome. Nonetheless, the importance of such genetic interactions, known as epistasis, in explaining phenotypic variation remains a matter of debate in genetics. Recent work from our lab revealed that genes implicated from an association study of toxin tolerance in Saccharomyces cerevisiae show extensive interactions with the genetic background: most implicated genes, regardless of allele, are important for toxin tolerance in only one of two tested strains. The prevalence of background effects in our study adds to other reports of widespread genetic-background interactions in model organisms. We suggest that these effects represent many-way interactions with myriad features of the cellular system that vary across classes of individuals. Such gene-by-system interactions may influence diverse traits and require new modeling approaches to accurately represent genotype-phenotype relationships across individuals.

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.

Alzheimer’s Disease Neuroimaging Initiative biomarkers as quantitative phenotypes: Genetics core aims, progress, and plans

PubMed Central

Saykin, Andrew J.; Shen, Li; Foroud, Tatiana M.; Potkin, Steven G.; Swaminathan, Shanker; Kim, Sungeun; Risacher, Shannon L.; Nho, Kwangsik; Huentelman, Matthew J.; Craig, David W.; Thompson, Paul M.; Stein, Jason L.; Moore, Jason H.; Farrer, Lindsay A.; Green, Robert C.; Bertram, Lars; Jack, Clifford R.; Weiner, Michael W.

2010-01-01

The role of the Alzheimer’s Disease Neuroimaging Initiative Genetics Core is to facilitate the investigation of genetic influences on disease onset and trajectory as reflected in structural, functional, and molecular imaging changes; fluid biomarkers; and cognitive status. Major goals include (1) blood sample processing, genotyping, and dissemination, (2) genome-wide association studies (GWAS) of longitudinal phenotypic data, and (3) providing a central resource, point of contact and planning group for genetics within Alzheimer’s Disease Neuroimaging Initiative. Genome-wide array data have been publicly released and updated, and several neuroimaging GWAS have recently been reported examining baseline magnetic resonance imaging measures as quantitative phenotypes. Other preliminary investigations include copy number variation in mild cognitive impairment and Alzheimer’s disease and GWAS of baseline cerebrospinal fluid biomarkers and longitudinal changes on magnetic resonance imaging. Blood collection for RNA studies is a new direction. Genetic studies of longitudinal phenotypes hold promise for elucidating disease mechanisms and risk, development of therapeutic strategies, and refining selection criteria for clinical trials. PMID:20451875

Genetic constraints on adaptation: a theoretical primer for the genomics era.

PubMed

Connallon, Tim; Hall, Matthew D

2018-06-01

Genetic constraints are features of inheritance systems that slow or prohibit adaptation. Several population genetic mechanisms of constraint have received sustained attention within the field since they were first articulated in the early 20th century. This attention is now reflected in a rich, and still growing, theoretical literature on the genetic limits to adaptive change. In turn, empirical research on constraints has seen a rapid expansion over the last two decades in response to changing interests of evolutionary biologists, along with new technologies, expanding data sets, and creative analytical approaches that blend mathematical modeling with genomics. Indeed, one of the most notable and exciting features of recent progress in genetic constraints is the close connection between theoretical and empirical research. In this review, we discuss five major population genetic contexts of genetic constraint: genetic dominance, pleiotropy, fitness trade-offs between types of individuals of a population, sign epistasis, and genetic linkage between loci. For each, we outline historical antecedents of the theory, specific contexts where constraints manifest, and their quantitative consequences for adaptation. From each of these theoretical foundations, we discuss recent empirical approaches for identifying and characterizing genetic constraints, each grounded and motivated by this theory, and outline promising areas for future work. © 2018 New York Academy of Sciences.

Rotorcraft control system design for uncertain vehicle dynamics using quantitative feedback theory

NASA Technical Reports Server (NTRS)

Hess, R. A.

1994-01-01

Quantitative Feedback Theory describes a frequency-domain technique for the design of multi-input, multi-output control systems which must meet time or frequency domain performance criteria when specified uncertainty exists in the linear description of the vehicle dynamics. This theory is applied to the design of the longitudinal flight control system for a linear model of the BO-105C rotorcraft. Uncertainty in the vehicle model is due to the variation in the vehicle dynamics over a range of airspeeds from 0-100 kts. For purposes of exposition, the vehicle description contains no rotor or actuator dynamics. The design example indicates the manner in which significant uncertainty exists in the vehicle model. The advantage of using a sequential loop closure technique to reduce the cost of feedback is demonstrated by example.

Quantitative trait loci from the host genetic background modulate the durability of a resistance gene: a rational basis for sustainable resistance breeding in plants.

PubMed

Quenouille, J; Paulhiac, E; Moury, B; Palloix, A

2014-06-01

The combination of major resistance genes with quantitative resistance factors is hypothesized as a promising breeding strategy to preserve the durability of resistant cultivar, as recently observed in different pathosystems. Using the pepper (Capsicum annuum)/Potato virus Y (PVY, genus Potyvirus) pathosystem, we aimed at identifying plant genetic factors directly affecting the frequency of virus adaptation to the major resistance gene pvr2(3) and at comparing them with genetic factors affecting quantitative resistance. The resistance breakdown frequency was a highly heritable trait (h(2)=0.87). Four loci including additive quantitative trait loci (QTLs) and epistatic interactions explained together 70% of the variance of pvr2(3) breakdown frequency. Three of the four QTLs controlling pvr2(3) breakdown frequency were also involved in quantitative resistance, strongly suggesting that QTLs controlling quantitative resistance have a pleiotropic effect on the durability of the major resistance gene. With the first mapping of QTLs directly affecting resistance durability, this study provides a rationale for sustainable resistance breeding. Surprisingly, a genetic trade-off was observed between the durability of PVY resistance controlled by pvr2(3) and the spectrum of the resistance against different potyviruses. This trade-off seemed to have been resolved by the combination of minor-effect durability QTLs under long-term farmer selection.

"What is this genetics, anyway?" Understandings of genetics, illness causality and inheritance among British Pakistani users of genetic services.

PubMed

Shaw, Alison; Hurst, Jane A

2008-08-01

Misconceptions about basic genetic concepts and inheritance patterns may be widespread in the general population. This paper investigates understandings of genetics, illness causality and inheritance among British Pakistanis referred to a UK genetics clinic. During participant observation of genetics clinic consultations and semi-structured interviews in Urdu or English in respondents' homes, we identified an array of environmental, behavioral and spiritual understandings of the causes of medical and intellectual problems. Misconceptions about the location of genetic information in the body and of genetic mechanisms of inheritance were common, reflected the range of everyday theories observed for White British patients and included the belief that a child receives more genetic material from the father than the mother. Despite some participants' conversational use of genetic terminology, some patients had assimilated genetic information in ways that conflict with genetic theory with potentially serious clinical consequences. Additionally, skepticism of genetic theories of illness reflected a rejection of a dominant discourse of genetic risk that stigmatizes cousin marriages. Patients referred to genetics clinics may not easily surrender their lay or personal theories about the causes of their own or their child's condition and their understandings of genetic risk. Genetic counselors may need to identify, work with and at times challenge patients' understandings of illness causality and inheritance.

Quantitative Chemical-Genetic Interaction Map Connects Gene Alterations to Drug Responses | Office of Cancer Genomics

Cancer.gov

In a recent Cancer Discovery report, CTD2 researchers at the University of California in San Francisco developed a new quantitative chemical-genetic interaction mapping approach to evaluate drug sensitivity or resistance in isogenic cell lines. Performing a high-throughput screen with isogenic cell lines allowed the researchers to explore the impact of a panel of emerging and established drugs on cells overexpressing a single cancer-associated gene in isolation.

Rapid climate change and the rate of adaptation: insight from experimental quantitative genetics.

PubMed

Shaw, Ruth G; Etterson, Julie R

2012-09-01

Evolution proceeds unceasingly in all biological populations. It is clear that climate-driven evolution has molded plants in deep time and within extant populations. However, it is less certain whether adaptive evolution can proceed sufficiently rapidly to maintain the fitness and demographic stability of populations subjected to exceptionally rapid contemporary climate change. Here, we consider this question, drawing on current evidence on the rate of plant range shifts and the potential for an adaptive evolutionary response. We emphasize advances in understanding based on theoretical studies that model interacting evolutionary processes, and we provide an overview of quantitative genetic approaches that can parameterize these models to provide more meaningful predictions of the dynamic interplay between genetics, demography and evolution. We outline further research that can clarify both the adaptive potential of plant populations as climate continues to change and the role played by ongoing adaptation in their persistence. © 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.

The influence of genetic drift and selection on quantitative traits in a plant pathogenic fungus.

PubMed

Stefansson, Tryggvi S; McDonald, Bruce A; Willi, Yvonne

2014-01-01

Genetic drift and selection are ubiquitous evolutionary forces acting to shape genetic variation in populations. While their relative importance has been well studied in plants and animals, less is known about their relative importance in fungal pathogens. Because agro-ecosystems are more homogeneous environments than natural ecosystems, stabilizing selection may play a stronger role than genetic drift or diversifying selection in shaping genetic variation among populations of fungal pathogens in agro-ecosystems. We tested this hypothesis by conducting a QST/FST analysis using agricultural populations of the barley pathogen Rhynchosporium commune. Population divergence for eight quantitative traits (QST) was compared with divergence at eight neutral microsatellite loci (FST) for 126 pathogen strains originating from nine globally distributed field populations to infer the effects of genetic drift and types of selection acting on each trait. Our analyses indicated that five of the eight traits had QST values significantly lower than FST, consistent with stabilizing selection, whereas one trait, growth under heat stress (22°C), showed evidence of diversifying selection and local adaptation (QST>FST). Estimates of heritability were high for all traits (means ranging between 0.55-0.84), and average heritability across traits was negatively correlated with microsatellite gene diversity. Some trait pairs were genetically correlated and there was significant evidence for a trade-off between spore size and spore number, and between melanization and growth under benign temperature. Our findings indicate that many ecologically and agriculturally important traits are under stabilizing selection in R. commune and that high within-population genetic variation is maintained for these traits.

Genetic models of homosexuality: generating testable predictions

PubMed Central

Gavrilets, Sergey; Rice, William R

2006-01-01

Homosexuality is a common occurrence in humans and other species, yet its genetic and evolutionary basis is poorly understood. Here, we formulate and study a series of simple mathematical models for the purpose of predicting empirical patterns that can be used to determine the form of selection that leads to polymorphism of genes influencing homosexuality. Specifically, we develop theory to make contrasting predictions about the genetic characteristics of genes influencing homosexuality including: (i) chromosomal location, (ii) dominance among segregating alleles and (iii) effect sizes that distinguish between the two major models for their polymorphism: the overdominance and sexual antagonism models. We conclude that the measurement of the genetic characteristics of quantitative trait loci (QTLs) found in genomic screens for genes influencing homosexuality can be highly informative in resolving the form of natural selection maintaining their polymorphism. PMID:17015344

Quantitative estimation of time-variable earthquake hazard by using fuzzy set theory

NASA Astrophysics Data System (ADS)

Deyi, Feng; Ichikawa, M.

1989-11-01

In this paper, the various methods of fuzzy set theory, called fuzzy mathematics, have been applied to the quantitative estimation of the time-variable earthquake hazard. The results obtained consist of the following. (1) Quantitative estimation of the earthquake hazard on the basis of seismicity data. By using some methods of fuzzy mathematics, seismicity patterns before large earthquakes can be studied more clearly and more quantitatively, highly active periods in a given region and quiet periods of seismic activity before large earthquakes can be recognized, similarities in temporal variation of seismic activity and seismic gaps can be examined and, on the other hand, the time-variable earthquake hazard can be assessed directly on the basis of a series of statistical indices of seismicity. Two methods of fuzzy clustering analysis, the method of fuzzy similarity, and the direct method of fuzzy pattern recognition, have been studied is particular. One method of fuzzy clustering analysis is based on fuzzy netting, and another is based on the fuzzy equivalent relation. (2) Quantitative estimation of the earthquake hazard on the basis of observational data for different precursors. The direct method of fuzzy pattern recognition has been applied to research on earthquake precursors of different kinds. On the basis of the temporal and spatial characteristics of recognized precursors, earthquake hazards in different terms can be estimated. This paper mainly deals with medium-short-term precursors observed in Japan and China.

Limits to behavioral evolution: the quantitative genetics of a complex trait under directional selection.

PubMed

Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore

2013-11-01

Replicated selection experiments provide a powerful way to study how "multiple adaptive solutions" may lead to differences in the quantitative-genetic architecture of selected traits and whether this may translate into differences in the timing at which evolutionary limits are reached. We analyze data from 31 generations (n=17,988) of selection on voluntary wheel running in house mice. The rate of initial response, timing of selection limit, and height of the plateau varied significantly between sexes and among the four selected lines. Analyses of litter size and realized selection differentials seem to rule out counterposing natural selection as a cause of the selection limits. Animal-model analyses showed that although the additive genetic variance was significantly lower in selected than control lines, both before and after the limits, the decrease was not sufficient to explain the limits. Moreover, directional selection promoted a negative covariance between additive and maternal genetic variance over the first 10 generations. These results stress the importance of replication in selection studies of higher-level traits and highlight the fact that long-term predictions of response to selection are not necessarily expected to be linear because of the variable effects of selection on additive genetic variance and maternal effects. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Entering the second century of maize quantitative genetics

USDA-ARS?s Scientific Manuscript database

Maize is the most widely grown cereal in the world. In addition to its role in global agriculture, it has also long served as a model organism for genetic research. Maize stands at a genetic crossroads, as it has access to all the tools available for plant genetics but exhibits a genetic architectur...

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.

Quantitative genetic analysis of the bTB diagnostic single intradermal comparative cervical test (SICCT).

PubMed

Tsairidou, Smaragda; Brotherstone, Susan; Coffey, Mike; Bishop, Stephen C; Woolliams, John A

2016-11-24

Bovine tuberculosis (bTB) is a disease of significant economic importance and is a persistent animal health problem with implications for public health worldwide. Control of bTB in the UK has relied on diagnosis through the single intradermal comparative cervical test (SICCT). However, limitations in the sensitivity of this test hinder successful eradication and the control of bTB remains a major challenge. Genetic selection for cattle that are more resistant to bTB infection can assist in bTB control. The aim of this study was to conduct a quantitative genetic analysis of SICCT measurements collected during bTB herd testing. Genetic selection for bTB resistance will be partially informed by SICCT-based diagnosis; therefore it is important to know whether, in addition to increasing bTB resistance, this might also alter genetically the epidemiological characteristics of SICCT. Our main findings are that: (1) the SICCT test is robust at the genetic level, since its hierarchy and comparative nature provide substantial protection against random genetic changes that arise from genetic drift and from correlated responses among its components due to either natural or artificial selection; (2) the comparative nature of SICCT provides effective control for initial skin thickness and age-dependent differences; and (3) continuous variation in SICCT is only lowly heritable and has a weak correlation with SICCT positivity among healthy animals which was not significantly different from zero (P > 0.05). These emerging results demonstrate that genetic selection for bTB resistance is unlikely to change the probability of correctly identifying non-infected animals, i.e. the test's specificity, while reducing the overall number of cases. This study cannot exclude all theoretical risks from selection on resistance to bTB infection but the role of SICCT in disease control is unlikely to be rapidly undermined, with any adverse correlated responses expected to be weak and slow, which

Bigger Is Fitter? Quantitative Genetic Decomposition of Selection Reveals an Adaptive Evolutionary Decline of Body Mass in a Wild Rodent Population.

PubMed

Bonnet, Timothée; Wandeler, Peter; Camenisch, Glauco; Postma, Erik

2017-01-01

In natural populations, quantitative trait dynamics often do not appear to follow evolutionary predictions. Despite abundant examples of natural selection acting on heritable traits, conclusive evidence for contemporary adaptive evolution remains rare for wild vertebrate populations, and phenotypic stasis seems to be the norm. This so-called "stasis paradox" highlights our inability to predict evolutionary change, which is especially concerning within the context of rapid anthropogenic environmental change. While the causes underlying the stasis paradox are hotly debated, comprehensive attempts aiming at a resolution are lacking. Here, we apply a quantitative genetic framework to individual-based long-term data for a wild rodent population and show that despite a positive association between body mass and fitness, there has been a genetic change towards lower body mass. The latter represents an adaptive response to viability selection favouring juveniles growing up to become relatively small adults, i.e., with a low potential adult mass, which presumably complete their development earlier. This selection is particularly strong towards the end of the snow-free season, and it has intensified in recent years, coinciding which a change in snowfall patterns. Importantly, neither the negative evolutionary change, nor the selective pressures that drive it, are apparent on the phenotypic level, where they are masked by phenotypic plasticity and a non causal (i.e., non genetic) positive association between body mass and fitness, respectively. Estimating selection at the genetic level enabled us to uncover adaptive evolution in action and to identify the corresponding phenotypic selective pressure. We thereby demonstrate that natural populations can show a rapid and adaptive evolutionary response to a novel selective pressure, and that explicitly (quantitative) genetic models are able to provide us with an understanding of the causes and consequences of selection that is

Bigger Is Fitter? Quantitative Genetic Decomposition of Selection Reveals an Adaptive Evolutionary Decline of Body Mass in a Wild Rodent Population

PubMed Central

Wandeler, Peter; Camenisch, Glauco

2017-01-01

In natural populations, quantitative trait dynamics often do not appear to follow evolutionary predictions. Despite abundant examples of natural selection acting on heritable traits, conclusive evidence for contemporary adaptive evolution remains rare for wild vertebrate populations, and phenotypic stasis seems to be the norm. This so-called “stasis paradox” highlights our inability to predict evolutionary change, which is especially concerning within the context of rapid anthropogenic environmental change. While the causes underlying the stasis paradox are hotly debated, comprehensive attempts aiming at a resolution are lacking. Here, we apply a quantitative genetic framework to individual-based long-term data for a wild rodent population and show that despite a positive association between body mass and fitness, there has been a genetic change towards lower body mass. The latter represents an adaptive response to viability selection favouring juveniles growing up to become relatively small adults, i.e., with a low potential adult mass, which presumably complete their development earlier. This selection is particularly strong towards the end of the snow-free season, and it has intensified in recent years, coinciding which a change in snowfall patterns. Importantly, neither the negative evolutionary change, nor the selective pressures that drive it, are apparent on the phenotypic level, where they are masked by phenotypic plasticity and a non causal (i.e., non genetic) positive association between body mass and fitness, respectively. Estimating selection at the genetic level enabled us to uncover adaptive evolution in action and to identify the corresponding phenotypic selective pressure. We thereby demonstrate that natural populations can show a rapid and adaptive evolutionary response to a novel selective pressure, and that explicitly (quantitative) genetic models are able to provide us with an understanding of the causes and consequences of selection that is

Development and evaluation of event-specific quantitative PCR method for genetically modified soybean A2704-12.

PubMed

Takabatake, Reona; Akiyama, Hiroshi; Sakata, Kozue; Onishi, Mari; Koiwa, Tomohiro; Futo, Satoshi; Minegishi, Yasutaka; Teshima, Reiko; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

2011-01-01

A novel real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) soybean event; A2704-12. During the plant transformation, DNA fragments derived from pUC19 plasmid were integrated in A2704-12, and the region was found to be A2704-12 specific. The pUC19-derived DNA sequences were used as primers for the specific detection of A2704-12. We first tried to construct a standard plasmid for A2704-12 quantification using pUC19. However, non-specific signals appeared with both qualitative and quantitative PCR analyses using the specific primers with pUC19 as a template, and we then constructed a plasmid using pBR322. The conversion factor (C(f)), which is required to calculate the amount of the genetically modified organism (GMO), was experimentally determined with two real-time PCR instruments, the Applied Biosystems 7900HT and the Applied Biosystems 7500. The determined C(f) values were both 0.98. The quantitative method was evaluated by means of blind tests in multi-laboratory trials using the two real-time PCR instruments. The limit of quantitation for the method was estimated to be 0.1%. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSD(R)), and the determined bias and RSD(R) values for the method were each less than 20%. These results suggest that the developed method would be suitable for practical analyses for the detection and quantification of A2704-12.

Quantitative theory of driven nonlinear brain dynamics.

PubMed

Roberts, J A; Robinson, P A

2012-09-01

Strong periodic stimuli such as bright flashing lights evoke nonlinear responses in the brain and interact nonlinearly with ongoing cortical activity, but the underlying mechanisms for these phenomena are poorly understood at present. The dominant features of these experimentally observed dynamics are reproduced by the dynamics of a quantitative neural field model subject to periodic drive. Model power spectra over a range of drive frequencies show agreement with multiple features of experimental measurements, exhibiting nonlinear effects including entrainment over a range of frequencies around the natural alpha frequency f(α), subharmonic entrainment near 2f(α), and harmonic generation. Further analysis of the driven dynamics as a function of the drive parameters reveals rich nonlinear dynamics that is predicted to be observable in future experiments at high drive amplitude, including period doubling, bistable phase-locking, hysteresis, wave mixing, and chaos indicated by positive Lyapunov exponents. Moreover, photosensitive seizures are predicted for physiologically realistic model parameters yielding bistability between healthy and seizure dynamics. These results demonstrate the applicability of neural field models to the new regime of periodically driven nonlinear dynamics, enabling interpretation of experimental data in terms of specific generating mechanisms and providing new tests of the theory. Copyright © 2012 Elsevier Inc. All rights reserved.

Behavioural Susceptibility Theory: Professor Jane Wardle and the Role of Appetite in Genetic Risk of Obesity.

PubMed

Llewellyn, Clare H; Fildes, Alison

2017-03-01

There is considerable variability in human body weight, despite the ubiquity of the 'obesogenic' environment. Human body weight has a strong genetic basis and it has been hypothesised that genetic susceptibility to the environment explains variation in human body weight, with differences in appetite being implicated as the mediating mechanism; so-called 'behavioural susceptibility theory' (BST), first described by Professor Jane Wardle. This review summarises the evidence for the role of appetite as a mediator of genetic risk of obesity. Variation in appetitive traits is observable from infancy, drives early weight gain and is highly heritable in infancy and childhood. Obesity-related common genetic variants identified through genome-wide association studies show associations with appetitive traits, and appetite mediates part of the observed association between genetic risk and adiposity. Obesity results from an interaction between genetic susceptibility to overeating and exposure to an 'obesogenic' food environment.

A Quantitative Chemotherapy Genetic Interaction Map Reveals Factors Associated with PARP Inhibitor Resistance.

PubMed

Hu, Hsien-Ming; Zhao, Xin; Kaushik, Swati; Robillard, Lilliane; Barthelet, Antoine; Lin, Kevin K; Shah, Khyati N; Simmons, Andy D; Raponi, Mitch; Harding, Thomas C; Bandyopadhyay, Sourav

2018-04-17

Chemotherapy is used to treat most cancer patients, yet our understanding of factors that dictate response and resistance to such drugs remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells charting the impact of the knockdown of 625 genes related to cancer and DNA repair on sensitivity to 29 drugs, covering all classes of chemotherapy. This quantitative map is predictive of interactions maintained in other cell lines, identifies DNA-repair factors, predicts cancer cell line responses to therapy, and prioritizes synergistic drug combinations. We identify that ARID1A loss confers resistance to PARP inhibitors in cells and ovarian cancer patients and that loss of GPBP1 causes resistance to cisplatin and PARP inhibitors through the regulation of genes involved in homologous recombination. This map helps navigate patient genomic data and optimize chemotherapeutic regimens by delineating factors involved in the response to specific types of DNA damage. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Quantitative theory of hydrophobic effect as a driving force of protein structure

PubMed Central

Perunov, Nikolay; England, Jeremy L

2014-01-01

Various studies suggest that the hydrophobic effect plays a major role in driving the folding of proteins. In the past, however, it has been challenging to translate this understanding into a predictive, quantitative theory of how the full pattern of sequence hydrophobicity in a protein shapes functionally important features of its tertiary structure. Here, we extend and apply such a phenomenological theory of the sequence-structure relationship in globular protein domains, which had previously been applied to the study of allosteric motion. In an effort to optimize parameters for the model, we first analyze the patterns of backbone burial found in single-domain crystal structures, and discover that classic hydrophobicity scales derived from bulk physicochemical properties of amino acids are already nearly optimal for prediction of burial using the model. Subsequently, we apply the model to studying structural fluctuations in proteins and establish a means of identifying ligand-binding and protein–protein interaction sites using this approach. PMID:24408023

A robust rotorcraft flight control system design methodology utilizing quantitative feedback theory

NASA Technical Reports Server (NTRS)

Gorder, Peter James

1993-01-01

Rotorcraft flight control systems present design challenges which often exceed those associated with fixed-wing aircraft. First, large variations in the response characteristics of the rotorcraft result from the wide range of airspeeds of typical operation (hover to over 100 kts). Second, the assumption of vehicle rigidity often employed in the design of fixed-wing flight control systems is rarely justified in rotorcraft where rotor degrees of freedom can have a significant impact on the system performance and stability. This research was intended to develop a methodology for the design of robust rotorcraft flight control systems. Quantitative Feedback Theory (QFT) was chosen as the basis for the investigation. Quantitative Feedback Theory is a technique which accounts for variability in the dynamic response of the controlled element in the design robust control systems. It was developed to address a Multiple-Input Single-Output (MISO) design problem, and utilizes two degrees of freedom to satisfy the design criteria. Two techniques were examined for extending the QFT MISO technique to the design of a Multiple-Input-Multiple-Output (MIMO) flight control system (FCS) for a UH-60 Black Hawk Helicopter. In the first, a set of MISO systems, mathematically equivalent to the MIMO system, was determined. QFT was applied to each member of the set simultaneously. In the second, the same set of equivalent MISO systems were analyzed sequentially, with closed loop response information from each loop utilized in subsequent MISO designs. The results of each technique were compared, and the advantages of the second, termed Sequential Loop Closure, were clearly evident.

Inferring genetic interactions from comparative fitness data.

PubMed

Crona, Kristina; Gavryushkin, Alex; Greene, Devin; Beerenwinkel, Niko

2017-12-20

Darwinian fitness is a central concept in evolutionary biology. In practice, however, it is hardly possible to measure fitness for all genotypes in a natural population. Here, we present quantitative tools to make inferences about epistatic gene interactions when the fitness landscape is only incompletely determined due to imprecise measurements or missing observations. We demonstrate that genetic interactions can often be inferred from fitness rank orders, where all genotypes are ordered according to fitness, and even from partial fitness orders. We provide a complete characterization of rank orders that imply higher order epistasis. Our theory applies to all common types of gene interactions and facilitates comprehensive investigations of diverse genetic interactions. We analyzed various genetic systems comprising HIV-1, the malaria-causing parasite Plasmodium vivax , the fungus Aspergillus niger , and the TEM-family of β-lactamase associated with antibiotic resistance. For all systems, our approach revealed higher order interactions among mutations.

Global genetic architecture of an erythroid quantitative trait locus, HMIP-2.

PubMed

Menzel, Stephan; Rooks, Helen; Zelenika, Diana; Mtatiro, Siana N; Gnanakulasekaran, Akshala; Drasar, Emma; Cox, Sharon; Liu, Li; Masood, Mariam; Silver, Nicholas; Garner, Chad; Vasavda, Nisha; Howard, Jo; Makani, Julie; Adekile, Adekunle; Pace, Betty; Spector, Tim; Farrall, Martin; Lathrop, Mark; Thein, Swee Lay

2014-11-01

HMIP-2 is a human quantitative trait locus affecting peripheral numbers, size and hemoglobin composition of red blood cells, with a marked effect on the persistence of the fetal form of hemoglobin, HbF, in adults. The locus consists of multiple common variants in an enhancer region for MYB (chr 6q23.3), which encodes the hematopoietic transcription factor cMYB. Studying a European population cohort and four African-descended groups of patients with sickle cell anemia, we found that all share a set of two spatially separate HbF-promoting alleles at HMIP-2, termed "A" and "B." These typically occurred together ("A-B") on European chromosomes, but existed on separate homologous chromosomes in Africans. Using haplotype signatures for "A" and "B," we interrogated public population datasets. Haplotypes carrying only "A" or "B" were typical for populations in Sub-Saharan Africa. The "A-B" combination was frequent in European, Asian, and Amerindian populations. Both alleles were infrequent in tropical regions, possibly undergoing negative selection by geographical factors, as has been reported for malaria with other hematological traits. We propose that the ascertainment of worldwide distribution patterns for common, HbF-promoting alleles can aid their further genetic characterization, including the investigation of gene-environment interaction during human migration and adaptation. © 2014 The Authors. Annals of Human Genetics published by University College London (UCL) and John Wiley & Sons Ltd.

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

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.

PCR-free quantitative detection of genetically modified organism from raw materials. An electrochemiluminescence-based bio bar code method.

PubMed

Zhu, Debin; Tang, Yabing; Xing, Da; Chen, Wei R

2008-05-15

A bio bar code assay based on oligonucleotide-modified gold nanoparticles (Au-NPs) provides a PCR-free method for quantitative detection of nucleic acid targets. However, the current bio bar code assay requires lengthy experimental procedures including the preparation and release of bar code DNA probes from the target-nanoparticle complex and immobilization and hybridization of the probes for quantification. Herein, we report a novel PCR-free electrochemiluminescence (ECL)-based bio bar code assay for the quantitative detection of genetically modified organism (GMO) from raw materials. It consists of tris-(2,2'-bipyridyl) ruthenium (TBR)-labeled bar code DNA, nucleic acid hybridization using Au-NPs and biotin-labeled probes, and selective capture of the hybridization complex by streptavidin-coated paramagnetic beads. The detection of target DNA is realized by direct measurement of ECL emission of TBR. It can quantitatively detect target nucleic acids with high speed and sensitivity. This method can be used to quantitatively detect GMO fragments from real GMO products.

Quantitative Assessment of Eye Phenotypes for Functional Genetic Studies Using Drosophila melanogaster

PubMed Central

Iyer, Janani; Wang, Qingyu; Le, Thanh; Pizzo, Lucilla; Grönke, Sebastian; Ambegaokar, Surendra S.; Imai, Yuzuru; Srivastava, Ashutosh; Troisí, Beatriz Llamusí; Mardon, Graeme; Artero, Ruben; Jackson, George R.; Isaacs, Adrian M.; Partridge, Linda; Lu, Bingwei; Kumar, Justin P.; Girirajan, Santhosh

2016-01-01

About two-thirds of the vital genes in the Drosophila genome are involved in eye development, making the fly eye an excellent genetic system to study cellular function and development, neurodevelopment/degeneration, and complex diseases such as cancer and diabetes. We developed a novel computational method, implemented as Flynotyper software (http://flynotyper.sourceforge.net), to quantitatively assess the morphological defects in the Drosophila eye resulting from genetic alterations affecting basic cellular and developmental processes. Flynotyper utilizes a series of image processing operations to automatically detect the fly eye and the individual ommatidium, and calculates a phenotypic score as a measure of the disorderliness of ommatidial arrangement in the fly eye. As a proof of principle, we tested our method by analyzing the defects due to eye-specific knockdown of Drosophila orthologs of 12 neurodevelopmental genes to accurately document differential sensitivities of these genes to dosage alteration. We also evaluated eye images from six independent studies assessing the effect of overexpression of repeats, candidates from peptide library screens, and modifiers of neurotoxicity and developmental processes on eye morphology, and show strong concordance with the original assessment. We further demonstrate the utility of this method by analyzing 16 modifiers of sine oculis obtained from two genome-wide deficiency screens of Drosophila and accurately quantifying the effect of its enhancers and suppressors during eye development. Our method will complement existing assays for eye phenotypes, and increase the accuracy of studies that use fly eyes for functional evaluation of genes and genetic interactions. PMID:26994292

Genetics Home Reference: prostate cancer

MedlinePlus

... prostate cancer Genetic Testing Registry: Prostate cancer aggressiveness quantitative trait locus on chromosome 19 Genetic Testing Registry: ... OMIM (25 links) PROSTATE CANCER PROSTATE CANCER AGGRESSIVENESS QUANTITATIVE TRAIT LOCUS ON CHROMOSOME 19 PROSTATE CANCER ANTIGEN ...

Quantitative analysis of fatty-acid-based biofuels produced by wild-type and genetically engineered cyanobacteria by gas chromatography-mass spectrometry.

PubMed

Guan, Wenna; Zhao, Hui; Lu, Xuefeng; Wang, Cong; Yang, Menglong; Bai, Fali

2011-11-11

Simple and rapid quantitative determination of fatty-acid-based biofuels is greatly important for the study of genetic engineering progress for biofuels production by microalgae. Ideal biofuels produced from biological systems should be chemically similar to petroleum, like fatty-acid-based molecules including free fatty acids, fatty acid methyl esters, fatty acid ethyl esters, fatty alcohols and fatty alkanes. This study founded a gas chromatography-mass spectrometry (GC-MS) method for simultaneous quantification of seven free fatty acids, nine fatty acid methyl esters, five fatty acid ethyl esters, five fatty alcohols and three fatty alkanes produced by wild-type Synechocystis PCC 6803 and its genetically engineered strain. Data obtained from GC-MS analyses were quantified using internal standard peak area comparisons. The linearity, limit of detection (LOD) and precision (RSD) of the method were evaluated. The results demonstrated that fatty-acid-based biofuels can be directly determined by GC-MS without derivation. Therefore, rapid and reliable quantitative analysis of fatty-acid-based biofuels produced by wild-type and genetically engineered cyanobacteria can be achieved using the GC-MS method founded in this work. Copyright © 2011 Elsevier B.V. All rights reserved.

Genetic Diversity of Globally Dispersed Lacustrine Group I Haptophytes: Implications for Quantitative Temperature Reconstructions

NASA Astrophysics Data System (ADS)

Richter, N.; Longo, W. M.; Amaral-Zettler, L. A.; Huang, Y.

2017-12-01

There are significant uncertainties surrounding the forcings that drive terrestrial temperature changes on local and regional scales. Quantitative temperature reconstructions from terrestrial sites, such as lakes, help to unravel the fundamental processes that drive changes in temperature on different temporal and spatial scales. Recent studies at Brown University show that distinct alkenones, long chain ketones produced by haptophytes, are found in many freshwater, alkaline lakes in the Northern Hemisphere, highlighting these systems as targets for quantitative continental temperature reconstructions. These freshwater alkenones are produced by the Group I haptophyte phylotype and are characterized by a distinct signature: the presence of isomeric tri-unsaturated ketones and absence of alkenoates. There are currently no cultured representatives of the "Group I" haptophytes, hence they are only known based on their rRNA gene signatures. Here we present robust evidence that Northern Hemispheric freshwater, alkaline lakes with the characteristic "Group I" alkenone signature all host the same clade of Isochrysidales haptophytes. We employed next generation DNA amplicon sequencing to target haptophyte specific hypervariable regions of the large and small-subunit ribosomal RNA gene from 13 different lakes from three continents (i.e., North America, Europe, and Asia). Combined with previously published sequences, our genetic data show that the Group I haptophyte is genetically diverse on a regional and global scale, and even within the same lake. We present two case studies from a suite of five lakes in Alaska and three in Iceland to assess the impact of various environmental factors affecting Group I diversity and alkenone production. Despite the genetic diversity in this group, the overall ketone signature is conserved. Based on global surface sediment samples and in situ Alaskan lake calibrations, alkenones produced by different operational taxonomic units of the Group

The lack of foundation in the mechanism on which are based the physico-chemical theories for the origin of the genetic code is counterposed to the credible and natural mechanism suggested by the coevolution theory.

PubMed

Di Giulio, Massimo

2016-06-21

I analyze the mechanism on which are based the majority of theories that put to the center of the origin of the genetic code the physico-chemical properties of amino acids. As this mechanism is based on excessive mutational steps, I conclude that it could not have been operative or if operative it would not have allowed a full realization of predictions of these theories, because this mechanism contained, evidently, a high indeterminacy. I make that disapproving the four-column theory of the origin of the genetic code (Higgs, 2009) and reply to the criticism that was directed towards the coevolution theory of the origin of the genetic code. In this context, I suggest a new hypothesis that clarifies the mechanism by which the domains of codons of the precursor amino acids would have evolved, as predicted by the coevolution theory. This mechanism would have used particular elongation factors that would have constrained the evolution of all amino acids belonging to a given biosynthetic family to the progenitor pre-tRNA, that for first recognized, the first codons that evolved in a certain codon domain of a determined precursor amino acid. This happened because the elongation factors recognized two characteristics of the progenitor pre-tRNAs of precursor amino acids, which prevented the elongation factors from recognizing the pre-tRNAs belonging to biosynthetic families of different precursor amino acids. Finally, I analyze by means of Fisher's exact test, the distribution, within the genetic code, of the biosynthetic classes of amino acids and the ones of polarity values of amino acids. This analysis would seem to support the biosynthetic classes of amino acids over the ones of polarity values, as the main factor that led to the structuring of the genetic code, with the physico-chemical properties of amino acids playing only a subsidiary role in this evolution. As a whole, the full analysis brings to the conclusion that the coevolution theory of the origin of the

A Quantitative Chemotherapy Genetic Interaction Map Reveals Factors Associated with PARP Inhibitor Resistance. | Office of Cancer Genomics

Cancer.gov

Chemotherapy is used to treat most cancer patients, yet our understanding of factors that dictate response and resistance to such drugs remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells charting the impact of the knockdown of 625 genes related to cancer and DNA repair on sensitivity to 29 drugs, covering all classes of chemotherapy.

Making Quantitative Genetics Relevant: Effectiveness of a Laboratory Investigation that Links Scientific Research, Commercial Applications, and Legal Issues

ERIC Educational Resources Information Center

Rutledge, Michael L.; Mathis, Philip M.; Seipelt, Rebecca L.

2005-01-01

As students apply their knowledge of scientific concepts and of science as a method of inquiry, learning becomes relevant. This laboratory exercise is designed to foster students' understanding of the genetics of quantitative traits and of the nature of science as a method of inquiry by engaging them in a real-world business scenario. During the…

Quantitative genetics of circulating Hyaluronic Acid (HA) and its correlation with hand osteoarthritis and obesity-related phenotypes in a community-based sample.

PubMed

Prakash, Jai; Gabdulina, Gulzhan; Trofimov, Svetlana; Livshits, Gregory

2017-09-01

One of the potential molecular biomarkers of osteoarthritis (OA) is hyaluronic acid (HA). HA levels may be related to the severity and progression of OA. However, little is known about the contribution of major risk factors for osteoarthritis, e.g. obesity-related phenotypes and genetics to HA variation. To clarify the quantitative effect of these factors on HA. An ethnically homogeneous sample of 911 apparently healthy European-derived individuals, assessed for radiographic hand osteoarthritis (RHOA), HA, leptin, adiponectin, and several anthropometrical measures of obesity-related phenotypes was studied. Model-based quantitative genetic analysis was used to reveal genetic and shared environmental factors affecting the variation of the study's phenotypes. The HA levels significantly correlated with the age, RHOA, adiponectin, obesity-related phenotypes, and the waist-to-hip ratio. The putative genetic effects contributed significantly to the variation of HA (66.2 ± 9.3%) and they were also significant factors in the variations of all the other studied phenotypes, with the heritability estimate ranging between 0.122 ± 4.4% (WHR) and 45.7 ± 2.2% (joint space narrowing). This is the first study to report heritability estimates of HA variation and its correlation with obesity-related phenotypes, ADP and RHOA. However, the nature of genetic effects on HA and its correlation with other study phenotypes require further clarification.

Demand theory of gene regulation. II. Quantitative application to the lactose and maltose operons of Escherichia coli.

PubMed Central

Savageau, M A

1998-01-01

Induction of gene expression can be accomplished either by removing a restraining element (negative mode of control) or by providing a stimulatory element (positive mode of control). According to the demand theory of gene regulation, which was first presented in qualitative form in the 1970s, the negative mode will be selected for the control of a gene whose function is in low demand in the organism's natural environment, whereas the positive mode will be selected for the control of a gene whose function is in high demand. This theory has now been further developed in a quantitative form that reveals the importance of two key parameters: cycle time C, which is the average time for a gene to complete an ON/OFF cycle, and demand D, which is the fraction of the cycle time that the gene is ON. Here we estimate nominal values for the relevant mutation rates and growth rates and apply the quantitative demand theory to the lactose and maltose operons of Escherichia coli. The results define regions of the C vs. D plot within which selection for the wild-type regulatory mechanisms is realizable, and these in turn provide the first estimates for the minimum and maximum values of demand that are required for selection of the positive and negative modes of gene control found in these systems. The ratio of mutation rate to selection coefficient is the most relevant determinant of the realizable region for selection, and the most influential parameter is the selection coefficient that reflects the reduction in growth rate when there is superfluous expression of a gene. The quantitative theory predicts the rate and extent of selection for each mode of control. It also predicts three critical values for the cycle time. The predicted maximum value for the cycle time C is consistent with the lifetime of the host. The predicted minimum value for C is consistent with the time for transit through the intestinal tract without colonization. Finally, the theory predicts an optimum value

Quantitative structure-property relationship (QSPR) modeling of drug-loaded polymeric micelles via genetic function approximation.

PubMed

Wu, Wensheng; Zhang, Canyang; Lin, Wenjing; Chen, Quan; Guo, Xindong; Qian, Yu; Zhang, Lijuan

2015-01-01

Self-assembled nano-micelles of amphiphilic polymers represent a novel anticancer drug delivery system. However, their full clinical utilization remains challenging because the quantitative structure-property relationship (QSPR) between the polymer structure and the efficacy of micelles as a drug carrier is poorly understood. Here, we developed a series of QSPR models to account for the drug loading capacity of polymeric micelles using the genetic function approximation (GFA) algorithm. These models were further evaluated by internal and external validation and a Y-randomization test in terms of stability and generalization, yielding an optimization model that is applicable to an expanded materials regime. As confirmed by experimental data, the relationship between microstructure and drug loading capacity can be well-simulated, suggesting that our models are readily applicable to the quantitative evaluation of the drug-loading capacity of polymeric micelles. Our work may offer a pathway to the design of formulation experiments.

Coevolution Theory of the Genetic Code at Age Forty: Pathway to Translation and Synthetic Life

PubMed Central

Wong, J. Tze-Fei; Ng, Siu-Kin; Mat, Wai-Kin; Hu, Taobo; Xue, Hong

2016-01-01

The origins of the components of genetic coding are examined in the present study. Genetic information arose from replicator induction by metabolite in accordance with the metabolic expansion law. Messenger RNA and transfer RNA stemmed from a template for binding the aminoacyl-RNA synthetase ribozymes employed to synthesize peptide prosthetic groups on RNAs in the Peptidated RNA World. Coevolution of the genetic code with amino acid biosynthesis generated tRNA paralogs that identify a last universal common ancestor (LUCA) of extant life close to Methanopyrus, which in turn points to archaeal tRNA introns as the most primitive introns and the anticodon usage of Methanopyrus as an ancient mode of wobble. The prediction of the coevolution theory of the genetic code that the code should be a mutable code has led to the isolation of optional and mandatory synthetic life forms with altered protein alphabets. PMID:26999216

Investigating the genetic basis of theory of mind (ToM): the role of catechol-O-methyltransferase (COMT) gene polymorphisms.

PubMed

Xia, Haiwei; Wu, Nan; Su, Yanjie

2012-01-01

The ability to deduce other persons' mental states and emotions which has been termed 'theory of mind (ToM)' is highly heritable. First molecular genetic studies focused on some dopamine-related genes, while the genetic basis underlying different components of ToM (affective ToM and cognitive ToM) remain unknown. The current study tested 7 candidate polymorphisms (rs4680, rs4633, rs2020917, rs2239393, rs737865, rs174699 and rs59938883) on the catechol-O-methyltransferase (COMT) gene. We investigated how these polymorphisms relate to different components of ToM. 101 adults participated in our study; all were genetically unrelated, non-clinical and healthy Chinese subjects. Different ToM tasks were applied to detect their theory of mind ability. The results showed that the COMT gene rs2020917 and rs737865 SNPs were associated with cognitive ToM performance, while the COMT gene rs5993883 SNP was related to affective ToM, in which a significant gender-genotype interaction was found (p = 0.039). Our results highlighted the contribution of DA-related COMT gene on ToM performance. Moreover, we found out that the different SNP at the same gene relates to the discriminative aspect of ToM. Our research provides some preliminary evidence to the genetic basis of theory of mind which still awaits further studies.

Genetic dissection of fruiting body-related traits using quantitative trait loci mapping in Lentinula edodes.

PubMed

Gong, Wen-Bing; Li, Lei; Zhou, Yan; Bian, Yin-Bing; Kwan, Hoi-Shan; Cheung, Man-Kit; Xiao, Yang

2016-06-01

To provide a better understanding of the genetic architecture of fruiting body formation of Lentinula edodes, quantitative trait loci (QTLs) mapping was employed to uncover the loci underlying seven fruiting body-related traits (FBRTs). An improved L. edodes genetic linkage map, comprising 572 markers on 12 linkage groups with a total map length of 983.7 cM, was constructed by integrating 82 genomic sequence-based insertion-deletion (InDel) markers into a previously published map. We then detected a total of 62 QTLs for seven target traits across two segregating testcross populations, with individual QTLs contributing 5.5 %-30.2 % of the phenotypic variation. Fifty-three out of the 62 QTLs were clustered in six QTL hotspots, suggesting the existence of main genomic regions regulating the morphological characteristics of fruiting bodies in L. edodes. A stable QTL hotspot on MLG2, containing QTLs for all investigated traits, was identified in both testcross populations. QTLs for related traits were frequently co-located on the linkage groups, demonstrating the genetic basis for phenotypic correlation of traits. Meta-QTL (mQTL) analysis was performed and identified 16 mQTLs with refined positions and narrow confidence intervals (CIs). Nine genes, including those encoding MAP kinase, blue-light photoreceptor, riboflavin-aldehyde-forming enzyme and cyclopropane-fatty-acyl-phospholipid synthase, and cytochrome P450s, were likely to be candidate genes controlling the shape of fruiting bodies. The study has improved our understanding of the genetic architecture of fruiting body formation in L. edodes. To our knowledge, this is the first genome-wide QTL detection of FBRTs in L. edodes. The improved genetic map, InDel markers and QTL hotspot regions revealed here will assist considerably in the conduct of future genetic and breeding studies of L. edodes.

Genetics: A New Landscape for Medical Geography

PubMed Central

Carrel, Margaret; Emch, Michael

2014-01-01

The emergence and re-emergence of human pathogens resistant to medical treatment will present a challenge to the international public health community in the coming decades. Geography is uniquely positioned to examine the progressive evolution of pathogens across space and through time, and to link molecular change to interactions between population and environmental drivers. Landscape as an organizing principle for the integration of natural and cultural forces has a long history in geography, and, more specifically, in medical geography. Here, we explore the role of landscape in medical geography, the emergent field of landscape genetics, and the great potential that exists in the combination of these two disciplines. We argue that landscape genetics can enhance medical geographic studies of local-level disease environments with quantitative tests of how human-environment interactions influence pathogenic characteristics. In turn, such analyses can expand theories of disease diffusion to the molecular scale and distinguish the important factors in ecologies of disease that drive genetic change of pathogens. PMID:24558292

Inferring genetic interactions from comparative fitness data

PubMed Central

2017-01-01

Darwinian fitness is a central concept in evolutionary biology. In practice, however, it is hardly possible to measure fitness for all genotypes in a natural population. Here, we present quantitative tools to make inferences about epistatic gene interactions when the fitness landscape is only incompletely determined due to imprecise measurements or missing observations. We demonstrate that genetic interactions can often be inferred from fitness rank orders, where all genotypes are ordered according to fitness, and even from partial fitness orders. We provide a complete characterization of rank orders that imply higher order epistasis. Our theory applies to all common types of gene interactions and facilitates comprehensive investigations of diverse genetic interactions. We analyzed various genetic systems comprising HIV-1, the malaria-causing parasite Plasmodium vivax, the fungus Aspergillus niger, and the TEM-family of β-lactamase associated with antibiotic resistance. For all systems, our approach revealed higher order interactions among mutations. PMID:29260711

Determination of Mycotoxin Production of Fusarium Species in Genetically Modified Maize Varieties by Quantitative Flow Immunocytometry.

PubMed

Bánáti, Hajnalka; Darvas, Béla; Fehér-Tóth, Szilvia; Czéh, Árpád; Székács, András

2017-02-22

Levels of mycotoxins produced by Fusarium species in genetically modified (GM) and near-isogenic maize, were determined using multi-analyte, microbead-based flow immunocytometry with fluorescence detection, for the parallel quantitative determination of fumonisin B1, deoxynivalenol, zearalenone, T-2, ochratoxin A, and aflatoxin B1. Maize varieties included the genetic events MON 810 and DAS-59122-7 , and their isogenic counterparts. Cobs were artificially infested by F. verticillioides and F. proliferatum conidia, and contained F. graminearum and F. sporotrichoides natural infestation. The production of fumonisin B1 and deoxynivalenol was substantially affected in GM maize lines: F. verticillioides , with the addition of F. graminearum and F. sporotrichoides , produced significantly lower levels of fumonisin B1 (~300 mg·kg -1 ) in DAS-59122-7 than in its isogenic line (~580 mg·kg -1 ), while F. proliferatum , in addition to F. graminearum and F. sporotrichoides , produced significantly higher levels of deoxynivalenol (~18 mg·kg -1 ) in MON 810 than in its isogenic line (~5 mg·kg -1 ). Fusarium verticillioides , with F. graminearum and F. sporotrichoides , produced lower amounts of deoxynivalenol and zearalenone than F. proliferatum , with F. graminearum and F. sporotrichoides . T-2 toxin production remained unchanged when considering the maize variety. The results demonstrate the utility of the Fungi-Plex™ quantitative flow immunocytometry method, applied for the high throughput parallel determination of the target mycotoxins.

Testing for biases in selection on avian reproductive traits and partitioning direct and indirect selection using quantitative genetic models.

PubMed

Reed, Thomas E; Gienapp, Phillip; Visser, Marcel E

2016-10-01

Key life history traits such as breeding time and clutch size are frequently both heritable and under directional selection, yet many studies fail to document microevolutionary responses. One general explanation is that selection estimates are biased by the omission of correlated traits that have causal effects on fitness, but few valid tests of this exist. Here, we show, using a quantitative genetic framework and six decades of life-history data on two free-living populations of great tits Parus major, that selection estimates for egg-laying date and clutch size are relatively unbiased. Predicted responses to selection based on the Robertson-Price Identity were similar to those based on the multivariate breeder's equation (MVBE), indicating that unmeasured covarying traits were not missing from the analysis. Changing patterns of phenotypic selection on these traits (for laying date, linked to climate change) therefore reflect changing selection on breeding values, and genetic constraints appear not to limit their independent evolution. Quantitative genetic analysis of correlational data from pedigreed populations can be a valuable complement to experimental approaches to help identify whether apparent associations between traits and fitness are biased by missing traits, and to parse the roles of direct versus indirect selection across a range of environments. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

PCR-free quantitative detection of genetically modified organism from raw materials – A novel electrochemiluminescence-based bio-barcode method

PubMed Central

Zhu, Debin; Tang, Yabing; Xing, Da; Chen, Wei R.

2018-01-01

Bio-barcode assay based on oligonucleotide-modified gold nanoparticles (Au-NPs) provides a PCR-free method for quantitative detection of nucleic acid targets. However, the current bio-barcode assay requires lengthy experimental procedures including the preparation and release of barcode DNA probes from the target-nanoparticle complex, and immobilization and hybridization of the probes for quantification. Herein, we report a novel PCR-free electrochemiluminescence (ECL)-based bio-barcode assay for the quantitative detection of genetically modified organism (GMO) from raw materials. It consists of tris-(2’2’-bipyridyl) ruthenium (TBR)-labele barcode DNA, nucleic acid hybridization using Au-NPs and biotin-labeled probes, and selective capture of the hybridization complex by streptavidin-coated paramagnetic beads. The detection of target DNA is realized by direct measurement of ECL emission of TBR. It can quantitatively detect target nucleic acids with high speed and sensitivity. This method can be used to quantitatively detect GMO fragments from real GMO products. PMID:18386909

Quantitative Resistance: More Than Just Perception of a Pathogen.

PubMed

Corwin, Jason A; Kliebenstein, Daniel J

2017-04-01

Molecular plant pathology has focused on studying large-effect qualitative resistance loci that predominantly function in detecting pathogens and/or transmitting signals resulting from pathogen detection. By contrast, less is known about quantitative resistance loci, particularly the molecular mechanisms controlling variation in quantitative resistance. Recent studies have provided insight into these mechanisms, showing that genetic variation at hundreds of causal genes may underpin quantitative resistance. Loci controlling quantitative resistance contain some of the same causal genes that mediate qualitative resistance, but the predominant mechanisms of quantitative resistance extend beyond pathogen recognition. Indeed, most causal genes for quantitative resistance encode specific defense-related outputs such as strengthening of the cell wall or defense compound biosynthesis. Extending previous work on qualitative resistance to focus on the mechanisms of quantitative resistance, such as the link between perception of microbe-associated molecular patterns and growth, has shown that the mechanisms underlying these defense outputs are also highly polygenic. Studies that include genetic variation in the pathogen have begun to highlight a potential need to rethink how the field considers broad-spectrum resistance and how it is affected by genetic variation within pathogen species and between pathogen species. These studies are broadening our understanding of quantitative resistance and highlighting the potentially vast scale of the genetic basis of quantitative resistance. © 2017 American Society of Plant Biologists. All rights reserved.

Quantitative Resistance: More Than Just Perception of a Pathogen

PubMed Central

2017-01-01

Molecular plant pathology has focused on studying large-effect qualitative resistance loci that predominantly function in detecting pathogens and/or transmitting signals resulting from pathogen detection. By contrast, less is known about quantitative resistance loci, particularly the molecular mechanisms controlling variation in quantitative resistance. Recent studies have provided insight into these mechanisms, showing that genetic variation at hundreds of causal genes may underpin quantitative resistance. Loci controlling quantitative resistance contain some of the same causal genes that mediate qualitative resistance, but the predominant mechanisms of quantitative resistance extend beyond pathogen recognition. Indeed, most causal genes for quantitative resistance encode specific defense-related outputs such as strengthening of the cell wall or defense compound biosynthesis. Extending previous work on qualitative resistance to focus on the mechanisms of quantitative resistance, such as the link between perception of microbe-associated molecular patterns and growth, has shown that the mechanisms underlying these defense outputs are also highly polygenic. Studies that include genetic variation in the pathogen have begun to highlight a potential need to rethink how the field considers broad-spectrum resistance and how it is affected by genetic variation within pathogen species and between pathogen species. These studies are broadening our understanding of quantitative resistance and highlighting the potentially vast scale of the genetic basis of quantitative resistance. PMID:28302676

Genetic and Quantitative Trait Locus Analysis for Bio-Oil Compounds after Fast Pyrolysis in Maize Cobs.

PubMed

Jeffrey, Brandon; Kuzhiyil, Najeeb; de Leon, Natalia; Lübberstedt, Thomas

2016-01-01

Fast pyrolysis has been identified as one of the biorenewable conversion platforms that could be a part of an alternative energy future, but it has not yet received the same attention as cellulosic ethanol in the analysis of genetic inheritance within potential feedstocks such as maize. Ten bio-oil compounds were measured via pyrolysis/gas chromatography-mass spectrometry (Py/GC-MS) in maize cobs. 184 recombinant inbred lines (RILs) of the intermated B73 x Mo17 (IBM) Syn4 population were analyzed in two environments, using 1339 markers, for quantitative trait locus (QTL) mapping. QTL mapping was performed using composite interval mapping with significance thresholds established by 1000 permutations at α = 0.05. 50 QTL were found in total across those ten traits with R2 values ranging from 1.7 to 5.8%, indicating a complex quantitative inheritance of these traits.

Development and Evaluation of Event-Specific Quantitative PCR Method for Genetically Modified Soybean MON87701.

PubMed

Tsukahara, Keita; Takabatake, Reona; Masubuchi, Tomoko; Futo, Satoshi; Minegishi, Yasutaka; Noguchi, Akio; Kondo, Kazunari; Nishimaki-Mogami, Tomoko; Kurashima, Takeyo; Mano, Junichi; Kitta, Kazumi

2016-01-01

A real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) soybean event, MON87701. First, a standard plasmid for MON87701 quantification was constructed. The conversion factor (C f ) required to calculate the amount of genetically modified organism (GMO) was experimentally determined for a real-time PCR instrument. The determined C f for the real-time PCR instrument was 1.24. For the evaluation of the developed method, a blind test was carried out in an inter-laboratory trial. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSDr), respectively. The determined biases and the RSDr values were less than 30 and 13%, respectively, at all evaluated concentrations. The limit of quantitation of the method was 0.5%, and the developed method would thus be applicable for practical analyses for the detection and quantification of MON87701.

Quantitative Structure-Property Relationship (QSPR) Modeling of Drug-Loaded Polymeric Micelles via Genetic Function Approximation

PubMed Central

Lin, Wenjing; Chen, Quan; Guo, Xindong; Qian, Yu; Zhang, Lijuan

2015-01-01

Self-assembled nano-micelles of amphiphilic polymers represent a novel anticancer drug delivery system. However, their full clinical utilization remains challenging because the quantitative structure-property relationship (QSPR) between the polymer structure and the efficacy of micelles as a drug carrier is poorly understood. Here, we developed a series of QSPR models to account for the drug loading capacity of polymeric micelles using the genetic function approximation (GFA) algorithm. These models were further evaluated by internal and external validation and a Y-randomization test in terms of stability and generalization, yielding an optimization model that is applicable to an expanded materials regime. As confirmed by experimental data, the relationship between microstructure and drug loading capacity can be well-simulated, suggesting that our models are readily applicable to the quantitative evaluation of the drug-loading capacity of polymeric micelles. Our work may offer a pathway to the design of formulation experiments. PMID:25780923

The aminoacyl-tRNA synthetases had only a marginal role in the origin of the organization of the genetic code: Evidence in favor of the coevolution theory.

PubMed

Di Giulio, Massimo

2017-11-07

The coevolution theory of the origin of the genetic code suggests that the organization of the genetic code coevolved with the biosynthetic relationships between amino acids. The mechanism that allowed this coevolution was based on tRNA-like molecules on which-this theory-would postulate the biosynthetic transformations between amino acids to have occurred. This mechanism makes a prediction on how the role conducted by the aminoacyl-tRNA synthetases (ARSs), in the origin of the genetic code, should have been. Indeed, if the biosynthetic transformations between amino acids occurred on tRNA-like molecules, then there was no need to link amino acids to these molecules because amino acids were already charged on tRNA-like molecules, as the coevolution theory suggests. In spite of the fact that ARSs make the genetic code responsible for the first interaction between a component of nucleic acids and that of proteins, for the coevolution theory the role of ARSs should have been entirely marginal in the genetic code origin. Therefore, I have conducted a further analysis of the distribution of the two classes of ARSs and of their subclasses-in the genetic code table-in order to perform a falsification test of the coevolution theory. Indeed, in the case in which the distribution of ARSs within the genetic code would have been highly significant, then the coevolution theory would be falsified since the mechanism on which it is based would not predict a fundamental role of ARSs in the origin of the genetic code. I found that the statistical significance of the distribution of the two classes of ARSs in the table of the genetic code is low or marginal, whereas that of the subclasses of ARSs statistically significant. However, this is in perfect agreement with the postulates of the coevolution theory. Indeed, the only case of statistical significance-regarding the classes of ARSs-is appreciable for the CAG code, whereas for its complement-the UNN/NUN code-only a marginal

Applying ecological models to communities of genetic elements: the case of neutral theory.

PubMed

Linquist, Stefan; Cottenie, Karl; Elliott, Tyler A; Saylor, Brent; Kremer, Stefan C; Gregory, T Ryan

2015-07-01

A promising recent development in molecular biology involves viewing the genome as a mini-ecosystem, where genetic elements are compared to organisms and the surrounding cellular and genomic structures are regarded as the local environment. Here, we critically evaluate the prospects of ecological neutral theory (ENT), a popular model in ecology, as it applies at the genomic level. This assessment requires an overview of the controversy surrounding neutral models in community ecology. In particular, we discuss the limitations of using ENT both as an explanation of community dynamics and as a null hypothesis. We then analyse a case study in which ENT has been applied to genomic data. Our central finding is that genetic elements do not conform to the requirements of ENT once its assumptions and limitations are made explicit. We further compare this genome-level application of ENT to two other, more familiar approaches in genomics that rely on neutral mechanisms: Kimura's molecular neutral theory and Lynch's mutational-hazard model. Interestingly, this comparison reveals that there are two distinct concepts of neutrality associated with these models, which we dub 'fitness neutrality' and 'competitive neutrality'. This distinction helps to clarify the various roles for neutral models in genomics, for example in explaining the evolution of genome size. © 2015 John Wiley & Sons Ltd.

A quantitative chemotherapy genetic interaction map reveals new factors associated with PARP inhibitor resistance | Office of Cancer Genomics

Cancer.gov

Nearly every cancer patient is treated with chemotherapy yet our understanding of factors that dictate response and resistance to such agents remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells that charts the impact of knockdown of 625 cancer and DNA repair related genes on sensitivity to 29 drugs, covering all classes of cancer chemotherapeutics.

Demonstration of a viable quantitative theory for interplanetary type II radio bursts

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

Schmidt, J. M., E-mail: jschmidt@physics.usyd.edu.au; Cairns, Iver H.

Between 29 November and 1 December 2013 the two widely separated spacecraft STEREO A and B observed a long lasting, intermittent, type II radio burst for the extended frequency range ≈ 4 MHz to 30 kHz, including an intensification when the shock wave of the associated coronal mass ejection (CME) reached STEREO A. We demonstrate for the first time our ability to quantitatively and accurately simulate the fundamental (F) and harmonic (H) emission of type II bursts from the higher corona (near 11 solar radii) to 1 AU. Our modeling requires the combination of data-driven three-dimensional magnetohydrodynamic simulations for the CME andmore » plasma background, carried out with the BATS-R-US code, with an analytic quantitative kinetic model for both F and H radio emission, including the electron reflection at the shock, growth of Langmuir waves and radio waves, and the radiations propagation to an arbitrary observer. The intensities and frequencies of the observed radio emissions vary hugely by factors ≈ 10{sup 6} and ≈ 10{sup 3}, respectively; the theoretical predictions are impressively accurate, being typically in error by less than a factor of 10 and 20 %, for both STEREO A and B. We also obtain accurate predictions for the timing and characteristics of the shock and local radio onsets at STEREO A, the lack of such onsets at STEREO B, and the z-component of the magnetic field at STEREO A ahead of the shock, and in the sheath. Very strong support is provided by these multiple agreements for the theory, the efficacy of the BATS-R-US code, and the vision of using type IIs and associated data-theory iterations to predict whether a CME will impact Earth’s magnetosphere and drive space weather events.« less

Demonstration of a viable quantitative theory for interplanetary type II radio bursts

NASA Astrophysics Data System (ADS)

Schmidt, J. M.; Cairns, Iver H.

2016-03-01

Between 29 November and 1 December 2013 the two widely separated spacecraft STEREO A and B observed a long lasting, intermittent, type II radio burst for the extended frequency range ≈ 4 MHz to 30 kHz, including an intensification when the shock wave of the associated coronal mass ejection (CME) reached STEREO A. We demonstrate for the first time our ability to quantitatively and accurately simulate the fundamental (F) and harmonic (H) emission of type II bursts from the higher corona (near 11 solar radii) to 1 AU. Our modeling requires the combination of data-driven three-dimensional magnetohydrodynamic simulations for the CME and plasma background, carried out with the BATS-R-US code, with an analytic quantitative kinetic model for both F and H radio emission, including the electron reflection at the shock, growth of Langmuir waves and radio waves, and the radiations propagation to an arbitrary observer. The intensities and frequencies of the observed radio emissions vary hugely by factors ≈ 106 and ≈ 103, respectively; the theoretical predictions are impressively accurate, being typically in error by less than a factor of 10 and 20 %, for both STEREO A and B. We also obtain accurate predictions for the timing and characteristics of the shock and local radio onsets at STEREO A, the lack of such onsets at STEREO B, and the z-component of the magnetic field at STEREO A ahead of the shock, and in the sheath. Very strong support is provided by these multiple agreements for the theory, the efficacy of the BATS-R-US code, and the vision of using type IIs and associated data-theory iterations to predict whether a CME will impact Earth's magnetosphere and drive space weather events.

Highly multiplexed and quantitative cell-surface protein profiling using genetically barcoded antibodies.

PubMed

Pollock, Samuel B; Hu, Amy; Mou, Yun; Martinko, Alexander J; Julien, Olivier; Hornsby, Michael; Ploder, Lynda; Adams, Jarrett J; Geng, Huimin; Müschen, Markus; Sidhu, Sachdev S; Moffat, Jason; Wells, James A

2018-03-13

Human cells express thousands of different surface proteins that can be used for cell classification, or to distinguish healthy and disease conditions. A method capable of profiling a substantial fraction of the surface proteome simultaneously and inexpensively would enable more accurate and complete classification of cell states. We present a highly multiplexed and quantitative surface proteomic method using genetically barcoded antibodies called phage-antibody next-generation sequencing (PhaNGS). Using 144 preselected antibodies displayed on filamentous phage (Fab-phage) against 44 receptor targets, we assess changes in B cell surface proteins after the development of drug resistance in a patient with acute lymphoblastic leukemia (ALL) and in adaptation to oncogene expression in a Myc-inducible Burkitt lymphoma model. We further show PhaNGS can be applied at the single-cell level. Our results reveal that a common set of proteins including FLT3, NCR3LG1, and ROR1 dominate the response to similar oncogenic perturbations in B cells. Linking high-affinity, selective, genetically encoded binders to NGS enables direct and highly multiplexed protein detection, comparable to RNA-sequencing for mRNA. PhaNGS has the potential to profile a substantial fraction of the surface proteome simultaneously and inexpensively to enable more accurate and complete classification of cell states. Copyright © 2018 the Author(s). Published by PNAS.

Sex chromosome linked genetic variance and the evolution of sexual dimorphism of quantitative traits.

PubMed

Husby, Arild; Schielzeth, Holger; Forstmeier, Wolfgang; Gustafsson, Lars; Qvarnström, Anna

2013-03-01

Theory predicts that sex chromsome linkage should reduce intersexual genetic correlations thereby allowing the evolution of sexual dimorphism. Empirical evidence for sex linkage has come largely from crosses and few studies have examined how sexual dimorphism and sex linkage are related within outbred populations. Here, we use data on an array of different traits measured on over 10,000 individuals from two pedigreed populations of birds (collared flycatcher and zebra finch) to estimate the amount of sex-linked genetic variance (h(2)z ). Of 17 traits examined, eight showed a nonzero h(2)Z estimate but only four were significantly different from zero (wing patch size and tarsus length in collared flycatchers, wing length and beak color in zebra finches). We further tested how sexual dimorphism and the mode of selection operating on the trait relate to the proportion of sex-linked genetic variance. Sexually selected traits did not show higher h(2)Z than morphological traits and there was only a weak positive relationship between h(2)Z and sexual dimorphism. However, given the relative scarcity of empirical studies, it is premature to make conclusions about the role of sex chromosome linkage in the evolution of sexual dimorphism. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

High-Density Genetic Linkage Map Construction and Quantitative Trait Locus Mapping for Hawthorn (Crataegus pinnatifida Bunge).

PubMed

Zhao, Yuhui; Su, Kai; Wang, Gang; Zhang, Liping; Zhang, Jijun; Li, Junpeng; Guo, Yinshan

2017-07-14

Genetic linkage maps are an important tool in genetic and genomic research. In this study, two hawthorn cultivars, Qiujinxing and Damianqiu, and 107 progenies from a cross between them were used for constructing a high-density genetic linkage map using the 2b-restriction site-associated DNA (2b-RAD) sequencing method, as well as for mapping quantitative trait loci (QTL) for flavonoid content. In total, 206,411,693 single-end reads were obtained, with an average sequencing depth of 57× in the parents and 23× in the progeny. After quality trimming, 117,896 high-quality 2b-RAD tags were retained, of which 42,279 were polymorphic; of these, 12,951 markers were used for constructing the genetic linkage map. The map contained 17 linkage groups and 3,894 markers, with a total map length of 1,551.97 cM and an average marker interval of 0.40 cM. QTL mapping identified 21 QTLs associated with flavonoid content in 10 linkage groups, which explained 16.30-59.00% of the variance. This is the first high-density linkage map for hawthorn, which will serve as a basis for fine-scale QTL mapping and marker-assisted selection of important traits in hawthorn germplasm and will facilitate chromosome assignment for hawthorn whole-genome assemblies in the future.

Novel Autism Subtype-Dependent Genetic Variants Are Revealed by Quantitative Trait and Subphenotype Association Analyses of Published GWAS Data

PubMed Central

Hu, Valerie W.; Addington, Anjene; Hyman, Alexander

2011-01-01

The heterogeneity of symptoms associated with autism spectrum disorders (ASDs) has presented a significant challenge to genetic analyses. Even when associations with genetic variants have been identified, it has been difficult to associate them with a specific trait or characteristic of autism. Here, we report that quantitative trait analyses of ASD symptoms combined with case-control association analyses using distinct ASD subphenotypes identified on the basis of symptomatic profiles result in the identification of highly significant associations with 18 novel single nucleotide polymorphisms (SNPs). The symptom categories included deficits in language usage, non-verbal communication, social development, and play skills, as well as insistence on sameness or ritualistic behaviors. Ten of the trait-associated SNPs, or quantitative trait loci (QTL), were associated with more than one subtype, providing partial replication of the identified QTL. Notably, none of the novel SNPs is located within an exonic region, suggesting that these hereditary components of ASDs are more likely related to gene regulatory processes (or gene expression) than to structural or functional changes in gene products. Seven of the QTL reside within intergenic chromosomal regions associated with rare copy number variants that have been previously reported in autistic samples. Pathway analyses of the genes associated with the QTL identified in this study implicate neurological functions and disorders associated with autism pathophysiology. This study underscores the advantage of incorporating both quantitative traits as well as subphenotypes into large-scale genome-wide analyses of complex disorders. PMID:21556359

MaGelLAn 1.0: a software to facilitate quantitative and population genetic analysis of maternal inheritance by combination of molecular and pedigree information.

PubMed

Ristov, Strahil; Brajkovic, Vladimir; Cubric-Curik, Vlatka; Michieli, Ivan; Curik, Ino

2016-09-10

Identification of genes or even nucleotides that are responsible for quantitative and adaptive trait variation is a difficult task due to the complex interdependence between a large number of genetic and environmental factors. The polymorphism of the mitogenome is one of the factors that can contribute to quantitative trait variation. However, the effects of the mitogenome have not been comprehensively studied, since large numbers of mitogenome sequences and recorded phenotypes are required to reach the adequate power of analysis. Current research in our group focuses on acquiring the necessary mitochondria sequence information and analysing its influence on the phenotype of a quantitative trait. To facilitate these tasks we have produced software for processing pedigrees that is optimised for maternal lineage analysis. We present MaGelLAn 1.0 (maternal genealogy lineage analyser), a suite of four Python scripts (modules) that is designed to facilitate the analysis of the impact of mitogenome polymorphism on quantitative trait variation by combining molecular and pedigree information. MaGelLAn 1.0 is primarily used to: (1) optimise the sampling strategy for molecular analyses; (2) identify and correct pedigree inconsistencies; and (3) identify maternal lineages and assign the corresponding mitogenome sequences to all individuals in the pedigree, this information being used as input to any of the standard software for quantitative genetic (association) analysis. In addition, MaGelLAn 1.0 allows computing the mitogenome (maternal) effective population sizes and probability of mitogenome (maternal) identity that are useful for conservation management of small populations. MaGelLAn is the first tool for pedigree analysis that focuses on quantitative genetic analyses of mitogenome data. It is conceived with the purpose to significantly reduce the effort in handling and preparing large pedigrees for processing the information linked to maternal lines. The software source

Quantitative genetic analysis of brain copper and zinc in BXD recombinant inbred mice.

PubMed

Jones, Leslie C; McCarthy, Kristin A; Beard, John L; Keen, Carl L; Jones, Byron C

2006-01-01

Copper and zinc are trace nutrients essential for normal brain function, yet an excess of these elements can be toxic. It is important therefore that these metals be closely regulated. We recently conducted a quantitative trait loci (QTL) analysis to identify chromosomal regions in the mouse containing possible regulatory genes. The animals came from 15 strains of the BXD/Ty recombinant inbred (RI) strain panel and the brain regions analyzed were frontal cortex, caudate-putamen, nucleus accumbens and ventral midbrain. Several QTL were identified for copper and/or zinc, most notably on chromosomes 1, 8, 16 and 17. Genetic correlational analysis also revealed associations between these metals and dopamine, cocaine responses, saccharine preference, immune response and seizure susceptibility. Notably, the QTL on chromosome 17 is also associated with seizure susceptibility and contains the histocompatibility H2 complex. This work shows that regulation of zinc and copper is under polygenic influence and is intimately related to CNS function. Future work will reveal genes underlying the QTL and how they interact with other genes and the environment. More importantly, revelation of the genetic underpinnings of copper and zinc brain homeostasis will aid our understanding of neurological diseases that are related to copper and zinc imbalance.

Social contract theory and just decision making: lessons from genetic testing for the BRCA mutations.

PubMed

Williams-Jones, Bryn; Burgess, Michael M

2004-06-01

Decisions about funding health services are crucial to controlling costs in health care insurance plans, yet they encounter serious challenges from intellectual property protection--e.g., patents--of health care services. Using Myriad Genetics' commercial genetic susceptibility test for hereditary breast cancer (BRCA testing) in the context of the Canadian health insurance system as a case study, this paper applies concepts from social contract theory to help develop more just and rational approaches to health care decision making. Specifically, Daniel's and Sabin's "accountability for reasonableness" is compared to broader notions of public consultation, demonstrating that expert assessments in specific decisions must be transparent and accountable and supplemented by public consultation.

Theory and preliminary experimental verification of quantitative edge illumination x-ray phase contrast tomography.

PubMed

Hagen, C K; Diemoz, P C; Endrizzi, M; Rigon, L; Dreossi, D; Arfelli, F; Lopez, F C M; Longo, R; Olivo, A

2014-04-07

X-ray phase contrast imaging (XPCi) methods are sensitive to phase in addition to attenuation effects and, therefore, can achieve improved image contrast for weakly attenuating materials, such as often encountered in biomedical applications. Several XPCi methods exist, most of which have already been implemented in computed tomographic (CT) modality, thus allowing volumetric imaging. The Edge Illumination (EI) XPCi method had, until now, not been implemented as a CT modality. This article provides indications that quantitative 3D maps of an object's phase and attenuation can be reconstructed from EI XPCi measurements. Moreover, a theory for the reconstruction of combined phase and attenuation maps is presented. Both reconstruction strategies find applications in tissue characterisation and the identification of faint, weakly attenuating details. Experimental results for wires of known materials and for a biological object validate the theory and confirm the superiority of the phase over conventional, attenuation-based image contrast.

Testing natural selection vs. genetic drift in phenotypic evolution using quantitative trait locus data.

PubMed Central

Orr, H A

1998-01-01

Evolutionary biologists have long sought a way to determine whether a phenotypic difference between two taxa was caused by natural selection or random genetic drift. Here I argue that data from quantitative trait locus (QTL) analyses can be used to test the null hypothesis of neutral phenotypic evolution. I propose a sign test that compares the observed number of plus and minus alleles in the "high line" with that expected under neutrality, conditioning on the known phenotypic difference between the taxa. Rejection of the null hypothesis implies a role for directional natural selection. This test is applicable to any character in any organism in which QTL analysis can be performed. PMID:9691061

Beyond Punnett Squares: Student Word Association and Explanations of Phenotypic Variation through an Integrative Quantitative Genetics Unit Investigating Anthocyanin Inheritance and Expression in "Brassica rapa" Fast Plants

ERIC Educational Resources Information Center

Batzli, Janet M.; Smith, Amber R.; Williams, Paul H.; McGee, Seth A.; Dosa, Katalin; Pfammatter, Jesse

2014-01-01

Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question "What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev)," we developed a 4-wk unit for an inquiry-based laboratory…

Model-Based Linkage Analysis of a Quantitative Trait.

PubMed

Song, Yeunjoo E; Song, Sunah; Schnell, Audrey H

2017-01-01

Linkage Analysis is a family-based method of analysis to examine whether any typed genetic markers cosegregate with a given trait, in this case a quantitative trait. If linkage exists, this is taken as evidence in support of a genetic basis for the trait. Historically, linkage analysis was performed using a binary disease trait, but has been extended to include quantitative disease measures. Quantitative traits are desirable as they provide more information than binary traits. Linkage analysis can be performed using single-marker methods (one marker at a time) or multipoint (using multiple markers simultaneously). In model-based linkage analysis the genetic model for the trait of interest is specified. There are many software options for performing linkage analysis. Here, we use the program package Statistical Analysis for Genetic Epidemiology (S.A.G.E.). S.A.G.E. was chosen because it also includes programs to perform data cleaning procedures and to generate and test genetic models for a quantitative trait, in addition to performing linkage analysis. We demonstrate in detail the process of running the program LODLINK to perform single-marker analysis, and MLOD to perform multipoint analysis using output from SEGREG, where SEGREG was used to determine the best fitting statistical model for the trait.

Developmental Systems Theory and the Person-Oriented Approach. Commentary on: "An Interpretation of Part of Gilbert Gottlieb's Legacy: Developmental Systems Theory Contra Developmental Behavior Genetics"

ERIC Educational Resources Information Center

Bergman, Lars R.

2015-01-01

Molenaar's (2015) article concerns Developmental Systems Theory (DST) in relation to behavior genetics and he presents implications of DST for empirical research, especially the need for subject-specific studies. In this commentary, the article is discussed from a broader developmental science perspective, particularly regarded through the lens of…

A test for selection employing quantitative trait locus and mutation accumulation data.

PubMed

Rice, Daniel P; Townsend, Jeffrey P

2012-04-01

Evolutionary biologists attribute much of the phenotypic diversity observed in nature to the action of natural selection. However, for many phenotypic traits, especially quantitative phenotypic traits, it has been challenging to test for the historical action of selection. An important challenge for biologists studying quantitative traits, therefore, is to distinguish between traits that have evolved under the influence of strong selection and those that have evolved neutrally. Most existing tests for selection employ molecular data, but selection also leaves a mark on the genetic architecture underlying a trait. In particular, the distribution of quantitative trait locus (QTL) effect sizes and the distribution of mutational effects together provide information regarding the history of selection. Despite the increasing availability of QTL and mutation accumulation data, such data have not yet been effectively exploited for this purpose. We present a model of the evolution of QTL and employ it to formulate a test for historical selection. To provide a baseline for neutral evolution of the trait, we estimate the distribution of mutational effects from mutation accumulation experiments. We then apply a maximum-likelihood-based method of inference to estimate the range of selection strengths under which such a distribution of mutations could generate the observed QTL. Our test thus represents the first integration of population genetic theory and QTL data to measure the historical influence of selection.

Development and validation of an event-specific quantitative PCR method for genetically modified maize MIR162.

PubMed

Takabatake, Reona; Masubuchi, Tomoko; Futo, Satoshi; Minegishi, Yasutaka; Noguchi, Akio; Kondo, Kazunari; Teshima, Reiko; Kurashima, Takeyo; Mano, Junichi; Kitta, Kazumi

2014-01-01

A novel real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) maize event, MIR162. We first prepared a standard plasmid for MIR162 quantification. The conversion factor (Cf) required to calculate the genetically modified organism (GMO) amount was empirically determined for two real-time PCR instruments, the Applied Biosystems 7900HT (ABI7900) and the Applied Biosystems 7500 (ABI7500) for which the determined Cf values were 0.697 and 0.635, respectively. To validate the developed method, a blind test was carried out in an interlaboratory study. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSDr). The determined biases were less than 25% and the RSDr values were less than 20% at all evaluated concentrations. These results suggested that the limit of quantitation of the method was 0.5%, and that the developed method would thus be suitable for practical analyses for the detection and quantification of MIR162.

Quantitative genetics and utilization of mutants

USDA-ARS?s Scientific Manuscript database

The relatively low level of genetic variability currently available in cotton makes mutagenesis attractive to overcome this problem. Mutations can occur either spontaneously or be induced. The majority of the genes we use today are spontaneous mutants that developed over a long period of time. Induc...

Can genetics help psychometrics? Improving dimensionality assessment through genetic factor modeling.

PubMed

Franić, Sanja; Dolan, Conor V; Borsboom, Denny; Hudziak, James J; van Beijsterveldt, Catherina E M; Boomsma, Dorret I

2013-09-01

In the present article, we discuss the role that quantitative genetic methodology may play in assessing and understanding the dimensionality of psychological (psychometric) instruments. Specifically, we study the relationship between the observed covariance structures, on the one hand, and the underlying genetic and environmental influences giving rise to such structures, on the other. We note that this relationship may be such that it hampers obtaining a clear estimate of dimensionality using standard tools for dimensionality assessment alone. One situation in which dimensionality assessment may be impeded is that in which genetic and environmental influences, of which the observed covariance structure is a function, differ from each other in structure and dimensionality. We demonstrate that in such situations settling dimensionality issues may be problematic, and propose using quantitative genetic modeling to uncover the (possibly different) dimensionalities of the underlying genetic and environmental structures. We illustrate using simulations and an empirical example on childhood internalizing problems.

Experimental evidence for the evolution of indirect genetic effects: changes in the interaction effect coefficient, psi (Psi), due to sexual selection.

PubMed

Chenoweth, Stephen F; Rundle, Howard D; Blows, Mark W

2010-06-01

Indirect genetics effects (IGEs)--when the genotype of one individual affects the phenotypic expression of a trait in another--may alter evolutionary trajectories beyond that predicted by standard quantitative genetic theory as a consequence of genotypic evolution of the social environment. For IGEs to occur, the trait of interest must respond to one or more indicator traits in interacting conspecifics. In quantitative genetic models of IGEs, these responses (reaction norms) are termed interaction effect coefficients and are represented by the parameter psi (Psi). The extent to which Psi exhibits genetic variation within a population, and may therefore itself evolve, is unknown. Using an experimental evolution approach, we provide evidence for a genetic basis to the phenotypic response caused by IGEs on sexual display traits in Drosophila serrata. We show that evolution of the response is affected by sexual but not natural selection when flies adapt to a novel environment. Our results indicate a further mechanism by which IGEs can alter evolutionary trajectories--the evolution of interaction effects themselves.

Quantitative trait nucleotide analysis using Bayesian model selection.

PubMed

Blangero, John; Goring, Harald H H; Kent, Jack W; Williams, Jeff T; Peterson, Charles P; Almasy, Laura; Dyer, Thomas D

2005-10-01

Although much attention has been given to statistical genetic methods for the initial localization and fine mapping of quantitative trait loci (QTLs), little methodological work has been done to date on the problem of statistically identifying the most likely functional polymorphisms using sequence data. In this paper we provide a general statistical genetic framework, called Bayesian quantitative trait nucleotide (BQTN) analysis, for assessing the likely functional status of genetic variants. The approach requires the initial enumeration of all genetic variants in a set of resequenced individuals. These polymorphisms are then typed in a large number of individuals (potentially in families), and marker variation is related to quantitative phenotypic variation using Bayesian model selection and averaging. For each sequence variant a posterior probability of effect is obtained and can be used to prioritize additional molecular functional experiments. An example of this quantitative nucleotide analysis is provided using the GAW12 simulated data. The results show that the BQTN method may be useful for choosing the most likely functional variants within a gene (or set of genes). We also include instructions on how to use our computer program, SOLAR, for association analysis and BQTN analysis.

Quantitative genetic insights into the coevolutionary dynamics of male and female genitalia

PubMed Central

Evans, Jonathan P.; van Lieshout, Emile; Gasparini, Clelia

2013-01-01

The spectacular variability that typically characterizes male genital traits has largely been attributed to the role of sexual selection. Among the evolutionary mechanisms proposed to account for this diversity, two processes in particular have generated considerable interest. On the one hand, females may exploit postcopulatory mechanisms of selection to favour males with preferred genital traits (cryptic female choice; CFC), while on the other hand females may evolve structures or behaviours that mitigate the direct costs imposed by male genitalia (sexual conflict; SC). A critical but rarely explored assumption underlying both processes is that male and female reproductive traits coevolve, either via the classic Fisherian model of preference-trait coevolution (CFC) or through sexually antagonistic selection (SC). Here, we provide evidence for this prediction in the guppy (Poecilia reticulata), a polyandrous livebearing fish in which males transfer sperm internally to females via consensual and forced matings. Our results from a paternal half-sibling breeding design reveal substantial levels of additive genetic variation underlying male genital size and morphology—two traits known to predict mating success during non-consensual matings. Our subsequent finding that physically interacting female genital traits exhibit corresponding levels of genetic (co)variation reveals the potential intersexual coevolutionary dynamics of male and female genitalia, thereby fulfilling a fundamental assumption underlying CFC and SC theory. PMID:23720546

Event-specific qualitative and quantitative detection of five genetically modified rice events using a single standard reference molecule.

PubMed

Kim, Jae-Hwan; Park, Saet-Byul; Roh, Hyo-Jeong; Shin, Min-Ki; Moon, Gui-Im; Hong, Jin-Hwan; Kim, Hae-Yeong

2017-07-01

One novel standard reference plasmid, namely pUC-RICE5, was constructed as a positive control and calibrator for event-specific qualitative and quantitative detection of genetically modified (GM) rice (Bt63, Kemingdao1, Kefeng6, Kefeng8, and LLRice62). pUC-RICE5 contained fragments of a rice-specific endogenous reference gene (sucrose phosphate synthase) as well as the five GM rice events. An existing qualitative PCR assay approach was modified using pUC-RICE5 to create a quantitative method with limits of detection correlating to approximately 1-10 copies of rice haploid genomes. In this quantitative PCR assay, the square regression coefficients ranged from 0.993 to 1.000. The standard deviation and relative standard deviation values for repeatability ranged from 0.02 to 0.22 and 0.10% to 0.67%, respectively. The Ministry of Food and Drug Safety (Korea) validated the method and the results suggest it could be used routinely to identify five GM rice events. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development and interlaboratory validation of quantitative polymerase chain reaction method for screening analysis of genetically modified soybeans.

PubMed

Takabatake, Reona; Onishi, Mari; Koiwa, Tomohiro; Futo, Satoshi; Minegishi, Yasutaka; Akiyama, Hiroshi; Teshima, Reiko; Kurashima, Takeyo; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

2013-01-01

A novel real-time polymerase chain reaction (PCR)-based quantitative screening method was developed for three genetically modified soybeans: RRS, A2704-12, and MON89788. The 35S promoter (P35S) of cauliflower mosaic virus is introduced into RRS and A2704-12 but not MON89788. We then designed a screening method comprised of the combination of the quantification of P35S and the event-specific quantification of MON89788. The conversion factor (Cf) required to convert the amount of a genetically modified organism (GMO) from a copy number ratio to a weight ratio was determined experimentally. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSDR), respectively. The determined RSDR values for the method were less than 25% for both targets. We consider that the developed method would be suitable for the simple detection and approximate quantification of GMO.

Sex-specific genetic effects in physical activity: results from a quantitative genetic analysis.

PubMed

Diego, Vincent P; de Chaves, Raquel Nichele; Blangero, John; de Souza, Michele Caroline; Santos, Daniel; Gomes, Thayse Natacha; dos Santos, Fernanda Karina; Garganta, Rui; Katzmarzyk, Peter T; Maia, José A R

2015-08-01

The objective of this study is to present a model to estimate sex-specific genetic effects on physical activity (PA) levels and sedentary behaviour (SB) using three generation families. The sample consisted of 100 families covering three generations from Portugal. PA and SB were assessed via the International Physical Activity Questionnaire short form (IPAQ-SF). Sex-specific effects were assessed by genotype-by-sex interaction (GSI) models and sex-specific heritabilities. GSI effects and heterogeneity were tested in the residual environmental variance. SPSS 17 and SOLAR v. 4.1 were used in all computations. The genetic component for PA and SB domains varied from low to moderate (11% to 46%), when analyzing both genders combined. We found GSI effects for vigorous PA (p = 0.02) and time spent watching television (WT) (p < 0.001) that showed significantly higher additive genetic variance estimates in males. The heterogeneity in the residual environmental variance was significant for moderate PA (p = 0.02), vigorous PA (p = 0.006) and total PA (p = 0.001). Sex-specific heritability estimates were significantly higher in males only for WT, with a male-to-female difference in heritability of 42.5 (95% confidence interval: 6.4, 70.4). Low to moderate genetic effects on PA and SB traits were found. Results from the GSI model show that there are sex-specific effects in two phenotypes, VPA and WT with a stronger genetic influence in males.

Quantitative genetics of secondary hip joint osteoarthritis in a Labrador Retriever-Greyhound pedigree.

PubMed

Hays, Laurel; Zhang, Zhiwu; Mateescu, Raluca G; Lust, George; Burton-Wurster, Nancy I; Todhunter, Rory J

2007-01-01

To evaluate the quantitative inheritance of secondary hip joint osteoarthritis in a canine pedigree. 137 Labrador Retrievers, Greyhounds, and mixed-breed dogs. Necropsy scores ranging from 0 to 4 were obtained for each hip joint. Seven unaffected Greyhounds with normal hip joint conformation were also used for genetic modeling, but were not euthanized. Sixty-six male and 71 female dogs were allocated to 2 groups (< or = 12 months of age and > 12 months of age). Statistical models were developed to establish the inheritance pattern of hip joint osteoarthritis that developed secondary to hip dysplasia. 62 dogs had evidence of osteoarthritis in a hip joint, and 75 had no evidence of osteoarthritis. After sex was adjusted for, the necropsy score was found to be inherited additively but without dominance. Each Labrador Retriever allele increased the necropsy score by 0.7 to 0.9 points, compared with the Greyhound allele, and male sex increased the necropsy score 0.74 over female sex. Approximately 10% of the variation in necropsy score was attributable to the litter of puppies' origin. Because secondary hip joint osteoarthritis is inherited additively, selection pressure could be applied to reduce its incidence. Similar statistical models can be used in linkage and association mapping to detect the genes in the underlying quantitative trait loci that contribute to hip joint osteoarthritis.

The synthesis paradigm in genetics.

PubMed

Rice, William R

2014-02-01

Experimental genetics with model organisms and mathematically explicit genetic theory are generally considered to be the major paradigms by which progress in genetics is achieved. Here I argue that this view is incomplete and that pivotal advances in genetics--and other fields of biology--are also made by synthesizing disparate threads of extant information rather than generating new information from experiments or formal theory. Because of the explosive expansion of information in numerous "-omics" data banks, and the fragmentation of genetics into numerous subdisciplines, the importance of the synthesis paradigm will likely expand with time.

Integrating Evolutionary Game Theory into Mechanistic Genotype-Phenotype Mapping.

PubMed

Zhu, Xuli; Jiang, Libo; Ye, Meixia; Sun, Lidan; Gragnoli, Claudia; Wu, Rongling

2016-05-01

Natural selection has shaped the evolution of organisms toward optimizing their structural and functional design. However, how this universal principle can enhance genotype-phenotype mapping of quantitative traits has remained unexplored. Here we show that the integration of this principle and functional mapping through evolutionary game theory gains new insight into the genetic architecture of complex traits. By viewing phenotype formation as an evolutionary system, we formulate mathematical equations to model the ecological mechanisms that drive the interaction and coordination of its constituent components toward population dynamics and stability. Functional mapping provides a procedure for estimating the genetic parameters that specify the dynamic relationship of competition and cooperation and predicting how genes mediate the evolution of this relationship during trait formation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quantitative Reappraisal of the Helmholtz-Guyton Resonance Theory of Frequency Tuning in the Cochlea

PubMed Central

Babbs, Charles F.

2011-01-01

To explore the fundamental biomechanics of sound frequency transduction in the cochlea, a two-dimensional analytical model of the basilar membrane was constructed from first principles. Quantitative analysis showed that axial forces along the membrane are negligible, condensing the problem to a set of ordered one-dimensional models in the radial dimension, for which all parameters can be specified from experimental data. Solutions of the radial models for asymmetrical boundary conditions produce realistic deformation patterns. The resulting second-order differential equations, based on the original concepts of Helmholtz and Guyton, and including viscoelastic restoring forces, predict a frequency map and amplitudes of deflections that are consistent with classical observations. They also predict the effects of an observation hole drilled in the surrounding bone, the effects of curvature of the cochlear spiral, as well as apparent traveling waves under a variety of experimental conditions. A quantitative rendition of the classical Helmholtz-Guyton model captures the essence of cochlear mechanics and unifies the competing resonance and traveling wave theories. PMID:22028708

The Epimmunity Theory: The Single Cell Defenses against Infectious and Genetic Diseases.

PubMed

Barghouthi, Sameer A

2017-01-01

Single cell defense against diseases defines "epimmunity." Epimmunity is complementary to the immune system and can neither be substituted by innate nor by acquired immunity. Epimmunity, the proposed new branch of immunity, is further explored and analyzed for enucleated mature mammalian erythrocytes and nucleated erythrocytes of non-mammalian vertebrates leading to the development of "The Epimmunity Theory." Enucleation of mammalian erythroblast and inactivation of nuclei in erythrocytes of non-mammalian vertebrates are major contributors to the collective immunity: epimmunity, innate, and acquired. The fact that diseases of mature erythrocytes (MEs) are rare supports the notion that a single cell can resist microbial and genetic diseases; MEs are refractory to malaria and cancer. Nucleated cells, such as B-cells, T-cells, hepatocytes, and cell developmental stages are susceptible to genetic and specific microbial diseases depending on their nuclear activities and the receptors they express; such cells show lower epimmunity relative to MEs. Epimmunity is important as a disease insulator that prevents the spread of diseases from an infected tissue to the majority of other tissues. Breakdown of epimmunity may lead to disease development.

Novel quantitative pigmentation phenotyping enhances genetic association, epistasis, and prediction of human eye colour.

PubMed

Wollstein, Andreas; Walsh, Susan; Liu, Fan; Chakravarthy, Usha; Rahu, Mati; Seland, Johan H; Soubrane, Gisèle; Tomazzoli, Laura; Topouzis, Fotis; Vingerling, Johannes R; Vioque, Jesus; Böhringer, Stefan; Fletcher, Astrid E; Kayser, Manfred

2017-02-27

Success of genetic association and the prediction of phenotypic traits from DNA are known to depend on the accuracy of phenotype characterization, amongst other parameters. To overcome limitations in the characterization of human iris pigmentation, we introduce a fully automated approach that specifies the areal proportions proposed to represent differing pigmentation types, such as pheomelanin, eumelanin, and non-pigmented areas within the iris. We demonstrate the utility of this approach using high-resolution digital eye imagery and genotype data from 12 selected SNPs from over 3000 European samples of seven populations that are part of the EUREYE study. In comparison to previous quantification approaches, (1) we achieved an overall improvement in eye colour phenotyping, which provides a better separation of manually defined eye colour categories. (2) Single nucleotide polymorphisms (SNPs) known to be involved in human eye colour variation showed stronger associations with our approach. (3) We found new and confirmed previously noted SNP-SNP interactions. (4) We increased SNP-based prediction accuracy of quantitative eye colour. Our findings exemplify that precise quantification using the perceived biological basis of pigmentation leads to enhanced genetic association and prediction of eye colour. We expect our approach to deliver new pigmentation genes when applied to genome-wide association testing.

Novel quantitative pigmentation phenotyping enhances genetic association, epistasis, and prediction of human eye colour

PubMed Central

Wollstein, Andreas; Walsh, Susan; Liu, Fan; Chakravarthy, Usha; Rahu, Mati; Seland, Johan H.; Soubrane, Gisèle; Tomazzoli, Laura; Topouzis, Fotis; Vingerling, Johannes R.; Vioque, Jesus; Böhringer, Stefan; Fletcher, Astrid E.; Kayser, Manfred

2017-01-01

Success of genetic association and the prediction of phenotypic traits from DNA are known to depend on the accuracy of phenotype characterization, amongst other parameters. To overcome limitations in the characterization of human iris pigmentation, we introduce a fully automated approach that specifies the areal proportions proposed to represent differing pigmentation types, such as pheomelanin, eumelanin, and non-pigmented areas within the iris. We demonstrate the utility of this approach using high-resolution digital eye imagery and genotype data from 12 selected SNPs from over 3000 European samples of seven populations that are part of the EUREYE study. In comparison to previous quantification approaches, (1) we achieved an overall improvement in eye colour phenotyping, which provides a better separation of manually defined eye colour categories. (2) Single nucleotide polymorphisms (SNPs) known to be involved in human eye colour variation showed stronger associations with our approach. (3) We found new and confirmed previously noted SNP-SNP interactions. (4) We increased SNP-based prediction accuracy of quantitative eye colour. Our findings exemplify that precise quantification using the perceived biological basis of pigmentation leads to enhanced genetic association and prediction of eye colour. We expect our approach to deliver new pigmentation genes when applied to genome-wide association testing. PMID:28240252

A Network Neuroscience of Human Learning: Potential To Inform Quantitative Theories of Brain and Behavior

PubMed Central

Bassett, Danielle S.; Mattar, Marcelo G.

2017-01-01

Humans adapt their behavior to their external environment in a process often facilitated by learning. Efforts to describe learning empirically can be complemented by quantitative theories that map changes in neurophysiology to changes in behavior. In this review we highlight recent advances in network science that offer a sets of tools and a general perspective that may be particularly useful in understanding types of learning that are supported by distributed neural circuits. We describe recent applications of these tools to neuroimaging data that provide unique insights into adaptive neural processes, the attainment of knowledge, and the acquisition of new skills, forming a network neuroscience of human learning. While promising, the tools have yet to be linked to the well-formulated models of behavior that are commonly utilized in cognitive psychology. We argue that continued progress will require the explicit marriage of network approaches to neuroimaging data and quantitative models of behavior. PMID:28259554

A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior.

PubMed

Bassett, Danielle S; Mattar, Marcelo G

2017-04-01

Humans adapt their behavior to their external environment in a process often facilitated by learning. Efforts to describe learning empirically can be complemented by quantitative theories that map changes in neurophysiology to changes in behavior. In this review we highlight recent advances in network science that offer a sets of tools and a general perspective that may be particularly useful in understanding types of learning that are supported by distributed neural circuits. We describe recent applications of these tools to neuroimaging data that provide unique insights into adaptive neural processes, the attainment of knowledge, and the acquisition of new skills, forming a network neuroscience of human learning. While promising, the tools have yet to be linked to the well-formulated models of behavior that are commonly utilized in cognitive psychology. We argue that continued progress will require the explicit marriage of network approaches to neuroimaging data and quantitative models of behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

Developmental Patterning as a Quantitative Trait: Genetic Modulation of the Hoxb6 Mutant Skeletal Phenotype

PubMed Central

Kappen, Claudia

2016-01-01

The process of patterning along the anterior-posterior axis in vertebrates is highly conserved. The function of Hox genes in the axis patterning process is particularly well documented for bone development in the vertebral column and the limbs. We here show that Hoxb6, in skeletal elements at the cervico-thoracic junction, controls multiple independent aspects of skeletal pattern, implicating discrete developmental pathways as substrates for this transcription factor. In addition, we demonstrate that Hoxb6 function is subject to modulation by genetic factors. These results establish Hox-controlled skeletal pattern as a quantitative trait modulated by gene-gene interactions, and provide evidence that distinct modifiers influence the function of conserved developmental genes in fundamental patterning processes. PMID:26800342

Etiological theories of addiction: A comprehensive update on neurobiological, genetic and behavioural vulnerability.

PubMed

Ouzir, Mounir; Errami, Mohammed

2016-09-01

Currently, about 246 million people around the world have used an illicit drug. The reasons for this use are multiple: e.g. to augment the sensation of pleasure or to reduce the withdrawal and other aversive effects of a given substance. This raises the problem of addiction, which remains a disease of modern society. This review offers a comprehensive update of the different theories about the etiology of addictive behaviors with emphasis on the neurobiological, environmental, psychopathological, behavioural and genetic aspects of addictions, discussed from an evolutionary perspective. The main conclusion of this review is that vulnerability to drug addiction suggests an interaction between many brain systems (including the reward, decision-making, serotonergic, oxytocin, interoceptive insula, CRF, norepinephrine, dynorphin/KOR, orexin and vasopressin systems), genetic predisposition, sociocultural context, impulsivity and drugs types. Further advances in biological and psychological science are needed to address the problems of addiction at its roots. Copyright © 2016 Elsevier Inc. All rights reserved.

Rotorcraft flight control design using quantitative feedback theory and dynamic crossfeeds

NASA Technical Reports Server (NTRS)

Cheng, Rendy P.

1995-01-01

A multi-input, multi-output controls design with robust crossfeeds is presented for a rotorcraft in near-hovering flight using quantitative feedback theory (QFT). Decoupling criteria are developed for dynamic crossfeed design and implementation. Frequency dependent performance metrics focusing on piloted flight are developed and tested on 23 flight configurations. The metrics show that the resulting design is superior to alternative control system designs using conventional fixed-gain crossfeeds and to feedback-only designs which rely on high gains to suppress undesired off-axis responses. The use of dynamic, robust crossfeeds prior to the QFT design reduces the magnitude of required feedback gain and results in performance that meets current handling qualities specifications relative to the decoupling of off-axis responses. The combined effect of the QFT feedback design following the implementation of low-order, dynamic crossfeed compensator successfully decouples ten of twelve off-axis channels. For the other two channels it was not possible to find a single, low-order crossfeed that was effective.

Development of a screening method for genetically modified soybean by plasmid-based quantitative competitive polymerase chain reaction.

PubMed

Shimizu, Eri; Kato, Hisashi; Nakagawa, Yuki; Kodama, Takashi; Futo, Satoshi; Minegishi, Yasutaka; Watanabe, Takahiro; Akiyama, Hiroshi; Teshima, Reiko; Furui, Satoshi; Hino, Akihiro; Kitta, Kazumi

2008-07-23

A novel type of quantitative competitive polymerase chain reaction (QC-PCR) system for the detection and quantification of the Roundup Ready soybean (RRS) was developed. This system was designed based on the advantage of a fully validated real-time PCR method used for the quantification of RRS in Japan. A plasmid was constructed as a competitor plasmid for the detection and quantification of genetically modified soy, RRS. The plasmid contained the construct-specific sequence of RRS and the taxon-specific sequence of lectin1 (Le1), and both had 21 bp oligonucleotide insertion in the sequences. The plasmid DNA was used as a reference molecule instead of ground seeds, which enabled us to precisely and stably adjust the copy number of targets. The present study demonstrated that the novel plasmid-based QC-PCR method could be a simple and feasible alternative to the real-time PCR method used for the quantification of genetically modified organism contents.

Development of an event-specific hydrolysis probe quantitative real-time polymerase chain reaction assay for Embrapa 5.1 genetically modified common bean (Phaseolus vulgaris).

PubMed

Treml, Diana; Venturelli, Gustavo L; Brod, Fábio C A; Faria, Josias C; Arisi, Ana C M

2014-12-10

A genetically modified (GM) common bean event, namely Embrapa 5.1, resistant to the bean golden mosaic virus (BGMV), was approved for commercialization in Brazil. Brazilian regulation for genetically modified organism (GMO) labeling requires that any food containing more than 1% GMO be labeled. The event-specific polymerase chain reaction (PCR) method has been the primary trend for GMO identification and quantitation because of its high specificity based on the flanking sequence. This work reports the development of an event-specific assay, named FGM, for Embrapa 5.1 detection and quantitation by use of SYBR Green or hydrolysis probe. The FGM assay specificity was tested for Embrapa 2.3 event (a noncommercial GM common bean also resistant to BGMV), 46 non-GM common bean varieties, and other crop species including maize, GM maize, soybean, and GM soybean. The FGM assay showed high specificity to detect the Embrapa 5.1 event. Standard curves for the FGM assay presented a mean efficiency of 95% and a limit of detection (LOD) of 100 genome copies in the presence of background DNA. The primers and probe developed are suitable for the detection and quantitation of Embrapa 5.1.

Interlaboratory validation of quantitative duplex real-time PCR method for screening analysis of genetically modified maize.

PubMed

Takabatake, Reona; Koiwa, Tomohiro; Kasahara, Masaki; Takashima, Kaori; Futo, Satoshi; Minegishi, Yasutaka; Akiyama, Hiroshi; Teshima, Reiko; Oguchi, Taichi; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

2011-01-01

To reduce the cost and time required to routinely perform the genetically modified organism (GMO) test, we developed a duplex quantitative real-time PCR method for a screening analysis simultaneously targeting an event-specific segment for GA21 and Cauliflower Mosaic Virus 35S promoter (P35S) segment [Oguchi et al., J. Food Hyg. Soc. Japan, 50, 117-125 (2009)]. To confirm the validity of the method, an interlaboratory collaborative study was conducted. In the collaborative study, conversion factors (Cfs), which are required to calculate the GMO amount (%), were first determined for two real-time PCR instruments, the ABI PRISM 7900HT and the ABI PRISM 7500. A blind test was then conducted. The limit of quantitation for both GA21 and P35S was estimated to be 0.5% or less. The trueness and precision were evaluated as the bias and reproducibility of the relative standard deviation (RSD(R)). The determined bias and RSD(R) were each less than 25%. We believe the developed method would be useful for the practical screening analysis of GM maize.

Analysis of conditional genetic effects and variance components in developmental genetics.

PubMed

Zhu, J

1995-12-01

A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

The paradox of forest fragmentation genetics

Treesearch

Andrea T. Kramer; Jennifer L. Ison; Mary V. Ashley; Henry F. Howe

2008-01-01

Theory predicts widespread loss of genetic diversity from drift and inbreeding in trees subjected to habitat fragmentation, yet empirical support of this theory is scarce. We argue that population genetics theory may be misapplied in light of ecological realities that, when recognized, require scrutiny of underlying evolutionary assumptions. One ecological reality is...

Quantitative Theoretical and Conceptual Framework Use in Agricultural Education Research

ERIC Educational Resources Information Center

Kitchel, Tracy; Ball, Anna L.

2014-01-01

The purpose of this philosophical paper was to articulate the disciplinary tenets for consideration when using theory in agricultural education quantitative research. The paper clarified terminology around the concept of theory in social sciences and introduced inaccuracies of theory use in agricultural education quantitative research. Finally,…

Construction of a high-density genetic map by specific locus amplified fragment sequencing (SLAF-seq) and its application to Quantitative Trait Loci (QTL) analysis for boll weight in upland cotton (Gossypium hirsutum.).

PubMed

Zhang, Zhen; Shang, Haihong; Shi, Yuzhen; Huang, Long; Li, Junwen; Ge, Qun; Gong, Juwu; Liu, Aiying; Chen, Tingting; Wang, Dan; Wang, Yanling; Palanga, Koffi Kibalou; Muhammad, Jamshed; Li, Weijie; Lu, Quanwei; Deng, Xiaoying; Tan, Yunna; Song, Weiwu; Cai, Juan; Li, Pengtao; Rashid, Harun or; Gong, Wankui; Yuan, Youlu

2016-04-11

Upland Cotton (Gossypium hirsutum) is one of the most important worldwide crops it provides natural high-quality fiber for the industrial production and everyday use. Next-generation sequencing is a powerful method to identify single nucleotide polymorphism markers on a large scale for the construction of a high-density genetic map for quantitative trait loci mapping. In this research, a recombinant inbred lines population developed from two upland cotton cultivars 0-153 and sGK9708 was used to construct a high-density genetic map through the specific locus amplified fragment sequencing method. The high-density genetic map harbored 5521 single nucleotide polymorphism markers which covered a total distance of 3259.37 cM with an average marker interval of 0.78 cM without gaps larger than 10 cM. In total 18 quantitative trait loci of boll weight were identified as stable quantitative trait loci and were detected in at least three out of 11 environments and explained 4.15-16.70 % of the observed phenotypic variation. In total, 344 candidate genes were identified within the confidence intervals of these stable quantitative trait loci based on the cotton genome sequence. These genes were categorized based on their function through gene ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis and eukaryotic orthologous groups analysis. This research reported the first high-density genetic map for Upland Cotton (Gossypium hirsutum) with a recombinant inbred line population using single nucleotide polymorphism markers developed by specific locus amplified fragment sequencing. We also identified quantitative trait loci of boll weight across 11 environments and identified candidate genes within the quantitative trait loci confidence intervals. The results of this research would provide useful information for the next-step work including fine mapping, gene functional analysis, pyramiding breeding of functional genes as well as marker-assisted selection.

Using multiple PCR and CE with chemiluminescence detection for simultaneous qualitative and quantitative analysis of genetically modified organism.

PubMed

Guo, Longhua; Qiu, Bin; Chi, Yuwu; Chen, Guonan

2008-09-01

In this paper, an ultrasensitive CE-CL detection system coupled with a novel double-on-column coaxial flow detection interface was developed for the detection of PCR products. A reliable procedure based on this system had been demonstrated for qualitative and quantitative analysis of genetically modified organism-the detection of Roundup Ready Soy (RRS) samples was presented as an example. The promoter, terminator, function and two reference genes of RRS were amplified with multiplex PCR simultaneously. After that, the multiplex PCR products were labeled with acridinium ester at the 5'-terminal through an amino modification and then analyzed by the proposed CE-CL system. Reproducibility of analysis times and peak heights for the CE-CL analysis were determined to be better than 0.91 and 3.07% (RSD, n=15), respectively, for three consecutive days. It was shown that this method could accurately and qualitatively detect RRS standards and the simulative samples. The evaluation in terms of quantitative analysis of RRS provided by this new method was confirmed by comparing our assay results with those of the standard real-time quantitative PCR (RT-QPCR) using SYBR Green I dyes. The results showed a good coherence between the two methods. This approach demonstrated the possibility for accurate qualitative and quantitative detection of GM plants in a single run.

Cognitive Development, Genetics Problem Solving, and Genetics Instruction: A Critical Review.

ERIC Educational Resources Information Center

Smith, Mike U.; Sims, O. Suthern, Jr.

1992-01-01

Review of literature concerning problem solving in genetics and Piagetian stage theory. Authors conclude the research suggests that formal-operational thought is not strictly required for the solution of the majority of classical genetics problems; however, some genetic concepts are difficult for concrete operational students to understand.…

Using the realist perspective to link theory from qualitative evidence synthesis to quantitative studies: Broadening the matrix approach.

PubMed

van Grootel, Leonie; van Wesel, Floryt; O'Mara-Eves, Alison; Thomas, James; Hox, Joop; Boeije, Hennie

2017-09-01

This study describes an approach for the use of a specific type of qualitative evidence synthesis in the matrix approach, a mixed studies reviewing method. The matrix approach compares quantitative and qualitative data on the review level by juxtaposing concrete recommendations from the qualitative evidence synthesis against interventions in primary quantitative studies. However, types of qualitative evidence syntheses that are associated with theory building generate theoretical models instead of recommendations. Therefore, the output from these types of qualitative evidence syntheses cannot directly be used for the matrix approach but requires transformation. This approach allows for the transformation of these types of output. The approach enables the inference of moderation effects instead of direct effects from the theoretical model developed in a qualitative evidence synthesis. Recommendations for practice are formulated on the basis of interactional relations inferred from the qualitative evidence synthesis. In doing so, we apply the realist perspective to model variables from the qualitative evidence synthesis according to the context-mechanism-outcome configuration. A worked example shows that it is possible to identify recommendations from a theory-building qualitative evidence synthesis using the realist perspective. We created subsets of the interventions from primary quantitative studies based on whether they matched the recommendations or not and compared the weighted mean effect sizes of the subsets. The comparison shows a slight difference in effect sizes between the groups of studies. The study concludes that the approach enhances the applicability of the matrix approach. Copyright © 2017 John Wiley & Sons, Ltd.

Validation and application of quantitative PCR assays using host-specific Bacteroidales genetic markers for swine fecal pollution tracking.

PubMed

Fan, Lihua; Shuai, Jiangbing; Zeng, Ruoxue; Mo, Hongfei; Wang, Suhua; Zhang, Xiaofeng; He, Yongqiang

2017-12-01

Genome fragment enrichment (GFE) method was applied to identify host-specific bacterial genetic markers that differ among different fecal metagenomes. To enrich for swine-specific DNA fragments, swine fecal DNA composite (n = 34) was challenged against a DNA composite consisting of cow, human, goat, sheep, chicken, duck and goose fecal DNA extracts (n = 83). Bioinformatic analyses of 384 non-redundant swine enriched metagenomic sequences indicated a preponderance of Bacteroidales-like regions predicted to encode metabolism-associated, cellular processes and information storage and processing. After challenged against fecal DNA extracted from different animal sources, four sequences from the clone libraries targeting two Bacteroidales- (genes 1-38 and 3-53), a Clostridia- (gene 2-109) as well as a Bacilli-like sequence (gene 2-95), respectively, showed high specificity to swine feces based on PCR analysis. Host-specificity and host-sensitivity analysis confirmed that oligonucleotide primers and probes capable of annealing to select Bacteroidales-like sequences (1-38 and 3-53) exhibited high specificity (>90%) in quantitative PCR assays with 71 fecal DNAs from non-target animal sources. The two assays also demonstrated broad distributions of corresponding genetic markers (>94% positive) among 72 swine feces. After evaluation with environmental water samples from different areas, swine-targeted assays based on two Bacteroidales-like GFE sequences appear to be suitable quantitative tracing tools for swine fecal pollution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Experimental game theory and behavior genetics.

PubMed

Cesarini, David; Dawes, Christopher T; Johannesson, Magnus; Lichtenstein, Paul; Wallace, Björn

2009-06-01

We summarize the findings from a research program studying the heritability of behavior in a number of widely used economic games, including trust, dictator, and ultimatum games. Results from the standard behavior genetic variance decomposition suggest that strategies and fundamental economic preference parameters are moderately heritable, with estimates ranging from 18 to 42%. In addition, we also report new evidence on so-called "hyperfair" preferences in the ultimatum game. We discuss the implications of our findings with special reference to current efforts that seek to understand the molecular genetic architecture of complex social behaviors.

High Points of Human Genetics

ERIC Educational Resources Information Center

Stern, Curt

1975-01-01

Discusses such high points of human genetics as the study of chromosomes, somatic cell hybrids, the population formula: the Hardy-Weinberg Law, biochemical genetics, the single-active X Theory, behavioral genetics and finally how genetics can serve humanity. (BR)

The Influence of Self-Efficacy Beliefs and Metacognitive Prompting on Genetics Problem Solving Ability among High School Students in Kenya

NASA Astrophysics Data System (ADS)

Aurah, Catherine Muhonja

Within the framework of social cognitive theory, the influence of self-efficacy beliefs and metacognitive prompting on genetics problem solving ability among high school students in Kenya was examined through a mixed methods research design. A quasi-experimental study, supplemented by focus group interviews, was conducted to investigate both the outcomes and the processes of students' genetics problem-solving ability. Focus group interviews substantiated and supported findings from the quantitative instruments. The study was conducted in 17 high schools in Western Province, Kenya. A total of 2,138 high school students were purposively sampled. A sub-sample of 48 students participated in focus group interviews to understand their perspectives and experiences during the study so as to corroborate the quantitative data. Quantitative data were analyzed through descriptive statistics, zero-order correlations, 2 x 2 factorial ANOVA,, and sequential hierarchical multiple regressions. Qualitative data were transcribed, coded, and reported thematically. Results revealed metacognitive prompts had significant positive effects on student problem-solving ability independent of gender. Self-efficacy and metacognitive prompting significantly predicted genetics problem-solving ability. Gender differences were revealed, with girls outperforming boys on the genetics problem-solving test. Furthermore, self-efficacy moderated the relationship between metacognitive prompting and genetics problem-solving ability. This study established a foundation for instructional methods for biology teachers and recommendations are made for implementing metacognitive prompting in a problem-based learning environment in high schools and science teacher education programs in Kenya.

Analysis of Conditional Genetic Effects and Variance Components in Developmental Genetics

PubMed Central

Zhu, J.

1995-01-01

A genetic model with additive-dominance effects and genotype X environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t - 1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects. PMID:8601500

Dealing with the genetic load in bacterial synthetic biology circuits: convergences with the Ohm's law

PubMed Central

Carbonell-Ballestero, M.; Garcia-Ramallo, E.; Montañez, R.; Rodriguez-Caso, C.; Macía, J.

2016-01-01

Synthetic biology seeks to envision living cells as a matter of engineering. However, increasing evidence suggests that the genetic load imposed by the incorporation of synthetic devices in a living organism introduces a sort of unpredictability in the design process. As a result, individual part characterization is not enough to predict the behavior of designed circuits and thus, a costly trial-error process is eventually required. In this work, we provide a new theoretical framework for the predictive treatment of the genetic load. We mathematically and experimentally demonstrate that dependences among genes follow a quantitatively predictable behavior. Our theory predicts the observed reduction of the expression of a given synthetic gene when an extra genetic load is introduced in the circuit. The theory also explains that such dependence qualitatively differs when the extra load is added either by transcriptional or translational modifications. We finally show that the limitation of the cellular resources for gene expression leads to a mathematical formulation that converges to an expression analogous to the Ohm's law for electric circuits. Similitudes and divergences with this law are outlined. Our work provides a suitable framework with predictive character for the design process of complex genetic devices in synthetic biology. PMID:26656950

The Design of Power System Stability Controller Based on the PCH Theory and Improved Genetic Algorithm

NASA Astrophysics Data System (ADS)

Liu, Zhijian; Yin, Donghui; Yan, Jun

2017-05-01

Low frequency oscillation is still frequently happened in the power system and it affects the safety and stability of power system directly. With the continuously expending of the interconnection scale of power grid, the risk of low frequency oscillation becomes more and more noticeable. Firstly, the basic theory of port-controlled Hamilton (PCH) and its application is analyzed. Secondly, based on the PCH theory and the dynamic model of system, from the viewpoint of energy, the nonlinear stability controller of power system is designed. By the improved genetic algorithm, the parameters of the PCH model are optimized. Finally, a simulation model with PCH is built to vary the effectiveness of the method proposed in this paper.

A functional-structural model of rice linking quantitative genetic information with morphological development and physiological processes.

PubMed

Xu, Lifeng; Henke, Michael; Zhu, Jun; Kurth, Winfried; Buck-Sorlin, Gerhard

2011-04-01

Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype-phenotype model, we present here a three-dimensional functional-structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs. The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data. Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered. We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed.

A functional–structural model of rice linking quantitative genetic information with morphological development and physiological processes

PubMed Central

Xu, Lifeng; Henke, Michael; Zhu, Jun; Kurth, Winfried; Buck-Sorlin, Gerhard

2011-01-01

Background and Aims Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype–phenotype model, we present here a three-dimensional functional–structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs. Methods The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data. Key Results Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered. Conclusions We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed. PMID:21247905

Quantitative genetic analysis of the body composition and blood pressure association in two ethnically diverse populations.

PubMed

Ghosh, Sudipta; Dosaev, Tasbulat; Prakash, Jai; Livshits, Gregory

2017-04-01

The major aim of this study was to conduct comparative quantitative-genetic analysis of the body composition (BCP) and somatotype (STP) variation, as well as their correlations with blood pressure (BP) in two ethnically, culturally and geographically different populations: Santhal, indigenous ethnic group from India and Chuvash, indigenous population from Russia. Correspondently two pedigree-based samples were collected from 1,262 Santhal and1,558 Chuvash individuals, respectively. At the first stage of the study, descriptive statistics and a series of univariate regression analyses were calculated. Finally, multiple and multivariate regression (MMR) analyses, with BP measurements as dependent variables and age, sex, BCP and STP as independent variables were carried out in each sample separately. The significant and independent covariates of BP were identified and used for re-examination in pedigree-based variance decomposition analysis. Despite clear and significant differences between the populations in BCP/STP, both Santhal and Chuvash were found to be predominantly mesomorphic irrespective of their sex. According to MMR analyses variation of BP significantly depended on age and mesomorphic component in both samples, and in addition on sex, ectomorphy and fat mass index in Santhal and on fat free mass index in Chuvash samples, respectively. Additive genetic component contributes to a substantial proportion of blood pressure and body composition variance. Variance component analysis in addition to above mentioned results suggests that additive genetic factors influence BP and BCP/STP associations significantly. © 2017 Wiley Periodicals, Inc.

Quantitative reactive modeling and verification.

PubMed

Henzinger, Thomas A

Formal verification aims to improve the quality of software by detecting errors before they do harm. At the basis of formal verification is the logical notion of correctness , which purports to capture whether or not a program behaves as desired. We suggest that the boolean partition of software into correct and incorrect programs falls short of the practical need to assess the behavior of software in a more nuanced fashion against multiple criteria. We therefore propose to introduce quantitative fitness measures for programs, specifically for measuring the function, performance, and robustness of reactive programs such as concurrent processes. This article describes the goals of the ERC Advanced Investigator Project QUAREM. The project aims to build and evaluate a theory of quantitative fitness measures for reactive models. Such a theory must strive to obtain quantitative generalizations of the paradigms that have been success stories in qualitative reactive modeling, such as compositionality, property-preserving abstraction and abstraction refinement, model checking, and synthesis. The theory will be evaluated not only in the context of software and hardware engineering, but also in the context of systems biology. In particular, we will use the quantitative reactive models and fitness measures developed in this project for testing hypotheses about the mechanisms behind data from biological experiments.

Beyond Punnett Squares: Student Word Association and Explanations of Phenotypic Variation through an Integrative Quantitative Genetics Unit Investigating Anthocyanin Inheritance and Expression in Brassica rapa Fast Plants

PubMed Central

Smith, Amber R.; Williams, Paul H.; McGee, Seth A.; Dósa, Katalin; Pfammatter, Jesse

2014-01-01

Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question “What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev),” we developed a 4-wk unit for an inquiry-based laboratory course focused on the inheritance and expression of a quantitative trait in varying environments. We utilized Brassica rapa Fast Plants as a model organism to study variation in the phenotype anthocyanin pigment intensity. As an initial curriculum assessment, we used free word association to examine students’ cognitive structures before and after the unit and explanations in students’ final research posters with particular focus on variation (Pv = Gv + Ev). Comparison of pre- and postunit word frequency revealed a shift in words and a pattern of co-occurring concepts indicative of change in cognitive structure, with particular focus on “variation” as a proposed threshold concept and primary goal for students’ explanations. Given review of 53 posters, we found ∼50% of students capable of intermediate to high-level explanations combining both Gv and Ev influence on expression of anthocyanin intensity (Pv). While far from “plug and play,” this conceptually rich, inquiry-based unit holds promise for effective integration of quantitative and Mendelian genetics. PMID:25185225

Study books on ADHD genetics: balanced or biased?

PubMed

Te Meerman, Sanne; Batstra, Laura; Hoekstra, Rink; Grietens, Hans

2017-06-01

Academic study books are essential assets for disseminating knowledge about ADHD to future healthcare professionals. This study examined if they are balanced with regard to genetics. We selected and analyzed study books (N=43) used in (pre) master's programmes at 10 universities in the Netherlands. Because the mere behaviourally informed quantitative genetics give a much higher effect size of the genetic involvement in ADHD, it is important that study books contrast these findings with molecular genetics' outcomes. The latter studies use real genetic data, and their low effect sizes expose the potential weaknesses of quantitative genetics, like underestimating the involvement of the environment. Only a quarter of books mention both effect sizes and contrast these findings, while another quarter does not discuss any effect size. Most importantly, however, roughly half of the books in our sample mention only the effect sizes from quantitative genetic studies without addressing the low explained variance of molecular genetic studies. This may confuse readers by suggesting that the weakly associated genes support the quite spectacular, but potentially flawed estimates of twin, family and adoption studies, while they actually contradict them.

Quantitative collision induced mass spectrometry of substituted piperazines - A correlative analysis between theory and experiment

NASA Astrophysics Data System (ADS)

Ivanova, Bojidarka; Spiteller, Michael

2017-12-01

The present paper deals with quantitative kinetics and thermodynamics of collision induced dissociation (CID) reactions of piperazines under different experimental conditions together with a systematic description of effect of counter-ions on common MS fragment reactions of piperazines; and intra-molecular effect of quaternary cyclization of substituted piperazines yielding to quaternary salts. There are discussed quantitative model equations of rate constants as well as free Gibbs energies of series of m-independent CID fragment processes in GP, which have been evidenced experimentally. Both kinetic and thermodynamic parameters are also predicted by computational density functional theory (DFT) and ab initio both static and dynamic methods. The paper examines validity of Maxwell-Boltzmann distribution to non-Boltzmann CID processes in quantitatively as well. The experiments conducted within the latter framework yield to an excellent correspondence with theoretical quantum chemical modeling. The important property of presented model equations of reaction kinetics is the applicability in predicting unknown and assigning of known mass spectrometric (MS) patterns. The nature of "GP" continuum of CID-MS coupled scheme of measurements with electrospray ionization (ESI) source is discussed, performing parallel computations in gas-phase (GP) and polar continuum at different temperatures and ionic strengths. The effect of pressure is presented. The study contributes significantly to methodological and phenomenological developments of CID-MS and its analytical implementations for quantitative and structural analyses. It also demonstrates great prospective of a complementary application of experimental CID-MS and computational quantum chemistry studying chemical reactivity, among others. To a considerable extend this work underlies the place of computational quantum chemistry to the field of experimental analytical chemistry in particular highlighting the structural analysis.

Ancestral trees for modeling stem cell lineages genetically rather than functionally: understanding mutation accumulation and distinguishing the restrictive cancer stem cell propagation theory and the unrestricted cell propagation theory of human tumorigenesis.

PubMed

Shibata, Darryl K; Kern, Scott E

2008-01-01

Cancer stem cells either could be rare or common in tumors, constituting the major distinction between the two fundamentally opposed theoretical models of tumor progression: A newer and restrictive stem cell propagation model, in which the stem cells are a small and special minority of the tumor cells, and a standard older model, an unrestricted cell proliferation theory, in which many or most tumor cells are capable of indefinite generations of cell division. Stem cells of tumors are difficult to quantitate using functional assays, and the validity of the most common assays is seriously questioned. Nonetheless, stem cells are an essential component of any tumorigenesis model. Alternative approaches to studying tumor stem cells should be explored. Cell populations can be conceived of as having a genealogy, a relationship of cells to their ancestral lineage, from the zygote to the adult cells or neoplasms. Models using ancestral trees thus offer an anatomic and genetic means to "observe" stem cells independent of artificial conditions. Ancestral trees broaden our attention backward along a lineage, to the zygote stage, and thereby add insight into how the mutations of tumors accumulate. It is possible that a large fraction of mutations in a tumor originate from normal, endogenous, replication errors (nearly all being passenger mutations) occurring prior to the emergence of the first transformed cell. Trees can be constructed from experimental measurements - molecular clocks - of real human tissues and tumors. Detailed analysis of single-cell methylation patterns, heritable yet slightly plastic, now can provide this information in the necessary depth. Trees based on observations of molecular clocks may help us to distinguish between competing theories regarding the proliferative properties among cells of actual human tumors, to observe subtle and difficult phenomena such as the extinction of stem lineages, and to address the origins and rates of mutations in various

Controls design with crossfeeds for hovering rotorcraft using quantitative feedback theory

NASA Technical Reports Server (NTRS)

Tischler, Mark B.; Biezad, Daniel J.; Cheng, Rendy

1996-01-01

A multi-input, multi-output controls design with dynamic crossfeed pre-compensation is presented for rotorcraft in near-hovering flight using Quantitative Feedback Theory (QFT). The resulting closed-loop control system bandwidth allows the rotorcraft to be considered for use as an inflight simulator. The use of dynamic, robust crossfeeds prior to the QFT design reduces the magnitude of required feedback gain and results in performance that meets most handling qualities specifications relative to the decoupling of off-axis responses. Handling qualities are Level 1 for both low-gain tasks and high-gain tasks in the roll, pitch, and yaw axes except for the 10 deg/sec moderate-amplitude yaw command where the rotorcraft exhibits Level 2 handling qualities in the yaw axis caused by phase lag. The combined effect of the QFT feedback design following the implementation of low-order, dynamic crossfeed compensators successfully decouples ten of twelve off-axis channels. For the other two channels it was not possible to find a single, low-order crossfeed that was effective. This is an area to be investigated in future research.

Mate choice theory and the mode of selection in sexual populations.

PubMed

Carson, Hampton L

2003-05-27

Indirect new data imply that mate and/or gamete choice are major selective forces driving genetic change in sexual populations. The system dictates nonrandom mating, an evolutionary process requiring both revised genetic theory and new data on heritability of characters underlying Darwinian fitness. Successfully reproducing individuals represent rare selections from among vigorous, competing survivors of preadult natural selection. Nonrandom mating has correlated demographic effects: reduced effective population size, inbreeding, low gene flow, and emphasis on deme structure. Characters involved in choice behavior at reproduction appear based on quantitative trait loci. This variability serves selection for fitness within the population, having only an incidental relationship to the origin of genetically based reproductive isolation between populations. The claim that extensive hybridization experiments with Drosophila indicate that selection favors a gradual progression of "isolating mechanisms" is flawed, because intra-group random mating is assumed. Over deep time, local sexual populations are strong, independent genetic systems that use rich fields of variable polygenic components of fitness. The sexual reproduction system thus particularizes, in small subspecific populations, the genetic basis of the grand adaptive sweep of selective evolutionary change, much as Darwin proposed.

Rethinking the transmission gap: What behavioral genetics and evolutionary psychology mean for attachment theory: A comment on Verhage et al. (2016).

PubMed

Barbaro, Nicole; Boutwell, Brian B; Barnes, J C; Shackelford, Todd K

2017-01-01

Traditional attachment theory posits that attachment in infancy and early childhood is the result of intergenerational transmission of attachment from parents to offspring. Verhage et al. (2016) present meta-analytic evidence addressing the intergenerational transmission of attachment between caregivers and young children. In this commentary, we argue that their appraisal of the behavioral genetics literature is incomplete. The suggested research focus on shared environmental effects may dissuade the pursuit of profitable avenues of research and may hinder progress in attachment theory. Specifically, further research on the "transmission gap" will continue to limit our understanding of attachment etiology. We discuss recent theoretical developments from an evolutionary psychological perspective that can provide a valuable framework to account for the existing behavioral genetic data. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Efficacy of a Web-based Intelligent Tutoring System for Communicating Genetic Risk of Breast Cancer: A Fuzzy-Trace Theory Approach

PubMed Central

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

2014-01-01

Background Many healthy women consider genetic testing for breast cancer risk, yet BRCA testing issues are complex. Objective Determining whether an intelligent tutor, BRCA Gist, grounded in fuzzy-trace theory (FTT), increases gist comprehension and knowledge about genetic testing for breast cancer risk, improving decision-making. Design In two experiments, 410 healthy undergraduate women were randomly assigned to one of three groups: an online module using a web-based tutoring system (BRCA Gist) that uses artificial intelligence technology, a second group read highly similar content from the NCI web site, and a third completed an unrelated tutorial. Intervention BRCA Gist applied fuzzy trace theory and was designed to help participants develop gist comprehension of topics relevant to decisions about BRCA genetic testing, including how breast cancer spreads, inherited genetic mutations, and base rates. Measures We measured content knowledge, gist comprehension of decision-relevant information, interest in testing, and genetic risk and testing judgments. Results Control knowledge scores ranged from 54% to 56%, NCI improved significantly to 65% and 70%, and BRCA Gist improved significantly more to 75% and 77%, p<.0001. BRCA Gist scored higher on gist comprehension than NCI and control, p<.0001. Control genetic risk-assessment mean was 48% correct; BRCA Gist (61%), and NCI (56%) were significantly higher, p<.0001. BRCA Gist participants recommended less testing for women without risk factors (not good candidates), (24% and 19%) than controls (50%, both experiments) and NCI, (32%) Experiment 2, p<.0001. BRCA Gist testing interest was lower than controls, p<.0001. Limitations BRCA Gist has not been tested with older women from diverse groups. Conclusions Intelligent tutors, such as BRCA Gist, are scalable, cost effective ways of helping people understand complex issues, improving decision-making. PMID:24829276

Easy calculations of lod scores and genetic risks on small computers.

PubMed Central

Lathrop, G M; Lalouel, J M

1984-01-01

A computer program that calculates lod scores and genetic risks for a wide variety of both qualitative and quantitative genetic traits is discussed. An illustration is given of the joint use of a genetic marker, affection status, and quantitative information in counseling situations regarding Duchenne muscular dystrophy. PMID:6585139

Genes, Environment, and Race: Quantitative Genetic Approaches

ERIC Educational Resources Information Center

Whitfield, Keith E.; McClearn, Gerald

2005-01-01

Understanding the origins of racial health disparities is currently a central focus of health-oriented funding agencies and the health policy community. In particular, the role of genetics in the origin of racial health disparities is receiving growing attention and has been susceptible to considerable misinterpretation. In this article, the…

Study books on ADHD genetics: balanced or biased?

PubMed Central

te Meerman, Sanne; Batstra, Laura; Hoekstra, Rink; Grietens, Hans

2017-01-01

ABSTRACT Academic study books are essential assets for disseminating knowledge about ADHD to future healthcare professionals. This study examined if they are balanced with regard to genetics. We selected and analyzed study books (N=43) used in (pre) master’s programmes at 10 universities in the Netherlands. Because the mere behaviourally informed quantitative genetics give a much higher effect size of the genetic involvement in ADHD, it is important that study books contrast these findings with molecular genetics’ outcomes. The latter studies use real genetic data, and their low effect sizes expose the potential weaknesses of quantitative genetics, like underestimating the involvement of the environment. Only a quarter of books mention both effect sizes and contrast these findings, while another quarter does not discuss any effect size. Most importantly, however, roughly half of the books in our sample mention only the effect sizes from quantitative genetic studies without addressing the low explained variance of molecular genetic studies. This may confuse readers by suggesting that the weakly associated genes support the quite spectacular, but potentially flawed estimates of twin, family and adoption studies, while they actually contradict them. PMID:28532325

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

Classification of cassava genotypes based on qualitative and quantitative data.

PubMed

Oliveira, E J; Oliveira Filho, O S; Santos, V S

2015-02-02

We evaluated the genetic variation of cassava accessions based on qualitative (binomial and multicategorical) and quantitative traits (continuous). We characterized 95 accessions obtained from the Cassava Germplasm Bank of Embrapa Mandioca e Fruticultura; we evaluated these accessions for 13 continuous, 10 binary, and 25 multicategorical traits. First, we analyzed the accessions based only on quantitative traits; next, we conducted joint analysis (qualitative and quantitative traits) based on the Ward-MLM method, which performs clustering in two stages. According to the pseudo-F, pseudo-t2, and maximum likelihood criteria, we identified five and four groups based on quantitative trait and joint analysis, respectively. The smaller number of groups identified based on joint analysis may be related to the nature of the data. On the other hand, quantitative data are more subject to environmental effects in the phenotype expression; this results in the absence of genetic differences, thereby contributing to greater differentiation among accessions. For most of the accessions, the maximum probability of classification was >0.90, independent of the trait analyzed, indicating a good fit of the clustering method. Differences in clustering according to the type of data implied that analysis of quantitative and qualitative traits in cassava germplasm might explore different genomic regions. On the other hand, when joint analysis was used, the means and ranges of genetic distances were high, indicating that the Ward-MLM method is very useful for clustering genotypes when there are several phenotypic traits, such as in the case of genetic resources and breeding programs.

Synthesis strategy: building a culturally sensitive mid-range theory of risk perception using literary, quantitative, and qualitative methods.

PubMed

Siaki, Leilani A; Loescher, Lois J; Trego, Lori L

2013-03-01

This article presents a discussion of development of a mid-range theory of risk perception. Unhealthy behaviours contribute to the development of health inequalities worldwide. The link between perceived risk and successful health behaviour change is inconclusive, particularly in vulnerable populations. This may be attributed to inattention to culture. The synthesis strategy of theory building guided the process using three methods: (1) a systematic review of literature published between 2000-2011 targeting perceived risk in vulnerable populations; (2) qualitative and (3) quantitative data from a study of Samoan Pacific Islanders at high risk of cardiovascular disease and diabetes. Main concepts of this theory include risk attention, appraisal processes, cognition, and affect. Overarching these concepts is health-world view: cultural ways of knowing, beliefs, values, images, and ideas. This theory proposes the following: (1) risk attention varies based on knowledge of the health risk in the context of health-world views; (2) risk appraisals are influenced by affect, health-world views, cultural customs, and protocols that intersect with the health risk; (3) strength of cultural beliefs, values, and images (cultural identity) mediate risk attention and risk appraisal influencing the likelihood that persons will engage in health-promoting behaviours that may contradict cultural customs/protocols. Interventions guided by a culturally sensitive mid-range theory may improve behaviour-related health inequalities in vulnerable populations. The synthesis strategy is an intensive process for developing a culturally sensitive mid-range theory. Testing of the theory will ascertain its usefulness for reducing health inequalities in vulnerable groups. © 2012 Blackwell Publishing Ltd.

DRIFTSEL: an R package for detecting signals of natural selection in quantitative traits.

PubMed

Karhunen, M; Merilä, J; Leinonen, T; Cano, J M; Ovaskainen, O

2013-07-01

Approaches and tools to differentiate between natural selection and genetic drift as causes of population differentiation are of frequent demand in evolutionary biology. Based on the approach of Ovaskainen et al. (2011), we have developed an R package (DRIFTSEL) that can be used to differentiate between stabilizing selection, diversifying selection and random genetic drift as causes of population differentiation in quantitative traits when neutral marker and quantitative genetic data are available. Apart from illustrating the use of this method and the interpretation of results using simulated data, we apply the package on data from three-spined sticklebacks (Gasterosteus aculeatus) to highlight its virtues. DRIFTSEL can also be used to perform usual quantitative genetic analyses in common-garden study designs. © 2013 John Wiley & Sons Ltd.

Genetical Genomics Identifies the Genetic Architecture for Growth and Weevil Resistance in Spruce

PubMed Central

Porth, Ilga; White, Richard; Jaquish, Barry; Alfaro, René; Ritland, Carol; Ritland, Kermit

2012-01-01

In plants, relationships between resistance to herbivorous insect pests and growth are typically controlled by complex interactions between genetically correlated traits. These relationships often result in tradeoffs in phenotypic expression. In this study we used genetical genomics to elucidate genetic relationships between tree growth and resistance to white pine terminal weevil (Pissodes strobi Peck.) in a pedigree population of interior spruce (Picea glauca, P. engelmannii and their hybrids) that was growing at Vernon, B.C. and segregating for weevil resistance. Genetical genomics uses genetic perturbations caused by allelic segregation in pedigrees to co-locate quantitative trait loci (QTLs) for gene expression and quantitative traits. Bark tissue of apical leaders from 188 trees was assayed for gene expression using a 21.8K spruce EST-spotted microarray; the same individuals were genotyped for 384 SNP markers for the genetic map. Many of the expression QTLs (eQTL) co-localized with resistance trait QTLs. For a composite resistance phenotype of six attack and oviposition traits, 149 positional candidate genes were identified. Resistance and growth QTLs also overlapped with eQTL hotspots along the genome suggesting that: 1) genetic pleiotropy of resistance and growth traits in interior spruce was substantial, and 2) master regulatory genes were important for weevil resistance in spruce. These results will enable future work on functional genetic studies of insect resistance in spruce, and provide valuable information about candidate genes for genetic improvement of spruce. PMID:22973444

Application of Fault Management Theory to the Quantitative Selection of a Launch Vehicle Abort Trigger Suite

NASA Technical Reports Server (NTRS)

Lo, Yunnhon; Johnson, Stephen B.; Breckenridge, Jonathan T.

2014-01-01

The theory of System Health Management (SHM) and of its operational subset Fault Management (FM) states that FM is implemented as a "meta" control loop, known as an FM Control Loop (FMCL). The FMCL detects that all or part of a system is now failed, or in the future will fail (that is, cannot be controlled within acceptable limits to achieve its objectives), and takes a control action (a response) to return the system to a controllable state. In terms of control theory, the effectiveness of each FMCL is estimated based on its ability to correctly estimate the system state, and on the speed of its response to the current or impending failure effects. This paper describes how this theory has been successfully applied on the National Aeronautics and Space Administration's (NASA) Space Launch System (SLS) Program to quantitatively estimate the effectiveness of proposed abort triggers so as to select the most effective suite to protect the astronauts from catastrophic failure of the SLS. The premise behind this process is to be able to quantitatively provide the value versus risk trade-off for any given abort trigger, allowing decision makers to make more informed decisions. All current and planned crewed launch vehicles have some form of vehicle health management system integrated with an emergency launch abort system to ensure crew safety. While the design can vary, the underlying principle is the same: detect imminent catastrophic vehicle failure, initiate launch abort, and extract the crew to safety. Abort triggers are the detection mechanisms that identify that a catastrophic launch vehicle failure is occurring or is imminent and cause the initiation of a notification to the crew vehicle that the escape system must be activated. While ensuring that the abort triggers provide this function, designers must also ensure that the abort triggers do not signal that a catastrophic failure is imminent when in fact the launch vehicle can successfully achieve orbit. That is

Author's Response to Commentaries on: "An Interpretation of Part of Gilbert Gottlieb's Legacy: Developmental Systems Theory Contra Developmental Behavior Genetics"

ERIC Educational Resources Information Center

Molenaar, Peter C. M.

2015-01-01

In this article, Peter Molenaar responds to three commentaries (this issue) on his article, "An Interpretation of Part of Gilbert Gottlieb's Legacy: Developmental Systems Theory Contra Developmental Behavior Genetics." He addresses aspects of relational developmental systems (RDS) mentioned and questions raised in each of the…

Species detection and identification in sexual organisms using population genetic theory and DNA sequences.

PubMed

Birky, C William

2013-01-01

Phylogenetic trees of DNA sequences of a group of specimens may include clades of two kinds: those produced by stochastic processes (random genetic drift) within a species, and clades that represent different species. The ratio of the mean pairwise sequence difference between a pair of clades (K) to the mean pairwise sequence difference within a clade (θ) can be used to determine whether the clades are samples from different species (K/θ ≥ 4) or the same species (K/θ<4) with probability ≥ 0.95. Previously I applied this criterion to delimit species of asexual organisms. Here I use data from the literature to show how it can also be applied to delimit sexual species using four groups of sexual organisms as examples: ravens, spotted leopards, sea butterflies, and liverworts. Mitochondrial or chloroplast genes are used because these segregate earlier during speciation than most nuclear genes and hence detect earlier stages of speciation. In several cases the K/θ ratio was greater than 4, confirming the original authors' intuition that the clades were sufficiently different to be assigned to different species. But the K/θ ratio split each of two liverwort species into two evolutionary species, and showed that support for the distinction between the common and Chihuahuan raven species is weak. I also discuss some possible sources of error in using the K/θ ratio; the most significant one would be cases where males migrate between different populations but females do not, making the use of maternally inherited organelle genes problematic. The K/θ ratio must be used with some caution, like all other methods for species delimitation. Nevertheless, it is a simple theory-based quantitative method for using DNA sequences to make rigorous decisions about species delimitation in sexual as well as asexual eukaryotes.

Characteristics of quantitative nursing research from 1990 to 2010.

PubMed

Yarcheski, Adela; Mahon, Noreen E

2013-12-01

To assess author credentials of quantitative research in nursing, the composition of the research teams, and the disciplinary focus of the theories tested. Nursing Research, Western Journal of Nursing Research, and Journal of Advanced Nursing were selected for this descriptive study; 1990, 1995, 2000, 2005, and 2010 were included. The final sample consisted of 484 quantitative research articles. From 1990 to 2010, there was an increase in first authors holding doctoral degrees, research from other countries, and funding. Solo authorship decreased; multi-authorship and multidisciplinary teams increased. Theories tested were mostly from psychology; the testing of nursing theory was modest. Multidisciplinary research far outdistanced interdisciplinary research. Quantitative nursing research can be characterized as multidisciplinary (distinct theories from different disciplines) rather than discipline-specific to nursing. Interdisciplinary (theories synthesized from different disciplines) research has been conducted minimally. This study provides information about the growth of the scientific knowledge base of nursing, which has implications for practice. © 2013 Sigma Theta Tau International.

Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir

Treesearch

Nicholas C. Wheeler; Kathleen D. Jermstad; Konstantin V. Krutovsky; Sally N. Aitken; Glenn T. Howe; Jodie Krakowski; David B. Neale

2005-01-01

Quantitative trait locus (QTL) analyses are used by geneticists to characterize the genetic architecture of quantitative traits, provide a foundation for marker-aided-selection (MAS), and provide a framework for positional selection of candidate genes. The most useful QTL for breeding applications are those that have been verified in time, space, and/or genetic...

Sex-dependent expression of behavioural genetic architectures and the evolution of sexual dimorphism.

PubMed

Han, Chang S; Dingemanse, Niels J

2017-10-11

Empirical studies imply that sex-specific genetic architectures can resolve evolutionary conflicts between males and females, and thereby facilitate the evolution of sexual dimorphism. Sex-specificity of behavioural genetic architectures has, however, rarely been considered. Moreover, as the expression of genetic (co)variances is often environment-dependent, general inferences on sex-specific genetic architectures require estimates of quantitative genetics parameters under multiple conditions. We measured exploration and aggression in pedigreed populations of southern field crickets ( Gryllus bimaculatus ) raised on either naturally balanced (free-choice) or imbalanced (protein-deprived) diets. For each dietary condition, we measured for each behavioural trait (i) level of sexual dimorphism, (ii) level of sex-specificity of survival selection gradients, (iii) level of sex-specificity of additive genetic variance, and (iv) strength of the cross-sex genetic correlation. We report here evidence for sexual dimorphism in behaviour as well as sex-specificity in the expression of genetic (co)variances as predicted by theory. The additive genetic variances of exploration and aggression were significantly greater in males compared with females. Cross-sex genetic correlations were highly positive for exploration but deviating (significantly) from one for aggression; findings were consistent across dietary treatments. This suggests that genetic architectures characterize the sexually dimorphic focal behaviours across various key environmental conditions in the wild. Our finding also highlights that sexual conflict can be resolved by evolving sexually independent genetic architectures. © 2017 The Author(s).

Quantitative assessment of skin, hair, and iris variation in a diverse sample of individuals and associated genetic variation.

PubMed

Norton, Heather L; Edwards, Melissa; Krithika, S; Johnson, Monique; Werren, Elizabeth A; Parra, Esteban J

2016-08-01

The main goals of this study are to 1) quantitatively measure skin, hair, and iris pigmentation in a diverse sample of individuals, 2) describe variation within and between these samples, and 3) demonstrate how quantitative measures can facilitate genotype-phenotype association tests. We quantitatively characterize skin, hair, and iris pigmentation using the Melanin (M) Index (skin) and CIELab values (hair) in 1,450 individuals who self-identify as African American, East Asian, European, Hispanic, or South Asian. We also quantify iris pigmentation in a subset of these individuals using CIELab values from high-resolution iris photographs. We compare mean skin M index and hair and iris CIELab values among populations using ANOVA and MANOVA respectively and test for genotype-phenotype associations in the European sample. All five populations are significantly different for skin (P <2 × 10(-16) ) and hair color (P <2 × 10(-16) ). Our quantitative analysis of iris and hair pigmentation reinforces the continuous, rather than discrete, nature of these traits. We confirm the association of three loci (rs16891982, rs12203592, and rs12913832) with skin pigmentation and four loci (rs12913832, rs12203592, rs12896399, and rs16891982) with hair pigmentation. Interestingly, the derived rs12203592 T allele located within the IRF4 gene is associated with lighter skin but darker hair color. The quantitative methods used here provide a fine-scale assessment of pigmentation phenotype and facilitate genotype-phenotype associations, even with relatively small sample sizes. This represents an important expansion of current investigations into pigmentation phenotype and associated genetic variation by including non-European and admixed populations. Am J Phys Anthropol 160:570-581, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

IWGT report on quantitative approaches to genotoxicity risk ...

EPA Pesticide Factsheets

This is the second of two reports from the International Workshops on Genotoxicity Testing (IWGT) Working Group on Quantitative Approaches to Genetic Toxicology Risk Assessment (the QWG). The first report summarized the discussions and recommendations of the QWG related to the need for quantitative dose–response analysis of genetic toxicology data, the existence and appropriate evaluation of threshold responses, and methods to analyze exposure-response relationships and derive points of departure (PoDs) from which acceptable exposure levels could be determined. This report summarizes the QWG discussions and recommendations regarding appropriate approaches to evaluate exposure-related risks of genotoxic damage, including extrapolation below identified PoDs and across test systems and species. Recommendations include the selection of appropriate genetic endpoints and target tissues, uncertainty factors and extrapolation methods to be considered, the importance and use of information on mode of action, toxicokinetics, metabolism, and exposure biomarkers when using quantitative exposure-response data to determine acceptable exposure levels in human populations or to assess the risk associated with known or anticipated exposures. The empirical relationship between genetic damage (mutation and chromosomal aberration) and cancer in animal models was also examined. It was concluded that there is a general correlation between cancer induction and mutagenic and/or clast

Human genetics of infectious diseases: a unified theory

PubMed Central

Casanova, Jean-Laurent; Abel, Laurent

2007-01-01

Since the early 1950s, the dominant paradigm in the human genetics of infectious diseases postulates that rare monogenic immunodeficiencies confer vulnerability to multiple infectious diseases (one gene, multiple infections), whereas common infections are associated with the polygenic inheritance of multiple susceptibility genes (one infection, multiple genes). Recent studies, since 1996 in particular, have challenged this view. A newly recognised group of primary immunodeficiencies predisposing the individual to a principal or single type of infection is emerging. In parallel, several common infections have been shown to reflect the inheritance of one major susceptibility gene, at least in some populations. This novel causal relationship (one gene, one infection) blurs the distinction between patient-based Mendelian genetics and population-based complex genetics, and provides a unified conceptual frame for exploring the molecular genetic basis of infectious diseases in humans. PMID:17255931

Differential contribution of genomic regions to marked genetic variation and prediction of quantitative traits in broiler chickens.

PubMed

Abdollahi-Arpanahi, Rostam; Morota, Gota; Valente, Bruno D; Kranis, Andreas; Rosa, Guilherme J M; Gianola, Daniel

2016-02-03

phenotypic variation for the three traits studied. Overall, the contribution of additive genetic variance to the total genetic variance was much greater than that of dominance variance. Our results show that all genomic regions are important for the prediction of the targeted traits, and the whole-genome approach was reaffirmed as the best tool for genome-enabled prediction of quantitative traits.

Factor analysis in the Genetics of Asthma International Network family study identifies five major quantitative asthma phenotypes.

PubMed

Pillai, S G; Tang, Y; van den Oord, E; Klotsman, M; Barnes, K; Carlsen, K; Gerritsen, J; Lenney, W; Silverman, M; Sly, P; Sundy, J; Tsanakas, J; von Berg, A; Whyte, M; Ortega, H G; Anderson, W H; Helms, P J

2008-03-01

quantitative traits may be better phenotypes in epidemiological and genetic analyses than those categories derived from the presence or absence of combinations of +ve SPTs and/or elevated IgE.

Application of the protection motivation theory to genetic testing for breast cancer risk.

PubMed

Helmes, Almut W

2002-11-01

Many women, even women at low risk, are interested in genetic testing for breast cancer risk. However, the test has little to offer for women at low to moderate risk. We applied the Protection Motivation Theory (PMT) to investigate predictors of women's motivation to obtain such a test. Women at low to moderate risk (n = 330) were recruited through a physician network. They received an informational letter by mail and completed a telephone survey and a written baseline questionnaire. Structural equation analyses with motivation to test as the outcome variable showed that the full model was not supported by the data. However, modifications to the model resulted in good model fit and explained 51% of the variance. Women with increased breast cancer worries, which were influenced by perceived risk, and women who saw more disadvantages of not getting tested showed more motivation to pursue testing. Women who saw more advantages of not getting tested showed less motivation. Applying the PMT was helpful in determining factors that play a role in women's intentions to obtain genetic testing. Counseling should aim at decreasing perceived risk and breast cancer worries and include a discussion of the consequences of not getting tested.

Application of Fault Management Theory to the Quantitive Selection of a Launch Vehicle Abort Trigger Suite

NASA Technical Reports Server (NTRS)

Lo, Yunnhon; Johnson, Stephen B.; Breckenridge, Jonathan T.

2014-01-01

SHM/FM theory has been successfully applied to the selection of the baseline set Abort Triggers for the NASA SLS center dot Quantitative assessment played a useful role in the decision process ? M&FM, which is new within NASA MSFC, required the most "new" work, as this quantitative analysis had never been done before center dot Required development of the methodology and tool to mechanize the process center dot Established new relationships to the other groups ? The process is now an accepted part of the SLS design process, and will likely be applied to similar programs in the future at NASA MSFC ? Future improvements center dot Improve technical accuracy ?Differentiate crew survivability due to an abort, vs. survivability even no immediate abort occurs (small explosion with little debris) ?Account for contingent dependence of secondary triggers on primary triggers ?Allocate "? LOC Benefit" of each trigger when added to the previously selected triggers. center dot Reduce future costs through the development of a specialized tool ? Methodology can be applied to any manned/unmanned vehicle, in space or terrestrial

The Genetic Interpretation of Area under the ROC Curve in Genomic Profiling

PubMed Central

Wray, Naomi R.; Yang, Jian; Goddard, Michael E.; Visscher, Peter M.

2010-01-01

Genome-wide association studies in human populations have facilitated the creation of genomic profiles which combine the effects of many associated genetic variants to predict risk of disease. The area under the receiver operator characteristic (ROC) curve is a well established measure for determining the efficacy of tests in correctly classifying diseased and non-diseased individuals. We use quantitative genetics theory to provide insight into the genetic interpretation of the area under the ROC curve (AUC) when the test classifier is a predictor of genetic risk. Even when the proportion of genetic variance explained by the test is 100%, there is a maximum value for AUC that depends on the genetic epidemiology of the disease, i.e. either the sibling recurrence risk or heritability and disease prevalence. We derive an equation relating maximum AUC to heritability and disease prevalence. The expression can be reversed to calculate the proportion of genetic variance explained given AUC, disease prevalence, and heritability. We use published estimates of disease prevalence and sibling recurrence risk for 17 complex genetic diseases to calculate the proportion of genetic variance that a test must explain to achieve AUC = 0.75; this varied from 0.10 to 0.74. We provide a genetic interpretation of AUC for use with predictors of genetic risk based on genomic profiles. We provide a strategy to estimate proportion of genetic variance explained on the liability scale from estimates of AUC, disease prevalence, and heritability (or sibling recurrence risk) available as an online calculator. PMID:20195508

The population genetics of mutations: good, bad and indifferent

PubMed Central

Loewe, Laurence; Hill, William G.

2010-01-01

Population genetics is fundamental to our understanding of evolution, and mutations are essential raw materials for evolution. In this introduction to more detailed papers that follow, we aim to provide an oversight of the field. We review current knowledge on mutation rates and their harmful and beneficial effects on fitness and then consider theories that predict the fate of individual mutations or the consequences of mutation accumulation for quantitative traits. Many advances in the past built on models that treat the evolution of mutations at each DNA site independently, neglecting linkage of sites on chromosomes and interactions of effects between sites (epistasis). We review work that addresses these limitations, to predict how mutations interfere with each other. An understanding of the population genetics of mutations of individual loci and of traits affected by many loci helps in addressing many fundamental and applied questions: for example, how do organisms adapt to changing environments, how did sex evolve, which DNA sequences are medically important, why do we age, which genetic processes can generate new species or drive endangered species to extinction, and how should policy on levels of potentially harmful mutagens introduced into the environment by humans be determined? PMID:20308090

Preferential access to genetic information from endogenous hominin ancient DNA and accurate quantitative SNP-typing via SPEX

PubMed Central

Brotherton, Paul; Sanchez, Juan J.; Cooper, Alan; Endicott, Phillip

2010-01-01

The analysis of targeted genetic loci from ancient, forensic and clinical samples is usually built upon polymerase chain reaction (PCR)-generated sequence data. However, many studies have shown that PCR amplification from poor-quality DNA templates can create sequence artefacts at significant levels. With hominin (human and other hominid) samples, the pervasive presence of highly PCR-amplifiable human DNA contaminants in the vast majority of samples can lead to the creation of recombinant hybrids and other non-authentic artefacts. The resulting PCR-generated sequences can then be difficult, if not impossible, to authenticate. In contrast, single primer extension (SPEX)-based approaches can genotype single nucleotide polymorphisms from ancient fragments of DNA as accurately as modern DNA. A single SPEX-type assay can amplify just one of the duplex DNA strands at target loci and generate a multi-fold depth-of-coverage, with non-authentic recombinant hybrids reduced to undetectable levels. Crucially, SPEX-type approaches can preferentially access genetic information from damaged and degraded endogenous ancient DNA templates over modern human DNA contaminants. The development of SPEX-type assays offers the potential for highly accurate, quantitative genotyping from ancient hominin samples. PMID:19864251

Indicators of Theory of Mind in Narrative Production: A Comparison between Individuals with Genetic Syndromes and Typically Developing Children

ERIC Educational Resources Information Center

Lorusso, M. L.; Galli, R.; Libera, L.; Gagliardi, C.; Borgatti, R.; Hollebrandse, B.

2007-01-01

It is a matter of debate whether the development of theory of mind (ToM) depends on linguistic development or is, rather, an expression of cognitive development. The study of genetic syndromes, which are characterized by intellectual impairment as well as by different linguistic profiles, may provide useful information with respect to this issue.…

Using information content and base frequencies to distinguish mutations from genetic polymorphisms in splice junction recognition sites.

PubMed

Rogan, P K; Schneider, T D

1995-01-01

Predicting the effects of nucleotide substitutions in human splice sites has been based on analysis of consensus sequences. We used a graphic representation of sequence conservation and base frequency, the sequence logo, to demonstrate that a change in a splice acceptor of hMSH2 (a gene associated with familial nonpolyposis colon cancer) probably does not reduce splicing efficiency. This confirms a population genetic study that suggested that this substitution is a genetic polymorphism. The information theory-based sequence logo is quantitative and more sensitive than the corresponding splice acceptor consensus sequence for detection of true mutations. Information analysis may potentially be used to distinguish polymorphisms from mutations in other types of transcriptional, translational, or protein-coding motifs.

Development and in-house validation of the event-specific qualitative and quantitative PCR detection methods for genetically modified cotton MON15985.

PubMed

Jiang, Lingxi; Yang, Litao; Rao, Jun; Guo, Jinchao; Wang, Shu; Liu, Jia; Lee, Seonghun; Zhang, Dabing

2010-02-01

To implement genetically modified organism (GMO) labeling regulations, an event-specific analysis method based on the junction sequence between exogenous integration and host genomic DNA has become the preferential approach for GMO identification and quantification. In this study, specific primers and TaqMan probes based on the revealed 5'-end junction sequence of GM cotton MON15985 were designed, and qualitative and quantitative polymerase chain reaction (PCR) assays were established employing the designed primers and probes. In the qualitative PCR assay, the limit of detection (LOD) was 0.5 g kg(-1) in 100 ng total cotton genomic DNA, corresponding to about 17 copies of haploid cotton genomic DNA, and the LOD and limit of quantification (LOQ) for quantitative PCR assay were 10 and 17 copies of haploid cotton genomic DNA, respectively. Furthermore, the developed quantitative PCR assays were validated in-house by five different researchers. Also, five practical samples with known GM contents were quantified using the developed PCR assay in in-house validation, and the bias between the true and quantification values ranged from 2.06% to 12.59%. This study shows that the developed qualitative and quantitative PCR methods are applicable for the identification and quantification of GM cotton MON15985 and its derivates.

Relaxation of herbivore-mediated selection drives the evolution of genetic covariances between plant competitive and defense traits.

PubMed

Uesugi, Akane; Connallon, Tim; Kessler, André; Monro, Keyne

2017-06-01

Insect herbivores are important mediators of selection on traits that impact plant defense against herbivory and competitive ability. Although recent experiments demonstrate a central role for herbivory in driving rapid evolution of defense and competition-mediating traits, whether and how herbivory shapes heritable variation in these traits remains poorly understood. Here, we evaluate the structure and evolutionary stability of the G matrix for plant metabolites that are involved in defense and allelopathy in the tall goldenrod, Solidago altissima. We show that G has evolutionarily diverged between experimentally replicated populations that evolved in the presence versus the absence of ambient herbivory, providing direct evidence for the evolution of G by natural selection. Specifically, evolution in an herbivore-free habitat altered the orientation of G, revealing a negative genetic covariation between defense- and competition-related metabolites that is typically masked in herbivore-exposed populations. Our results may be explained by predictions of classical quantitative genetic theory, as well as the theory of acquisition-allocation trade-offs. The study provides compelling evidence that herbivory drives the evolution of plant genetic architecture. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Real-Time PCR-Based Quantitation Method for the Genetically Modified Soybean Line GTS 40-3-2.

PubMed

Kitta, Kazumi; Takabatake, Reona; Mano, Junichi

2016-01-01

This chapter describes a real-time PCR-based method for quantitation of the relative amount of genetically modified (GM) soybean line GTS 40-3-2 [Roundup Ready(®) soybean (RRS)] contained in a batch. The method targets a taxon-specific soybean gene (lectin gene, Le1) and the specific DNA construct junction region between the Petunia hybrida chloroplast transit peptide sequence and the Agrobacterium 5-enolpyruvylshikimate-3-phosphate synthase gene (epsps) sequence present in GTS 40-3-2. The method employs plasmid pMulSL2 as a reference material in order to quantify the relative amount of GTS 40-3-2 in soybean samples using a conversion factor (Cf) equal to the ratio of the RRS-specific DNA to the taxon-specific DNA in representative genuine GTS 40-3-2 seeds.

Genetic association of ubiquilin with Alzheimer's disease and related quantitative measures.

PubMed

Kamboh, M I; Minster, R L; Feingold, E; DeKosky, S T

2006-03-01

The gene coding for ubiquilin 1 (UBQLN1) is located near a linkage peak on chromosome 9q22.2 and it also impacts the function of presenilin proteins involved in early-onset Alzheimer's disease (AD). Recently, genetic variation in UBQLN1 has been shown to affect the risk of AD in two independent family-based samples. The purpose of this study was to confirm the reported association in a large case-control sample and to also examine the association of UBQLN1 SNPs with quantitative measures of AD progression, namely age-at-onset (AAO), disease duration and Mini-Mental State Examination (MMSE) score. We examined the associations of three SNPs in the UBQLN1 gene (intron 6/A>C, intron 8/T>C and intron 9/A>G) in up to 978 LOAD cases and 808 controls. All SNPs were in significant linkage disequilibrium (P<0.0001). While modest significant associations were observed in the single-site regression analysis, 3-site haplotype analysis revealed significant associations (P<0.0001 for overall haplotype analysis). One common haplotype (H4) defined by intron 6/A-intron 8/C-intron 9/G alleles was associated with AD risk and one less common haplotype (H5) defined by intron 6/C-intron 8/C-intron 9/A alleles was associated with protection. The adjusted odds ratios with potentially one and two copies of risk haplotype H4 were 1.5 (95% CI: 0.99-2.26; P=0.054) and 3.66 (95% CI: 1.43-9.39; P=0.007), respectively, and odds ratio for haplotype H5 carriers was 0.31 (95% CI: 0.10-0.95; P=0.0398). In addition to disease risk, the homozygosity of the risk haplotype was also associated with older AAO, longer disease duration and lower MMSE score. In summary, our data from a large case-control cohort indicate that genetic variation in the UBQLN1 gene has a modest effect on risk, AAO and disease duration of AD. Our haplotype data suggest the presence of additional putative functional variants either in the UBQLN1 gene or nearby genes and provide strong justification for additional work in this

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.

Event specific qualitative and quantitative polymerase chain reaction detection of genetically modified MON863 maize based on the 5'-transgene integration sequence.

PubMed

Yang, Litao; Xu, Songci; Pan, Aihu; Yin, Changsong; Zhang, Kewei; Wang, Zhenying; Zhou, Zhigang; Zhang, Dabing

2005-11-30

Because of the genetically modified organisms (GMOs) labeling policies issued in many countries and areas, polymerase chain reaction (PCR) methods were developed for the execution of GMO labeling policies, such as screening, gene specific, construct specific, and event specific PCR detection methods, which have become a mainstay of GMOs detection. The event specific PCR detection method is the primary trend in GMOs detection because of its high specificity based on the flanking sequence of the exogenous integrant. This genetically modified maize, MON863, contains a Cry3Bb1 coding sequence that produces a protein with enhanced insecticidal activity against the coleopteran pest, corn rootworm. In this study, the 5'-integration junction sequence between the host plant DNA and the integrated gene construct of the genetically modified maize MON863 was revealed by means of thermal asymmetric interlaced-PCR, and the specific PCR primers and TaqMan probe were designed based upon the revealed 5'-integration junction sequence; the conventional qualitative PCR and quantitative TaqMan real-time PCR detection methods employing these primers and probes were successfully developed. In conventional qualitative PCR assay, the limit of detection (LOD) was 0.1% for MON863 in 100 ng of maize genomic DNA for one reaction. In the quantitative TaqMan real-time PCR assay, the LOD and the limit of quantification were eight and 80 haploid genome copies, respectively. In addition, three mixed maize samples with known MON863 contents were detected using the established real-time PCR systems, and the ideal results indicated that the established event specific real-time PCR detection systems were reliable, sensitive, and accurate.

Island Rule, quantitative genetics and brain–body size evolution in Homo floresiensis

PubMed Central

2017-01-01

Colonization of islands often activate a complex chain of adaptive events that, over a relatively short evolutionary time, may drive strong shifts in body size, a pattern known as the Island Rule. It is arguably difficult to perform a direct analysis of the natural selection forces behind such a change in body size. Here, we used quantitative evolutionary genetic models, coupled with simulations and pattern-oriented modelling, to analyse the evolution of brain and body size in Homo floresiensis, a diminutive hominin species that appeared around 700 kya and survived up to relatively recent times (60–90 kya) on Flores Island, Indonesia. The hypothesis of neutral evolution was rejected in 97% of the simulations, and estimated selection gradients are within the range found in living natural populations. We showed that insularity may have triggered slightly different evolutionary trajectories for body and brain size, which means explaining the exceedingly small cranial volume of H. floresiensis requires additional selective forces acting on brain size alone. Our analyses also support previous conclusions that H. floresiensis may be most likely derived from an early Indonesian H. erectus, which is coherent with currently accepted biogeographical scenario for Homo expansion out of Africa. PMID:28637851

Island Rule, quantitative genetics and brain-body size evolution in Homo floresiensis.

PubMed

Diniz-Filho, José Alexandre Felizola; Raia, Pasquale

2017-06-28

Colonization of islands often activate a complex chain of adaptive events that, over a relatively short evolutionary time, may drive strong shifts in body size, a pattern known as the Island Rule. It is arguably difficult to perform a direct analysis of the natural selection forces behind such a change in body size. Here, we used quantitative evolutionary genetic models, coupled with simulations and pattern-oriented modelling, to analyse the evolution of brain and body size in Homo floresiensis , a diminutive hominin species that appeared around 700 kya and survived up to relatively recent times (60-90 kya) on Flores Island, Indonesia. The hypothesis of neutral evolution was rejected in 97% of the simulations, and estimated selection gradients are within the range found in living natural populations. We showed that insularity may have triggered slightly different evolutionary trajectories for body and brain size, which means explaining the exceedingly small cranial volume of H. floresiensis requires additional selective forces acting on brain size alone. Our analyses also support previous conclusions that H. floresiensis may be most likely derived from an early Indonesian H. erectus , which is coherent with currently accepted biogeographical scenario for Homo expansion out of Africa. © 2017 The Author(s).

Quantitative trait loci associated with anthracnose resistance in sorghum

USDA-ARS?s Scientific Manuscript database

With an aim to develop a durable resistance to the fungal disease anthracnose, two unique genetic sources of resistance were selected to create genetic mapping populations to identify regions of the sorghum genome that encode anthracnose resistance. A series of quantitative trait loci were identifi...

The genetic architecture of local adaptation and reproductive isolation in sympatry within the Mimulus guttatus species complex.

PubMed

Ferris, Kathleen G; Barnett, Laryssa L; Blackman, Benjamin K; Willis, John H

2017-01-01

The genetic architecture of local adaptation has been of central interest to evolutionary biologists since the modern synthesis. In addition to classic theory on the effect size of adaptive mutations by Fisher, Kimura and Orr, recent theory addresses the genetic architecture of local adaptation in the face of ongoing gene flow. This theory predicts that with substantial gene flow between populations local adaptation should proceed primarily through mutations of large effect or tightly linked clusters of smaller effect loci. In this study, we investigate the genetic architecture of divergence in flowering time, mating system-related traits, and leaf shape between Mimulus laciniatus and a sympatric population of its close relative M. guttatus. These three traits are probably involved in M. laciniatus' adaptation to a dry, exposed granite outcrop environment. Flowering time and mating system differences are also reproductive isolating barriers making them 'magic traits'. Phenotypic hybrids in this population provide evidence of recent gene flow. Using next-generation sequencing, we generate dense SNP markers across the genome and map quantitative trait loci (QTLs) involved in flowering time, flower size and leaf shape. We find that interspecific divergence in all three traits is due to few QTL of large effect including a highly pleiotropic QTL on chromosome 8. This QTL region contains the pleiotropic candidate gene TCP4 and is involved in ecologically important phenotypes in other Mimulus species. Our results are consistent with theory, indicating that local adaptation and reproductive isolation with gene flow should be due to few loci with large and pleiotropic effects. © 2016 John Wiley & Sons Ltd.

Biology Undergraduates' Misconceptions about Genetic Drift

ERIC Educational Resources Information Center

Andrews, T. M.; Price, R. M.; Mead, L. S.; McElhinny, T. L.; Thanukos, A.; Perez, K. E.; Herreid, C. F.; Terry, D. R.; Lemons, P. P.

2012-01-01

This study explores biology undergraduates' misconceptions about genetic drift. We use qualitative and quantitative methods to describe students' definitions, identify common misconceptions, and examine differences before and after instruction on genetic drift. We identify and describe five overarching categories that include 16 distinct…

Estimation of genetic parameters and detection of quantitative trait loci for metabolites in Danish Holstein milk.

PubMed

Buitenhuis, A J; Sundekilde, U K; Poulsen, N A; Bertram, H C; Larsen, L B; Sørensen, P

2013-05-01

Small components and metabolites in milk are significant for the utilization of milk, not only in dairy food production but also as disease predictors in dairy cattle. This study focused on estimation of genetic parameters and detection of quantitative trait loci for metabolites in bovine milk. For this purpose, milk samples were collected in mid lactation from 371 Danish Holstein cows in first to third parity. A total of 31 metabolites were detected and identified in bovine milk by using (1)H nuclear magnetic resonance (NMR) spectroscopy. Cows were genotyped using a bovine high-density single nucleotide polymorphism (SNP) chip. Based on the SNP data, a genomic relationship matrix was calculated and used as a random factor in a model together with 2 fixed factors (herd and lactation stage) to estimate the heritability and breeding value for individual metabolites in the milk. Heritability was in the range of 0 for lactic acid to >0.8 for orotic acid and β-hydroxybutyrate. A single SNP association analysis revealed 7 genome-wide significant quantitative trait loci [malonate: Bos taurus autosome (BTA)2 and BTA7; galactose-1-phosphate: BTA2; cis-aconitate: BTA11; urea: BTA12; carnitine: BTA25; and glycerophosphocholine: BTA25]. These results demonstrate that selection for metabolites in bovine milk may be possible. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Combining Quantitative Genetic Footprinting and Trait Enrichment Analysis to Identify Fitness Determinants of a Bacterial Pathogen

PubMed Central

Wiles, Travis J.; Norton, J. Paul; Russell, Colin W.; Dalley, Brian K.; Fischer, Kael F.; Mulvey, Matthew A.

2013-01-01

Strains of Extraintestinal Pathogenic Escherichia c oli (ExPEC) exhibit an array of virulence strategies and are a major cause of urinary tract infections, sepsis and meningitis. Efforts to understand ExPEC pathogenesis are challenged by the high degree of genetic and phenotypic variation that exists among isolates. Determining which virulence traits are widespread and which are strain-specific will greatly benefit the design of more effective therapies. Towards this goal, we utilized a quantitative genetic footprinting technique known as transposon insertion sequencing (Tn-seq) in conjunction with comparative pathogenomics to functionally dissect the genetic repertoire of a reference ExPEC isolate. Using Tn-seq and high-throughput zebrafish infection models, we tracked changes in the abundance of ExPEC variants within saturated transposon mutant libraries following selection within distinct host niches. Nine hundred and seventy bacterial genes (18% of the genome) were found to promote pathogen fitness in either a niche-dependent or independent manner. To identify genes with the highest therapeutic and diagnostic potential, a novel Trait Enrichment Analysis (TEA) algorithm was developed to ascertain the phylogenetic distribution of candidate genes. TEA revealed that a significant portion of the 970 genes identified by Tn-seq have homologues more often contained within the genomes of ExPEC and other known pathogens, which, as suggested by the first axiom of molecular Koch's postulates, is considered to be a key feature of true virulence determinants. Three of these Tn-seq-derived pathogen-associated genes—a transcriptional repressor, a putative metalloendopeptidase toxin and a hypothetical DNA binding protein—were deleted and shown to independently affect ExPEC fitness in zebrafish and mouse models of infection. Together, the approaches and observations reported herein provide a resource for future pathogenomics-based research and highlight the diversity of

Levels of reconstruction as complementarity in mixed methods research: a social theory-based conceptual framework for integrating qualitative and quantitative research.

PubMed

Carroll, Linda J; Rothe, J Peter

2010-09-01

Like other areas of health research, there has been increasing use of qualitative methods to study public health problems such as injuries and injury prevention. Likewise, the integration of qualitative and quantitative research (mixed-methods) is beginning to assume a more prominent role in public health studies. Likewise, using mixed-methods has great potential for gaining a broad and comprehensive understanding of injuries and their prevention. However, qualitative and quantitative research methods are based on two inherently different paradigms, and their integration requires a conceptual framework that permits the unity of these two methods. We present a theory-driven framework for viewing qualitative and quantitative research, which enables us to integrate them in a conceptually sound and useful manner. This framework has its foundation within the philosophical concept of complementarity, as espoused in the physical and social sciences, and draws on Bergson's metaphysical work on the 'ways of knowing'. Through understanding how data are constructed and reconstructed, and the different levels of meaning that can be ascribed to qualitative and quantitative findings, we can use a mixed-methods approach to gain a conceptually sound, holistic knowledge about injury phenomena that will enhance our development of relevant and successful interventions.

Missing heritability in the tails of quantitative traits? A simulation study on the impact of slightly altered true genetic models.

PubMed

Pütter, Carolin; Pechlivanis, Sonali; Nöthen, Markus M; Jöckel, Karl-Heinz; Wichmann, Heinz-Erich; Scherag, André

2011-01-01

Genome-wide association studies have identified robust associations between single nucleotide polymorphisms and complex traits. As the proportion of phenotypic variance explained is still limited for most of the traits, larger and larger meta-analyses are being conducted to detect additional associations. Here we investigate the impact of the study design and the underlying assumption about the true genetic effect in a bimodal mixture situation on the power to detect associations. We performed simulations of quantitative phenotypes analysed by standard linear regression and dichotomized case-control data sets from the extremes of the quantitative trait analysed by standard logistic regression. Using linear regression, markers with an effect in the extremes of the traits were almost undetectable, whereas analysing extremes by case-control design had superior power even for much smaller sample sizes. Two real data examples are provided to support our theoretical findings and to explore our mixture and parameter assumption. Our findings support the idea to re-analyse the available meta-analysis data sets to detect new loci in the extremes. Moreover, our investigation offers an explanation for discrepant findings when analysing quantitative traits in the general population and in the extremes. Copyright © 2011 S. Karger AG, Basel.

Genetic basis of climatic adaptation in scots pine by bayesian quantitative trait locus analysis.

PubMed Central

Hurme, P; Sillanpää, M J; Arjas, E; Repo, T; Savolainen, O

2000-01-01

We examined the genetic basis of large adaptive differences in timing of bud set and frost hardiness between natural populations of Scots pine. As a mapping population, we considered an "open-pollinated backcross" progeny by collecting seeds of a single F(1) tree (cross between trees from southern and northern Finland) growing in southern Finland. Due to the special features of the design (no marker information available on grandparents or the father), we applied a Bayesian quantitative trait locus (QTL) mapping method developed previously for outcrossed offspring. We found four potential QTL for timing of bud set and seven for frost hardiness. Bayesian analyses detected more QTL than ANOVA for frost hardiness, but the opposite was true for bud set. These QTL included alleles with rather large effects, and additionally smaller QTL were supported. The largest QTL for bud set date accounted for about a fourth of the mean difference between populations. Thus, natural selection during adaptation has resulted in selection of at least some alleles of rather large effect. PMID:11063704

Beyond Punnett squares: Student word association and explanations of phenotypic variation through an integrative quantitative genetics unit investigating anthocyanin inheritance and expression in Brassica rapa Fast plants.

PubMed

Batzli, Janet M; Smith, Amber R; Williams, Paul H; McGee, Seth A; Dósa, Katalin; Pfammatter, Jesse

2014-01-01

Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question "What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev)," we developed a 4-wk unit for an inquiry-based laboratory course focused on the inheritance and expression of a quantitative trait in varying environments. We utilized Brassica rapa Fast Plants as a model organism to study variation in the phenotype anthocyanin pigment intensity. As an initial curriculum assessment, we used free word association to examine students' cognitive structures before and after the unit and explanations in students' final research posters with particular focus on variation (Pv = Gv + Ev). Comparison of pre- and postunit word frequency revealed a shift in words and a pattern of co-occurring concepts indicative of change in cognitive structure, with particular focus on "variation" as a proposed threshold concept and primary goal for students' explanations. Given review of 53 posters, we found ∼50% of students capable of intermediate to high-level explanations combining both Gv and Ev influence on expression of anthocyanin intensity (Pv). While far from "plug and play," this conceptually rich, inquiry-based unit holds promise for effective integration of quantitative and Mendelian genetics. © 2014 J. M. Batzli et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

The IQ Quantitative Trait Loci Project: A Critique.

ERIC Educational Resources Information Center

King, David

1998-01-01

Describes the IQ Quantitative Trait Loci (QTL) project, an attempt to identify genes underlying IQ score variations using maps from the Human Genome Project. The essay argues against funding the IQ QTL project because it will end the debates about the genetic basis of intelligence and may lead directly to eugenic programs of genetic testing. (SLD)

Microsatellite data analysis for population genetics

USDA-ARS?s Scientific Manuscript database

Theories and analytical tools of population genetics have been widely applied for addressing various questions in the fields of ecological genetics, conservation biology, and any context where the role of dispersal or gene flow is important. Underlying much of population genetics is the analysis of ...

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

International collaborative study of the endogenous reference gene, sucrose phosphate synthase (SPS), used for qualitative and quantitative analysis of genetically modified rice.

PubMed

Jiang, Lingxi; Yang, Litao; Zhang, Haibo; Guo, Jinchao; Mazzara, Marco; Van den Eede, Guy; Zhang, Dabing

2009-05-13

One rice ( Oryza sativa ) gene, sucrose phosphate synthase (SPS), has been proven to be a suitable endogenous reference gene for genetically modified (GM) rice detection in a previous study. Herein are the reported results of an international collaborative ring trial for validation of the SPS gene as an endogenous reference gene and its optimized qualitative and quantitative polymerase chain reaction (PCR) systems. A total of 12 genetically modified organism (GMO) detection laboratories from seven countries participated in the ring trial and returned their results. The validated results confirmed the species specificity of the method through testing 10 plant genomic DNAs, low heterogeneity, and a stable single-copy number of the rice SPS gene among 7 indica varieties and 5 japonica varieties. The SPS qualitative PCR assay was validated with a limit of detection (LOD) of 0.1%, which corresponded to about 230 copies of haploid rice genomic DNA, while the limit of quantification (LOQ) for the quantitative PCR system was about 23 copies of haploid rice genomic DNA, with acceptable PCR efficiency and linearity. Furthermore, the bias between the test and true values of eight blind samples ranged from 5.22 to 26.53%. Thus, we believe that the SPS gene is suitable for use as an endogenous reference gene for the identification and quantification of GM rice and its derivates.

An event-specific method for the detection and quantification of ML01, a genetically modified Saccharomyces cerevisiae wine strain, using quantitative PCR.

PubMed

Vaudano, Enrico; Costantini, Antonella; Garcia-Moruno, Emilia

2016-10-03

The availability of genetically modified (GM) yeasts for winemaking and, in particular, transgenic strains based on the integration of genetic constructs deriving from other organisms into the genome of Saccharomyces cerevisiae, has been a reality for several years. Despite this, their use is only authorized in a few countries and limited to two strains: ML01, able to convert malic acid into lactic acid during alcoholic fermentation, and ECMo01 suitable for reducing the risk of carbamate production. In this work we propose a quali-quantitative culture-independent method for the detection of GM yeast ML01 in commercial preparations of ADY (Active Dry Yeast) consisting of efficient extraction of DNA and qPCR (quantitative PCR) analysis based on event-specific assay targeting MLC (malolactic cassette), and a taxon-specific S. cerevisiae assay detecting the MRP2 gene. The ADY DNA extraction methodology has been shown to provide good purity DNA suitable for subsequent qPCR. The MLC and MRP2 qPCR assay showed characteristics of specificity, dynamic range, limit of quantification (LOQ) limit of detection (LOD), precision and trueness, which were fully compliant with international reference guidelines. The method has been shown to reliably detect 0.005% (mass/mass) of GM ML01 S. cerevisiae in commercial preparations of ADY. Copyright © 2016 Elsevier B.V. All rights reserved.

Precocious quantitative cognition in monkeys.

PubMed

Ferrigno, Stephen; Hughes, Kelly D; Cantlon, Jessica F

2016-02-01

Basic quantitative abilities are thought to have an innate basis in humans partly because the ability to discriminate quantities emerges early in child development. If humans and nonhuman primates share this developmentally primitive foundation of quantitative reasoning, then this ability should be present early in development across species and should emerge earlier in monkeys than in humans because monkeys mature faster than humans. We report that monkeys spontaneously make accurate quantity choices by 1 year of age in a task that human children begin to perform only at 2.5 to 3 years of age. Additionally, we report that the quantitative sensitivity of infant monkeys is equal to that of the adult animals in their group and that rates of learning do not differ between infant and adult animals. This novel evidence of precocious quantitative reasoning in infant monkeys suggests that human quantitative reasoning shares its early developing foundation with other primates. The data further suggest that early developing components of primate quantitative reasoning are constrained by maturational factors related to genetic development as opposed to learning experience alone.

Could refuge theory and rivers acting as barriers explain the genetic variability distribution in the Atlantic Forest?

PubMed

Cazé, Ana Luiza R; Mäder, Geraldo; Nunes, Teonildes S; Queiroz, Luciano P; de Oliveira, Guilherme; Diniz-Filho, José Alexandre F; Bonatto, Sandro L; Freitas, Loreta B

2016-08-01

The Atlantic Forest is one of the most species-rich ecoregions in the world. The historical origins of this richness and the evolutionary processes that produced diversification and promoted speciation in this ecosystem remain poorly understood. In this context, focusing on Passiflora contracta, an endemic species from the Atlantic Forest distributed exclusively at sea level along forest edges, this study aimed to characterize the patterns of genetic variability and explore two hypotheses that attempt to explain the possible causes of the genetic diversity in this region: the refuge and riverine barrier theories. We employed Bayesian methods combined with niche modeling to identify genetically homogeneous groups, to determine the diversification age, and identify long-term climate stability areas to species survival. The analyses were performed using molecular markers from nuclear and plastid genomes, with samples collected throughout the entire geographic distribution of the species, and comparisons with congeners species. The results indicated that populations were genetically structured and provided evidence of demographic stability. The molecular markers indicated the existence of a clear structure and the presence of five homogeneous groups. Interestingly, the separation of the groups coincides with the geographical locations of local rivers, corroborating the hypothesis of rivers acting as barriers to gene flow in this species. The highest levels of genetic diversity and the areas identified as having long-term climate stability were found in the same region reported for other species as a possible refuge area during the climatic changes of the Quaternary. Copyright © 2016 Elsevier Inc. All rights reserved.

Behavioral and molecular studies of quantitative differences in hygienic behavior in honeybees.

PubMed

Gempe, Tanja; Stach, Silke; Bienefeld, Kaspar; Otte, Marianne; Beye, Martin

2016-10-21

Hygienic behavior (HB) enables honeybees to tolerate parasites, including infection with the parasitic mite Varroa destructor, and it is a well-known example of a quantitative genetic trait. The understanding of the molecular processes underpinning the quantitative differences in this behavior remains limited. We performed gene expression studies in worker bees that displayed quantitative genetic differences in HB. We established a high and low genetic source of HB performance and studied the engagements into HB of single worker bees under the same environmental conditions. We found that the percentage of worker bees that engaged in a hygienic behavioral task tripled in the high versus low HB sources, thus suggesting that genetic differences may mediate differences in stimulated states to perform HB. We found 501 differently expressed genes (DEGs) in the brains of hygienic and non-hygienic performing workers in the high HB source bees, and 342 DEGs in the brains of hygienic performing worker bees, relative to the gene expression in non-hygienic worker bees from the low HB source group. "Cell surface receptor ligand signal transduction" in the high and "negative regulation of cell communication" in the low HB source were overrepresented molecular processes, suggesting that these molecular processes in the brain may play a role in the regulation of quantitative differences in HB. Moreover, only 21 HB-associated DEGs were common between the high and low HB sources. The better HB colony performance is primarily achieved by a high number of bees engaging in the hygienic tasks that associate with distinct molecular processes in the brain. We propose that different gene products and pathways may mediate the quantitative genetic differences of HB.

On the RNG theory of turbulence

NASA Technical Reports Server (NTRS)

Lam, S. H.

1992-01-01

The Yakhot and Orszag (1986) renormalization group (RNG) theory of turbulence has generated a number of scaling law constants in reasonable quantitative agreement with experiments. The theory itself is highly mathematical, and its assumptions and approximations are not easily appreciated. The present paper reviews the RNG theory and recasts it in more conventional terms using a distinctly different viewpoint. A new formulation based on an alternative interpretation of the origin of the random force is presented, showing that the artificially introduced epsilon in the original theory is an adjustable parameter, thus offering a plausible explanation for the remarkable record of quantitative success of the so-called epsilon-expansion procedure.

[Prospect and application of microsatellite population genetics in study of geoherbs].

PubMed

Zhang, Wen-Jing; Zhang, Yong-Qing; Yuan, Qing-Jun; Huang, Lu-Qi; Jiang, Dan; Jing, Li

2013-12-01

The author introduces the basic concepts of microsatellite and population genetics and its characteristics, expounds the application of these theories for population genetic structure and genetic diversity, gene flow and evolutionary significant unit ESU division research. This paper discuss its applicationin study of genetic causes, origin of cultivation, different regional origins of geoherbs, aiming at providing a new theory and method for geoherbs.

Modelling the co-evolution of indirect genetic effects and inherited variability.

PubMed

Marjanovic, Jovana; Mulder, Han A; Rönnegård, Lars; Bijma, Piter

2018-03-28

When individuals interact, their phenotypes may be affected not only by their own genes but also by genes in their social partners. This phenomenon is known as Indirect Genetic Effects (IGEs). In aquaculture species and some plants, however, competition not only affects trait levels of individuals, but also inflates variability of trait values among individuals. In the field of quantitative genetics, the variability of trait values has been studied as a quantitative trait in itself, and is often referred to as inherited variability. Such studies, however, consider only the genetic effect of the focal individual on trait variability and do not make a connection to competition. Although the observed phenotypic relationship between competition and variability suggests an underlying genetic relationship, the current quantitative genetic models of IGE and inherited variability do not allow for such a relationship. The lack of quantitative genetic models that connect IGEs to inherited variability limits our understanding of the potential of variability to respond to selection, both in nature and agriculture. Models of trait levels, for example, show that IGEs may considerably change heritable variation in trait values. Currently, we lack the tools to investigate whether this result extends to variability of trait values. Here we present a model that integrates IGEs and inherited variability. In this model, the target phenotype, say growth rate, is a function of the genetic and environmental effects of the focal individual and of the difference in trait value between the social partner and the focal individual, multiplied by a regression coefficient. The regression coefficient is a genetic trait, which is a measure of cooperation; a negative value indicates competition, a positive value cooperation, and an increasing value due to selection indicates the evolution of cooperation. In contrast to the existing quantitative genetic models, our model allows for co-evolution of

Lessons to be learned from a contentious challenge to mainstream radiobiological science (the linear no-threshold theory of genetic mutations)

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

Beyea, Jan, E-mail: jbeyea@cipi.com

There are both statistically valid and invalid reasons why scientists with differing default hypotheses can disagree in high-profile situations. Examples can be found in recent correspondence in this journal, which may offer lessons for resolving challenges to mainstream science, particularly when adherents of a minority view attempt to elevate the status of outlier studies and/or claim that self-interest explains the acceptance of the dominant theory. Edward J. Calabrese and I have been debating the historical origins of the linear no-threshold theory (LNT) of carcinogenesis and its use in the regulation of ionizing radiation. Professor Calabrese, a supporter of hormesis, hasmore » charged a committee of scientists with misconduct in their preparation of a 1956 report on the genetic effects of atomic radiation. Specifically he argues that the report mischaracterized the LNT research record and suppressed calculations of some committee members. After reviewing the available scientific literature, I found that the contemporaneous evidence overwhelmingly favored a (genetics) LNT and that no calculations were suppressed. Calabrese's claims about the scientific record do not hold up primarily because of lack of attention to statistical analysis. Ironically, outlier studies were more likely to favor supra-linearity, not sub-linearity. Finally, the claim of investigator bias, which underlies Calabrese's accusations about key studies, is based on misreading of text. Attention to ethics charges, early on, may help seed a counter narrative explaining the community's adoption of a default hypothesis and may help focus attention on valid evidence and any real weaknesses in the dominant paradigm. - Highlights: • Edward J Calabrese has made a contentious challenge to mainstream radiobiological science. • Such challenges should not be neglected, lest they enter the political arena without review. • Key genetic studies from the 1940s, challenged by Calabrese, were found

Genetic dissection of quantitative trait locus for ethanol sensitivity in long- and short-sleep mice.

PubMed

Bennett, B; Carosone-Link, P; Beeson, M; Gordon, L; Phares-Zook, N; Johnson, T E

2008-08-01

Interval-specific congenic strains (ISCS) allow fine mapping of a quantitative trait locus (QTL), narrowing its confidence interval by an order of magnitude or more. In earlier work, we mapped four QTL specifying differential ethanol sensitivity, assessed by loss of righting reflex because of ethanol (LORE), in the inbred long-sleep (ILS) and inbred short-sleep (ISS) strains, accounting for approximately 50% of the genetic variance for this trait. Subsequently, we generated reciprocal congenic strains in which each full QTL interval from ILS was bred onto the ISS background and vice versa. An earlier paper reported construction and results of the ISCS on the ISS background; here, we describe this process and report results on the ILS background. We developed multiple ISCS for each Lore QTL in which the QTL interval was broken into a number of smaller intervals. For each of the four QTL regions (chromosomes 1, 2, 11 and 15), we were successful in reducing the intervals significantly. Multiple, positive strains were overlapped to generate a single, reduced interval. Subsequently, this reduced region was overlaid on previous reductions from the ISS background congenics, resulting in substantial reductions in all QTL regions by approximately 75% from the initial mapping study. Genes with sequence or expression polymorphisms in the reduced intervals are potential candidates; evidence for these is presented. Genetic background effects can be important in detection of single QTL; combining this information with the generation of congenics on both backgrounds, as described here, is a powerful approach for fine mapping QTL.

Terminology, concepts, and models in genetic epidemiology.

PubMed

Teare, M Dawn; Koref, Mauro F Santibàñez

2011-01-01

Genetic epidemiology brings together approaches and techniques developed in mathematical genetics and statistics, medical genetics, quantitative genetics, and epidemiology. In the 1980s, the focus was on the mapping and identification of genes where defects had large effects at the individual level. More recently, statistical and experimental advances have made possible to identify and characterise genes associated with small effects at the individual level. In this chapter, we provide a brief outline of the models, concepts, and terminology used in genetic epidemiology.

Quantitative genetic analysis of cellular adhesion molecules: the Fels Longitudinal Study.

PubMed

Lee, Miryoung; Czerwinski, Stefan A; Choh, Audrey C; Demerath, Ellen W; Sun, Shumei S; Chumlea, Wm C; Towne, Bradford; Siervogel, Roger M

2006-03-01

Circulating concentrations of inflammatory markers predict cardiovascular disease (CVD) risk and are closely associated with obesity. However, little is known concerning genetic influences on serum levels of inflammatory markers. In this study, we estimated the heritability (h2) of soluble cellular adhesion molecule (sCAM) concentrations and examined the correlational architecture between different sCAMs. The study population included 234 men and 270 women aged 18-76 years, belonging to 121 families participating in the Fels Longitudinal Study. Serum levels of soluble intercellular adhesion molecule-1 (sICAM-1), vascular cell adhesion molecule-1 (sVCAM-1), E-selectin (sESEL-1) and P-selectin (sPSEL-1) were assayed using commercially available kits. A variance components-based maximum likelihood method was used to estimate the h2 of the different serum inflammatory markers while simultaneously adjusting for the effects of known CVD risk factors, such as age and smoking. Additionally, we used bivariate extensions of these methods to estimate genetic and random environmental correlations among sCAMs. Levels of sCAMs were significantly heritable: h2=0.24+/-0.10 for sICAM-1, h2=0.22+/-0.10 for sVCAM-1, h2=0.50+/-0.11 for sESEL-1, and h2=0.46+/-0.10 for sPSEL-1. In addition, a significant genetic correlation (rho(G)=0.63) was found between sICAM-1 and sVCAM-1 indicating some degree of shared genetic control. In the Fels Longitudinal Study, the levels of four sCAMs are significantly influenced by genetic effects, and sICAM-1 shares a common genetic background with sVCAM-1.

The Price Equation, Gradient Dynamics, and Continuous Trait Game Theory.

PubMed

Lehtonen, Jussi

2018-01-01

A recent article convincingly nominated the Price equation as the fundamental theorem of evolution and used it as a foundation to derive several other theorems. A major section of evolutionary theory that was not addressed is that of game theory and gradient dynamics of continuous traits with frequency-dependent fitness. Deriving fundamental results in these fields under the unifying framework of the Price equation illuminates similarities and differences between approaches and allows a simple, unified view of game-theoretical and dynamic concepts. Using Taylor polynomials and the Price equation, I derive a dynamic measure of evolutionary change, a condition for singular points, the convergence stability criterion, and an alternative interpretation of evolutionary stability. Furthermore, by applying the Price equation to a multivariable Taylor polynomial, the direct fitness approach to kin selection emerges. Finally, I compare these results to the mean gradient equation of quantitative genetics and the canonical equation of adaptive dynamics.

Performance Theories for Sentence Coding: Some Quantitative Models

ERIC Educational Resources Information Center

Aaronson, Doris; And Others

1977-01-01

This study deals with the patterns of word-by-word reading times over a sentence when the subject must code the linguistic information sufficiently for immediate verbatim recall. A class of quantitative models is considered that would account for reading times at phrase breaks. (Author/RM)

Biometric Modeling of Gene-Environment Interplay: The Intersection of Theory and Method and Applications for Social Inequality

PubMed Central

South, Susan C.; Hamdi, Nayla; Krueger, Robert F.

2015-01-01

For more than a decade, biometric moderation models have been used to examine whether genetic and environmental influences on individual differences might vary within the population. These quantitative gene × environment interaction (G×E) models not only have the potential to elucidate when genetic and environmental influences on a phenotype might differ, but why, as they provide an empirical test of several theoretical paradigms that serve as useful heuristics to explain etiology—diathesis-stress, bioecological, differential susceptibility, and social control. In the current manuscript, we review how these developmental theories align with different patterns of findings from statistical models of gene-environment interplay. We then describe the extant empirical evidence, using work by our own research group and others, to lay out genetically-informative plausible accounts of how phenotypes related to social inequality—physical health and cognition—might relate to these theoretical models. PMID:26426103

Biometric Modeling of Gene-Environment Interplay: The Intersection of Theory and Method and Applications for Social Inequality.

PubMed

South, Susan C; Hamdi, Nayla R; Krueger, Robert F

2017-02-01

For more than a decade, biometric moderation models have been used to examine whether genetic and environmental influences on individual differences might vary within the population. These quantitative Gene × Environment interaction models have the potential to elucidate not only when genetic and environmental influences on a phenotype might differ, but also why, as they provide an empirical test of several theoretical paradigms that serve as useful heuristics to explain etiology-diathesis-stress, bioecological, differential susceptibility, and social control. In the current article, we review how these developmental theories align with different patterns of findings from statistical models of gene-environment interplay. We then describe the extant empirical evidence, using work by our own research group and others, to lay out genetically informative plausible accounts of how phenotypes related to social inequality-physical health and cognition-might relate to these theoretical models. © 2015 Wiley Periodicals, Inc.

Accounting for Sampling Error in Genetic Eigenvalues Using Random Matrix Theory.

PubMed

Sztepanacz, Jacqueline L; Blows, Mark W

2017-07-01

The distribution of genetic variance in multivariate phenotypes is characterized by the empirical spectral distribution of the eigenvalues of the genetic covariance matrix. Empirical estimates of genetic eigenvalues from random effects linear models are known to be overdispersed by sampling error, where large eigenvalues are biased upward, and small eigenvalues are biased downward. The overdispersion of the leading eigenvalues of sample covariance matrices have been demonstrated to conform to the Tracy-Widom (TW) distribution. Here we show that genetic eigenvalues estimated using restricted maximum likelihood (REML) in a multivariate random effects model with an unconstrained genetic covariance structure will also conform to the TW distribution after empirical scaling and centering. However, where estimation procedures using either REML or MCMC impose boundary constraints, the resulting genetic eigenvalues tend not be TW distributed. We show how using confidence intervals from sampling distributions of genetic eigenvalues without reference to the TW distribution is insufficient protection against mistaking sampling error as genetic variance, particularly when eigenvalues are small. By scaling such sampling distributions to the appropriate TW distribution, the critical value of the TW statistic can be used to determine if the magnitude of a genetic eigenvalue exceeds the sampling error for each eigenvalue in the spectral distribution of a given genetic covariance matrix. Copyright © 2017 by the Genetics Society of America.

Quantitative Genetic Analysis Reveals Potential to Genetically Improve Fruit Yield and Drought Resistance Simultaneously in Coriander

PubMed Central

Khodadadi, Mostafa; Dehghani, Hamid; Jalali Javaran, Mokhtar

2017-01-01

Enhancing water use efficiency of coriander (Coriandrum sativum L.) is a major focus for coriander breeding to cope with drought stress. The purpose of this study was; (a) to identify the predominant mechanism(s) of drought resistance in coriander and (b) to evaluate the genetic control mechanism(s) of traits associated with drought resistance and higher fruit yield. To reach this purpose, 15 half-diallel hybrids of coriander and their six parents were evaluated under well-watered and water deficit stressed (WDS) in both glasshouse lysimetric and field conditions. The parents were selected for their different response to water deficit stress following preliminary experiments. Results revealed that the genetic control mechanism of fruit yield is complex, variable and highly affected by environment. The mode of inheritance and nature of gene action for percent assimilate partitioned to fruits were similar to those for flowering time in both well-watered and WDS conditions. A significant negative genetic linkage was found between fruit yield and percent assimilate partitioned to root, percent assimilate partitioned to shoot, root number, root diameter, root dry mass, root volume, and early flowering. Thus, to improve fruit yield under water deficit stress, selection of low values of these traits could be used. In contrast, a significant positive genetic linkage between fruit yield and percent assimilate partitioned to fruits, leaf relative water content and chlorophyll content indicate selection for high values of these traits. These secondary or surrogate traits could be selected during early segregating generations. The early ripening parent (P1; TN-59-230) contained effective genes involved in preferred percent assimilate partitioning to fruit and drought stress resistance. In conclusion, genetic improvement of fruit yield and drought resistance could be simultaneously gained in coriander when breeding for drought resistance. PMID:28473836

Genetic variation in social mammals: the marmot model.

PubMed

Schwartz, O A; Armitage, K B

1980-02-08

The social substructure and the distribution of genetic variation among colonies of yellow-bellied marmots, when analyzed as an evolutionary system, suggests that this substructure enhances the intercolony variance and retards the fixation of genetic variation. This result supports a traditional theory of gradual evolution rather than recent theories suggesting accelerated evolution in social mammals.

Natural selection. VII. History and interpretation of kin selection theory.

PubMed

Frank, S A

2013-06-01

Kin selection theory is a kind of causal analysis. The initial form of kin selection ascribed cause to costs, benefits and genetic relatedness. The theory then slowly developed a deeper and more sophisticated approach to partitioning the causes of social evolution. Controversy followed because causal analysis inevitably attracts opposing views. It is always possible to separate total effects into different component causes. Alternative causal schemes emphasize different aspects of a problem, reflecting the distinct goals, interests and biases of different perspectives. For example, group selection is a particular causal scheme with certain advantages and significant limitations. Ultimately, to use kin selection theory to analyse natural patterns and to understand the history of debates over different approaches, one must follow the underlying history of causal analysis. This article describes the history of kin selection theory, with emphasis on how the causal perspective improved through the study of key patterns of natural history, such as dispersal and sex ratio, and through a unified approach to demographic and social processes. Independent historical developments in the multivariate analysis of quantitative traits merged with the causal analysis of social evolution by kin selection. © 2013 The Author. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

Expression quantitative trait loci and genetic regulatory network analysis reveals that Gabra2 is involved in stress responses in the mouse.

PubMed

Dai, Jiajuan; Wang, Xusheng; Chen, Ying; Wang, Xiaodong; Zhu, Jun; Lu, Lu

2009-11-01

Previous studies have revealed that the subunit alpha 2 (Gabra2) of the gamma-aminobutyric acid receptor plays a critical role in the stress response. However, little is known about the gentetic regulatory network for Gabra2 and the stress response. We combined gene expression microarray analysis and quantitative trait loci (QTL) mapping to characterize the genetic regulatory network for Gabra2 expression in the hippocampus of BXD recombinant inbred (RI) mice. Our analysis found that the expression level of Gabra2 exhibited much variation in the hippocampus across the BXD RI strains and between the parental strains, C57BL/6J, and DBA/2J. Expression QTL (eQTL) mapping showed three microarray probe sets of Gabra2 to have highly significant linkage likelihood ratio statistic (LRS) scores. Gene co-regulatory network analysis showed that 10 genes, including Gria3, Chka, Drd3, Homer1, Grik2, Odz4, Prkag2, Grm5, Gabrb1, and Nlgn1 are directly or indirectly associated with stress responses. Eleven genes were implicated as Gabra2 downstream genes through mapping joint modulation. The genetical genomics approach demonstrates the importance and the potential power of the eQTL studies in identifying genetic regulatory networks that contribute to complex traits, such as stress responses.

Genetic Map Construction and Quantitative Trait Locus (QTL) Detection of Growth-Related Traits in Litopenaeus vannamei for Selective Breeding Applications

PubMed Central

Andriantahina, Farafidy; Liu, Xiaolin; Huang, Hao

2013-01-01

Growth is a priority trait from the point of view of genetic improvement. Molecular markers linked to quantitative trait loci (QTL) have been regarded as useful for marker-assisted selection (MAS) in complex traits as growth. Using an intermediate F2 cross of slow and fast growth parents, a genetic linkage map of Pacific whiteleg shrimp, Litopenaeusvannamei , based on amplified fragment length polymorphisms (AFLP) and simple sequence repeats (SSR) markers was constructed. Meanwhile, QTL analysis was performed for growth-related traits. The linkage map consisted of 451 marker loci (429 AFLPs and 22 SSRs) which formed 49 linkage groups with an average marker space of 7.6 cM; they spanned a total length of 3627.6 cM, covering 79.50% of estimated genome size. 14 QTLs were identified for growth-related traits, including three QTLs for body weight (BW), total length (TL) and partial carapace length (PCL), two QTLs for body length (BL), one QTL for first abdominal segment depth (FASD), third abdominal segment depth (TASD) and first abdominal segment width (FASW), which explained 2.62 to 61.42% of phenotypic variation. Moreover, comparison of linkage maps between L . vannamei and Penaeus japonicus was applied, providing a new insight into the genetic base of QTL affecting the growth-related traits. The new results will be useful for conducting MAS breeding schemes in L . vannamei . PMID:24086466

General Contingency Theory of Organizations: An Alternative to Open Systems Theory.

DTIC Science & Technology

1982-08-01

genetic and mechanical open systems. We have recently proposed a general contingency theory (GCT) of management (Luthans and Stewart, 1977) which promises...developed in response to the need for an integrative theory of management that incorporates the environment (in the open systems sense. and begins to... management and desired performance out- comes. We will show that the GCT matrix can lead to organizational effec- tiveness. The Theory as a Basis for More

Endogenous Molecular-Cellular Network Cancer Theory: A Systems Biology Approach.

PubMed

Wang, Gaowei; Yuan, Ruoshi; Zhu, Xiaomei; Ao, Ping

2018-01-01

In light of ever apparent limitation of the current dominant cancer mutation theory, a quantitative hypothesis for cancer genesis and progression, endogenous molecular-cellular network hypothesis has been proposed from the systems biology perspective, now for more than 10 years. It was intended to include both the genetic and epigenetic causes to understand cancer. Its development enters the stage of meaningful interaction with experimental and clinical data and the limitation of the traditional cancer mutation theory becomes more evident. Under this endogenous network hypothesis, we established a core working network of hepatocellular carcinoma (HCC) according to the hypothesis and quantified the working network by a nonlinear dynamical system. We showed that the two stable states of the working network reproduce the main known features of normal liver and HCC at both the modular and molecular levels. Using endogenous network hypothesis and validated working network, we explored genetic mutation pattern in cancer and potential strategies to cure or relieve HCC from a totally new perspective. Patterns of genetic mutations have been traditionally analyzed by posteriori statistical association approaches in light of traditional cancer mutation theory. One may wonder the possibility of a priori determination of any mutation regularity. Here, we found that based on the endogenous network theory the features of genetic mutations in cancers may be predicted without any prior knowledge of mutation propensities. Normal hepatocyte and cancerous hepatocyte stable states, specified by distinct patterns of expressions or activities of proteins in the network, provide means to directly identify a set of most probable genetic mutations and their effects in HCC. As the key proteins and main interactions in the network are conserved through cell types in an organism, similar mutational features may also be found in other cancers. This analysis yielded straightforward and testable

Eye growth and myopia development: Unifying theory and Matlab model.

PubMed

Hung, George K; Mahadas, Kausalendra; Mohammad, Faisal

2016-03-01

The aim of this article is to present an updated unifying theory of the mechanisms underlying eye growth and myopia development. A series of model simulation programs were developed to illustrate the mechanism of eye growth regulation and myopia development. Two fundamental processes are presumed to govern the relationship between physiological optics and eye growth: genetically pre-programmed signaling and blur feedback. Cornea/lens is considered to have only a genetically pre-programmed component, whereas eye growth is considered to have both a genetically pre-programmed and a blur feedback component. Moreover, based on the Incremental Retinal-Defocus Theory (IRDT), the rate of change of blur size provides the direction for blur-driven regulation. The various factors affecting eye growth are shown in 5 simulations: (1 - unregulated eye growth): blur feedback is rendered ineffective, as in the case of form deprivation, so there is only genetically pre-programmed eye growth, generally resulting in myopia; (2 - regulated eye growth): blur feedback regulation demonstrates the emmetropization process, with abnormally excessive or reduced eye growth leading to myopia and hyperopia, respectively; (3 - repeated near-far viewing): simulation of large-to-small change in blur size as seen in the accommodative stimulus/response function, and via IRDT as well as nearwork-induced transient myopia (NITM), leading to the development of myopia; (4 - neurochemical bulk flow and diffusion): release of dopamine from the inner plexiform layer of the retina, and the subsequent diffusion and relay of neurochemical cascade show that a decrease in dopamine results in a reduction of proteoglycan synthesis rate, which leads to myopia; (5 - Simulink model): model of genetically pre-programmed signaling and blur feedback components that allows for different input functions to simulate experimental manipulations that result in hyperopia, emmetropia, and myopia. These model simulation programs

Genetics and epigenetics of aging and longevity

PubMed Central

Moskalev, Alexey A; Aliper, Alexander M; Smit-McBride, Zeljka; Buzdin, Anton; Zhavoronkov, Alex

2014-01-01

Evolutionary theories of aging predict the existence of certain genes that provide selective advantage early in life with adverse effect on lifespan later in life (antagonistic pleiotropy theory) or longevity insurance genes (disposable soma theory). Indeed, the study of human and animal genetics is gradually identifying new genes that increase lifespan when overexpressed or mutated: gerontogenes. Furthermore, genetic and epigenetic mechanisms are being identified that have a positive effect on longevity. The gerontogenes are classified as lifespan regulators, mediators, effectors, housekeeping genes, genes involved in mitochondrial function, and genes regulating cellular senescence and apoptosis. In this review we demonstrate that the majority of the genes as well as genetic and epigenetic mechanisms that are involved in regulation of longevity are highly interconnected and related to stress response. PMID:24603410

Facial averageness and genetic quality: Testing heritability, genetic correlation with attractiveness, and the paternal age effect.

PubMed

Lee, Anthony J; Mitchem, Dorian G; Wright, Margaret J; Martin, Nicholas G; Keller, Matthew C; Zietsch, Brendan P

2016-01-01

Popular theory suggests that facial averageness is preferred in a partner for genetic benefits to offspring. However, whether facial averageness is associated with genetic quality is yet to be established. Here, we computed an objective measure of facial averageness for a large sample ( N = 1,823) of identical and nonidentical twins and their siblings to test two predictions from the theory that facial averageness reflects genetic quality. First, we use biometrical modelling to estimate the heritability of facial averageness, which is necessary if it reflects genetic quality. We also test for a genetic association between facial averageness and facial attractiveness. Second, we assess whether paternal age at conception (a proxy of mutation load) is associated with facial averageness and facial attractiveness. Our findings are mixed with respect to our hypotheses. While we found that facial averageness does have a genetic component, and a significant phenotypic correlation exists between facial averageness and attractiveness, we did not find a genetic correlation between facial averageness and attractiveness (therefore, we cannot say that the genes that affect facial averageness also affect facial attractiveness) and paternal age at conception was not negatively associated with facial averageness. These findings support some of the previously untested assumptions of the 'genetic benefits' account of facial averageness, but cast doubt on others.

Genetic Architecture of Micro-Environmental Plasticity in Drosophila melanogaster.

PubMed

Morgante, Fabio; Sørensen, Peter; Sorensen, Daniel A; Maltecca, Christian; Mackay, Trudy F C

2015-05-06

Individuals of the same genotype do not have the same phenotype for quantitative traits when reared under common macro-environmental conditions, a phenomenon called micro-environmental plasticity. Genetic variation in micro-environmental plasticity is assumed in models of the evolution of phenotypic variance, and is important in applied breeding and personalized medicine. Here, we quantified genetic variation for micro-environmental plasticity for three quantitative traits in the inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel. We found substantial genetic variation for micro-environmental plasticity for all traits, with broad sense heritabilities of the same magnitude or greater than those of trait means. Micro-environmental plasticity is not correlated with residual segregating variation, is trait-specific, and has genetic correlations with trait means ranging from zero to near unity. We identified several candidate genes associated with micro-environmental plasticity of startle response, including Drosophila Hsp90, setting the stage for future genetic dissection of this phenomenon.

Genetic Architecture of Micro-Environmental Plasticity in Drosophila melanogaster

PubMed Central

Morgante, Fabio; Sørensen, Peter; Sorensen, Daniel A.; Maltecca, Christian; Mackay, Trudy F. C.

2015-01-01

Individuals of the same genotype do not have the same phenotype for quantitative traits when reared under common macro-environmental conditions, a phenomenon called micro-environmental plasticity. Genetic variation in micro-environmental plasticity is assumed in models of the evolution of phenotypic variance, and is important in applied breeding and personalized medicine. Here, we quantified genetic variation for micro-environmental plasticity for three quantitative traits in the inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel. We found substantial genetic variation for micro-environmental plasticity for all traits, with broad sense heritabilities of the same magnitude or greater than those of trait means. Micro-environmental plasticity is not correlated with residual segregating variation, is trait-specific, and has genetic correlations with trait means ranging from zero to near unity. We identified several candidate genes associated with micro-environmental plasticity of startle response, including Drosophila Hsp90, setting the stage for future genetic dissection of this phenomenon. PMID:25943032

Detection of nonauthorized genetically modified organisms using differential quantitative polymerase chain reaction: application to 35S in maize.

PubMed

Cankar, Katarina; Chauvensy-Ancel, Valérie; Fortabat, Marie-Noelle; Gruden, Kristina; Kobilinsky, André; Zel, Jana; Bertheau, Yves

2008-05-15

Detection of nonauthorized genetically modified organisms (GMOs) has always presented an analytical challenge because the complete sequence data needed to detect them are generally unavailable although sequence similarity to known GMOs can be expected. A new approach, differential quantitative polymerase chain reaction (PCR), for detection of nonauthorized GMOs is presented here. This method is based on the presence of several common elements (e.g., promoter, genes of interest) in different GMOs. A statistical model was developed to study the difference between the number of molecules of such a common sequence and the number of molecules identifying the approved GMO (as determined by border-fragment-based PCR) and the donor organism of the common sequence. When this difference differs statistically from zero, the presence of a nonauthorized GMO can be inferred. The interest and scope of such an approach were tested on a case study of different proportions of genetically modified maize events, with the P35S promoter as the Cauliflower Mosaic Virus common sequence. The presence of a nonauthorized GMO was successfully detected in the mixtures analyzed and in the presence of (donor organism of P35S promoter). This method could be easily transposed to other common GMO sequences and other species and is applicable to other detection areas such as microbiology.

Statistics for Learning Genetics

NASA Astrophysics Data System (ADS)

Charles, Abigail Sheena

This study investigated the knowledge and skills that biology students may need to help them understand statistics/mathematics as it applies to genetics. The data are based on analyses of current representative genetics texts, practicing genetics professors' perspectives, and more directly, students' perceptions of, and performance in, doing statistically-based genetics problems. This issue is at the emerging edge of modern college-level genetics instruction, and this study attempts to identify key theoretical components for creating a specialized biological statistics curriculum. The goal of this curriculum will be to prepare biology students with the skills for assimilating quantitatively-based genetic processes, increasingly at the forefront of modern genetics. To fulfill this, two college level classes at two universities were surveyed. One university was located in the northeastern US and the other in the West Indies. There was a sample size of 42 students and a supplementary interview was administered to a select 9 students. Interviews were also administered to professors in the field in order to gain insight into the teaching of statistics in genetics. Key findings indicated that students had very little to no background in statistics (55%). Although students did perform well on exams with 60% of the population receiving an A or B grade, 77% of them did not offer good explanations on a probability question associated with the normal distribution provided in the survey. The scope and presentation of the applicable statistics/mathematics in some of the most used textbooks in genetics teaching, as well as genetics syllabi used by instructors do not help the issue. It was found that the text books, often times, either did not give effective explanations for students, or completely left out certain topics. The omission of certain statistical/mathematical oriented topics was seen to be also true with the genetics syllabi reviewed for this study. Nonetheless

Differential association of family subsystem negativity on siblings' maladjustment: using behavior genetic methods to test process theory.

PubMed

Feinberg, Mark E; Reiss, David; Neiderhiser, Jenae M; Hetherington, E Mavis

2005-12-01

This study investigated the family context of adolescent sibling similarity and differentiation in maladjustment (antisocial behavior and depression) by examining negativity in different subsystems. Two hypotheses were proposed: (1) Parental and sibling negativity tends to diffuse through the family system, especially because of the high level of reciprocity in sibling relationships, leading to sibling similarity; and (2) interparental (coparenting) conflict disrupts cohesive functioning and thereby motivates and facilitates sibling differentiation and niche picking. To control for the effects of similar genes between siblings, the authors used behavioral genetic models with a genetically informed sample of 720 two-parent families, each with at least 2 adolescent siblings. Results for the differences in shared environmental influences across groups high and low in each of the domains of family negativity provided partial support for the hypotheses. The results further understanding of influences on individual differences and support a theory of how parent-child and interparental relationships intersect with sibling relationship dynamics. Copyright 2006 APA, all rights reserved).

Another Curriculum Requirement? Quantitative Reasoning in Economics: Some First Steps

ERIC Educational Resources Information Center

O'Neill, Patrick B.; Flynn, David T.

2013-01-01

In this paper, we describe first steps toward focusing on quantitative reasoning in an intermediate microeconomic theory course. We find student attitudes toward quantitative aspects of economics improve over the duration of the course (as we would hope). Perhaps more importantly, student attitude toward quantitative reasoning improves, in…

Quantitative results of stellar evolution and pulsation theories.

NASA Technical Reports Server (NTRS)

Fricke, K.; Stobie, R. S.; Strittmatter, P. A.

1971-01-01

The discrepancy between the masses of Cepheid variables deduced from evolution theory and pulsation theory is examined. The effect of input physics on evolutionary tracks is first discussed; in particular, changes in the opacity are considered. The sensitivity of pulsation masses to opacity changes and to the ascribed values of luminosity and effective temperature are then analyzed. The Cepheid mass discrepancy is discussed in the light of the results already obtained. Other astronomical evidence, including the mass-luminosity relation for main sequence stars, the solar neutrino flux, and cluster ages are also considered in an attempt to determine the most likely source of error in the event that substantial mass loss has not occurred.

The Future of Piaget's Theory in Education.

ERIC Educational Resources Information Center

Murray, Frank B.

This paper assesses the utility of Piagetian theory for educational practice. Educational practice cannot be formally deduced from psychological theory, but may be theory-compatible if the theory does not specifically forbid the practice. Piaget's genetic epistemology has provided a theoretical justification for longstanding educational…

Quantitative PCR for Genetic Markers of Human Fecal Pollution

EPA Science Inventory

Assessment of health risk and fecal bacteria loads associated with human fecal pollution requires reliable host-specific analytical methods and a rapid quantificationapproach. We report the development of quantitative PCR assays for quantification of two recently described human-...

Genetics and plant development.

PubMed

Prunet, Nathanaël; Meyerowitz, Elliot M

2016-01-01

There are only three grand theories in biology: the theory of the cell, the theory of the gene, and the theory of evolution. Two of these, the cell and gene theories, originated in the study of plants, with the third resulting in part from botanical considerations as well. Mendel's elucidation of the rules of inheritance was a result of his experiments on peas. The rediscovery of Mendel's work in 1900 was by the botanists de Vries, Correns, and Tschermak. It was only in subsequent years that animals were also shown to have segregation of genetic elements in the exact same manner as had been shown in plants. The story of developmental biology is different - while the development of plants has long been studied, the experimental and genetic approaches to developmental mechanism were developed via experiments on animals, and the importance of genes in development (e.g., Waddington, 1940) and their use for understanding developmental mechanisms came to botanical science much later - as late as the 1980s. Copyright © 2016 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Quantitative PCR for genetic markers of human fecal pollution

EPA Science Inventory

Assessment of health risk and fecal bacteria loads associated with human fecal pollution requires reliable host-specific analytical methods and a rapid quantification approach. We report the development of quantitative PCR assays for enumeration of two recently described hum...

SoyBase, The USDA-ARS Soybean Genetics and Genomics Database

USDA-ARS?s Scientific Manuscript database

SoyBase, the USDA-ARS soybean genetic database, is a comprehensive repository for professionally curated genetics, genomics and related data resources for soybean. SoyBase contains the most current genetic, physical and genomic sequence maps integrated with qualitative and quantitative traits. The...

[Study on once sampling quantitation based on information entropy of ISSR amplified bands of Houttuynia cordata].

PubMed

Wang, Haiqin; Liu, Wenlong; He, Fuyuan; Chen, Zuohong; Zhang, Xili; Xie, Xianggui; Zeng, Jiaoli; Duan, Xiaopeng

2012-02-01

To explore the once sampling quantitation of Houttuynia cordata through its DNA polymorphic bands that carried information entropy, from other form that the expression of traditional Chinese medicine polymorphism, genetic polymorphism, of traditional Chinese medicine. The technique of inter simple sequence repeat (ISSR) was applied to analyze genetic polymorphism of H. cordata samples from the same GAP producing area, the DNA genetic bands were transformed its into the information entropy, and the minimum once sampling quantitation with the mathematical mode was measured. One hundred and thirty-four DNA bands were obtained by using 9 screened ISSR primers to amplify from 46 strains DNA samples of H. cordata from the same GAP, the information entropy was H=0.365 6-0.978 6, and RSD was 14.75%. The once sampling quantitation was W=11.22 kg (863 strains). The "once minimum sampling quantitation" were calculated from the angle of the genetic polymorphism of H. cordata, and a great differences between this volume and the amount from the angle of fingerprint were found.

Quantitative trait loci and metabolic pathways

PubMed Central

McMullen, M. D.; Byrne, P. F.; Snook, M. E.; Wiseman, B. R.; Lee, E. A.; Widstrom, N. W.; Coe, E. H.

1998-01-01

The interpretation of quantitative trait locus (QTL) studies is limited by the lack of information on metabolic pathways leading to most economic traits. Inferences about the roles of the underlying genes with a pathway or the nature of their interaction with other loci are generally not possible. An exception is resistance to the corn earworm Helicoverpa zea (Boddie) in maize (Zea mays L.) because of maysin, a C-glycosyl flavone synthesized in silks via a branch of the well characterized flavonoid pathway. Our results using flavone synthesis as a model QTL system indicate: (i) the importance of regulatory loci as QTLs, (ii) the importance of interconnecting biochemical pathways on product levels, (iii) evidence for “channeling” of intermediates, allowing independent synthesis of related compounds, (iv) the utility of QTL analysis in clarifying the role of specific genes in a biochemical pathway, and (v) identification of a previously unknown locus on chromosome 9S affecting flavone level. A greater understanding of the genetic basis of maysin synthesis and associated corn earworm resistance should lead to improved breeding strategies. More broadly, the insights gained in relating a defined genetic and biochemical pathway affecting a quantitative trait should enhance interpretation of the biological basis of variation for other quantitative traits. PMID:9482823

Genetic and Environmental Influences on Behavior: Capturing All the Interplay

ERIC Educational Resources Information Center

Johnson, Wendy

2007-01-01

Basic quantitative genetic models of human behavioral variation have made clear that individual differences in behavior cannot be understood without acknowledging the importance of genetic influences. Yet these basic models estimate average, population-level genetic and environmental influences, obscuring differences that might exist within the…

Effects of normalization on quantitative traits in association test

PubMed Central

2009-01-01

Background Quantitative trait loci analysis assumes that the trait is normally distributed. In reality, this is often not observed and one strategy is to transform the trait. However, it is not clear how much normality is required and which transformation works best in association studies. Results We performed simulations on four types of common quantitative traits to evaluate the effects of normalization using the logarithm, Box-Cox, and rank-based transformations. The impact of sample size and genetic effects on normalization is also investigated. Our results show that rank-based transformation gives generally the best and consistent performance in identifying the causal polymorphism and ranking it highly in association tests, with a slight increase in false positive rate. Conclusion For small sample size or genetic effects, the improvement in sensitivity for rank transformation outweighs the slight increase in false positive rate. However, for large sample size and genetic effects, normalization may not be necessary since the increase in sensitivity is relatively modest. PMID:20003414

TOPICAL PROBLEMS: The phenomenological theory of world population growth

NASA Astrophysics Data System (ADS)

Kapitza, Sergei P.

1996-01-01

Of all global problems world population growth is the most significant. Demographic data describe this process in a concise and quantitative way in its past and present. Analysing this development it is possible by applying the concepts of systems analysis and synergetics, to work out a mathematical model for a phenomenological description of the global demographic process and to project its trends into the future. Assuming self-similarity as the dynamic principle of development, growth can be described practically over the whole of human history, assuming the growth rate to be proportional to the square of the number of people. The large parameter of the theory and the effective size of a coherent population group is of the order of 105 and the microscopic parameter of the phenomenology is the human lifespan. The demographic transition — a transition to a stabilised world population of some 14 billion in a foreseeable future — is a systemic singularity and is determined by the inherent pattern of growth of an open system, rather than by the lack of resources. The development of a quantitative nonlinear theory of the world population is of interest for interdisciplinary research in anthropology and demography, history and sociology, for population genetics and epidemiology, for studies in evolution of humankind and the origin of man. The model also provides insight into the stability of growth and the present predicament of humankind, and provides a setting for discussing the main global problems.

Quantitative measures of healthy aging and biological age

PubMed Central

Kim, Sangkyu; Jazwinski, S. Michal

2015-01-01

Numerous genetic and non-genetic factors contribute to aging. To facilitate the study of these factors, various descriptors of biological aging, including ‘successful aging’ and ‘frailty’, have been put forth as integrative functional measures of aging. A separate but related quantitative approach is the ‘frailty index’, which has been operationalized and frequently used. Various frailty indices have been constructed. Although based on different numbers and types of health variables, frailty indices possess several common properties that make them useful across different studies. We have been using a frailty index termed FI34 based on 34 health variables. Like other frailty indices, FI34 increases non-linearly with advancing age and is a better indicator of biological aging than chronological age. FI34 has a substantial genetic basis. Using FI34, we found elevated levels of resting metabolic rate linked to declining health in nonagenarians. Using FI34 as a quantitative phenotype, we have also found a genomic region on chromosome 12 that is associated with healthy aging and longevity. PMID:26005669

Intelligence: Genetic and Environmental Influences.

ERIC Educational Resources Information Center

Cancro, Robert, Ed.

This book on the genetic and environmental influences on intelligence is comprised of the following papers: "The Structure of Intelligence in Relation to the Nature-Nurture Controversy," R. B. Cattell; "Theory of Intelligence," L. G. Humphreys; "Using Measured Intelligence Intelligently," P. R. Merrifield; "Intelligence: Definition, Theory, and…

Utility of computer simulations in landscape genetics

Treesearch

Bryan K. Epperson; Brad H. McRae; Kim Scribner; Samuel A. Cushman; Michael S. Rosenberg; Marie-Josee Fortin; Patrick M. A. James; Melanie Murphy; Stephanie Manel; Pierre Legendre; Mark R. T. Dale

2010-01-01

Population genetics theory is primarily based on mathematical models in which spatial complexity and temporal variability are largely ignored. In contrast, the field of landscape genetics expressly focuses on how population genetic processes are affected by complex spatial and temporal environmental heterogeneity. It is spatially explicit and relates patterns to...

Evolution equation of population genetics: Relation to the density-matrix theory of quasiparticles with general dispersion laws

NASA Astrophysics Data System (ADS)

Bezák, V.

2003-02-01

The Waxman-Peck theory of population genetics is discussed in regard of soil bacteria. Each bacterium is understood as a carrier of a phenotypic parameter p. The central objective is the calculation of the probability density with respect to p, Φ(p,t;p0), of the carriers living at time t>0, provided that initially at t0=0, all bacteria carried the phenotypic parameter p0=0. The theory involves two small parameters: the mutation probability μ and a parameter γ involved in a function w(p) defining the fitness of the bacteria to survive the generation time τ and give birth to an offspring. The mutation from a state p to a state q is defined by a Gaussian with a dispersion σ2m. The author focuses our attention on a function φ(p,t) which determines uniquely the function Φ(p,t;p0) and satisfies a linear equation (Waxman’s equation). The Green function of this equation is mathematically identical with the one-particle Bloch density matrix, where μ characterizes the order of magnitude of the potential energy. (In the x representation, the potential energy is proportional to the inverted Gaussian with the dispersion σ2m). The author solves Waxman’s equation in the standard style of a perturbation theory and discusses how the solution depends on the choice of the fitness function w(p). In a sense, the function c(p)=1-w(p)/w(0) is analogous to the dispersion function E(p) of fictitious quasiparticles. In contrast to Waxman’s approximation, where c(p) was taken as a quadratic function, c(p)≈γp2, the author exemplifies the problem with another function, c(p)=γ[1-exp(-ap2)], where γ is small but a may be large. The author shows that the use of this function in the theory of the population genetics is the same as the use of a nonparabolic dispersion law E=E(p) in the density-matrix theory. With a general function c(p), the distribution function Φ(p,t;0) is composed of a δ-function component, N(t)δ(p), and a blurred component. When discussing the limiting

Quantitative analysis of bristle number in Drosophila mutants identifies genes involved in neural development

NASA Technical Reports Server (NTRS)

Norga, Koenraad K.; Gurganus, Marjorie C.; Dilda, Christy L.; Yamamoto, Akihiko; Lyman, Richard F.; Patel, Prajal H.; Rubin, Gerald M.; Hoskins, Roger A.; Mackay, Trudy F.; Bellen, Hugo J.

2003-01-01

BACKGROUND: The identification of the function of all genes that contribute to specific biological processes and complex traits is one of the major challenges in the postgenomic era. One approach is to employ forward genetic screens in genetically tractable model organisms. In Drosophila melanogaster, P element-mediated insertional mutagenesis is a versatile tool for the dissection of molecular pathways, and there is an ongoing effort to tag every gene with a P element insertion. However, the vast majority of P element insertion lines are viable and fertile as homozygotes and do not exhibit obvious phenotypic defects, perhaps because of the tendency for P elements to insert 5' of transcription units. Quantitative genetic analysis of subtle effects of P element mutations that have been induced in an isogenic background may be a highly efficient method for functional genome annotation. RESULTS: Here, we have tested the efficacy of this strategy by assessing the extent to which screening for quantitative effects of P elements on sensory bristle number can identify genes affecting neural development. We find that such quantitative screens uncover an unusually large number of genes that are known to function in neural development, as well as genes with yet uncharacterized effects on neural development, and novel loci. CONCLUSIONS: Our findings establish the use of quantitative trait analysis for functional genome annotation through forward genetics. Similar analyses of quantitative effects of P element insertions will facilitate our understanding of the genes affecting many other complex traits in Drosophila.

Extending DFT-based genetic algorithms by atom-to-place re-assignment via perturbation theory: A systematic and unbiased approach to structures of mixed-metallic clusters

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

Weigend, Florian, E-mail: florian.weigend@kit.edu

2014-10-07

Energy surfaces of metal clusters usually show a large variety of local minima. For homo-metallic species the energetically lowest can be found reliably with genetic algorithms, in combination with density functional theory without system-specific parameters. For mixed-metallic clusters this is much more difficult, as for a given arrangement of nuclei one has to find additionally the best of many possibilities of assigning different metal types to the individual positions. In the framework of electronic structure methods this second issue is treatable at comparably low cost at least for elements with similar atomic number by means of first-order perturbation theory, asmore » shown previously [F. Weigend, C. Schrodt, and R. Ahlrichs, J. Chem. Phys. 121, 10380 (2004)]. In the present contribution the extension of a genetic algorithm with the re-assignment of atom types to atom sites is proposed and tested for the search of the global minima of PtHf{sub 12} and [LaPb{sub 7}Bi{sub 7}]{sup 4−}. For both cases the (putative) global minimum is reliably found with the extended technique, which is not the case for the “pure” genetic algorithm.« less

An integrated genetic map based on four mapping populations and quantitative trait loci associated with economically important traits in watermelon (Citrullus lanatus)

PubMed Central

2014-01-01

Background Modern watermelon (Citrullus lanatus L.) cultivars share a narrow genetic base due to many years of selection for desirable horticultural qualities. Wild subspecies within C. lanatus are important potential sources of novel alleles for watermelon breeding, but successful trait introgression into elite cultivars has had limited success. The application of marker assisted selection (MAS) in watermelon is yet to be realized, mainly due to the past lack of high quality genetic maps. Recently, a number of useful maps have become available, however these maps have few common markers, and were constructed using different marker sets, thus, making integration and comparative analysis among maps difficult. The objective of this research was to use single-nucleotide polymorphism (SNP) anchor markers to construct an integrated genetic map for C. lanatus. Results Under the framework of the high density genetic map, an integrated genetic map was constructed by merging data from four independent mapping experiments using a genetically diverse array of parental lines, which included three subspecies of watermelon. The 698 simple sequence repeat (SSR), 219 insertion-deletion (InDel), 36 structure variation (SV) and 386 SNP markers from the four maps were used to construct an integrated map. This integrated map contained 1339 markers, spanning 798 cM with an average marker interval of 0.6 cM. Fifty-eight previously reported quantitative trait loci (QTL) for 12 traits in these populations were also integrated into the map. In addition, new QTL identified for brix, fructose, glucose and sucrose were added. Some QTL associated with economically important traits detected in different genetic backgrounds mapped to similar genomic regions of the integrated map, suggesting that such QTL are responsible for the phenotypic variability observed in a broad array of watermelon germplasm. Conclusions The integrated map described herein enhances the utility of genomic tools over

Rapid changes in genetic architecture of behavioural syndromes following colonization of a novel environment.

PubMed

Karlsson Green, K; Eroukhmanoff, F; Harris, S; Pettersson, L B; Svensson, E I

2016-01-01

Behavioural syndromes, that is correlated behaviours, may be a result from adaptive correlational selection, but in a new environmental setting, the trait correlation might act as an evolutionary constraint. However, knowledge about the quantitative genetic basis of behavioural syndromes, and the stability and evolvability of genetic correlations under different ecological conditions, is limited. We investigated the quantitative genetic basis of correlated behaviours in the freshwater isopod Asellus aquaticus. In some Swedish lakes, A. aquaticus has recently colonized a novel habitat and diverged into two ecotypes, presumably due to habitat-specific selection from predation. Using a common garden approach and animal model analyses, we estimated quantitative genetic parameters for behavioural traits and compared the genetic architecture between the ecotypes. We report that the genetic covariance structure of the behavioural traits has been altered in the novel ecotype, demonstrating divergence in behavioural correlations. Thus, our study confirms that genetic correlations behind behaviours can change rapidly in response to novel selective environments. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

Generalist Genes: Genetic Links between Brain, Mind, and Education

ERIC Educational Resources Information Center

Plomin, Robert; Kovas, Yulia; Haworth, Claire M. A.

2007-01-01

Genetics contributes importantly to learning abilities and disabilities--not just to reading, the target of most genetic research, but also to mathematics and other academic areas as well. One of the most important recent findings from quantitative genetic research such as twin studies is that the same set of genes is largely responsible for…

[Quantitative assessment of urban ecosystem services flow based on entropy theory: A case study of Beijing, China].

PubMed

Li, Jing Xin; Yang, Li; Yang, Lei; Zhang, Chao; Huo, Zhao Min; Chen, Min Hao; Luan, Xiao Feng

2018-03-01

Quantitative evaluation of ecosystem service is a primary premise for rational resources exploitation and sustainable development. Examining ecosystem services flow provides a scientific method to quantity ecosystem services. We built an assessment indicator system based on land cover/land use under the framework of four types of ecosystem services. The types of ecosystem services flow were reclassified. Using entropy theory, disorder degree and developing trend of indicators and urban ecosystem were quantitatively assessed. Beijing was chosen as the study area, and twenty-four indicators were selected for evaluation. The results showed that the entropy value of Beijing urban ecosystem during 2004 to 2015 was 0.794 and the entropy flow was -0.024, suggesting a large disordered degree and near verge of non-health. The system got maximum values for three times, while the mean annual variation of the system entropy value increased gradually in three periods, indicating that human activities had negative effects on urban ecosystem. Entropy flow reached minimum value in 2007, implying the environmental quality was the best in 2007. The determination coefficient for the fitting function of total permanent population in Beijing and urban ecosystem entropy flow was 0.921, indicating that urban ecosystem health was highly correlated with total permanent population.

Phenotype-Environment Interactions in Genetic Syndromes Associated with Severe or Profound Intellectual Disability

ERIC Educational Resources Information Center

Tunnicliffe, Penny; Oliver, Chris

2011-01-01

The research literature notes both biological and operant theories of behavior disorder in individuals with intellectual disabilities. These two theories of genetic predisposition and operant reinforcement remain quite distinct; neither theory on its own is sufficient to explain challenging behavior in genetic syndromes and an integrated approach…

Sex-dependent selection differentially shapes genetic variation on and off the guppy Y chromosome.

PubMed

Postma, Erik; Spyrou, Nicolle; Rollins, Lee Ann; Brooks, Robert C

2011-08-01

Because selection is often sex-dependent, alleles can have positive effects on fitness in one sex and negative effects in the other, resulting in intralocus sexual conflict. Evolutionary theory predicts that intralocus sexual conflict can drive the evolution of sex limitation, sex-linkage, and sex chromosome differentiation. However, evidence that sex-dependent selection results in sex-linkage is limited. Here, we formally partition the contribution of Y-linked and non-Y-linked quantitative genetic variation in coloration, tail, and body size of male guppies (Poecilia reticulata)-traits previously implicated as sexually antagonistic. We show that these traits are strongly genetically correlated, both on and off the Y chromosome, but that these correlations differ in sign and magnitude between both parts of the genome. As predicted, variation in attractiveness was found to be associated with the Y-linked, rather than with the non-Y-linked component of genetic variation in male ornamentation. These findings show how the evolution of Y-linkage may be able to resolve sexual conflict. More generally, they provide unique insight into how sex-specific selection has the potential to differentially shape the genetic architecture of fitness traits across different parts of the genome. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Maternal genetic effects on adaptive divergence between anadromous and resident brook charr during early life history.

PubMed

Perry, G M L; Audet, C; Bernatchez, L

2005-09-01

The importance of directional selection relative to neutral evolution may be determined by comparing quantitative genetic variation in phenotype (Q(ST)) to variation at neutral molecular markers (F(ST)). Quantitative divergence between salmonid life history types is often considerable, but ontogenetic changes in the significance of major sources of genetic variance during post-hatch development suggest that selective differentiation varies by developmental stage. In this study, we tested the hypothesis that maternal genetic differentiation between anadromous and resident brook charr (Salvelinus fontinalis Mitchill) populations for early quantitative traits (embryonic size/growth, survival, egg number and developmental time) would be greater than neutral genetic differentiation, but that the maternal genetic basis for differentiation would be higher for pre-resorption traits than post-resorption traits. Quantitative genetic divergence between anadromous (seawater migratory) and resident Laval River (Québec) brook charr based on maternal genetic variance was high (Q(ST) > 0.4) for embryonic length, yolk sac volume, embryonic growth rate and time to first response to feeding relative to neutral genetic differentiation [F(ST) = 0.153 (0.071-0.214)], with anadromous females having positive genetic coefficients for all of the above characters. However, Q(ST) was essentially zero for all traits post-resorption of the yolk sac. Our results indicate that the observed divergence between resident and anadromous brook charr has been driven by directional selection, and may therefore be adaptive. Moreover, they provide among the first evidence that the relative importance of selective differentiation may be highly context-specific, and varies by genetic contributions to phenotype by parental sex at specific points in offspring ontogeny. This in turn suggests that interpretations of Q(ST)-F(ST) comparisons may be improved by considering the structure of quantitative genetic

Local Genetic Correlation Gives Insights into the Shared Genetic Architecture of Complex Traits.

PubMed

Shi, Huwenbo; Mancuso, Nicholas; Spendlove, Sarah; Pasaniuc, Bogdan

2017-11-02

Although genetic correlations between complex traits provide valuable insights into epidemiological and etiological studies, a precise quantification of which genomic regions disproportionately contribute to the genome-wide correlation is currently lacking. Here, we introduce ρ-HESS, a technique to quantify the correlation between pairs of traits due to genetic variation at a small region in the genome. Our approach requires GWAS summary data only and makes no distributional assumption on the causal variant effect sizes while accounting for linkage disequilibrium (LD) and overlapping GWAS samples. We analyzed large-scale GWAS summary data across 36 quantitative traits, and identified 25 genomic regions that contribute significantly to the genetic correlation among these traits. Notably, we find 6 genomic regions that contribute to the genetic correlation of 10 pairs of traits that show negligible genome-wide correlation, further showcasing the power of local genetic correlation analyses. Finally, we report the distribution of local genetic correlations across the genome for 55 pairs of traits that show putative causal relationships. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

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.

Communicating the role of genetics in management

Treesearch

Mary F. Mahalovich

1997-01-01

Three current issues serve as examples to convey the role of genetics in management. (1) Consequences of silvicultural systems on the genetic resource of tree species are limited to one generation of study and isozyme (qualitative) data. Results of simulated data for diameter (quantitative data) over several generations, illustrate the pitfalls of working towards...

Electromagnetic braking: A simple quantitative model

NASA Astrophysics Data System (ADS)

Levin, Yan; da Silveira, Fernando L.; Rizzato, Felipe B.

2006-09-01

A calculation is presented that quantitatively accounts for the terminal velocity of a cylindrical magnet falling through a long copper or aluminum pipe. The experiment and the theory are a dramatic illustration of Faraday's and Lenz's laws.

An optimization design for evacuation planning based on fuzzy credibility theory and genetic algorithm

NASA Astrophysics Data System (ADS)

Zhang, D.; Zhang, W. Y.

2017-08-01

Evacuation planning is an important activity in disaster management. It has to be planned in advance due to the unpredictable occurrence of disasters. It is necessary that the evacuation plans are as close as possible to the real evacuation work. However, the evacuation plan is extremely challenging because of the inherent uncertainty of the required information. There is a kind of vehicle routing problem based on the public traffic evacuation. In this paper, the demand for each evacuation set point is a fuzzy number, and each routing selection of the point is based on the fuzzy credibility preference index. This paper proposes an approximate optimal solution for this problem by the genetic algorithm based on the fuzzy reliability theory. Finally, the algorithm is applied to an optimization model, and the experiment result shows that the algorithm is effective.

Advances in Genetical Genomics of Plants

PubMed Central

Joosen, R.V.L.; Ligterink, W.; Hilhorst, H.W.M.; Keurentjes, J.J.B.

2009-01-01

Natural variation provides a valuable resource to study the genetic regulation of quantitative traits. In quantitative trait locus (QTL) analyses this variation, captured in segregating mapping populations, is used to identify the genomic regions affecting these traits. The identification of the causal genes underlying QTLs is a major challenge for which the detection of gene expression differences is of major importance. By combining genetics with large scale expression profiling (i.e. genetical genomics), resulting in expression QTLs (eQTLs), great progress can be made in connecting phenotypic variation to genotypic diversity. In this review we discuss examples from human, mouse, Drosophila, yeast and plant research to illustrate the advances in genetical genomics, with a focus on understanding the regulatory mechanisms underlying natural variation. With their tolerance to inbreeding, short generation time and ease to generate large families, plants are ideal subjects to test new concepts in genetics. The comprehensive resources which are available for Arabidopsis make it a favorite model plant but genetical genomics also found its way to important crop species like rice, barley and wheat. We discuss eQTL profiling with respect to cis and trans regulation and show how combined studies with other ‘omics’ technologies, such as metabolomics and proteomics may further augment current information on transcriptional, translational and metabolomic signaling pathways and enable reconstruction of detailed regulatory networks. The fast developments in the ‘omics’ area will offer great potential for genetical genomics to elucidate the genotype-phenotype relationships for both fundamental and applied research. PMID:20514216

Molecular Population Genetics

PubMed Central

Casillas, Sònia; Barbadilla, Antonio

2017-01-01

Molecular population genetics aims to explain genetic variation and molecular evolution from population genetics principles. The field was born 50 years ago with the first measures of genetic variation in allozyme loci, continued with the nucleotide sequencing era, and is currently in the era of population genomics. During this period, molecular population genetics has been revolutionized by progress in data acquisition and theoretical developments. The conceptual elegance of the neutral theory of molecular evolution or the footprint carved by natural selection on the patterns of genetic variation are two examples of the vast number of inspiring findings of population genetics research. Since the inception of the field, Drosophila has been the prominent model species: molecular variation in populations was first described in Drosophila and most of the population genetics hypotheses were tested in Drosophila species. In this review, we describe the main concepts, methods, and landmarks of molecular population genetics, using the Drosophila model as a reference. We describe the different genetic data sets made available by advances in molecular technologies, and the theoretical developments fostered by these data. Finally, we review the results and new insights provided by the population genomics approach, and conclude by enumerating challenges and new lines of inquiry posed by increasingly large population scale sequence data. PMID:28270526

Genetic programming based quantitative structure-retention relationships for the prediction of Kovats retention indices.

PubMed

Goel, Purva; Bapat, Sanket; Vyas, Renu; Tambe, Amruta; Tambe, Sanjeev S

2015-11-13

The development of quantitative structure-retention relationships (QSRR) aims at constructing an appropriate linear/nonlinear model for the prediction of the retention behavior (such as Kovats retention index) of a solute on a chromatographic column. Commonly, multi-linear regression and artificial neural networks are used in the QSRR development in the gas chromatography (GC). In this study, an artificial intelligence based data-driven modeling formalism, namely genetic programming (GP), has been introduced for the development of quantitative structure based models predicting Kovats retention indices (KRI). The novelty of the GP formalism is that given an example dataset, it searches and optimizes both the form (structure) and the parameters of an appropriate linear/nonlinear data-fitting model. Thus, it is not necessary to pre-specify the form of the data-fitting model in the GP-based modeling. These models are also less complex, simple to understand, and easy to deploy. The effectiveness of GP in constructing QSRRs has been demonstrated by developing models predicting KRIs of light hydrocarbons (case study-I) and adamantane derivatives (case study-II). In each case study, two-, three- and four-descriptor models have been developed using the KRI data available in the literature. The results of these studies clearly indicate that the GP-based models possess an excellent KRI prediction accuracy and generalization capability. Specifically, the best performing four-descriptor models in both the case studies have yielded high (>0.9) values of the coefficient of determination (R(2)) and low values of root mean squared error (RMSE) and mean absolute percent error (MAPE) for training, test and validation set data. The characteristic feature of this study is that it introduces a practical and an effective GP-based method for developing QSRRs in gas chromatography that can be gainfully utilized for developing other types of data-driven models in chromatography science

Using Expectancy Theory to quantitatively dissociate the neural representation of motivation from its influential factors in the human brain: An fMRI study.

PubMed

Kohli, Akshay; Blitzer, David N; Lefco, Ray W; Barter, Joseph W; Haynes, M Ryan; Colalillo, Sam A; Ly, Martina; Zink, Caroline F

2018-05-08

Researchers have yet to apply a formal operationalized theory of motivation to neurobiology that would more accurately and precisely define neural activity underlying motivation. We overcome this challenge with the novel application of the Expectancy Theory of Motivation to human fMRI to identify brain activity that explicitly reflects motivation. Expectancy Theory quantitatively describes how individual constructs determine motivation by defining motivation force as the product of three variables: expectancy - belief that effort will better performance; instrumentality - belief that successful performance leads to particular outcome, and valence - outcome desirability. Here, we manipulated information conveyed by reward-predicting cues such that relative cue-evoked activity patterns could be statistically mapped to individual Expectancy Theory variables. The variable associated with activity in any voxel is only reported if it replicated between two groups of healthy participants. We found signals in midbrain, ventral striatum, sensorimotor cortex, and visual cortex that specifically map to motivation itself, rather than other factors. This is important because, for the first time, it empirically clarifies approach motivation neural signals during reward anticipation. It also highlights the effectiveness of the application of Expectancy Theory to neurobiology to more precisely and accurately probe motivation neural correlates than has been achievable previously. Copyright © 2018 Elsevier Inc. All rights reserved.

Data Sufficiency Assessment and Pumping Test Design for Groundwater Prediction Using Decision Theory and Genetic Algorithms

NASA Astrophysics Data System (ADS)

McPhee, J.; William, Y. W.

2005-12-01

This work presents a methodology for pumping test design based on the reliability requirements of a groundwater model. Reliability requirements take into consideration the application of the model results in groundwater management, expressed in this case as a multiobjective management model. The pumping test design is formulated as a mixed-integer nonlinear programming (MINLP) problem and solved using a combination of genetic algorithm (GA) and gradient-based optimization. Bayesian decision theory provides a formal framework for assessing the influence of parameter uncertainty over the reliability of the proposed pumping test. The proposed methodology is useful for selecting a robust design that will outperform all other candidate designs under most potential 'true' states of the system

High-resolution genetic linkage mapping, high-temperature tolerance and growth-related quantitative trait locus (QTL) identification in Marsupenaeus japonicus.

PubMed

Lu, Xia; Luan, Sheng; Hu, Long Yang; Mao, Yong; Tao, Ye; Zhong, Sheng Ping; Kong, Jie

2016-06-01

The Kuruma prawn, Marsupenaeus japonicus, is one of the most promising marine invertebrates in the industry in Asia, Europe and Australia. However, the increasing global temperatures result in considerable economic losses in M. japonicus farming. In the present study, to select genetically improved animals for the sustainable development of the Kuruma prawn industry, a high-resolution genetic linkage map and quantitative trait locus (QTL) identification were performed using the RAD technology. The maternal map contained 5849 SNP markers and spanned 3127.23 cM, with an average marker interval of 0.535 cM. Instead, the paternal map contained 3927 SNP markers and spanned 3326.19 cM, with an average marker interval of 0.847 cM. The consensus map contained 9289 SNP markers and spanned 3610.90 cM, with an average marker interval of 0.388 cM and coverage of 99.06 % of the genome. The markers were grouped into 41 linkage groups in the maps. Significantly, negative correlation was detected between high-temperature tolerance (UTT) and body weight (BW). The QTL mapping revealed 129 significant QTL loci for UTT and four significant QTL loci for BW at the genome-wide significance threshold. Among these QTLs, 129 overlapped with linked SNPs, and the remaining four were located in regions between contiguous SNPs. They explained the total phenotypic variance ranging from 8.9 to 12.4 %. Because of a significantly negative correlation between growth and high-temperature tolerance, we demonstrate that this high-resolution linkage map and QTLs would be useful for further marker-assisted selection in the genetic improvement of M. japonicus.

Joint effects of pleiotropic selection and stabilizing selection on the maintenance of quantitative genetic variation at mutation-selection balance.

PubMed Central

Zhang, Xu-Sheng; Hill, William G

2002-01-01

In quantitative genetics, there are two basic "conflicting" observations: abundant polygenic variation and strong stabilizing selection that should rapidly deplete that variation. This conflict, although having attracted much theoretical attention, still stands open. Two classes of model have been proposed: real stabilizing selection directly on the metric trait under study and apparent stabilizing selection caused solely by the deleterious pleiotropic side effects of mutations on fitness. Here these models are combined and the total stabilizing selection observed is assumed to derive simultaneously through these two different mechanisms. Mutations have effects on a metric trait and on fitness, and both effects vary continuously. The genetic variance (V(G)) and the observed strength of total stabilizing selection (V(s,t)) are analyzed with a rare-alleles model. Both kinds of selection reduce V(G) but their roles in depleting it are not independent: The magnitude of pleiotropic selection depends on real stabilizing selection and such dependence is subject to the shape of the distributions of mutational effects. The genetic variation maintained thus depends on the kurtosis as well as the variance of mutational effects: All else being equal, V(G) increases with increasing leptokurtosis of mutational effects on fitness, while for a given distribution of mutational effects on fitness, V(G) decreases with increasing leptokurtosis of mutational effects on the trait. The V(G) and V(s,t) are determined primarily by real stabilizing selection while pleiotropic effects, which can be large, have only a limited impact. This finding provides some promise that a high heritability can be explained under strong total stabilizing selection for what are regarded as typical values of mutation and selection parameters. PMID:12242254

What Use Is Population Genetics?

PubMed

Charlesworth, Brian

2015-07-01

The Genetic Society of America's Thomas Hunt Morgan Medal is awarded to an individual GSA member for lifetime achievement in the field of genetics. For over 40 years, 2015 recipient Brian Charlesworth has been a leader in both theoretical and empirical evolutionary genetics, making substantial contributions to our understanding of how evolution acts on genetic variation. Some of the areas in which Charlesworth's research has been most influential are the evolution of sex chromosomes, transposable elements, deleterious mutations, sexual reproduction, and life history. He also developed the influential theory of background selection, whereby the recurrent elimination of deleterious mutations reduces variation at linked sites, providing a general explanation for the correlation between recombination rate and genetic variation. Copyright © 2015 by the Genetics Society of America.

The power of exact conditions in electronic structure theory

NASA Astrophysics Data System (ADS)

Bartlett, Rodney J.; Ranasinghe, Duminda S.

2017-02-01

Once electron correlation is included in an effective one-particle operator, one has a correlated orbital theory (COT). One such theory is Kohn-Sham density functional theory (KS-DFT), but there are others. Such methods have the prospect to redefine traditional Molecular Orbital (MO) theory by building a quantitative component upon its conceptual framework. This paper asks the question what conditions should such a theory satisfy and can this be accomplished? One such condition for a COT is that the orbital eigenvalues should satisfy an ionization theorem that generalizes Koopmans' approximation to the exact principal ionization potentials for every electron in a molecule. Guided by this principle, minimal parameterizations of KS-DFT are made that provide a good approximation to a quantitative MO theory.

7 CFR 3430.309 - Priority areas.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Agriculture and Food Research Initiative § 3430.309 Priority areas. NIFA will award competitive grants in the...) Conventional breeding, including cultivar and breed development, selection theory, applied quantitative... development, selection theory, applied quantitative genetics, breeding for improved food quality, breeding for...

7 CFR 3430.309 - Priority areas.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Agriculture and Food Research Initiative § 3430.309 Priority areas. NIFA will award competitive grants in the...) Conventional breeding, including cultivar and breed development, selection theory, applied quantitative... development, selection theory, applied quantitative genetics, breeding for improved food quality, breeding for...

7 CFR 3430.309 - Priority areas.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Agriculture and Food Research Initiative § 3430.309 Priority areas. NIFA will award competitive grants in the...) Conventional breeding, including cultivar and breed development, selection theory, applied quantitative... development, selection theory, applied quantitative genetics, breeding for improved food quality, breeding for...

7 CFR 3430.309 - Priority areas.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Agriculture and Food Research Initiative § 3430.309 Priority areas. NIFA will award competitive grants in the...) Conventional breeding, including cultivar and breed development, selection theory, applied quantitative... development, selection theory, applied quantitative genetics, breeding for improved food quality, breeding for...

Genetic variation in social environment construction influences the development of aggressive behavior in Drosophila melanogaster

PubMed Central

Saltz, J B

2017-01-01

Individuals are not merely subject to their social environments; they choose and create them, through a process called social environment (or social niche) construction. When genotypes differ in social environment-constructing behaviors, different genotypes are expected to experience different social environments. As social experience often affects behavioral development, quantitative genetics and psychology theories predict that genetic variation in social environment construction should have an important role in determining phenotypic variation; however, this hypothesis has not been tested directly. I identify multiple mechanisms of social environment construction that differ among natural genotypes of Drosophila melanogaster and investigate their consequences for the development of aggressive behavior. Male genotypes differed in the group sizes that they preferred and in their aggressive behavior; both of these behaviors influenced social experience, demonstrating that these behaviors function as social environment-constructing traits. Further, the effects of social experience—as determined in part by social environment construction—carried over to affect focal male aggression at a later time and with a new opponent. These results provide manipulative experimental support for longstanding hypotheses in psychology, that genetic variation in social environment construction has a causal role in behavioral development. More broadly, these results imply that studies of the genetic basis of complex traits should be expanded to include mechanisms by which genetic variation shapes the environments that individuals experience. PMID:27848947

The quantitative LOD score: test statistic and sample size for exclusion and linkage of quantitative traits in human sibships.

PubMed

Page, G P; Amos, C I; Boerwinkle, E

1998-04-01

We present a test statistic, the quantitative LOD (QLOD) score, for the testing of both linkage and exclusion of quantitative-trait loci in randomly selected human sibships. As with the traditional LOD score, the boundary values of 3, for linkage, and -2, for exclusion, can be used for the QLOD score. We investigated the sample sizes required for inferring exclusion and linkage, for various combinations of linked genetic variance, total heritability, recombination distance, and sibship size, using fixed-size sampling. The sample sizes required for both linkage and exclusion were not qualitatively different and depended on the percentage of variance being linked or excluded and on the total genetic variance. Information regarding linkage and exclusion in sibships larger than size 2 increased as approximately all possible pairs n(n-1)/2 up to sibships of size 6. Increasing the recombination (theta) distance between the marker and the trait loci reduced empirically the power for both linkage and exclusion, as a function of approximately (1-2theta)4.

Selection of Suitable DNA Extraction Methods for Genetically Modified Maize 3272, and Development and Evaluation of an Event-Specific Quantitative PCR Method for 3272.

PubMed

Takabatake, Reona; Masubuchi, Tomoko; Futo, Satoshi; Minegishi, Yasutaka; Noguchi, Akio; Kondo, Kazunari; Teshima, Reiko; Kurashima, Takeyo; Mano, Junichi; Kitta, Kazumi

2016-01-01

A novel real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) maize, 3272. We first attempted to obtain genome DNA from this maize using a DNeasy Plant Maxi kit and a DNeasy Plant Mini kit, which have been widely utilized in our previous studies, but DNA extraction yields from 3272 were markedly lower than those from non-GM maize seeds. However, lowering of DNA extraction yields was not observed with GM quicker or Genomic-tip 20/G. We chose GM quicker for evaluation of the quantitative method. We prepared a standard plasmid for 3272 quantification. The conversion factor (Cf), which is required to calculate the amount of a genetically modified organism (GMO), was experimentally determined for two real-time PCR instruments, the Applied Biosystems 7900HT (the ABI 7900) and the Applied Biosystems 7500 (the ABI7500). The determined Cf values were 0.60 and 0.59 for the ABI 7900 and the ABI 7500, respectively. To evaluate the developed method, a blind test was conducted as part of an interlaboratory study. The trueness and precision were evaluated as the bias and reproducibility of the relative standard deviation (RSDr). The determined values were similar to those in our previous validation studies. The limit of quantitation for the method was estimated to be 0.5% or less, and we concluded that the developed method would be suitable and practical for detection and quantification of 3272.

Genetic influences on adolescent sexual behavior: Why genes matter for environmentally oriented researchers.

PubMed

Harden, K Paige

2014-03-01

There are dramatic individual differences among adolescents in how and when they become sexually active adults, and early sexual activity is frequently cited as a cause of concern for scientists, policymakers, and the general public. Understanding the causes and developmental impact of adolescent sexual activity can be furthered by considering genes as a source of individual differences. Quantitative behavioral genetics (i.e., twin and family studies) and candidate gene association studies now provide clear evidence for the genetic underpinnings of individual differences in adolescent sexual behavior and related phenotypes. Genetic influences on sexual behavior may operate through a variety of direct and indirect mechanisms, including pubertal development, testosterone levels, and dopaminergic systems. Genetic differences may be systematically associated with exposure to environments that are commonly treated as causes of sexual behavior (gene-environment correlation). Possible gene-environment correlations pose a serious challenge for interpreting the results of much behavioral research. Multivariate, genetically informed research on adolescent sexual behavior compares twins and family members as a form of quasi experiment: How do twins who differ in their sexual experiences differ in their later development? The small but growing body of genetically informed research has already challenged dominant assumptions regarding the etiology and sequelae of adolescent sexual behavior, with some studies indicating possible positive effects of teenage sexuality. Studies of Gene × Environment interaction may further elucidate the mechanisms by which genes and environments combine to shape the development of sexual behavior and its psychosocial consequences. Overall, the existence of heritable variation in adolescent sexual behavior has profound implications for environmentally oriented theory and research.

Endosymbiosis and its implications for evolutionary theory.

PubMed

O'Malley, Maureen A

2015-08-18

Historically, conceptualizations of symbiosis and endosymbiosis have been pitted against Darwinian or neo-Darwinian evolutionary theory. In more recent times, Lynn Margulis has argued vigorously along these lines. However, there are only shallow grounds for finding Darwinian concepts or population genetic theory incompatible with endosymbiosis. But is population genetics sufficiently explanatory of endosymbiosis and its role in evolution? Population genetics "follows" genes, is replication-centric, and is concerned with vertically consistent genetic lineages. It may also have explanatory limitations with regard to macroevolution. Even so, asking whether population genetics explains endosymbiosis may have the question the wrong way around. We should instead be asking how explanatory of evolution endosymbiosis is, and exactly which features of evolution it might be explaining. This paper will discuss how metabolic innovations associated with endosymbioses can drive evolution and thus provide an explanatory account of important episodes in the history of life. Metabolic explanations are both proximate and ultimate, in the same way genetic explanations are. Endosymbioses, therefore, point evolutionary biology toward an important dimension of evolutionary explanation.

[The genetic control of mouse coat color and its applications in genetics teaching].

PubMed

Xing, Wanjin; Morigen, Morigen

2014-10-01

Mice are the most commonly used mammalian model. The coat colors of mice are typical Mendelian traits, which have various colors such as white, black, yellow and agouti. The inheritance of mouse coat color is usually stated as an example only in teaching the knowledge of recessive lethal alleles. After searched the related literatures and summarized the molecular mechanisms of mouse coat color inheritance, we further expanded the application of this example into the introduction of the basic concepts of alleles and Mendelian laws, demonstration of the gene structure and function, regulation of gene expression, gene interaction, epigenetic modification, quantitative genetics, as well as evolutionary genetics. By running this example through the whole genetics-teaching lectures, we help the student to form a systemic and developmental view of genetic analysis. At the same time, this teaching approach not only highlights the advancement and integrity of genetics, but also results in a good teaching effect on inspiring the students' interest and attracting students' attention.

Genetic counseling and the ethical issues around direct to consumer genetic testing.

PubMed

Hawkins, Alice K; Ho, Anita

2012-06-01

Over the last several years, direct to consumer(DTC) genetic testing has received increasing attention in the public, healthcare and academic realms. DTC genetic testing companies face considerable criticism and scepticism,particularly from the medical and genetic counseling community. This raises the question of what specific aspects of DTC genetic testing provoke concerns, and conversely,promises, for genetic counselors. This paper addresses this question by exploring DTC genetic testing through an ethic allens. By considering the fundamental ethical approaches influencing genetic counseling (the ethic of care and principle-based ethics) we highlight the specific ethical concerns raised by DTC genetic testing companies. Ultimately,when considering the ethics of DTC testing in a genetic counseling context, we should think of it as a balancing act. We need careful and detailed consideration of the risks and troubling aspects of such testing, as well as the potentially beneficial direct and indirect impacts of the increased availability of DTC genetic testing. As a result it is essential that genetic counselors stay informed and involved in the ongoing debate about DTC genetic testing and DTC companies. Doing so will ensure that the ethical theories and principles fundamental to the profession of genetic counseling are promoted not just in traditional counseling sessions,but also on a broader level. Ultimately this will help ensure that the public enjoys the benefits of an increasingly genetic based healthcare system.

Little effect of HSP90 inhibition on the quantitative wing traits variation in Drosophila melanogaster.

PubMed

Takahashi, Kazuo H

2017-02-01

Drosophila wings have been a model system to study the effect of HSP90 on quantitative trait variation. The effect of HSP90 inhibition on environmental buffering of wing morphology varies among studies while the genetic buffering effect of it was examined in only one study and was not detected. Variable results so far might show that the genetic background influences the environmental and genetic buffering effect of HSP90. In the previous studies, the number of the genetic backgrounds used is limited. To examine the effect of HSP90 inhibition with a larger number of genetic backgrounds than the previous studies, 20 wild-type strains of Drosophila melanogaster were used in this study. Here I investigated the effect of HSP90 inhibition on the environmental buffering of wing shape and size by assessing within-individual and among-individual variations, and as a result, I found little or very weak effects on environmental and genetic buffering. The current results suggest that the role of HSP90 as a global regulator of environmental and genetic buffering is limited at least in quantitative traits.

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

Quantitative assessment of cerebral blood flow in genetically confirmed spinocerebellar ataxia type 6.

PubMed

Honjo, Kie; Ohshita, Tomohiko; Kawakami, Hideshi; Naka, Hiromitsu; Imon, Yukari; Maruyama, Hirofumi; Mimori, Yasuyo; Matsumoto, Masayasu

2004-06-01

Spinocerebellar ataxia type 6 (SCA6) is an autosomal dominant cerebellar ataxia caused by CAG trinucleotide expansion. The characteristics of regional cerebral blood flow (rCBF) in SCA6 patients have not been established, whereas it has been reported that decreased rCBF in the cerebrum seems to be a remote effect of cerebellar impairment in other cerebellar disorders. To clarify the characteristics of rCBF, including cerebro-cerebellar relationship, and its correlation with clinical manifestations in patients with genetically confirmed SCA6 using quantitative assessment of rCBF by brain single-photon emission computed tomography (SPECT). Technetium Tc 99m ethyl cysteinate dimer SPECT study using a Patlak plot. Patients Hiroshima University Hospital, Hiroshima, Japan. Ten patients with SCA6 and 9 healthy controls. Main Outcome Measure The rCBF of the cerebellar vermis, cerebellar hemisphere, and frontal lobes. In SCA6 patients, rCBF was decreased only in the cerebellar vermis and hemisphere compared with healthy controls, and this was inversely correlated with duration of illness. The rCBF in the frontal lobes was slightly correlated with duration of illness without statistical significance. The rCBF in the vermis was inversely correlated with severity of dysarthria, but there was no significant correlation with CAG repeated expansions. Decrease in rCBF was found only in the cerebellum and was associated with duration of illness, dysarthria and ataxia, and cerebellar atrophy. No remote effect of cerebellar hypoperfusion was found in the SCA6 patients.

Colour ornamentation in the blue tit: quantitative genetic (co)variances across sexes

PubMed Central

Charmantier, A; Wolak, M E; Grégoire, A; Fargevieille, A; Doutrelant, C

2017-01-01

Although secondary sexual traits are commonly more developed in males than females, in many animal species females also display elaborate ornaments or weaponry. Indirect selection on correlated traits in males and/or direct sexual or social selection in females are hypothesized to drive the evolution and maintenance of female ornaments. Yet, the relative roles of these evolutionary processes remain unidentified, because little is known about the genetic correlation that might exist between the ornaments of both sexes, and few estimates of sex-specific autosomal or sex-linked genetic variances are available. In this study, we used two wild blue tit populations with 9 years of measurements on two colour ornaments: one structurally based (blue crown) and one carotenoid based (yellow chest). We found significant autosomal heritability for the chromatic part of the structurally based colouration in both sexes, whereas carotenoid chroma was heritable only in males, and the achromatic part of both colour patches was mostly non heritable. Power limitations, which are probably common among most data sets collected so far in wild populations, prevented estimation of sex-linked genetic variance. Bivariate analyses revealed very strong cross-sex genetic correlations in all heritable traits, although the strength of these correlations was not related to the level of sexual dimorphism. In total, our results suggest that males and females share a majority of their genetic variation underlying colour ornamentation, and hence the evolution of these sex-specific traits may depend greatly on correlated responses to selection in the opposite sex. PMID:27577691

Application of image analysis in studies of quantitative disease resistance, exemplified using common bacterial blight-common bean pathosystem.

PubMed

Xie, Weilong; Yu, Kangfu; Pauls, K Peter; Navabi, Alireza

2012-04-01

The effectiveness of image analysis (IA) compared with an ordinal visual scale, for quantitative measurement of disease severity, its application in quantitative genetic studies, and its effect on the estimates of genetic parameters were investigated. Studies were performed using eight backcross-derived families of common bean (Phaseolus vulgaris) (n = 172) segregating for the molecular marker SU91, known to be associated with a quantitative trait locus (QTL) for resistance to common bacterial blight (CBB), caused by Xanthomonas campestris pv. phaseoli and X. fuscans subsp. fuscans. Even though both IA and visual assessments were highly repeatable, IA was more sensitive in detecting quantitative differences between bean genotypes. The CBB phenotypic difference between the two SU91 genotypic groups was consistently more than fivefold for IA assessments but generally only two- to threefold for visual assessments. Results suggest that the visual assessment results in overestimation of the effect of QTL in genetic studies. This may have been caused by lack of additivity and uneven intervals of the visual scale. Although visual assessment of disease severity is a useful tool for general selection in breeding programs, assessments using IA may be more suitable for phenotypic evaluations in quantitative genetic studies involving CBB resistance as well as other foliar diseases.

Current and future developments in patents for quantitative trait loci in dairy cattle.

PubMed

Weller, Joel I

2007-01-01

Many studies have proposed that rates of genetic gain in dairy cattle can be increased by direct selection on the individual quantitative loci responsible for the genetic variation in these traits, or selection on linked genetic markers. The development of DNA-level genetic markers has made detection of QTL nearly routine in all major livestock species. The studies that attempted to detect genes affecting quantitative traits can be divided into two categories: analysis of candidate genes, and genome scans based on within-family genetic linkage. To date, 12 patent cooperative treaty (PCT) and US patents have been registered for DNA sequences claimed to be associated with effects on economic traits in dairy cattle. All claim effects on milk production, but other traits are also included in some of the claims. Most of the sequences found by the candidate gene approach are of dubious validity, and have been repeated in only very few independent studies. The two missense mutations on chromosomes 6 and 14 affecting milk concentration derived from genome scans are more solidly based, but the claims are also disputed. A few PCT in dairy cattle are commercialized as genetic tests where commercial dairy farmers are the target market.

Genetic algorithms as global random search methods

NASA Technical Reports Server (NTRS)

Peck, Charles C.; Dhawan, Atam P.

1995-01-01

Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that the schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solutions and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.

Genetic algorithms as global random search methods

NASA Technical Reports Server (NTRS)

Peck, Charles C.; Dhawan, Atam P.

1995-01-01

Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that that schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solution and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.

Molecular Population Genetics.

PubMed

Casillas, Sònia; Barbadilla, Antonio

2017-03-01

Molecular population genetics aims to explain genetic variation and molecular evolution from population genetics principles. The field was born 50 years ago with the first measures of genetic variation in allozyme loci, continued with the nucleotide sequencing era, and is currently in the era of population genomics. During this period, molecular population genetics has been revolutionized by progress in data acquisition and theoretical developments. The conceptual elegance of the neutral theory of molecular evolution or the footprint carved by natural selection on the patterns of genetic variation are two examples of the vast number of inspiring findings of population genetics research. Since the inception of the field, Drosophila has been the prominent model species: molecular variation in populations was first described in Drosophila and most of the population genetics hypotheses were tested in Drosophila species. In this review, we describe the main concepts, methods, and landmarks of molecular population genetics, using the Drosophila model as a reference. We describe the different genetic data sets made available by advances in molecular technologies, and the theoretical developments fostered by these data. Finally, we review the results and new insights provided by the population genomics approach, and conclude by enumerating challenges and new lines of inquiry posed by increasingly large population scale sequence data. Copyright © 2017 Casillas and Barbadilla.

Awareness of Societal Issues Among High School Biology Teachers Teaching Genetics

NASA Astrophysics Data System (ADS)

Lazarowitz, Reuven; Bloch, Ilit

2005-12-01

The purpose of this study was to investigate how aware high school biology teachers are of societal issues (values, moral, ethic, and legal issues) while teaching genetics, genetics engineering, molecular genetics, human heredity, and evolution. The study includes a short historical review of World War II atrocities during the Holocaust when scientists from all the above-mentioned disciplines had been involved in trying to support and develop the eugenics theories. It investigates pre- and postwar theories of the eugenics movement in the United States which were implemented successfully in Germany and a literature survey of the studies of societal issues related to these subjects. The sample consisted of 30 male and female biology teachers. Enclosed are teachers' answers in favor or against including debates about societal issues in their classrooms while teaching the disciplines mentioned above. Teachers' answers were analyzed in relation to three variables: years of teaching experience, gender, and religion faith. Data were collected from questionnaires and personal interviews and analyzed according to qualitative and quantitative methods. The results show that amongst the teachers there is a medium to low level of awareness of societal issues, while mainly emphasizing scientific subjects in preparation of matriculation examinations. The majority of the teachers do not include societal issues in their teaching, but if students raise these issues, teachers claimed to address them. No differences in teachers' opinions to societal issues were found in relation to gender or religious faith. Teachers with more years of teaching experience tend to teach with a more Science, Technology, and Society (STS) approach than novice teachers. The results are discussed in relation to teachers' professional development and teaching strategies are suggested to be used in their classrooms based on a STS approach, which includes the societal issues as a main goal.

Quantitative steps in the evolution of metabolic organisation as specified by the Dynamic Energy Budget theory.

PubMed

Kooijman, S A L M; Troost, T A

2007-02-01

The Dynamic Energy Budget (DEB) theory quantifies the metabolic organisation of organisms on the basis of mechanistically inspired assumptions. We here sketch a scenario for how its various modules, such as maintenance, storage dynamics, development, differentiation and life stages could have evolved since the beginning of life. We argue that the combination of homeostasis and maintenance induced the development of reserves and that subsequent increases in the maintenance costs came with increases of the reserve capacity. Life evolved from a multiple reserves - single structure system (prokaryotes, many protoctists) to systems with multiple reserves and two structures (plants) or single reserve and single structure (animals). This had profound consequences for the possible effects of temperature on rates. We present an alternative explanation for what became known as the down-regulation of maintenance at high growth rates in microorganisms; the density of the limiting reserve increases with the growth rate, and reserves do not require maintenance while structure-specific maintenance costs are independent of the growth rate. This is also the mechanism behind the variation of the respiration rate with body size among species. The DEB theory specifies reserve dynamics on the basis of the requirements of weak homeostasis and partitionability. We here present a new and simple mechanism for this dynamics which accounts for the rejection of mobilised reserve by busy maintenance/growth machinery. This module, like quite a few other modules of DEB theory, uses the theory of Synthesising Units; we review recent progress in this field. The plasticity of membranes that evolved in early eukaryotes is a major step forward in metabolic evolution; we discuss quantitative aspects of the efficiency of phagocytosis relative to the excretion of digestive enzymes to illustrate its importance. Some processes of adaptation and gene expression can be understood in terms of allocation

Quantitative prediction of solute strengthening in aluminium alloys.

PubMed

Leyson, Gerard Paul M; Curtin, William A; Hector, Louis G; Woodward, Christopher F

2010-09-01

Despite significant advances in computational materials science, a quantitative, parameter-free prediction of the mechanical properties of alloys has been difficult to achieve from first principles. Here, we present a new analytic theory that, with input from first-principles calculations, is able to predict the strengthening of aluminium by substitutional solute atoms. Solute-dislocation interaction energies in and around the dislocation core are first calculated using density functional theory and a flexible-boundary-condition method. An analytic model for the strength, or stress to move a dislocation, owing to the random field of solutes, is then presented. The theory, which has no adjustable parameters and is extendable to other metallic alloys, predicts both the energy barriers to dislocation motion and the zero-temperature flow stress, allowing for predictions of finite-temperature flow stresses. Quantitative comparisons with experimental flow stresses at temperature T=78 K are made for Al-X alloys (X=Mg, Si, Cu, Cr) and good agreement is obtained.

Prospects and challenges of quantitative phase imaging in tumor cell biology

NASA Astrophysics Data System (ADS)

Kemper, Björn; Götte, Martin; Greve, Burkhard; Ketelhut, Steffi

2016-03-01

Quantitative phase imaging (QPI) techniques provide high resolution label-free quantitative live cell imaging. Here, prospects and challenges of QPI in tumor cell biology are presented, using the example of digital holographic microscopy (DHM). It is shown that the evaluation of quantitative DHM phase images allows the retrieval of different parameter sets for quantification of cellular motion changes in migration and motility assays that are caused by genetic modifications. Furthermore, we demonstrate simultaneously label-free imaging of cell growth and morphology properties.

Efficacy of a web-based intelligent tutoring system for communicating genetic risk of breast cancer: a fuzzy-trace theory approach.

PubMed

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

2015-01-01

. Many healthy women consider genetic testing for breast cancer risk, yet BRCA testing issues are complex. . To determine whether an intelligent tutor, BRCA Gist, grounded in fuzzy-trace theory (FTT), increases gist comprehension and knowledge about genetic testing for breast cancer risk, improving decision making. . In 2 experiments, 410 healthy undergraduate women were randomly assigned to 1 of 3 groups: an online module using a Web-based tutoring system (BRCA Gist) that uses artificial intelligence technology, a second group read highly similar content from the National Cancer Institute (NCI) Web site, and a third that completed an unrelated tutorial. . BRCA Gist applied FTT and was designed to help participants develop gist comprehension of topics relevant to decisions about BRCA genetic testing, including how breast cancer spreads, inherited genetic mutations, and base rates. . We measured content knowledge, gist comprehension of decision-relevant information, interest in testing, and genetic risk and testing judgments. . Control knowledge scores ranged from 54% to 56%, NCI improved significantly to 65% and 70%, and BRCA Gist improved significantly more to 75% and 77%, P < 0.0001. BRCA Gist scored higher on gist comprehension than NCI and control, P < 0.0001. Control genetic risk-assessment mean was 48% correct; BRCA Gist (61%) and NCI (56%) were significantly higher, P < 0.0001. BRCA Gist participants recommended less testing for women without risk factors (not good candidates; 24% and 19%) than controls (50%, both experiments) and NCI (32%), experiment 2, P < 0.0001. BRCA Gist testing interest was lower than in controls, P < 0.0001. . BRCA Gist has not been tested with older women from diverse groups. . Intelligent tutors, such as BRCA Gist, are scalable, cost-effective ways of helping people understand complex issues, improving decision making. © The Author(s) 2014.

Quantitative Assessment of CYP2C9 Genetic Polymorphisms Effect on the Oral Clearance of S-Warfarin in Healthy Subjects.

PubMed

Shaul, Chanan; Blotnick, Simcha; Muszkat, Mordechai; Bialer, Meir; Caraco, Yoseph

2017-02-01

Genetic polymorphisms in CYP2C9 account for 10-20% of the variability in warfarin dose requirement. As such CYP2C9 genetic polymorphisms are commonly included in algorithms aimed to optimize warfarin therapy as a way to account for variability in warfarin responsiveness that is due to altered pharmacokinetics. However, most of the currently available pharmacokinetic data were derived from studies among patients on chronic warfarin therapy and therefore suffer from the confounding effects of disease states and drug interactions. The purpose of the present study was to provide an accurate quantitative estimate of S-warfarin oral clearance (CL S ) among healthy subjects carrying different CYP2C9 genotypes. Single dose of warfarin was administered to 150 non-smokers, age (mean ± SD) 23.3 ± 4.5 years, 60% male, non-obese, healthy subjects. Blood samples were taken for up to 168 h and urine was collected over the entire study period. Compared with carriers of the wild-type CYP2C9*1/*1 genotype (n = 69), CL S was reduced by 25, 39 and 47% among heterozygote for CYP2C9*2 (n = 41) CYP2C9*3 (n = 26) and carriers of 2 variant alleles (n = 14), respectively (p < 0.001). The corresponding decrease in the formation clearance of 6 and 7 S-hydroxy-warfarin was 45, 65 and 75%, respectively (p < 0.001). The current study provides an estimate concerning the effect of CYP2C9 polymorphisms on S-warfarin pharmacokinetics among healthy subjects. As such it is free of the confounding effects of disease states and drug interactions. Further research is needed to evaluate whether the incorporation of quantitative data obtained in the present study into pharmacogenetic warfarin algorithm may enhance its precision. Clinicaltrials.gov Identifier NCT00162474.

Quantitative genetics and sex-specific selection on sexually dimorphic traits in bighorn sheep

PubMed Central

Poissant, Jocelyn; Wilson, Alastair J; Festa-Bianchet, Marco; Hogg, John T; Coltman, David W

2008-01-01

Sexual conflict at loci influencing traits shared between the sexes occurs when sex-specific selection pressures are antagonistic relative to the genetic correlation between the sexes. To assess whether there is sexual conflict over shared traits, we estimated heritability and intersexual genetic correlations for highly sexually dimorphic traits (horn volume and body mass) in a wild population of bighorn sheep (Ovis canadensis) and quantified sex-specific selection using estimates of longevity and lifetime reproductive success. Body mass and horn volume showed significant additive genetic variance in both sexes, and intersexual genetic correlations were 0.24±0.28 for horn volume and 0.63±0.30 for body mass. For horn volume, selection coefficients did not significantly differ from zero in either sex. For body weight, selection coefficients were positive in females but did not differ from zero in males. The absence of detectable sexually antagonistic selection suggests that currently there are no sexual conflicts at loci influencing horn volume and body mass. PMID:18211870

Genetic Mapping of Quantitative Trait Loci Controlling Growth and Wood Quality Traits in Eucalyptus Grandis Using a Maternal Half-Sib Family and Rapd Markers

PubMed Central

Grattapaglia, D.; Bertolucci, FLG.; Penchel, R.; Sederoff, R. R.

1996-01-01

Quantitative trait loci (QTL) mapping of forest productivity traits was performed using an open pollinated half-sib family of Eucalyptus grandis. For volume growth, a sequential QTL mapping approach was applied using bulk segregant analysis (BSA), selective genotyping (SG) and cosegregation analysis (CSA). Despite the low heritability of this trait and the heterogeneous genetic background employed for mapping. BSA detected one putative QTL and SG two out of the three later found by CSA. The three putative QTL for volume growth were found to control 13.7% of the phenotypic variation, corresponding to an estimated 43.7% of the genetic variation. For wood specific gravity five QTL were identified controlling 24.7% of the phenotypic variation corresponding to 49% of the genetic variation. Overlapping QTL for CBH, WSG and percentage dry weight of bark were observed. A significant case of digenic epistasis was found, involving unlinked QTL for volume. Our results demonstrate the applicability of the within half-sib design for QTL mapping in forest trees and indicate the existence of major genes involved in the expression of economically important traits related to forest productivity in Eucalyptus grandis. These findings have important implications for marker-assisted tree breeding. PMID:8913761

Ethical issues in predictive genetic testing: a public health perspective.

PubMed

Fulda, K G; Lykens, K

2006-03-01

As a result of the increase in genetic testing and the fear of discrimination by insurance companies, employers, and society as a result of genetic testing, the disciplines of ethics, public health, and genetics have converged. Whether relatives of someone with a positive predictive genetic test should be notified of the results and risks is a matter urgently in need of debate. Such a debate must encompass the moral and ethical obligations of the diagnosing physician and the patient. The decision to inform or not will vary depending on what moral theory is used. Utilising the utilitarian and libertarian theories produces different outcomes. The principles of justice and non-maleficence will also play an important role in the decision.

Logistics for Working Together to Facilitate Genomic/Quantitative Genetic Prediction

USDA-ARS?s Scientific Manuscript database

The incorporation of DNA tests into the national cattle evaluation system will require estimation of variances of and covariances among the additive genetic components of the DNA tests and the phenotypic traits they are intended to predict. Populations with both DNA test results and phenotypes will ...

Quantitative Imaging in Cancer Evolution and Ecology

PubMed Central

Grove, Olya; Gillies, Robert J.

2013-01-01

Cancer therapy, even when highly targeted, typically fails because of the remarkable capacity of malignant cells to evolve effective adaptations. These evolutionary dynamics are both a cause and a consequence of cancer system heterogeneity at many scales, ranging from genetic properties of individual cells to large-scale imaging features. Tumors of the same organ and cell type can have remarkably diverse appearances in different patients. Furthermore, even within a single tumor, marked variations in imaging features, such as necrosis or contrast enhancement, are common. Similar spatial variations recently have been reported in genetic profiles. Radiologic heterogeneity within tumors is usually governed by variations in blood flow, whereas genetic heterogeneity is typically ascribed to random mutations. However, evolution within tumors, as in all living systems, is subject to Darwinian principles; thus, it is governed by predictable and reproducible interactions between environmental selection forces and cell phenotype (not genotype). This link between regional variations in environmental properties and cellular adaptive strategies may permit clinical imaging to be used to assess and monitor intratumoral evolution in individual patients. This approach is enabled by new methods that extract, report, and analyze quantitative, reproducible, and mineable clinical imaging data. However, most current quantitative metrics lack spatialness, expressing quantitative radiologic features as a single value for a region of interest encompassing the whole tumor. In contrast, spatially explicit image analysis recognizes that tumors are heterogeneous but not well mixed and defines regionally distinct habitats, some of which appear to harbor tumor populations that are more aggressive and less treatable than others. By identifying regional variations in key environmental selection forces and evidence of cellular adaptation, clinical imaging can enable us to define intratumoral

Theory Development: A Bridge between Practice and Research

ERIC Educational Resources Information Center

Southern, Stephen; Devlin, James

2010-01-01

Theory development is an intentional process by which marriage and family counselors may bridge the gap between research and practice. The theory building process includes inductive and deductive forms of reasoning, qualitative and quantitative approaches to knowledge development, and diffusion of innovations. Grounded theory provides an…

Human fecal source identification with real-time quantitative PCR

EPA Science Inventory

Waterborne diseases represent a significant public health risk worldwide, and can originate from contact with water contaminated with human fecal material. We describe a real-time quantitative PCR (qPCR) method that targets a Bacteroides dori human-associated genetic marker for...

The Quantitative Nature of Autistic Social Impairment

PubMed Central

Constantino, John N.

2011-01-01

Autism, like intellectual disability, represents the severe end of a continuous distribution of developmental impairments that occur in nature, that are highly inherited, and that are orthogonally related to other parameters of development. A paradigm shift in understanding the core social abnormality of autism as a quantitative trait rather than as a categorically-defined condition has key implications for diagnostic classification, the measurement of change over time, the search for underlying genetic and neurobiologic mechanisms, and public health efforts to identify and support affected children. Here a recent body of research in genetics and epidemiology is presented to examine a dimensional reconceptualization of autistic social impairment—as manifested in clinical autistic syndromes, the broader autism phenotype, and normal variation in the general population. It illustrates how traditional categorical approaches to diagnosis may lead to misclassification of subjects (especially girls and mildly affected boys in multiple-incidence autism families), which can be particularly damaging to biological studies, and proposes continued efforts to derive a standardized quantitative system by which to characterize this family of conditions. PMID:21289537

KRN4 Controls Quantitative Variation in Maize Kernel Row Number

PubMed Central

Liu, Lei; Du, Yanfang; Shen, Xiaomeng; Li, Manfei; Sun, Wei; Huang, Juan; Liu, Zhijie; Tao, Yongsheng; Zheng, Yonglian; Yan, Jianbing; Zhang, Zuxin